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i

NASA/TP—2012–217465

Statistical Aspects of Tropical Cyclone Activity

in the North Atlantic Basin, 1945–2010

Robert M. Wilson

Marshall Space Flight Center, Huntsville, Alabama

August 2012

National Aeronautics and

Space Administration

Marshall Space Flight Center • Huntsville, Alabama 35812
ii

Available from:

NASA Center for AeroSpace Information

7115 Standard Drive

Hanover, MD 21076 –1320

443–757–5802

This report is also available in electronic form at

<https://www2.sti.nasa.gov/login/wt/>
iii

TABLE OF CONTENTS

1. INTRODUCTION ............................................................................................................. 1

2. RESULTS AND DISCUSSION ......................................................................................... 2

2.1 Seasonal Frequencies of North Atlantic Basin Tropical Cyclones, 1945–2010 ............. 2

2.2 The Monthly Distribution of Tropical Cyclones, 1945–2010 ....................................... 15

2.3 The Distribution of Tropical Cyclones by Geographical Region, 1945–2010 ............... 21

2.4 The Seasonal Centroid Location of Tropical Cyclones, 1945–2010 ............................. 27

2.5 The Distribution of Peak Wind Speed and Lowest Pressure ........................................ 32

2.6 Other Aspects of Tropical Cyclones ............................................................................ 39

2.7 Surface Air Temperature and ENSO-Related Parameters ........................................... 53

2.8 Correlation Analyses ................................................................................................... 94

2.9 The Strongest Inferred Correlations ............................................................................ 124

2.10 Additional Remarks .................................................................................................... 149

3. SUMMARY ........................................................................................................................ 165

APPENDIX ............................................................................................................................. 170

REFERENCES ....................................................................................................................... 238
iv

LIST OF FIGURES

 1. Yearly tropical cyclones: (a) NTC, (b) difference (d(NTC)), 

and (c) first difference (fd(NTC)) ............................................................................. 4

 2. Yearly tropical storms: (a) NTS, (b) difference (d(NTS)), and (c) first difference 

(fd(NTS)) ................................................................................................................. 8

 3. The ratio NTS/NTC versus year .............................................................................. 9

 4. Yearly hurricanes: (a) NH, (b) difference (d(NH)), and (c) first difference 

(fd(NH)) .................................................................................................................. 10

 5. Yearly major hurricanes: (a) NMH, (b) difference (d(NMH)), and (c) first 

difference (fd(NMH)) .............................................................................................. 12

 6. Yearly US landfalling hurricanes: (a) NUSLFH, (b) difference (d(NUSLFH)), 

and (c) first difference (fd(NUSLFH)) ..................................................................... 13

 7. Onset location regions of Atlantic basin tropical cyclones by group—reduced

version of the Atlantic basin hurricane tracking chart, National Hurricane

Center, Miami, FL ................................................................................................... 21

 8. NTC versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, 

and (e) group 5 ......................................................................................................... 23

 9. NTS versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, 

and (e) group 5 ......................................................................................................... 24

10. NH versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, 

and (e) group 5 ......................................................................................................... 25

11. NMH versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, 

and (e) group 5 ......................................................................................................... 26

12. NUSLFH versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, 

and (e) group 5 ......................................................................................................... 27

13. Yearly latitudinal centroid locations of tropical cyclones: (a) <N. LAT>, 

(b) difference (d<N. LAT>), and (c) first difference (fd<N. LAT>) ......................... 28

14. Yearly longitudinal centroid locations of tropical cyclones: (a) <W. LONG>, 

(b) difference (d<W. LONG>), and (c) first difference (fd<W. LONG>) ................. 30
v

LIST OF FIGURES (Continued)

15. <N. LAT> versus <W. LONG> ............................................................................... 32

16. Yearly peak wind speed: (a) PWS, (b) difference (d(PWS)), and (c) first 

difference (fd(PWS)) ............................................................................................... 33

17. Yearly seasonal mean of individual cyclone’s peak wind speed: (a) <PWS>,

(b) difference (d<PWS>), and (c) first difference (fd<PWS>) .................................. 34

18. Yearly lowest pressure: (a) LP, (b) difference (d(LP)), and (c) first difference 

(fd(LP)) .................................................................................................................... 36

19. Yearly lowest pressure seasonal mean: (a) <LP>, (b) difference (d<LP>), 

and (c) first difference (fd<LP>) .............................................................................. 37

20. Scatter plots of 10-yma values: (a) LP versus PWS and (b) <LP> versus 

<PWS> .................................................................................................................... 38

21. Yearly variation of accumulated cyclone energy: (a) ACE, (b) difference 

(d(ACE)), and (c) first difference (fd(ACE)) ............................................................ 40

22. Yearly storm days: (a) NSD, (b) difference (d (NSD)), and (c) first difference 

(fd(NSD)) ................................................................................................................ 42

23. Yearly hurricane days: (a) NHD, (b) difference (d (NHD)), and (c) first 

difference (fd(NHD)) ............................................................................................... 43

24. Yearly major hurricane days: (a) NMHD, (b) difference (d(NMHD)), 

and (c) first difference (fd(NMHD)) ........................................................................ 45

25. Yearly tropical cyclone activity: (a) NTCA, (b) difference (d(NTCA)), 

and (c) first difference (fd(NTCA)) .......................................................................... 47

26. Yearly variation of the ratio: (a) ACE/NSD (b) difference (d(ACE/NSD)), 

and (c) first difference (fd(ACE/NSD)) .................................................................... 49

27. Yearly variation of individual storm cyclone energy: (a) HISACE,

(b) difference (d(HISACE)), and (c) first difference (fd(HISACE)) .......................... 51

28. Yearly variation of individual storm storm days: (a) LISNSD, (b) difference 

(d(LISNSD)), and (c) first difference (fd(LISNSD)) ................................................ 52

29. Yearly variation of air temperature: (a) <AT>, (b) difference (d<AT>), 

and (c) first difference (fd<AT>) .............................................................................. 56
vi

LIST OF FIGURES (Continued)

30. Yearly variation of Oceanic Niño index: (a) <ONI>, (b) difference (d<ONI>), 

and (c) first difference (fd<ONI>) ........................................................................... 59

31. Yearly variation of Southern Oscillation index: (a) <SOI>, (b) difference 

(d<SOI>), and (c) first difference (fd<SOI>) .......................................................... 62

32. Yearly variation of North Atlantic Oscillation index: (a) <NAO>, 

(b) difference (d<NAO>), and (c) first difference (fd<NAO>) ................................. 65

33. Yearly variation of Pacific Decadal Oscillation index: (a) <PDO>, 

(b) difference (d<PDO>), and (c) first difference (fd<PDO>) ................................. 68

34. Yearly variation of Trans-Niño index: (a) <TNI>, (b) difference (d<TNI>),

and (c) first difference (fd<TNI>) ............................................................................ 70

35. Yearly multivariate ENSO index: (a) <MEI>, (b) difference (d<MEI>), 

and (c) first difference (fd<MEI>) ........................................................................... 73

36. Yearly variations of global sea surface temperature: (a) <GSSTEI>, 

(b) difference (d<GSSTEI>), and (c) first difference (fd<GSSTEI>) ....................... 76

37. Yearly JMA SST mean index: (a) <JMASSTM>, (b) difference 

(d<JMASSTM>), and (c) first difference (fd<AJMASSTM>) ................................ 78

38. North Tropical Atlantic index yearly variation: (a) <NTA>, (b) difference 

(d<NTA>)and (c) first difference (fd<NTA>) ......................................................... 80

39. Caribbean index yearly variation: (a) <CAR>, (b) difference (d<CAR>), 

and (c) first difference (fd<CAR>) .......................................................................... 83

40. Quasi-Biennial Oscillation index yearly variation: (a) <QBO>, (b) difference 

(d<QBO>), and (c) first difference (fd<QBO>) ....................................................... 85

41. Atlantic Multidecadal Oscillation index yearly variation: (a) <AMO>,

(b) difference (d<AMO>), and (c) first difference (fd<AMO>) ............................... 88

42. Atlantic Meridional Oscillation index yearly variation: (a) <AMM>, 

(b) difference (d<AMM>), and (c) first difference (fd<AMM>) ............................. 92

43. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <AT> ................................................................................ 96
vii

LIST OF FIGURES (Continued)

44. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <SOI> ............................................................................... 99

45. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <ONI> .............................................................................. 101

46. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <NAO> ............................................................................. 103

47. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <PDO> ............................................................................. 105

48. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <TNI> ............................................................................... 107

49. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <MEI> .............................................................................. 109

50. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <GSSTEI> ........................................................................ 111

51. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <JMASSTM> ................................................................... 113

52. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <NTA> ............................................................................. 115

53. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <CAR> ............................................................................. 117

54. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <QBO> ............................................................................. 119

55. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <AMO> ............................................................................ 121

56. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <AMM> ........................................................................... 123

57. 10-yma values of NTC versus 10-yma values of <AT> ............................................ 124

58. 10-yma values of NTS versus 10-yma values of <AT> ............................................ 126
viii

LIST OF FIGURES (Continued)

59. 10-yma values of NH versus 10-yma values of <NTA> ........................................... 127

60. 10-yma values of NMH versus 10-yma values of <AMO> ...................................... 128

61. 10-yma values of NUSLFH versus 10-yma values of <AMO> ............................... 130

62. 10-yma values of <N. LAT> versus 10-yma values of <AMO> .............................. 131

63. 10-yma values of <W. LONG> versus 10-yma values of <ONI> ............................ 132

64. 10-yma values of PWS versus 10-yma values of <AMM> ....................................... 134

65. 10-yma values of <PWS> versus 10-yma values of <NAO> ................................... 135

66. 10-yma values of ACE versus 10-yma values of <AMO> ........................................ 136

67. 10-yma values of NSD versus 10-yma values of <NTA> ......................................... 137

68. 10-yma values of ACE/NSD versus 10-yma values of <AMM> .............................. 138

69. 10-yma values of HISACE versus 10-yma values of <AMM> ................................ 140

70. 10-yma values of LISNSD versus 10-yma values of <QBO> ................................... 142

71. 10-yma values of <NSD> versus 10-yma values of <AMO> .................................. 143

72. 10-yma values of NHD versus 10-yma values of <AMO> ...................................... 145

73. 10-yma values of NMHD versus 10-yma values of <AMO> ................................... 146

74. 10-yma values of NTCA versus 10-yma values of <AMO> .................................... 147

75. Decadal variations for (a) NTC, (b) NTS, (c) NH, (d) NMH, 

and (e) NUSLFH ..................................................................................................... 157

76. Decadal variations for (a) <N. LAT>, (b) <W. LONG>, (c) PWS, 

and (d) <PWS> ........................................................................................................ 158

77. Decadal variations for (a) <ACE>, (b) <NSD>, (c) <ACE/NSD>, 

and (d) <NTCA> ..................................................................................................... 159

78. Decadal variations for (a) <HISACE>, (b) <LISNSD>, (c) <NHD>, 

and (d) <NMHD> ................................................................................................... 160
ix

LIST OF FIGURES (Continued)

79. Decadal variations for (a) <AT>, (b) <SOI>, (c) <ONI>, (d) <NAO>, 

and (e) <QBO> ........................................................................................................ 161

80. Decadal variations for (a) <PDO>, (b) <TNI>, (c) <MEI>, (d) <GSSTEI>, 

and (e) <JMASSTM> .............................................................................................. 162

81. Decadal variations for (a) <NTA>, (b) <CAR>, (c) <AMO>, 

and (d) <AMM> ..................................................................................................... 163
x

LIST OF TABLES

 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, 

based on National Hurricane Center ‘best tracks’ archival database, available 

online at <http://www.nhc.noaa.gov> ....................................................................... 171

 2. Yearly tropical cyclone parametric values ................................................................. 191

 3. 10-yma values of tropical cyclone parameters .......................................................... 192

 4. Differences of tropical cyclone parametric values (d=x – 10-yma) ........................... 193

 5. First-differences of tropical cyclone parametric values based on 10-yma values ....... 194

 6. Poisson probability distributions for Atlantic basin tropical cyclones: 

(a) 1945–2010 and (b) 1995–2010 ............................................................................. 195

 7. Comparison of observed and expected first differences ............................................ 197

 8. Monthly counts of the number of tropical cyclone onsets ........................................ 198

 9. Monthly counts of the number of tropical cyclones that attained 

only tropical storm strength ..................................................................................... 199

10. Monthly counts of the number of tropical cyclones that attained hurricane 

storm strength .......................................................................................................... 200

11. Monthly counts of the number of tropical cyclones that attained major 

or intense hurricane storm strength .......................................................................... 201

12. Monthly counts of the number of tropical cyclones that became US 

landfalling hurricanes ............................................................................................... 202

13. Poisson probabilities by onset month, June–November, 1945–2010 .......................... 203

14. Yearly US hurricane landstrikes by state .................................................................. 204

15. Poisson probabilities by geographical grouping, 1945–2010 ..................................... 205

16. Yearly surface air temperature and ENSO parametric values ................................... 206

17. 10-yma of surface air temperature and ENSO parametric values ............................. 207
xi

LIST OF TABLES (Continued)

18. Differences of surface air and ENSO parametric values (d = x – 10-yma) ................ 208

19. First differences of surface air and ENSO parametric values based 

on 10-yma values ...................................................................................................... 209

20. Tropical cyclone parametric means and standard deviations based 

on the yearly ENSO phase condition......................................................................... 210

21. Poisson probability distributions for North Atlantic basin tropical cyclones 

based on ENSO phase condition .............................................................................. 211

22. Comparison of surface air temperature and ENSO-related parametric values 

for different ENSO phase conditions ........................................................................ 213

23. Poisson probability distributions for North Atlantic basin tropical cyclones 

based on yearly parametric values being either above (+) or below (–) 

long-term parametric averages .................................................................................. 214

24. Inferred linear regression equations using 10-yma parametric values 

for the intervals 1950–2005 and 1990–2005, arranged by r value .............................. 221

25. Listing of North Atlantic basin tropical cyclones for the year 2011 .......................... 229

26. The 34 strongest tropical cyclones, ranked by PWS (135–165 kt) from earliest 

to latest ..................................................................................................................... 230

27. Frequency distribution of PWS ................................................................................ 231

28. Frequency distribution of ISACE ............................................................................ 232

29. Frequency distribution of ISNSD ............................................................................ 233

30. Frequency distribution of ISNHD ........................................................................... 234

31. Frequency distribution of ISNMHD ....................................................................... 235

32. Frequency distribution of onset location N. LAT ..................................................... 236

33. Frequency distribution of onset location W. LONG ................................................. 237
xii

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS

10-yma 10-year moving average

ACE accumulated cyclone energy

ACE/NSD ACE divided by NSD 

AFL Northwest Florida

AMM Atlantic Meridional Mode (index)

<AMM> yearly or decadal mean of the AMM

AMO Atlantic Multidecadal Oscillation (index)

<AMO> yearly or decadal mean of the AMO

AT Armagh Observatory surface air temperature

<AT> yearly or decadal mean of the AT

ATX South Texas

BFL Southwest Florida

BTX Central Texas

CAR Caribbean (index)

<CAR> yearly or decadal mean of the CAR index

CFL Southeast Florida

Class. classification

COADS Comprehensive Ocean-Atmosphere Data Set

CTX North Texas

d(ACE) difference between yearly and 10-yma values of ACE
xiii

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

d(ACE/NSD) difference between yearly and 10-yma values of ACE/NSD

d(<AMM>) difference between yearly and 10-yma values of AMM

d(<AMO>) difference between yearly and 10-yma values of AMO

d(<AT>) difference between yearly and 10-yma values of <AT>

d(<CAR>) difference between yearly and 10-yma values of <CAR>

d(<GSSTEI>) difference between yearly and 10-yma values of <GSSTEI>

d(HISACE) difference between yearly and 10-yma values of <HISACE>

d(<JMASSTM>) difference between yearly and 10-yma values of <JMASSTM>

d(LISNSD) difference between yearly and 10-yma values of <LISNSD>

d(LP) difference between yearly and 10-yma values of LP

d(<LP>) difference between yearly and 10-yma values of <LP>

d(<MEI>) difference between yearly and 10-yma values of <MEI>

d(<NAO>) difference between yearly and 10-yma values of <NAO>

d(NH) difference between yearly and 10-yma values of NH

d(NHD) difference between yearly and 10-yma values of NHD

d(<N. LAT>) difference between yearly and 10-yma values of <N. LAT>

d(NMH) difference between yearly and 10-yma values of NMH

d(NMHD) difference between yearly and 10-yma values of NMHD

d(NSD) difference between yearly and 10-yma values of NSD

d(<NSD>) difference between yearly and 10-yma values of <NSD>

d(<NTA>) difference between yearly and 10-yma values of <NTA>

d(NTC) difference between yearly and 10-yma values of NTC
xiv

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

d(NTCA) difference between yearly and 10-yma values of NTCA

d(NTS) difference between yearly and 10-yma values of NTS

d(NUSLFH) difference between yearly and 10-yma values of NUSLFH

d(<ONI>) difference between yearly and 10-yma values of <ONI>

d(<PDO>) difference between yearly and 10-yma values of <PDO>

d(PWS) difference between yearly and 10-yma values of PWS

d(<PWS>) difference between yearly and 10-yma values of <PWS>

d(<QBO>) difference between yearly and 10-yma values of <QBO>

d(<SOI>) difference between yearly and 10-yma values of <SOI>

d(<TNI>) difference between yearly and 10-yma values of <TNI>

d(<W. LONG>) difference between yearly and 10-yma values of <W. LONG>

DFL Northeast Florida

EN El Niño

ENSO El Niño-Southern Oscillation

ENY El Niño year

EXP expected

fd first difference

fd(ACE) first difference of the 10-yma values of ACE

fd(ACE/NSD) first difference of the 10-yma values of ACE/NSD

fd(<AMM>) first difference of the 10-yma values of <AMM>

fd(<AMO>) first difference of the 10-yma values of <AMO>
xv

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

fd(<AT>) first difference of the 10-yma values of <AT>

fd(<CAR>) first difference of the 10-yma values of <CAR>

fd(<GSSTEI>) first difference of the 10-yma values of <GSSTEI>

fd(HISACE) first difference of the 10-yma values of HISACE

fd(<JMASSTM>) first difference of the 10-yma values of <JMASSTM>

fd(LISNSD) first difference of the 10-yma values of LISNSD

fd(LP) first difference of the 10-yma values of LP

fd(<LP>) first difference of the 10-yma values of <LP>

fd(<MEI>) first difference of the 10-yma values of <MEI>

fd(<NAO>) first difference of the 10-yma values of <NAO>

fd(NH) first difference of the 10-yma values of NH

fd(NHD) first difference of the 10-yma values of NHD

fd(<N. LAT>) first difference of the 10-yma values of <N. LAT>

fd(NMH) first difference of the 10-yma values of NMH

fd(NMHD) first difference of the 10-yma values of NMHD

fd(NSD) first difference of the 10-yma values of NSD

fd(<NSD>) first difference of the 10-yma values of <NSD>

fd(<NTA>) first difference of the 10-yma values of <NTA>

fd(NTCA) first difference of the 10-yma values of NTCA

fd(NTC) first difference of the 10-yma values of NTC

fd(NTS) first difference of the 10-yma values of NTS
xvi

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

fd(NUSLFH) first difference of the 10-yma values of NUSLFH

fd(<ONI>) first difference of the 10-yma values of <ONI>

fd(<PDO>) first difference of the 10-yma values of <PDO>

fd(PWS) first difference of the 10-yma values of PWS

fd(<PWS>) first difference of the 10-yma values of <PWS>

fd(<QBO>) first difference of the 10-yma values of <QBO>

fd(<SOI>) first difference of the 10-yma values of <SOI>

fd(<TNI>) first difference of the 10-yma values of <TNI>

fd(<W. LONG>) first difference of the 10-yma values of <W. LONG>

FSD first storm day

GSSTEI Global Sea Surface Temperature ENSO index

<GSSTEI> yearly or decadal mean of the GSSTEI

HISACE highest individual storm ACE

IAL inland Alabama (hurricane strike)

IGA inland Georgia (hurricane strike)

INC inland North Carolina (hurricane strike)

ISACE individual storm ACE

ISNHD individual storm NHD

ISNMHD individual storm NMHD

ISNSD individual storm NSD

J–M January–March (average temperature)

JMA Japan Meteorological Agency
xvii

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

JMASSTM Japan Meteorological Agency SST Mean (index) 

<JMASSTM> yearly or decadal mean of the JMASSTM

LISNSD longest individual storm NSD

LN La Niña

LNY La Niña year

LP lowest pressure

<LP> yearly mean LP

LSD last storm day

MCA maximum covariance analysis

MEI multivariate ENSO index

<MEI> yearly or decadal mean of the MEI

NAO North Atlantic Oscillation index

<NAO> yearly or decadal mean of the NAO

NCEP National Centers for Environmental Prediction

NH number of hurricanes

NHD number of hurricane days

N. LAT north latitude

<N. LAT> yearly or decadal mean of N. LAT

NMH number of major hurricanes

NMHD number of major hurricane days

NOAA National Oceanic and Atmospheric Administration
xviii

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

NSD number of storm days

<NSD> yearly or decadal mean of the NSD

NTA North Tropical Atlantic index

<NTA> yearly or decadal mean of the NTA

NTC number of tropical cyclones

NTCA Net Tropical Cyclone Activity index

NTS number of tropical storms

NTS/NTC NTS divided by NTC

NUSLFH number of US landfalling hurricanes

NY (ENSO) neutral year

OBS observed

ONI Oceanic Niño index

<ONI> yearly or decadal mean of the ONI

PDO Pacific Decadal Oscillation index

<PDO> yearly or decadal mean of the PDO

PWS peak wind speed

<PWS> yearly or decadal mean of the PWS

QBO Quasi-Biennial Oscillation index

<QBO> yearly or decadal mean of the QBO

RES residual

SLP sea level pressure
xix

LIST OF ACRONYMS, ABBREVIATIONS, AND DESIGNATORS (Continued)

SNBR storm number

SOI Southern Oscillation index

<SOI> yearly or decadal mean of the SOI

SST sea surface temperature

THC thermohaline circulation

TNI Trans-Niño index

<TNI> yearly or decadal mean of the TNI

TP Technical Publication

TS tropical storm

US United States

USLFH US landfalling hurricane

W. LONG west longitude

<W. LONG> yearly or decadal mean of the W. LONG
xx

NOMENCLATURE

a the y-intercept

b the slope

cl confidence level

d difference

fd first difference

m mean

n+ number above mean

n– number below mean

n+r number of runs above mean

nr(t) number of positive residual runs

P probability

P(r) probability of r events occurring

r coefficient of correlation; the number of events occurring per unit time

r2 coefficient of determination

sd standard deviation

se standard error of estimate

t t-statistic; year

x independent variable

y dependent variable

y1 dependent variable for overall interval

y2 dependent variable for current interval

z z-statistic
1

TECHNICAL PUBLICATION

STATISTICAL ASPECTS OF TROPICAL CYCLONE ACTIVITY

IN THE NORTH ATLANTIC BASIN, 1945–2010

1. INTRODUCTION

A tropical cyclone is described as a warm-core, nonfrontal, synoptic-scale system that originates over tropical or subtropical waters and has an organized deep convection and closed surface 

wind circulation (counterclockwise in the Northern Hemisphere) about a well-defined center.1 When 

its maximum sustained surface wind speed is 33 kt or less it is called a tropical depression; when its 

maximum sustained surface wind speed is 34–63 kt it is called a tropical storm and usually given a 

name; when its maximum sustained surface wind speed is 64 kt or more it is called a hurricane; and 

when its maximum sustained surface wind speed is 96 kt or more it is called a major or intense hurricane. Using the Saffir-Simpson Hurricane Wind Scale,2 a major hurricane is one that is classified as 

category3, 4, or 5, where category 4 means the storm has a maximum sustained surface wind speed 

exceeding 112kt and category 5 means the storm has a maximum sustained surface wind speed 

exceeding 136kt. Major hurricanes generally produce catastrophic damage measured in the tens of 

billions of United States (US) dollars when they make landfall along the populous US coastline (e.g., 

Andrew in 1992 and Katrina in 2005) and can result in tremendous loss of life (e.g., the Galveston, 

TX, category 4 hurricane of 1900, a storm that killed, at least 8,000 people).3

Although tropical cyclone occurrences in the North Atlantic basin have been documented 

historically going back several hundreds of years, a detailed record of their occurrences extends only 

from 1851 to the present.4,5 While true, the record considered to be of greatest reliability is much 

shorter, extending only from about 1945 to the present, owing to the near continuous use of reconnaissance aircraft and especially Earth-orbiting satellites (since the 1960s).6–9

Beginning in 1953, tropical cyclones in the North Atlantic basin have been named using 

a list of names originated by the National Hurricane Center, although now the naming of tropical 

cyclones is maintained and updated by the World Meteorological Organization following a strict 

procedure.10 The 21 yearly names of tropical cyclones are rotated and recycled every 6 yr, with new 

names being substituted when a name has been retired (i.e., after an especially deadly and/or costly 

tropical cyclone, like Katrina in 2005). In the event that a hurricane season produces more than 

21 storms, additional storm names are employed using the Greek alphabet in sequential order (i.e., 

alpha, beta, gamma, etc.), as was the case in 2005 when 28 named storms occurred, the most ever to 

be recorded in a single season. Occasionally, however, a hurricane season might still produce at least 

one unnamed storm, as what happened in September 2011. (The practice of using alternating male 

and female names began in 1979, with male names being the first named storm for a yearly hurricane 

season in even-numbered years, as will be the case for the 2012 hurricane season—Alberto.)
2

Tropical cyclones are essentially large heat engines, drawing their strength from the condensation of water evaporated from the ocean’s surface, which releases heat, thus driving the winds.11

Warm sea surface temperature (at least 27 °C), lack of severe vertical wind shear, and clustering 

of thunderstorms are necessary conditions for the formation of a tropical cyclone. In a tropical 

cyclone, the most violent winds and rain occur near its center, with air rising outward at the top of 

the eyewall and relatively calm sinking air occurring within the storm’s eye (typically, measuring tens 

of miles in diameter). Surrounding the eyewall and extending outward for a hundred miles or more 

are the spiral rainbands, which can be tens of miles wide and hundreds of miles long and often are 

the progenitors of tornadoes, especially in major hurricanes. Because the movement and direction 

of a tropical cyclone is governed by the interaction of complex atmosphere-ocean weather patterns, 

accurate forecasting of the strength and path of the storm sometimes can be quite difficult. Also, 

while strong, violent tropical cyclones are certainly ones not to be ignored, so too are weaker, slowmoving tropical cyclones, since these storms can be quite devastating as well, owing to their copious 

torrential rainfall and high potential for flooding.

In this Technical Publication (TP), the statistical aspects of tropical cyclones that formed in 

the North Atlantic basin during the interval 1945 to 2010 are investigated. In particular, the seasonal 

(or yearly) frequencies of tropical cyclones, tropical storms (i.e., those tropical cyclones that never 

attained hurricane wind speed), hurricanes, major hurricanes, and hurricanes striking the US coastline are examined and long-term trends (i.e., 10-year moving averages (10-yma)) are determined. 

Also examined are the statistical aspects (both seasonal and long term) of the positions of origin 

(i.e., latitude and longitude), peak wind speed and lowest air pressure, accumulated cyclone energy, 

number of storm days, and net tropical cyclone activity, as well as the statistical aspects (both seasonal and long term) of various markers of surface air temperature and El Niño-Southern Oscillation- (ENSO-) related indices and the interrelationship between these parameters, in particular as 

related to climatic change and tropical cyclone frequency.12–19 Parametric values as determined for 

the 2011 hurricane season are reviewed, and estimates are given for the upcoming 2012 hurricane 

season. Lastly, examined are decadal variations of the tropical cyclone parameters, the 34 strongest 

tropical cyclones that occurred in the North Atlantic basin since 1945, and the frequency distributions of selected tropical cyclone parameters. This TP continues the long-term study of tropical 

cyclone activity and its relationship to climatic factors that has been ongoing since 1997.20–30
3

2. RESULTS AND DISCUSSION

2.1 Seasonal Frequencies of North Atlantic Basin Tropical Cyclones, 1945–2010

Table 1 (see appendix) gives a listing of the North Atlantic basin tropical cyclones for the interval 

1945–2010, based on the National Hurricane Center’s ‘best tracks’ archival database, available online 

at <http://www.nhc.noaa.gov>. For each year the storm number (SNBR), classification (Class.), first 

storm day (FSD), last storm day (LSD), genesis location (in terms of north latitude (N. LAT) and 

west longitude (W. LONG) positions), group (i.e., the regional location of the genesis location, where 

1 refers to the Gulf of Mexico area, 2 the Caribbean Sea area, 3 the East coast area, 4 the lower 

North Atlantic-Cape Verde area, and 5 the upper open North Atlantic area), the peak wind speed 

(PWS), the lowest pressure (LP), the accumulated cyclone energy (ACE), the number of storm days 

(NSD), the number of hurricane days (NHD), the number of major hurricane days (NMHD), and 

information regarding US landfalling hurricanes (USLFHs). For each year, a summary is also given 

(including a calculation of the net tropical cyclone activity index, or NTCA), where the values inside 

<> represent seasonal averages.

From the summary data given in table 1, tables 2–5 (see appendix) are constructed, where 

table 2 gives the yearly tropical cyclone parametric values, table 3 gives the 10-yma, table 4 gives the 

differences (where the difference is d=x–10-yma, x being the yearly value), and table 5 gives the 

first differences based on the 10-yma values (i.e., the difference in 10-yma values for two consecutive 

years). At the bottom of tables 2, 4, and 5 are the parametric means and standard deviations (sd) for 

each parameter. Also included in tables 4 and 5 are the number of positive (n+) and negative (n–) values and the number of positive runs (n+r) for each parameter. These tables form the basis for the following discussion regarding the frequency of tropical cyclones in the North Atlantic basin, including 

all tropical cyclones, tropical cyclones that attained only tropical storm strength, hurricanes, major 

hurricanes, and US landfalling hurricanes.

2.1.1 The Number of Tropical Cyclones

Figure 1(a) displays the yearly number of tropical cyclones (NTC) in the North Atlantic basin 

during the interval 1945–2010. The thin, jagged line represents the yearly variation of NTC and the 

thick, smoothed line represents the 10-yma of NTC (used here to indicate the long-term trend). The 

thin horizontal line represents the long-term mean frequency for the entire interval. Thus, for the 

interval 1945–2010, spanning 66 yr, some 715 tropical cyclones have been documented in the North 

Atlantic basin, yielding a mean of about 11 storms per year. The fewest number of storms during 

a single year measures 4 (occurring in 1983) and the greatest number of storms during a single year 

measures 28 (occurring in 2005). Prior to 1995, the average number of tropical cyclones that formed 

in the North Atlantic basin measured about 9.6 storms per year, while from 1995 onwards, the average number has measured about 14.8 storms per year, an increase of about 54%. Indeed, the difference in means for the two time intervals (1945–1994 versus 1995–2010) is found to be statistically 

important (t = –5.39) at confidence level (cl) >99.9%, on the basis of the t-statistic for independent
4

First Difference (fd(NTC))

–1

–0.5

0

0.5

1

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NTC)t

 = NTC(10-yma)t+1 – NTC(10-yma)t

 sd = 0.3

1965 1975 1985 1995 2005

Year

(c)

Difference (d(NTC))

–10

–5

0

5

10

15 d(NTC)t

 = NTC(yearly)t – NTC(10-yma)t

 sd = 3.3

(b)

NTC

5

0

10

15

20

30

25

1945–2010

NTC

sum = 715

(a)

1950–1989: mean = –0.023

sd = 0.198 

1990–2004: mean = 0.387

sd = 0.297

⇒t = –5.93

⇒cl >99.9%

1945–1994: mean = 9.58

sd = 2.785

 sum = 479 

1995–2010: mean = 14.75

sd = 4.726

 sum = 236

⇒t = –5.385 

⇒cl >99.9%

Note: NTC2011 ≥ 0

 ⇒NTC(10-yma)2006 ≥ 14.75

 ⇒fd(NTC)2005 ≥ –0.55

 ⇒d(NTC)2006 ≤ –4.75

NTC2011

NTC(10-yma)2006

fd(NTC)2005

d(NTC)2006

= 11

= 15.3

= 0

= –5.3

 NTC = 15

 NTC(10-yma)2006 = 15.5

 fd(NTC)2005 = 0.2

 d(NTC)2006 = –5.5

mean = 10.8

 sd = 4

range = 4–28

Figure 1. Yearly tropical cyclones: (a) NTC, (b) difference (d (NTC)), and (c) first difference 

(fd(NTC)).
5

samples.31 Obviously, a shift has occurred from a former less active interval to a more active interval 

that now is being experienced today. How long this active state will persist depends on whether it is 

part of a quasi-cyclic occurrence of less active and more active intervals or if it is the direct result 

of climatic change (i.e., the long-term warming of the atmosphere and oceans that the Earth now is 

experiencing).

Presuming the current, more active state will continue at least for the near-term, foreseeable 

future, one easily predicts that NTC should average about 15 storms per year with a ±1 sd about 

the mean of about 5 storms, suggesting a yearly rate between 10 and 20 storms per year (the ±1 sd

prediction interval), assuming a normal distribution. The 50% prediction interval is 14.8 ± 3.3, inferring that there is a 50% chance that NTC for any given year will lie within the range of about 12–18 

storms per year during this current, more active interval. The 90% prediction interval is computed to 

be about 14.8 ± 8.3, yielding the larger range of about 7–23 storms per year; hence, one infers only 

a 5% chance each that 6 or fewer storms or 24 or more storms would be expected in any given year 

during this current, more active interval, presuming, of course, a normal distribution for NTC.

Because NTC is a measure of the number of events per unit time (i.e., the number of tropical 

cyclones per year) and clearly is positively skewed (i.e., a rightward tail towards higher numbers), the 

more appropriate distribution is the Poisson distribution.32 Table 6 (see appendix) gives the Poisson 

probabilities for a specific number of events (r) occurring per year, table 6A for the entire interval 

(1945–2010) and 6B for the current, more active interval (1995–2010). The central 50% interval for 

the two time intervals are approximately 10 ± 2 (actually 55%) and 14 ± 2 (actually 48%), respectively. By summing specific ranges of r, one can deduce the probability of observing that range of r’s 

in any given season. Hence, the probability of having 20 or more tropical cyclones per year during the 

current, more active interval is computed to be P(20) + P(21) + P(22) + ... + P(35) = 12.4%, or about 

1 chance in 8. Similarly, the probability of having 10 or fewer tropical cyclones per year during the 

current, more active interval is computed to be about 12.9%, also about 1 chance in 8. Therefore, the 

probability of having a rate of about 11–19 tropical cyclones in any given season during this current, 

more active interval measures about 75% (i.e., 100% – 12.4% – 12.9% = 74.7%), based on Poisson 

statistics.

Figure 1(b) shows the variation of the difference d (NTC)t, where the d(NTC)t = NTC(yearly)t

– NTC(10-yma)t and t is the year in question. Visual inspection of d (NTC)t reveals that there have 

been 29 positive differences, 27 negative differences, and 19 positive difference runs (18 negative 

difference runs) between 1950 and 2005, with sd = 3.3 (thereby, inferring a reduction in the variance by about 32%). So, presuming that d (NTC)t

 is distributed normally, one expects it to measure 

about ±3.3 units for any given year (i.e., the ±1 sd prediction interval). Unfortunately, this poses an 

untenable conclusion regarding its value for 2006. The yearly NTC for 2006 is already known to be 

10. It can be shown (see note at the bottom of fig. 1(c)) that d(NTC) for 2006 must be at least –4.75 

or more negative in value. As an example, a value of NTC = 0 in 2011 results in a 10-yma of NTC 

for 2006 equal to 14.75 and a yearly d(NTC) for 2006 equal to –4.75 (= 10 – 14.75). Instead, using 

the long-term average (11 storms per year), one finds that the 10-yma of NTC for 2006 equals 15.3 

and the yearly d(NTC) for 2006 equals –5.3, while using the current, more active interval average 

(15 storms per year) one finds that the 10-yma of NTC for 2006 equals 15.5 and the yearly d(NTC) 

for 2006 equals –5.5. Any value of NTC higher than the current, more active interval average (i.e., 
6

NTC >15) for 2011 results in an even higher value of the 10-yma of NTC (>15.5) for 2006 and 

a more negative value of d (NTC) for 2006 (more negative than –5.5). Runs testing33 of d(NTC)t

suggests that the distribution of positive difference runs for d(NTC) might be nonrandom (z = 2.39, 

cl > 95%), inferring that a systematic variation, perhaps, is present within the data.

Figure 1(c) depicts the variation of fd (NTC)t, where fd(NTC)t = NTC(10-yma)t+1 – NTC(10-

yma)t and t is again the year. The average first difference during the current, more active interval 

measures about 0.39, having sd = 0.3, while the average first difference for the years prior to 1995 

measures –0.02, having sd = 0.2. The difference in the means is statistically important at cl >99.9%. 

Plainly, the number of positive-valued first differences is found to greatly outnumber the number of 

negative-valued first differences, especially in the current, more active interval. In fact, visual inspection of fd(NTC)t

 reveals that there have been 34 positive first differences, 21 negative first differences, 

and 10 positive first difference runs (9 negative first difference runs) between 1950 and 2004, with 

sd = 0.3. Presuming that fd(NTC)t is distributed normally, one expects it to measure about ±0.3 units 

for any given year (i.e., the ±1 sd prediction interval). As with d(NTC)t, runs testing of fd(NTC)t

suggests that the distribution of positive-valued first difference runs might also be nonrandom 

(z = –2.02, cl >95%). It seems noteworthy that the current, more active interval of positive-valued 

first differences now spans at least 16 yr, beginning in 1989 (i.e., 0 ≤ fd ≤ 0.9), averaging 0.4 and having 

sd = 0.3. A linear fit of fd(NTC)t versus t (for all t between 1950 and 2005) results in the linear regression y = –18.383 + 0.009x, where x is the year and y is the expected first difference. The inferred 

regression (not shown) has a linear correlation coefficient r = 0.513, a coefficient of determination 

r2 = 0.263 (meaning that 26.3% of the variance can be explained by the inferred regression), a standard error of estimate se = 0.4, and cl >99.5%. Thus, indeed, there appears to be a systematic, longterm increase in the first difference of 10-yma values of NTC with time (year) during the interval 

1950–2004.

Table 7 (see appendix) compares the observed (OBS) and expected (EXP) first differences for 

the interval 1950–2004, where the observed values are those taken from table 5 and the expected values are those deduced using the inferred regression. The residual (RES) is computed as the difference 

between the two values (i.e., RES = OBS – EXP). At the bottom of table 7 are located the number of 

positive residuals (n(+)), the number of negative residuals (n(–)), the number of positive residual runs 

((n+r)), the normal deviate z for the sample results, the cl, and the decision based on hypothesis testing as to whether or not the residuals appear to be randomly (yes) or nonrandomly (no) distributed. 

Indeed, it appears that the residuals (having removed an inferred linear increase) are randomly distributed, with the bulk of the residuals occurring in the interval –0.3 to 0.3 (49 of 55 residual values, or 

about 89%). The interval –0.1 to 0.1 contains 27 of 55 residual values (49%). Only two residual values 

are more negative than –0.3 (–0.4 in 1977 and –0.5 in 1974) and only four residual values exceed 0.3 

(0.5 in 1964 and 1998 and 0.6 in 1990 and 1999). So, for 2005, one infers its expected first difference 

to be 0.4 (from the regression), thereby suggesting that the 10-yma of NTC for 2006 will be about 

15.7 ± 0.3 (i.e., 15.3 + 0.4 ± 0.3, where 15.3 is the 10-yma of NTC for 2005, 0.4 is the expected first 

difference from the inferred regression, and ±0.3 is the standard error of estimate). In actuality, the 

10-yma of NTC for 2006, indeed, turned out to be 15.7, owing to NTC = 19 in 2011, thereby yielding 

a first difference of 0.4 for 2005 (and a difference d=–5.7 for 2006). Presuming the inferred regression 

remains valid for 2006, one expects a first difference of 0.4 for 2006 and a 10-yma of NTC of 15.7 

+ (0.4 ± 0.3), or about 16.1 ± 0.3 for 2007. Hence, one anticipates a 10-yma of NTC ≥15.8 for 2007, 
7

a first difference fd ≥0.1 for 2006, a difference d ≥0.8 for 2007, and NTC ≥10 for 2012 (perhaps as high 

as 22, the upper limit of the ±1 sd prediction interval). (The 10-yma NTC has a minimum value of 

15.3 for the year 2007, computed by assuming a frequency of zero NTC in 2012.)

2.1.2 The Number of Tropical Cyclones of Tropical Storm Strength Only

Figure 2 is constructed similarly to figure 1 and is drawn from the data tabulated in tables 2–5. 

For the interval 1945–2010, the number of tropical cyclones of tropical storm strength only (NTS) is 

found to average about 5 storms per year, with a range of 1 to 13 storms per year and sd of 2.3 storms 

per year. Thus, on average, about 40% of all tropical cyclones (i.e., 306/715 = 43%) that formed in the 

North Atlantic basin between 1945 and 2010 never strengthened beyond tropical storm strength (i.e., 

maximum sustained surface wind speed 34–63 kt). The fewest NTS (1) occurred in 1983 and the most 

(13) occurred in 2005. Also, noticeable is that the number of tropical storms forming in the North 

Atlantic basin has increased dramatically from an average of about 3.9 tropical storms per year 

during the interval prior to 1995 to an average of about 6.8 tropical storms per year since 1995, an 

increase of about 74%. Thus, a large part of the increase in tropical cyclone formation in the North 

Atlantic basin since 1945 can be attributed directly to an increase in the number of tropical cyclones 

of tropical storm strength only. Runs testing of d (NTS)t suggests that its distribution is random 

(z = 1.43, cl <90%), having a range of –3 to 5.3 and sd of 1.9. In contrast, runs testing of fd(NTS)t

suggests that its distribution is nonrandom (z = –2.79, cl >99%), having a range of –0.3 to 0.4 and 

sd of 0.2. Indeed, a linear fit of fd(NTS)t versus t results in the regression (not shown) y = –10.069 

+ 0.005x, where x is the year and y is fd(NTS)t, the inferred regression having r = 0.426, r2 = 0.182 

(meaning 18.2% of the variance can be explained by the inferred regression), se = 0.22, and cl >98%. 

For 2005, one infers fd(NTS)t = 0.2 ± 0.2 (the ±1 sd prediction interval), suggesting the 10-yma of 

NTS to be about 7.7 + 0.2 ± 0.2 and the yearly NTS to be about 6 to 14 for 2011. In actuality, NTS 

for 2011 measured 12, the second highest NTS on record behind the 13 NTS that occurred in 2005, 

the 10-yma of NTS for 2006 measures 8, and the fd(NTS) measures 0.3. Presuming the inferred 

regression remains valid for 2006, one expects a first difference of 0.2 for 2006 and a 10-yma of NTS 

= 8 + (0.2 ± 0.2), or about 8.2 ± 0.2 for 2007. Hence, one anticipates a 10-yma of NTS ≥8 for 2007, 

a first difference ≥0 for 2006, and NTS ≥2 for 2012 (perhaps as high as 10). (A comparison of the 

first difference means for the interval prior to 1995 and subsequent to 1995 also clearly shows that 

the difference in means is statistically important, having cl >99.9%. The average first difference in the 

current, more active interval measures 0.22, with sd of 0.19. The 10-yma NTS has a minimum value 

of 7.9 for the year 2007, computed by assuming a frequency of zero NTS in 2012.)
8

First Difference (fd(NTS)) Difference (d(NTS))

–0.4

0

0.4

–5

0

5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NTS)t

 = NTS(10-yma)t+1 – NTS(10-yma)t

 sd = 0.2

d(NTS)t

 = NTS(yearly)t – NTS(10-yma)t

 sd = 1.9

1945–2010

NTS

sum = 306

1965 1975 1985 1995 2005

(c) Year NTS

10

5

0

20

10

15

(a)

(b)

1950–1989: mean = 0.018

sd = 0.165 

1990–2004: mean = 0.22

sd = 0.19

⇒t = –3.88

⇒cl >99.9%

1945–1994: mean = 3.94

sd = 1.812

 sum = 197 

1995–2010: mean = 6.813

sd = 2.373

 sum = 109 

⇒t = –5.109

⇒ cl >99.9%

mean = 4.6

sd = 2.3

range = 1–13

 Figure 2. Yearly tropical storms: (a) NTS, (b) difference (d (NTS)), and (c) first difference 

(fd(NTS)).

Figure 3 displays the yearly ratios of NTS to NTC for the interval 1945–2010. While the 

ratios appear to be randomly distributed about the mean of 0.42, having an sd of 0.14, and range of 

0.14 to 0.67, and, the number of ratios below the mean appears to occur slightly more often during 

the interval 1945 to 1977 (22 of 33 ratios) than during the interval 1978 to 2010 (18 of 33 ratios). For 

2011, the ratio measures 0.63 (= 12/19).
9

Year

NTS/NTC

1

0

0.5

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

mean = 0.42

sd = 0.14 

range = 0.14–0.67

Figure 3. The ratio NTS/NTC versus year.

Based on Poisson statistics (see table 6) for the current, more active interval, one finds 

P(r = 4–8) = 66.2% for NTS. For r <4, P(r <4) = 9.3%, or about 1 chance in 10, and for r >8, P(r >8) 

= 24.5%, or about 1 chance in 4. There is about 1 chance in 22 for NTS ≥12 (P(r ≥12) = 4.5%).

2.1.3 The Number of Tropical Cyclones of Hurricane Strength

Figure 4 is similarly constructed to figures 1 and 2, being drawn from the data given in 

tables 2–5. For the interval 1945–2010, the number of hurricanes (NH) is found to average about 

6 storms per year, with a range of 2 to 15 storms per year and sd of 2.6 storms per year. Thus, about 

60% of the tropical cyclones that form in the North Atlantic basin eventually strengthen into hurricanes (i.e., 409/715 = 57%), having a maximum sustained surface wind speed in excess of 63 kt. 

The fewest NH (2) occurred in 1982 and the most (15) occurred in 2005. As with NTC and NTS, the 

average for NH is higher since 1995 than before 1995, 7.9 storms per year as compared to 5.6 storms 

per year, an increase of about 41% (cl >99.8%).
10

First Difference (fd(NH))

–0.5

0

0.5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NH)t

 = NH(10-yma)t+1 – NH(10-yma)t

 sd = 0.2

d(NH)t

 = NH(yearly)t – NH(10-yma)t

 sd = 2.4

mean = 6.2

sd = 2.6

range = 2–15

1965 1975 1985 1995 2005

Year (c) Difference (d(NH)) NH

–5

5

0

10

15

10

5

0

(b)

(a)

1950–1989: mean = –0.04

sd = 0.172 

1990–2004: mean = 0.167

sd = 0.229

⇒t = –3.622

⇒cl >99.9%

1950–1994: mean = 5.64

sd = 2.117

sum = 282 

1995–2010: mean = 7.938

sd = 3.276

sum = 127

⇒t = –3.281

⇒ cl >99.8%

1945–2010

NH

sum = 409

Figure 4. Yearly hurricanes: (a) NH, (b) difference (d (NH)), and (c) first difference (fd(NH)).

Runs testing of d(NH)t reveals that its distribution appears random, having z = 0.27, cl <90%, 

and sd = 2.4. However, as was the case for NTC and NTS, the distribution of the first differences of 

NH appears to be nonrandom, having z = –2.79, cl >99%, and sd = 0.2. The mean first difference 

for the interval prior to 1995 measures –0.04, having sd = 0.17, while the mean first difference for 

the interval since 1995 measures 0.167, having sd = 0.23. The difference in means is found to be statistically important, having cl >99.9%. A linear fit of fd(NH)t

 versus t results in the regression (not 

shown) y = –8.328 + 0.004x, where x is the year and y is fd (NH)t, r = 0.324, r2 = 0.105, se = 0.32, 

and cl >95%. For 2005, one infers fd(NH)t = 0.13 ± 0.32 (the ±1 sd prediction interval), suggesting 

the 10-yma of NH to be about 7.6 + 0.1 ± 0.3 and NH for 2011 to be about 1 to 13. In actuality, NH 

for 2011 measured 7 (about average in number), the 10-yma of NH for 2006 measures 7.7, and the 

fd(NH) measures 0.1. Presuming the inferred regression remains valid for 2006, one expects a first 

difference of about 0.1 for 2006 and a 10-yma of NH of 7.7 + (0.1 ± 0.3), or about 7.8 ± 0.3 for 2007. 

Hence, one anticipates a 10-yma of NH ≥7.5 for 2007, a first difference ≥–0.2 for 2006, and NH ≥2 

for 2012 (perhaps as high as 14). (A comparison of the first difference means for the interval prior to 

1995 and subsequent to 1995 also clearly shows that the difference in means is statistically important, 

having cl >99.9%. The average first difference in the current, more active interval measures 0.17, with 
11

sd of 0.23. The 10-yma NH has a minimum value of 7.4 for the year 2007, computed by assuming 

afrequency of zero NH in 2012.)

Based on Poisson statistics (see table 6) for the current, more active interval, one finds 

P(r = 5–9) = 49.8% for NH. For r <5, P(r <5) = 10.5%, or about 1 chance in 10, and for r >9, 

P(r >9) = 39.7%, or about 4 chances in 10. There is about 1 chance in 4 for NH ≥12 (P(r ≥12) 

= 23.1%).

2.1.4 The Number of Tropical Cyclones of Major Hurricane Strength

As with the preceding summary figures, figure 5 is similarly constructed, drawing from 

tables 2–5. For the interval 1945–2010, the number of major or intense hurricanes (NMH) is found 

to average about 3 storms per year, with a range of 0 to 8 storms per year and sd of 1.9 storms per 

year. Thus, about 25% of the tropical cyclones that form in the North Atlantic basin eventually 

strengthen into major hurricanes (i.e., 179/715 = 25%), having a maximum sustained surface wind 

speed in excess of 95 kt. About 44% of those tropical cyclones that attain hurricane status eventually 

become major hurricanes (i.e., 179/409 = 44%). The fewest NMH (0) occurred in 1968, 1972, 1986, 

and 1994, and the most (8) occurred in 1950. As with NTC, NTS, and NH, the average for NMH is 

higher since 1995 than before 1995, 3.81 storms per year as compared to 2.36 storms per year, respectively, an increase of about 62% (cl >99%). It should be noted that the values of NMH now being 

experienced (in particular, the 10-yma values of NMH) are very similar to those experienced earlier 

in the 1950s and 1960s. This suggests, perhaps, that, like the 1950s and 1960s, the present interval is 

one best described as having increased activity (more active), being in stark contrast with that of the 

preceding interval of the 1970s and 1980s, which is one best described as having reduced activity (less 

active), at least in terms of NMH. The question remains, however, regarding the basis for this behavior for NMH: Is its behavior reflective of one that is quasi-cyclic in nature (i.e., consisting of cycles of 

more and less activity, each tens of years in length) or is its behavior reflective of one that is directly 

attributable to climatic change (i.e., driven by increasing temperature)? It also seems noteworthy that, 

although today’s 10-yma values of NMH (averaging about 3.8 storms per year) are similar to those 

of the early 1950s, presently, they still fall slightly below that of the earlier maximum value (4 storms 

per year in 1953 and 1954). Does this mean that the current active interval has not yet peaked, but 

will continue for another decade or so before weakening to levels indicative of another less active 

interval (presuming a cyclic cause) or will it continue to increase unabatedly (presuming a climatic 

change cause, perhaps, due to increased warming of the atmosphere and oceans)?
12

First Difference (fd(NMH)

–0.5

0

0.5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NMH)t

 = NMH(10-yma)t+1 – NMH(10-yma)t

 sd = 0.2

d(NMH)t

 = NMH(yearly)t – NMH(10-yma)t

 sd = 1.7

mean = 2.7

sd = 1.9

range = 0–8

1965 1975 1985 1995 2005

(c) Year Difference (d(NMH) NMH

–5

5

0

10

5

0

(b)

(a)

1950–1989: mean = –0.055

sd = 0.143 

1990–2004: mean = 0.147

sd = 0.181

⇒t = –4.334

⇒cl >99.9%

1945–1994: mean = 2.36

sd = 1.804

sum = 118 

1995–2010: mean = 3.813

sd = 1.797

sum = 61

⇒t = –2.807

⇒ cl >99%

1945–2010

NMH

sum = 179

Figure 5. Yearly major hurricanes: (a) NMH, (b) difference (d (NMH)), and (c) first difference 

(fd(NMH)). 

Runs testing of d(NMH)t and fd(NMH)t reveals that both distributions probably are random, having z = 1.86, cl >90%, and sd = 1.7 and z = –1.46, cl <90%, and sd = 0.2, respectively. The 

mean difference is expected to be about ±1.7 (±1 sd prediction interval) and the mean first difference is expected to be about ±0.2. Hence, for 2006, d (NMH)t

 was expected to measure about ±1.7 

and fd(NMH)t about ±0.2, inferring the 10-yma of NMH for 2006 to be about 2 ± 1.7 (based on 

the difference) or about 3.7 ± 0.2 (based on the first difference). In actuality, NMH measured 3 for 

2011, yielding the 10-yma value of NMH to be 3.75, thereby yielding d = 1.75 for 2006 and fd = 0.05 

for 2005. Assuming the mean difference and first difference values remain valid for 2007 and 2006, 

respectively, one anticipates a 10-yma of NMH of 2 ± 1.7 (based on the expected difference, 2 being 

the observed value for NMH in 2007) or 3.75 ± 0.2 (based on the expected first difference, 3.75 being 

the 10-yma of NMH for 2006), inferring NMH = 3 ± 4 for 2012 (i.e., NMH = 0–7).

A comparison of the first difference means for the interval prior to 1995 and subsequent to 

1995 also clearly shows that the difference in first difference means is statistically important, having 

cl >99.9%. The average first difference in the current, more active interval measures 0.15, with sd of 

0.18. Presuming the first difference will be 0.15 ± 0.18 for 2006, one infers that the 10-yma of NMH 

for 2007 will be 3.75 ± 0.15 ± 0.18, or about 3.9 ± 0.2, inferring NMH = 6 ± 4 in 2012 (i.e., NMH 

= 2–10). (The 10-yma NMH has a minimum value of 3.7 for the year 2007, computed by assuming 

a frequency of zero NMH in 2012.)
13

Based on Poisson statistics (see table 6) for the current, more active interval, one finds 

P(r = 2–4) = 56% for NMH. For r <2, P(r <2) = 10.7%, or about 1 chance in 10, and for r >4, 

P(r >4) = 33.2%, or about 1 chance in 3. There is about 1 chance in 10 for NMH ≥7 (P(r ≥7) = 9.1%).

2.1.5 The Number of US Landfalling Hurricanes

As with the preceding summary figures, figure 6 is similarly constructed and draws data from 

tables 2–5. For the interval 1945–2010, the number of US landfalling hurricanes (NUSLFH) is found 

to average about 1–2 storms per year, with a range of 0 to 6 storms per year and sd of 1.5 storms 

per year. Thus, about 15% of the tropical cyclones that form in the North Atlantic basin eventually strengthen into hurricanes that strike the US coastline with hurricane-force winds (maximum 

sustained surface winds in excess of 63 kt; 108/715 = 15%). Of these, more than one-third (40/108 

= 37%) have struck the US as major hurricanes, the two largest being Camille in 1969 (striking 

Louisiana and Mississippi) and Andrew in 1992 (striking Florida), both striking the US coastline as 

category 5 hurricanes (maximum sustained surface wind speed in excess of 136 kt). First Difference (fd(NUSLFH)) –0.5

0.5

0

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NUSLFH)t

 = NUSLFH(10-yma)t+1 – NUSLFH(10-yma)t

 sd = 0.1

1965 1975 1985 1995 2005

Year (c)

(b)

(a)

1945–2010

NUSLFH

sum = 108

1950–1989: mean = –0.023

sd = 0.121 

1990–2004: mean = 0.033

sd = 0.184

⇒t = –1.317

⇒cl <90%

Difference (d(NUSLFH)) –5

5

0

d(NUSLFH)t

 = NUSLFH(yearly)t – NUSLFH(10-yma)t

 sd = 1.4

NUSLFH

10

5

0

1945–1994: mean = 1.56

sd = 1.264

sum = 78 

1995–2010: mean = 1.875

sd = 1.962

sum = 30

⇒t = –0.752 

⇒ cl <90%

mean = 1.6

sd = 1.5

range = 0–6

 Figure 6. Yearly US landfalling hurricanes: (a) NUSLFH, (b) difference (d (NUSLFH)), 

and (c) first difference (fd(NUSLFH)).
14

Examination of figure 6 (and table 2) reveals that only 13 of the 66 yr have had no US landfalling hurricanes, these occurring in the years 1951, 1962, 1973, 1978, 1981, 1982, 1990, 1994, 2000, 

2001, 2006, 2009, and 2010. Only three times have there been back-to-back years when no US landfalling hurricanes occurred (1981–1982, 2000–2001, and 2009–2010), and there has never been a 3-yr 

respite between US landfalling hurricanes. For nearly half the seasons, a US landfalling hurricane 

has struck as a major hurricane (31/66 yr, or 47%). Fifteen years had back-to-back strikes by major 

hurricanes along the US coastline; 6 yr had major hurricanes striking along the US coastline after 

a 1-yr respite; 4 yr each had major hurricane strikes along the US coastline after a 2- and 3-yr 

respite; and only 1 yr (excluding the present respite) had a major hurricane strike along the US coastline after a 5-yr respite. Including the 2011 season, the respite in major hurricane strikes along the 

US coastline now spans 6 yr, the longest such respite in the interval 1945–2011. (The last strike by 

a major hurricane along the US coastline was Wilma in 2005, which struck Florida as a category 

3 storm; the 2011 season had one US landfalling hurricane, Irene, but it struck North Carolina as 

a category 1 storm in August.)

Usually, the major hurricanes that strike the US coastline are singular seasonal events. Of the 

40 major hurricanes that have struck the US in 31 seasons, 25 struck the US coastline at the rate of 

one major hurricane strike per season (25/40 = 63%). Fifteen major hurricanes struck the US coastline at the rates of 2–4 major hurricane strikes per season over 6 seasons, including 8 major hurricane 

strikes of the US coastline at the rate of 2 strikes per season (1950, 1955, 1985, and 2004), 3 major 

hurricane strikes in a single season (1954), and 4 major hurricane strikes in a single season (2005).

Of the 40 major hurricane strikes along the US coastline, 27 struck a single state at major 

hurricane strength (27/40 = 68%) and 13 struck multiple states at major hurricane strength: 8 major 

hurricanes striking two states at major hurricane strength and 5 major hurricanes striking three 

states at major hurricane strength. For example, an unnamed storm in 1947 first struck Florida as a 

category 4 storm, then went on to strike both Louisiana and Mississippi as a category 3 storm. In 

1954, Carol struck New York, Connecticut, and Rhode Island as a category 3 storm. In 1960, Donna 

first struck Florida as a category 4 storm, prior to striking both North Carolina and New York 

as a category 3 storm. In 1985, Elena struck the states of Alabama, Mississippi, and Florida as a 

category 3 storm. Lastly, in 1992, Andrew struck the state of Florida twice (first the east coast 

then the west coast), first as a category 5 storm then as a category 4 storm, and continued onwards 

striking Louisiana as a category 3 storm.

Runs testing of d(NUSLFH)t and fd (NUSLFH)t reveals that both distributions are probably 

random, having z = 0.28, cl <90%, and sd = 1.4 and z = –0.89, cl <90%, and sd = 0.1, respectively. 

The mean difference is expected to be about ±1.4 (±1 sd prediction interval) and the mean first difference is expected to be about ±0.1. Hence, for 2006, d(NUSLFH)t

 was expected to measure about 

±1.4 and fd (NUSLFH)t about ±0.1, inferring the 10-yma of NUSLFH for 2006 to be about 0 ± 1.4 

(based on the difference) or about 1.9 ± 0.1 (based on the first difference). In actuality, NUSLFH 

measured 1 for 2011, yielding the 10-yma value of NUSLFH to be 2, thereby yielding the difference 

for 2006 to be 2 and the first difference for 2005 to be 0.1. Assuming the mean difference and first 

difference values remain valid for 2007 and 2006, respectively, one anticipates a 10-yma of NUSLFH 

for 2007 of 1 ± 1.4 (based on the expected difference, 1 being the observed yearly value for NUSLFH 
15

in 2007) and 2 ± 0.1 (based on the expected first difference, 2 being the 10-yma of NUSLFH for 

2006), inferring NUSLFH = 1 ± 4 for 2012 (i.e., NUSLFH = 0–5).

A comparison of the first difference means for the interval prior to 1995 and subsequent to 

1995 clearly shows that the difference in means is not statistically important, having cl <90%. The 

average first difference in the current, more active interval measures 0.03, with sd of 0.18. Presuming the first difference will be 0.03 ± 0.18 for 2006, one infers that the 10-yma of NUSLFH for 2007 

will be 2 + 0.03 ± 0.18 or about 2.03 ± 0.18, inferring NUSLFH = 2 ± 4 in 2012 (i.e., NUSLFH 

= 0–6). (The 10-yma NUSLFH has a minimum value of 1.95 for the year 2007, computed by assuming 

a frequency of zero NUSLFH in 2012.)

Based on Poisson statistics (see table 6) for the current, more active interval, one finds 

P(r = 0–2) = 70.4% for NUSLFH. For r = 0, P(r = 0) = 15%, or about 1 chance in 7, and for r >2, 

P(r >2) = 29.6%, or about 3 chances in 10. There is about 1 chance in 8 for NUSLFH ≥4 (P(r ≥4) 

= 12.5%).

2.2 The Monthly Distribution of Tropical Cyclones, 1945–2010

Tables 8–12 give year-by-year monthly counts of the onsets of all tropical cyclones (table 8), 

those tropical cyclones that attained only tropical storm strength (table 9), hurricanes (table 10), 

major hurricanes (table 11), and US landfalling hurricanes (table 12). Table 13 provides the Poisson 

probabilities for onsets in the months of June–November, the nominal hurricane season in the North 

Atlantic basin. Each table will be described separately in the appropriate subsections that follow (see 

appendix for individual tables).

2.2.1 Tropical Cyclones

For the interval 1945–2010, 715 tropical cyclones formed in the North Atlantic basin. Of 

these, only 22 (table 8) had onsets outside the nominal hurricane season. Thus, 693 (97%) had their 

onsets during the June–November hurricane season. Of the 693 tropical cyclones that occurred during the nominal hurricane season, 38 (5.5%) occurred in June, 62 (8.9%) in July, 188 (27.1%) in 

August, 245 (35.4%) in September, 125 (18%) in October, and 35 (5.1%) in November. Together, more 

than 60% of the tropical cyclones had their onsets in the months of August and September (433/693 

= 62.5%), and the combined months of August, September, and October account for about 80% of 

all tropical cyclone onsets in the North Atlantic basin (558/693 = 80.5%). In the interval 1945–2010, 

every year saw an onset of at least one tropical cyclone in September, and all but 2 yr (1961 and 1997) 

saw an onset of at least one tropical cyclone in August. For October, at least one tropical cyclone 

occurred in every year except the years 1956, 1960, 1966, 1972, 1983, 1986, 1993, 1994, 2002, and 

2006.

For the month of June, 31 of the 66 yr had at least one tropical cyclone onset, and 6 of the 

66 yr had at least 2 onsets. Only the year 1968 saw at least 3 onsets in June. (The year 2011 saw one 

tropical cyclone onset in June.)
16

For the month of July, 37 of the 66 yr had at least one tropical cyclone onset, 15 of the 

66 yr had at least 2 onsets, 5 of the 66 yr had at least 3 onsets, and 4 of the 66 yr had at least 4 onsets. 

Only the year 2005 saw at least 5 onsets in July. (The year 2011 saw 3 onsets in July.)

For the month of August, 64 of the 66 yr had at least one tropical cyclone onset, 52 of the 

66 yr had at least 2 onsets, 37 of the 66 yr had at least 3 onsets, 23 of the 66 yr had at least 4 onsets, 

6 of the 66 yr had at least 5 onsets, 3 of the 66 yr had at least 6 onsets, and 2 of the 66 yr had at least 

7 onsets. Only the year 2004 saw at least 8 onsets in August. (The year 2011 saw 7 onsets in August.)

For the month of September, 66 of the 66 yr had at least one tropical cyclone onset, 

63 of the 66 yr had at least 2 onsets, 48 of the 66 yr had at least 3 onsets, 29 of the 66 yr had at least 

4 onsets, 17 of the 66 yr had at least 5 onsets, 9 of the 66 yr had at least 6 onsets, and 6 of the 66 yr 

had at least 7 onsets. Only the years 2002, 2007, and 2010 saw at least 8 onsets in September. Since 

the year 2000, every year except 2009 had at least 4 onsets in the month of September. (The year 2011 

saw 6 onsets in September.)

For the month of October, 56 of the 66 yr had at least one tropical cyclone onset, 35 of the 

66 yr had at least 2 onsets, 18 of the 66 yr had at least 3 onsets, 9 of the 66 yr had at least 4 onsets, 

4 of the 66 yr had at least 5 onsets, and 2 of the 66 yr had at least 6 onsets. Only the year 2005 saw at 

least 7 onsets in October. (The year 2011 saw one onset in October.)

For the month of November, 27 of the 66 yr had at least one tropical cyclone onset, and 

6 of the 66 yr had at least 2 onsets. Only the years 2001 and 2005 saw at least 3 onsets in November. 

(The year 2011 saw one onset in November.)

From table 13, the Poisson probabilities for the months of June–November are given. For 

the month of June, P(r = 0) = 56%, P(r <2) = 88.5%, and P(r <3) = 97.9%. For the month of July, 

P(r = 0) = 39.1%, P(r <2) = 75.8%, P(r <3) = 93%, and P(r <4) = 98.5%. For the month of August, 

P(r = 0) = 5.8%, P(r <2) = 22.3%, P(r <3) = 45.8%, P(r <4) = 68.1%, P(r <5) = 84%, P(r <6) 

= 93%, and P(r <7) = 97.4%. For the month of September, P(r = 0) = 2.4%, P(r <2) = 11.5%, P(r <3) 

= 28.4%, P(r <4) = 49.2%, P(r <5) = 68.5%, P(r <6) = 82.9%, P(r <7) = 91.7%, and P(r <8) = 96.4%. 

For the month of October, P(r = 0) = 15.1%, P(r <2) = 43.7%, P(r <3) = 70.6%, P(r <4) = 87.6%, 

and P(r <5) = 95.7%. For the month of November, P(r = 0) = 58.6%, P(r <2) = 89.8%, and P(r <3) 

= 98%. Hence, there appears greater than 50% probability that one would not expect a tropical 

cyclone onset in June or November, but greater than 50% probability that one would expect at least 

1 tropical cyclone onset in July, at least 3 onsets in August, at least 4 onsets in September, and at least 

2 tropical onsets in October.

2.2.2 Tropical Cyclones That Attained Only Tropical Storm Strength

For the interval 1945–2010, 306 tropical cyclones occurred that only attained tropical storm 

strength (306/715 = 42.8%). Of these, only 18 (table 9) had onsets outside the nominal hurricane 

season in the North Atlantic basin. Thus, 288 (94%) had their onsets during the June–November 

hurricane season. Of the 288 tropical cyclones that attained only tropical storm strength during 

the nominal hurricane season, 26 (9%) occurred in June, 35 (12.2%) in July, 78 (27.1%) in August, 
17

84 (29.2%) in September, 52 (18.1%) in October, and 13 (4.5%) in November. Together, nearly 60% 

of the tropical cyclones that attained only tropical storm strength had their onsets in the months of 

August and September (162/288 = 56.3%), and the combined months of August, September, and 

October account for about 75% (214/288 = 74.3%). In the interval 1945–2010, about 70% of the 

seasons saw an onset of at least one tropical cyclone that attained only tropical storm strength in 

the months of August and September, and about 50% of the seasons saw an onset of at least one 

in the month of October.

For the month of June, 25 of the 66 yr had at least one onset of a tropical cyclone that 

attained only tropical storm strength, and only 1 of the 66 yr had at least 2 onsets (2005). (The year 

2011 saw one onset of a tropical cyclone that attained only tropical storm strength in June.)

For the month of July, 30 of the 66 yr had at least one onset of a tropical cyclone that attained 

tropical storm strength, 4 of the 66 yr had at least 2 onsets (1995, 1997, 2005, and 2006), and only 

1 of the 66 yr had at least 3 onsets (1995). (The year 2011 saw 3 onsets in July.)

For the month of August, 44 of the 66 yr had at least one onset of a tropical cyclone that 

attained only tropical storm strength, 21 of the 66 yr had at least 2 onsets, 11 of the 66 yr had 

at least 3 onsets, and 2 of the 66 yr had at least 4 onsets (1984 and 1990). (The year 2011 saw 

5 onsets in August.)

For the month of September, 47 of the 66 yr had at least one onset of a tropical cyclone that 

attained only tropical storm strength, 25 of the 66 yr had at least 2 onsets, 7 of the 66 yr had at least 

3 onsets, and only 4 of the 66 yr had at least 4 onsets (1984, 2002, 2007, and 2010). (The year 2011 

saw 2 onsets in September.)

For the month of October, 34 of the 66 yr had at least one onset of a tropical cyclone that 

attained only tropical storm strength, 14 of the 66 yr had at least 2 onsets, and only 4 of the 66 yr 

had at least 3 onsets (1953, 2000, 2003, and 2005). (The year 2011 saw no onsets of tropical cyclones 

that attained only tropical storm strength in October.)

For the month of November, 12 of the 66 yr had at least one onset of a tropical cyclone that 

attained only tropical storm strength, and only 1 of the 66 yr had at least 2 onsets (2005). (The year 

2011 saw 1 onset in November.)

From table 13, the Poisson probabilities for the months of June–November are given. For 

the month of June, P(r = 0) = 67.7%, P(r <2) = 94.1%, and P(r <3) = 99.3%. For the month of July, 

P(r = 0) = 58.9%, P(r <2) = 90.1%, P(r <3) = 98.3%, and P(r <4) = 99.8%. For the month of August, 

P(r = 0) = 30.7%, P(r <2) = 67%, P(r <3) = 88.4%, P(r <4) = 96.8%, and P(r <5) = 99.3%. For the 

month of September, P(r = 0) = 28.1%, P(r <2) = 63.8%, P(r <3) = 86.4%, P(r <4) = 96%, and 

P(r <5) = 99%. For the month of October, P(r = 0) = 45.4%, P(r <2) = 81.2%, P(r <3) = 95.4%, 

and P(r <4) = 99.1%. For the month of November, P(r = 0) = 81.9%, P(r <2) = 98.2%, and P(r <3) 

= 99.9%. Hence, there appears greater than 50% probability that one would not expect the onset of 

a tropical cyclone attaining only tropical storm strength in June, July, or November, but greater than 

50% probability that one would expect at least one onset in each of the months of August, September, and October.
18

2.2.3 Hurricanes

For the interval 1945–2010, 409 tropical cyclones became hurricanes (409/715 = 57.2%). Of 

these, only 4 (table 10) had onsets outside the nominal hurricane season (2 in May and 2 in December). Thus, 405 (99%) tropical cyclones that became hurricanes had their onsets during the nominal hurricane season. Of these 405 tropical cyclones that became hurricanes, 12 (3%) occurred in 

June, 27 (6.7%) in July, 110 (27.2%) in August, 161 (39.8%) in September, 73 (18%) in October, and 

22 (5.4%) in November. Together, more than 65% of the tropical cyclones that became hurricanes 

had their onsets in the months of August and September (271/405 = 66.9%), and the combined 

months of August, September, and October account for about 85% of all those tropical cyclones that 

became hurricanes (344/405 = 84.9%). In the interval 1945–2010, 56 of the 66 yr had an onset of at 

least one tropical cyclone that became a hurricane in August, and all but 2 yr (1962 and 1994) saw 

onsets of at least one tropical cyclone becoming a hurricane in September. For October, at least one 

tropical cyclone that became a hurricane occurred in 46 of the 66 yr.

For the month of June, 11 of the 66 yr had at least one onset of a tropical cyclone that became 

a hurricane, with only the year 1968 having had at least 2 onsets. (The year 2011 saw no onsets of 

tropical cyclones that became hurricanes in June.)

For the month of July, 18 of the 66 yr had at least one onset of a tropical cyclone that 

became a hurricane, 7 of the 66 yr had at least 2 onsets, and only 2 of the 66 yr had at least 

3 onsets (1966 and 2005). (The year 2011 saw no onsets of tropical cyclones that became hurricanes 

in July.)

For the month of August, 56 of the 66 yr had onsets of at least one tropical cyclone that 

became a hurricane, 34 of the 66 yr had at least 2 onsets, 12 of the 66 yr had at least 3 onsets, and 

6 of the 66 yr had at least 4 onsets. Only the year 2004 saw the onset of at least 5 tropical cyclones 

that became hurricanes in August. (The year 2011 saw 2 onsets in August.)

For the month of September, 64 of the 66 yr had at least one onset of a tropical cyclone 

that became a hurricane, 43 of the 66 yr had at least 2 onsets, 30 of the 66 yr had at least 

3 onsets, and 18 of the 66 yr had at least 4 onsets. Only the years 1955, 1961, 1981, 2000, and 2005 

had at least 5 onsets of tropical cyclones that became hurricanes. (The year 2011 saw 4 onsets in 

September.)

For the month of October, 46 of the 66 yr had at least one onset of a tropical cyclone 

that became a hurricane, 17 of the 66 yr had at least 2 onsets, 6 of the 66 yr had at least 

3 onsets, and 3 of the 66 yr had at least 4 onsets. Only the year 2010 saw at least 5 onsets of tropical 

cyclones that became hurricanes in October. (The year 2011 saw 1 onset in October.)

For the month of November, 18 of the 66 yr had at least one onset of a tropical cyclone that 

became a hurricane, and 3 of the 66 yr had at least 2 onsets. Only the year 2001 saw the onset of at 

least 3 tropical cyclones that became hurricanes in November. (The year 2011 saw no onsets of tropical cyclones that became hurricanes in November.)
19

From table 13, the Poisson probabilities for the months of June–November are given. For 

the month of June, P(r = 0) = 83.5%, P(r <2) = 98.6%, and P(r <3) = 99.9%. For the month of July, 

P(r = 0) = 66.4%, P(r <2) = 93.6%, and P(r <3) = 99.2%. For the month of August, P(r = 0) 

= 18.8%, P(r <2) = 50.3%, P(r <3) = 76.5%, P(r <4) = 91.1%, and P(r <5) = 97.2%. For the month 

of September, P(r = 0) = 8.7%, P(r <2) = 30%, P(r <3) = 55.9%, P(r <4) = 77%, P(r <5) = 89.9%, 

P(r <6) = 96.2%, and P(r <7) = 98.7%. For the month of October, P(r = 0) = 33%, P(r <2) = 69.5%, 

P(r <3) = 89.8%, and P(r <4) = 97.4%. For the month of November, P(r = 0) = 71.9%, P(r <2) 

= 95.6%, and P(r <3) = 99.5%. Hence, there appears greater than 50% probability that one would not 

expect an onset of a hurricane in June, July, or November, but greater than 50% probability that one 

would expect at least 1 hurricane onset in August and October, and at least 2 onsets in September.

2.2.4 Major Hurricanes

For the interval 1945–2010, 179 tropical cyclones became major or intense hurricanes (179/715 

= 25% and 179/409 = 43.8%). Of these, only one (table 11) had onset outside the nominal hurricane 

season (in May 1951). Thus, 178 (99.4%) had onsets during the nominal hurricane season. Of the 

178 tropical cyclones that became major hurricanes, 3 (1.7%) occurred in June, 5 (2.8%) in July, 

61 (34.3%) in August, 85 (47.8%) in September, 19 (10.7%) in October, and 5 (2.8%) in November. 

Together, more than 80% of the tropical cyclones that became major hurricanes had onsets in the 

months of August and September (146/178 = 82%), and the combined months of August, September, and October account for more than 90% of all major hurricane onsets (165/178 = 92.7%). 

In the interval 1945–2010, 43 of the 66 yr saw an onset of at least 1 tropical cyclone that became 

a major hurricane in August, and 50 of the 66 yr had at least 1 onset of a tropical cyclone that became 

a major hurricane in September. For October, it had at least 1 onset in only 17 of the 66 yr. Since 

1995, every year (including the 2011 season) had an onset of at least 1 tropical cyclone that became 

a major hurricane in September, and 13 of the past 17 yr (1995–2011) had an onset of at least 

1 tropical cyclone that became a major hurricane in August (exceptions include 1997, 2001, 2002, 

and 2006). For 32 of the 66 yr, major hurricanes had onsets in both August and September, especially 

true between 1948 and 1958 (true in 8 of 11 yr) and between 1995 and 2011 (true in 13 of 17 yr), but 

rarely true in the interim (only 11 of 36 yr between 1959 and 1994). 

For the month of June, only 3 of the 66 yr had at least 1 onset of a tropical cyclone that 

became a major hurricane (1945, 1957, and 1966). The interval of no June onsets for a major hurricane now spans 45 yr (including the 2011 season).

For the month of July, 4 of the 66 yr had at least 1 onset of a tropical cyclone that became 

a major hurricane, with the year 2005 accounting for 2 onsets. Four of the 5 July onsets have occurred 

since 1995, the last in 2008.

For the month of August, 43 of the 66 yr had at least 1 onset of a tropical cyclone that 

became a major hurricane, 13 of the 66 yr had at least 2 onsets, and 4 of the 66 yr had at least 

3 onsets. Only the year 1950 had at least 4 onsets in August. (The year 2011 saw 2 onsets in August, 

Irene and Katia.)
20

For the month of September, 50 of the 66 yr had at least 1 onset of a tropical cyclone that 

became a major hurricane, 25 of the 66 yr had at least 2 onsets, 7 of the 66 yr had at least 3 onsets, 

and 2 of the 66 yr had at least 4 onsets. Only the year 1961 saw the onset of at least 5 tropical cyclones 

that became major hurricanes in September. Since 1995, every year has seen at least 1 onset of 

a tropical cyclone that became a major hurricane, accounting for 29 of the 85 September major hurricane onsets. (The year 2011 saw 1 onset in September of a tropical cyclone that became a major 

hurricane.)

For the month of October, 17 of the 66 yr had at least 1 onset of a tropical cyclone that 

became a major hurricane, with only the years 1950 and 2005 having at least 2 onsets. Since 1995, 

7 onsets have occurred of tropical cyclones that became major hurricanes, including 1 in the 2011 

hurricane season (Rina).

For the month of November, 5 of the 66 yr had at least 1 onset of a tropical cyclone that 

became a major hurricane, 4 of the 5 occurring since 1985. (The year 2011 saw no onsets of tropical 

cyclones that became major hurricanes in November.)

From table 13, the Poisson probabilities for the months of June–November are given. For the 

month of June, P(r = 0) = 95.1% and P(r <2) = 99.9%. For the month of July, P(r = 0) = 92.3% and 

P(r <2) = 99.7%. For the month of August, P(r = 0) = 39.9%, P(r <2) = 76.5%, P(r <3) = 93.4%, and 

P(r <4) = 98.6%. For the month of September, P(r = 0) = 27.5%, P(r <2) = 63%, P(r <3) = 85.9%, 

P(r <4) = 95.8%, and P(r <5) = 99%. For the month of October, P(r = 0) = 74.8%, P(r <2) = 96.5%, 

and P(r <3) = 99.7%. For the month of November, P(r = 0) = 92.3% and P(r <2) = 99.7%. Hence, 

there appears greater than 50% probability that one would not expect an onset of a major hurricane 

in June, July, October, or November, but greater than 50% probability that one would expect at least 

one major hurricane onset in August and September.

2.2.5 US Landfalling Hurricanes

For the interval 1945–2010, 108 tropical cyclones struck the US as hurricanes (table 12), 

with all strikes occurring during the nominal hurricane season (108/715 = 15.1% and 108/409 

= 26.4%). Of the 108 tropical cyclones that struck the US as hurricanes, 5 (4.6%) occurred in June, 

12 (11.1%) in July, 38 (35.2%) in August, 40 (37%) in September, 12 (11.1%) in October, and only 

1 (0.9%) in November. Together, more than 70% of the tropical cyclones that struck the US did so in the 

months of August and September (78/108 = 72.2%), and the combined months of July, August, September, and October account for more than 90% of all US strikes by landfalling hurricanes (102/108 

= 94.4%). In the interval 1945–2010, there have been no more than 2 strikes in a single month, with 

the lone exception being August 2004 when 4 strikes occurred in the month. As previously noted, the 

longest lull between strikes has been 2 yr, occurring only three times, the years 1981–1982, 2000–2001, 

and 2009–2010. The most US strikes by hurricanes in a single season (6) occurred three times, in the 

years 1985, 2004, and 2005. Prior to 1985, the most US strikes by hurricanes occurred in 1964 when 

4 strikes occurred. Between 1945 and 1960, there were 34 US strikes by hurricanes (34/108 = 31.5%, 

striking at the mean rate of 2.1 strikes per year), with the years 1947–1950 having 3 strikes each year 

and only the year 1951 not having a single US strike. (There was only one strike of the US by a hurricane in the 2011 season, Irene, which struck North Carolina as a category 1 hurricane in August.) 
21

From table 13, the Poisson probabilities for the months of June–November are given. For 

the month of June, P(r = 0) = 92.3% and P(r <2) = 99.7%. For the month of July, P(r = 0) = 83.5% 

and P(r <2) = 98.6%. For the month of August, P(r = 0) = 56%, P(r <2) = 88.5%, and P(r <3) 

= 97.9%. For the month of September, P(r = 0) = 54.3%, P(r <2) = 87.5%, and P(r <3) = 97.6%. 

For the month of October, P(r = 0) = 83.5% and P(r <2) = 98.6%. For the month of November, 

P(r = 0) = 98%.

Table 14 (see appendix) gives the yearly distribution of US hurricane landstrikes by state. While 

there were 108 tropical cyclones that struck the US as hurricanes, they actually accounted for 178 separate hits, with Florida taking the brunt (50/178 = 28.1%), Louisiana and North Carolina each having 

the second most hits (each 23/178 = 12.9%), and Texas having the next most hits (21/178 = 11.8%). 

Together, these four states account for nearly two-thirds of all US hits by hurricanes (117/178 

= 65.7%).

2.3 The Distribution of Tropical Cyclones by Geographical Region, 1945–2010

The North Atlantic basin can be arbitrarily divided into selected geographical regions or 

areas of activity. Figure 7 depicts one such division into five areas, denoted by the thick lines and 

numbered 1–5. Area 1 corresponds to the area of the Gulf of Mexico, area 2 can be regarded as the 

area of the Caribbean Sea, area 3 is the eastern seaboard area of the US, area 4 is the lower North 

Atlantic-Cape Verde area, and area 5 is the open North Atlantic basin northward of the Cape Verde 

Islands. Figures 8–12 show the yearly variation of each grouping, respectively, and table 15 (see 

appendix) provides the Poisson probabilities for each grouping.

1

3 5

4 2

 Figure 7. Onset location regions of Atlantic basin tropical cyclones by group—reduced

version of the Atlantic basin hurricane tracking chart, National Hurricane Center, 

Miami, FL.
22

2.3.1 NTC

Figure 8 shows the yearly variation of NTC in each of the areal groupings. Area or group 4 

is the single largest progenitor of tropical cyclones in the North Atlantic basin during the interval 

1945–2010, accounting for more than 25% of the total number of tropical cyclones that formed in 

the North Atlantic basin (199/715 = 27.8%). This is understandable since it is this area where the 

westerly waves coming off Africa occur. The second largest progenitor of tropical cyclones in the 

North Atlantic basin is group 3, accounting for almost 25% of the total (165/715 = 23.1%). Together, 

these two regions account for about 50% of the tropical cyclone formations in the North Atlantic 

basin in the interval 1945–2010 (364/715 = 50.9%). Including group 1, the third largest progenitor of 

tropical cyclone formation (149/715 = 20.8%), these three groups account for more than 70% of the 

tropical cyclones in the North Atlantic basin (513/715 = 71.7%), and, including group 2, the combined total now accounts for more than 85% of the tropical cyclones (624/715 = 87.3%). Group 5 

(the open North Atlantic basin) produced the fewest number of tropical cyclone formations (111/715 

= 15.5%), which also is understandable because of the cooler surface waters and the strong easterly 

flows off the US.

Interestingly, visual inspection of group 2 tropical cyclones (fig. 8(b)) suggests that, on average, tropical cyclone formation was higher for this group prior to about 1955 and now subsequent 

to about 1994 than what was seen between 1955 and 1994. This suggests, perhaps, the existence of 

a long-term multidecadal variation of tropical cyclone formation within the Caribbean Sea region. 

Also, group 4 storms (fig. 8(d)) appear to be on the rise since about the mid 1980s (8 formations in the 

year 1990, and 9 each in the years 1995 and 2010), while group 3 storms (fig. 8(c)) appear to be more 

frequent progenitors of tropical cyclones between the mid 1960s and the mid 1980s. Group 5 storms 

are 3 or fewer in number every year in the interval 1945–2010, except the year 2005 when 8 tropical 

cyclones formed. (For the 2011 season, group 1 accounted for 4 NTC, group 2 accounted for 3 NTC, 

group 3 accounted for 6 NTC, group 4 accounted for 5 NTC, and group 5 accounted for 1 NTC.)

For group 1 NTC (table 15), P(r = 0) = 10%, P(r <2) = 33.1%, P(r <3) = 59.6%, P(r <4) 

= 79.9%, P(r <5) = 91.6%, and P(r <6) = 97%. For group 2 NTC, P(r = 0) = 18.3%, P(r <2) = 49.3%, 

P(r <3) = 75.7%, P(r <4) = 90.7%, and P(r <5) = 97.1%. For group 3 NTC, P(r = 0) = 8.2%, P(r

<2) = 28.7%, P(r <3) = 54.4%, P(r <4) = 75.8%, P(r <5) = 89.1%, P(r <6) = 95.8%, and P(r <7) 

= 98.6%. For group 4 NTC, P(r = 0) = 5%, P(r <2) = 19.9%, P(r <3) = 42.3%, P(r <4) = 64.7%, 

P(r <5) = 81.5%, P(r <6) = 91.6%, P(r <7) = 96.6%, and P(r <8) = 98.8%. Lastly, for group 5 NTC, P(r

= 0) = 24.7%, P(r <2) = 59.2%, P(r <3) = 83.4%, P(r <4) = 94.6%, and P(r < 5) = 98.5%. The central 

3 highest probabilities for NTC are 2 ± 1 (69.9%) for group 1, 1 ± 1 (75.7%) for group 2, 2 ± 1 (67.6%) 

for group 3, 3 ± 1 (61.6%) for group 4, and 1 ± 1 (83.4%) for group 5.
23

NTC

5

10

NTC

5

0

0

0

0

0

10

(a)

(b)

(c)

(d)

(e)

1950

Group 5 (91)

1945–2010

Group 1 (149)

1945 1955 1960 1970 1980 1990 2000 2010

mean = 1.4

sd = 1.4

range = 0–8

NTC

5

10 Group 4 (199)

mean = 3.0

sd = 2.1

range = 0–9

NTC

5

10 Group 3 (165)

mean = 2.5

sd = 1.6

range = 0–7

NTC

5

10 Group 2 (111)

mean = 1.7

sd = 1.6

range = 0–7

mean = 2.3

sd = 1.2

range = 0–5

1965 1975 1985 1995 2005

Year

Figure 8. NTC versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4,

and (e) group.

2.3.2 NTS

Figure 9 displays the variation by group for NTS. Group 1 is the largest progenitor of tropical 

cyclones that attained only tropical storm strength (88/306 = 28.8%), group 3 is the second largest 

progenitor of NTS (76/306 = 24.8%), group 4 is the third largest (65/306 = 21.2%), and group 5 is the 

fourth largest (42/306 = 13.7%). The region of fewest NTS is group 2 (35/306 = 11.4%). The greatest NTS (5) occurred twice in 1974 and 1997, both associated with group 3. The greatest NTS for 

group 1 (4) occurred in 1957 and 2003, group 2 (3) in 2005, group 4 (4) in 1990, and group 5 (4) in 

2005. (For the 2011 season, group 1 accounted for 3 NTS, group 2 accounted for 2 NTS, group 3 

accounted for 6 NTS, group 4 accounted for no NTS, and group 5 accounted for 1 NTS.)
24

NTS

5

0

0

0

0

0

NTS

5

1950

Group 5 (42)

Group 4 (65)

1945 1955 1960 1970 1980 1990 2000 2010

mean = 0.6

sd = 0.8

range = 0–4

mean = 1

sd = 1

range = 0–4

NTS

5 Group 3 (76) mean = 1.2

sd = 1.2

range = 0–5

NTS

5 Group 2 (35) mean = 0.5

sd = 0.7

range = 0–3

NTS

5 Group 1 (88)

1945–2010

mean = 1.3

sd = 1

range = 0–4

1965 1975 1985 1995 2005

Year

(a)

(b)

(c)

(d)

(e)

Figure 9. NTS versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, and (e) group 5.

For group 1, P(r = 0) = 27.3%, P(r <2) = 62.7%, P(r <3) = 85.7%, P(r <4) = 95.7%, and 

P(r <5) = 98.9%. For group 2, P(r = 0) = 60.7%, P(r <2) = 91%, and P(r <3) = 98.6%. For 

group 3, P(r = 0) = 30.1%, P(r <2) = 66.3%, P(r <3) = 88%, P(i <4) = 96.6%, and P(r <5) = 99.2%. For 

group 4, P(r = 0) = 36.8%, P(r <2) = 73.6%, P(r <3) = 92%, and P(r <4) = 98.1%. For group 5, P(r = 0) 

= 54.9%, P(r <2) = 87.8%, and P(r <3) = 97.7%. The central 3 highest probabilities for NTS are 

1 ± 1 (85.7%) for group 1, 1 ± 1 (98.6%) for group 2, 1 ± 1 (88%) for group 3, 1 ± 1 (91.7%) for 

group 4, and 1 ± 1 (97.7%) for group 5.

2.3.3 NH

Figure 10 displays the variation by group for NH. Group 4 is the largest progenitor of tropical cyclones that attained hurricane strength (134/409 = 32.8%), group 3 is the second largest progenitor of NH (89/409 = 21.8%), group 2 is the third largest (76/409 = 18.6%), and group 1 is the 

fourth largest (61/ 409 = 14.9%). The region of fewest NH is group 5 (49/409 = 12%). The greatest 

NH (6) occurred twice in 1995 and 2010, both associated with group 4. The greatest NH for group 1 

(4) occurred in 1985, group 2 (4) in 1949, 1996, 2005, and 2008, group 3 (4) in 1969, 1976, and 2005, 

and group 5 (4) in 2005. (For the 2011 season, group 1 accounted for 1 NH, group 2 accounted for 

1 NH, group 3 accounted for no NH, group 4 accounted for 5 NH, and group 5 accounted for no 

NH.)
25

NH

5

NH

5

5

10

1950

Group 5 (49)

Group 4 (134)

Group 3 (89)

1945 1955 1960 1970 1980 1990 2000 2010

mean = 0.7

sd = 1

range = 0–4

mean = 2

sd = 1.8

range = 0–6

NH

mean = 1.3

sd = 1.1

range = 0–4

5 Group 2 (76)

NH

mean = 1.2

sd = 1.2

range = 0–4

5

0

0

0

0

0

1945–2010

Group 1 (61)

NH

mean = 0.9

sd = 0.8

range = 0–4

1965 1975 1985 1995 2005

Year

(a)

(b)

(c)

(d)

(e)

Figure 10. NH versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, and (e) group 5.

For group 1, P(r = 0) = 40.7%, P(r <2) = 77.3%, P(r <3) = 93.7%, and P(r <4) = 98.7%. For 

group 2, P(r = 0) = 30.1%, P(r <2) = 66.3%, P(r <3) = 88%, P(r <4) = 96.6%, and P(r <5) = 99.2%. 

For group 3, P(r = 0) = 27.3%, P(r <2) = 62.7%, P(r <3) = 85.7%, P(r <4) = 95.7%, and P(r <5) 

= 98.9%. For group 4, P(r = 0) = 13.5%, P(r <2) = 40.6%, P(r <3) = 67.7%, P(r <4) = 85.7%, P(r <5) 

= 94.7%, and P(r <6) = 98.3%. For group 5, P(r = 0) = 49.7%, P(r <2) = 84.4%, P(r <3) = 96.6%, 

and P(r <4) = 99.4%. The central 3 highest probabilities for NH are 1 ± 1 (93.7%) for group 1, 1 ± 1 

(88%) for group 2, 1 ± 1 (85.7%) for group 3, 2 ± 1 (72.2%) for group 4, and 1 ± 1 (96.6%) for group 5.

2.3.4 NMH

Figure 11 displays the variation by group for NMH. Group 4 is the largest progenitor of 

tropical cyclones that attained major hurricane strength (93/179 = 52%), group 2 is the second largest progenitor of NMH (43/179 = 24%), group 3 is the third largest (20/179 = 11.2%), and group 1 is 

the fourth largest (17/179 = 9.5%). The region of fewest NMH is group 5 (6/179 = 3.4%). The greatest NMH (5) occurred twice in 1950 and 1996, both associated with group 4. The greatest NMH 

for group 1 (2) occurred in 1964 and 1970, group 2 (3) in 1961, 2005, and 2008, group 3 (2) in 1958 

and 2005, and group 5 (1) in 1950, 1959, 1991, 2003, 2005, and 2006. (For the 2011 season, group 1 

accounted for no NMH, group 2 accounted for 1 NMH, group 3 accounted for no NMH, group 4 

accounted for 3 NMH, and group 5 accounted for no NMH.)
26

NMH

5

0

0

0

0

0

NMH

5

1950

Group 5 (6)

Group 4 (93)

1945 1955 1960 1970 1980 1990 2000 2010

mean = 0.1

sd = 0.3

range = 0–1

mean = 1.4

sd = 1.3

range = 0–5

NMH

5 Group 3 (20) mean = 0.3

sd = 0.5

range = 0–2

NMH

5 Group 2 (43) mean = 0.7

sd = 0.9

range = 0–3

NMH

5 1945–2010

Group 1 (17) mean = 0.3

sd = 0.5

range = 0–2

1965 1975 1985 1995 2005

Year

(a)

(b)

(c)

(d)

(e)

Figure 11. NMH versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, and (e) group 5.

For group 1, P(r = 0) = 74.1%, P(r <2) = 96.3%, and P(r <3) = 99.6%. For group 2, P(r = 0) 

= 49.7%, P(r <2) = 84.4%, P(r <3) = 96.6%, and P(r <4) = 99.4%. For group 3, P(r = 0) = 74.1%, 

P(r <2) = 96.3%, and P(r <3) = 99.6%. For group 4, P(r = 0) = 24.7%, P(r <2) = 59.2%, P(r <3) 

= 83.4%, P(r <4) = 94.6%, and P(r <5) = 98.6%. For group 5, P(r = 0) = 90.5% and P(r <2) = 99.5%. 

The central 3 highest probabilities for NMH are 1 ± 1 (99.6%) for group 1, 1 ± 1 (96.6%) for group 2, 

1 ± 1 (99.6%) for group 3, 1 ± 1 (83.4%) for group 4, and 1 ± 1 (99.5%) for group 5.

2.3.5 NUSLFH

Figure 12 displays the variation by group for NUSLFH. Group 1 is the largest progenitor of 

tropical cyclones that struck the US coastline as hurricanes (34/108 = 31.5%), group 4 is the second 

largest progenitor of NUSLFH (30/108 = 27.8%), group 2 is the third largest (24/108 = 22.2%), and 

group 3 is the fourth largest (20/108 = 18.5%). The region of fewest NUSLFH is group 5, which 

produced none. The greatest NUSLFH (4) occurred in 1985, associated with group 1. The greatest 

NUSLFH for group 2 (2) occurred in 1948, 1950, 2004, 2005, and 2008, group 3 (3) in 2005, and 

group 4 (3) in 1955. (For the 2011 season, there was only one US landfalling hurricane, it being associated with group 4.)

For group 1, P(r = 0) = 60.7%, P(r <2) = 91%, and P(r <3) = 98.6%. For group 2, P(r = 0) 

= 67%, P(r <2) = 93.8%, and P(r <3) = 98.5 %. For group 3, P(r = 0) = 74.1%, P(r <2) = 96.3%, and 

P(r <3) = 99.6%. For group 4, P(r = 0) = 60.7%, P(r <2) = 91%, and P(r <3) = 98.6%. The central 

3 highest probabilities for NUSLFH are 1 ± 1 (98.6%) for group 1, 1 ± 1 (98.5%) for group 2, 1 ± 1 

(99.6%) for group 3, and 1 ± 1 (98.6%) for group 4.
27

NUSLFH NUSLFH NUSLFH NUSLFH NUSLFH

5

5

1950

Group 5 (0)

Group 4 (30)

1945 1955 1960 1970 1980 1990 2000 2010

mean = 0.5

sd = 0.7

range = 0–3

5 Group 3 (20)

mean = 0.3

sd = 0.6

range = 0–3

5 Group 2 (24)

mean = 0.4

sd = 0.6

range = 0–2

5

0

0

0

0

0

1945–2010

Group 1 (34)

mean = 0.5

sd = 0.7

range = 0–4

1965 1975 1985 1995 2005

Year

(a)

(b)

(c)

(d)

(e)

Figure 12. NUSLFH versus year: (a) Group 1, (b) group 2, (c) group 3, (d) group 4, and

(e) group 5.

2.4 The Seasonal Centroid Location of Tropical Cyclones, 1945–2010

The National Hurricane Center’s ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> provides at 6-hr intervals the position (latitude and longitude in deg) and intensity (wind speed in kt and pressure in mbar) of tropical cyclones that form in the North Atlantic 

basin, along with other descriptive information regarding them. As an example as to how one determines the seasonal centroid location of tropical cyclones, the following is given: In 1983, four tropical cyclones formed in the North Atlantic basin. These included Alicia, Barry, Chantal, and Dean. 

Alicia formed on August 15, located at 27.2 deg N. LAT and 91 deg W. LONG; Barry formed on 

August 24 at 27.4 deg N. LAT and 76.3 deg W. LONG; Chantal formed on September 1l at 31.6 deg 

N. LAT and 63.3 deg W. LONG; and Dean formed on September 26 at 28 deg N. LAT and 73 deg 

W. LONG. The mean of all latitudinal and longitudinal positions is 28.6 deg N. and 75.9. deg W., 

respectively. Thus, the seasonal centroid for 1984 is 28.6 deg N. LAT and 75.9 deg W. LONG.

2.4.1 Latitude

Figure 13 depicts the yearly latitudinal centroid locations of the tropical cyclones for the 

interval 1945–2010, employing the same construction as used in the preceding parametric summary 

charts. Figure 13(a) shows that for the interval 1945–2010 the mean latitude is about 22 deg N., 

having sd = 3.4 deg and range 16.4 to 32.2 deg N. Prior to the mid 1960s, the 10-yma values of latitude were always below the long-term mean latitude (i.e., more southerly), rising above the mean 
28

 First Difference (fd(<N. LAT>))

–1

–0.5

0.0

1.0

0.5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<N. LAT>)t

 = <N. LAT>(10-yma)t+1 – <N. LAT>(10-yma)t

 sd = 0.3

1965 1975 1985 1995 2005

Year

(c)

(b)

1950–1989: mean = 0.058

sd = 0.361 

1990–2004: mean = –0.02

sd = 0.296

 Difference (d(<N. LAT>))

–5

0

5

10 d(<N. LAT>)t

 = <N. LAT>(yearly)t – <N. LAT>(10-yma)t

 sd = 2.8

(a)

<N. LAT>

15

20

25

30

35 1945–2010

<N. LAT>

⇒t = 0.747

⇒cl <90%

1945–1994: mean = 22.41

sd = 3.38

1995–2010: mean = 20.763

sd = 3.042

⇒t = 1.736 

⇒ cl >90%

mean = 22

sd = 3.4

range = 16.4–32.2

Figure 13. Yearly latitudinal centroid locations of tropical cyclones: (a) <N. LAT>,

(b) difference (d<N. LAT>), and (c) first difference (fd<N. LAT>).

about 1964 (i.e., more northerly) and remaining above the mean until about 1990 when it once again 

dropped below the long-term mean latitude where it has remained ever since, although the lowest 

values now being seen are slightly higher than were seen prior to the mid 1960s (20.8 deg N. as compared to 19.5 deg N.). For the interval 1995–2010, latitude averages about 20.8 deg N., having sd

= 3 deg and range 16.2 to 27.1 deg N. (For the 2011 season, its mean latitude measured 22 deg N.)
29

Figure 13(b) displays the variation of the difference. Runs testing indicates that, while the 

differences appear somewhat more variable now (in their extremes) than earlier on, the differences 

seem to be distributed randomly (z = 0.38, cl <90%, and sd = 2.8 deg). Hence, one should have 

expected the 10-yma of <N. LAT> = 21.9 ± 2.8 deg N. in 2006, based on the expected difference, 

where 21.9 deg N. is the yearly value for 2006. As it turns out, the yearly <N. LAT> = 22 deg N. for 

2011, thereby yielding the 10-yma of <N. LAT> = 21.2 deg N. for 2006. For 2007, one also expects 

the 10-yma of <N. LAT> = 21.9 ± 2.8 deg N., based on the expected difference, where 21.9 deg N. is 

the yearly <N. LAT> for 2007.

Figure 13(c) shows the variation of the first differences. Runs testing indicates that its distribution is nonrandom (z = –3.14, cl >99.5%, and sd = 0.3 deg). For the interval 1950–1972, every 

year had fd(N. LAT)t ≥0 deg, except the year 1961, averaging about 0.3 deg, with sd = 0.2 deg. and 

range –0.2 to 0.7 deg. For the interval 1973–1990, every year had fd(N. LAT)t <0 deg, except 1978, 

1985, and 1986, averaging about –0.3 deg, with sd = 0.3 deg and range –0.8 to 0.3 deg. For the interval 1991–2010, fd(N. LAT)t

 ≥0 deg except for the years 1993, 1995, 1996, 2002, and 2004, averaging 

about 0 deg, with sd = 0.2 deg and range –0.3 to 0.5 deg. (The 10-yma <N. LAT> has a minimum 

value of 19.9 deg for the year 2007, computed by assuming a frequency of zero NTC in 2012.)

Given that fd(N. LAT) averages about 0 ± 0.3 deg, one expected the 10-yma of <N. LAT> to 

be about 21.5 ± 0.3 deg N. for 2006 (where 21.5 deg N. is the 10-yma value for 2005), thereby inferring the yearly <N. LAT> = 27.6 ± 6 deg N. for 2011. As noted above, the yearly seasonal latitudinal 

value for 2011 measured 22 deg N., thus yielding the 10-yma of <N. LAT> = 21.2 deg N. for 2006 

and fd(<N. LAT>) = –0.3 deg for 2005. For 2007, one anticipates the10-yma value of <N. LAT> 

= 21.2 ± 0.3 deg N., inferring the yearly value of <N. LAT> = 26.2 ± 6 deg N. for 2012.

2.4.2 Longitude

Figure 14 depicts the yearly longitudinal centroid locations of the tropical cyclones for the 

interval 1945–2010, employing the same construction as used in the preceding parametric summary 

charts. Figure 14(a) shows that for the interval 1945–2010 the mean longitude is about 65 deg W., 

having sd = 6.6 deg and range 51.8 to 82.6 deg W. Interestingly, the 10-yma values of longitude 

appear to vacillate more westward and eastward of the long-term mean longitude over time, with 

the 10-yma values now being consistently eastward of the mean since 1984. In fact, a linear fit of the 

10-yma values of <W. LONG> against year suggests that it is moving progressively more eastward 

(away from the US) with time, such that the expected 10-yma value of <W. LONG> = 62 ± 2.5 

deg W. for 2006, based on the inferred regression (not shown) y = 259.5272 – 0.0985x, where x is the 

year and y is the 10-yma value of <W. LONG> (r = –0.727, r2 = 0.528, se = 2.46 deg, and cl >99.9%), 

inferring the yearly seasonal value of <W. LONG> = 67.4 ± 5 deg W. for 2011. As it turns out, 

the yearly seasonal <W. LONG> = 65.2 deg for 2011, yielding the 10-yma value of <W. LONG> 

= 61.9 deg W. for 2006. For 2007, the inferred regression suggests <W. LONG> = 61.9 ± 2.5 deg W., 

inferring the yearly seasonal value of <W. LONG> = 68.7 ± 5 deg W. for 2012.

Figure 14(b) displays the variation of the difference. Runs testing indicates that the distribution of the differences is random (z = 1.39, cl <90%, sd = 5.6 deg). Hence, one should 

have expected the 10-yma of <W. LONG> = 56.6 ± 5.6 deg W. for 2006, based on the expected
30

First Difference (fd(<W. LONG>)) –2.5

–2

–1.5

–0.5

–1

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

(c)

1950–1989: mean = –0.173

sd = 0.736 

1990–2004: mean = 0.027

sd = 0.504

0

0.5

1

1.5 fd(<W. LONG>)t

 = <W. LONG>(10-yma)t+1 – <W. LONG>(10-yma)t

 sd = 0.7

1945–2010

<W. LONG>

⇒t = –0.968

⇒cl <90%

Difference (d(<W. LONG>))

–15

–10

–5

5

0

(b)

10

15 d(<W. LONG>)t

 = <W. LONG>(yearly)t – <W. LONG>(10-yma)t

 sd = 5.6

<W. LONG>

(a)

80

75

70

65

60

55

50

85

1945–1994: mean = 65.806

sd = 6.863 

1995–2010: mean = 62.238

sd = 4.812

⇒t = 1.929 

⇒cl >90%

mean = 64.9

sd = 6.6

range = 51.8–82.6

Figure 14. Yearly longitudinal centroid locations of tropical cyclones: (a) <W. LONG>, 

(b) difference (d<W. LONG>), and (c) first difference (fd<W. LONG>).
31

difference. As it turns out, the yearly <W. LONG> = 65.2 deg W. for 2011, thereby yielding the

10-yma of <W. LONG> = 61.9 deg W. in 2006. For 2007, one expects the 10-yma of <W. LONG> = 65.1 

± 5.6 deg W., based on the expected difference, where 65.1 deg W. is the yearly <W. LONG> for 2007.

Figure 14(c) shows the variation of the first differences. Runs testing indicates that its distribution is nonrandom (z = –2.80, cl >99%, and sd = 0.7 deg). Certainly, to the eye, at least, there 

appears to exist strong variations in fd(<W. LONG>), with values, perhaps, trending towards smaller 

(albeit, negative) values with time (i.e., continued movement of the longitudinal centroid eastward 

away from the US). (The 10-yma <W. LONG> has a minimum value of 58.5 deg for the year 2007, 

computed by assuming a frequency of zero NTC in 2012.)

Given that fd(W. LONG) averages about –0.1 ± 0.7 deg, one expected the 10-yma of 

<W. LONG> to be about 62 – 0.1 ± 0.7 deg W. for 2006 (where 62 deg W. is the 10-yma value for 

2005), inferring the yearly <W. LONG> = 61.9 ± 14 deg for 2011. As noted above, the yearly seasonal longitude value for 2011 measured 65.2 deg W., thus yielding the 10-yma of <W. LONG> 

= 61.9 deg W. for 2006 and fd(<W. LONG>) = –0.1 deg for 2005. For 2007, one anticipates the 

10-yma value of <W. LONG> = 61.9 – 0.1 ± 0.7 deg W. or 61.8 ± 0.7 deg W., inferring the yearly 

value of <W. LONG> = 61.8 ± 14 deg W. for 2012.

2.4.3 Systematic Variation of Latitude and Longitude

Figure 15 shows the scatter plot of 10-yma values of <N. LAT> against <W. LONG> for the 

interval 1950–2005. Perhaps surprisingly, one finds evidence for systematic variation to really exist. 

In the figure, the dots are time tagged at 10-yr intervals. The vertical and horizontal lines represent 

the means of longitude and latitude, respectively, subdividing the figure into four quadrants. Clearly, 

the 10-yma values for 1950–1961 appear in the lower-left quadrant, indicating that tropical cyclones 

during this interval tended to form at lower latitude and in closer proximity to the US than those of 

later years. For 1962 and 1963, the centroids moved farther eastward into the lower-right quadrant, 

then moved northward into the upper-right quadrant for 1964–1967. For 1968–1983, the centroids 

moved farther northward, but also westward into the upper-left quadrant. For 1984–1989, the centroids moved eastward again into the upper-right quadrant. Lastly, for the interval 1990–2005, all 

10-yma values are located in the lower-right quadrant. The 10-yma values of latitude and longitude 

for 2006 (not plotted) have remained in the lower-right quadrant. The projected 10-yma values of 

latitude (21.2 ± 0.3 deg N.) and longitude (either 61.9 ± 2.5 deg W. from the inferred linear regression 

or 61.8 ± 0.7 deg W. from the usual first difference) for 2007 are such that one expects the centroids 

to remain in the lower-right quadrant.
32

<N. LAT>10-yma

<W. LONG>10-yma

15

20

25

30

70 65 60

1980

2005

1990

2000

1970

1960

1950

Figure 15. <N. LAT> versus <W. LONG>.

2.5 The Distribution of Peak Wind Speed and Lowest Pressure

2.5.1 PWS

Figure 16(a) displays the yearly variation of the PWS (in kt) for the interval 1945–2010. PWS 

is defined as the highest sustained maximum wind speed for a tropical cyclone for the year. As an 

example, the storm with the highest sustained maximum wind speed in 1983 was Alicia, which had 

PWS = 100 kt. Thus, 100 kt is the PWS for 1983, which is plotted in figure 16(a). The long-term mean 

is 126.7 kt, having sd = 19.7 kt and range 75 to 165 kt. There appears to be no statistical difference in 

the means for the two intervals 1945–1994 and 1995–2010, although the current, more active interval 

has a mean that is about 5% higher than the preceding interval (131.6 kt as compared to 125.4 kt). 
33

First Difference (fd(PWS))

0

–5

(c)

(b)

(a)

5

1945 1950 1955 1960 1970 1980 1990 2000 2010

mean = 126.9

sd = 19.7

range = 75–165

1965 1975 1985 1995 2005

Year

fd(PWS)t

 = PWS(10-yma)t+1 – PWS(10-yma)t

 sd = 2.2

Difference (d(PWS))

0

–50

50 d(PWS)t

 = PWS(yearly)t – PWS(10-yma)t

 sd = 19.5

PWS

100

50

150

200 1945–2010

PWS

1950–1989: mean = –0.305

sd = 1.539 

1990–2004: mean = 0.867

sd = 1.792

⇒t = –2.405

⇒cl >98%

1945–1994: mean = 125.4

sd = 20.698 

1995–2010: mean = 131.563

sd = 15.992

⇒t = –1.089 

⇒cl <90%

Figure 16. Yearly peak wind speed: (a) PWS, (b) difference (d(PWS)), and (c) first difference (fd(PWS)).

The highest PWS (165 kt) has occurred twice, in 1969 (Camille) and 1980 (Allen), and the lowest 

PWS (75 kt) occurred in 1968 (Gladys). The peak 10-yma PWS measured 135 kt in 1954 and 2003, 

and the lowest 10-yma PWS measured 118 kt in 1972.

Figure 16(b) shows the yearly variation of the difference (d(PWS)t). Runs testing indicates 

that the distribution of differences is random (z = 0.80, cl <90%, sd = 19.5 kt). Hence, one should 

have expected the 10-yma of PWS = 105 ± 19.5 kt in 2006, where 105 kt is the yearly PWS for 2006. 

As it turns out, PWS = 120 kt in 2011, thereby yielding the 10-yma of PWS = 132.8 kt in 2006, 

a value outside high the ±1 sd prediction interval. For 2007, based on the usual observed difference, 

one expects the 10-yma of PWS = 150 ±19.5 kt, or PWS >130 kt, where 150 kt is the yearly PWS for 

2007.

Figure 16(c) depicts the yearly variation of the first difference (fd(PWS)t). Runs testing 

indicates that the distribution of first differences is nonrandom (z = –2.27, cl >95%, sd = 2.2 kt). 

A comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 is found 

to be statistically important (cl >98%), with the current, more active interval having a mean first 

difference equal to 0.9 kt and sd of 1.8 kt. Hence, one would have anticipated the 10-yma of PWS 

for 2006 to be about 132.3 + 0.9 ± 1.8 kt, or 133.2 ± 1.8 kt. As noted above, the 2011 season had

PWS = 120 kt, thereby yielding the 10-yma of PWS = 132.8 kt for 2006 (up from 132.3 kt in 2005), 
34

inferring an fd = 0.5 kt for 2005. For 2007, one anticipates the 10-yma of PWS = 133.2 + 0.9 ± 1.8 kt, 

or 134.1 ± 1.8 kt, indicating PWS >120 kt in 2012. (The 10-yma PWS has a minimum value of

126.3 kt for the year 2007, computed by assuming a frequency of zero NTC in 2012.)

2.5.2 <PWS>

Figure 17(a) displays the yearly variation of the <PWS> (in kt) for the interval 1945–2010. 

<PWS> is defined as the seasonal mean of the individual tropical cyclone highest sustained maximum wind speeds. As an example, the four storms of 1983 had PWS equal to 100 kt (Alicia),

70 kt (Barry), 65 kt (Chantal), and 55 kt (Dean), thus yielding a mean of 72.5 kt, which is plotted in

figure 17(a). The long-term mean is 74.9 kt, having sd = 9.1 kt and range 55.6 to 100.4 kt. There appears 

to be no statistical difference in the means for the two intervals 1945–1994 and 1995–2010, although 

the current, more active interval has a mean that is about 2% lower than the preceding interval 

(73.8 kt as compared to 75.3 kt). The highest <PWS> (100.4 kt) occurred in 1950, and the lowest 

<PWS> (59.3 kt) occurred in 1987. The peak 10-yma <PWS> measured 82.3 kt in 1952, and the 

lowest 10-yma <PWS> measured 69.1 kt in 1986. First Difference (fd(<PWS>))

–5

0

5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<PWS>)t

 = <PWS>(10-yma)t+1 – <PWS>(10-yma)t

 sd = 1

Difference (d(<PWS>)) –25

0

25 d(<PWS>)t

 = <PWS>(yearly)t – <PWS>(10-yma)t

 sd = 8.2

<PWS>

50

75

100

1965 1975 1985 1995 2005

Year (c)

(b)

(a)

1950–1989: mean = –0.268

sd = 1.012 

1990–2004: mean = 0.16

sd = 0.8

1945–2010

<PWS>

⇒t = –1.472

⇒cl <90%

1945–1994: mean = 75.268

sd = 9.216

1995–2010: mean = 73.788

sd = 8.901

⇒t = 0.564

⇒ cl <90%

mean = 74.9

sd = 9.1

range = 55.6–100.4

Figure 17. Yearly seasonal mean of individual cyclone’s peak wind speed: (a) <PWS>, 

(b) difference (d<PWS>), and (c) first difference (fd<PWS>). 
35

Figure 17(b) shows the yearly variation of the difference (d (<PWS>)t). Runs testing indicates 

that the distribution of differences possibly could be nonrandom (z = 1.86, cl >90%, sd = 8.2 kt). 

Ignoring that the distribution of differences might possibly be nonrandom (albeit, only of marginal 

statistical importance), one would have expected the 10-yma of <PWS> = 68.5 ± 8.2 kt for 2006, 

where 68.5 kt is the yearly <PWS> for 2006 (i.e., the same value as determined for 2005). As it turns 

out, <PWS> = 66.3 kt in 2011, thereby yielding the 10-yma of <PWS> = 72 kt in 2006. For 2007, 

based on the usual observed difference, one anticipates the 10-yma of <PWS> = 65 ± 8.2 kt, or 

<PWS> < 73.2 kt, where 65 kt is the yearly <PWS> for 2007. 

Figure 17(c) depicts the yearly variation of the first difference (fd(<PWS>)t). Runs testing 

indicates that the distribution of first differences is random (z = –0.59, cl <95%, sd = 1 kt). A comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 is found not to 

be statistically important (cl <90%). Hence, one would have expected the 10-yma of <PWS> for 

2006 to be about 72 ± 1 kt. As noted above, the 2011 season had <PWS> = 66.3 kt, thereby yielding the 10-yma of <PWS> = 72 kt for 2006 and fd = 0 kt for 2005. For 2007, one again anticipates 

the 10-yma of <PWS> = 72 ± 1 kt, indicating <PWS> >54.2 kt in 2012. (The 10-yma <PWS> has 

a minimum value of 68.3 kt for the year 2007, computed by assuming a frequency of zero NTC in 

2012.)

2.5.3 LP

Figure 18(a) displays the yearly variation of the LP (in mbar) for the interval 1945–2010. LP is 

defined as the lowest measured pressure for a tropical cyclone for the year. As an example, the storm 

with the lowest pressure in 1983 was Alicia, which had LP = 963 mbar. Thus, 963 mbar is the LP for 

1983, which is plotted in figure 18(a). The long-term mean is 938.3 mbar, having sd = 20.5 mbar and 

range 882 to 979 mbar (pressure and wind speed vary in the opposite sense, with lower pressures/

higher wind speeds indicative of stronger storms and higher pressures/lower wind speeds indicative 

of weaker storms). There appears to be no statistical difference in the means for the two intervals 

1945–1994 and 1995–2010, although the current, more active interval has a mean that is about 1% 

lower than the preceding interval (925.4 mbar as compared to 936.4 mbar). The highest (weakest) 

LP (979 mbar) occurred in 1986 (Earl), and the lowest (strongest) LP (882 mbar) occurred in 2005 

(Wilma). The peak 10-yma LP measured 949.1 mbar in 1950, and the lowest 10-yma LP measured 

922.1 mbar in 2003. (It is important to note that the measured pressures are incomplete for much 

of the early record, especially prior to the mid 1970s. Consequently, values of LP before the 1980s 

should not be considered reliable.)
36

First Difference (fd(LP)) –5

0

5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(LP)t

 = LP(10-yma)t+1 – LP(10-yma)t

 sd = 1.8

d(LP)t

 = LP(yearly)t – LP(10-yma)t

 sd = 19.3

Difference (d(LP))

0

–50

50

LP

1,000

950

900

850

1965 1975 1985 1995 2005

Year

(c)

(b)

(a)

1950–1989: mean = –0.168

sd = 1.625 

1990–2004: mean = –1.16

sd = 2.057

1945–2010

LP

⇒t = 1.873

⇒cl >90%

1945–1994: mean = 936.4

sd = 45.5

1995–2010: mean = 925.4

sd = 18.5

⇒t = 0.938 

⇒ cl <90%

mean = 938.3

sd = 20.5

range = 882–979

Figure 18. Yearly lowest pressure: (a) LP, (b) difference (d(LP)), and (c) first difference (fd(LP)).

Figure 18(b) shows the yearly variation of the difference (d(LP)t). Runs testing indicates that 

the distribution of differences is random (z = –0.25, cl <90%, sd = 19.3 mbar). Hence, one should 

have expected the 10-yma of LP = 955 ± 19.3 mbar in 2006, where 955 mbar is the yearly LP for 

2006. As it turns out, LP = 940 mbar in 2011, thereby yielding the 10-yma of LP = 924.4 mbar in 

2006, a value outside low the ±1 sd prediction interval. For 2007, based on the usual observed difference, one expects the 10-yma of LP = 907 ± 19.3 mbar, or LP <926.3 mbar, where 907 mbar is the 

yearly LP for 2007. 

Figure 18(c) depicts the yearly variation of the first difference (fd(LP)t). Runs testing indicates that the distribution of first differences is random (z = –1.13, cl <90%, sd = 1.8 mbar). A comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 is found to be of 

marginal statistically importance (cl >90%), with the current, more active interval having a mean first 

difference equal to –1.2 and sd of 2.1 mbar. Hence, one expected the 10-yma of LP for 2006 to be 

about 925 – 1.2 ± 2.1 mbar, or 923.8 ± 2.1 mbar. As noted above, the 2011 season had LP = 940 mbar, 

thereby yielding the 10-yma of LP = 924.4 mbar for 2006 (down from 925 mbar in 2005), inferring 

an fd = –0.6 mbar for 2005. For 2007, one anticipates the 10-yma of LP = 924.4 – 1.2 ± 2.1 mbar, 

or 923.2 ± 2.1 mbar, indicating LP <946 mbar in 2012. (The 10-yma LP has a minimum value of 

878 mbar for the year 2007, computed by assuming a frequency of zero NTC in 2012.)
37

2.5.4 <LP>

Figure 19(a) displays the yearly variation of the <LP> (in mbar) for the interval 1945–2010. 

<LP> is defined as the seasonal mean of the individual tropical cyclone lowest pressure. As an example, the four storms of 1983 had LP equal to 963 mbar (Alicia), 986 mbar (Barry), 994 mbar (Chantal), and 999 mbar (Dean), thus yielding a mean of 985.5 mbar, which is plotted in figure 19(a). The 

long-term mean is 979.2 mbar, having sd = 8.3 mbar and range 951.4 to 992.8 mbar. There appears 

to be no statistical difference in the means for the two intervals 1945–1994 and 1995–2010, although 

the current, more active interval has a mean that is lower than the preceding interval (978.7 mbar as 

compared to 979.3 mbar). The highest (weakest) <LP> (992.8 mbar) occurred in 1986, and the lowest (strongest) <LP> (951.4 mbar) occurred in 1955. The peak 10-yma <LP> measured 983.9 mbar 

in 1973 and 1982, and the lowest 10-yma <LP> measured 973.2 mbar in 1952, 1954, and 1958. First Difference (fd(<LP>))

–2.5

0

2.5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<LP>)t

 = <LP>(10-yma)t+1 – <LP>(10-yma)t

 sd = 0.8

d(<LP>)t

 = <LP>(yearly)t – <LP>(10-yma)t

 sd = 7.4

Difference (d(<LP>))

0

–25

25

<LP>

1,000

975

950

1965 1975 1985 1995 2005

Year (c)

(b)

(a)

1950–1989: mean = 0.245

sd = 0.733 

1990–2004: mean = –0.2

sd = 0.821

⇒t = 1.941

⇒cl >90%

1945–1994: mean = 979.324

sd = 8.731

1995–2010: mean = 978.706

sd = 7.045

⇒t = 0.257

⇒ cl <90%

mean = 979.2

sd = 8.3

range = 951.4–992.8

1945–2010

<LP>

Figure 19. Yearly lowest pressure seasonal mean: (a) <LP>, (b) difference (d<LP>),

and (c) first difference (fd<LP>). 

Figure 19(b) shows the yearly variation of the difference (d(<LP>)t). Runs testing indicates 

that the distribution of differences appears random (z = –0.8, cl <90%, sd = 7.4 mbar). Given that 

the distribution of differences appears random, one should have expected the 10-yma of <LP> 

= 984.7 ± 7.4 mbar for 2006, where 984.7 mbar is the yearly <LP> for 2006. As it turns out, <LP> 

= 984.2 mbar in 2011, thereby yielding the 10-yma of <LP> = 980.5 mbar in 2006. For 2007, based 

on the usual observed difference, one anticipates the 10-yma of <LP> = 986.1 ± 7.4 mbar, or <LP> 

<993.5 mbar, where 986.1 mbar is the yearly <LP> for 2007. 
38

Figure 19(c) depicts the yearly variation of the first difference (fd (<LP>)t). Runs testing indicates that the distribution of first differences is random (z = –1.67, cl <90%, sd = 0.8 mbar). A comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 is found to be only 

of marginal statistical importance (cl >90%). Hence, one should have expected the 10-yma of <LP> 

= 980.6 ± 0.8 mbar for 2006. As noted above, the 2011 season had <LP> = 984.2 mbar, thereby 

yielding the 10-yma of <LP> = 980.5 mbar for 2006 and fd = –0.1 mbar for 2005. For 2007, one 

again anticipates the 10-yma of <LP> = 980.5 ± 0.8 mbar, indicating <LP> <996.6 mbar in 2012. 

(The 10-yma <LP> has a minimum value of 931.5 mbar for the year 2007, computed by assuming 

a frequency of zero NTC in 2012.)

2.5.5 Correlation Behavior of LP and PWS and Between <LP> and <PWS>

Figure 20 shows the scatter plots of 10-yma values of (a) LP versus PWS and (b) <LP> versus 

<PWS>. In the figure, the filled circles correspond to the data for 1991–2005 and the filled squares 

correspond to the earlier data for 1950–1990. The inferred regressions (the diagonal lines) were 

determined using only the more recent 1991–2005 data. Plainly, very strong correlations (r >0.99) 

are inferred to exist between pressure and wind speed when using the 1991–2005 data, which is what 

one expects. However, there is an obvious lack of correlation, especially in figure 20(a), for most of 

the data prior to 1991. The lack of correlation is due to the unreliable pressure determinations for the 

earlier time span, due to the incompleteness of the pressure determination record, especially prior to 

the 1980s. Regarding figure 20(b), the earlier data suggest a possible correlation between the parameters, however, to the eye, the earlier data appears to be offset right to the shown inferred regression 

line. (Again, it is important to remember that the earlier record suffers from incompleteness in pressure determinations.). LP10-yma

920

925

930

935

940

945

950

<LP>10-yma

970

975

980

985

110 115 120 125 130 135 140

y (1991–2005) y (1991–2005)

y = 1094 – 1.277x

r = –0.998, r2 = 0.995

y = 1048.4 – 0.944x

 r = 0.99, r2 = 0.981

1950–1990

1991–2005

1950–1990

1991–2005

65 70 75 80 85

<PWS>10-yma PWS10-yma

(a) (b)

Figure 20. Scatter plots of 10-yma values: (a) LP versus PWS and (b) <LP> versus <PWS>.
39

2.6 Other Aspects of Tropical Cyclones

2.6.1 ACE

Figure 21(a) displays the yearly variation of the accumulated cyclone energy (ACE) for the 

interval 1945–2010. For an individual storm, ACE is defined as the sum of the square of the tropical cyclone’s maximum wind speed (multiplied by 10–4 kt–2) for each 6-hr period when the storm is 

classified as being either in the tropical cyclone stage or subtropical stage (i.e., when 6-hr wind speed 

is ≥34 kt; by definition, wind speeds during the extra-tropical stage are excluded in the computation of a storm’s ACE). Summing the individual storm ACEs yields the yearly or seasonal ACE, 

which is plotted in figure 21(a). As an example, the four storms of 1983 had individual ACEs of 

6.4 (Alicia), 3.1 (Barry), 4.3 (Chantal), and 3.6 (Dean), thus yielding the total of 17.4 for the yearly 

or seasonal ACE for 1983, which is plotted in figure 21(a). The long-term mean is 103.5, having sd

= 58.5 and range 17.4 to 250.3. A statistically important difference (cl >99.9%) in the means for the 

two intervals 1945–1994 and 1995–2010 is apparent, with the current, more active interval having

a mean that is more than 63% higher than the preceding interval (146.6 as compared to 89.7). The 

highest yearly ACE (250.3) occurred in 2005, and the lowest yearly ACE (17.4) occurred in 1983. 

The peak 10-yma ACE measured 159.7 in 2000, and the lowest 10-yma ACE measured 68.2 in 

1987. (Higher seasonal ACE values can be achieved by having more storms to occur in a season, 

storms with higher 6-hr peak wind speeds, and/or having storms that persist longer in the tropical/

subtropical cyclone stages.)

Figure 21(b) shows the yearly variation of the difference (d(ACE)t). Runs testing indicates 

that the distribution of differences appears random (z = 0.28, cl <90%, sd = 51.8). Given that the 

distribution of differences appears random, one should have expected the 10-yma of ACE = 78.5 

± 51.8 for 2006, where 78.5 is the yearly ACE for 2006. As it turns out, ACE = 127.6 in 2011 (down 

from 166.5 in 2010), thereby yielding the 10-yma of ACE = 144.6 in 2006 (up from 141.3 in 2005 

and about 11% higher than the upper limit of the ±1 sd prediction interval). For 2007, based on the 

usual observed difference, one anticipates the 10-yma ACE = 73.8 ± 51.8, or ≤125.6, where 73.8 is 

the yearly ACE for 2007.

Figure 21(c) depicts the yearly variation of the first difference (fd(ACE)t). Runs testing indicates that the distribution of first differences might be nonrandom (z = –2.16, cl >95%, sd = 5.5). 

A comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 is also 

found to be statistically important (cl >99.9%). Hence, one should have expected the 10-yma of ACE 

= 141.3 + 4.5 ± 7.1, or about 145.8 ± 7.1 for 2006, where 141.3 is the 10-yma value of ACE for 2005, 

4.5 is the mean of the current, more active interval, and 7.1 is the sd in the current, more active interval. As noted above, the 2011 season had ACE = 127.6, thereby yielding the 10-yma of ACE = 144.6 

for 2006 and fd = 3.3 for 2005. For 2007, one anticipates the 10-yma of ACE = 144.6 + 4.5 ± 7.1, or 

about 149.1 ± 7.1, indicating ACE >93 in 2012. (The 10-yma ACE has a minimum value of 137.4 for 

the year 2007, computed by assuming a frequency of zero NTC in 2012.)
40 First Difference (fd(ACE)) –10

–5

0

10

15

20

5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(ACE)t

 = ACE(10-yma)t+1 – ACE(10-yma)t

 sd = 5.5

d(ACE)t

 = ACE(yearly)t – ACE(10-yma)t

 sd = 51.8

1965 1975 1985 1995 2005

Year

(c)

(b)

1950–1989: mean = –1.033

sd = 3.992 

1990–2004: mean = 4.48

sd = 7.108

 Difference (d(ACE)) –150

–100

–50

150

100

50

0

(a) ACE

50

0

100

300

250

200

150

1945–2010

ACE

⇒t = –3.637

⇒cl >99.9%

mean = 103.5

sd = 58.5

range = 17.4–250.3

1945–1994: mean = 89.7

sd = 50.1

1995–2010: mean = 146.6

sd = 63.2

⇒t = –3.706

⇒ cl >99.9%

Figure 21. Yearly variation of accumulated cyclone energy: (a) ACE, (b) difference (d(ACE)), 

and (c) first difference (fd(ACE))
41

2.6.2 NSD

Figure 22(a) displays the yearly variation of the number of storm days (NSD) for the interval 1945–2010. For an individual storm, NSD is simply defined as the number of days when the 

storm was in the tropical cyclone stage or subtropical cyclone stage (i.e., when the 6-hr wind speed is 

≥34 kt; again, by definition, the extra-tropical stage wind speed days are excluded in the computation 

of NSD). Summing the individual storm NSDs yields the yearly or seasonal NSD, which is plotted 

in figure 22(a). As an example, the four storms of 1983 had individual NSDs of 2.75 days (Alicia), 

3 days (Barry), 4 days (Chantal), and 4 days (Dean), thus yielding the total of 13.75 days for 

the yearly or seasonal NSD for 1983, which is plotted in figure 22(a). The long-term mean is

55.71 days, having sd = 30.01 days and range 13.75 to 191.25 days. A statistically important difference 

(cl >99.9%) in the means for the two intervals 1945–1994 and 1995–2010 is apparent, with the 

current, more active interval having a mean that is about 75% longer than the preceding interval

(82.6 days as compared to 47.1 days). The longest yearly NSD (191.25 days) occurred in 2010, and 

the shortest yearly NSD (13.75 days) occurred in 1983. The peak 10-yma NSD measured 79.43 days 

in 2005, and the lowest 10-yma NSD measured 41.35 days in 1979 and 1982.

Figure 22(b) shows the yearly variation of the difference (d(NSD)t). Runs testing indicates 

that the distribution of differences appears random (z = 0.80, cl <90%, sd = 22 days). Given that the 

distribution of differences appears random, one should have expected the 10-yma of NSD = 63.75 

± 22 days for 2006, where 63.75 days is the yearly NSD for 2006. As it turns out, NSD = 91.5 days 

in 2011 (down from 191.25 days in 2010, the highest ever recorded), thereby yielding the 10-yma of 

NSD = 86.59 days in 2006 (up from 79.43 days in 2005, becoming the new record high, and about 1% 

higher than the upper limit of the ±1 sd prediction interval). For 2007, based on the usual observed 

difference, one anticipates the 10-yma of NSD = 38.25 ± 22 days, or ≤60.25 days, where 38.25 days 

is the yearly NSD for 2007. 

Figure 22(c) depicts the yearly variation of the first difference (fd(NSD)t). While runs testing indicates that the distribution of first differences appears to be random (z = –1.62, cl <90%,

sd = 2.16 days), a comparison of the difference of the means for the intervals 1950–1989 and 1990–

2004 finds that the difference in means is statistically important (cl >99.9%). Hence, one should 

have expected the 10-yma of NSD = 79.43 + 2.28 ± 2.42 days, or about 81.71 ± 2.42 days for 2006 

(using the mean and sd for the current, more active interval). As noted above, however, the 2011 

season actually had NSD = 91.5 days (down from the record number of 191.25 days experienced 

in 2010), thereby yielding the 10-yma of NSD = 86.59 days for 2006 (up from 79.43 days in 2005 

and becoming the new record high) and fd = 7.16 days for 2005 (also a record high), about 3% 

higher than the upper limit of the ±1 sd prediction interval. For 2007, one anticipates the 10-yma of

NSD = 86.59 + 2.28 ± 2.42 days, or about 88.87 ± 2.42 days, inferring NSD >31 days in 2012. 

(The 10-yma NSD has a minimum value of 84.9 days for the year 2007, computed by assuming a

frequency of zero NTC in 2012.)
42

First Difference (fd(NSD)) –5

0

5

10

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NSD)t

 = NSD(10-yma)t+1 – NSD(10-yma)t

 sd = 2.16

d(NSD)t

 = NSD(yearly)t – NSD(10-yma)t

 sd = 22.0

Difference (d(NSD)) –25

0

–50

25

50

1965 1975 1985 1995 2005

Year

(c)

(b)

1945–2010

NSD

NSD

50

0

100

150

200

(a)

1950–1989: mean = –0.250

sd = 1.609 

1990–2004: mean = 2.280

sd = 2.418

⇒t = –4.499

⇒cl >99.9%

1945–1994: mean = 47.105

sd = 19.391

1995–2010: mean = 82.609

sd = 40.691

⇒t = –4.754 

⇒ cl >99.9%

mean = 55.71

sd = 30.01

range = 13.75–191.25

2.6.3 NHD

Figure 23(a) displays the yearly variation of the number of hurricane days (NHD) for the 

interval 1945–2010. For an individual storm, NHD is simply defined as the number of days when the 

storm was in the tropical cyclone stage or subtropical cyclone stage and its maximum sustained wind 

speed exceeded 63 kt (i.e., when the peak 6-hr wind speed is ≥64 kt; again, by definition, the extratropical stage wind speed days are excluded in the computation of NHD). Summing the individual 

storm NHDs yields the yearly or seasonal NHD, which is plotted in figure 23(a). As an example, the 

four storms of 1983 had individual NHDs of 1.75 days (Alicia), 0.5 days (Barry), 1.25 days (Chantal), and 0 days (Dean), thus yielding the total of 3.5 days for the yearly or seasonal NHD for 1983, 

which is plotted in figure 23(a). The long-term mean is 24.62 days, having sd = 14.44 days and range 

3.5 to 61.25 days. A statistically important difference (cl >98%) in the means for the two intervals 

Figure 22. Yearly storm days: (a) NSD, (b) difference (d(NSD)),

and (c) first difference (fd(NSD)).
43

First Difference (fd(NHD)) Difference (d(NHD)) –4

–2

0

2

4

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(NHD)t

 = NHD(10-yma)t+1 – NHD(10-yma)t

 sd = 1.38

d(NHD)t = NHD(yearly)t

 – NHD(10-yma)t

 sd = 13.42

NHD

0

0

25

–25

25

50

1965 1975 1985 1995 2005

Year (c)

(b)

(a)

1950–1989: mean = –0.265

sd = 1.144 

1990–2004: mean = 0.647

sd = 1.755

⇒t = –2.26

⇒cl >95%

1945–1994: mean = 22.22

sd = 13.186 

1995–2010: mean = 32.109

sd = 16.022

⇒t = –2.476

⇒cl >98%

mean = 24.62

sd = 14.44

range = 3.50 – 61.25

1945–2010

NHD

1945–1994 and 1995–2010 is apparent, with the current, more active interval having a mean that 

is about 45% longer than the preceding interval (32.1 days as compared to 22.2 days). The longest 

yearly NHD (61.25 days) occurred in 1995, and the shortest yearly NHD (3.5 days) occurred in 

1983. The peak 10-yma NHD measured 34.46 days in 2000, and the lowest 10-yma NHD measured 

15.63 days in 1987.

Figure 23(b) shows the yearly variation of the difference (d (NHD)t). Runs testing indicates 

that the distribution of differences appears random (z = 0.27, cl <90%, sd = 13.42 days). Given 

that the distribution of differences appears random, one should have expected the 10-yma of NHD 

= 21.25 ± 13.42 days for 2006, where 21.25 days is the yearly NHD for 2006. As it turns out, NHD 

= 26 days in 2011 (down from 38.5 days in 2010), thereby yielding the 10-yma of NHD = 27.68 days 

in 2006 (up from 27.36 days in 2005). For 2007, based on the usual observed difference, one anticipates the 10-yma of NHD = 12.25 ± 13.42 days, or ≤25.67 days, where 12.25 days is the yearly NHD 

for 2007. 

Figure 23. Yearly hurricane days: (a) NHD, (b) difference (d (NHD)),

and (c) first difference (fd(NHD)). 
44

Figure 23(c) depicts the yearly variation of the first difference (fd(NHD)t). Both runs testing 

of the distribution of first differences and the difference in means between the intervals 1950–1989 

and 1990–2004 suggest a nonrandom distribution in the first differences of NHD (i.e., z = –2.21, 

cl >95%, sd = 1.38; and t = –2.26 and cl >95%). Hence, one should have expected the 10-yma of 

NHD = 27.36 + 0.65 ± 1.76 days, or about 28.01 ± 1.76 days for 2006 (using the mean and sd for the 

current, more active interval). As noted above, the 2011 season actually had NHD = 26 days (down 

from 38.5 days experienced in 2010), thereby yielding the 10-yma of NHD = 27.68 days for 2006 (up 

from 27.36 days in 2005) and fd = 0.32 days for 2005. For 2007, one anticipates the 10-yma of NHD 

= 27.68 + 0.65 ± 1.76 days, or about 28.33 ± 1.76 days, inferring NHD ≥ 0 days in 2012 (perhaps as 

many as 58 days, the upper limit of the ±1 sd prediction interval). (The 10-yma NHD has a minimum 

value of 27.21 days for the year 2007, computed by assuming a frequency of zero NTC in 2012.)

2.6.4 NMHD

Figure 24(a) displays the yearly variation of the number of major hurricane days (NMHD) 

for the interval 1945–2010. For an individual storm, NMHD is simply defined as the number of days 

when the storm was in the tropical cyclone stage or subtropical cyclone stage and its maximum sustained wind speed exceeded 95 kt (i.e., when the peak 6-hr wind speed is ≥96 kt; again, by definition, 

the extra-tropical stage wind speed days are excluded in the computation of NMHD). Summing the 

individual storm NMHDs yields the yearly or seasonal NMHD, which is plotted in figure 24(a). As 

an example, of the four storms of 1983, only Alicia attained major hurricane status and then only 

briefly for one 6-hr period; hence NMHD = 0.25 day for1983, which is plotted in figure 24(a). The 

long-term mean is 6.23 days, having sd = 5.68 days and range 0 to 24.5 days. A statistically important 

difference (cl >98%) in the means for the two intervals 1945–1994 and 1995–2010 is apparent, with 

the current, more active interval having a mean that is about 77% longer than the preceding interval 

(5.25 days as compared to 9.3 days). The longest yearly NMHD (24.5 days) occurred in 1961, and the 

shortest yearly NMHD (0 days) occurred in 1968, 1972, 1986, and 1994. The peak 10-yma NMHD 

measured 10.43 days in 2000, and the lowest 10-yma NMHD measured 1.9 days in 1973.

Figure 24(b) shows the yearly variation of the difference (d (NMHD)t). Runs testing indicates 

that the distribution of differences appears random (z = –0.15, cl <90%, sd = 5.05 days). Given that 

the distribution of differences appears random, one should have expected the 10-yma of NMHD 

= 2 ± 5.05 days for 2006, where 2 days is the yearly NMHD for 2006. As it turns out, NMHD 

= 4.5 days in 2011 (down from 11 days in 2010), thereby yielding the 10-yma of NMHD = 9.39 days 

in 2006 (up from 9.08 days in 2005). For 2007, based on the usual observed difference, one anticipates 

the 10-yma of NHD = 6 ± 5.05 days, or ≤11.05 days, where 6 days is the yearly NMHD for 2007. 

Figure 24(c) depicts the yearly variation of the first difference (fd(NMHD)t). Both runs 

testing of the distribution of first differences and the difference in means between the intervals 

1950–1989 and 1990–2004 suggest a nonrandom distribution in the first differences of NMHD (i.e., 

z = –2.27, cl >95%, sd = 0.58; and t = –3.07 and cl >99.5%). Hence, one should have expected 

the 10-yma of NMHD = 9.08 + 0.38 ± 0.69 days, or about 9.46 ± 0.69 days for 2006 (using the 

mean and sd for the current, more active interval). As noted above, the 2011 season actually had 

NMHD = 4.5 days (down from 11 days experienced in 2010), thereby yielding the 10-yma of NMHD 

= 9.39 days for 2006 (up from 9.08 days in 2005) and fd = 0.31 day for 2005. For 2007, one anticipates the 10-yma of NMHD = 9.39 + 0.38 ± 0.69 days, or about 9.77 ± 0.69 days, inferring NMHD 
45

First Difference (fd(NMHD))

–2

–1.5

–1

0

0.5

1

1.5

2

–0.5

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

(c)

(b)

(a)

fd(NMHD)t

 = NMHD(10-yma)t+1 – NMHD(10-yma)t

 sd = 0.58

d(NMHD)t

 = NMHD(yearly)t – NMHD(10-yma)t

 sd = 5.05

1950–1989: mean = –0.119

sd = 0.473 

1990–2004: mean = 0.382

sd = 0.69

⇒t = –3.071

⇒cl >99.5%

Difference (d(NMHD)) –10

–5

0

10

15

20

25

5

NMHD

5

0

10

20

25

15

1945–2010

NMHD 1945–1994: mean = 5.250

sd = 5.207 

1995–2010: mean = 9.297

sd = 6.156

⇒t = –2.588 

⇒cl >98%

mean = 6.23

sd = 5.68

range = 0–24.5

 

Figure 24. Yearly major hurricane days: (a) NMHD, (b) difference (d(NMHD)), 

and (c) first difference (fd(NMHD)).
46

≥ 0 days in 2012 (perhaps as many as 24 days, the upper limit of the ±1 sd prediction interval). (The 

10-yma NMHD has a minimum value of 9.25 days for the year 2007, computed by assuming a frequency of zero NTC in 2012.)

2.6.5 NTCA

Figure 25(a) displays the yearly variation of the net tropical cyclone activity (NTCA) for 

the interval 1945–2010. NTCA is a yearly or seasonal parameter rather than an individual storm 

parameter, developed by Colorado State University to provide a simple comparison to the average seasonal tropical cyclone activity based on 1950–2000 parametric averages. To determine the 

NTCA, one needs the values of NTC, NSD, NH, NHD, NMH, and NMHD. A convenient calculator for determining NTCA is available online at <http://einstein.atmos.colostate.edu/~mcnoldy/tropics/NTC.html>. As an example, the 1983 season had NTC = 4, NH = 3, NMH = 1, NSD = 13.75 

days, NHD = 3.5 days, and NMHD = 0.25 day. Entering these data into the online calculator yields 

NTCA = 30.5% for the 1983 season, meaning that in comparison to the average seasonal activity for 

1950–2000, the 1983 season was only about 30% as active. 

The long-term mean of NTCA for the interval 1945–2010 is 112.6%, having sd = 59.3% and 

range 30.5% to 278.3%. A statistically important difference (cl >98%) in the means for the two intervals 1945–1994 and 1995–2010 is apparent, with the current, more active interval having a mean that 

is about 59% higher than the preceding interval (98.6% as compared to 156.5%). The highest yearly 

NTCA (278.3%) occurred in 2005, and the least yearly NTCA (30.5%) occurred in 1983. The peak 

10-yma NTCA measured 160.5% in 2000, and the lowest 10-yma NTCA measured 75.5% in 1987. 

(The peak 10-yma NTCA value of 160.5% measured in 2000 is about 18% higher than the earlier 

peak 10-yma NTCA value of 136.1% measured in 1954.) 

Figure 25(b) shows the yearly variation of the difference (d(NTCA)t). Runs testing indicates 

that the distribution of differences appears random (z = –0.21, cl <90%, sd = 53.1%). Given that the 

distribution of differences appears random, one should have expected the 10-yma of NTCA = 88.7% 

± 53.1% for 2006, where 88.7% is the yearly NTCA for 2006. As it turns out, NTCA = 145.5% in 

2011 (down from 230.9% in 2010), thereby yielding the 10-yma of NTCA = 156.1% in 2006 (up from 

150.7% in 2005), which is about 10% higher than the upper limit of the ±1 sd prediction interval 

based on the usual observed difference. For 2007, based on the usual observed difference, one anticipates the 10-yma of NTCA = 98.8% ± 53.1%, or ≤151.9%, where 98.8% is the yearly NTCA for 2007. 

Figure 25(c) depicts the yearly variation of the first difference (fd(NTCA)t). While runs testing of the distribution of first differences indicates a nonrandom distribution of only marginal statistical importance (z = –1.71, cl >90%, sd = 5.1%), in contrast, the difference in means between the 

intervals 1950–1989 and 1990–2004 strongly suggests a nonrandom distribution of the first differences (t = –4.38, cl >99.9%). Hence, one should have expected the 10-yma of NTCA = 150.7% + 4.7% 

± 6.3%, or about 155.4% ± 6.3% for 2006 (using the mean and sd for the current, more active interval). As noted above, the 2011 season actually had NTCA = 145.5% (down from 230.9% experienced 

in 2010), thereby yielding the 10-yma of NTCA = 156.1% for 2006 (up from 150.7% in 2005) and 

fd = 5.4% for 2005. For 2007, one anticipates the 10-yma of NTCA = 156.1% + 4.7% ± 6.3%, or about 

160.8% ± 6.3%, inferring NTCA ≥ 41.2% in 2012 (perhaps as high as 293.2%, the upper limit of the 
47

First Difference (fd(NTCA)) –10

–5

0

10

15

20

5

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

(c)

(b)

(a)

1950–1989: mean = –1.198

sd = 3.567 

1990–2004: mean = 4.687

sd = 6.266

fd(NTCA)t = NTCA(10-yma)t+1 – NTCA(10-yma)t

 sd = 5.1

1945–2010

NTCA

⇒t = –4.376

⇒cl >99.9%

Difference (d(NTCA)) –100

–50

0

100

150

50

1945–1994: mean = 98.568

sd = 50.056 

1995–2010: mean = 156.525

sd = 66.01

d(NTCA)t

 = NTCA(yearly)t – NTCA(10-yma)t

 sd = 53.1

NTCA

50

0

100

200

300

250

150

⇒t = –3.722

⇒cl >99.9%

mean = 112.6

sd = 59.3

range = 30.5–278.3

Figure 25. Yearly tropical cyclone activity: (a) NTCA, (b) difference (d(NTCA)),

and (c) first difference (fd(NTCA)). 
48

±1 sd prediction interval). (The 10-yma NTCA has a minimum value of 152.4% for the year 2007, 

computed by assuming a frequency of zero NTC in 2012.)

2.6.6 ACE/NSD

Figure 26(a) displays the yearly variation of the ratio of ACE to NSD for the interval 1945–

2010. The long-term mean is 1.83, having sd = 0.45 and range 0.93 to 2.98. While the difference in 

the means for the two time intervals 1945–1994 and 1995–2010 does not appear to be statistically 

important (t = –0.14, cl <90%), noticeable is that the 10-yma of ACE/NSD is always above the mean 

during the interval prior to 1968, always below the mean during the interval 1968–1997, and now 

is once again above the mean, at least through 2005. Overall, the highest yearly ACE/NSD (2.98) 

occurred in 1960, and the lowest yearly ACE/NSD (0.93) occurred in 1987. The highest yearly ACE/

NSD during the current, more active interval measures 2.88 in 2002, and the lowest yearly ACE/

NSD during the current, more active interval measures 0.98 in 2010. Overall, the highest 10-yma of 

ACE/NSD (2.27) occurred in 1962, and lowest 10-yma of ACE/NSD (1.55) occurred in 1973. During 

the current, more active interval, the peak 10-yma of ACE/NSD measured 2.01 in 2000 (about 11% 

smaller than the overall peak of 2.27), and the lowest 10-yma of ACE/NSD measures 1.69 in 1995. 

(The 10-yma values of ACE/NSD appear to be trending downward since 2000, measuring 1.85 in 

2005.) 

Figure 26(b) shows the yearly variation of the difference (d (ACE/NSD)t). Runs testing indicates that the distribution of differences appears random (z = 1.33, cl <90%, sd = 0.36). Given that 

the distribution of differences appears random, one should have expected the 10-yma of ACE/NSD 

= 1.23 ± 0.36 for 2006, where 1.23 is the yearly ACE/NSD for 2006. As it turns out, ACE/NSD = 1.39 

in 2011 (up from 0.98 in 2010), thereby yielding the 10-yma of ACE/NSD = 1.81 in 2006 (down from 

1.85 in 2005 and about 14% higher than the upper limit of the ±1 sd prediction interval). For 2007, 

based on the usual observed difference, one anticipates the 10-yma of ACE/NSD = 1.93 ± 0.39, or 

<2.32, where 1.93 is the yearly ACE/NSD for 2007.

Figure 26(c) depicts the yearly variation of the first difference (fd(ACE/NSD)t). Runs testing indicates that the distribution of first differences appears nonrandom (z = –3.70, cl >99.9%, 

sd = 0.05). A comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 

is also found to be statistically important (cl >95%). Hence, one should have expected the 10-yma 

of ACE/NSD = 1.85 + 0.02 + ± 0.05, or about 1.87 ± 0.05 for 2006, where 1.85 is the 10-yma value 

of ACE/NSD for 2005, 0.02 is the mean of the current, more active interval, and 0.05 is the sd in 

the current, more active interval. As noted above, the 2011 season had ACE/NSD = 1.39, thereby 

yielding the 10-yma of ACE/NSD = 1.81 for 2006 and fd = –0.04 for 2005. For 2007, one anticipates 

the 10-yma of ACE/NSD = 1.81 + 0.02 ± 0.05, or about 1.83 ± 0.05, indicating ACE/NSD >2.54 in 

2012. (The 10-yma ACE/NSD has a minimum value of 1.65 for the year 2007, computed by assuming a frequency of zero NTC in 2012.)

The ratio of ACE/NSD becomes larger if the rate of change in ACE is greater than the rate 

of change in NSD, and it becomes smaller if the rates are reversed. So, a yearly value of ACE/NSD 

= 2.54 in 2012 means the 10-yma of ACE/NSD = 1.78 for 2007 and suggests a continuing downward 

progression of the 10-yma values of ACE/NSD. For the downward trend in the 10-yma of ACE/
49

First Difference (fd(ACE/NSD))

–1.5

–1

–.05

.05

1

 0

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

(c)

(b)

(a)

1950–1989: mean = –0.011

sd = 0.046 

1990–2004: mean = 0.019

sd = 0.047

fd(ACE/NSD)t

 = ACE/NSD(10-yma)t+1 – ACE/NSD(10-yma)t

 sd = 0.05

⇒t = –2.142

⇒cl >95%

Difference (d(ACE/NSD))

–1

–.5

0

1

.5

d(ACE/NSD)t

 = ACE/NSD(yearly)t – ACE/NSD(10-yma)t

 sd = 0.36

ACE/NSD

1

1.5

2

3

2.5

1945–2010

ACE/NSD

mean = 1.83

sd = 0.45

range = 0.93–2.98

1945–1994: mean = 1.823

sd = 0.451 

1995–2010: mean = 1.841

sd = 0.469

⇒t = –0.138 

⇒cl <90%

NSD to reverse, the yearly ratio ACE/NSD for 2012 would have to measure ≥3.14, a value never seen 

before. Therefore, it appears likely that the 10-yma ratio of ACE/NSD will continue to decrease with 

time, with the first difference of ACE/NSD continuing to be negative.

Figure 26. Yearly variation of the ratio: (a) ACE/NSD (b) difference (d(ACE/NSD)),

and (c) first difference (fd(ACE/NSD)). 
50

2.6.7 HISACE

Figure 27(a) displays the yearly variation of the highest individual storm accumulated cyclone 

energy (HISACE) for the interval 1945–2010. Recall that ACE is defined as the sum of the square of 

the tropical cyclone’s maximum wind speed (multiplied by 10–4 kt–2) for each 6-hr period when the 

storm is classified as being either in the tropical cyclone stage or subtropical stage (i.e., when 6-hr 

wind speed is ≥34 kt; by definition, wind speeds during the extra-tropical stage are excluded in the 

computation of a storm’s ACE). The highest observed individual storm ACE during a hurricane 

season by definition is HISACE. As an example, the four storms of 1983 had individual ACEs of 

6.4 (Alicia), 3.1 (Barry), 4.3 (Chantal), and 3.6 (Dean). The storm with the highest ACE was Alicia 

and its value of 6.4 is plotted as HISACE for 1983 in figure 27(a). The long-term mean is 32.8, having sd = 16.1 and range 6.4 to 70.4. A marginally statistically important difference (cl >90%) in the 

means for the two intervals 1945–1994 and 1995–2010 is apparent, with the current, more active 

interval having a mean that is more than 28% higher than the preceding interval (39.2 as compared 

to 30.7). The highest yearly HISACE (70.4) occurred in 2004 (Ivan), and the lowest yearly HISACE 

(6.4) occurred in 1983 (Alicia). The peak 10-yma HISACE measured 44.1 in 1962, and the lowest 

10-yma HISACE measured 21.4 in 1986 and 1987. Interestingly, the 10-yma of HISACE is above 

the mean during the interval of 1950–1968, below the mean during the interval 1969–1997, and now 

once again is above the mean during the current interval 1998–2005. The peak 10-yma of HISACE 

in the current, more active interval (41.4) may have occurred in 2000, measuring about 6% smaller 

than the peak (44.1) in 1962. 

Figure 27(b) shows the yearly variation of the difference (d(HISACE)t). Runs testing indicates that the distribution of differences appears random (z = 0.32, cl <90%, sd = 14.3). Given that 

the distribution of differences appears random, one should have expected the 10-yma of HISACE 

= 24.3 ± 14.3 for 2006, where 24.3 (Helene) is the yearly HISACE for 2006. As it turns out, 

HISACE = 27 (Katia) in 2011 (down from 41.9, Igor, in 2010), thereby yielding the 10-yma of 

HISACE = 38.2 in 2006 (up from 37.6 in 2005, but within the ±1 sd prediction interval). For 2007, 

based on the usual observed difference, one anticipates the 10-yma of HISACE = 35.2 ± 14.3, or 

≤49.5, where 35.2 (Dean) is the yearly HISACE for 2007.

Figure 27(c) depicts the yearly variation of the first difference (fd(HISACE)t). Both runs 

testing and the difference in means for the two intervals 1950–1989 and 1990–2004 indicate that 

the distribution of first differences appears to be nonrandom and statistically important (z = –3.30, 

cl >99.8%, sd = 1.6, and t = –2.53, cl >98%, respectively). Hence, one should have expected the 

10-yma of HISACE = 37.6 + 0.9 ± 1.8, or about 38.5 ± 1.8 for 2006, where 37.6 is the 10-yma value 

of HISACE for 2005, 0.9 is the mean of the current, more active interval, and 1.8 is the sd in the current, more active interval. As noted above, the 2011 season had HISACE = 27, thereby yielding the 

10-yma of HISACE = 38.2 for 2006 and fd = 0.6 for 2005. For 2007, one anticipates the 10-yma of 

ACE = 38.2 + 0.9 ± 1.8, or about 39.1 ± 1.8, indicating HISACE <65.6 in 2012 (the upper limit of 

the ±1 sd prediction interval). (The 10-yma HISACE has a minimum value of 37.6 for the year 2007, 

computed by assuming a frequency of zero NTC in 2012.)
51

First Difference (fd(HISACE)) –5

5

0

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

(c) Year

(b)

1950–1989: mean = –0.288

sd = 1.456 

1990–2004: mean = 0.9

sd = 1.792

 Difference (d(HISACE)) –25

0

25

d(HISACE)t

 = HISACE(yearly)t – HISACE(10-yma)t

 sd = 14.3

fd(HISACE)t

 = HISACE(10-yma)t+1 – HISACE(10-yma)t

 sd = 1.6

(a)

HISACE

25

0

50

75

100

1945–2010

HISACE

⇒t = –2.529

⇒cl >98%

1945–1994: mean = 30.718

sd = 16.092

1995–2010: mean = 39.175

sd = 14.638

⇒t = –1.868

⇒ t >90%

mean = 32.8

sd = 16.1

range = 6.4–70.4

Figure 27. Yearly variation of individual storm cyclone energy: (a) HISACE, (b) difference 

(d (HISACE)), and (c) first difference (fd(HISACE)).

2.6.8 LISNSD

Figure 28(a) displays the yearly variation of the longest individual storm number of storm 

days (LISNSD) for the interval 1945–2010. For an individual storm, NSD is simply defined as the 

number of days when the storm was in the tropical cyclone stage or subtropical cyclone stage (i.e., 

when the 6-hr wind speed is ≥34 kt; again, by definition, the extra-tropical stage wind speed days are 

excluded in the computation of NSD). The longest observed individual storm NSD during a hurricane season by definition is LISNSD. As an example, the four storms of 1983 had individual NSDs 

of 2.75 days (Alicia), 3 days (Barry), 4 days (Chantal), and 4 days (Dean). The storms with the longest NSD were Chantal and Dean, both having NSD = 4 days, and it is this value (4) that is plotted 

as LISNSD for 1983 in figure 28(a). The long-term mean is about 11.5 days, having sd = 3.6 days and 
52

First Difference (fd(LISNSD))

–1

–0.5

0

1

0.5

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

(c)

(b)

 Difference (d(LISNSD))

–5

–10

0

5

10 d(LISNSD)t

 = LISNSD(yearly)t – LISNSD(10-yma)t

 sd = 3.25

fd(LISNSD)t

 = LISNSD(10-yma)t+1 – LISNSD(10-yma)t

 sd = 0.32

(a)

 LISNSD

5

0

10

15

20

25 1945-2010

LISNSD

1950–1989: mean = 0.001

sd = 0.324 

1990–2004: mean = 0.138

sd = 0.31

1945–1994: mean = 11

sd = 3.713

1995–2010: mean = 12.891

sd = 2.928

⇒t = –1.981 

⇒ cl >90%

mean = 11.46

sd = 3.61

range = 3.75–21.25

range 3.75 to 21.25 days. Although the difference in the means for the two intervals 1945–1994 and 

1995–2010 is marginally statistically important, it seems noteworthy that the current, more active 

interval has a mean that is about 17% longer than the preceding interval (12.9 days as compared to 

11 days). The longest yearly LISNSD (21.25 days) occurred in 1971 (Ginger), and the shortest yearly 

LISNSD (3.75 days) occurred in 1946 (2 unnamed storms). The peak 10-yma LISNSD measured 

13.66 days in 2000, and the lowest 10-yma LISNSD measured 9.3 days in 1981.

Figure 28. Yearly variation of individual storm storm days: (a) LISNSD, (b) difference 

(d(LISNSD)), and (c) first difference (fd(LISNSD)).
53

Figure 28(b) shows the yearly variation of the difference (d(LISNSD)t). Runs testing indicates 

that the distribution of differences appears random (z = 0.28, cl <90%, sd = 3.25 days). Given that 

the distribution of differences appears random, one should have expected the 10-yma of LISNSD 

= 10.75 ± 3.25 days for 2006, where 10.75 days is the yearly LISNSD for 2006. As it turns out, 

LISNSD = 13.75 days (Philippe) in 2011 (down from 12.25 days, Igor, in 2010), thereby yielding the 

10-yma of LISNSD = 12.51 days in 2006 (down from 12.73 days in 2005). For 2007, based on the 

usual observed difference, one anticipates the 10-yma of LISNSD = 8.5 ± 3.25 days, or ≤11.75 days, 

where 8.5 days (Dean) is the yearly LISNSD for 2007. 

Figure 28(c) depicts the yearly variation of the first difference (fd(LISNSD)t). Although runs 

testing indicates that the distribution of first differences appears nonrandom (z = –2.58, cl >98%, 

sd = 0.32), a comparison of the difference of the means for the intervals 1950–1989 and 1990–2004 

suggests that the difference in means is not statistically important (t = –1.13, cl <90%). Hence, one 

should have expected the 10-yma of LISNSD = 12.73 ± 0.32 days for 2006, where 12.73 days is 

the LISNSD for 2005 and 0.32 is the sd of the first difference. As noted above, the 2011 season 

actually had LISNSD = 13.75 days (up from 12.25 days in 2010), thereby yielding the 10-yma of 

LISNSD = 12.51 days for 2006 and fd = –0.22 days for 2005, within the ±1 sd prediction interval. 

For 2007, one anticipates the 10-yma of LISNSD = 12.51 ± 0.32 days, inferring LISNSD >7.55 days 

in 2012 (perhaps as long as 20.35 days, the upper limit of the ±1 sd prediction interval). (The 10-yma 

LISNSD has a minimum value of 11.81 days for the year 2007, computed by assuming a frequency 

of zero NTC in 2012.)

2.7 Surface Air Temperature and ENSO-Related Parameters

Physically, one expects the systematic variations found in the tropical cyclone parametric 

values during the interval 1945–2010 (shown in the previous summary charts) to be directly related 

to physical changes in the environment where the tropical cyclones are birthed and grow. In this section, the yearly variations in surface air temperature recorded at the Armagh Observatory (<AT>) 

and a number of ENSO-related parameters for the same interval 1945–2010 are investigated. The 

ENSO-related parameters examined herein include the Oceanic Niño index (ONI), Southern Oscillation index (SOI), North Atlantic Oscillation (NAO) index, Pacific Decadal Oscillation (PDO) index, 

Trans-Niño index (TNI), Multivariate ENSO index (MEI), Global Sea Surface Temperature (SST) 

ENSO index (GSSTEI), Japan Meteorological Agency SST Mean (JMASSTM) index, North Tropical Atlantic (NTA) index, Caribbean (CAR) index, Quasi-Biennial Oscillation (QBO) index, Atlantic 

Multidecadal Oscillation (AMO) index, and Atlantic Meridional Mode (AMM) index. Tables 16–19 

(see appendix) provide the yearly means, 10-yma values, differences, and first differences of these 

parameters for the interval 1945–2010. Each parameter will be discussed appropriately in the following subsections.

Monthly values of ONI provide a convenient means for determining the occurrences of ENSO 

anomalies – El Niño (EN) (warm) and La Niña (LN) (cool) events, where an El Niño is said to be 

occurring when the monthly ONI anomaly is 0.5 °C or warmer for at least 5 consecutive months and 

a La Niña is said to be occurring when the monthly ONI anomaly is –0.5 °C or cooler for at least 

5 consecutive months. When neither anomaly is occurring, the ENSO condition is described as being 

ENSO neutral. During the interval 1950–2010, based on monthly ONI values, some 32 anomalous 
54

periods can be discerned, consisting of 18 EN and 14 LN events, with EN events averaging about 

10 mo in duration and LN events averaging about 15 mo in duration. On average, the recurrence rate 

for EN events is about 40.5 mo (i.e., the elapsed time in months between starts of EN events), having 

sd = 18.7 mo and range 10 to 75 mo, while, on average, the recurrence rate for LN events is about 

56.3  mo, having sd = 36.9 mo and range 19 to 137 mo.30,34

Table 20 (see appendix) gives the tropical cyclone parametric means and standard deviations 

for NTC, NTS, NH, NMH, NUSLFH, LAT, LONG, PWS, <PWS>, ACE, NSD, and NTCA based 

on the yearly ENSO phase condition, where a year is considered EN-related when an EN event was 

operative for at least 4 mo during the nominal 6-mo hurricane season, LN-related when a LN event 

was operative at least 4 mo during the 6-mo nominal hurricane season, and ENSO neutral when 

neither an EN nor LN event was operative during the nominal 6-mo hurricane season. On this basis, 

there were 16 EN-related years (ENY), 15 LN-related years (LNY), and 35 ENSO neutral years 

(NY) during the interval 1945–2010. Inspection of table 20 reveals that, on average, every frequency 

and strength parameter is higher when the year is classified as an LNY or NY than when the year is 

classified an ENY. Likewise, the position of the centroids is found to be more tropically located and 

closer to the US during years classified as LNY and NY than during years classified as ENY. Similar 

results are also found on the basis of simply grouping the years by the sign of the yearly <ONI> (i.e., 

<ONI> ≥0 or <ONI> <0). For the 31 negative-valued <ONI> years, on average, both the frequency 

and strength of the tropical cyclones are above long-term means as compared to the 30 positivevalued <ONI> years. Likewise, the storms, on average, are more tropically located and closer to the 

US when the yearly <ONI> is negative in value than when it is positive in value. On this basis, one 

should expect both the frequency and strength of the tropical cyclones to be either above long-term 

means during 2012 if the yearly <ONI> in 2012 is negative in value, or below long-term means if the 

yearly <ONI> in 2012 is positive in value. (LN events have been associated with increased frequency 

of landfalling hurricanes along the US coastline and increased damage.35–40)

Similarly, table 21 (see appendix) gives the Poisson probabilities for the frequencies of NTC, 

NTS, NH, NMH, and NUSLFH for different ENSO phase conditions (ENY, LNY, and NY). 

Plainly, when the year is described as an ENY, on average, the frequencies of NTC, NTS, NH, NMH, 

and NUSLFH are all lower in comparison to when the year is described as a LNY or NY. For ENY, 

one expects NTC = 9 ± 2 (59.5%), NTC <7 (19.5%), and NTC >11 (21%); NTS = 4 ± 2 (78.3%), NTS 

<2 (7.1%), and NTS >6 (14.5%); NH = 4 ± 2 (74.2%), NH <2 (4.7%), and NH >6 (21.1%); NMH 

= 2 ± 1 (72.2%), NMH = 0 (13.5%), and NMH >3 (14.3%); and NUSLFH = 1 ± 1 (89.4%) and 

NUSLFH >2 (10.6%). For LNY, NTC = 11 ± 2 (53.8%), NTC <9 (25.8%), and NTC >13 (20.4%); 

NTS = 4 ± 2 (75.6%), NTS <2 (5.3%), and NTS > 6 (19.1%); NH = 7 ± 2 (65.8%), NH <5 (17.3%), and 

NH > 9 (17%); NMH = 3 ± 1 (59.2%), NMH <2 (13.9%), and NMH >4 (26.9%); and NUSLFH = 2 

± 1 (70.9%), NUSLFH = 0 (11.1%), and NUSLFH >3 (18.1%). For NY, NTC = 11 ± 2 (54.7%), 

NTC <9 (23.8%), and NTC >13 (21.6%); NTS = 4 ± 2 (74.6%), NTS <2 (4.9%), NTS >6 (20.5%); NH = 6 

± 2 (68%), NH <4 (11.3%), and NH >8 (20.7%); NMH = 2 ± 1 (64.5%), NMH = 0 (6.7%), and NMH 

>3 (28.8%); and NUSLFH = 1 ± 1 (77.6%), and NUSLFH >2 (22.4%).

Table 22 (see appendix) gives a comparison of the means and sds for <AT> and the ENSOrelated parameters based on the yearly ENSO phase condition as determined using ONI, similar in 

construction to table 20. Table 23 (see appendix) gives Poisson probabilities for the frequencies of 
55

NTC, NTS, NH, NMH, and NUSLFH for each of the <AT> and ENSO-related parameters, in 

terms of whether the yearly parametric value is above (+) or below (–) its long-term average. These 

tables will be discussed appropriately in each of the following subsections.

2.7.1 <AT>

Figure 29(a) displays the yearly variation of <AT> (in °C) for the interval 1945–2010. The 

Armagh Observatory surface air temperature record is one of the longest available for study.41–50

Mean temperatures based on maximum and minimum thermometers extend continuously from 1844 

to the present. The Armagh Observatory lies about 1 km northeast of the center of the ancient city 

of Armagh in Northern Ireland at 54° 21.2 ́ N. latitude and 6° 38.9 ́ W. longitude. It is situated about 

64 m above mean sea level at the top of a small hill in an estate of natural woodland and parkland

that measures about 7 ha. Previous studies have shown that its rural environment has ensured that 

the observatory suffers from little or no urban microclimatic effects and that its temperature readings 

can be used as a proxy for studying long-term trends in annual mean surface air temperature for the 

Northern Hemisphere and for the Earth as a whole. Hence, it provides a useful measure for studying 

the effects of surface air temperature changes on the frequency and strength of tropical cyclones that 

form in the North Atlantic basin.

The construction of figure 29 (and the other summary charts that follow) mimics that of 

the previously shown summary charts. From figure 29(a), one notes that the long-term mean for 

the interval 1945–2010 is 9.48 °C, having sd = 0.53 °C and range 8.35 to 10.59 °C. A statistically 

important difference (t = –5, cl >99.9%) is found between the means for the intervals 1945–1994 and 

1995–2010, with the current, more active interval being about 7% warmer than the previous interval (9.97 °C versus 9.33 °C). The yearly value of <AT> = 10.59 °C in 2007 is the warmest annual 

surface air temperature ever recorded at Armagh Observatory, surpassing the previous high of 

10.4 °C recorded in 1846; the coolest <AT> = 7.4 °C occurred in 1879. A local peak may have been 

seen in the 10-yma of <AT> of 10.13 °C in 2002–2003, this value being the warmest in the entire 

Armagh Observatory surface air temperature record. The 10-yma of <AT> has since slightly cooled, 

at least through 2005, although it still remains above 10 °C. The coolest 10-yma of <AT> measured 

8.44 °C in 1883; hence, between 1883 and 2007 the 10-yma of <AT> has warmed by about 1.7 °C, 

or about 0.014 °C per year. Since about 1991, the 10-yma of <AT> has continuously been warmer 

than the long-term mean, with the current local warming trend having begun about 1982 (9.05 °C). 

(Noticeable in fig. 29(a) is the sharp decrease in temperature from 10.59 °C in 2007 to 8.74 °C in 

2010, the coolest yearly temperature since 1986, which measured 8.57 °C, a decrease of 1.85 °C. 

Temperature, however, quickly rebounded in 2011 to 10.31 °C, an increase of 1.57 °C from 2010.)

Figure 29(b) depicts the yearly variation of the difference (d<AT>)t. Runs testing indicates 

that the distribution of differences appears random (z = –0.26, cl <90%, sd = 0.4 °C). Given that 

the distribution of differences appears random, one should have expected the 10-yma of <AT> 

= 10.43 ± 0.4 °C for 2006, where 10.43 °C is the yearly <AT> for 2006 and 0.4 °C is the sd of the differences. As it turns out, <AT> = 10.31 °C in 2011 (up substantially from 8.74 °C in 2010), thereby 

yielding the 10-yma of <AT> = 10 °C in 2006 (down slightly from 10.02 °C in 2005). For 2007, based 

on the observed differences, one anticipates the 10-yma of <AT> = 10.59 ± 0.4 °C, where 10.59 °C 

is the yearly <AT> for 2007, inferring the 10-yma of <AT> ≥10.19 °C for 2007. This value, however, is simply too high to be considered realistic, since it indicates a yearly <AT> ≥13.3 °C for 2012, 
56 First Difference (fd(<AT>)) –0.1

–0.05

0

0.05

0.1

0.15

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<AT>)t

 = <AT>(10-yma)t+1 – <AT>(10-yma)t

 sd = 0.05

1965 1975 1985 1995 2005

Year

(c)

1950–1989: mean = 0

sd = 0.048 

1990–2004: mean = 0.04

sd = 0.052

⇒t = –2.691 

⇒cl >99%

1945–1994: mean = 9.327

sd = 0.444 

1995–2010: mean = 9.973

sd = 0.470

⇒t = –4.995

⇒cl >99.9%

Difference (d(<AT>))

–1

–0.5

0

0.5

1 d(<AT>)t

 = <AT>(yearly)t – <AT>(10-yma)t

 sd = 0.4

(b)

<AT>

8

8.5

9

9.5

10

10.5

11

(a)

1945–2010

<AT>

mean = 9.48

sd = 0.53

range = 8.35 to 10.59

a value more than 2.7 °C warmer than has ever been measured at Armagh Observatory and a value 

of about 3 °C, or more, higher than was seen in 2011. A more reasonable value of the 10-yma of 

<AT> is given below. (It is important to remember that the ±1 sd prediction interval is reliable only 

about 68% of the time, presuming a normal distribution of the differences. So, a value outside the 

Figure 29. Yearly variation of air temperature: (a) <AT>, (b) difference (d<AT>), 

and (c) first difference (fd<AT>) .
57

±1 sd prediction interval can still occur, on average, about 32% of the time. Clearly, one expects the 

10-yma of <AT> to be <10.19 °C in 2007, implying that the yearly <AT> for 2012 will be <13.3 °C, 

very probable considerably less. If the 10-yma of <AT> remains the same for 2007 as was observed 

in 2006, 10 °C, this implies the yearly <AT> = 9.5 °C in 2012. For every 0.01 °C increase or decrease 

in the 10-yma of <AT>, the yearly <AT> for 2012 will increase or decrease 0.2 °C accordingly.)

Figure 29(c) depicts the yearly variation of the first difference fd<AT>t. Runs testing indicates 

that the distribution of first differences appears nonrandom (z = –4.31, cl >99.9%, sd = 0.05 °C), 

as does the difference in the means for the intervals 1950–1989 and 1990–2004 (t = –2.69, cl >99%). 

Hence, one should have expected the 10-yma of <AT> = 10.02 + 0.04 ± 0.05 °C, or about 10.06 

± 0.05 °C for 2006, where 10.02 °C is the 10-yma of <AT> for 2005, 0.04 °C is the mean first difference for the current, more active interval, and 0.05 °C is the sd of the first difference. As noted above, 

the 2011 season actually had <AT> = 10.31 °C (up considerably from 8.74 °C in 2010), thereby yielding the 10-yma of <AT> = 10 °C for 2006 and fd = –0.02 °C for 2005. For 2007, one anticipates the 

10-yma of <AT> = 10 + 0.04 ± 0.05 °C, or about 10.04 ± 0.05 °C, inferring the yearly <AT> to be 

>9.3 °C in 2012 (perhaps as warm as 11.3 °C, the upper limit of the ±1 sd prediction interval).

From table 22, one finds that the difference in the yearly means for <AT> is not statistically 

important when comparing the mean yearly <AT> during the 16 EN years (ENY) against the mean 

yearly <AT> during the 15 LN years (LNY) (t = 0.1, cl <90%), or when comparing the mean yearly 

<AT> during the 30 yr when <ONI> was positive in value against the mean yearly <AT> during 

the 31 yr when <ONI> was negative in value (t = 0.37, cl <90%). Hence, strong correlation between 

yearly values of <AT> and <ONI> seems unlikely.

From table 23(a), one finds that, based on the Poisson distribution, if the year 2012 has 

a yearly mean <AT> greater (+) than its long-term average (9.48 °C), then one should expect NTC 

= 12 ± 2, having P(r = 10–14) = 51.9%; for NTC <10, P(r <10) = 18.7%; for NTC >14, P(r >14) 

= 29.4%; and for NTC >20, P(r >20) = 2%. For NTS, one should expect NTS = 5 ± 2, having 

P(r = 3–7) = 69.5%; for NTS <3, P(r <3) = 6.1%; for NTS >7, P(r >7) = 24.5%; and for NTS >10, 

P(r >10) = 4.5%. For NH, one should expect NH = 6 ± 2, having P(r = 4–8) = 66%; for NH <4, 

P(r <4) = 9.1%; for NH >8, P(r >8) = 24.9%; and for NH >10, P(r >10) = 8.7%. For NMH, one 

should expect NMH = 3 ± 1, having P(r = 2–4) = 59.9%; for NMH <2, P(r <2) = 14.9%; for NMH 

>4, P(r >4) = 25.2%; and for NMH >6, P(r >6) = 5.6%. For NUSLFH, one should expect NUSLFH 

= 2 ± 1, having P(r = 1–3) = 71.6%; for NUSLFH = 0, P(r = 0) = 12.2%; for NUSLFH >3, P(r >3) 

= 16.1%; and for NUSLFH >5, P(r >5) = 6.2%.

Likewise, from table 23(a), one finds that, based on the Poisson distribution, if the year 2012 

has a yearly mean <AT> lesser (–) than its long-term average (9.48 °C), then one should expect NTC 

= 9 ± 2, having P(r = 7–11) = 59%; for NTC <7, P(r <7) = 17.4%; for NTC >11, P(r >11) = 23.5%; 

and for NTC >15, P(r >15) = 3.1%. For NTS, one should expect NTS = 3 ± 1, having P(r = 2–4) 

= 57.3%; for NTS <2, P(r <2) = 11.8%; for NTS >4, P(r >4) = 30.9%; and for NTS >8, P(r >8) = 8%. 

For NH, one should expect NH = 5 ± 2, having P(r = 3–7) = 70.8%; for NH <3, P(r <3) = 7.7%; for 

NH >7, P(r >7) = 21.6%; and for NH >9, P(r >9) = 6.5%. For NMH, one should expect NMH = 2 

± 1, having P(r = 1–3) = 70.9%; for NMH = 0, P(r = 0) = 11.2%; for NMH >3, P(r >4) = 17.9%; 

and for NMH >5, P(r >5) = 2.4%. For NUSLFH, one should expect NUSLFH = 1 ± 1, having
58

P(r = 0–2) = 86.4%; for NUSLFH = 0, P(r = 0) = 28.1%; for NUSLFH >2, P(r >2) = 13.6%; and for 

NUSLFH >4, P(r >4) = 1%. 

It should be noted that monthly surface air temperature at Armagh Observatory measured, 

respectively, 6.3, 6.8, and 9 °C for the months of January, February, and March 2012, all readings 

among the warmest monthly-specific readings ever recorded at Armagh Observatory and all well 

above their respective monthly-specific mean temperatures of about 4.4, 4.6, and 6.4 °C, based on the 

interval 1950–2011. Hence, it seems likely that the yearly mean surface air temperature at Armagh 

Observatory for 2012 will exceed its long-term average of 9.48 °C, rather than fall below it, suggesting that tropical cyclone frequency likely will be above average for the 2012 hurricane season, unless 

of course, the summer temperatures at Armagh Observatory turn out to be cooler than usual.

2.7.2 <ONI>

Figure 30(a) displays the yearly variation of <ONI>. <ONI> is the yearly mean of the 3-mo 

running mean (i.e., 2-mo moving average) of the National Oceanic and Atmospheric Administration’s (NOAA’S) Extended Reconstructed SST, version 3b anomalies in the Niño 3.4 region (5 °N.–5 

°S., 120–170 °W.) based on the 1971–2000 base period.51 The long-term mean of <ONI> is –0.01 °C, 

having sd = 0.62 °C and range of –1.24 °C (1955) to 1.29 °C (1987). The difference in means for the 

intervals 1950–1994 and 1995–2010 is not statistically important (t = –0.53, cl <90%), although the 

mean for the current, more active interval is about 0.1 °C warmer than the preceding earlier interval 

(0.06 °C versus –0.04 °C). Prior to 1980, the 10-yma of <ONI> was nearly always negative in value 

(for all years except 1961, 1962, 1965, and 1968), while from 1980 onwards, the 10-yma of <ONI> 

has been almost always positive in value (for all years except 2003), with the 10-yma of <ONI> now 

being very close to 0 °C. (ONI monthly values have recently changed from those used in this analysis.45 Newer ONI monthly values result in yearly values that are slightly different. For example, in the 

illustration above, the value of <ONI> for 2010 based on the newer entries is now –3.2/12 = –0.27 

rather than –1.8/12 = –0.15.)

In figure 30(a), the positive (warm) spikes generally represent EN-related years and the negative (cool) spikes generally represent LN-related years. The two warmest <ONI> years occurred in 

1987 (1.29 °C) and 1997 (1.26 °C), both EN-related years, and the two coolest <ONI> years occurred 

in 1955 (–1.24 °C) and 1975 (–1.14 °C), both LN-related years. In terms of the 10-yma <ONI>, the 

warmest <ONI> measured 0.3 °C in 1993, and the coolest <ONI> measured –0.29 °C in 1971. (As 

already mentioned, the 10-yma of <ONI> now is very near 0 °C.)

Figure 30(b) displays the yearly variation of the difference (d<ONI>t). Runs testing indicates 

that the distribution of differences appears random (z = –0.66, cl <90%, sd = 0.61 °C). Given that the 

distribution of differences appears random, one should have expected the 10-yma of <ONI> = 0.25 

± 0.61 °C for 2006, where 0.25 °C is the yearly <ONI> for 2006 and 0.61 °C is the sd of the differences. 

As it turns out, the yearly <ONI> = –0.6 °C in 2011 (substantially cooler than <ONI> = –0.15 °C 

that was observed in 2010), thereby yielding the 10-yma of <ONI> = 0.14 °C in 2006 (a value about 

0.1 °C warmer than the 0.04 °C that was observed in 2005). For 2007, based on the observed differences, one anticipates the 10-yma of <ONI> = –0.3 ± 0.61 °C, where –0.3 °C is the yearly <ONI> 
59

First Difference (fd(<ONI>)) –0.1

–0.15

–0.05

0

0.05

0.1

0.15

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<ONI>)t

 = <ONI>(10-yma)t+1 – <ONI>(10-yma)t

 sd = 0.06

1965 1975 1985 1995 2005

Year

(c)

1955–1989: mean = 0.014

sd = 0.059 

1990–2004: mean = –0.016

sd = 0.05

⇒t = 1.72

⇒cl >90%

1950–1994: mean = –0.036

sd = 0.635 

1995–2010: mean = 0.06

sd = 0.59

⇒t = –0.529

⇒cl <90%

Difference (d(<ONI>)) –1.5

–1

–0.5

0

0.5

1

1.5 d(<ONI>)t

 = <ONI>(yearly)t – <ONI>(10-yma)t

 sd = 0.61

<ONI>

–1.5

–1

–0.5

0

0.5

1

1.5 1950–2010

<ONI>

(b)

(a)

mean = –0.01

sd = 0.62

range = –1.24 to 1.29

Figure 30. Yearly variation of Oceanic Niño index: (a) <ONI>, (b) difference (d<ONI>), 

and (c) first difference (fd<ONI>).
60

for 2007, inferring the 10-yma of <ONI> ≤0.31 °C for 2007. If the 10-yma of <ONI> = 0 °C or less 

(i.e., more negative in value) for 2007, then the yearly <ONI> = –1.5 °C or more negative in value for 

2012, a value indicative of LN conditions. On the other hand, if the 10-yma of <ONI> = 0.1 °C or 

more positive in value for 2007, then the yearly <ONI> = 0.5 °C or higher in value, a value indicative 

of possibly ENSO neutral to EN-like conditions in 2012. Therefore, it is apparent that the 10-yma 

of <ONI> will be very close to 0 °C for 2007. (Based on the previously observed extremes, <ONI> 

= 1.29 °C in 2012 means that the 10-yma of <ONI> = 0.14 °C in 2007, while <ONI> = –1.24 °C in 

2012 means that the 10-yma of <ONI> = 0.01 °C in 2007. Plainly, one expects the 10-yma of <ONI> 

to lie within the range of 0.01 to 0.14 °C in 2007, inferring d(<ONI>)t = –0.31 to –0.17 °C in 2007.)

Figure 30(c) depicts the yearly variation of the first difference (fd<ONI>t). While runs testing 

indicates that the distribution of first differences appears random (z = –0.54, cl <90%, sd = 0.06 °C), 

the difference in the means for the intervals 1955–1989 and 1990–2004 is found to be marginally statically important (t = 1.72, cl >90%). Hence, for 2006 one should have expected the 10-yma of <ONI> 

= 0.04 ± 0.06 °C (presuming a random distribution of the first difference values) or 0.04 – 0.02 

± 0.05 °C (i.e., about 0.02 ± 0.05 °C), where 0.04 °C is the 10-yma of <ONI> for 2005 and –0.02 °C 

and 0.05 °C are the mean first difference and sd, respectively, for the current, more active interval. 

As noted above, the 2011 season actually had <ONI> = –0.6 °C (cooler than the –0.15 °C measured 

in 2010), thereby yielding the 10-yma of <ONI> = 0.14 °C for 2006 and fd<ONI>t = 0.1 °C for 

2005 (both values outside high the ±1 sd prediction intervals). For 2007, one anticipates the 10-yma 

of <ONI> = 0.14 ± 0.06 °C, based on a normal distribution of the first differences, or 0.14 – 0.02 

± 0.05 °C (i.e., about 0.12 ± 0.05 °C), based on the mean and sd of the current, more active interval. 

Hence, one expects the yearly <ONI> to be ≥0.1 °C in 2012 (perhaps as warm as 2.5 °C, the upper 

limit of the ±1 sd prediction interval), based on the normal distribution of the first difference, or 

≥–0.1 °C (perhaps as warm as 1.9 °C, the upper limit of the ±1 sd prediction interval for the current, 

more active interval). These values, if true, are indicative of ENSO neutral to EN-like conditions in 

2012. (Recall that the recurrence rate for EN events is about 40–41 mo, on average, and the last EN 

event, which was one of strong intensity, had its start in June 2009. Hence, the possibility exists that 

an EN event likely could occur during the 2012 hurricane season.30)

From table 22, one finds that the difference in the means for <ONI> is highly statistically 

important, as one would expect, when comparing the mean yearly <ONI> during the 16 ENYs 

against the mean yearly <ONI> during the 15 LNYs (t = 11.05, cl »99.9%), or when comparing the 

mean yearly <ONI> during the 30 yr when it was positive in value against the mean yearly <ONI> 

during the 31 yr when it was negative in value (t = 11.91, cl »99.9%). Hence, the yearly <ONI> 

appears to be a robust measure for determining the phase of the ENSO quasi-periodic cycle.

From table 23(b), for <ONI> ‘+,’ NTC = 10 ± 2 (56.2%), NTC <8 (17.3%), and NTC >12 

(26.5%); NTS = 4 ± 2 (76.2%), NTS <2 (5.6%), and NTS >6 (18.2%); NH = 5 ± 2 (68.5%), NH <3 

(6.3%), and NH >7 (25.2%); NMH = 2 ± 1 (69.1%), NMH = 0 (9.4%), and NMH >3 (21.5%); and 

NUSLFH = 1 ± 1 (80.9%) and NUSLFH >2 (19.1%). For <ONI> ‘–,’ NTC = 11 ± 2 (54.7%), NTC 

<9 (20.7%), and NTC >13 (24.6%); NTS = 4 ± 2 (75.2%), NTS <2 (5.1%), and NTS >6 (19.7%); NH 

= 6 ± 2 (67.6%), NH <4 (10.6%), and NH >8 (21.8%); NMH = 3 ± 1 (61.5%), NMH <2 (19%), and 

NMH >4 (19.5%); and NUSLFH = 1 ± 1 (78.1%) and NUSLFH >2 (21.9%). 
61

Presently, the monthly values of ONI indicate a weakening LN event. Based on the former 

version of the ONI values, those used in this analysis, the current LN event began in October 2011, 

attained a peak anomalous value of –0.9 °C in December 2011 and now measures, respectively, –0.8 

and –0.6 °C in January and February 2012; based on the newer version of the ONI values, the LN 

event began in September 2011, attained a peak anomalous value of –1 °C in November and December 2011 and now measures, respectively, –0.9 and –0.7 °C in January and February 2012. Monthly 

ONI values are expected to be reflective of ENSO neutral conditions in April 2012.52 One cannot, 

as yet, determine the likelihood of whether <ONI> will be positive or negative in value for the year 

2012.

2.7.3 <SOI>

While the ONI often is used to describe the oceanic response to anomalous changes in sea 

surface temperature associated with the quasi-periodic ENSO phenomenon, the SOI similarly is 

used to describe the atmospheric response to changes in surface air pressure associated with ENSO. 

Typically, the two parameters vary inversely (i.e., in the opposite sense), with one or the other sometimes slightly leading or lagging. During EN (warm) events, ONI is of positive sustained value 

(0.5 °C or warmer) and SOI usually is of negative sustained value (≤–8), while during LN (cool) 

events, ONI is of negative sustained value (–0.5 °C or cooler) and SOI is usually of positive sustained 

value (≥8). The SOI is calculated using the air pressure differences between Tahiti, French Polynesia 

and Darwin, Australia. The SOI values used in this study were taken from the Australian Bureau of 

Meteorology.53 Monthly values of the SOI are available from 1876 to the present, being based on the 

means and standard deviations calculated over the interval 1933 to 1992 inclusive.

Figure 31(a) displays the yearly variation of <SOI>. For the interval 1945–2010, <SOI> 

averages about –0.1, having sd = 6.8 and range = –13.1 to 15.4. For the two intervals, 1945–1994 and 

1995–2010, the difference in means is found not to be statistically important (t = –0.43, cl <90%). As 

with <ONI>, the spikes in <SOI> usually denote years containing anomalous ENSO events. The 

2 yr of most positive <SOI> (15.4 and 13.6) are 1950 and 1975, both years being LN-related years. 

The 2 yr of most negative <SOI> (–13.1) are 1982 and 1987, both years being EN-related years. In 

terms of the 10-yma of <SOI>, it nearly always was positive in value for the interval 1950–1977 (the 

lone exception being 1962), and it always was negative in value for the interval 1978–2003. For 2004 

and 2005, the 10-yma of <SOI> has been positive in value, but just barely so (0.44 and 0.13, respectively). (The yearly value of <SOI> appears to have turned generally positive in value beginning in 

2007, with the interval 2007–2011 having yearly <SOI> = 1.5. 10.2, –0.2, 9.8, and 13.3, respectively. 

So, the 10-yma of <SOI> is expected to remain positive in value, at least for the near-term, foreseeable future. In fact, the 10-yma of <SOI> grew from 0.13 in 2005 to 0.87 in 2006, an increase of 

0.71 units. For the 10-yma of <SOI> to become negative in value in 2007, the yearly <SOI> for 2012 

would have to measure <–36.3, a value much more negative than the yearly value of <SOI> = –20, 

the lowest ever seen, which occurred in 1905; the lowest yearly <SOI> in the interval 1945–2010 is 

<SOI> = –13.1 in 1982 and 1987, as previously mentioned.)

Figure 31(b) shows the yearly variation of the difference (d<SOI>t). Runs testing indicates 

that the distribution of differences appears random (z = –1.23, cl <90%, sd = 6.45). Given that the 

distribution of differences appears random, one should have expected the 10-yma of <SOI> = –1.9 
62

First Difference (fd(<SOI>))

–2

–1.5

–1

–0.5

0

0.5

1

1.5

2

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<SOI>)t

 = <SOI>(10-yma)t+1 – <SOI>(10-yma)t

 sd = 0.7

1965 1975 1985 1995 2005

Year

(c)

1950–1989: mean = –0.14

sd = 0.721 

1990–2004: mean = 0.305

sd = 0.524

⇒t = –2.179

⇒cl >95%

Difference (d(<SOI>))

–15

–10

–5

0

5

10

15 d(<SOI>)t

 = <SOI>(yearly)t – <SOI>(10-yma)t

 sd = 6.45

(b)

1945–1994: mean = –0.308

sd = 7.065 

1995–2010: mean = 0.544

sd = 6.245

<SOI>

–15

–10

–5

0

5

10

15

20

(a)

⇒t = –0.431

⇒cl <90%

1945–2010

<SOI>

mean = –0.1

sd = 6.8

range = –13.1 to 15.4

Figure 31. Yearly variation of Southern Oscillation index: (a) <SOI>, (b) difference 

(d<SOI>), and (c) first difference (fd<SOI>).
63

± 6.45 for 2006, where –1.9 is the yearly <SOI> for 2006 and 6.45 is the sd of the differences. As it 

turns out, the yearly <SOI> = 13.3 in 2011 (slightly higher than the yearly <SOI> = 9.8 that was 

observed in 2010), thereby yielding the 10-yma of <SOI> = 0.87 in 2006 (up from 0.13 measured 

in 2005). For 2007, based on the observed differences, one anticipates the 10-yma of <SOI> = 1.5 

± 6.45, where 1.5 is the yearly <SOI> for 2007. A value of the 10-yma of <SOI> = 1.5 in 2007 means 

that the yearly <SOI> = –6.3 in 2012; a value of the 10-yma of <SOI> = 1.8 in 2007 means that 

the yearly <SOI> = –0.3 in 2012; and a value of the 10-yma of <SOI> = 1.2 in 2007 means that the 

yearly <SOI> = –12.3. Hence, a 10-yma of <SOI> equal to 1.5 or higher yields a yearly value of 

<SOI> suggestive of ENSO neutral to LN-like conditions in 2012, while a value smaller than 1.5 

yields a yearly <SOI> suggestive of EN-like conditions in 2012.

Figure 31(c) depicts the yearly variation of the first difference (fd<SOI>t). Both runs testing and the difference in means for the two intervals 1950–1989 and 1990–2004 indicate that the 

distribution of first differences appears nonrandom (z = –2.25, cl >95%, sd = 0.70; and t = –2.18, 

cl >95%). Hence, for 2006 one should have expected the 10-yma of <SOI> = 0.13 + 0.31 ± 0.52, or 

about 0.44 ± 0.52, where 0.13 is the 10-yma of <SOI> for 2005 and 0.31 and 0.52, respectively, are 

the mean first difference and sd for the current, more active interval. As noted above, the 2011 season

actually had <SOI> = 13.3 (slightly higher than 9.8 measured in 2010), thereby yielding the 10-yma of

<SOI> = 0.87 for 2006 and fd<SOI>t = 0.74 for 2005. For 2007, one anticipates the 10-yma

of <SOI> = 0.87 + 0.31 ± 0.52, or about 1.18 ± 0.52, which, if true, suggests that the yearly

value of <SOI> = –23.1 to –2.3 for 2012, a range of values indicative of ENSO neutral to EN-like 

conditions. 

From table 22, one finds that the difference in the means for <SOI> is statistically important, 

when comparing the mean of <SOI> during the 16 ENY against the mean of <SOI> during the 

15 LNY (t = –8.86, cl >99.9%), or when comparing the mean of <SOI> during the 30 yr when 

<ONI> was positive in value against the mean of <SOI> during the 31 yr when <ONI> was negative 

in value (t = –10.36, cl >99.9%). Hence, strong inverse correlation between yearly values of <SOI> 

and <ONI> seems highly likely, as would be expected, with both measures independently serving as 

robust measures for determining the phase of the ENSO quasi-periodic cycle (i.e., the two parameters vary inversely, being of opposite signs in 58 of the 61 yr in the interval 1950–2010; only the 

years 1952, 1978, and 1984 were of the same sign).

From table 23(c), for <SOI> ‘+,’ NTC = 11 ± 2 (54.7%), NTC <9 (20.9%), and NTC >13 

(24.4%); NTS = 4 ± 2 (75.6%), NTS <2 (5.3%), and NTS >6 (19.1%); NH = 6 ± 2 (67.5%), NH <4 

(10.5%), and NH >8 (22%); NMH = 3 ± 1 (61.2%), NMH <2 (18.1%), and NMH >4 (20.7%); and 

NUSLFH = 1 ± 1 (73.1%) and NUSLFH >2 (26.9%). For <SOI> ‘–,’ NTC = 10 ± 2 (56.4%), NTC 

<8 (18.1%), and NTC >12 (25.5%); NTS = 4 ± 2 (76.1%), NTS <2 (5.6%), and NTS >6 (18.3%); NH 

= 5 ± 2 (69.5%), NH <3 (6.9%), and NH >7 (23.7%); NMH = 2 ± 1 (69.3%), NMH = 0 (9.4%), and 

NMH >3 (21.3%); and NUSLFH = 1 ± 1 (80.9%) and NUSLFH >2 (19.1%).

Monthly values of SOI have returned to values indicative of ENSO neutral conditions, measuring 9.4, 2.5, and 2.9, respectively, for January, February, and March 2012. It is anticipated that 

ENSO neutral conditions will persist, at least through the middle of 2012.54 Presuming that an EN 

event will occur later this year, one anticipates monthly values of SOI that are negative in value (more 

negative than –8), inferring that <SOI> will be ‘–’ for 2012.
64

2.7.4 <NAO>

Like the Southern Oscillation, the North Atlantic Oscillation (NAO) is one based on changes 

in surface air pressure between two widely separated locations (e.g., Iceland and the subtropical 

Atlantic Ocean basin—the Azores, Portugal, or Gibraltar). The large-scale, air-mass movements 

described by the NAO thus control the strength and direction of westerly winds and storm tracks 

across the North Atlantic Ocean. During the positive phase of the NAO, there is a stronger than 

usual subtropical high pressure center and a deeper than usual Icelandic low, while during the negative phase of the NAO, the opposite is true.55–58

Figure 32(a) displays the yearly variation of <NAO>.59 For the interval 1945–2010, <NAO> 

averages about –0.03, having sd = 0.37 and range = –1.15 to 0.8. For the two intervals, 1945–1994 

and 1995–2010, the difference in means is found not to be statistically important (t = 1.41, cl <90%). 

Unlike <ONI> and <SOI>, the spikes in <NAO> do not always correspond to years when anomalous ENSO events occur. For example, the 2 yr of most positive <NAO> (0.7 and 0.8) are 1989 and 

1994, but only the year 1994 is associated with an anomalous ENSO extreme event (EN). Similarly, 

the 2 yr of most negative <NAO> (–0.94 and –1.15) are 1968 and 2010, but only the year 2010 is 

associated with an anomalous ENSO extreme event (LN). In terms of the 10-yma of <NAO>, 

it always was negative in value for the interval 1950–1973, varying between –0.02 and –0.22 and 

averaging about –0.15 ± 0.06, and it always was positive in value for the interval 1974–1999, varying between 0.02 and 0.34 and averaging about 0.14 ± 0.11. For the interval 2000–2004, the 10-yma 

of <NAO> has varied between –0.01 to –0.03, averaging about –0.02 ± 0.01. For 2005 and 2006, 

the 10-yma of <NAO> became significantly more negative in value (–0.12 and –0.16, respectively). 

For the 10-yma of <NAO> to become positive in value in 2007, the yearly <NAO> must measure 

in excess of 2.86 in 2012, a value that is about 3.6 times larger than the previously observed largest 

positive value of 0.8 in 1994. So, it seems highly unlikely that the 10-yma of <NAO> will be positive 

in value in 2007 (or anytime soon in the near-term, foreseeable future). Instead, it seems highly probable that the 10-yma of <NAO> will remain negative in value. (Presuming a yearly <NAO> = –0.14 

± 0.36 for 2012, the ±1 sd prediction interval about the mean for the current, more active interval, 

one expects the 10-yma of <NAO> = –0.15 ± 0.02 for 2007.) 

Figure 32(b) shows the yearly variation of the difference (d<NAO>t). Unlike the differences 

for <AT>, <ONI>, and <SOI>, runs testing indicates that the distribution of differences for <NAO> 

might be nonrandom (z = 2.08, cl >95%, sd = 0.31). However, if one had assumed that the differences 

are distributed randomly, one would have estimated the 10-yma of <NAO> = –0.27 ± 0.31 for 2006, 

where –0.27 is the yearly <NAO> for 2006 and 0.31 is the sd of the differences. As it turns out, the 

yearly <NAO> = 0.29 in 2011, yielding the 10-yma of <NAO> = –0.16 for 2006, within the ±1 sd

prediction interval. For 2007, again, if one assumes the distribution of differences is random, one 

expects the 10-yma of <NAO> = 0.17 ± 0.31, or >–0.14, where 0.17 is the yearly <NAO> for 2007 

and 0.31 is the sd of the differences, which, if true, implies the yearly <NAO> ≥0.06 in 2012. (From 

above, a yearly <NAO> ≤0.17 in 2012 is expected.) 

Figure 32(c) depicts the yearly variation of the first difference (fd<NAO>t). Both runs testing and the difference in means for the two intervals 1955–1989 and 1990–2004 indicate that the 

distribution of first differences appears nonrandom (z = –3.33, cl >99.8%, sd = 0.03; and t = –5.46, 
65

First Difference (fd(<NAO>)) –0.15

–0.1

–0.05

0

0.05

0.1

0.15

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<NAO>)t

 = <NAO>(10-yma)t+1 – <NAO>(10-yma)t

 sd = 0.03

1965 1975 1985 1995 2005

Year

(c)

1955–1989: mean = 0.014

sd = 0.027 

1990–2004: mean = –0.031

sd = 0.026

⇒t = 5.459 

⇒cl >99.9%

Difference (d(<NAO>))

–1

–0.5

0

0.5

1 d(<NAO>)t

 = <NAO>(yearly)t – <NAO>(10-yma)t

 sd = 0.31

(b)

<NAO>

–1

–1.5

–0.5

0

0.5

1 1950–2010

<NAO>

(a)

1950–1994: mean = 0.012

sd = 0.366 

1995–2010: mean = –0.138

sd = 0.362

⇒t = 1.412 

⇒cl <90%

mean = –0.03

sd = 0.37

range = –1.15 to 0.8

cl >99.9%). Hence, for 2006 one should have expected the 10-yma of <NAO> = –0.12 ± –0.03 

± 0.03, or about –0.15 ± 0.03, where ± 0.12 is the 10-yma of <NAO> for 2005 and ± 0.03 and 0.03, 

respectively, are the mean first difference and sd for the current, more active interval. As noted above, 

the 2011 season actually had <NAO> = 0.29 (up from ± 1.15 measured in 2010), thereby yielding 

Figure 32. Yearly variation of North Atlantic Oscillation index: (a) <NAO>, 

(b) difference (d<NAO>), and (c) first difference (fd<NAO>) .
66

the 10-yma of <NAO> = ± 0.16 for 2006 and fd<NAO>t = –0.04 for 2005. For 2007, one anticipates 

the 10-yma of <NAO> = –0.16 – 0.03 ± 0.03, or about –0.19 ± 0.03, which, if true, suggests a yearly 

value of <NAO> between –0.34 and –1.54 for 2012 (this being in stark contrast to that found above 

based on the expected difference).

From table 22, one finds that the difference in the means for <NAO> is only of marginal 

statistical importance or of no statistical importance, respectively, when comparing the mean of 

<NAO> during the 16 ENY against the mean of <NAO> during the 15 LNY (t = 1.86, cl >90%), or 

when comparing the mean of <NAO> during the 30 yr when <ONI> was positive in value against 

the mean of <NAO> during the 31 yr when <ONI> was negative in value (t = 0.95, cl <90%). Hence, 

strong correlation between yearly values of <NAO> and <ONI> seems unlikely (i.e., the two parameters are of the same or opposite sign in only 31 of the 62 yr in the interval 1950–2011).

From table 23(d), for <NAO> ‘+,’ NTC = 10 ± 2 (56.5%), NTC <8 (18.2%), and NTC >12 

(25.4%); NTS = 4 ± 2 (73.5%), NTS <2 (4.5%), and NTS >6 (22.1%); NH = 5 ± 2 (71.6%), NH <3 

(8.4%), and NH >7 (20%); NMH = 2 ± 1 (72.2%), NMH = 0 (13.5%), and NMH >3 (14.3%); and 

NUSLFH = 1 ± 1 (79.9%) and NUSLFH >2 (20.1%). For <NAO> ‘–,’ NTC = 11 ± 2 (54.7%), NTC 

<9 (20.7%), and NTC >13 (24.6%); NTS = 4 ± 2 (77.1%), NTS <2 (6.2%), and NTS >6 (16.8%); NH 

= 6 ± 2 (66.2%), NH < 4 (9.3%), and NH >8 (24.5%); NMH = 3 ± 1 (60.6%), NMH <2 (16.4%), and 

NMH >4 (235); and NUSLFH = 1 ± 1 (79.1%) and NUSLFH >2 (20.9%). 

Presently, the monthly values of NAO are running positive in value, measuring 1.17, 0.42, 

and 1.27, respectively, for January, February, and March 2012. The string of positive values now 

spans 7 mo, having begun in September 2011, with the December 2011 value being 2.52, the most 

positive December value in the span of 1950–2011, surpassing the previous high of 2.02 that was 

seen in December 1995. The longest string of positive NAO values spans 9 mo, between April and 

December 1959, averaging 0.51 and ranging 0.06 to 0.89. Two other long, positive value strings have 

occurred: (1) 8 mo, between August 1999 and March 2000, averaging 0.79 and ranging 0.2 to 1.7; 

and (2) 7 mo, between September 2007 and March 2008, averaging 0.54 and ranging 0.08 to 0.89. 

Since 1950, the nominal hurricane season has had slightly more negative values than positive values, 

194 to 178. Thus, while it seems likely that monthly values of NAO will turn negative sometime during the year 2012, one cannot, as yet, determine the likelihood that <NAO> for 2012 will be positive 

or negative in value. From the usual difference, one anticipates that it will be of positive value; however, from the usual first difference, one anticipates that it will be of negative value.

2.7.5 <PDO>

The PDO index is defined as the leading principal component of the monthly SST anomalies in the North Pacific Ocean, northward of 20 °N. Like the ENSO quasi-periodic cycle, the PDO 

fluctuates between warm (positive) and cool (negative) phases. During the warm phase, the western Pacific Ocean surface waters become cool and part of the eastern Pacific Ocean surface waters 

becomes warm, while during the cool phase, the opposite is true. While the PDO is a climate index 

that is based upon patterns of SST variation in the North Pacific Ocean basin, it has been found to 

correlate with many varied climate records, including sea level pressure, winter land surface temperature and precipitation, stream flow, and salmon catches.60–68
67

Figure 33(a) displays the yearly variation of <PDO>.69 For the interval 1945–2010, <PDO> 

averages about –0.13 °C, having sd = 0.83 °C and range = –1.95 to 1.82 °C. For the two intervals, 1945–1994 and 1995–2010, the difference in means is found not to be statistically important 

(t = –0.91, cl <90%). Like <NAO>, the spikes in <PDO> do not always correspond to years when 

anomalous ENSO events occur. For example, the 2 yr of most positive <PDO> (1.65 and 1.82 °C) 

are 1983 and 1987, but only the year 1987 is associated with an anomalous ENSO extreme event 

(EN) (the year 1983 follows an EN event). Similarly, the 2 yr of most negative <PDO> (–1.81 and 

–1.95 °C) are 1950 and 1955, both associated with anomalous ENSO extreme events (LN). In terms 

of the 10-yma of <PDO>, it always was negative in value for the interval 1950–1977, varying between 

–0.04 and –0.94 °C and averaging about –0.55 ± 0.19 °C, and it always was positive in value for the 

interval 1974–2002, varying between 0.08 and 0.84 °C and averaging about 0.45 ± 0.22 °C. For the 

interval 2003–2005, the 10-yma of <PDO> has varied between –0.08 and –0.13 °C, averaging about 

–0.1 ± 0.03 °C. For the 10-yma of <PDO> to become positive in value in 2007, the yearly <PDO> 

must measure in excess of 3.24 °C in 2012, a value that is about 1.8 times larger than the previously 

observed largest positive value of 1.82 in 1987. So, it seems unlikely that the 10-yma of <PDO> 

will be positive in value in 2007 (or anytime soon in the near-term, foreseeable future). Instead, it 

seems highly probable that the 10-yma of <PDO> will remain negative in value. (Presuming a yearly 

<PDO> = 0.03 ± 0.74 °C for 2012, the ±1 sd prediction interval about the mean for the current, more 

active interval, one expects the 10-yma of <PDO> = –0.16 ± 0.04 for 2007.) 

Figure 33(b) shows the yearly variation of the difference (d<PDO>t). Like the differences for 

<AT>, <ONI>, and <SOI>, runs testing indicates that the distribution of differences for <PDO> 

appears to be random (z = –1.63, cl <90%, sd = 0.65 °C). Given that the distribution of differences 

appears random, one should have expected the 10-yma of <PDO> = 0.19 ± 0.65 °C for 2006, where 

0.19 °C is the yearly <PDO> for 2006 and 0.65 °C is the sd of the differences. As it turns out, the 

yearly <PDO> = –1.23 °C in 2011 (considerably more negative in value than the yearly <PDO> 

= –0.31 °C that was observed in 2010), thereby yielding the 10-yma of <PDO> = –0.16 °C in 2006 

(more negative than the –0.12 °C measured in 2005). For 2007, based on the observed differences, 

one anticipates the 10-yma of <PDO> = –0.2 ± 0.65 °C, where –0.2 °C is the yearly <PDO> for 

2007. A value of the 10-yma of <PDO> = –0.2 °C in 2007 means that the yearly <PDO> = –0.76 °C 

in 2012, while a value more negative (positive) than –0.2 °C for the 10-yma of <PDO> in 2007 means 

that the yearly <PDO> for 2012 will be more negative (positive) as well. (An increase or decrease 

of 0.01 °C in the 10-yma of <PDO> for 2007 changes the 2012 estimate for the yearly <PDO> by 

0.2 °C, accordingly.) 

Figure 33(c) depicts the yearly variation of the first difference (fd<PDO>t). Both runs testing 

and the difference in means for the two intervals 1950–1989 and 1990–2004 indicate that the distribution of first differences appears nonrandom (z = –3.26, cl >99.5%, sd = 0.09; and t = –2.68, cl >99%). 

Hence, for 2006, one should have expected the 10-yma of <PD0> = –0.1 – 0.04 ± 0.05 °C, or about 

–0.14 ± 0.05 °C, where –0.1 °C is the 10-yma of <PDO> for 2005 and –0.04 °C and 0.05 °C, respectively, are the mean first difference and sd for the current, more active interval. As noted above, the 

2011 season actually had <PDO> = –1.23 °C (more negative than the –0.31 °C measured in 2010), 

thereby yielding the 10-yma of <PDO> = –0.12 °C for 2006 and fd<PDO>t = –0.02 °C for 2005. 

For 2007, one anticipates the 10-yma of <PDO> = –0.16 – 0.04 ± 0.05 °C, or about –0.2 ± 0.05 °C, 

which, if true, suggests that the yearly value of <PDO> = –0.76 ± 1 °C for 2012.
68

First Difference (fd(<PDO>)) –0.2

–0.15

–0.1

0.05

0

0.05

0.1

0.15

0.2

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<PDO>)t

 = <PDO>(10-yma)t+1 – <PDO>(10-yma)t

 sd = 0.09

1965 1975 1985 1995 2005

Year

(c)

1950–1989: mean = –0.025

sd = 0.092 

1990–2004: mean = –0.042

sd = 0.047

⇒t = –2.681 ⇒cl >99%

Difference (d(<PDO>)) –1.5

–1

–0.5

0

0.5

1

1.5 d(<PDO>)t

 = <PDO>(yearly)t – <PDO>(10-yma)t

 sd = 0.65

(b)

1945–1994: mean = –0.185

sd = 0.853 

1995–2010: mean = 0.031

sd = 0.739

⇒t = –0.909 

⇒cl <90%

1945–2010

<PDO>

<PDO>

–2

–1.5

–1

–0.5

0

0.5

1

1.5

2

(a)

mean = –0.13

sd = 0.83

range = –1.95 to 1.82

Figure 33. Yearly variation of Pacific Decadal Oscillation index: (a) <PDO>, (b) difference 

(d<PDO>), and (c) first difference (fd<PDO>). 
69

From table 22, one finds that the difference in the means for <PDO> is statistically important 

when comparing the mean of <PDO> during the 16 ENY against the mean of <PDO> during the 

15 LNY (t = 2.85, cl >99%), or when comparing the mean of <PDO> during the 30 yr when <ONI> 

was positive in value against the mean of <PDO> during the 31 yr when <ONI> was negative in 

value (t = 4.09, cl >99.9%). Hence, strong correlation between yearly values of <PDO> and <ONI> 

seems likely, with positive <PDO> tending to occur with positive <ONI> and negative <PDO> 

tending to occur with negative <ONI> (i.e., the two parameters are of the same sign in 42 of the 

62 yr in the interval 1950–2011).

From table 23(e), for <PDO> ‘+,’ NTC = 10 ± 2 (55.3%), NTC <8 (15.5%), and NTC >12 

(29.2%); NTS = 4 ± 2 (73.7%), NTS <2 (4.6%), and NTS >6 (21.8%); NH = 5 ± 2 (68.6%), NH <3 

(6.4%), and NH >7 (25.1%); NMH = 2 ± 1 (67.6%), NMH = 0 (8.2%), and NMH >3 (24.2%); and 

NUSLFH = 1 ± 1 (73.3%) and NUSLFH >2 (26.7%). For <PDO> ‘–,’ NTC = 10 ± 2 (55.2%), NTC 

<8 (15.4%), and NTC >12 (29.4%); NTS = 4 ± 2 (77.2%), NTS <2 (6.3%), and NTS >6 (16.5%); NH 

= 6 ± 2 (68.6%), NH <4 (12.1%), and NH >8 (19.3%); NMH = 2 ± 1 (62%), NMH = 0 (5.7%), and 

NMH >3 (32.4%); and NUSLFH = 1 ± 1 (80.1%) and NUSLFH >2 (19.9%).

The monthly values of PDO are running negative in value, measuring –1.38 and 

–0.85 °C, respectively, for January and February 2012. The string of negative values now 

spans 21 mo, having begun in June 2010, with the November 2011 value being –2.33 °C, the most 

negative November value since November 1955 (–3.08 °C, which happens to be the most negative 

November, as well as the most negative value for any month in the interval 1900–2010). In the interval 

1948–2010, the longest string of negative PDO values spans 36 mo, between July 1948 and June 1951, 

averaging –1.41 °C and ranging –0.25 to –2.93 °C. Four other long negative strings have occurred 

during the interval 1948–2011: (1) 28 mo, between May 1961 and August 1963, averaging –1.01 °C and 

ranging –0.06 to –2.28 °C; (2) 25 mo, between February 1955 and February 1957, averaging –1.91 °C 

and ranging –0.68 to –3.08 °C; (3) 23 mo, between August 1966 and June 1968, averaging –0.68 °C 

and ranging –0.05 to –1.24 °C; and (4) 23 mo, between September 2007 and July 2009, averaging 

–1.17 °C and ranging –0.31 to –1.76 °C. Since 1950, the nominal hurricane season has had slightly 

more negative values than positive values, 194 to 178. Thus, the possibility exists that the year 2012 

may indeed turn out to have <PDO> of negative value, although it remains unknown as to how 

negative its value will be. If the yearly <PDO> for 2012 happens to be of negative value, this would 

indicate a slightly better chance (1 in 3) that more than 3 major hurricanes will occur in the 2012 

hurricane season, as compared to a slightly lesser chance (1 in 4) if the yearly <PDO> for 2012 turns 

out to be of positive value.

2.7.6 <TNI>

The TNI is an index given by the difference in normalized anomalies of SST between the 

Niño 1 + 2 and Niño 4 regions, where the Niño 1 + 2 region spans 0–10 °S. and 80– 90 °W. and the 

Niño 4 region spans 5 °S.–5 °N. and 160 °E.–150 °W.70 Hence, TNI can be regarded as the gradient 

in SST across the Pacific region where ENSO events develop.

Figure 34(a) displays the yearly variation of <TNI>.71 For the interval 1945–2010, <TNI> 

averages about –0.19 °C, having sd = 1.128 °C and range = –2.246 to 3.096 °C. For the two
70

First Difference (fd(<TNI>)) Difference (d(<TNI>)) 0.3

0

–0.3

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<TNI>)t

 = <TNI>(10-yma)t+1 – <TNI>(10-yma)t

 sd = 0.117

1965 1975 1985 1995 2005

Year

(c)

(b)

(a)

1950–1989: mean = –0.018

sd = 0.109 

1990–2004: mean = –0.013

sd = 0.140

⇒t = –0.14

⇒cl <90%

1945–1994: mean = –0.137

sd = 0.961 

1995–2010: mean = –0.359

sd = 1.568

⇒t = 0.682 

⇒cl <90%

<TNI>

4

2

0

–2

2

4

0

–2

–4

d(<TNI>)t

 = <TNI>(yearly)t – <TNI>(10-yma)t

 sd = 1.057

1945–2010

<TNI>

mean = –0.19

sd = 1.128

range = –2.246 to 3.096

intervals, 1945–1994 and 1995–2010, the difference in means is found not to be statistically important 

(t = 0.68, cl <90%). The spikes in <TNI> do not always correspond to the years when anomalous 

ENSO events occur. For example, the 2 yr of most positive <TNI> (3.096 and 2.985 °C) are 1983 and 

1998, but only the year 1998 is associated with an anomalous ENSO extreme event (LN) (the year 

1983 follows an EN event). Similarly, the 2 yr of most negative <TNI> (–2.246 and –2.149 °C) are 

2004 and 2003, but only the year 2004 is associated with an ENSO extreme event (EN) (the year 2003 

precedes the 2004 EN event). In terms of the 10-yma of <TNI>, it essentially has been flat (with 

excursions of about ±0.4 °C), at least until fairly recently (about 1982). The 10-yma of <TNI> was 

negative in value between 1957 and 1970, varying between –0.016 and –0.491 °C, except for the year 

1960 (0.022 °C), positive in value between 1971 and 1980, varying between 0.068 and 0.246 °C, then 

negative once again from 1981 through 2005, varying between –0.021 and –0.944 °C, except for the 

year 1996 (0.013 °C). The 10-yma of <TNI> has its most negative value (–0.944 °C) in 2005 (it was 

–0.903 °C in 2006). For the 10-yma of <TNI> to become positive in value in 2007, the yearly <TNI> 

must measure in excess of 14.188 °C in 2012, a value that is about 4.6 times larger than the previously observed largest positive value of 3.096 °C in 1983. So, it seems highly unlikely that the 10-yma 

of <TNI> will be positive in value in 2007 (or anytime soon in the near-term, foreseeable future). 

Instead, it is highly probable that the 10-yma of <TNI> will remain negative in value. (Presuming 

Figure 34. Yearly variation of Trans-Niño index: (a) <TNI>, (b) difference (d<TNI>), 

and (c) first difference (fd<TNI>).
71

a yearly <TNI> = –0.359 ± 1.568 °C for 2012, the ±1 sd prediction interval about the mean for the 

current, more active interval, one expects the 10-yma of <TNI> = –0.727 ± 0.078 °C for 2007.) 

Figure 34(b) shows the yearly variation of the difference (d<TNI>t). Like the differences for 

<AT>, <ONI>, <SOI>, and <PDO>, runs testing indicates that the distribution of differences for 

<TNI> appears to be random (z = –1.54, cl <90%, sd = 1.057 °C). Given that the distribution of 

differences appears random, one should have expected the 10-yma of <TNI> = –0.562 ± 1.057 °C 

for 2006, where –0.562 °C is the yearly <TNI> for 2006 and 1.057 °C is the sd of the differences. 

As it turns out, the yearly <TNI> = 1.044 °C in 2011 (considerably more positive in value than 

the yearly <TNI> = –0.452 °C that was observed in 2010), thereby yielding the 10-yma of <TNI> 

= –0.903 °C in 2006 (more positive in value than the –0.944 °C measured in 2005). For 2007, based on 

the observed differences, one anticipates the 10-yma of <TNI> = –1.444 ± 1.057 °C, where –1.444 °C 

is the yearly <TNI> for 2007. A value of the 10-yma of <TNI> = –1.444 °C in 2007 means that the 

yearly <TNI> = –14.692 °C in 2012 (a value about 6.5 times more negative than the most negative 

value of –2.246 °C in 2004), while a value more negative (positive) than –1.444 °C for the 10-yma of 

<TNI> in 2007 means that the yearly <TNI> for 2012 will be more negative (positive) as well. (An 

increase or decrease of 0.001 °C in the 10-yma of <TNI> for 2007 changes the 2012 estimate for the 

yearly <TNI> by 0.020 °C, accordingly.) 

Figure 34(c) depicts the yearly variation of the first difference (fd<TNI>t). While the difference in means for the two intervals 1950–1989 and 1990–2004 indicates that the distribution of first 

differences appears random (t = –1.40, cl <90%), runs testing suggests that the distribution of first 

differences is nonrandom (z = –4.35, cl >99.9%, sd = 0.117 °C). Presuming that the first differences 

are indeed distributed nonrandomly, one should have expected the 10-yma of <TNI> = –0.944 – 

0.013 ± 0.140 °C, or about –0.957 ± 0.14 °C for 2006, where –0.944 °C is the 10-yma of <TNI> 

for 2005 and –0.013 and 0.14 °C, respectively, are the mean first difference and sd for the current, 

more active interval. As noted above, the 2011 season actually had <TNI> = 1.044 °C (more positive than the –0.452 °C measured in 2010), thereby yielding the 10-yma of <TNI> = –0.903 °C for 

2006 and fd<TNI>t = 0.041 °C for 2005. For 2007, one anticipates the 10-yma of <TNI> = –0.903 

– 0.013 ± 0.14 °C, or about –0.916 ± 0.14 °C, which, if true, suggests that the yearly value of <TNI> 

= –4.132 ± 2.8 °C for 2012 (i.e., the ±1 sd prediction interval is –1.132 to –6.932 °C, inferring that the 

yearly <TNI> should be negative in value for 2012).

From table 22, one finds that the difference in the means for <TNI> is not statistically important when comparing the mean of <TNI> during the 16 ENY against the mean of <TNI> during 

the 15 LNY (t = –1.65, cl <90%), or when comparing the mean of <TNI> during the 30 yr when 

<ONI> was positive in value against the mean of <TNI> during the 31 yr when <ONI> was negative in value (t = –1.18, cl <90%). Hence, strong correlation between yearly values of <TNI> and 

<ONI> seems unlikely (i.e., the two parameters are of the same sign in only 25 of the 62 yr in the 

interval 1950–2011). 

From table 23(f), for <TNI> ‘+,’ NTC = 10 ± 2 (55.3%), NTC <8 (15.5%), and NTC >12 

(29.3%); NTS = 4 ± 2 (75.7%), NTS <2 (5.4%), and NTS >6 (18.9%); NH = 6 ± 2 (69.2%), NH <4 

(13.7%), and NH >8 (17.1%); NMH = 3 ± 1 (61.5%), NMH <2 (19.3%), and NMH >4 (19.2%); and 

NUSLFH = 1 ± 1 (73.6%) and NUSLFH >2 (26.4%). For <TNI> “–,” NTC = 10 ± 2 (55.2%), NTC 
72

<8 (15.2%), and NTC >12 (29.6%); NTS = 4 ± 2 (75.6%), NTS <2 (5.5%), and NTS >6 (18.9%); NH 

= 6 ± 2 (69.1%), NH <4 (13.3%), and NH >8 (17.5%); NMH = 2 ± 1 (67.1%), NMH = 0 (8%), and 

NMH >3 (24.9%); and NUSLFH = 1 ± 1 (79.4%) and NUSLFH >2 (20.6%).

The monthly value of TNI for January 2012 measures 1.356 °C and is part of a string of 

positive TNI values. The string of positive TNI values now spans 18 mo, having begun in August 

2010, with the February 2011 value being 1.851 °C. In the interval December 1949–January 2011, 

the longest string of positive TNI values spans 40 mo, between September 1973 and December 1976, 

averaging 1.397 °C and ranging 0.066 to 2.354 °C. Five other long positive strings have occurred 

during the interval 1949–2011: (1) 27 mo, between November 1949 and January 1952, averaging 

0.803 °C and ranging 0.119 to 1.627 °C; (2) 23 mo, between December 1954 and October 1956, averaging 0.577 °C and ranging 0.045 to 1.119 °C; (3) 26 mo, between November 1970 and December 

1972, averaging 0.638 °C and ranging 0.087 to 1.659 °C; (4) 22 mo, between September 1982 and 

June 1984, averaging 2.142 °C and ranging 0.092 to 4.501 °C; and (5) 27 mo, between April 1997 and 

June 1999, averaging 2.521 °C and ranging 0.174 to 3.484 °C. Since 1950, the nominal hurricane season has had considerably more negative values than positive values, 235 to 137. Thus, the possibility 

exists that the present string of positive values in TNI may soon end and that the year 2012 might be 

of negative value as suggested from above.

2.7.7 <MEI>

Originally, the MEI was defined as the first seasonally varying principal component of six 

atmosphere-ocean variable fields in the tropical Pacific basin, based on the Comprehensive OceanAtmosphere Data Set (COADS).72,73 The six variables included sea level pressure (SLP), zonal and 

meridional components of the surface wind, SST, surface air temperature, and total fractional cloudiness of the sky. A more simplified method, based only on the Hadley Center SLP and SST (called 

MEI.ext),74 is also available for use.

Figure 35(a) displays the yearly variation of <MEI>.75 For the interval 1945–2010, <MEI> 

averages about 0.039, having sd = 0.768 and range = –1.607 to 1.65. For the two intervals, 1945–

1994 and 1995–2010, the difference in means is found not to be statistically important (t = –0.36, 

cl <90%). Like <NAO>, <PDO>, and <TNI>, the spikes in the yearly <MEI> do not always correspond to the years when anomalous ENSO events occur. For example, the 2 yr of most positive 

<MEI> (1.594 and 1.650) are 1983 and 1987, but only the year 1987 is associated with an anomalous 

ENSO extreme event (EN) (the year 1983 follows an EN event); however, the 2 yr of most negative 

<MEI> (–1.607 and –1.426), 1955 and 1971, are both associated with ENSO extreme events (LN). 

In terms of the 10-yma of <MEI>, it always is negative in value prior to 1978 and always positive 

in value from 1978. During the interval 1955–1977, the 10-yma <MEI> varied between –0.011 and 

–0.491, and during the interval 1978–2005, the 10-yma <MEI> varied between 0.01 and 0.58 (the 

value decreased slightly from 0.081 to 0.047 between 2005 and 2006). For the 10-yma of <MEI> to 

become negative in value in 2007, the yearly <MEI> must measure less than 0.414 in 2012, a value 

well within the range of previously observed values in the interval 1950–2010. (Presuming a yearly 

<MEI> = 0.103 ± 0.638 for 2012, the ±1 sd prediction interval about the mean for the current, more 

active interval, one expects the 10-yma of <MEI> = –0.016 ± 0.032 for 2007.) 
73

First Difference (fd(<TNI>)) Difference (d(<TNI>)) 0.3

0

–0.3

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<TNI>)t

 = <TNI>(10-yma)t+1 – <TNI>(10-yma)t

 sd = 0.117

1965 1975 1985 1995 2005

Year

(c)

(b)

(a)

1950–1989: mean = –0.018

sd = 0.109 

1990–2004: mean = –0.013

sd = 0.140

⇒t = –0.14

⇒cl <90%

1945–1994: mean = –0.137

sd = 0.961 

1995–2010: mean = –0.359

sd = 1.568

⇒t = 0.682 

⇒cl <90%

<TNI>

4

2

0

–2

2

4

0

–2

–4

d(<TNI>)t

 = <TNI>(yearly)t – <TNI>(10-yma)t

 sd = 1.057

1945–2010

<TNI>

mean = –0.19

sd = 1.128

range = –2.246 to 3.096

Figure 35(b) shows the yearly variation of the difference (d<MEI>t). Runs testing indicates 

that the distribution of differences for <MEI> appears to be random (z = –1.25, cl <90%, sd = 0.713). 

Given that the distribution of differences appears random, one should have expected the 10-yma of 

<MEI> = 0.307 ± 0.713 for 2006, where 0.307 is the yearly <MEI> for 2006 and 0.713 is the sd of 

the differences. As it turns out, the yearly <MEI> = –0.935 in 2011 (considerably more negative in 

value than the yearly <MEI> = –0.429 that was observed in 2010), thereby yielding the 10-yma of 

<MEI> = 0.047 in 2006 (a value smaller than the 0.081 measured in 2005). For 2007, based on the 

observed differences, one anticipates the 10-yma of <MEI> = –0.337 ± 0.713, where –0.337 is the 

yearly <MEI> for 2007. A value of the 10-yma of <MEI> = –0.337 in 2007 means that the yearly 

<MEI> = –6.326 in 2012 (a value about 3.9 times more negative than the most negative value of 

–1.607 in 1955), while a value more negative (positive) than –0.337 for the 10-yma of <MEI> in 

2007 means that the yearly <MEI> for 2012 will be more negative (positive) as well. (An increase or 

decrease of 0.001 in the 10-yma of <MEI> for 2007 changes the 2012 estimate for the yearly <MEI> 

by 0.02, accordingly.) 

Figure 35. Yearly multivariate ENSO index: (a) <MEI>, (b) difference (d<MEI>), 

and (c) first difference (fd<MEI>).
74

Figure 35(c) depicts the yearly variation of the first difference (fd<MEI>t). While the difference in means for the two intervals 1955–1989 and 1990–2004 indicates that the distribution of first 

differences appears nonrandom (t = 2.18, cl >95%), runs testing suggests that the distribution of first 

differences is random (z = –1.66, cl <90%, sd = 0.079). Presuming that the first differences are indeed 

distributed randomly, one should have expected the 10-yma of <MEI> = 0.081 ± 0.079 for 2006, 

where 0.081 is the 10-yma of <MEI> for 2005 and 0.079 is the sd of the first differences. As noted 

above, the 2011 season actually had <MEI> = –0.935 (more negative than the –0.429 measured in 

2010), thereby yielding the 10-yma of <MEI> = 0.047 for 2006 and fd<TNI>t = –0.034 for 2005. For 

2007, one anticipates the 10-yma of <MEI> = 0.047 ± 0.079, which, if true, suggests that the yearly 

value of <MEI> = 1.354 ± 1.58 for 2012 (i.e., the ±1 sd prediction interval is –0.226 to 2.934).

From table 22, one finds that the difference in the means for <MEI> is highly statistically 

important when comparing the mean of <MEI> during the 16 ENY against the mean of <MEI> 

during the 15 LNY (t = 7.81, cl >99.9%), or when comparing the mean of <MEI> during the 30 yr 

when <ONI> was positive in value against the mean of <MEI> during the 31 yr when <ONI> was 

negative in value (t = 10.85, cl >99.9%). Hence, strong correlation between yearly values of <MEI> 

and <ONI> seems very likely (i.e., the two parameters are of the same sign in 59 of the 62 yr in the 

interval 1950–2011, being of different signs only in 1959, 1978 an 1981). 

From table 23(g), for <MEI> ‘+,’ NTC = 10 ± 2 (54.6%), NTC <8 (14.6%), and NTC >12 

(30.7%); NTS = 4 ± 2 (72.7%), NTS <2 (4.2%), and NTS >6 (23.1%); NH = 6 ± 2 (69.6%), NH <4 

(14.9%), and NH >8 (15.5%); NMH = 2 ± 1 (68.1%), NMH = 0 (8.5%), and NMH >4 (23.4%); and 

NUSLFH = 1 ± 1 (79.4%) and NUSLFH >2 (20.6%). For <MEI> ‘–,’ NTC = 10 ± 2 (55.2%), NTC 

<8 (15.3%), and NTC >12 (29.5%); NTS = 4 ± 2 (79.6%), NTS <2 (8.8%), and NTS >6 (11.6%); NH 

= 6 ± 2 (66.2%), NH <4 (9.3%), and NH >8 (24.5%); NMH = 3 ± 1 (60.7%), NMH <2 (16.5%), and 

NMH >4 (22.8%); and NUSLFH = 1 ± 1 (79.6%) and NUSLFH >2 (20.4%).

The monthly value of MEI for January, February, and March 2012 measures, respectively, 

–1.046, –0.702, and –0.41 and is part of a string of negative MEI values. The string of negative MEI 

values now spans 22 mo, having begun in June 2010, with the September 2010 value being –2.037. 

In the interval January 1950–March 2011, the longest string of negative MEI values spans 37 mo, 

between May 1973 and May 1976, averaging –1.245 and ranging –0.131 and –2. Three other long 

negative strings have occurred during the interval 1950–2011: (1) 35 mo, between April 1954 and 

February 1957, averaging –1.344 and ranging –0.356 to –2.276; (2) 26 mo, between May 1961 and 

June 1963, averaging –0.591 and ranging –0.038 to –1.093; and (3) 25 mo, between April 1970 and 

April 1972, averaging –1.057 and ranging –0.056 to –1.898. Since 1950, the nominal hurricane season 

has had essentially equal numbers of positive and negative values of MEI, 187 to 185. Thus, as yet, 

one cannot know with any certainty as to whether the yearly <MEI> for 2012 will be positive or 

negative in value. Because of the inferred strong relationship between the yearly <ONI> and <MEI> 

and because the ENSO condition is expected to be ENSO neutral to EN-like, the year 2012 may turn 

out to be positive in value (with <SOI> being negative in value).

2.7.8 <GSSTEI>

The University of Washington Joint Institute for the Study of the Atmosphere and Ocean 

has developed a new experimental index, called the GSSTEI, with values available only through 
75

February 2011. The index is taken as the average SST equatorward of 20 deg latitude (north and 

south) minus the average SST poleward of 20 deg latitude (north and south), with anomalies determined relative to the 1950–1979 period. The number of observations contributing to the index is at 

least 1,000 per month, using product data from the International COADS. Because GSSTEI has not 

been updated since February 2011, this index, unfortunately, will not serve as a potential useful predictor for the frequency and strength of tropical cyclones in the 2012 hurricane season.

Figure 36(a) displays the yearly variation of <GSSTEI>.76 For the interval 1945–2010, 

<GSSTEI> averages about 0.062 °C, having sd = 0.171 °C and range = –0.349 to 0.474 °C. For the 

two intervals, 1945–1994 and 1995–2010, the difference in means is found to be only of marginal statistical importance (t = –1.94, cl >90%). Like <NAO>, <PDO>, <TNI>, and <MEI>, the spikes in 

the yearly <GSSTEI> do not always correspond to the years when anomalous ENSO events occur. 

For example, the 2 yr of most positive <GSSTEI> (0.395 and 0.474 °C) are 1983 and 1987, but only 

the year 1987 is associated with an anomalous ENSO extreme event (EN) (the year 1983 follows an 

EN event); however, the 2 yr of most negative <GSSTEI> (–0.349 and –0.317 °C), 1950 and 1955, 

are both associated with ENSO extreme events (LN). In terms of the 10-yma of <GSSTEI>, it 

always is negative in value prior to 1960 and always positive in value from 1960. During the interval 

1950–1959, the 10-yma <GSSTEI> varied between –0.03 and –0.134 °C, and during the interval 

1960–2005, the 10-yma <GSSTEI> varied between 0.008 and 0.204 °C (the last available 10-yma 

value of <GSSTEI> measures 0.079 °C in 2005, up from 0.044 °C in 2004). For the 10-yma of 

<GSSTEI> to become negative in value in 2006, the yearly <GSSTEI> must measure more negatively 

than –1.946 °C, a value more than 5.5 times larger in negative value than ever seen. Consequently, one 

expects the 10-yma of <GSSTEI> to remain positive in value, at least for the near-term, foreseeable 

future. (Presuming a yearly <GSSTEI> = 0.092 ± 0.141 for 2011, the ±1 sd prediction interval about 

the mean for the current, more active interval, one would have expected the 10-yma of <GSSTEI> 

= 0.102 ± 0.007 for 2006.) 

Figure 36(b) shows the yearly variation of the difference (d<GSSTEI>t). Runs testing indicates that the distribution of differences for <GSSTEI> appears to be random (z = –1.23, cl <90%, 

sd = 0.15 °C). Given that the distribution of differences appears random, one should have expected 

the 10-yma of <GSSTEI> = 0.118 ± 0.15 for 2006, where 0.118 is the yearly <GSSTEI> for 2006 

and 0.15 is the sd of the differences. Because the yearly value of <GSSTEI> for 2011 is unknown, 

one cannot determine how well the projection for the 10-yma of <GSSTEI> was for 2006. (For 2007, 

one expects the 10-yma of <GSSTEI> = 0.068 ± 0.15 °C.)

Figure 36(c) depicts the yearly variation of the first difference (fd<GSSTEI>t). Both the 

difference in means for the two intervals 1950–1989 and 1990–2004 and runs testing indicate that 

the distribution of first differences appears nonrandom (t = 2.11, cl >95%; z = –3.88, cl >99.9%, 

sd = 0.019 °C). Presuming that the first differences are indeed distributed nonrandomly, one should 

have expected the 10-yma of <GSSTEI> = 0.079 – 0.006 ± 0.015 °C, or 0.073 ± 0.015 °C for 2006, 

where 0.079 °C is the 10-yma of <GSSTEI> for 2005 and 0.006 and 0.015 °C is the mean and sd of 

the first differences for the current, more active interval. (To predict the value for 2007, one needs to 

know the 10-yma value of <GSSTEI> for 2006.)
76

First Difference (fd(<GSSTEI>)) –0.05

0

0.05

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<GSSTEI>)t

 = <GSSTEI>(10-yma)t+1 – <GSSTEI>(10-yma)t

 sd = 0.019

d(<GSSTEI>)t

 = <GSSTEI>(yearly)t – <GSSTEI>(10-yma)t

 sd = 0.15

1965 1975 1985 1995 2005

(c) Year

1950–1989: mean = 0.006

sd = 0.02 

1990–2004: mean = –0.006

sd = 0.015

⇒t = 2.107

⇒cl >95%

1945–1994: mean = 0.053

sd = 0.018 

1995–2010: mean = 0.092

sd = 0.141

⇒t = –1.938 

⇒cl >90%

Difference (d(<GSSTEI>)) –0.3

0

0.3

0.5 1945–2010

<GSSTEI>

(b)

<GSSTEI> –0.5

0

(a)

mean = 0.062

sd = 0.171

range = –0.349 to 0.474

From table 22, one finds that the difference in the means for <GSSTEI> is statistically important 

when comparing the mean of <GSSTEI> during the 16 ENY against the mean of <GSSTEI> 

during the 15 LNY (t = 4.43, cl >99.9%), or when comparing the mean of <GSSTEI> during the 

30 yr when <ONI> was positive in value against the mean of <GSSTEI> during the 31 yr when 

<ONI> was negative in value (t = 7.08, cl >99.9%). Hence, strong correlation between yearly values 

of <GSSTEI> and <ONI> seems likely (i.e., the two parameters are of the same sign in 46 of the 

61 yr in the interval 1950–2010). 

From table 23(h), for <GSSTEI> ‘+,’ NTC = 10 ± 2 (55.4%), NTC <8 (15.8%), and NTC >12 

(28.8%); NTS = 4 ± 2 (73.4%), NTS <2 (4.4%), and NTS >6 (22.2%); NH = 5 ± 2 (69.2%), NH <3 

(6.7%), and NH >7 (24.1%); NMH = 2 ± 1 (56.6%), NMH = 0 (9.2%), and NMH >4 (34.3%); and 

NUSLFH = 1 ± 1 (78.7%) and NUSLFH >2 (21.3%). For <GSSTEI> ‘–,’ NTC = 11 ± 2 (54.8%), 

NTC <9 (14.6%), and NTC >13 (30.6%); NTS = 4 ± 2 (79.6%), NTS <2 (8.8%), and NTS >6 

(11.6%); NH = 6 ± 2 (65.5%), NH <4 (8.7%), and NH >8 (25.8%); NMH = 3 ± 1 (59.4%), NMH <2 

(14.1%), and NMH >4 (26.5%); and NUSLFH = 1 ± 1 (75.7%) and NUSLFH >2 (24.3%).

Figure 36. Yearly variations of global sea surface temperature: (a) <GSSTEI>, (b) difference 

(d<GSSTEI>), and (c) first difference (fd<GSSTEI>).
77

Presently, there are no monthly values of GSSTEI available after February 2011. Consequently, one cannot determine its yearly values for 2011 or project values for 2012. 

2.7.9 <JMASSTM>

While ONI and SOI are two chief measures most often used to describe and characterize the 

onset dates, intensities, and durations of ENSO events, another index that has come into recent use 

is the JMASST index. This index is a 5-mo running mean of spatially averaged SST anomalies over 

the tropical Pacific Ocean, between 4 °S.–4 °N. latitude and 150–90 °W. longitude. When the index is 

0.5 °C or greater for at least 6 consecutive months, the ENSO year of October through the following 

September is categorized as El Niño (warm phase), while when the index is –0.5 °C or more negative for at least 6 consecutive months, the ENSO year of October through the following September 

is categorized as La Niña (also called El Viejo, or cold phase, by the JMA). When neither anomaly 

is occurring, the ENSO year is categorized as neutral. (Recall that in this study, the ENSO condition 

is determined from monthly ONI values, with a year being denoted ENY, LNY, or NY based on 

whether the anomaly is operative for at least 4 of the 6-mo nominal hurricane season.)

The JMASST index can be found at <ftp://www.coaps.fsu.edu/pub/JMA_SST_Index/>. Two 

tabulations are available: (1) the mean values and (2) the anomalies, where the anomalies are derived 

from the means by subtracting ‘normals’ or ‘monthly climatological means’ used by the JMA. The 

monthly normals are 25.4, 26.2, 26.9, 27.1, 26.6, 26.1, 25.2, 24.6, 24.6, 24.6, 24.6, and 24.9 °C, representing, respectively, the months of January–December. As an example, the mean JMASST index 

for January 2012 is 25.1 °C and the anomaly is –0.3 °C (= 25.1 – 25.4 °C).

Figure 37(a) displays the yearly variation of the JMASST index using the means (i.e., 

<JMASSTM>). For the interval 1949–2010, <JMASSTM> averages about 25.6 °C, having 

sd = 0.6 °C and range = 24.5 to 27.4 °C. For the two intervals, 1949–1994 and 1995–2010, the difference in means is found not to be statistically important (t = –1.1, cl <90%). The spikes in the yearly 

<JMASSTM> correspond to years when anomalous ENSO events occur, warmer positive spikes 

with EN events and cooler negative spikes with LN events. In terms of the 10-yma of <JMASSTM>, 

it always is equal to or below the mean of 25.6 °C prior to 1978 and always above the mean from 1978 

onwards. In 2005, the 10-yma of <JMASSTM> measured 25.8 °C. For the 10-yma of <JMASSTM> 

to fall below the mean in 2006, the yearly <JMASST> must measure cooler than 21.3 °C, much 

cooler than has ever been seen (24.5 °C in 1955). As it turns out, the yearly <JMASSTM> measured 

25.3 °C in 2011, thereby yielding the 10-yma <JMASSTM> = 25.8 °C in 2006, a value unchanged 

from that of the previous year. For 2012, the yearly <JMASSTM> is expected to be about 25.6 

± 0.6 °C (i.e., the ±1 sd prediction interval about the mean), suggesting that the 10-yma <JMASSTM> 

= 25.76 ± 0.03 °C for 2007, a value slightly higher than the mean. For the 10-yma <JMASSTM> 

= 25.6 °C or cooler, the yearly <JMASSTM> = 22.5 °C or cooler in 2012, a value also cooler than 

ever been seen. Consequently, one does not expect the 10-yma <JMASSTM> to fall below the mean 

in the near-term, foreseeable future. (The January–March 2012 values of JMASST, respectively, are 

25.1, 26.2, and 26.9 °C, and the ENSO condition is presently categorized as neutral.)

Figure 37(b) shows the yearly variation of the difference (d<JMASSTM>t). Runs testing indicates that the distribution of differences for <JMASSTM> appears to be random (z = –0.71, cl <90%, 
78

First Difference (fd(<JMASSTM>)) –0.15

–0.1

–0.05

0

0.05

0.1

0.15

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<JMASSTM>)t

 = <JMASSTM>(10-yma)t+1 – <JMASSTM>(10-yma)t

 sd = 0.06

1965 1975 1985 1995 2005

Year

(c)

1954–1989: mean = 0.011

sd = 0.053 

1990–2010: mean = –0.001

sd = 0.068

⇒t = 0.677

⇒cl <90%

 Difference (d(<JMASSTM>))

–2

–1

0

1

2

d(<JMASSTM>)t

 = <JMASSTM>t – <JMASSTM>(10-yma)t

 sd = 0.6

(b)

1949–1994: mean = 25.567

sd = 0.636 

1995–2010: mean = 25.769

sd = 0.627

⇒t = –1.098

⇒cl <90%

1949–2010

<JMASSTM>

<JMASSTM>

24

25

26

27

28

(a)

mean = 25.6

sd = 0.6

range = 24.5 to 27.4

sd = 0.6 °C). Given that the distribution of differences appears random, one should have expected 

the 10-yma of <JMASSTM> = 26.1 ± 0.6 °C for 2006, where 26.1 °C is the yearly <JMASSTM> 

for 2006 and 0.6 °C is the sd of the differences. From above, the yearly <JMASSTM> = 25.3 °C in 

2011 and the 10-yma <JMASSTM> = 25.8 °C in 2006. For 2007, the 10-yma <JMASSTM> = 25.2 

± 0.6 °C, based on the observed differences, 25.2 °C being the yearly <JMASSTM> for 2007. Hence, 

Figure 37. Yearly JMA SST mean index: (a) <JMASSTM>, (b) difference (d<JMASSTM>), 

and (c) first difference (fd<AJMASSTM>).
79

one expects the yearly <JMASSTM> = 14.5 ± 12 °C, or ≤26.5 °C (i.e., the upper limit of the ±1 sd

prediction interval) in 2012.

Figure 37(c) depicts the yearly variation of the first difference (fd<JMASSTM>t). Both the 

difference in means for the two intervals 1954–1989 and 1990–2004 and runs testing indicate that the 

distribution of first differences appears random (t = 0.68, cl <90%; z = –1.10, cl <90%, sd = 0.06 °C). 

Presuming that the first differences are indeed distributed randomly, one should have expected the 

10-yma of <JMASSTM> = 25.8 ± 0.06 °C for 2006, where 25.8 °C is the 10-yma of <JMASSTM> 

for 2005 and 0.06 °C is the sd of the first differences, inferring a yearly <JMASSTM> = 25.3 ± 1.2 °C 

in 2011. As it turns out, the yearly <JMASSTM> = 25.3 °C in 2011, thereby yielding the 10-yma 

<JMASSTM> = 25.8 °C in 2006. For 2007, one expects the 10-yma<JMASSTM> = 25.8 ± 0.06 °C, 

inferring the yearly <JMASSTM> = 26.5 ± 1.2 °C in 2012.

From table 22, one finds that the difference in the means for <JMASSTM> is statistically 

important when comparing the mean of <JMASSTM> during the 16 ENY against the mean 

of <JMASSTM> during the 15 LNY (t = 9.43, cl >99.9%), or when comparing the mean of 

<JMASSTM> during the 30 yr when <ONI> was positive in value against the mean of <JMASSTM> 

during the 31 yr when <ONI> was negative in value (t = 10.53, cl >99.9%). Hence, strong correlation 

between yearly values of <JMASSTM> and <ONI> seems highly likely.

From table 23(i), for <JMASSTM> ‘+,’ NTC = 10 ± 2 (56.5%), NTC <8 (18.4%), and NTC 

>12 (25.1%); NTS = 4 ± 2 (76.2%), NTS <2 (5.6%), and NTS >6 (18.2%); NH = 5 ± 2 (69.7%), NH 

<3 (7%), and NH >7 (23.3%); NMH = 2 ± 1 (69.6%), NMH = 0 (9.7%), and NMH >3 (20.7%); 

and NUSLFH = 1 ± 1 (66.7%) and NUSLFH >2 (33.3%). For <JMASSTM> ‘–,’ NTC = 11 ± 2 

(54.3%), NTC <9 (19.3%), and NTC >13 (26.4%); NTS = 4 ± 2 (74.8%), NTS <2 (14.7%), and NTS 

>6 (10.5%); NH = 6 ± 2 (66.7%), NH <4 (9.8%), and NH >8 (23.5%); NMH = 3 ± 1 (61.4%), NMH 

<2 (14.6%), and NMH >4 (24%); and NUSLFH = 1 ± 1 (76.8%) and NUSLFH >2 (23.2%).

2.7.10 <NTA>

The NTA is an experimental time series of SST anomalies based on the COADS dataset for 

the interval 1951–1991 and the National Centers for Environmental Prediction dataset afterwards. 

The SST data are averaged over two regions: 6–18 °N. latitude and 20–60 °W. longitude and over 

6–10 °N. latitude and 10–20 °W. longitude. It is calculated relative to the 1951–2000 climatology, 

smoothed by a 3-mo running mean procedure, and projected onto 20 leading empirical orthogonal 

functions.77–79

Figure 38(a) displays the yearly variation of <NTA>.80 For the interval February 1951–

December 2010, <NTA> averages about 0.063 °C, having sd = 0.28 °C and range = –0.495 to 

0.915 °C. For the two intervals, 1951–1994 and 1995–2010, the difference in means is found to be 

statistically important (t = –5.687, cl >99.9%). The spikes in the yearly <NTA> do not always correspond to years when anomalous ENSO events occur. For example, the five largest positive spikes are 

0.501 (1958), 0.545 (1969), 0.555 (1998), 0.624 (2005), and 0.915 (2010) °C. Of these, only the spikes 

of 1969 (EN), 1998 (LN), and 2010 (LN) are associated with the occurrences of ENSO anomalies. Similarly, the five largest negative spikes are –0.286 (1954), –0.239 (1965), –0.304 (1972), –0.495 
80

First Difference (fd(<NTA>)) –0.05

0

0.05

0.1

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<NTA>)t

 = <NTA>(10-yma)t+1 – <NTA>(10-yma)t

 sd = 0.026

d(<NTA>)t

 = <NTA>(yearly)t – <NTA>(10-yma)t

 sd = 0.226

1965 1975 1985 1995 2005

Year

(c)

1956–1989: mean = –0.000

sd = 0.023 

1990–2004: mean = 0.024

sd = 0.024

⇒t = –3.323

⇒cl >99.8%

Difference (d(<NTA>)) –0.5

0

0.5

1

(b)

<NTA> –0.5

–1

0

0.5

1

1951–2010

<NTA>

(a)

1951–1994: mean = –0.037

sd = 0.227 

1995–2010: mean = 0.339

sd = 0.225

⇒t = –5.687 

⇒cl >99.9%

mean = 0.063

sd = 0.280

range = –0.495 to 0.915

(1974), and –0.286 (1994) °C. Of these, only the spike of 2005 is not associated with an ENSO 

anomaly. While the other largest negative spikes are associated with ENSO anomalies, the types are 

different: the spikes of 1954 and 1974 are both associated with LNY events, and the spikes of 1965 

and 1972 are both associated with ENY events. In terms of the 10-yma of <NTA>, it was relatively 

flat between 1956 and the late 1960s, becoming negative between 1968 and 1981 (–0.165 °C in 1975) 

and positive thereafter, except for the years 1988, 1989, and 1990. Values have been increasingly more 

positive in value of late, perhaps peaking about 2005 (0.347 °C in 2005). (Monthly values of NTA 

have not been updated beyond December 2010.)

Figure 38. North Tropical Atlantic index yearly variation: (a) <NTA>, (b) difference 

(d<NTA>), and (c) first difference (fd<NTA>). 
81

Figure 38(b) shows the yearly variation of the difference (d<NTA>t). Runs testing indicates that the distribution of differences for <NTA> appears to be random (z = –1.064, cl <90%, 

sd = 0.226 °C). Given that the distribution of differences appears random, one should have expected 

the 10-yma of <NTA> = 0.412 ± 0.226 °C for 2006, where 0.412 °C is the yearly <NTA> for 2006 

and 0.226 °C is the sd of the differences. Hence, one expected a 10-yma <NTA> of 0.186–0.638 °C in 

2006 (it measured 0.347 °C in 2005 with a difference of 0.277 °C), inferring a yearly <NTA> = 1.001 

± 4.52 °C in 2011. Unfortunately, monthly values of NTA have not been published beyond December 2010, as noted above. 

Figure 38(c) depicts the yearly variation of the first difference (fd<NTA>t). Both the difference in means for the two intervals 1954–1989 and 1990–2004 and runs testing indicate that the 

distribution of first differences appears nonrandom (t = –3.32, cl >99.8%; z = –2.51, cl >98%, sd

= 0.026 °C). Presuming that the first differences are indeed distributed nonrandomly, one should 

have expected the 10-yma of <NTA> = 0.347 + 0.024 ± 0.024 °C, or 0.371 ± 0.024 °C for 2006, 

where 0.347 °C is the 10-yma of <NTA> for 2005 and 0.024 and 0.024 °C, respectively, are the mean 

and sd of the first differences for the current, more active interval, inferring a yearly <NTA> = 

–0.183 ± 0.48 °C in 2011.

From table 22, one finds that the difference in the means for <NTA> is not statistically important when comparing the mean of <NTA> during the 16 ENY against the mean of <NTA> during 

the 14 LNY (t = 0.552, cl <90%; <NTA> for 1950, a LNY, is not available). However, when comparing the mean of <NTA> during the 30 yr when <ONI> was positive in value against the mean of 

<NTA> during the 30 yr when <ONI> was negative in value, one finds that the difference in means 

is statistically important (t = 2.12, cl >95%). Hence, strong correlation between yearly values of 

<NTA> and <ONI> possibly exists (i.e., the two parameters were of the same sign in 36 of the 60 yr 

in the interval 1951–2010.)

From table 23(j), for <NTA> ‘+,’ NTC = 12 ± 2 (52.2%), NTC <10 (19.7%), and NTC >14 

(28.1%); NTS = 5 ± 2 (73%), NTS <3 (9.8%), and NTS >7 (17.2%); NH = 7 ± 2 (65.4%), NH <5 

(15.5%), and NH >9 (19.2%); NMH = 3 ± 1 (59.7%), NMH = <2 (14.6%), and NMH >4 (25.8%); 

and NUSLFH = 1 ± 1 (66.7%) and NUSLFH >2 (33.3%). For <NTA> ‘–,’ NTC = 8 ± 2 (60.4%), 

NTC <6 (13.3%), and NTC >10 (26.3%); NTS = 3 ± 2 (79.3%), NTS = 0 (2.1%), and NTS >5 

(18.6%); NH = 4 ± 2 (73.5%), NH <2 (4.5%), and NH >6 (22.1%); NMH = 1 ± 1 (77.8%) and NMH 

>2 (22.2%); and NUSLFH = 1 ± 1 (78.9%) and NUSLFH >2 (21.2%).

2.7.11 <CAR>

Like NTA, the CAR index is an experimental time series of SST anomalies based on the 

COADS dataset for the interval 1951–1991 and the National Centers for Environmental Prediction 

dataset afterwards. The SST data are averaged over the region approximately bounded by 10–26 °N. 

latitude and the open waters region eastward of Mesoamerica to 60 °W. It is calculated relative to the 

1951–2000 climatology, smoothed by a 3-mo running mean procedure, and projected onto 20 leading empirical orthogonal functions.77 (The Caribbean Sea region appears to be getting warmer and 

wetter with the passage of time.81,82)
82

Figure 39(a) displays the yearly variation of <CAR>.83 For the interval February 1951–

December 2010, <CAR> averages about 0.033 °C, having sd = 0.159 °C and range = –0.332 to 

0.384 °C. For the two intervals, 1951–1994 and 1995–2010, the difference in means is found to be 

statistically important (t = –4.399, cl >99.9%). Like the yearly <NTA>, the spikes in the yearly 

<CAR> do not always correspond to the years when anomalous ENSO events occur. For example, 

while the three largest positive spikes are 0.337 (1958), 0.384 (1998), and 0.265 (2005), only the spike 

of 1998 is associated with an ENSO anomaly (LN); the spike of 1958 follows the 1957 EN and 

the spike of 2005 follows the 2004 EN. Similarly, while the three largest negative spikes are –0.256 

(1971), –0.312 (1974), and –0.332 (1976) °C, only the largest negative spike is not associated with an 

ENSO anomaly; the other two were associated with LN events. In terms of the 10-yma <CAR>, its 

behavior mimics somewhat that of the 10-yma <NTA>, being relatively flat early on (through about 

1962), declining between 1962 and 1972 to its most negative value, –0.143 °C, then rising to a peak 

of 0.189 °C in 2002 and remaining relatively flat through 2005 (0.177 °C). Between 1982 and 2005, all 

10-yma values of <CAR> are positive, except for 1988 and 1989 (–0.009 and –0.012 °C, respectively). 

As with monthly values of NTA, monthly values of CAR have not been updated beyond December 

2010.

Figure 39(b) shows the yearly variation of the difference (d<CAR>t). Runs testing indicates 

that the distribution of differences for <CAR> appears to be random (z = –1.006, cl <90%, sd

= 0.123 °C). Given that the distribution of differences appears random, one should have expected 

the 10-yma of <CAR> = 0.164 ± 0.123 °C for 2006, where 0.164 °C is the yearly <CAR> for 2006 

and 0.123 °C is the sd of the differences. Hence, one expected a 10-yma <NTA> of 0.041–0.287 °C 

in 2006 (it measured 0.177 °C in 2005 with a difference of 0.013 °C), inferring a yearly <NTA> 

= –0.352 ± 2.46 °C in 2011. Unfortunately, as noted above for NTA, monthly values of CAR have 

not been published beyond December 2010. 

Figure 39(c) depicts the yearly variation of the first difference (fd<CAR>t). Both the difference in means for the two intervals 1954–1989 and 1990–2004 and runs testing indicate that 

the distribution of first differences appears nonrandom (t = –2.72, cl >99%; z = –2.68, cl >99%, 

sd = 0.017 °C). Presuming that the first differences are indeed distributed nonrandomly, one should 

have expected the 10-yma of <NTA> = 0.177 + 0.011 ± 0.014 °C, or 0.188 ± 0.014 °C for 2006, 

where 0.177 °C is the 10-yma of <CAR> for 2005 and 0.011 °C and 0.014 °C, respectively, are the 

mean and sd of the first differences for the current, more active interval, inferring a yearly <CAR> 

= 0.128 ± 0.28 °C in 2011.

From table 22, one finds that the difference in the means for <CAR> is only of marginal statistical importance when comparing the mean of <CAR> during the 16 ENY against the mean of 

<CAR> during the 14 LNY (t = 1.99, cl >90%; <CAR> for 1950, a LNY, is not available). However, 

when comparing the mean of <CAR> during the 30 yr when <ONI> was positive in value against 

the mean of <CAR> during the 30 yr when <ONI> was negative in value, one finds that the difference in means is statistically important (t = 3.12, cl >99.5%). Hence, strong correlation between 

yearly values of <CAR> and <ONI> possibly exists (i.e., the two parameters were of the same sign 

in 38 of the 60 yr in the interval 1951–2010.)
83

First Difference (fd(<CAR>)) –0.05

0

0.05

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<CAR>)t

 = <CAR>(10-yma)t+1 – <CAR>(10-yma)t

 sd = 0.017

d(<CAR>)t

 = <CAR>(yearly)t – <CAR>(10-yma)t

 sd = 0.123

1965 1975 1985 1995 2005

Year

(c)

1956–1989: mean = –0.002

sd = 0.016 

1990–2004: mean = 0.011

sd = 0.014

⇒t = –2.718

⇒cl >99%

Difference (d(<CAR>))

0

0.5

(b)

<CAR> –0.5

0

0.5

1951–2010

<CAR>

(a)

1951–1994: mean = –0.015

sd = 0.147 

1995–2010: mean = 0.163

sd = 0.111

⇒t = –4.399

⇒cl >99.9%

mean = 0.033

sd = 0.159

range = –0.332 to 0.384

From table 23(k), for <CAR> ‘+,’ NTC = 11 ± 2 (53%), NTC <9 (16.1%), and NTC >13 

(30.9%); NTS = 5 ± 2 (73.4%), NTS <3 (10.5%), and NTS >7 (16.1%); NH = 6 ± 2 (67.1%), NH <4 

(10.1%), and NH >8 (22.8%); NMH = 3 ± 1 (61.6%), NMH = <2 (19.9%), and NMH >4 (18.5%); 

and NUSLFH = 1 ± 1 (82.4%) and NUSLFH >2 (17.6%). For <CAR> ‘–,’ NTC = 9 ± 2 (57.8), NTC 

<7 (14.7%), and NTC >11 (27.5%); NTS = 4 ± 2 (79.5%), NTS <2 (8.7%), and NTS >6 (11.8%); NH 

= 5 ± 2 (70.9%), NH <3 (7.8%), and NH >7 (21.3%); NMH = 2 ± 1 (70.8%), NMH = 0 (11%) and 

NMH >3 (18.3%); and NUSLFH = 1 ± 1 (77.3%) and NUSLFH >2 (22.7%).

Figure 39. Caribbean index yearly variation: (a) <CAR>, (b) difference (d<CAR>), 

and (c) first difference (fd<CAR>).
84

2.7.12 <QBO>

The quasi-biennial oscillation (QBO) refers to the quasi-periodic oscillation of the equatorial 

zonal winds (in ms–1) in the tropical stratosphere, having a mean period of about 28 mo (range 20 to 

36 mo) that was first discovered in the 1950s.84–87 The winds alternate between easterlies (generally 

the stronger winds) and westerlies (generally the longer lasting winds at higher levels, but shorter 

lasting winds at lower levels), first developing at the top of the stratosphere and propagating slowly 

downwards at the rate of about 1 km per month until they dissipate at the tropical tropopause. 

The phase of the QBO has previously been linked to the frequency of North Atlantic basin tropical cyclones, with increased activity occurring during westerly (positive) zonal wind anomalies and 

decreased activity during the easterly (negative) zonal wind anomalies.35

Figure 40(a) displays the variation of the yearly <QBO> index as measured for the 30 mbar 

height.88,89 For the interval 1948–2010, <QBO> averages about –3.65 ms–1, having sd = 7.94 ms–1

and range = –17.13 to 10.17 ms–1. For the two intervals, 1948–1994 and 1995–2010, the difference in 

means is found not to be statistically important (t = –0.07, cl <90%). The 25 positive yearly <QBO> 

values correspond to years when westerlies dominate and the 38 negative yearly <QBO> values 

correspond to years when easterlies dominate. The average positive yearly <QBO> measures 4.69 

± 2.86 ms–1 (range 0.85 to 10.17 ms–1) and the average negative yearly <QBO> measures 

–9.14 ± 4.74 ms–1 (range –0.55 to –17.13 ms–1). Hence, the easterlies, on average, are about twice 

as strong as the westerlies based on the 30 mbar data. Regarding the 10-yma <QBO>, it has been 

continuously negative throughout the entire interval 1953–2005, varying between –2.3 ms–1 in 1990 

and –4.6 ms–1 in 2005. The 10-yma <QBO> in 2005 is essentially the same value as was measured in 

1953 (–4.57 ms–1).

For the interval January 1948–December 2011, there were 317 positive QBO monthly values 

and 451 negative QBO monthly values. The positive QBO monthly values have occurred in 27 runs, 

averaging about 11 ± 3.7 mo in length (range 2 to 16 mo), while the negative QBO monthly values 

have occurred in 27 runs, averaging 16 ± 6.1 mo in length (range 3 to 39 mo; this excludes the current run of negative QBO monthly values that started in August 2011 and continues today, at least 

through March 2012). For the 64 yr (1948–2011), all months more often have been of negative QBO 

monthly value, except April and May (33 and 32 mo, respectively, of positive QBO monthly value). 

For 2012, because the current string of negative QBO monthly values measures 8 mo in length 

(through March 2012) and the average length of a negative QBO monthly run is 16 mo, it may be that 

negative QBO monthly values will continue for most of the remainder of the year, making the yearly 

<QBO> negative in value (i.e., the occurrence of dominate easterly wind at 30 mbar height in 2012). 

Also supporting this view is the observation that back-to-back positive yearly <QBO> has occurred 

only twice during the interval 1948–2010 (the years 1966–1967 and 1975–1976). Since the year 2011 

turned out to be of positive <QBO>, it appears more likely that the yearly <QBO> for 2012 will be 

of negative value (indicative of ENSO neutral or EN-like conditions).

For the interval 1948–2011, the nominal hurricane season (June–November) has more often 

been of negative QBO monthly value than of positive QBO monthly value (238 versus 146 mo). For 

the years 1948–1952, 1954, 1956, 1958, 1960, 1962, 1965, 1967, 1968, 1970, 1972, 1974, 1977, 1979, 

1981, 1984, 1986, 1989, 1991, 1994, 1996, 1998, 2000, 2001, 2003, 2005, 2007, and 2009, all months 
85

First Difference (fd(<QBO>))

0

–0.5

–1

–1.5

0.5

1

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<QBO>)t

 = <QBO>(10-yma)t+1 – <QBO>(10-yma)t

 sd = 0.372

d(<QBO>)t

 = <QBO>(yearly)t – <QBO>(10-yma)t

 sd = 8.06

1965 1975 1985 1995 2005

Year

(c)

1953–1989: mean = 0.061

sd = 0.313 

1990–2004: mean = –0.123

sd = 0.471

⇒t = 1.65

⇒cl <90%

Difference (d(<QBO>))

15

10

5

0

–5

–10

–15

(b)

<QBO> –20

–15

–10

–5

0

5

10 1948–2010

<QBO>

(a)

1948–1994: mean = –3.686

sd = 6.897 

1995–2010: mean = –3.519

sd = 10.727

⇒t = –0.072 

⇒cl <90%

mean = –3.65

sd = 7.94

range = –17.13 to 10.17

Figure 40. Quasi-Biennial Oscillation index yearly variation: (a) <QBO>, (b) difference 

(d<QBO>), and (c) first difference (fd<QBO>).
86

during the nominal hurricane season were of negative QBO monthly value. For the years 1953, 1976, 

1983, 1988, 1993, and 2011, 4–5 mo of the nominal hurricane season were of negative QBO monthly 

value. For the years 1955, 1957, 1961, 1966, 1969, 1971, 1973, 1975, 1978, 1980, 1985, 1990, 1997, 

1999, 2002, 2004, 2006, and 2008, all months during the nominal hurricane season were of positive 

QBO monthly value. For the years 1959, 1995, and 2010, 4–5 mo of the nominal hurricane season 

were of positive QBO monthly value. Only the years of 1963, 1964, 1982, 1987, and 1992 were years 

that were evenly divided between negative and positive QBO monthly values during the nominal 

hurricane season.

Comparison of years since 1950 with ENY, LNY, and NY (as defined in this study) shows the 

following: 

(1) When the nominal hurricane season is of negative QBO monthly value for all months of 

the hurricane season (true for 30 of the 62 seasons), 7 of the seasons were classified ENY, 6 were 

classified LNY, and 17 were classified NY. 

(2) When the nominal hurricane season is of negative QBO monthly value for 4–5 mo of the 

hurricane season (true for 6 of the 62 seasons), none was classified ENY, 1 was classified LNY, and 

5 were classified NY. 

(3) When the nominal hurricane season is of positive QBO monthly value (true for 18 of the 

62 seasons), 6 of the seasons were classified ENY, 6 were classified LNY, and 6 were classified NY. 

(4) When the nominal hurricane season is of positive QBO monthly value for 4–5 mo of the 

hurricane season (true for 3 of the 62 seasons), none was classified ENY, 1 was classified LNY, and 

2 were classified NY. 

(5) When the nominal hurricane season is evenly divided between positive and negative QBO 

monthly values (true for 5 of the 62 seasons), 3 of the seasons were classified ENY, one was classified LNY, and one was classified NY. Thus, the occurrence of positive/negative QBO monthly values 

during the nominal hurricane season provides no clear indication as to whether the season will be 

classified ENY, LNY, or NY. 

Figure 40(b) shows the yearly variation of the difference (d<QBO>t). Runs testing indicates 

that the distribution of differences for <QBO> appears to be nonrandom (z = 5.03, cl >99.9%, 

sd = 8.06 ms–1). Presuming instead that the distribution of differences is random, one would have 

expected the 10-yma of <QBO> = 4.47 ± 8.06 ms–1 for 2006, where 4.47 ms–1 is the yearly <QBO> 

for 2006 and 8.06 ms–1 is the sd of the differences. For 2011, its yearly <QBO> = 1.96 ms–1, thereby 

yielding the 10-yma <QBO> = –3.82 ms–1 in 2006 (up from –4.6 ms–1 in 2005), well within the 

predicted range. However, for 2007, presuming a random distribution of the differences yields an 

expected 10-yma <QBO> = –15.91 ± 8.06 ms–1, or about –23.97 to –7.85 ms–1, where –15.91 ms–1 is 

the yearly <QBO> for 2007, which plainly is well outside the range of previously observed 10-yma 

<QBO> values (i.e., –2.3 to –4.6 ms–1) and implies a yearly <QBO> value for 2012 that is completely 

unreasonable.
87

Figure 40(c) depicts the yearly variation of the first difference (fd<QBO>t). Both the difference in means for the two intervals 1953–1989 and 1990–2004 and runs testing indicate that the distribution of first differences appears random (t = 1.65, cl <90%; z = 0.30, cl <90%, sd = 0.37

ms–1). 

Presuming that the first differences are indeed distributed randomly, one should have expected the 

10-yma of <QBO> = –4.6 ± 0.37 ms–1 for 2006, where –4.6 ms–1 is the 10-yma of <QBO> for 2005 

and 0.3 ms–1 is the sd of the first differences, inferring a yearly <QBO> = –13.7 ± 7.4 ms–1 in 2011. 

As it turns out, the yearly <QBO> = 1.96 in 2011, thereby yielding the 10-yma <QBO> = –3.82 ms–1

in 2006, a value just outside the ±1 sd prediction interval. For 2007, one expects the 10-yma<QBO> 

= –3.82 ± 0.37 ms–1, inferring the yearly <QBO> = –8.54 ± 7.4 ms–1 in 2012.

From table 22, one finds that the difference in the means for <QBO> is not statistically important when comparing the mean of <QBO> during the 16 ENY against the mean of <QBO> during 

the 15 LNY (t = –0.46, cl <90%), or when comparing the mean of <QBO> during the 30 yr when 

<ONI> was positive in value against the mean of <QBO> during the 31 yr when <ONI> was negative in value (t = 0.44, cl <90%). Hence, strong correlation between yearly values of <QBO> and 

<ONI> seems highly unlikely (substantiating that found above regarding the lack of preferential 

behavior between the occurrence of positive/negative QBO monthly values during the nominal hurricane season and the classification of the season as either ENY, LNY, or NY).

From table 23(l), for <QBO> ‘+,’ NTC = 11 ± 2 (54.5%), NTC <9 (20.2%), and NTC >13 

(25.3%); NTS = 4 ± 2 (73.5%), NTS <2 (4.5%), and NTS >6 (22.1%); NH = 6 ± 2 (68.1%), NH <4 

(11.3%), and NH >8 (20.6%); NMH = 3 ± 1 (61.5%), NMH <2 (19.3%), and NMH >4 (19.2%); and 

NUSLFH = 1 ± 1 (73.1%) and NUSLFH >2 (26.9%). For <QBO> “–,” NTC = 10 ± 2 (55.9%), NTC 

<8 (16.6%), and NTC >12 (27.5%); NTS = 4 ± 2 (77%), NTS <2 (6.1%), and NTS >6 (16.9%); NH 

= 6 ± 2 (69.3%), NH <4 (13.8%), and NH >8 (17%); NMH = 2 ± 1 (66.9%), NMH = 0 (7.8%), and 

NMH >3 (25.3%); and NUSLFH = 1 ± 1 (81.6%) and NUSLFH >2 (18.4%).

2.7.13 <AMO>

The AMO is defined as a fluctuation in detrended SST in the North Atlantic Ocean, north of 

the equator (0–70 °N.).90–103 The AMO has a cycle length of about 70 yr, fluctuating between warm 

(positive) and cold (negative) phases. The SST pattern has been suggested to be linked to variations 

in the strength of the Atlantic thermohaline circulation (THC), a density-driven, global circulation 

pattern that involves the movement of warm equatorial surface waters to higher latitudes and the 

subsequent cooling and sinking of these waters into the deep ocean. As such, the warm phase of the 

AMO represents intervals of faster THC, and the cold phase represents intervals of slower THC.104

Figure 41(a) displays the variation of the yearly <AMO> index.105,106 For the interval 

1948–2010, the yearly <AMO> averages about –0.002 °C, having sd = 0.191 °C and range = –0.416 

to 0.389 °C. For the two intervals 1948–1994 and 1995–2010 the difference in means is found to 

be statistically important (t = –5.023, cl >99.9%). For the interval 1948–2010, the greatest positive spike (0.389 °C) occurred in 1998 and the greatest negative spike (–0.416 °C) occurred in 1974, 

both years being classified as LNY. In terms of the 10-yma <AMO>, it always is positive in value 

for the interval 1953–1963, always negative in value for the interval 1964–1995, and again always 

positive in value from 1996 onwards. In 2005, the 10-yma of <AMO> measured 0.191 °C. For the 

10-yma of <AMO> to become negative in 2006, the yearly <AMO> must measure cooler than 
88

–3.999 °C in 2011, much cooler than has ever been seen. As it turns out, the yearly <AMO> measured 

0.126 °C in 2011, thereby yielding the 10-yma <AMO> = 0.206 °C in 2006, a value up slightly from 

0.191 °C in 2005. For 2012, the yearly <AMO> is expected to be about 0.174 ± 0.124 °C (i.e., the 

±1 sd prediction interval about the mean for the current, more active interval), suggesting that the 

10-yma <AMO> = 0.21 ± 0.06 °C for 2007. For the 10-yma <AMO> to become negative in 2007, the 

yearly <AMO> in 2012 would have to measure cooler than –4.024 °C, again a value well outside low 

the observed range since 1948. Consequently, one does not expect the 10-yma <AMO> to become 

negative anytime soon, certainly not in the near-term, foreseeable future. (The January–March 2012 

monthly values of AMO, respectively, are –0.032, 0.037, and 0.058 °C.) First Difference (fd(<AMO>))

0

–0.05

0.05

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<AMO>)t

 = <AMO>(10-yma)t+1 – <AMO>(10-yma)t

 sd = 0.021

d(<AMO>)t

 = <AMO>(yearly)t – <AMO>(10-yma)t

 sd = 0.109

1965 1975 1985 1995 2005

Year

(c)

1953–1989: mean = –0.006

sd = 0.018 

1990–2004: mean = 0.02

sd = 0.015

⇒t = –4.935

⇒cl >99.9%

Difference (d(<AMO>))

0.4

0.2

0

–0.2

(b)

<AMO> –0.5

0

0.5 1948–2010

<AMO>

(a)

1948–1994: mean = –0.062

sd = 0.173 

1995–2010: mean = 0.174

sd = 0.124

⇒t = –5.023

⇒cl >99.9%

mean = –0.002

sd = 0.191

range = –0.416 to 0.389

Figure 41. Atlantic Multidecadal Oscillation index yearly variation: (a) <AMO>,

(b) difference (d<AMO>), and (c) first difference (fd<AMO>).

For the interval 1948–2011, there were 381 positive AMO monthly values and 387 negative 

AMO monthly values (a new positive string began in February 2012). The positive AMO monthly 

values have occurred in 45 runs, averaging about 8.5 ± 14 mo in length (range 1 to 77 mo), while the 
89

negative AMO monthly values have occurred in 46 runs, averaging 8.4 ± 18.7 mo in length (range 

1 to 116 mo). For the 64 yr (1948–2011), the months of predominantly positive AMO monthly value 

include March, April, August, and September (35, 37, 34, and 34 mo, respectively), the months of 

predominantly negative AMO monthly values include January, February, May, July, October, and 

November (35, 35, 33, 34, 34, and 36 mo), respectively, and the months evenly split include June and 

December (32 mo each). For 2012, one cannot say, as yet, whether the year will be turn out to be of 

positive or negative <AMO> value. 

While one cannot strictly determine whether 2012 will be of positive or negative <AMO> 

value, one should note that 14 of the positive AMO monthly runs have had a length of only 1 mo, 

23 have had lengths of 1–2 mo, 30 have had lengths of 1–6 mo, and 37 have had lengths of 1–12 mo; 

only 8 positive AMO monthly runs have had lengths greater than 12 mo. For negative AMO monthly 

runs, 13 have had a length of only 1 mo, 20 have had lengths of 1–2 mo, 35 have had lengths of 

1–6 mo, and 40 have had lengths of 1–12 mo; only 6 negative AMO monthly runs have had lengths 

>12 mo. Thus, strings of positive and negative AMO monthly values tend to be short, 1–6 mo, 

accounting for two-thirds (30/45) of the positive runs and three-fourths (35/46) of the negative runs. 

The current string of positive AMO monthly values began in February 2012 and the AMO monthly 

value remained positive in March, meaning that the current string of positive AMO monthly values 

is, at least, 2 mo in length. (Based on yearly <AMO>, the current string of positive yearly <AMO> 

measures at least 15 yr, starting in 1997 and running through 2011, which is the longest positive 

yearly <AMO> run during the interval 1949–2011. The longest negative yearly run was 17 yr, from 

1970 through 1986.)

For the interval 1948–2011, the nominal hurricane season (June–November) has more often 

been of negative AMO monthly value than of positive AMO monthly value (196 versus 188 mo). For 

the interval 1948–1963, positive AMO monthly values dominate the nominal hurricane season (166 

versus 26 mo), with only the years 1950, 1956, and 1963 having 3 or more negative AMO monthly 

values during the nominal hurricane season—the years 1950 and 1956 were years of negative yearly 

<AMO>, equal to –0.004 and –0.014 °C, respectively, while the year 1963 measured 0.01 °C, even 

though the entire nominal hurricane season was of negative AMO monthly value. For the interval 

1964–1994, all yearly <AMO> values were of negative value, except for the years 1966 (0.01 °C), 

1969 (0.015 °C), 1987 (0.071 °C), and 1988 (0.005 °C), and negative AMO monthly values dominated 

during the nominal hurricane season (345 versus 27 mo). For the current interval 1995–2011, positive 

AMO monthly values now once again dominate the nominal hurricane season (194 versus 10 mo), 

and all years have been of positive yearly <AMO> value, except 1996 (–0.047 °C).

Comparison of years since 1950 with ENY, LNY, and NY (as defined in this study) shows the 

following: 

(1) When the nominal hurricane season is of negative AMO monthly value for all months 

of the hurricane season (true for 23 of the 62 seasons), 6 of the seasons were classified ENY, 7 were 

classified LNY, and 10 were classified NY. 

(2) When the nominal hurricane season is of negative AMO monthly value for 4–5 mo of 

the hurricane season (true for 5 of the 62 seasons), 2 were classified ENY, 1 was classified LNY, and 

2 were classified NY. 
90

(3) When the nominal hurricane season is of positive AMO monthly value for all months of 

the hurricane season (true for 19 of the 62 seasons), 5 of the seasons were classified ENY, 4 were 

classified LNY, and 10 were classified NY. 

(4) When the nominal hurricane season is of positive AMO monthly value for 4–5 mo of the 

hurricane season (true for 10 of the 62 seasons), 2 were classified ENY, 1 was classified LNY, and 

7 were classified NY. 

(5) When the nominal hurricane season is evenly divided between positive and negative AMO 

monthly values (true for 5 of the 62 seasons), none was classified ENY, 3 were classified LNY, and 

2 were classified NY. Thus, the occurrence of positive/negative AMO monthly values during the 

nominal hurricane season provides no clear indication as to whether the season will be classified 

ENY, LNY, or NY. 

Figure 41(b) shows the yearly variation of the difference (d<AMO>t). Runs testing indicates that the distribution of differences for <AMO> appears to be random (z = –0.40, cl <90%, 

sd = 0.109 °C). Given that the distribution of differences appears random, one should have expected 

the 10-yma of <AMO> = 0.287 ± 0.109 °C for 2006, where 0.287 °C is the yearly <AMO> for 2006 

and 0.109 °C is the sd of the differences. From above, the yearly <AMO> = 0.126 °C in 2011 and the 

10-yma <AMO> = 0.206 °C in 2006. For 2007, the 10-yma <AMO> = 0.169 ± 0.109 °C, based on 

the observed differences, 0.169 °C being the yearly <AMO> for 2007. Hence, one expects the yearly 

<AMO> = –0.644 ± 2.18 °C for 2012.

Figure 41(c) depicts the yearly variation of the first difference (fd<AMO>t). Both the difference in means for the two intervals 1953–1989 and 1990–2004 and runs testing indicate that the 

distribution of first differences appears nonrandom (t = –4.94, cl >99.9%; z = –5.22, cl >99.9%, 

sd = 0.021 °C). Presuming that the first differences are indeed distributed nonrandomly, one should 

have expected the 10-yma of <AMO> = 0.191 + 0.02 ± 0.015 °C, or about 0.211 ± 0.015 °C for 

2006, where 0.191 °C is the 10-yma of <AMO> for 2005 and 0.02 and 0.015 °C are the mean and 

sd of the first differences for the current, more active interval, inferring a yearly <AMO> = 0.221 

± 0.3 °C in 2011. As it turns out, the yearly <AMO> = 0.126 °C in 2011, thereby yielding the 

10-yma <AMO> = 0.206 °C in 2006. For 2007, one expects the 10-yma <AMO> = 0.206 + 0.02 

± 0.015 °C, or about 0.226 ± 0.015 °C, inferring the yearly <AMO> = 0.496 ± 0.3 °C in 2012 (i.e., 

the yearly <AMO> likely will be of positive value for 2012.)

From table 22, one finds that the difference in the means for <AMO> is not statistically 

important when comparing the mean of <AMO> during the 16 ENY against the mean of <AMO> 

during the 15 LNY (t = 0.33, cl <90%), or when comparing the mean of <AMO> during the 30 yr 

when <ONI> was positive in value against the mean of <AMO> during the 31 yr when <ONI> was 

negative in value (t = 0.64, cl <90%). Hence, strong correlation between yearly values of <AMO> 

and <ONI> seems highly unlikely.

From table 23(m), for <AMO> ‘+,’ NTC = 12 ± 2 (52.6%), NTC <10 (21.2%), and NTC >14 

(26.1%); NTS = 5 ± 2 (73.3%), NTS <3 (10.4%), and NTS >7 (16.3%); NH = 7 ± 2 (65.6%), NH <5 

(16.5%), and NH >9 (17.9%); NMH = 3 ± 1 (59.1%), NMH <2 (13.8%), and NMH >4 (27.1%); and 

NUSLFH = 1 ± 1 (73.3%) and NUSLFH >2 (26.7%). For <AMO> ‘–,’ NTC = 9 ± 2 (59.1%), NTC 
91

<7 (17.5%), and NTC >11 (23.4%); NTS = 3 ± 2 (77.1%), NTS = 0 (1.9%), and NTS >5 (21%); NH 

= 5 ± 2 (72.7%), NH <3 (9.5%), and NH >7 (17.8%); NMH = 1 ± 1 (69.6%) and NMH >2 (30.5%); 

and NUSLFH = 1 ± 1 (83.4%) and NUSLFH >2 (16.7%).

2.7.14 <AMM>

The AMM is part of a broader class of meridional modes that is characterized by an anomalous meridional SST gradient across the mean latitude of the intertropical convergence zone.107–113 

The AMM spatial pattern is defined by applying maximum covariance analysis (MCA) to SST and 

the zonal and meridional components of the 10-m wind field over the interval 1950–2005, from the 

NCEP/National Center for Atmospheric Research reanalysis.114 To determine the spatial pattern, 

the data are first defined over the region bounded by 21 °S.–32 °N. latitude and 74 °W.–15 °E. longitude and spatially smoothed, the seasonal cycle is removed, the data are detrended, a 3-mo running 

mean is applied, and the linear fit to the Cold Tongue index (a measure of ENSO variability) is subtracted from each spatial point. The spatial patterns are then defined as the first SST and winds maps 

resulting from singular value decomposition of the covariance matrix between the two fields, with 

the AMM time series being calculated by means of projecting SST (or the 10-m wind field) onto the 

spatial structure resulting from the MCA.

Figure 42(a) displays the variation of the yearly <AMM> index.115 For the interval 1948–

2010, the yearly <AMM> index averages about 0.13, having sd = 1.94 and range = –4.13 to 4.98. 

For the two intervals, 1948–1994 and 1995–2010, the difference in means is found to be statistically important (t = –2.875, cl >99%). For the interval 1948–2010, the greatest positive spike (4.98) 

occurred in 2010 and the greatest negative spike (–4.13) occurred in 1974, both years being classified 

as LNY. In terms of the 10-yma <AMM>, it always is positive in value for the interval 1953–1967, 

always negative in value for the interval 1968–1997, and again always positive in value from 1998 

onwards. In 2005, the 10-yma of <AMM> measured 1.27. For the 10-yma of <AMM> to become 

negative in 2006, the yearly <AMM> must measure less than –29.64 in 2011, much more negative in 

value than has ever been seen. As it turns out, the yearly <AMM> measured 2.48 in 2011, thereby 

yielding the 10-yma <AMM> = 1.61 in 2006, a value up slightly from 1.27 in 2005. For 2012, the 

yearly <AMM> is expected to be about 1.27 ± 1.54 (i.e., the ±1 sd prediction interval about the 

mean for the current, more active interval), suggesting that the 10-yma <AMM> = 1.75 ± 0.08 for 

2007. For the 10-yma <AMM> to become negative in 2007, the yearly <AMM> in 2012 would have 

to measure less than –33.72, again a value well outside low the observed range since 1948. Consequently, one does not expect the 10-yma <AMM> to become negative anytime soon, certainly not in 

the near-term, foreseeable future. (The January–March 2012 monthly values of AMM, respectively, 

are 3.13, 1.33, and –2.18.)

For the interval 1948–2011, there were 423 positive AMM monthly values and 345 negative 

AMM monthly values (a new negative string began in March 2012). The positive AMM monthly 

values have occurred in 57 runs, averaging about 7.4 ± 7.6 mo in length (range 1 to 32 mo), while 

the negative AMM monthly values have occurred in 56 runs, averaging 6.2 ± 8.4 mo in length (range 

1 to 55 mo). For the 64 yr (1948–2011), the months of predominantly positive AMM monthly 

value include all months except February, which is evenly split between negative and positive AMM 

monthly values. For 2012, one cannot say, as yet, whether the year will be of positive or negative 

value.
92 First Difference (fd(<AMM>))

0

–0.5

0.5

1945 1950 1955 1960 1970 1980 1990 2000 2010

fd(<AMM>)t

 = <AMM>(10-yma)t+1 – <AMM>(10-yma)t

 sd = 0.208

d(<AMM>)t

 = <AMM>(yearly)t – <AMM>(10-yma)t

 sd = 1.65

1965 1975 1985 1995 2005

Year

(c)

1953–1989: mean = –0.067

sd = 0.179 

1990–2004: mean = 0.18

sd = 0.171

⇒t = –4.564

⇒cl >99.9%

Difference (d(<AMM>))

0

–4

4

(b)

<AMM>

–5

0

5 1948–2010

<AMM>

(a)

1948–1994: mean = –0.259

sd = 1.923 

1995–2010: mean = 1.268

sd = 1.535

⇒t = –2.875 

⇒cl >99%

mean = 0.13

sd = 1.94

range = –4.13 to 4.98

Figure 42. Atlantic Meridional Oscillation index yearly variation: (a) <AMM>, (b) difference 

(d<AMM>), and (c) first difference (fd<AMM>). 

For the interval 1948–2011, the nominal hurricane season (June–November) has more often 

been of positive AMM monthly value than of negative AMM monthly value (219 versus 165 mo). 

For the interval 1948–1970, positive AMM monthly values dominate the nominal hurricane season 

(229 versus 47 mo), with only the years 1951, 1954, 1956, 1959, 1963, 1965, and 1968 having 3 or 

more negative AMM monthly values during the nominal hurricane season (only the years 1951 

and 1956 were years of positive <AMM>, equal to 1.35 and 0.92, respectively). For the interval 

1971–1986, all yearly <AMM> values were negative, except for the years 1978–1981 (0.72, 1.09, 2.34, 

and 1.84, respectively), and negative AMM monthly values dominated during the nominal hurricane 

season (70 versus 26 mo; positive AMM monthly values dominated in the years 1976, 1980 and 1981, 

with the years 1978, 1979, and 1983 being even split between positive and negative AMM monthly 

values). Since 1987, all years have been of positive <AMM> yearly value, except 1989, 1991–1994, 
93

2000, 2002, and 2009, with positive AMM monthly values once again dominating the nominal hurricane season (95 versus 49 mo).

Comparison of years since 1950 with ENY, LNY, and NY (as defined in this study) shows the 

following:

(1) When the nominal hurricane season is of negative AMM monthly value for all months 

of the hurricane season (true for 13 of the 62 seasons), 6 of the seasons were classified ENY, 3 were 

classified LNY, and 4 were classified NY. 

(2) When the nominal hurricane season is of negative AMM monthly value for 4–5 mo of 

the hurricane season (true for 9 of the 62 seasons), 3 were classified ENY, 4 were classified LNY, and 

2 were classified NY.

(3) When the nominal hurricane season is of positive AMM monthly value for all months 

of the hurricane season (true for 16 of the 62 seasons), one of the seasons was classified ENY, 

5 were classified LNY, and 10 were classified NY.

(4) When the nominal hurricane season is of positive AMM monthly value for 4–5 mo of the 

hurricane season (true for 18 of the 62 seasons), 5 were classified ENY, 3 were classified LNY, and 

10 were classified NY.

(5) When the nominal hurricane season is evenly divided between positive and negative AMM 

monthly values (true for 6 of the 62 seasons), one was classified ENY, none was classified LNY, and 

5 were classified NY. Thus, the occurrence of positive/negative AMM monthly values during the 

nominal hurricane season provides no clear indication as to whether the season will be classified 

ENY, LNY, or NY. 

Figure 42(b) shows the yearly variation of the difference (d<AMM>t). Runs testing indicates 

that the distribution of differences for <AMM> appears to be random (z = 0.21, cl <90%, sd = 1.65). 

Given that the distribution of differences appears random, one should have expected the 10-yma of 

<AMM> = 1.73 ± 1.65 for 2006, where 1.73 is the yearly <AMM> for 2006 and 1.65 is the sd of 

the differences. From above, the yearly <AMM> = 2.48 in 2011 and the 10-yma <AMM> = 1.61 in 

2006. For 2007, the 10-yma <AMM> = 1.25 ± 1.65, based on the observed differences, 1.25 being 

the yearly <AMM> for 2007. Hence, one expects the yearly <AMM> = –8.72 ± 33 for 2012.

Figure 42(c) depicts the yearly variation of the first difference (fd<AMM>t). Both the difference in means for the two intervals 1953–1989 and 1990–2004 and runs testing indicate that 

the distribution of first differences appear nonrandom (t = –4.56, cl >99.9%; z = –2.47, cl >98%, 

sd = 0.208). Presuming that the first differences are indeed distributed nonrandomly, one should have 

expected the 10-yma of <AMM> = 1.27 + 0.18 ± 0.17, or about 1.45 ± 0.17 for 2006, where 1.27 is 

the 10-yma of <AMM> for 2005 and 0.18 and 0.17 are the mean and sd of the first differences for 

the current, more active interval, inferring a yearly <AMM> = –0.64 ± 3.4 in 2011. As it turns out, 

the yearly <AMM> = 2.48 in 2011, thereby yielding the 10-yma <AMM> = 1.61 in 2006. For 2007, 
94

one expects the 10-yma <AMM> = 1.61 + 0.18 ± 0.17, or about 1.79 ± 0.17, inferring the yearly 

<AMM> = 2.08 ± 3.4 in 2012.

From table 22, one finds that the difference in the means for <AMM> is not statistically 

important when comparing the mean of <AMM> during the 16 ENY against the mean of <AMM> 

during the 15 LNY (t = –0.93, cl <90%), or when comparing the mean of <AMM> during the 30 yr 

when <ONI> was positive in value against the mean of <AMM> during the 31 yr when <ONI> was 

negative in value (t = –0.18, cl <90%). Hence, strong correlation between yearly values of <AMM> 

and <ONI> seems highly unlikely.

From table 23(n), for <AMM> ‘+,’ NTC = 12 ± 2 (52.6%), NTC <10 (20.9%), and NTC 

>14 (26.5%); NTS = 5 ± 2 (74.1%), NTS <3 (12%), and NTS >7 (14%); NH = 7 ± 2 (65%), NH <5 

(14.4%), and NH >9 (20.6%); NMH = 3 ± 1 (56.7%), NMH <2 (11.3%), and NMH >4 (32.1%); and 

NUSLFH = 1 ± 1 (73.9%) and NUSLFH >2 (26.1%). For <AMM> ‘–,’ NTC = 9 ± 2 (59.5%), NTC 

<7 (19.7%), and NTC >11 (20.8%); NTS = 4 ± 2 (79.3%), NTS <2 (8.2%), and NTS >6 (12.6%); NH 

= 4 ± 2 (72.6%), NH <2 (4.2%), and NH >6 (23.2%); NMH = 1 ± 1 (80.9%) and NMH >2 (19.1%); 

and NUSLFH = 1 ± 1 (83.6%) and NUSLFH >2 (16.4%).

2.8 Correlation Analyses

In the next 14 subsections, scatter plots are shown of the 10-yma values of NTC, NTS, NH, 

NMH, and NUSLFH versus the 10-yma values of the surface air temperature and ENSO-related 

parameters discussed in the previous subsections. In each subpanel, two regressions are drawn: y1 and 

y2, where y1 is the inferred regression using the 10-yma values for the interval 1950–2010 and y2 is the 

inferred regression using only the 10-yma values for the current, more active interval 1990–2005. In 

each subpanel the arrow indicates the 10-yma value for the year 2005, and the asterisk indicates that the 

correlation is inferred to be highly statistically significant (cl >99.9%). Table 24 (see appendix) summarizes the results of the linear regression analyses for each time interval, giving the inferred regression 

equation (of the form y = a + bx, where y is the dependent variable, a is the y-intercept, b is the slope, and 

x is the independent variable), the linear regression coefficient r, the coefficient of determination r2

(a measure of the amount of variance explained by the regression), the standard error of estimate 

se, the confidence level cl, and the parametric mean and sd of y presuming no correlation against x.

Recall that there exists a minimum 10-yma value for each parameter for the year 2007 (see

fig. 1). This minimum 10-yma value is easily calculated by assuming that the yearly parametric value 

for 2012 is zero. One computes the minimum 10-yma value for the year 2007 as {2[x(2003) + x(2004) + 

... + x(2011)] + x(2002)}/20, where x(2003), x(2004), etc. are the yearly parametric values for the years 

2003, 2004, etc. As an example, the minimum 10-yma value for NTC for the year 2007 is {2[16 + 15 

+ ...+ 19] + 12}/20 = {2(147) + 12}/20 = 306/20 = 15.3. The minimum 10-yma values for the year 

2007 for NTS, NH, NMH, and NUSLFH are 7.9, 7.4, 3.7, and 1.95, respectively. Because a negative value for each of the yearly parametric values for the year 2012 (or any year) is not allowed, the 

10-yma parametric value is the smallest allowable 10-yma parametric value for the year in question 

(in this case, the year 2007). 
95

For each subsection, the expected 10-yma value for the independent variable (i.e., <AT>, 

<SOI>, <ONI>, etc.) is given and used in the inferred regressions to estimate the 10-yma value 

for the dependent variables. This value is then compared to various estimates using the minimum 

10-yma parametric value, the long-term mean, and the mean for the current, more active interval. It 

is important to remember that, based on the Poisson distribution for the current, more active interval, there is only about 1 chance in 8 of having NTC >19, about 1 chance in 22 of having NTS >11, 

about 1 chance in 4 of having NH >11, about 1 chance in 10 of having NMH >6, and about 1 chance 

in 8 of having NUSLFH >3.

2.8.1 NTC, NTS, NH, NMH, and NUSLFH Versus <AT>

Figure 43 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <AT>. For all comparisons the inferred linear regressions 

are found to be positive (i.e., the y parametric value increases as the x parametric value increases) and 

highly statistically significant. Also, for all comparisons the inferred regressions based upon the current, more active interval are the stronger of the two, having inferred linear correlation coefficients 

r = 0.87–0.97, as compared to r = 0.5–0.9. Therefore, it appears reasonable to assume that, having

a reliable estimate for the 10-yma value of <AT>, one should be able to reliably estimate the 10-yma 

value of the parameter in question. 

Recall from section 2.7.1 that, based on the expected first difference fd(<AT>)t, the 

10-yma <AT> = 10.04 ± 0.05 °C for 2007 (i.e., the ±1 sd prediction interval). Applying the value 

10.04 °C in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, NH, NMH, 

and NUSLFH for 2007, these being, respectively, about 14.4 ± 0.6, 6.7 ± 0.5, 7.8 ± 0.1, 3.7 ± 0.2, and 

2 ± 0.2 (i.e., the ±1 se prediction intervals). Comparison of these estimates with the minimum values 

for the 10-yma parameters for the year 2007 indicates that, while the estimates for NH, NMH, and 

NUSLFH might be tenable, the estimates for NTC and NTS are not; they simply are too low (i.e., 

they result in the year 2012 having negative frequencies for NTC and NTS). In order to have meaningful estimates for the 10-yma values of NTC and NTS, presuming the validity of the inferred linear 

regressions, a higher 10-yma <AT> must occur in 2007, one of value >10.04 °C, inferring a yearly 

<AT> higher than 10.3 °C for 2012 (recall that the 10-yma <AT> = 10.04 ± 0.05 °C in 2007 implies 

that the yearly <AT> for 2012 should be between 9.3 and 11.3 °C). Accepting the above 10-yma 

values for NH, NMH, and NUSLFH, based on using the 10-yma <AT> = 10.04 °C, implies yearly 

values of 6–10, 0–4, and 0–5, respectively, in 2012. A higher 10-yma <AT> in 2007 results in higher 

expected frequencies for NH, NMH, and NUSLFH in 2012.

For NTC, its long-term mean is about 11 ± 4, and its mean for the current, more active interval is about 15 ± 5 (i.e., the ±1 sd prediction intervals). Presuming NTC = 11 ± 4 in 2012 yields the 

10-yma NTC = 15.85 ± 0.2 for 2007, while presuming NTC = 15 ± 5 in 2012 yields the 10-yma NTC 

= 16.05 ± 0.25 for 2007. Such values suggest higher 10-yma for <AT> equal to 10.19 ± 0.03 °C and 

10.22 ± 0.02 °C, respectively, for 2007, these values being higher than the 10.04 ± 0.05 °C suggested 

for 2007 from the expected fd(AT>)t. Accepting these temperatures, however, implies a yearly <AT> 

in 2012 that has never been seen before (i.e., <AT> >12.7 °C in 2012; the highest observed yearly 

<AT> is 10.59 °C in 2007).
96

NUSLFH10-yma

0

2

4

9 9.5 10 10.5

 y2

 = (r = 0.873, se = 0.2)*

y1

 = (r = 0.501, se = 0.3)*

<AT>10-yma

(e)

NMH10-yma

1

3

5

y2

 = (r = 0.972, se = 0.2)*

 y1

 = (r = 0.636, se = 0.7)*

(d)

NH10-yma

4

7

10

y2

 = (r = 0.98, se = 0.1)*

y1

 = (r = 0.821, se = 0.5)*

(c)

NTS10-yma

2

5

8 y2

 = (r = 0.904, se = 0.5)*

y1

 = (r = 0.804, se = 0.7)*

(b)

NTC10-yma

8

12

16 y2

 = (r = 0.971, se = 0.6)*

y1

 = (r = 0.896, se = 0.8)*

(a)

Figure 43. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <AT>.
97

Similarly, for NTS, its long-term mean is about 5 ± 2, and its mean for the current, more 

active interval is about 7 ± 2. Presuming NTS = 5 ± 2 in 2012 yields the 10-yma NTS = 8.15 ± 0.1 for 

2007, while presuming NTS = 7 ± 2 in 2012 yields the 10-yma NTS = 8.25 ± 0.1 for 2007. Such values suggest even higher 10-yma for <AT> equal to 10.34 ± 0.02 °C and 10.36 ± 0.02 °C, respectively, 

for 2007. As with NTC, accepting these higher temperatures implies a yearly <AT> in 2012 that is 

completely unreasonable (i.e., <AT> >15.9 °C). Hence, the 10-yma <AT> for 2007 appears destined 

to be a statistical outlier, with respect to NTC and NTS. (For 2006, the 10-yma <AT> was 10 °C, 

inferring the 10-yma values for NTC, NTS, NH, NMH, and NUSLFH to be 14.08 ± 0.6, 6.5 ± 0.5, 

7.59 ± 0.1, 3.52 ± 0.2, and 1.91 ± 0.2, respectively. The observed 10-yma values for 2006 turned out 

to be 15.7, 8, 7.7, 3.8, and 2. Hence, the differences between the observed and inferred values are 2.7, 

3, 1.1, 1.4, and 0.05 se.)
98

2.8.2 NTC, NTS, NH, NMH, and NUSLFH Versus <SOI>

Figure 44 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <SOI>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be positive and highly statistically significant, 

having r = 0.83–0.97. Therefore, having a reliable estimate for the 10-yma value of <SOI> should 

allow one to reliably estimate the 10-yma value of the parameter in question.

Recall from section 2.7.3 that, based on the expected first difference fd(<SOI>)t, the 10-yma 

<SOI> = 1.18 ± 0.52 for 2007 (i.e., the ±1 sd prediction interval). Applying the value 1.18 in the y2

regressions results in estimates for the 10-yma values of NTC, NTS, NH, NMH, and NUSLFH for 

2007, these being, respectively, about 16.69 ± 0.5, 8.03 ± 0.3, 8.66 ± 0.4, 4.48 ± 0.3, and 2.36 ± 0.2 

(i.e., the ±1 se prediction intervals). Comparison of these estimates with the minimum values for the 

10-yma parameters for the year 2007 indicates that all estimates exceed the minimum values, suggesting that they might be tenable. (Recall that the 10-yma <SOI> = 1.18 ± 0.52 for 2007 implies that 

the yearly <SOI> for 2012 should be between –2.3 and –23.1, values indicative of ENSO neutral to 

EN-like conditions in 2012.)

For NTC, a 10-yma value 16.69 ± 0.5 in 2007 suggests a yearly value of about 18–38 in 

2012. For NTS, a 10-yma value 8.03 ± 0.3 in 2007 suggests a yearly value of about 0–9 in 2012. For 

NH, a 10-yma value 8.66 ± 0.4 in 2007 suggests a yearly value of about 17–33 in 2012. For NMH, 

a 10-yma value 4.48 ± 0.3 in 2007 suggests a yearly value of about 10–22 in 2012. For NUSLFH, 

a 10-yma value 2.36 ± 0.2 in 2007 suggests a yearly value of about 4–12 in 2012. In comparison to the 

Poisson distributions for the current, more active interval, all ±1 se prediction intervals for the 2012 

season seem too high, suggesting, perhaps, that the 10-yma <SOI> for 2007 is likely too high (i.e., 

the 10-yma <SOI> probably should be <1.18 in 2007 and the yearly <SOI> for 2012 probably should 

be more negative than –12.7, which suggests that 2012 likely will be an ENY). (For 2006, the 10-yma 

<SOI> was 0.87, inferring the 10-yma values for NTC, NTS, NH, NMH, and NUSLFH to be 16.33 

± 0.5, 7.82 ± 0.3, 8.5 ± 0.4, 4.34 ± 0.3, and 2.3 ± 0.2, respectively. Hence, the differences between the 

observed and inferred values are –1.26, 0.6, –2, –1.8, and –1.5 se, respectively.) 
99

NUSLFH10-yma

0

2

4

–5 0 5

y1

 = (r = 0.184, se = 0.4)

y2

 = (r = 0.83, se = 0.2)*

<SOI>10-yma

(e) NMH10-yma

1

3

5

y1

 = (r = 0.363, se = 0.8)

y2

 = (r = 0.938, se = 0.3)*

(d) NH10-yma

4

7

10

y1

 = (r = 0.177, se = 0.9)

y2

 = (r = 0.902, se = 0.4)*

(c) NTS10-yma

2

5

8

y1

 = (r = –0.202, se = 1.1)

y2

 = (r = 0.959, se = 0.3)*

(b) NTC10-yma

8

12

16

y1

 = (r = –0.038, se = 1.8)

y2

 = (r = 0.966, se = 0.5)*

(a)

Figure 44. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH,

and (e) NUSLFH versus 10-yma values of <SOI>.
100

2.8.3 NTC, NTS, NH, NMH, and NUSLFH Versus <ONI>

Figure 45 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <ONI>. For all comparisons the inferred linear regressions based on the current, more active interval are found to be negative (i.e., the parameters vary 

inversely) and highly statistically significant (except for NUSLFH), having r = –0.72 to –0.89. Therefore, having a reliable estimate for the 10-yma value of <ONI> should allow one to reliably estimate 

the 10-yma value of the parameter in question.

Recall from section 2.7.2 that, based on the expected first difference fd(<ONI>)t, the 10-yma 

<ONI> = 0.12 ± 0.05 °C for 2007 (i.e., the ±1 sd prediction interval). Applying the 10-yma value 

<ONI> = 0.12 in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, NH, 

NMH, and NUSLFH for 2007, these being, respectively, about 13.37 ± 1, 6.15 ± 0.6, 7.23 ± 0.5, 3.25 

± 0.4, and 1.77 ± 0.3 (i.e., the ±1 se prediction intervals). Comparison of these estimates with the 

minimum values for the 10-yma parameters for the year 2007 indicates that the estimates for NTC, 

NTS, NH, and NMH are too low. For NUSLFH, the ±1 se prediction interval barely exceeds the 

minimum values, with NUSLFH = 1.95–2.03, suggesting that it possibly is tenable. (Recall that the 

10-yma <ONI> = 0.12 ± 0.05 °C for 2007 implies that the yearly <ONI> for 2012 should be more 

positive in value than –0.1 °C, an expected value indicative of ENSO neutral to possibly EN-like 

conditions in 2012.)

For NTC, NTS, NH, and NMH, a 10-yma value of <ONI> = 0.12 °C in 2007 simply is too 

high to be meaningful. A lower (more negative) value closer to zero should be expected, indicating, 

perhaps, that ENSO neutral conditions likely will persist in 2012. For NUSLFH, a 10-yma value of 

1.95–2.03 implies NUSLFH equal to about 0–2 in 2012. A more negative value of the 10-yma value 

of NUSLFH increases the expected yearly NUSLFH in 2012. A 10-yma <ONI> = 0 °C in 2007 

implies 10-yma values of NTC, NTS, NH, NMH, and NUSLFH of 15.45 ± 1, 7.31 ± 0.6, 8.14 ± 0.5, 

4.03 ± 0.4, and 2.11 ± 0.3 in 2007. (For 2006, the 10-yma <ONI> was 0.14 °C, inferring the 10-yma 

values for NTC, NTS, NH, NMH, and NUSLFH to be 13.03 ± 1, 5.95 ± 0.6, 7.08 ± 0.5, 3.12 ± 0.4, 

and 1.72 ± 0.3, respectively. Hence, the differences between the observed and inferred values are 2.67, 

1.15, –0.88, –0.58, and –0.37 se, respectively.)
101

NUSLFH10-yma

0

2

4

–0.5 0 0.5

y1

 = (r = 0.165, se = 0.3)

y2

 = (r = –0.718, se = 0.3)

y1

 = (r = 0, se = 0.8)

y2

 = (r = –0.877, se = 0.4)*

y1

 = (r = 0.133, se = 0.9)

y2

 = (r = –0.845, se = 0.5)*

y1

 = (r = 0.259, se = 1.1)

y2

 = (r = –0.877, se = 0.6)*

y1

 = (r = 0.221, se = 1.9)

y2

 = (r = –0.893, se = 1)*

<ONI>10-yma

(e) NMH10-yma

1

3

5

(d) NH10-yma

4

7

10

(c) NTS10-yma

2

5

8

(b) NTC10-yma

8

12

16

(a)

Figure 45. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH,

and (e) NUSLFH versus 10-yma values of <ONI>. 
102

2.8.4 NTC, NTS, NH, NMH, and NUSLFH Versus <NAO>

Figure 46 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <NAO>. For all comparisons the inferred linear regressions based on the current, more active interval are found to be negative (i.e., the parameters vary 

inversely) and highly statistically significant, having r = –0.81 to –0.97. Therefore, having a reliable 

estimate for the 10-yma value of <NAO> should allow one to reliably estimate the 10-yma value of 

the parameter in question.

Recall from section 2.7.4 that, based on the expected first difference fd(<NAO>)t, the 10-yma 

<NAO> = –0.19 ± 0.03 for 2007 (i.e., the ±1 sd prediction interval). Applying the 10-yma value 

<NAO> = –0.19 in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, NH, 

NMH, and NUSLFH for 2007, these being, respectively, about 16.75 ± 0.6, 7.93 ± 0.5, 8.82 ± 0.3, 

4.57 ± 0.2, and 2.35 ± 0.3 (i.e., the ±1 se prediction intervals). Comparison of these estimates with 

the minimum values for the 10-yma parameters for the year 2007 indicates that all estimates exceed 

the minimum values, suggesting that they might be tenable. (Recall that the 10-yma <NAO> = –0.19 

± 0.03 for 2007 implies that the yearly <NAO> for 2012 should be between –0.34 and –1.54.)

For NTC, a 10-yma value 16.75 ± 0.6 in 2007 suggests a yearly value of about 17–41 in 2012. 

For NTS, a 10-yma value 7.93 ± 0.5 in 2007 suggests a yearly value of about 0–11 in 2012. For 

NH, a 10-yma value 8.82 ± 0.3 in 2007 suggests a yearly value of about 22–34 in 2012. For NMH, 

a 10-yma value 4.57 ± 0.2 in 2007 suggests a yearly value of about 13–21 in 2012. For NUSLFH, 

a 10-yma value 2.35 ± 0.3 in 2007 suggests a yearly value of about 2–14 in 2012. (For 2006, the 

10-yma <NAO> was –0.16, inferring the 10-yma values for NTC, NTS, NH, NMH, and NUSLFH 

to be 16.33 ± 0.6, 7.7 ± 0.5, 8.62 ± 0.3, 4.41 ± 0.2, and 2.28 ± 0.3, respectively. Hence, the differences 

between the observed and inferred values are –1.05, 0.6, –3.07, –3.05, and –0.93 se, respectively.) 
103

NUSLFH10-yma

0

2

4

–0.5 0 0.5

y1

 = (r = –0.274, se = 0.3)

y2

 = (r = –0.805, se = 0.3)*

y1

 = (r = –0.539, se = 0.7)*

y2

 = (r = –0.973, se = 0.2)*

y1

 = (r = –0.296, se = 0.8)

y2

 = (r = –0.96, se = 0.3)*

y1

 = (r = 0.206, se = 1.1)

y2

 = (r = –0.894, se = 0.5)*

y1

 = (r = –0.014, se = 1.9)

y2

 = (r = –0.956, se = 0.6)*

<NAO>10-yma

(e) NMH10-yma

1

3

5

(d) NH10-yma

4

7

10

(c) NTS10-yma

2

5

8

(b) NTC10-yma

8

12

16

(a)

Figure 46. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH,

and (e) NUSLFH versus 10-yma values of <NAO>.
104

2.8.5 NTC, NTS, NH, NMH, and NUSLFH Versus <PDO>

Figure 47 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <PDO>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be negative and highly statistically significant, having r = –0.77 to –0.94. Therefore, having a reliable estimate for the 10-yma value of <PDO> 

should allow one to reliably estimate the 10-yma value of the parameter in question.

Recall from section 2.7.5 that, based on the expected first difference fd(<PDO>)t, the 10-yma 

<PDO> = –0.2 ± 0.05 °C for 2007 (i.e., the ±1 sd prediction interval). Applying the 10-yma value 

<PDO> = –0.2 °C in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, 

NH, NMH, and NUSLFH for 2007, these being, respectively, about 16.66 ± 0.8, 8.04 ± 0.4, 8.62 

± 0.5, 4.43 ± 0.4, and 2.32 ± 0.3 (i.e., the ±1 se prediction intervals). Comparison of these estimates 

with the minimum values for the 10-yma parameters for the year 2007 indicates that all estimates 

exceed the minimum values, suggesting that they might be tenable. (Recall that the 10-yma <PDO> 

= –0.2 ± 0.05 °C for 2007 implies that the yearly <PDO> for 2012 should be between –1.76 and 

0.24 °C.)

For NTC, a 10-yma value 16.66 ± 0.8 in 2007 suggests a yearly value of about 11–43 in 2012. 

For NTS, a 10-yma value 8.04 ± 0.4 in 2007 suggests a yearly value of about 0–11 in 2012. For NH, 

a 10-yma value 8.62 ± 0.5 in 2007 suggests a yearly value of about 14–34 in 2012. For NMH, a 10-yma 

value 4.43 ± 0.4 in 2007 suggests a yearly value of about 7–23 in 2012. For NUSLFH, a 10-yma value 

2.32 ± 0.3 in 2007 suggests a yearly value of about 1–13 in 2012. (For 2006, the 10-yma <PDO> was 

–0.12, inferring the 10-yma values for NTC, NTS, NH, NMH, and NUSLFH to be 15.94 ± 0.8, 7.62 

± 0.4, 8.31 ± 0.5, 4.16 ± 0.4, and 2.2 ± 0.3, respectively. Hence, the differences between the observed 

and inferred values are –0.3, 0.95, –1.22, –0.9, and –0.67 se, respectively.) 
105

NUSLFH10-yma

0

2

4

–1.0 –0.5 0 0.5 1

y1

 = (r = –0.266, se = 0.4)

y2

 = (r = –0.767, se = 0.3)*

<PDO>10-yma

(e)

NMH10-yma

1

3

5

y1

 = (r = –0.481, se = 0.8)*

y2

 = (r = –0.884, se = 0.4)*

(d)

NH10-yma

4

7

10

y1

 = (r = –0.267, se = 0.9)

y2

 = (r = –0.858, se = 0.5)*

(c)

NTS10-yma

2

5

8

y1

 = (r = 0.28, se = 1.1)

y2

 = (r = –0.939, se = 0.4)*

(b)

NTC10-yma

8

12

16

y1

 = (r = 0.040, se = 1.8)

y2

 = (r = –0.935, se = 0.8)*

(a)

Figure 47. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <PDO>. 
106

2.8.6 NTC, NTS, NH, NMH, and NUSLFH Versus <TNI>

Figure 48 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <TNI>. None of the inferred regressions based on the current, more active interval are found to be statistically important. Hence, as a predictor for tropical 

cyclone activity in the North Atlantic basin, this particular parameter does not appear to be useful.
107

NUSLFH10-yma

0

2

4

–1 –0.5 0 0.5

y1

 = (r = –0.25, se = 0.4)

y2

 = (r = –0.201, se = 0.4)

<TNI>10-yma

(e)

NMH10-yma

1

3

5

y2

 = (r = 0.066, se = 0.8)

y1

 = (r = –0.25, se = 0.4)

(d)

NH10-yma

4

7

10

y1

 = (r = –0.267, se = 0.9)

y2

 = (r = 0.114, se = 1)

(c)

NTS10-yma

2

5

8

y1

 = (r = –0.504, se = 1)*

y2

 = (r = –0.374, se = 1.1)

(b)

NTC10-yma

8

12

16

y1

 = (r = –0.441, se = 1.6)*

y2

 = (r = –0.161, se = 2.1)

(a)

Figure 48. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <TNI>.
108

2.8.7 NTC, NTS, NH, NMH, and NUSLFH Versus <MEI>

Figure 49 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <MEI>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be negative and highly statistically significant, having r = –0.81 to –0.96. Therefore, having a reliable estimate for the 10-yma value of <MEI> 

should allow one to reliably estimate the 10-yma value of the parameter in question.

Recall from section 2.7.7 that, based on the expected first difference fd(<MEI>)t, the 10-yma 

<MEI> = 0.047 ± 0.079 for 2007 (i.e., the ±1 sd prediction interval). Applying the 10-yma value 

<MEI> = 0.047 in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, NH, 

NMH, and NUSLFH for 2007, these being, respectively, about 15.49 ± 0.7, 7.38 ± 0.3, 8.1 ± 0.5, 

4 ± 0.4, and 2.14 ± 0.3 (i.e., the ±1 se prediction intervals). Comparison of these estimates with the 

minimum values for the 10-yma parameters for the year 2007 indicates that all estimates, except for 

NTS, exceed the minimum values, suggesting that they might be tenable. (Recall that the 10-yma 

<MEI> = 0.047 ± 0.079 for 2007 implies that the yearly <MEI> for 2012 should be between –0.226 

and 2.934.)

For NTC, a 10-yma value 15.49 ± 0.7 in 2007 suggests a yearly value of about 0–18 in 2012. 

For NTS, a 10-yma value 7.38 ± 0.3 in 2007 simply is too low to provide a meaningful estimate of the 

yearly NTS for 2012. For NH, a 10-yma value 8.1 ± 0.5 in 2007 suggests a yearly value of about 4–24 

in 2012. For NMH, a 10-yma value 4 ± 0.4 in 2007 suggests a yearly value of about 6–14 in 2012. 

For NUSLFH, a 10-yma value 2.14 ± 0.3 in 2007 suggests a yearly value of about 0–10 in 2012. (For 

2006, the 10-yma <MEI> was 0.047, inferring the 10-yma values for NTC, NTS, NH, NMH, and 

NUSLFH to be 15.49 ± 0.7, 7.38 ± 0.3, 8.1 ± 0.5, 4 ± 0.4, and 2.14 ± 0.3, respectively. Hence, the differences between the observed and inferred values are 0.3, 2.07, –0.8, –0.5, and –0.47 se, respectively.) 
109

NUSLFH10-yma

0

2

4

–1 –0.5 0 0.5 1

y1

 = (r = –0.03, se = 0.3)

y2

 = (r = –0.805, se = 0.3)*

<MEI>10-yma

(e) NMH10-yma

y2 = (r = –0.889, se = 0.4)*

y1

 = (r = –0.225, se = 0.8)

(d) NH10-yma

4

10

7

8

y1

 = (r = –0.055, se = 0.9)

y2

 = (r = –0.855, se = 0.5)* (c) NTS10-yma

2

5 y1

 = (r = 0.222, se = 1.1)

y2

 = (r = –0.96, se = 0.3)*

(b)

1

3

5

8

NTC10-yma

12

16

y1

 = (r = 0.108, se = 1.9)

y2

 = (r = –0.945, se = 0.7)*

(a)

Figure 49. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <MEI>.
110

2.8.8 NTC, NTS, NH, NMH, and NUSLFH Versus <GSSTEI>

Figure 50 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <GSSTEI>. For all comparisons the inferred linear regressions based on the current, more active interval are found to be negative and highly statistically 

significant, having r = –0.84 to –0.95. Therefore, having a reliable estimate for the 10-yma value of 

<MEI> should allow one to reliably estimate the 10-yma value of the parameter in question.

Unfortunately, monthly values of GSSTEI have not been updated beyond February 2011, 

so the yearly value of <GSSTEI> for 2011 and the 10-yma value of <GSSTEI> for 2006 cannot be 

computed. Likewise, the 10-yma value of <GSSTEI> cannot be estimated for 2007 (which is the one 

necessary for predicting NTC, NTS, NH, NMH, and NUSLFH on the basis of <GSSTEI>).
111

NUSLFH10-yma

0

2

4

4

–0.5 0 0.5

y2

 = (r = –0.842, se = 0.2)*

y1

 = (r = –0.422, se = 0.3)

<GSSTEI>10-yma

(e)

NMH10-yma

1

3

5

y2

 = (r = –0.946, se = 0.3)*

y1

 = (r = –0.660, se = 0.7)*

(d)

NH10-yma

7

10

y2

 = (r = –0.936, se = 0.3)*

y1

 = (r = –0.385, se = 0.8)

(c)

NTS10-yma

2

5

8

y2

 = (r = –0.905, se = 0.5)*

y1

 = (r = 0.212, se = 1.1)

(b)

NTC10-yma

8

12

16

y2

 = (r = –0.951, se = 0.7)*

y1

 = (r = –0.058, se = 1.8)

(a)

Figure 50. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, 

and (e) NUSLFH versus 10-yma values of <GSSTEI>. 
112

2.8.9 NTC, NTS, NH, NMH, and NUSLFH Versus <JMASSTM>

Figure 51 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <JMASSTM>. For all comparisons the inferred linear 

regressions based on the current, more active interval are found to be negative, but only the one 

between NTC and <JMASSTM> (having r = –0.54) appears to be statistically important. Therefore, 

having a reliable estimate for the 10-yma value of <MEI> should allow one to reliably estimate the 

10-yma value of the parameter in question.

Recall from section 2.7.9 that, based on the expected first difference fd(<JMASSTM>)t, the 

10-yma <JMASSTM> = 25.8 ± 0.06 °C for 2007 (i.e., the ±1 sd prediction interval). Applying the 

10-yma value <JMASSTM> = 25.8 °C in the y2 regressions results in the estimate for the 10-yma 

value of NTC = 12.82 ± 1.8 (i.e., the ±1 se prediction interval), a value that falls below its minimum 

value for the 10-yma for the year 2007. Hence, the estimate is untenable. (Recall that the 10-yma 

<JMASSTM> = 25.8 ± 0.06 °C for 2007 implies that the yearly <JMASSTM> for 2012 should 

be between 25.3 and 27.7 °C. For 2006, the 10-yma <JMASSTM> also was 25.8 °C, inferring the 

10-yma values for NTC to be 12.82 ± 1.8. Hence, the difference between the observed and inferred 

values is 1.6 se.) 
113

NUSLFH10-yma

0

2

4

4

25 25.5 26

y2

 = (r = –0.423, se = 0.4)

y1

 = (r = 0.102, se = 0.3)

y2

 = (r = –0.458, se = 0.7)

y1

 = (r = –0.054, se = 0.8)

<JMASSTM>10-yma

(e) NMH10-yma

1

3

5

(d) NH10-yma

7

10

y1

 = (r = 0.171, se = 0.9)

y2

 = (r = –0.41, se = 0.9)

(c) NTS10-yma

2

5

8

y2

 = (r = –0.612, se = 1)

y1

 = (r = 0.443, se = 1)*

(b) NTC10-yma

8

12

16

y2

 = (r = –0.54, se = 1.8)*

y1

 = (r = 0.348, se = 1.8)

(a)

Figure 51. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, 

and (e) NUSLFH versus 10-yma values of <JMASSTM>.
114

2.8.10 NTC, NTS, NH, NMH, and NUSLFH Versus <NTA>

Figure 52 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <NTA>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be positive and highly statistically significant, 

having r = 0.90–0.99. Therefore, having a reliable estimate for the 10-yma value of <NTA> should 

allow one to reliably estimate the 10-yma value of the parameter in question.

Unfortunately, monthly values of NTA have not been updated beyond December 2010, so the 

yearly value of <NTA> for 2011 and the 10-yma value of <NTA> for 2006 cannot be computed, nor 

can an estimate be made for the 10-yma of <NTA> for 2007 (which is the one necessary for predicting NTC, NTS, NH, NMH, and NUSLFH on the basis of <NTA>).
115

NUSLFH10-yma

0

2

4

4

–0.5 0 0.5

y2

 = (r = 0.897, se = 0.2)*

y1

 = (r = 0.707, se = 0.2)*

y2

 = (r = 0.973, se = 0.2)*

y1

 = (r = 0.741, se = 0.5)*

<NTA>10-yma

(e) NMH10-yma

1

3

5

(d) NH10-yma

7

10

y1

 = (r = 0.866, se = 0.4)*

y2

 = (r = 0.968, se = 0.3)*

(c) NTS10-yma

2

5

8

y2

 = (r = 0.947, se = 0.4)*

y1

 = (r = 0.797, se = 0.7)*

(b) NTC10-yma

8

12

16

y1

 = (r = 0.878, se = 0.9)*

y2

 = (r = 0.990, se = 0.3)*

(a)

Figure 52. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <NTA>.
116

2.8.11 NTC, NTS, NH, NMH, and NUSLFH Versus <CAR>

Figure 53 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <CAR>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be positive and highly statistically significant, 

having r = 0.90–0.98. Therefore, having a reliable estimate for the 10-yma value of <NTA> should 

allow one to reliably estimate the 10-yma value of the parameter in question.

Unfortunately, as above for NTA, monthly values of CAR have not been updated beyond 

December 2010, so the yearly value of <CAR> for 2011 and the 10-yma value of <CAR> for 2006 

cannot be computed, nor can an estimate be made for the 10-yma of <CAR> for 2007 (which is the 

one necessary for predicting NTC, NTS, NH, NMH, and NUSLFH on the basis of <CAR>).
117

NUSLFH10-yma NMH10-yma

0

2

4

–0.20 –0.15 –0.10 –0.05 0 0.05 0.1 0.15 0.2

y2

 = (r = 0.896, se = 0.2)*

y1

 = (r = 0.721, se = 0.2)*

<CAR>10-yma

(e) NH10-yma

(c)

(d) NTS10-yma

(b) NTC10-yma

(a)

1

3

5

y2

 = (r = 0.972, se = 0.2)*

y1

 = (r = 0.808, se = 0.5)*

4

7

10

y2

 = (r = 0.976, se = 0.2)*

y1

 = (r = 0.729, se = 0.6)*

2

5

8

y2

 = (r = 0.921, se = 0.5)*

y1

 = (r = 0.559, se = 1)*

8

12

16 y2

 = (r = 0.979, se = 0.4)*

y1

 = (r = 0.673, se = 1.4)*

Figure 53. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <CAR>.
118

2.8.12 NTC, NTS, NH, NMH, and NUSLFH Versus <QBO>

Figure 54 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <QBO>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be negative and highly statistically significant (except for NUSLFH), having r = –0.66 to –0.86. Therefore, having a reliable estimate for the 

10-yma value of <QBO> should allow one to reliably estimate the 10-yma value of the parameter in 

question.

Recall from section 2.7.12 that, based on the expected first difference fd (<QBO>)t, the 10-yma 

<QBO> = –3.82 ± 0.37 ms–1 for 2007 (i.e., the ±1 sd prediction interval). Applying the 10-yma value 

<QBO> = –3.82 ms–1 in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, 

NH, NMH, and NUSLFH for 2007, these being, respectively, about 13.83 ± 1.1, 6.42 ± 0.6, 7.42 

± 0.6, 3.4 ± 0.5, and 1.84 ± 0.3 (i.e., the ±1 se prediction intervals). Comparison of these estimates 

with the minimum values for the 10-yma parameters for the year 2007 indicates that all estimates 

(except NH) fall below their minimum values, suggesting that they are not tenable. (Recall that the 

10-yma <QBO> = –3.82 ± 0.37 ms–1 for 2007 implies that the yearly <QBO> for 2012 should be 

between –15.94 and –1.14 ms–1.)

For NTC, a 10-yma value 13.83 ± 1.1 in 2007 simply is too low since it results in yearly NTC 

for 2012 that is of negative value. The same is true for NTS. For NH, a 10-yma value 7.42 ± 0.6 

in 2007 suggests a yearly value of 0–12 in 2012. For NMH, a 10-yma value 3.4 ± 0.5 in 2007 suggests a yearly value of about 0–4 in 2012. For NUSLFH, a 10-yma value 1.84 ± 0.3 in 2007 suggests 

a yearly value of about 0–4 in 2012. (For 2006, the 10-yma <QBO> also was –3.82 ms–1, inferring the 

10-yma values for NTC, NTS, NH, NMH, and NUSLFH to be 13.83 ± 1.1, 6.42 ± 0.6, 7.42 ± 0.6, 

3.4 ± 0.5, and 1.84 ± 0.3, respectively. Hence, the differences between the observed and inferred values are 1.7, 2.63, 0.47, 0.8, and 0.53 se, respectively.) 
119

NUSLFH10-yma

0

2

4

–5 –4.5 –4 –3.5 –3 –2.5 –2

y2

 = (r = –0.656, se = 0.3)

y1

 = (r = –0.432, se = 0.3)

<QBO>10-yma

(e) NMH10-yma

1

3

5

y2

 = (r = –0.791, se = 0.5)*

y1

 = (r = –0.701, se = 0.6)* (d) NH10-yma

4

7

10

y2

 = (r = –0.777, se = 0.6)*

y1

 = (r = –0.587, se = 0.7)*

(c) NTS10-yma

2

5

8

y2

 = (r = –0.855, se = 0.6)*

y1

 = (r = –0.126, se = 1.1)

(b) NTC10-yma

8

12

16

y2

 = (r = –0.849, se = 1.1)*

y1

 = (r = –0.357, se = 1.7)

(a)

Figure 54. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH

versus 10-yma values of <QBO>. 
120

2.8.13 NTC, NTS, NH, NMH, and NUSLFH Versus <AMO>

Figure 55 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <AMO>. For all comparisons the inferred linear regressions 

based on the current, more active interval are found to be positive and highly statistically significant, 

having r = 0.9–0.99. Therefore, having a reliable estimate for the 10-yma value of <AMO> should 

allow one to reliably estimate the 10-yma value of the parameter in question.

Recall from section 2.7.13 that, based on the expected first difference fd(<AMO>)t, the 

10-yma <AMO> = 0.226 ± 0.015 °C for 2007 (i.e., the ±1 sd prediction interval). Applying the 

10-yma value <AMO> = 0.226 °C in the y2 regressions results in estimates for the 10-yma values 

of NTC, NTS, NH, NMH, and NUSLFH for 2007, these being, respectively, about 15.7 ± 0.3, 7.39 

± 0.4, 8.31 ± 0.2, 4.13 ± 0.2, and 2.21 ± 0.2 (i.e., the ±1 se prediction intervals). Comparison of these 

estimates with the minimum values for the 10-yma parameters for the year 2007 indicates that all 

estimates (except NTS) exceed their minimum values, suggesting that they might be tenable. (Recall 

that the 10-yma <AMO> = 0.226 ± 0.015 °C for 2007 implies that the yearly <AMO> for 2012 

should be between 0.196 and 0.796 °C.)

For NTC, a 10-yma value 15.7 ± 0.3 in 2007 suggests a yearly value of about 2–14 for 2012. 

For NTS, a 10-yma value 7.39 ± 0.4 simply is too low to provide a meaningful estimate of the yearly 

NTS for 2012. For NH, a 10-yma value 8.31 ± 0.2 in 2007 suggests a yearly value of 14–22 in 2012. 

For NMH, a 10-yma value 4.13 ± 0.2 in 2007 suggests a yearly value of about 4–13 in 2012. For 

NUSLFH, a 10-yma value 2.21 ± 0.2 in 2007 suggests a yearly value of about 1–9 in 2012. (For 

2006, the 10-yma <AMO> was 0.206, inferring the 10-yma values for NTC, NTS, NH, NMH, and 

NUSLFH to be 15.32 ± 0.3, 7.19 ± 0.4, 8.13 ± 0.2, 3.99 ± 0.2, and 2.14 ± 0.2, respectively. Hence, 

the differences between the observed and inferred values are 1.27, 2.03, –2.15, –0.95, and –0.7 se, 

respectively.) 
121

NUSLFH10-yma

0

2

4

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2

y2

 = (r = 0.896, se = 0.2)*

y1

 = (r = 0.788, se = 0.2)*

<AMO>10-yma

(e) NMH10-yma

1

3

5

y2

 = (r = 0.98, se = 0.2)*

y1

 = (r = 0.94, se = 0.3)*

y2

 = (r = 0.978, se = 0.2)*

y1

 = (r = 0.791, se = 0.5)*

(d) NH10-yma

4

7

10

(c)

y2 = (r = 0.94, se = 0.4)*

y1

 = (r = 0.388, se = 1.1)

NTS10-yma

2

5

8

(b)

y2 = (r = 0.991, se = 0.3)*

y1

 = (r = 0.613, se = 1.5)*

NTC10-yma

8

12

16

(a)

Figure 55. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <AMO>. 
122

2.8.14 NTC, NTS, NH, NMH, and NUSLFH Versus <AMM>

Figure 56 shows the scatter plots of the 10-yma values of NTC, NTS, NH, NMH, and 

NUSLFH against the 10-yma values of <AMM>. For all comparisons the inferred linear regressions based on the current, more active interval are found to be positive and highly statistically significant, having r = 0.9–0.99. Therefore, having a reliable estimate for the 10-yma value of <AMM> 

should allow one to reliably estimate the 10-yma value of the parameter in question.

Recall from section 2.7.14 that, based on the expected first difference fd(<AMM>)t, the 

10-yma <AMM> = 1.79 ± 0.17 for 2007 (i.e., the ±1 sd prediction interval). Applying the 10-yma 

value <AMM> = 1.79 in the y2 regressions results in estimates for the 10-yma values of NTC, NTS, 

NH, NMH, and NUSLFH for 2007, these being, respectively, about 16.33 ± 0.3, 7.73 ± 0.4, 8.6 

± 0.2, 4.37 ± 0.2, and 2.33 ± 0.2 (i.e., the ±1 se prediction intervals). Comparison of these estimates 

with the minimum values for the 10-yma parameters for the year 2007 indicates that all estimates 

(except NTS) exceed their minimum values, suggesting that they might be tenable. (Recall that the 

10-yma <AMM> = 1.79 ± 0.17 for 2007 implies that the yearly <AMM> for 2012 should be between 

–1.32 and 5.48.)

For NTC, a 10-yma value 16.33 ± 0.3 in 2007 suggests a yearly value of about 15–27 for 

2012. For NTS, a 10-yma value 7.73 ± 0.4 suggests a yearly value of about 0–5 for 2012. For NH, 

a 10-yma value 8.6 ± 0.2 in 2007 suggests a yearly value of 20–28 in 2012. For NMH, a 10-yma value 

4.37 ± 0.2 in 2007 suggests a yearly value of about 9–17 in 2012. For NUSLFH, a 10-yma value 2.33 

± 0.2 in 2007 suggests a yearly value of about 4–12 in 2012. (For 2006, the 10-yma <AMM> was 

1.61, inferring the 10-yma values for NTC, NTS, NH, NMH, and NUSLFH to be 15.93 ± 0.3, 7.51 

± 0.4, 8.42 ± 0.2, 4.22 ± 0.2, and 2.25 ± 0.2, respectively. Hence, the differences between the observed 

and inferred values are –0.77, 1.23, –3.6, –2.1, and –1.25 se, respectively.) 
123

NUSLFH10-yma

0

2

4

–2 –1.5 –1 –0.5 0 0.5 1 1.5 2

y2

 = (r = 0.904, se = 0.2)*

y1

 = (r = 0.693, se = 0.2)*

<AMM>10-yma

(e) NMH10-yma

1

3

5 y2

 = (r = 0.982, se = 0.2)*

y1

 = (r = 0.937, se = 0.3)*

(d) NH10-yma

4

7

10

y2

 = (r = 0.979, se = 0.2)*

y1

 = (r = 0.718, se = 0.6)*

(c) NTS10-yma

2

5

8 y2

 = (r = 0.939, se = 0.4)*

y1

 = (r = 0.176, se = 1.1)

(b) NTC10-yma

8

12

16 y2

 = (r = 0.991, se = 0.3)*

y1

 = (r = 0.45, se = 1.7)*

(a)

Figure 56. 10-yma values of (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH 

versus 10-yma values of <AMM>.
124

2.9 The Strongest Inferred Correlations

The next 18 subsections describe the relational aspects between 10-yma values of the various tropical cyclone parameters (e.g., PWS, ACE, NTCA, etc.) and the surface air temperature and 

ENSO-related parameters on the basis of the best linear fits using all available 10-yma values (i.e., 

the y1 regressions) and the resultant 2×2 contingency tables. In each scatter plot, the current, more 

active interval is plotted as filled squares and the parametric values for 2005 are identified using an 

arrow, as before. Interestingly, 8 of the 18 tropical cyclone parameters have best fits against <AMO> 

(the only tropical cyclone parameter not strongly tied to <AMO> is <W. LONG>, which better 

correlates against <ONI>). The final subsection (2.9.19) discusses the relational aspects between the 

surface air temperature and the ENSO-related parameters. 

2.9.1 NTC Versus <AT>

Figure 57 represents the best fit using all available 10-yma values of NTC versus <AT> (from 

among the 14 fits listed in table 24). The vertical and horizontal lines are the parametric median 

values and the diagonal line is the inferred linear regression between the two parameters, having 

r = 0.9 and se = 0.8 °C. Hence, the inferred regression is one described as being positive (or direct), 

meaning the higher (lower) the 10-yma <AT> the greater (lesser) the 10-yma NTC. Expressed as 

a 2×2 contingency table, the probability of obtaining the observed result, or one more suggestive of 

a departure from independence (chance), is computed using the Fisher’s exact test for 2×2 contingency tables116 to be P = 0.02%. Thus, for the distribution of 10-yma values of NTC versus <AT>, 

there is only 0.02% chance (i.e., about 1 chance in 5,000) that the observed 2×2 contingency table, 

or one more suggestive of a departure from independence, occurs purely by chance. Hence, one suspects a strong dependence of NTC on <AT>, especially now in the current, more active interval. In 

particular, when the 10-yma <AT> is <9.38 °C (the median value), the 10-yma NTC usually is <10.1 

(and always ≤10.3) and when the 10-yma <AT> ≥9.38 °C, the 10-yma NTC usually is ≥10.1. When 

the 10-yma <AT> exceeds 9.7 °C, the 10-yma NTC always exceeds 10.3. NTC10-yma

8

10

12

14

16

8.5 9 9.5 10 10.5

y1

 (r = 0.896, se = 0.8)

<AT>10-yma

⇒P = 0.02%

21

7

7

21

Figure 57. 10-yma values of NTC versus 10-yma values of <AT>.
125

Interestingly, the probability for obtaining the observed distribution is driven by the current, more active interval (the filled squares), with 15 of the 16 10-yma values for the current, more 

active interval lying in the upper-right quadrant. Since first difference values do not change radically 

from one year to the next (see figs. 1 and 29), it is apparent that the current, more active interval 

likely will persist for another decade or more, presuming the temperature variation is cyclic, or possibly longer if the temperature rise is due to long-term global warming. (The paired point for the 

year 2006, which is not plotted, remains in the upper-right quadrant, being located at <AT>10-yma

= 10 °C and NTC10-yma = 15.7.)

As previously mentioned, the expected 10-yma <AT> for 2007 remains above 9.38 °C (actually, about ≥10 °C, see fig. 29). Hence, one strongly suspects that the 10-yma NTC for 2007 will be 

≥10.1 (actually, ≥15.3, being located in the upper-right quadrant). Recall that the minimum value for 

the 10-yma NTC for 2007 is 15.3, computed by assuming a zero frequency for NTC in 2012. Consequently, any yearly value of NTC greater than zero increases the 10-yma NTC above its minimum 

value.

From figure 1, the 10-yma NTC for 2007 is expected to be about 16.1 ± 0.3, inferring a yearly 

NTC for 2012 that measures about 10–22. From the Poisson distribution (table 21), if 2012 is classified as ENY, then the probability of having NTC >11 is about 1 chance in 5, while if 2012 turns out 

to be classified as NY or LNY, then the probability of having NTC >13 is about 1 chance in 5. Based 

on the Poisson distribution (table 23), when the yearly <AT> is greater than its long-term mean 

(9.48 °C), the probability of having NTC >14 is about 1 chance in 3. (Yearly <AT> for 2012 is 

expected to exceed 9.48 °C.)

2.9.2 NTS Versus <AT>

Figure 58 represents the best fit using all available 10-yma values of NTS versus <AT> (from 

among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric 

median values and the diagonal line is the inferred linear regression between the two parameters, 

having r = 0.8 and se = 0.7 °C. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 9.1%. Thus, for the distribution of 

10-yma values of NTS versus <AT>, there is only a 9.1% chance (i.e., about 1 chance in 11) that the 

observed 2×2 contingency table, or one more suggestive of a departure from independence, occurs 

purely by chance. Hence, one suspects a slight dependence of NTS on <AT>, especially now in 

the current, more active interval, with warmer surface air temperature at the Armagh Observatory 

indicative of greater NTS and cooler temperature indicative of lesser NTS. In particular, when the 

10-yma <AT> is <9.38 °C, the 10-yma NTS usually is <4.3 (and always ≤4.8) and when the 10-yma 

<AT> ≥9.38 °C, the 10-yma NTS usually is ≥4.3. When the 10-yma <AT> exceeds 9.7 °C, the 10-yma 

NTS always exceeds 4.6.

As before, interesting is that the probability for obtaining the observed distribution is driven 

by the current, more active interval (the filled squares), with 16 of the 16 10-yma values for the 

current, more active interval lying in the upper-right quadrant. Since first difference values do not 

change radically from one year to the next (see figs. 2 and 29), it is apparent that the current, more 
126

NTS10-yma

2

4

6

8

8.5 9 9.5 10 10.5

y1

 (r = 0.804, se = 0.7)

<AT>10-yma

17

11

11

17

⇒P = 9.1%

Figure 58. 10-yma values of NTS versus 10-yma values of <AT>.

active interval likely will persist for another decade or more, presuming the temperature variation 

is cyclic, or possibly longer if the temperature rise is due to long-term global warming. (The paired 

point for the year 2006, which is not plotted, remains in the upper-right quadrant, being located at 

<AT>10-yma = 10 °C and NTS10-yma = 8.)

As previously noted, the expected 10-yma <AT> for 2007 remains above 9.38 °C (actually, 

about ≥10 °C). Hence, one suspects that the 10-yma of NTS for 2007 will be above 4.3 (actually, ≥7.9, 

located in the upper-right quadrant, since 7.9 is the minimum value for the 10-yma of NTS for the 

year 2007). 

From figure 2, the 10-yma NTS for 2007 is expected to be about 8.2 ± 0.2, inferring a yearly 

NTS for 2012 of about 2–10. From the Poisson distribution, if 2012 is classified as ENY, then the 

probability of having NTS >6 is about 1 chance in 7, while if 2012 turns out to be classified as NY or 

LNY, then the probability of having NTS >6 is about 1 chance in 5. Also, from the Poisson distribution, when the yearly <AT> is greater than its long-term mean (9.48 °C), the probability of having 

NTS >7 is about 1 chance in 4.

2.9.3 NH Versus <NTA>

Figure 59 represents the best fit using all available 10-yma values of NH versus <NTA> (from 

among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric 

median values and the diagonal line is the inferred linear regression between the two parameters, 

having r = 0.87 and se = 0.4. Expressed as a 2×2 contingency table, the probability of obtaining the 

observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 0.51%. Thus, for the distribution 

of 10-yma values of NH versus <NTA>, there is only 0.51% chance (i.e., about 1 chance in 196) 

that the observed 2×2 contingency table, or one more suggestive of a departure from independence, 

occurs purely by chance. Hence, one suspects a dependence of NH on <NTA>, especially now in 

the current, more active interval, with a warmer North Atlantic temperature anomaly indicative of 

greater NH and a cooler North Atlantic temperature anomaly indicative of lesser NH. In particular, 

when the 10-yma <NTA> is negative, the 10-yma NH usually is <5.8 (and always ≤6.2) and when 

the 10-yma <NTA> is positive in value, the 10-yma NH usually is ≥5.8. When the 10-yma <NTA> 

exceeds 0.09 °C, the 10-yma NH always exceeds 6.4.
127

NH10-yma

4.5

5

5.5

6

6.5

7

7.5

8

–0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

y1

 = (r = 0.866, se = 0.4)

<NTA>10-yma

⇒P = 0.51%

18

7

8

17

Figure 59. 10-yma values of NH versus 10-yma values of <NTA>.

As before, interesting is that the probability for obtaining the observed distribution is driven 

by the current, more active interval (the filled squares), with 14 of the 16 10-yma values for the 

current, more active interval lying in the upper-right quadrant. Since first difference values do not 

change radically from one year to the next (see figs. 4 and 38), it is apparent that the current, more 

active interval likely will persist for another decade or more, presuming the temperature anomaly is 

cyclic, or possibly longer if the temperature anomaly (increased strength) is due to long-term global 

warming. (The paired point for the year 2006 is unknown since NTA has not been updated beyond 

December 2010. However, one suspects that, should it become available, it would be located in the 

upper-right quadrant.)

The second best fit for NH is the one against <AT>, having r = 0.82, se = 0.5 °C, and 

P = 0.02%. Based on <AT>, the 10-yma NH definitely would be located in the upper-right quadrant; 

recall that the minimum value for NH in 2007 is 7.4. 

From figure 4, the 10-yma NH for 2007 is expected to be about 7.8 ± 0.3, inferring a yearly 

NH for 2012 of about 2–14. From the Poisson distribution, if 2012 is classified as ENY, then the 

probability of having NH >6 is about 1 chance in 5; if 2012 turns out to be classified as NY, then the 

probability of having NH >8 is about 1 chance in 5; and if 2012 turns out to be classified as LNY, 

then the probability of having NH >9 is about 1 chance in 6. Also, from the Poisson distribution, 

when the yearly <AT> is greater than its long-term mean (9.48 °C), the probability of having NH >8 

is about 1 chance in 4.
128

2.9.4 NMH Versus <AMO>

Figure 60 represents the best fit using all available 10-yma values of NMH versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, 

having r = 0.94 and se = 0.3 °C. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 4.2 × 10–11%. Thus, for the distribution of 10-yma values of NMH versus <AMO>, there is only 4.2 × 10–11% chance (i.e., about 1 

chance in 2.4 × 1012) that the observed 2×2 contingency table, or one more suggestive of a departure 

from independence, can occur purely by chance. Hence, there is little doubt not to believe that NMH 

is greatly dependent on <AMO>. Obviously, strong positive (warm) <AMO> means much greater 

likelihood for increased NMH, while strong negative (cool) <AMO> means much greater likelihood 

of reduced NMH. In particular, when the 10-yma <AMO> is positive in value, the 10-yma NMH 

always is ≥2.7, and when the 10-yma <AMO> is negative in value, the 10-yma NMH always is ≤2.8. NMH10-yma

1

1.5

2

2.5

3

3.5

4

5

4.5

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25

y1

 = (r = 0.94, se = 0.3)

<AMO>10-yma

⇒P = 4.2 ×10–11%

27

0

2

24

Figure 60. 10-yma values of NMH versus 10-yma values of <AMO>. 
129

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1964–1995) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests that 

the current, more active interval will persist, at least another one or two decades, inferring increased 

frequencies of major hurricanes over the near-term, foreseeable future. (The paired point for the year 

2006, which is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma

= 0.206 °C and NMH10-yma = 3.8.)

From figure 41, the 10-yma AMO for 2007 is expected to be about 0.226 ± 0.015 °C, inferring a yearly <AMO> for 2012 that is positive in value, being equal to about 0.496 ± 0.3 °C (i.e., the 

±1 sd prediction interval). A 10-yma <AMO> = 0.226 °C in 2007 implies a 10-yma NMH = 3.99 

± 0.3 in 2007 (i.e., located in the upper-right quadrant), inferring a yearly NMH for 2012 of about 

0–12. From the Poisson distribution, if 2012 is classified as ENY, then the probability of having 

NMH >3 is about 1 chance in 7; if 2012 turns out to be classified as NY, then the probability of 

having NMH >3 is about 1 chance in 3; and if 2012 turns out to be classified as LNY, then the probability of having NMH >4 is about 1 chance in 4. Also, from the Poisson distribution, for positive 

yearly <AMO>, the probability of NMH >4 is about 1 chance in 4. 

2.9.5 NUSLFH Versus <AMO>

Figure 61 represents the best fit using all available 10-yma values of NUSLFH versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, 

having r = 0.79 and se = 0.2 °C. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 0.18%. Thus, for the distribution 

of 10-yma values of NUSLFH versus <AMO>, there is only 0.18% chance (i.e., about 1 chance in 

556) that the observed 2×2 contingency table, or one more suggestive of a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe that NUSLFH is dependent 

on <AMO>. Obviously, strong positive (warm) <AMO> means greater likelihood for increased 

NUSLFH, while strong negative (cool) <AMO> means greater likelihood of reduced NUSLFH. 

In particular, when the 10-yma <AMO> ≥0.09 °C, the 10-yma NUSLFH always is ≥1.7, and when 

the 10-yma <AMO> <0.09 °C, the 10-yma NUSLFH generally is <1.7 (five exceptions: 1967, 1968, 

1987, 1988, and 1989).

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1964–1995) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests 

that the current, more active interval will persist, at least another one or two decades, inferring possibly increased frequencies of US landfalling hurricanes over the near-term, foreseeable future, especially if the 10-yma <AMO> stays above about 0.1 °C. (The paired point for the year 2006, which 

is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma = 0.206 °C and 

NUSLFH10-yma = 2.)
130

20

7

8

18

NUSLFH10-yma

0

0.5

1

1.5

2

2.5

3

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25

y1

 = (r = 0.788, se = 0.2)

<AMO>10-yma

⇒P = 0.18%

Figure 61. 10-yma values of NUSLFH versus 10-yma values of <AMO>.

As previously noted, from figure 41, the 10-yma AMO for 2007 is expected to be about 0.226 

± 0.015 °C, inferring a yearly <AMO> for 2012 that is positive in value and equal to about 0.496 

± 0.3 °C. A 10-yma <AMO> = 0.226 °C in 2007 implies a 10-yma NUSLFH = 2.05 ± 0.2 in 2007 

(i.e., located in the upper-right quadrant), inferring a yearly NUSLFH for 2012 of about 0–6. From 

the Poisson distribution, if 2012 is classified as ENY, then the probability of having NUSLFH >2 is 

about 1 chance in 9; if 2012 turns out to be classified as NY, then the probability of having NUSLFH 

>2 is about 1 chance in 4; and if 2012 turns out to be classified as LNY, then the probability of 

having NUSLFH >3 is about 1 chance in 6. Also, from the Poisson distribution, for positive yearly 

<AMO>, the probability of NUSLFH >2 is about 1 chance in 4. 

2.9.6 <N. LAT> Versus <AMO>

Figure 62 represents the best fit using all available 10-yma values of <N. LAT> versus 

<AMO> (from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are 

the parametric median values and the diagonal line is the inferred linear regression between the two 

parameters, having r = –0.87 and se = 0.9 °C. Unlike the preceding regressions, the one between

<N. LAT> and <AMO> is a negative (or inverse) relationship, meaning that greater (lesser)

<N. LAT> tends to be associated with more negative or cooler (positive or warmer) <AMO>. Expressed as 

a 2×2 contingency table, the probability of obtaining the observed result, or one more suggestive 

of a departure from independence (chance), is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 7.9 × 10–7%. Thus, for the distribution of 10-yma values of <N. LAT> 

versus <AMO>, there is only 7.9 × 10–7% chance (i.e., about 1 chance in 1.3 × 108) that the observed 
131

3

24

23

3

<N. LAT>10-yma

18

26

22

–0.3 –0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25 0.3

y1

 = (r = –0.871, se = 0.9)

<AMO>10-yma

⇒P = 7.9 ×10–7%

Figure 62. 10-yma values of <N. LAT> versus 10-yma values of <AMO>.

2×2 contingency table, or one more suggestive of a departure from independence, occurs purely by 

chance. Hence, there is little doubt not to believe that <N. LAT> is strongly dependent on <AMO>. 

Obviously, strong positive <AMO> means greater likelihood for decreased <N. LAT>, while strong 

negative <AMO> means greater likelihood of increased <N. LAT>. In particular, when the 10-yma 

<AMO> ≥0 °C, the 10-yma <N. LAT> always is ≤22 deg, and when the 10-yma <AMO> <0 °C, the 

10-yma <N. LAT> generally is >22 deg (six exceptions: 1990–1995).

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1964–1995) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests that 

the current, more active interval will persist at least another one or two decades, inferring the 10-yma 

<N. LAT> ≤22 °N. over the near-term, foreseeable future. (The paired point for the year 2006, which 

is not plotted, remains in the low-right quadrant, being located at <AMO>10-yma = 0.206 °C and 

<N. LAT>10-yma = 21.2.)

As previously noted, from figure 41, the 10-yma <AMO> for 2007 is expected to be about 

0.226 ± 0.015 °C, inferring a yearly <AMO> for 2012 that is positive in value and equal to about 

0.496 ± 0.3 °C. A 10-yma <AMO> = 0.226 °C in 2007 implies a 10-yma <N. LAT> ≤20.7 deg. for 

2007 (i.e., located in the lower-right quadrant), inferring a yearly <N. LAT> ≤16.2 deg. for 2012, 

while from figure 13, one anticipates the 10-yma <N. LAT> ≤21.5 deg for 2007, inferring a yearly 

<N. LAT> ≥20.2 deg for 2012 (both prediction intervals being ±1 sd). Thus, the two ±1 sd prediction 

intervals are incompatible, suggesting that one or the other will be a statistical outlier for 2012.

2.9.7 <W. LONG> Versus <ONI>

Figure 63 represents the best fit using all available 10-yma values of <W. LONG> versus 

<ONI> (from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are 

the parametric median values and the diagonal line is the inferred linear regression between the 

two parameters, having r = –0.81 and se = 1.3 °C. Like the preceding regression, the one between 

<W. LONG> and <ONI> is an inverse relationship, meaning that greater (lesser) <W. LONG> 

tends to be associated with more negative or cooler (positive or warmer) <ONI>. Expressed as 
132

<W. LONG)10-yma

60

65

70

–0.5 0 0.5

y1

 (r = –0.808, se = 1.3)

<ONI>10-yma

7

19

20

5

⇒P = 0.02%

Figure 63. 10-yma values of <W. LONG> versus 10-yma values of <ONI>.

a 2×2 contingency table, the probability of obtaining the observed result, or one more suggestive of

a departure from independence (chance), is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 0.02%. Thus, for the distribution of 10-yma values of <W. LONG> versus 

<AMO>, there is only 0.02% chance (i.e., about 1 chance in 5,000) that the observed 2×2 contingency table, or one more suggestive of a departure from independence, occurs purely by chance. 

Hence, there is little doubt not to believe that <W. LONG> is dependent on <ONI>. Obviously, 

strong positive (negative) <ONI> means greater likelihood for decreased (increased) <W. LONG>. 

In particular, when the 10-yma <ONI> ≥0 °C, the 10-yma <W. LONG> usually is ≤64.3 deg, and 

when the 10-yma <ONI> <0 °C, the 10-yma <W. LONG> usually is >64.3 deg. (Recall that more 

positive <ONI> values are indicative of years often having an EN event and more negative <ONI> 

values are indicative of years often having a LN event; when EN events occur, there is a tendency for 

<W. LONG> to be located farther away from the US coastline (i.e., more eastward), while when LN 

events occur, there is a tendency for <W. LONG> to be located closer to the US coastline (i.e., more 

westward).)

From figure 30 (also, see table 3), one finds that the 10-yma <ONI> has been >0 °C 

since 1980 (the lone exception being 2003, –0.02 °C). For 2007, on the basis of the expected first
133

difference, the 10-yma <ONI> is inferred to be of positive value and equal to about 0.12 ± 0.05 °C 

(see sec. 2.7.2), suggesting that the yearly <ONI> for 2012 will be between –0.1 and 1.9 °C, values 

indicative of ENSO neutral to EN-like conditions. If, indeed, the 10-yma <ONI> turns out to be 

≥0.07 °C for 2007, then one anticipates that the 10-yma <W. LONG> likely would be located in the 

lower-right quadrant. (From fig. 14, for 2007 one anticipates the 10-yma <W. LONG> = 61.8 ± 0.7 deg, 

located in the lower-right quadrant, inferring the yearly <W. LONG> = 66.7 ± 14 deg for 2012. 

The paired point for the year 2006, which is not plotted, remains in the lower-right quadrant, being 

located at <ONI>10-yma = 0.14 °C and <W> LONG>10-yma = 61.9.)

It is important to recall that the last observed EN had its start in June 2009, on the basis 

of monthly ONI, and EN events tend to recur, on average, about once every 40–41 mo;30,34 hence, 

the possibility exists that a new EN event might arise later in 2012. According to the May 3, 2012, 

NOAA forecast, ENSO neutral conditions are expected to prevail, at least, through the summer of 

2012.52

2.9.8 PWS Versus <AMM>

Figure 64 represents the best fit using all available 10-yma values of PWS versus <AMM> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.93 and se = 1.8 kt. Expressed as a 2×2 contingency table, the probability of 

obtaining the observed result, or one more suggestive of a departure from independence (chance), 

is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 2.8 × 10–5%. Thus, 

for the distribution of 10-yma values of PWS versus <AMM>, there is only a 2.8 × 10–5% chance 

(i.e., about 1 chance in 3.6 × 106) that the observed 2×2 contingency table, or one more suggestive of 

a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe 

that PWS is dependent on <AMM>. Obviously, strong positive <AMM> means greater likelihood 

for increased PWS, while strong negative <AMM> means greater likelihood of decreased PWS. In 

particular, when the 10-yma <AMM> ≥0, the 10-yma PWS always is ≥124.3 kt (i.e., 124.3–135 kt), 

and when the 10-yma <AMM> <0 °C, the 10-yma PWS always is ≤127 kt (i.e., 117.7–127 kt).

Recall that prior to 1968 and subsequent to 1997, the 10-yma <AMM> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 42 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMM>, which, if true, suggests 

that the current, more active interval will persist at least another one or two decades, inferring the 

10-yma PWS ≥126.9 kt over the near-term, foreseeable future. (The paired point for the year 2006, 

which is not plotted, remains in the upper-right quadrant, being located at <AMM>10-yma = 1.61 

and PWS10-yma = 132.8.)

From figure 42, the 10-yma <AMM> for 2007 is expected to be about 1.79 ± 0.17, inferring a yearly <AMM> for 2012 that is about 2.08 ± 3.4. A 10-yma <AMM> = 1.79 in 2007 implies 

a 10-yma PWS = 135.6 ± 1.8 kt for 2007 (i.e., located in the upper-right quadrant), inferring a yearly 

PWS >150 kt in 2012. However, from figure 16, one anticipates the 10-yma PWS to be about 134.1 

± 1.8 kt for 2007, inferring a yearly PWS >120 kt in 2012.
134PWS10-yma

115

120

125

130

135

140

–2 –1.5 –1 –0.5 0 0.5 1 1.5 2

y1

 = (r = 0.934, se = 1.8)

<AMM>10-yma

23

4

4

22

⇒P = 2.8 ×10–5%

Figure 64. 10-yma values of PWS versus 10-yma values of <AMM>.

2.9.9 <PWS> Versus <NAO>

Figure 65 represents the best fit using all available 10-yma values of <PWS> versus <NAO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, 

having r = –0.83 and se = 2.1 kt. Likewise, as with the scatter plots of <N. LAT> versus <AMO> 

and <W. LONG> versus <ONI>, the inferred regression between <PWS> and <NAO> is one that

varies inversely (i.e., a negative correlation). Expressed as a 2×2 contingency table, the probability of 

obtaining the observed result, or one more suggestive of a departure from independence (chance), 

is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 0.36%. Thus, for the 

distribution of 10-yma values of <PWS> versus <NAO>, there is only a 0.36% chance (i.e., about 

1 chance in 278) that the observed 2×2 contingency table, or one more suggestive of a departure 

from independence, occurs purely by chance. Hence, there is little doubt not to believe that <PWS> 

is somewhat dependent on <NAO>. Obviously, strong positive <NAO> means greater likelihood for 

decreased <PWS>, while strong negative <NAO> means greater likelihood of increased <PWS>. In 

particular, when the 10-yma <NAO> ≥0, the 10-yma <PWS> always is ≤74.3 kt (i.e., 69.1–74.3 kt), 

and when the 10-yma <NAO> <0 °C, the 10-yma <PWS> always is ≥72 kt (i.e., 72–82.3 kt).
135

8

18

18

7

<PWS>10-yma

65

70

80

85

75

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

y1

 = (r = –0.83, se = 2.1)

<NAO>10-yma

⇒P = 0.36%

Figure 65. 10-yma values of <PWS> versus 10-yma values of <NAO>.

Recall that prior to 1974 and subsequent to 1999, the 10-yma <NAO> values always are negative, while during the intervening years (i.e., 1968–1997) they always are positive (see fig. 32 and/or 

table 17). Such behavior possibly suggests a cyclic nature for <NAO>, which, if true, suggests that 

the current, more active interval will persist at least another one or two decades, inferring the 10-yma 

<PWS> ≥74.9 kt over the near-term, foreseeable future. (The paired point for the year 2006, which 

is not plotted, remains in the lower-left quadrant like the paired point for 2005, being located at 

<NAO>10-yma = –0.16 and <PWS>10-yma = 72.)

From figure 32, the 10-yma <NAO> for 2007 is expected to be about –0.19 ± 0.03, inferring 

a yearly <NAO> for 2012 that is about –0.94 ± 0.6. A 10-yma <NAO> = –0.19 in 2007 implies 

a 10-yma <PWS> = 78.1 ± 2.1 kt for 2007 (i.e., located in the upper-left quadrant), inferring a yearly 

<PWS> >150 kt in 2012, which is completely unrealistic, since the largest observed <PWS> is 

100.4 kt (in 1950). From figure 17, one anticipates the 10-yma <PWS> to be about 72 ± 1 kt for 2007 

(i.e., located in the lower-left quadrant), inferring a yearly <PWS> ≤94.2 kt in 2012.

2.9.10 ACE Versus <AMO>

Figure 66 represents the best fit using all available 10-yma values of ACE versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.92 and se = 12. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 7.2 × 10–11%. Thus, for the distribution of 10-yma values of ACE versus <AMO>, there is only a 7.2 × 10–11% chance (i.e., about 

1 chance in 1.4 × 1012) that the observed 2×2 contingency table, or one more suggestive of a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe that ACE 

is strongly dependent on <AMO>. Obviously, strong positive <AMO> means greater likelihood for 

increased ACE, while strong negative <AMO> means greater likelihood of decreased ACE. In particular, when the 10-yma <AMO> ≥0 °C, the 10-yma ACE always is ≥108.3 (i.e., 108.3–159.7), and 

when the 10-yma <AMO> <0 °C, the 10-yma ACE always is ≤114.6 (i.e., 67.4–114.6).
136ACE10-yma

60

140

120

160

100

80

–0.3 –0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25 0.3

y1

 = (r = 0.902, se = 12)

<AMO>10-yma

26

1

1

25

⇒P = 7.2 ×10–11%

Figure 66. 10-yma values of ACE versus 10-yma values of <AMO>.

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests 

that the current, more active interval will persist at least another one or two decades, inferring the 

10-yma ACE ≥103.5 over the near-term, foreseeable future. (Countering this is the observation that 

the 10-yma ACE appears to be slowly declining in value from its peak of 159.7 in 2000 to 141.3 in 

2005; it did increase slightly in 2006 to 144.6. The paired point for the year 2006, which is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma = 0.206 °C and ACE10-yma

= 144.6.)

From figure 41, the 10-yma <AMO> for 2007 is expected to be about 0.226 ± 0.015 °C, inferring a yearly <AMO> for 2012 that is about 0.496 ± 0.3 °C. A 10-yma <AMO> = 0.226 °C in 2007 

implies a 10-yma ACE = 146.5 ± 12 for 2007 (i.e., located in the upper-right quadrant), inferring 

a yearly ACE 183 ± 240 in 2012 (the minimum value for the 10-yma ACE in 2007 is 137.4). From 

figure 21, one anticipates the 10-yma ACE to be about 149.1 ± 7.1 for 2007 (i.e., located in the upperright quadrant), inferring a yearly ACE >93 in 2012.

2.9.11 NSD Versus <NTA>

Figure 67 represents the best fit using all available 10-yma values of NSD versus <NTA> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, 

having r = 0.93 and se = 4.5 days. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 0.08%. Thus, for the distribution 

of 10-yma values of NSD versus <NTA>, there is only 0.08% chance (i.e., about 1 chance in 1,250) 

that the observed 2×2 contingency table, or one more suggestive of a departure from independence, 

occurs purely by chance. Hence, one suspects a dependence of NSD on <NTA>, especially now in 

the current, more active interval, with a warmer North Atlantic temperature anomaly indicative of
137

NSD10-yma

40

45

50

55

60

65

70

75

80

–0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

y1

 = (r = 0.925, se = 4.5)

<NTA>10-yma

19

6

7

18

⇒P = 0.08%

Figure 67. 10-yma values of NSD versus 10-yma values of <NTA>.

greater NSD and a cooler North Atlantic temperature anomaly indicative of lesser NSD. In particular, when the 10-yma <NTA> is negative, the 10-yma NSD usually is <49 days (and always <53 days) 

and when the 10-yma <NTA> is positive in value, the 10-yma NSD usually is >49 days. When the 

10-yma <NTA> exceeds 0.04 °C, the 10-yma NSD always exceeds 53 days.

As before, interesting is that the probability for obtaining the observed distribution is driven 

by the current, more active interval (the filled squares), with 15 of the 16 10-yma values for the current, more active interval lying in the upper-right quadrant. In fact, during the current, more active 

interval, the 10-yma NSD has increased steadily from 45.23 days in 1990 to 86.59 days in 2006, an 

increase of >90%. Since first difference values do not change radically from 1 yr to the next (see 

figs. 22 and 38), it is apparent that the current, more active interval likely will persist for another 

decade or more, presuming the temperature anomaly is cyclic, or possibly longer if the temperature 

anomaly (increased strength) is due to long-term global warming. (The paired point for the year 

2006 is unknown since NTA has not been updated beyond December 2010. However, one suspects 

that, should it become available, it would be located in the upper-right quadrant.)

The second best fit for NSD is the one against <AT>, having r = 0.91, se = 4.7 days, and 

P = 0.01%. Based on <AT>, the 10-yma NSD definitely would be located in the upper-right quadrant since the minimum value for NSD in 2007 is 84.9 days. From figure 22, the 10-yma NSD for 
138

2007 is expected to be about 88.87 ± 2.42 days, inferring a yearly NSD >31 days for 2012 (to as many 

as 128 days; the observed range of NSD is 13.75 days in 1983 to 191.25 days in 2010).

2.9.12 ACE/NSD Versus <AMM>

Figure 68 represents the best fit using all available 10-yma values of ACE/NSD versus 

<AMM> (from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are 

the parametric median values and the diagonal line is the inferred linear regression between the two 

parameters, having r = 0.88 and se = 0.1. Expressed as a 2×2 contingency table, the probability of 

obtaining the observed result, or one more suggestive of a departure from independence (chance), 

is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 1.2 × 10–8%. Thus, for 

the distribution of 10-yma values of ACE/NSD versus <AMM>, there is only a 1.2 × 10–8% chance 

(i.e., about 1 chance in 8.3 × 109) that the observed 2×2 contingency table, or one more suggestive of 

a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe 

that ACE/NSD is dependent on <AMM>. Obviously, strong positive <AMM> means greater likelihood for increased ACE/NSD, while strong negative <AMM> means greater likelihood of decreased 

ACE/NSD. In particular, when the 10-yma <AMM> ≥0, the 10-yma ACE/NSD always is ≥1.85 (i.e., 

1.85–2.27), and when the 10-yma <AMM> <0, the 10-yma PWS always is ≤1.81 (i.e., 1.55–1.81). ACE/NSD10-yma

1.5

2

2.5

–2 –1.5 –1 –0.5 0 0.5 1 1.5 2

y1

 = (r = 0.884, se = 0.1)

<AMM>10-yma

2 25

24 2

⇒P = 1.2 ×10–8%

Figure 68. 10-yma values of ACE/NSD versus 10-yma values of <AMM>.

Recall that prior to 1968 and subsequent to 1997, the 10-yma <AMM> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 42 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMM>, which, if true, suggests 

that the current, more active interval will persist at least another one or two decades, inferring the 

10-yma ACE/NSD ≥1.83 over the near-term, foreseeable future (certainly, ACE/NSD ≥1.71). (The 
139

paired point for the year 2006, which is not plotted, remains in the upper-right quadrant, being 

located at <AMM>10-yma = 1.61 and ACE/NSD10-yma = 1.81.)

From figure 42, the 10-yma <AMM> for 2007 is expected to be about 1.79 ± 0.17, inferring a yearly <AMM> for 2012 that is about 2.08 ± 3.4. A 10-yma <AMM> = 1.79 in 2007 implies 

a 10-yma ACE/NSD = 2.26 ± 0.1 for 2007 (i.e., located in the upper-right quadrant). However, such 

a value simply is too high, for it suggests a completely unrealistic yearly ACE/NSD ≥10.14 in 2012. 

From figure 26, one anticipates the 10-yma ACE/NSD to be about 1.83 ± 0.05 for 2007, inferring 

a yearly ACE/NSD >2.54 in 2012. (The minimum value 10-yma ACE/NSD for 2007 is 1.65. The 

value of the 10-yma ACE/NSD has been tracking steadily downward from its high in the current, 

more active interval of 2.01 in 2000 to 1.81 in 2006, suggesting that the 10-yma ACE/NSD will be 

<1.81 in 2007 if the downward progression continues. The ratio has been tracking downward because 

10-yma values of ACE have been decreasing, while 10-yma values of NSD have been increasing.)

 2.9.13 HISACE Versus <AMM>

Figure 69 represents the best fit using all available 10-yma values of HISACE versus <AMM> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.9 and se = 3.3. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 1 × 10–7%. Thus, for the distribution 

of 10-yma values of HISACE versus <AMM>, there is only a 1 × 10–7% chance (i.e., about 1 chance 

in 1 × 109) that the observed 2×2 contingency table, or one more suggestive of a departure from 

independence, occurs purely by chance. Hence, there is little doubt not to believe that HISACE is 

dependent on <AMM>. Obviously, strong positive <AMM> means greater likelihood for increased 

HISACE, while strong negative <AMM> means greater likelihood of decreased HISACE. In particular, when the 10-yma <AMM> ≥0, the 10-yma HISACE always is ≥34 (i.e., 34–44.1), and when 

the 10-yma <AMM> <0, the 10-yma HISACE always is ≤33.8 (i.e., 21.4–33.8).
140

HISACE10-yma

40

35

30

25

20

45

50

–2 –1.5 –1 –0.5 0 0.5 1 1.5 2

y1

 (0.895, se = 3.3)

<AMM>10-yma

3 25

23 2

⇒P = 1 ×10–7%

Figure 69. 10-yma values of HISACE versus 10-yma values of <AMM>. 

Recall that prior to 1968 and subsequent to 1997, the 10-yma <AMM> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 42 

and/or table 17). Such behavior possibly suggests a cyclic nature for <AMM>, which, if true, suggests that the current, more active interval will persist at least another one or two decades, inferring 

the 10-yma HISACE ≥32.8 over the near-term, foreseeable future (certainly, HISACE ≥31.4). (The 

paired point for the year 2006, which is not plotted, remains in the upper-right quadrant, being 

located at <AMM>10-yma = 1.61 and HISACE10-yma = 38.2.)

From figure 42, the 10-yma <AMM> for 2007 is expected to be about 1.79 ± 0.17, inferring a yearly <AMM> for 2012 that is about 2.08 ± 3.4. A 10-yma <AMM> = 1.79 in 2007 implies 

a 10-yma HISACE = 45.2 ± 3.3 for 2007 (i.e., located in the upper-right quadrant), inferring a yearly 

HISACE >85.6 in 2012. However, from figure 27, one anticipates the 10-yma HISACE to be about 

39.1 ± 1.8 for 2007, inferring a yearly HISACE <65.6 in 2012. (The minimum value 10-yma HISACE 

for 2007 is 37.6.)
141

2.9.14 LISNSD Versus <QBO>

Figure 70 represents the best fit using all available 10-yma values of LISNSD versus <QBO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = –0.7 and se = 1. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 1.3 × 10–4%. Thus, for the distribution of 10-yma values of LISNSD versus <QBO>, there is only a 1.3 × 10–4% chance (i.e., about 

1 chance in 7.7 × 105) that the observed 2×2 contingency table, or one more suggestive of a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe that 

LISNSD is dependent on <QBO>. Obviously, less negative <QBO> means greater likelihood for 

decreased LISNSD, while more negative <QBO> means greater likelihood of increased LISNSD. In 

particular, when the 10-yma <QBO> is less negative than –3.43 ms–1, the 10-yma LISNSD usually is 

<11.64 days, and when the 10-yma <QBO> is more negative than –3.42 ms–1, the 10-yma LISNSD 

usually is ≥11.64 days. 

The 10-yma <QBO> has consistently been negative in value throughout the interval 1950–

2005, varying between –2.3 and –4.6 ms–1, while the yearly <QBO> has varied both negatively and 

positively between –17.13 and 10.17 ms–1. On the other hand, the 10-yma LISNSD has varied between 

9.3 and 13.66 days, while the yearly LISNSD has varied between 3.75 and 21.25 days. In particular, 

between 1952 and 1971 (except for 1954 and 1955), the 10-yma LISNSD consistently was above the 

long-term mean (11.46 days), while it consistently was below the long-term mean between 1972 and 

1994, increasing above the long-term mean in 1995 and continuing to be above the long-term mean 

since. Such behavior possibly suggests a cyclic nature for LISNSD, but not so much for <QBO>, 

although the yearly <QBO> seems to be undergoing greater year-to-year swings now than was seen 

prior to the current, more active interval. (The paired point for the year 2006, which is not plotted, 

remains in the upper-left quadrant, being located at <QBO>10-yma = –3.82 ms–1 and LISNSD10-yma

= 12.51 days.)
142

9

9.5

10

10.5

11

11.5

12

12.5

13

13.5

–5 –4.5 –4 –3.5 –3 –2.5 –2

y1

 = (r = –0.725, se = 0.8)

<QBO>10-yma

LISNSD10-yma

22 5

4 22

⇒P = 1.3 ×10–4%

Figure 70. 10-yma values of LISNSD versus 10-yma values of <QBO>.
143

From figure 40, the value of the 10-yma <QBO> for 2007 is expected to measure about –3.82 

± 0.37 ms–1, inferring a yearly <QBO> value for 2012 of about –8.54 ± 7.4 ms–1. A 10-yma <QBO> 

= –3.82 ms–1 in 2007 implies a 10-yma LISNSD = 12.18 ± 1.3 days for 2007 (i.e., located in the 

upper-left quadrant), inferring a yearly LISNSD ≤33.35 days in 2012. However, from figure 28, one 

anticipates the 10-yma LISNSD to be about 12.51 ± 0.32 days for 2007, inferring a yearly LISNSD 

<21 days in 2012. (The minimum value 10-yma LISNSD for 2007 is 11.81 days.)

2.9.15 <NSD> Versus <AMO>

Figure 71 represents the best fit using all available 10-yma values of <NSD> versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.73 and se = 0.3 days. Expressed as a 2×2 contingency table, the probability of 

obtaining the observed result, or one more suggestive of a departure from independence (chance), 

is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 7.8 × 10–7%. Thus, for 

the distribution of 10-yma values of <NSD> versus <AMO>, there is only a 7.8 × 10–7% chance 

(i.e., about 1 chance in 1.3 × 108) that the observed 2×2 contingency table, or one more suggestive of 

a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe 

that <NSD> is strongly dependent on <AMO>. Obviously, strong positive <AMO> means greater 

likelihood for increased <NSD>, while strong negative <AMO> means greater likelihood of 

decreased <NSD>. In particular, when the 10-yma <AMO> ≥0 °C, the 10-yma <NSD> always is 

≥4.91 days (i.e., 4.91–5.52 days), and when the 10-yma <AMO> <0 °C, the 10-yma <NSD> usually 

is ≤4.91 days (4.28–4.91 days; nine exceptions: 1964–1970, 1994, and 1995). <NSD>10-yma

4

4.5

6

5

5.5

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25

y1

 = (r = 0.728, se = 0.3)

<AMO>10-yma

24

3

3

23

⇒P = 7.8 ×10–7%

Figure 71. 10-yma values of <NSD> versus 10-yma values of <AMO>.

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests 
144

that the current, more active interval will persist, at least, another one or two decades, inferring the 

10-yma <NSD> ≥4.94 days over the near-term, foreseeable future. (The paired point for the year 

2006, which is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma

= 0.206 °C and <NSD>10-yma = 5.4 days.)

From figure 41, the 10-yma <AMO> for 2007 is expected to be about 0.226 ± 0.015 °C, 

inferring a yearly <AMO> for 2012 that is about 0.496 ± 0.3 °C. A 10-yma <NSD> = 0.226 °C in 

2007 implies a 10-yma <NSD> = 5.44 ± 0.3 days for 2007 (i.e., located in the upper-right quadrant), 

inferring a yearly <NSD> ≤7.29 days in 2012 (the minimum value for the 10-yma <NSD> in 2007 is

5.38 days). Based on the expected first difference during the current, more active interval, one expects 

the 10-yma <NSD> = 5.43 ± 0.11 days for 2007, inferring a yearly <NSD> ≤3.29 days. (The yearly 

<NSD> has a range of 2.46–10.07 days, with the two extremes occurring in 1977 and 2010, respectively. In 2011, the yearly <NSD> measured 4.82 days.)

2.9.16 NHD Versus <AMO>

Figure 72 represents the best fit using all available 10-yma values of NHD versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.82 and se = 3.4 days. Expressed as a 2×2 contingency table, the probability of 

obtaining the observed result, or one more suggestive of a departure from independence (chance), 

is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 4.7 × 10–10%. Thus, 

for the distribution of 10-yma values of NHD versus <AMO>, there is only a 4.7 × 10–10% chance 

(i.e., about 1 chance in 2.1 × 1011) that the observed 2×2 contingency table, or one more suggestive of 

a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe 

that NHD is strongly dependent on <AMO>. Obviously, strong positive <AMO> means greater 

likelihood for increased NHD, while strong negative <AMO> means greater likelihood of decreased 

NHD. In particular, when the 10-yma <AMO> ≥0 °C, the 10-yma NHD always is ≥26.51 days (i.e., 

26.51–34.46 days), and when the 10-yma <AMO> <0 °C, the 10-yma NHD usually is ≤25.01 days 

(i.e., 15.84–25.01 days; 7 exceptions: 1964–1968, 1994, and 1995).

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests 

that the current, more active interval will persist, at least, another one or two decades, inferring the 

10-yma NHD ≥26.51 days over the near-term, foreseeable future. (The paired point for the year 

2006, which is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma

= 0.206 °C and NHD10-yma = 27.68 days.)

From figure 41, the 10-yma <AMO> for 2007 is expected to be about 0.226 ± 0.015 °C, inferring a yearly <AMO> for 2012 that is about 0.496 ± 0.3 °C. A 10-yma <AMO> = 0.226 °C in 2007 

implies a 10-yma NHD = 33.34 ± 3.4 for 2007 (i.e., located in the upper-right quadrant), inferring 

a yearly NHD ≥54.55 days in 2012. However, from figure 23, one anticipates the 10-yma NHD to be 

about 28.33 ± 1.76 days for 2007, inferring a yearly NHD <58 days in 2012. (The minimum value for 

the 10-yma NHD in 2007 is 27.21 days.)
145

25

2

2

24

⇒P = 4.7 ×10–10%

NHD10-yma

15

20

35

25

30

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25

y1

 = (r = 0.823, se = 3.4)

<AMO>10-yma

Figure 72. 10-yma values of NHD versus 10-yma values of <AMO>.

2.9.17 NMHD Versus <AMO>

Figure 73 represents the best fit using all available 10-yma values of NMHD versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.95 and se = 0.9 days. Expressed as a 2×2 contingency table, the probability of 

obtaining the observed result, or one more suggestive of a departure from independence (chance), 

is computed using the Fisher’s exact test for 2×2 contingency tables to be P = 7.2 × 10–11%. Thus, 

for the distribution of 10-yma values of ACE versus <AMO>, there is only a 7.2 × 10–11% chance 

(i.e., about 1 chance in 14 × 109) that the observed 2×2 contingency table, or one more suggestive of 

a departure from independence, occurs purely by chance. Hence, there is little doubt not to believe that 

NMHD is strongly dependent on <AMO>. Obviously, strong positive <AMO> means greater likelihood for increased NMHD, while strong negative <AMO> means greater likelihood of decreased 

NMHD. In particular, when the 10-yma <AMO> ≥0 °C, the 10-yma ACE always is ≥ 6.2 days (i.e.,

6.20–10.43 days), and when the 10-yma <AMO> <0 °C, the 10-yma ACE usually is ≤5.85 days 

(i.e., 1.90–5.85 days; two exceptions: 1964 and 1966).

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 41 and/

or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests that 

the current, more active interval will persist at least another one or two decades, inferring the 10-yma 

NMHD ≥5.85 days over the near-term, foreseeable future. (The paired point for the year 2006, which 

is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma = 0.206 °C and 

NMHD10-yma = 9.39 days.)
146NMHD10-yma

0

3

6

9

12

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25

y1

 = (r = 0.948, se = 0.9)

<AMO>10-yma

26

0

1

26

⇒P = 7.2 ×10–11%

Figure 73. 10-yma values of NMHD versus 10-yma values of <AMO>.

From figure 41, the 10-yma <AMO> for 2007 is expected to be about 0.226 ± 0.015 °C, inferring a yearly <AMO> for 2012 that is about 0.496 ± 0.3 °C. A 10-yma <AMO> = 0.226 °C in 2007 

implies a 10-yma NMHD = 10.95 ± 0.9 days for 2007 (i.e., located in the upper-right quadrant), 

inferring a yearly NMHD = 34 ± 18 days in 2012 (the minimum value for the 10-yma NMHD in 

2007 is 9.25 days). However, from figure 24, one anticipates the 10-yma NMHD to be about 9.77 

± 0.69 days for 2007, inferring a yearly NMHD <24 days in 2012. (The minimum value for the 

10-yma NHD in 2007 is 27.21 days.)

2.9.18 NTCA Versus <AMO>

Figure 74 represents the best fit using all available 10-yma values of NTCA versus <AMO> 

(from among the 14 fits listed in table 24). As before, the vertical and horizontal lines are the parametric median values and the diagonal line is the inferred linear regression between the two parameters, having r = 0.93 and se = 9.8. Expressed as a 2×2 contingency table, the probability of obtaining 

the observed result, or one more suggestive of a departure from independence (chance), is computed 

using the Fisher’s exact test for 2×2 contingency tables to be P = 7.2 × 10–11%. Thus, for the distribution of 10-yma values of ACE versus <AMO>, there is only a 7.2 × 10–11% chance (i.e., about 

1 chance in 14 × 109) that the observed 2×2 contingency table, or one more suggestive of a departure 

from independence, occurs purely by chance. Hence, there is little doubt not to believe that NTCA 

is strongly dependent on <AMO>. Obviously, strong positive <AMO> means greater likelihood for 

increased NTCA, while strong negative <AMO> means greater likelihood of decreased NTCA. In 

particular, when the 10-yma <AMO> ≥0 °C, the 10-yma NTCA always is ≥118% (i.e., 118%–160.5%), 

and when the 10-yma <AMO> <0 °C, the 10-yma NTCA always is ≤120.4% (i.e., 75.5%–120.4%).
147

NTCA10-yma

70

100

130

160

–0.25 –0.2 –0.15 –0.1 –0.05 0 0.05 0.1 0.15 0.2 0.25

y1

 = (r = 0.932, se = 9.8)

<AMO>10-yma

⇒P = 7.2 ×10–11%

26

1

1

25

Figure 74. 10-yma values of NTCA versus 10-yma values of <AMO>.

Recall that prior to 1964 and subsequent to 1995, the 10-yma <AMO> values always are 

positive, while during the intervening years (i.e., 1968–1997) they always are negative (see fig. 41 

and/or table 17). Such behavior possibly suggests a cyclic nature for <AMO>, which, if true, suggests that the current, more active interval will persist at least another one or two decades, inferring 

the 10-yma NTCA ≥105.5% over the near-term, foreseeable future. (The paired point for the year 

2006, which is not plotted, remains in the upper-right quadrant, being located at <AMO>10-yma

= 0.206 °C and NTCA10-yma = 156.1%.)

From figure 41, the 10-yma <AMO> for 2007 is expected to be about 0.226 ± 0.015 °C, inferring a yearly <AMO> for 2012 that is about 0.496 ± 0.3 °C. A 10-yma <AMO> = 0.226 °C in 2007 

implies a 10-yma NTCA = 153.6% ± 9.8% for 2007 (i.e., located in the upper-right quadrant), inferring a yearly NTCA ≤219.2% in 2012 (the minimum value for the 10-yma NTCA in 2007 is 152.4%). 

From figure 25, one anticipates the 10-yma NTCA to be about 160.8% ± 6.3% for 2007 (i.e., located 

in the upper-right quadrant), inferring a yearly NTCA = 41.2%–293.2% in 2012.

2.9.19 Relational Aspects Between Surface Air Temperature and the ENSO-Related Parameters

Also included in table 24 are the inferred regressions between surface air temperature and the 

ENSO-related parameters for the intervals 1950–2005 and 1990–2005 using 10-yma values. For the 

larger interval, <AT> correlates strongly (i.e., r >|±0.7|) with <NTA> (r = 0.9), <CAR> (r = 0.83), 

and <AMO> (r = 0.76). For the current, more active interval, <AT> correlates more strongly (i.e., 

r > |±0.95|) with <AMM> (r = 0.98), <AMO> (r = 0.98), <NTA> (r = 0.97), and <CAR> r >0.97. 

All of these parameters share a common attribute in that they are measures of temperature, <AT> 

being a measure of surface air temperature in the North Atlantic basin and <AMO>, <AMM>, 

<NTA>, and <CAR> being measures of ocean temperature anomalies in the North Atlantic basin. 

So, one should not be surprised by the high degree of correlation between them.
148

For the ENSO-related parameters, the following appears true:

(1) <ONI> correlates strongly with <SOI> (r = –0.92), <JMASSTM> (r = 0.91), <MEI> 

(r = 0.9), <GSSTEI> (r = 0.78), and <PDO> (r = 0.74) for the larger interval. For the current, 

more active interval, <ONI> correlates more strongly with only <MEI> (r = 0.96) and <GSSTEI> 

(r = 0.95). 

(2) <SOI> correlates strongly with <MEI> (r = –0.98), <ONI> (r = –0.92), <JMASSTEI> 

(r = –0.92), and <PDO> (r = –0.91) for the larger interval. For the current, more active interval, 

<SOI> correlates more strongly with <MEI> (r = –0.98) and <AMO> (r = 0.95).

(3) <NAO> correlates strongly with <PDO> (r = 0.84), <MEI> (r = 0.81), <QBO> 

(r = 0.78), <SOI> (r = –0.77), <GSSTEI> (r = 0.73), and <JMASSTM> (r = 0.7) for the larger 

interval. For the current, more active interval, <NAO> correlates more strongly with <AMO> 

(r = –0.97), <NTA> (r = –0.97), <CAR> (r = –0.97), and <AMM> (r = –0.97).

(4) <PDO> correlates strongly with <MEI> (r = 0.95), <SOI> (r = –0.91), <JMASSTM> 

(r = 0.88), <GSSTEI> (r = 0.85), <NAO> (r = 0.84), <QBO> (r = 0.76), and <ONI> (r = 0.74) for 

the larger interval. For the current, more active interval, <PDO> best correlates with <GSSTEI> 

(r = 0.94) and <MEI> (r = 0.94).

(5) For <TNI>, there are no strong correlations for either the larger interval or the current, 

more active interval. The strongest correlations are with <NTA> (r = –0.6) and <ONI> (r = –0.6) for 

the larger interval and with <JMASSTM> (r = 0.41) for the current, more active interval, although 

the latter correlation is not statistically significant.

(6) <MEI> correlates strongly with <SOI> (r = –0.98), <JMASSTM> (r = 0.96), <PDO> (r

= 0.95), <ONI> (r = 0.9), <GSSTEI> (r = 0.84), and <NAO> (r = 0.81) for the larger interval. For 

the current, more active interval, <MEI> correlates more strongly with <SOI> (r = –0.98), <ONI> 

(r = 0.96), and <GSSTEI> (r = 0.95).

(7) <GSSTEI> correlates strongly with <PDO> (r = 0.85), <MEI> (r = 0.84), <SOI> 

(r = –0.83), <ONI> (r = 0.78), <JMASSTM> (r = 0.77), and <NAO> (r = 0.73) for the larger 

interval. For the current, more active interval, <GSSTEI> correlates more strongly with <AMO> 

(r = –0.96), <ONI> (r = 0.95), and <MEI> (r = 0.95).

(8) <JMASSTM> correlates strongly with <MEI> (r = 0.96), <SOI> (r = –0.92), <ONI> 

(r = 0.91), <PDO> (r = 0.88), <GSSTEI> (r = 0.77), and <NAO> (r = 0.7) for the larger interval. 

For the current, more active interval the strongest correlations are for <JMASSTM> with <ONI> 

(r = 0.77) and <MEI> (r = 0.76).

(9) <NTA> correlates strongly with <CAR> (r = 0.91), <AT> (r = 0.9), and <AMO> 

(r = 0.82) for the larger interval. For the current, more active interval, <NTA> correlates more 

strongly with <AMM> (r = 0.997), <AMO> (r = 0.991), <CAR> (r = 0.985), <AT> (r = 0.97), and 

<NAO> (r = –0.97).
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(10) <CAR> correlates strongly with <AMO> (r = 0.93), <NTA> (r = 0.91), <AT> 

(r = 0.83), and <AMM> (r = 0.75) for the larger interval. For the current, more active interval, <CAR> correlates more strongly with <AMO> (r = 0.996), <AMM> (r = 0.985), <NTA> 

(r = 0.985), <AT> (r = 0.97), and <NAO> (r = –0.968).

(11) <QBO> correlates strongly with <NAO> (r = 0.78), <PDO> (r = 0.76), and <AMM> 

(r = –0.7) for the larger interval. For the current, more active interval, the strongest correlations are 

for <QBO> with <NTA> (r = –0.84) and <SOI> (r = –0.84).

(12) <AMO> correlates strongly with <CAR> (r = 0.93), <AMM> (r = 0.9), <NTA> 

(r = 0.82), and <AT> (r = 0.76) for the larger interval. For the current, more active interval, <AMO> 

correlates more strongly with <CAR> (r = 0.996), <AMM> (r = 0.993), <NTA> (r = 0.991), <AT> 

(r = 0.979), <NAO> (r = –0.973), <GSSTEI> (r = –0.957), and <SOI> (r = 0.949).

(13) <AMM> correlates strongly with <AMO> (r = 0.9), <CAR> (r = 0.75), and <QBO> 

(r = –0.7) for the larger interval. For the current, more active interval, <AMM> correlates more 

strongly with <NTA> (r = 0.997), <AMO> (r = 0.993), <CAR> (r = 0.985), <AT> (r = 0.982), and 

<NAO> (r = –0.968).

2.10 Additional Remarks

Seasonal forecasting of North Atlantic basin tropical cyclone activity now spans nearly 

30 yr.17,35,117–119 Typically, these forecasting techniques often are statistical in nature, relying on 

measurements of SST and SLP anomalies, the phase/strength of the QBO, and the phase/strength 

of the ENSO. The product output of these investigations include the expected seasonal number of 

tropical cyclones, the number of storm days, the number of hurricanes, the number of hurricane 

days, the number of major or intense hurricanes, the number of major or intense hurricane days, 

the accumulated cyclone energy, the net tropical cyclone activity, and the number/probability of 

USLFHs. 

2.10.1 The 2011 Season Summary

Table 25 (see appendix) provides a listing of the tropical cyclones that formed in the North 

Atlantic basin during the 2011 hurricane season, along with parametric values and summaries following the format used in table 1. During the 2011 season, some 19 tropical cyclones formed in the North 

Atlantic basin, including 18 named storms and one unnamed storm. Of these 19 tropical cyclones, 

12 were tropical storms only, 7 were hurricanes, and 4 were major hurricanes. Only one US landfalling hurricane (Irene) occurred, which was the first to strike the US coastline since the 2008 hurricane 

season. The first tropical cyclone formed on June 28 and the last formed on November 8. At least, 

one tropical cyclone formed in each of the 6 mo comprising the nominal hurricane season (June–

November). The most powerful storms were Katia and Ophelia, both having maximum sustained 

winds of 120 kt (Ophelia had the lowest pressure, measuring 940 mbar). The highest latitudinal formation was 37.6 °N. (Franklin) and the lowest latitudinal formation was 11 °N. (Katia). The least 

western longitudinal formation was 29.6 °W. (Katia) and the most western longitudinal formation 

was 93.5 °W. (Arlene). The highest individual storm ACE was 27 (Katia) and the longest individual 
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NSD was 13.75 days (Philippe). The season as a whole had NTCA = 145%, meaning that it was 

about 45% more active climatologically.

Based on regional grouping, there were 4 storms that formed in region 1 (the Gulf of Mexico 

area). These included Arlene, Don, Lee, and Nate, all attaining only tropical storm strength, except 

Nate (hurricane). Region 2 (the Caribbean Sea area) accounted for 3 storms, including Emily, Harvey, 

and Rina, with Rina becoming a major hurricane. Region 3 (the US east coast area) accounted for 

6 storms, including Bret, Franklin, Gert, Jose, an unnamed storm, and Sean (the last storm of the 

2011 season). While region 3 was the most prolific, none of the storms attained hurricane strength. 

Region 4 (the lower Atlantic-Cape Verde area) accounted for 5 storms, including Irene, Katia, Maria, 

Ophelia, and Philippe, all becoming major hurricanes, except Maria and Philippe (hurricanes). 

Region 5 (the open North Atlantic area) accounted for only one storm (Cindy), a tropical storm.

The number of tropical cyclones (19) is tied for second place with the 1995 season, both having fewer NTC than the 2005 season (28 storms). Also, the number of tropical storms attaining only 

tropical storm strength (12) is second only to that of the 2005 season (13 tropical storms). The number of hurricanes (7) and number of major hurricanes (4), however, were only slightly above average 

in number. In terms of PWS, its peak wind speed (120 kt) is below the long-term average (126.9 kt), 

as is its <PWS> (66.3 kt as compared to 74.9 kt), LP (940 mbar as compared to 938.3 mbar), <LP> 

(984.2 as compared to 979.2 mbar), ACE/NSD (1.39 as compared to 1.83), HISACE (27 as compared to 32.8), <NSD> (4.74 days as compared to 4.98 days), and NMHD (4.5 days as compared to 

6.23 days). However, in terms of ACE, NSD, and LISNSD, all were larger than their respective averages: ACE, 126.3 as compared to 103.5; LISNSD, 13.75 days as compared to 11.46 days; and NSD, 

90 days as compared to 55.71 days. The seasonal centroid location (<N. LAT> and <W. LONG>) is 

essentially the same as its long-term average (22 °N., 65.2 °W. as compared to 22 °N., 64.9 °W.).

Prior to the 2011 season, the feeling was that the season would be one that would be above 

average in number.30,120,121 Indeed, overall, the 2011 hurricane season was greater in terms of the 

frequency of NTC, both in comparison to the long-term average (10.8 tropical cyclones per season) 

and the average during the current, more active interval (14.8 tropical cyclones per season). Recently, 

NOAA issued its 2011 NHC Forecast Verification Report, noting that the 2011 Atlantic hurricane 

season had above-normal activity. 122–124 NOAA also announced the retirement of the name ‘Irene’ 

from the list of North Atlantic basin storm names.125 ‘Irene’ will be replaced with ‘Irma’ in the 2017 

season. (Irene caused widespread damage along the US east coast and was directly responsible for 

48 deaths in the Atlantic basin, with damage in the US estimated to be $15.8 billion.)

2.10.2 The 2012 Season Forecast

Early predictions for the 2012 North Atlantic basin hurricane season suggest that it will be of 

near average to below average activity, although the official NOAA forecast has not yet been issued 

(as of this writing, early May 2012). For example, because the tropical Atlantic anomalously cooled 

during the latter portion of 2011 and because of the increased likelihood for an EN event to occur 

later this year, the Colorado State University team126 anticipates reduced hurricane activity and 

below-average probability for a major hurricane landfall along the US coast and in the Caribbean 

this hurricane season. In particular, they are presently predicting 10 named storms, 40 named storm 
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days, 4 hurricanes, 16 hurricane days, 2 major hurricanes, 3 major hurricane days, an ACE of 70, 

and an overall NTCA of about 77%, all parameters being below long-term averages and well below 

averages based strictly on the current, more active interval.

Likewise, the Met Office127, the United Kingdom’s National Weather Service, estimates the 

most likely number of tropical cyclones during the 2012 hurricane season to be 10, with a 70% 

chance that the number will be in the range 7 to 13. They also estimate the most likely value of ACE 

for the 2012 hurricane season to be 90, with a 70% chance that the index will be in the range of 28 to 

152. These estimates are slightly below normal activity relative to the 1980–2010 long-term averages, 

being 12 and 104, respectively. 

The Tropical Risk team128 also anticipates a below-average season for 2012. For the 2012 

hurricane season, they predict NTC = 12.5 ± 4.1, NH = 5.6 ± 2.8, NMH = 2.6 ± 1.6, and ACE = 95 

± 55. They also estimate a 33% probability that the 2012 North Atlantic basin hurricane season ACE 

index will be above average, a 34% probability that it will be near normal, and a 33% probability that 

it will be below normal.

Climatologically, based on the long-term interval 1945–2010, the yearly values for the parameters are the following: NTC = 10.8 ± 4, NH = 6.2 ± 2.6, NMH = 2.7 ± 1.9, NUSLFH = 1.6 ± 1.5, 

PWS = 126.9 ± 19.7 kt, <PWS> = 74.9 ± 9.1 kt, LP = 938.3 ± 20.5 mbar, <LP> = 979.2 ± 8.3 mbar, 

ACE = 103.5 ± 58.5, NSD = 55.7 ± 30 days, ACE/NSD = 1.83 ± 0.45, HISACE = 32.8 ± 16.1, 

LISNSD = 11.5 ± 3.6 days, NHD = 26.4 ± 14.4 days, NMHD = 6.2 ± 5.7 days, and NTCA = 112.6% 

± 59.3% (all values expressed as the ±1 sd prediction interval). However, based on the shorter current, more active interval 1995–2010, some of the averages are considerably higher, although not all. 

For example, NTC averages about 14.8 ± 4.7, NH = 7.9 ± 3.3, NMH = 3.8 ± 1.8, NUSLFH = 1.9

± 2, PWS = 131.6 ± 16 kt, <PWS> = 73.8 ± 8.9 kt, LP = 925.4 ±18.5 mbar, <LP> = 978.7 ± 7 mbar, 

ACE = 146.6 ± 63.2, NSD = 82.6 ± 40.7 days, ACE/NSD = 1.84 ± 0.47, HISACE = 39.2 ± 14.6, 

LISNSD = 12.9 ± 2.9 days, NHD = 32.1 ± 16 days, NMHD = 9.3 ± 6.2 days, and NTCA = 156.5 %

± 66%. Hence, dependent upon whether the 2012 hurricane season remains similar to or not the 

nature of the 1995–2010 current, more active interval, one expects either NTC = 11 ± 4 (based on 

the long-term interval) or NTC = 15 ± 5 (based on the current, more active interval), and so forth.

Based on the Poisson probability distribution for the long-term interval, NTC = 10 ± 1 

(35.3%), NTC <9 (25%), and NTC >11 (39.7%); NH = 6 ± 1 (45.7%), NH <5 (25.9%), and NH >7 

(28.4%); NMH = 2 ± 1 (64.7%), NMH = 0 (6.7%), and NMH >3 (28.6%); and NUSLFH = 1 ± 1 

(78.3%) and NUSLFH >2 (21.7%). Based on the Poisson probability distribution for the current, 

more active interval, NTC = 14 ± 1 (30.4%), NTC <13 (28.5%), and NTC >15 (41.1%); NH = 7 ± 1 

(40.6%), NH <6 (20.1%), and NH >8 (39.3%); NMH = 3 ± 1 (56%), NMH <2 (10.7%), and NMH 

>4 (33.2%); and NUSLFH = 1 ± 1 (70.4%) and NUSLFH >2 (29.6%).

Based on the Poisson probability distribution for the long-term interval and accounting for 

the ENSO condition (i.e., the year is classified as ENY, LNY, or NY) results in the following: 
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(1) If 2012 happens to be classified as ENY, then NTC = 9 ± 1 (38.2%), NTC <8 (30.9%), and 

NTC >10 (31%); NH = 4 ± 1 (50.8%), NH <3 (14.2%), and NH >5 (35.1%); NMH = 2 ± 1 (72.2%), NMH 

= 0 (13.5%), and NMH >3 (14.3%); and NUSLFH = 1 ± 1 (89.4%) and NUSLFH >2 (10.6%). 

(2) If 2012 happens to be classified as LNY, then NTC = 11 ± 1 (34.1%), NTC <10 (27.2%), 

and NTC >12 (38.6%); NH = 7 ± 1 (42.8%), NH <6 (30.1%), and NH >8 (27.1%); NMH = 3 ± 1 

(59.2%), NMH <2 (13.9%), and NMH >4 (26.9%); and NUSLFH = 2 ± 1 (70.9%), NUSLFH = 0 

(11.1%), and NUSLFH >3 (18.1%).

(3) If 2012 happens to be classified as NY, then NTC = 11 ± 1 (34.7%), NTC <10 (31.3%), and 

NTC >12 (34%); NH = 6 ± 1 (44.9%), NH <5 (22.5%), and NH >7 (32.6%); NMH = 2 ± 1 (64.5%), 

NMH = 0 (6.7%), and NMH >3 (28.8%); and NUSLFH = 1 ± 1 (77.6%) and NUSLFH >2 (22.4%).

Other factors, however, have been found that appear to mitigate the 2012 seasonal prediction (i.e., besides knowing whether the year 2012 will be classified as ENY, LNY, or NY, following 

the definition used in this study based on monthly ONI values). These other factors include <AT>, 

<NAO>, <NTA>, <CAR>, <QBO>, <AMO>, and <AMM>. Because <NTA> and <CAR> have 

not been updated beyond December 2010, only <AT>, <NAO>, <QBO>, <AMO>, and <AMM> 

offer the opportunity to perhaps improve the predictive ability for the frequency and strength of the 

2012 hurricane season. (<SOI> also could be used as a mitigating factor; however, because of its 

strong inverse correlation against <ONI>, it was decided to ignore the effects of <SOI>. The other 

factors are less strongly correlated against <ONI>.) 

Recall from figures 29 (<AT>), 32 (<NAO>), 40 (<QBO>), 41 (AMO>), and 42 (<AMM>) 

and from table 24 (correlations) that these particular parameters appear to influence greatly the frequency and strength of tropical cyclones in the North Atlantic basin. In particular, by knowing the 

sign of the parameters (i.e., whether the yearly value will be above/below average in the case of yearly 

<AT> or positive/negative in the case of the yearly <NAO>, <QBO>, <AMO>, and <AMM>), one 

might be able to better determine the prediction intervals and probabilities of NTC, NH, NMH, and 

NUSLFH for the 2012 season.

For å<AT>, when the yearly temperature exceeds its long-term average (9.48 °C), one expects 

greater numbers of tropical cyclones than when the yearly temperature is below the long-term mean. 

For example, when the yearly temperature is higher than the mean, based on the Poisson probability 

distribution, NTC = 12 ± 1 (32.8%), NTC <11 (27.9%), and NTC >13 (39.3%); NH = 6 ± 1 (43.5%), 

NH <5 (18.9%), and NH >7 (37.6%); NMH = 3 ± 1 (59.9%), NMH <2 (14.9%), and NMH >4 

(25.2%); and NUSLFH = 2 ± 1 (71.6%), NUSLFH = 0 (12.3%), and NUSLFH >3 (16.1%). In contrast, when the yearly temperature (<AT>) is lower than the mean, based on the Poisson probability 

distribution, NTC = 9 ± 1 (37.9%), NTC <8 (28.1%), and NTC >10 (34%); NH = 5 ± 1 (47.4%), NH 

<4 (18%), and NH >6 (34.6%); NMH = 2 ± 1 (70.9%), NMH = 0 (11.2%), and NMH >3 (17.9%); 

and NUSLFH = 1 ± 1 (86.4%) and NUSLFH >2 (13.6%).

For <NAO>, when the yearly value is positive, one expects fewer numbers of tropical cyclones 

than when the yearly value is negative. For example, when the yearly value is positive, based on the 

Poisson probability distribution, NTC = 10 ± 1 (36%), NTC <9 (28.4%), and NTC >12 (35.7%); NH 
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= 5 ± 1 (48.1%), NH <4 (19.3%), and NH >6 (32.7%); NMH = 2 ± 1 (72.2%), NMH = 0 (13.5%), and 

NMH >3 (14.3%); and NUSLFH = 1 ± 1 (79.9%) and NUSLFH >2 (20.1%). When the yearly value 

is negative, based on the Poisson probability distribution, NTC = 11 ± 1 (34.7%), NTC <10 (31%), 

and NTC >12 (34.4%); NH = 6 ± 1 (43.6%), NH <5 (19.2%), and NH >7 (37.2%); NMH = 3 ± 1 

(60.6%), NMH <2 (16.4%), and NMH >4 (23%), NMH >6 (4.8%); and NUSLFH = 1 ± 1 (79.1%) 

and NUSLFH >2 (20.9%).

For <QBO>, when the yearly value is positive, one expects greater numbers of tropical 

cyclones than when the yearly value is negative. For example, when the yearly value is positive, based 

on the Poisson probability distribution, NTC = 11 ± 1 (34.6%), NTC <10 (30.3%), and NTC >12 

(35.1%); NH = 6 ± 1 (45%), NH <5 (22.6%), and NH >7 (22.4%); NMH = 3 ± 1 (61.5%), NMH <2 

(19.3%), and NMH >4 (19.2%); and NUSLFH = 1 ± 1 (73.1%) and NUSLFH >3 (26.9%). When 

the yearly value is negative, based on the Poisson probability distribution, NTC = 10 ± 1 (35.6%), 

NTC <9 (26.3%), and NTC >11 (38.1%); NH = 6 ± 1 (45.8%), NH <5 (26.4%), and NH >7 (27.8%); 

NMH = 2 ± 1 (66.9%), NMH = 0 (7.8%), and NMH >3 (25.3%); and NUSLFH = 1 ± 1 (81.6%) and 

NUSLFH >2 (18.4%).

For <AMO>, when the yearly value is positive, one expects greater numbers of tropical 

cyclones than when the yearly value is negative. For example, when the yearly value is positive, based 

on the Poisson probability distribution, NTC = 12 ± 1 (33.3%), NTC <11 (31.1%), and NTC >13 

(35.7%); NH = 7 ± 1 (42.8%), NH <6 (28.9%), and NH >8 (28.3%); NMH = 3 ± 1 (59.1%), NMH <2 

(13.8%), and NMH >4 (27.1%); and NUSLFH = 1 ± 1 (73.3%) and NUSLFH >2 (26.7%). When the 

yearly value is negative, based on the Poisson probability distribution, NTC = 9 ± 1 (37.9%), NTC 

<8 (28.2%), and NTC >10 (33.9%); NH = 5 ± 1 (48.8%), NH <4 (21.3%), and NH >6 (29.8%); NMH 

= 1 ± 1 (69.6%) and NMH >2 (30.5%); and NUSLFH = 1 ± 1 (83.4%) and NUSLFH >2 (16.7%).

For <AMM>, when the yearly value is positive, one expects greater numbers of tropical 

cyclones than when the yearly value is negative. For example, when the yearly value is positive, based 

on the Poisson probability distribution, NTC = 12 ± 1 (33.2%), NTC <11 (30.7%), and NTC >13 

(36.1%); NH = 7 ± 1 (42.4%), NH <6 (25.9%), and NH >8 (31.6%); NMH = 3 ± 1 (56.7%), NMH <2 

(11.3%), and NMH >4 (32.1%); and NUSLFH = 1 ± 1 (73.9%) and NUSLFH >2 (26.1%). When the 

yearly value is negative, based on the Poisson probability distribution, NTC = 9 ± 1 (38.2%), NTC 

<8 (31.1%), and NTC >10 (30.7%); NH = 4 ± 1 (49.5%), NH <3 (12.8%), and NH >5 (37.7%); NMH 

= 1 ± 1 (80.9%) and NMH >2 (19.1%); and NUSLFH = 1 ± 1 (83.6%) and NUSLFH >2 (16.4%).

Through the first few months of 2012, the January–March average of monthly AT (7.37 

°C) has been running 2.18 °C warmer than the average January–March value (i.e., 5.19 ± 1.22 °C) 

based on the interval 1945–2011. In fact, the January–March 2012 average is the second warmest 

January–March average during the interval 1945–2011, second only to the 1996 January–March average (8.37 °C). Since 1995 (i.e., the beginning of the current, more active interval), there have been only 

2 yr with yearly <AT> below 9.48 °C (1996 and 2010). Also, since 1995, there have been only 2 yr with 

a January–March average below 5.19 °C (2001 and 2010). So, during the current interval 1945–2011, 

when the January–March average exceeds 5.19 °C, 14 of 17 yearly <AT> exceeded 9.48 °C (i.e., 82% 

of the years during the current, more active interval that had a January–March average temperature 

above 5.19 °C also had yearly <AT> higher than 9.48 °C). A linear fit of the yearly <AT> versus 
154

the January–March average for the interval 1945–2011 (not shown) results in the regression <AT> 

= 7.977 + 0.292 <J–M>, where <J–M> is the January–March average temperature. The inferred 

regression has r = 0.658, r2 = 0.433, se = 0.382 °C, and cl >99.9%. Applying the 2012 <J–M> 

= 7.37 °C, one infers the yearly <AT> = 10.13 ± 0.38 °C for 2012, a value considerably above the 

long-term average of 9.48 °C (a difference of about 1.7 se). So, unless 2012 turns out to be a statistical outlier, one strongly expects the yearly <AT> for 2012 to exceed its long-term average (probably, 

being above 10 °C). Hence, the Poisson probability distribution for yearly <AT> above its long-term 

average should be appropriate for predicting the 2012 hurricane season, thereby, indicating 72.1% 

probability that NTC ≥10, 81.1% probability that NH ≥5, 85.1% probability that NMH ≥2, and 

71.3% probability that NUSLFH ≤3.

For <NAO>, since 1995, 11 of the 17 yearly <NAO> have been of negative value. The first 

3 mo of 2012 have seen positive values for NAO (1.17, 0.42, and 1.27). Only 13 previous years during the interval 1945–2011 had positive NAO for the first 3 mo of the years, including the years 

1961, 1972, 1973, 1989, 1990, 1993, 1994, 1995, 1999, 2000, 2002, 2003, and 2008. Of these, all 

turned out to have positive yearly <NAO>, except 1973, 1995, and 2008. So, for 77% of the years 

that had positive monthly NAO for each of the first 3 mo of the year, those years also turned out 

to have positive yearly <NAO>. Presuming that 2012 will not be an outlier year, one expects the 

yearly <NAO> to be positive. Hence, the Poisson probability distribution for positive yearly <NAO> 

should be appropriate for predicting the 2012 hurricane season, thereby, indicating 71.6% probability 

that NTC ≥9, 80.7% probability that NH ≥4, 86.5% probability that NMH ≥1, and 79.1% probability 

that NUSLFH ≤2.

For <QBO>, in the span of 1948–2011, there have been only 26 yr of positive yearly <QBO> 

(at the 30 mbar height). So, more than half the years have been of negative yearly <QBO> (53.1%). 

Only on two occasions have there been back-to-back positive <QBO> years. Since 2011 was a positive <QBO> year, it is unlikely that the yearly <QBO> for 2012 will be positive. Indeed, the first 3 mo 

of 2012 have had negative monthly QBO (–16.09, –15.26, and –16.75). Of the 33 yr having the first 

3 mo always of negative monthly QBO value, 27 yr were of negative yearly <QBO> value (81.8%). 

Presuming 2012 will not be an outlier year, one expects the yearly <QBO> to be negative. Hence, the 

Poisson probability distribution for negative yearly <QBO> should be appropriate for predicting the 

2012 hurricane season, thereby, indicating 73.7% probability that NTC ≥9, 73.6% probability that 

NH ≥5, 92.2% probability that NMH ≥1, and 81.6% probability that NUSLFH ≤2.

For <AMO>, since 1995, all years, except 1996, have been of positive yearly <AMO>. For 

2012, the month of January had negative AMO, while the months of February and March had positive AMO, yielding a positive AMO average value for the first 3 mo of 2012. For the interval 1948–

2011, there have been 31 yr with the first 3 mo averaging a positive AMO value. Of these, all turned 

out to have positive yearly <AMO>, except the years 1950, 1956, 1964, 1967, and 1970 (83.9%). 

Presuming 2012 will not be an outlier year, one expects the yearly <AMO> to be positive. Hence, the 

Poisson probability distribution for positive yearly <AMO> should be appropriate for predicting the 

2012 hurricane season, thereby indicating 68.9% probability that NTC ≥11, 71.1% probability that 

NH ≥6, 86.2% probability that NMH ≥2, and 83.4% probability that NUSLFH ≤2.
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For <AMM>, since 1995, all years, except 2000 and 2002, have been of positive yearly 

<AMM>. For 2012, the month of March had negative AMM, while the months of January and 

February had positive AMM, yielding a positive AMM average value for the first 3 mo of 2012. For 

the interval 1948–2011, there have been 33 yr with the first 3 mo averaging a positive AMM value. 

Of these, all turned out to have positive yearly <AMM>, except the years 1954, 1959, 1963, 1967, 

2000, and 2002 (81.8%). Presuming 2012 will not be an outlier year, one expects the yearly <AMM> 

to be positive. Hence, the Poisson probability distribution for positive yearly <AMM> should be 

appropriate for predicting the 2012 hurricane season, thereby, indicating 69.3% probability that 

NTC ≥11, 74.1% probability that NH ≥6, 88.7% probability that NMH ≥2, and 83.6% probability 

that NUSLFH ≤2.

Regarding the other tropical cyclone parameters, when the yearly <AT> is ≥9.48 °C (true 

for 30 of the 67 yr during the interval 1945–2011 and anticipated to be true for 2012), <N. LAT> 

= 21.5 ± 3.1 deg, <W. LONG> = 64.4 ± 6.4 deg, PWS = 130.3 ± 16.4 kt, <PWS> = 74.9 ± 9 kt, LP 

= 932.3 ± 20.7 mbar, <LP> = 977.8 ± 8.9 mbar, ACE = 125.8 ± 59.7, NSD = 65.8 ± 26.4 days, ACE/

NSD = 1.87 ± 0.43, HISACE = 35.6 ± 14.6, LISNSD = 12.6 ± 3.7 days, <NSD> = 5 ± 1.1 days, 

NHD = 28.4 ± 14.2 days, NMHD = 8.1 ± 6.5 days, and NCTA = 135% ± 58.4%. Hence, presuming yearly <AT> ≥9.48 °C in 2012, one anticipates the following yearly parametric values for 2012: 

<N. LAT> ≤24.6 deg, <W. LONG> ≤70.8 deg, PWS ≤147 kt, <PWS> ≤83.9 kt, LP ≤953 mbar, <LP> 

≤986.7 mbar, ACE ≤185.5 (and ACE ≥66.1), NSD ≤92 days (and NSD ≥39 days), ACE/NSD ≤ 2.3, 

HISACE ≤50.2, LISNSD ≤16 days, <NSD> ≤6.2 days, NHD ≤42.5 days (and NHD ≥14.2 days), 

NMHD ≤14.6 days (and NMHD ≥1.7 days), and NTCA ≤193.4% (and NTCA ≥76.6%).

When the yearly <NAO> is negative (true for 35 of the 62 yr during the interval 1950–2011 

and anticipated to be true for 2012), <N. LAT> = 21.6 ± 3.1 deg, <W. LONG> = 64 ± 6.6 deg, PWS 

= 130 ± 20.6 kt, <PWS> = 77.4 ± 9.1 kt, LP = 934.7 ± 21.2 mbar, <LP> = 977.5 ± 8.1 mbar, ACE 

= 113 ± 61.6, NSD = 61.6 ± 35.4 days, ACE/NSD = 1.85 ± 0.46, HISACE = 33.7 ± 15.9, LISNSD 

= 11.5 ± 3.3 days, <NSD> = 5.3 ± 1.4 days, NHD = 27.7 ± 15.6 days, NMHD = 6.9 ± 5.1 days, and 

NCTA = 124.9% ± 63.1%. Hence, presuming yearly <NAO> to be negative in 2012, one anticipates 

the following yearly parametric values for 2012: <N. LAT> ≤24.7 deg, <W. LONG> ≤70.6 deg, 

PWS ≤151 kt, <PWS> ≤86.5 kt, LP ≤956 mbar, <LP> ≤985.6 mbar, ACE ≤174.6 (and ACE ≥51.4), 

NSD ≤97 days (and NSD ≥26 days), ACE/NSD ≤2.31, HISACE ≤49.6, LISNSD ≤15 days, <NSD>

≤6.7 days, NHD ≤43 days (and NHD ≥12 days), NMHD ≤12 days (and ≥2 days), and NTCA ≤188% 

(and NTCA ≥61.8%).

When the yearly <QBO> is negative (true for 38 of the 64 yr during the interval 1948–2011 

and anticipated to be true for 2012), <N. LAT> = 21.8 ± 3.6 deg, <W. LONG> = 64.9 ± 6.1 deg, 

PWS = 125.8 ± 20.1 kt, <PWS> = 75 ± 8.7 kt, LP = 940 ± 19.8 mbar, <LP> = 980.3 ± 7.2 mbar, 

ACE = 95.7 ± 56.2, NSD = 53.7 ± 33.8 days, ACE/NSD = 1.8 ± 0.42, HISACE = 31.2 ± 15.1, 

LISNSD = 10.56 ± 2.88 days, <NSD> = 4.87 ± 1.46 days, NHD = 22.8 ± 13.9 days, NMHD = 5.9 

± 5 days, and NCTA = 107.8% ± 60.6%. Hence, presuming yearly <QBO> to be negative in 2012, 

one anticipates the following yearly parametric values for 2012: <N. LAT> ≤25.4 deg, <W. LONG> 

≤71 deg, PWS ≤146 kt, <PWS> ≤83.7 kt, LP ≤960 mbar, <LP> ≤987.5 mbar, ACE ≤151.9 (and ACE 

≥39.5), NSD ≤88 days (and NSD ≥20 days), ACE/NSD ≤2.22, HISACE ≤46.3, LISNSD ≤13 days, 

<NSD> ≤6.3 days, NHD ≤37 days (and NHD ≥9 days), NMHD ≤11 days (and NMHD ≥1 day), and 

NTCA ≤168.4% (and NTCA ≥47.2%).
156

When the yearly <AMO> is positive (true for 34 of the 64 yr during the interval 1948–2011 

and anticipated to be true for 2012), <N. LAT> = 20.8 ± 2.5 deg, <W. LONG> = 63.6 ± 5.4 deg, 

PWS = 132.1 ± 16.3 kt, <PWS> = 76.4 ± 9.7 kt, LP = 931.9 ± 20.8 mbar, <LP> = 977.3 ± 8.7 mbar, 

ACE = 127.3 ± 56.4, NSD = 67.3 ± 34 days, ACE/NSD = 1.95 ± 0.49, HISACE = 37.6 ± 14.6, 

LISNSD = 12.6 ± 3.1 days, <NSD> = 5.3 ± 1.3 days, NHD = 29.3 ± 13.8 days, NMHD = 8.5 ± 

7.7 days, and NCTA = 135.2% ± 60.8%. Hence, presuming yearly <AMO> to be positive in 2012, 

one anticipates the following yearly parametric values for 2012: <N. LAT> ≤23.3 deg, <W. LONG> 

≤69 deg, PWS <148 kt, <PWS> ≤86.1 kt, LP ≤953 mbar, <LP> ≤986 mbar, ACE ≤183.7 (and ACE 

≥70.9), NSD ≤101 days (and NSD ≥33 days), ACE/NSD ≤ 2.44, HISACE ≤52.2, LISNSD ≤16 days, 

<NSD> ≤6.6 days, NHD ≤43 days (and NHD ≥15 days), NMHD ≤16 days (and NMHD ≥1 day), 

and NTCA ≤196% (and NTCA ≥74.4%).

When the yearly <AMM> is positive (true for 36 of the 64 yr during the interval 1948–2011 

and anticipated to be true for 2012), <N. LAT> = 20.7 ± 2.4 deg, <W. LONG> = 63 ± 5.4 deg, 

PWS = 133.5 ± 18.5 kt, <PWS> = 77.7 ± 10.1 kt, LP = 931.5 ± 21.5 mbar, <LP> = 977 ± 9.1 

mbar, ACE = 129.8 ± 60.8, NSD = 69.1 ± 33.5 days, ACE/NSD = 1.9 ± 0.49, HISACE = 36.9 

± 15.4, LISNSD = 12.1 ± 2.5 days, <NSD> = 5.4 ± 1.4 days, NHD = 30.5 ± 15 days, NMHD = 8.7 

± 6.2 days, and NCTA = 143.1% ± 61%. Hence, presuming yearly <AMM> to be positive in 2012, 

one anticipates the following yearly parametric values for 2012: <N. LAT> ≤23.1 deg, <W. LONG> 

≤68.4 deg, PWS ≤152 kt, <PWS> ≤87.8 kt, LP ≤953 mbar, <LP> ≤986.1 mbar, ACE ≤190.6 (and ACE 

≥69), NSD ≤103 days (and ≥36 days), ACE/NSD ≤ 2.39, HISACE ≤52.3, LISNSD ≤15 days, <NSD> 

≤6.8 days, NHD ≤46 days (and NHD ≥16 days), NMHD ≤15 days (and ≥3 days), and NTCA ≤204.1% 

(and NTCA ≥82.1%).

It is apparent then, that should the yearly <AT> for 2012 be ≥9.48 °C and the yearly <AMO> 

and <AMM> be positive, these conditions being expected, one would anticipate seasonal frequencies and parametric values of tropical cyclones in the North Atlantic basin during the 2012 hurricane 

season to be above long-term averages. Countering this, however, is the expected positive <NAO>, 

negative <QBO>, and the anticipated recurrence of EN in 2012, which, if true, would suggest near 

normal to below average frequencies and parametric values. Hence, at this time, it remains disconcertingly uncertain as to how active and strong the 2012 hurricane season will be. If EN fails to recur, 

then one leans towards the 2012 season being near normal to above average in activity, being driven 

by the warmer surface air and ocean temperatures. On the other hand, if EN should recur during 

the hurricane season, then one leans towards the 2012 season being near normal to below average in 

activity. (Presently, the ENSO condition is that of ENSO neutral, with LN not expected to redevelop 

later this year. The official NOAA forecast calls for ENSO neutral conditions through the summer of 

2012, followed by equal chances of either ENSO neutral or EN conditions after September 2012. It 

should be noted, however, that about half of the dynamical models predict development of EN conditions during the summer of 2012, although considerable forecast uncertainty continues due largely 

to the inability of the models to predict whether the warmer SST will result in the ocean-atmosphere 

coupling required for a sustained EN event.52,128) 
157

2.10.3 Decadal Trends

Figure 75 displays the decadal frequencies of NTC, NTS, NH, NMH, and NUSLFH for the 

6 decades of the 1950s–2000s. Plainly, NTC, NH, and NMH all show a decrease in activity from the 

1950s through the 1980s and an increase from the 1980s through the 2000s. For NTS, it has risen 

throughout, especially after the 1990s. For NUSLFH, it has remained fairly flat, although the variance has increased in the 2000s. What the current decade will be like, however, remains murky. Number

NTC

Decade

0 0

5

10

15

20

25

50s 60s 70s 80s 90s 00s 10s (a)

NTS

Number

Decade

5

10

15

50s 60s 70s 80s 90s 00s 10s (b)

NH

Number

Decade

5

0

10

15

50s 60s 70s 80s 90s 00s 10s (c)

NMH

Number

Number

Number

Decade

5

10

50s 60s 70s 80s 90s 00s 10s (d)

5

NUSLFH

Decade

10

0

5

0

50s 60s 70s 80s 90s 00s 10s (e)

Figure 75. Decadal variations for (a) NTC, (b) NTS, (c) NH, (d) NMH, and (e) NUSLFH.
158

The year 2012 will be the third year of the decade of the 2010s. The first 2 yr of the current 

decade have averaged NTC = 19, NTS = 9.5, NH = 9.5, NMH = 4.5, and NUSLFH = 0.5. For NTC, 

NTS, NH, and NMH, these averages seem reflective of the previous decade, although slightly higher, 

suggesting that the present decade either will continue to be reflective of an increase in activity and 

strength or, possibly, flatten, attaining a plateau of similar activity and strength that was seen in the 

previous decade.

Figures 76–78 show the decadal variation of the other tropical cyclone parameters. For 

<N. LAT>, plainly there was movement to more northerly latitudes of the latitudinal centroid from 

the 1950s to the 1970s. However, the centroid is found to have returned to a more tropical location in 

the 1990s and 2000s. While true, the decade of the 2000s may be the start of a new, more northerly 

movement that may manifest itself during the decade of the 2010s. Interestingly, the decadal movement of <W. LONG> seems suggestive of a long-term eastward movement over time. Degrees

<N. LAT>

Decade

15

20

25

30

50s 60s 70s 80s 90s 00s 10s

(a)

Degrees

<W. LONG>

Decade

50

60

70

80

50s 60s 70s 80s 90s 00s 10s

(b)

Knots

Knots

PWS

Decade

90

120

105

135

150

165

50s 60s 70s 80s 90s 00s 10s

(c)

<PWS>

Decade

50

80

90

70

60

100

50s 60s 70s 80s 90s 00s 10s

(d)

Figure 76. Decadal variations for (a) <N. LAT>, (b) <W. LONG>, (c) PWS, and (d) <PWS>.
159

Number

<ACE>

Decade

0

50

100

150

200

50s 60s 70s 80s 90s 00s 10s (a)

Number

<NSD>

Decade

0

50

100

150

50s 60s 70s 80s 90s 00s 10s (b)

Number

<ACE/NSD>

Decade

1

1.5

2

2.5

3

50s 60s 70s 80s 90s 00s 10s (c)

Number

<NTCA>

Decade

50

100

150

200

50s 60s 70s 80s 90s 00s 10s (d)

Figure 77. Decadal variations for (a) <ACE>, (b) <NSD>, (c) <ACE/NSD>, and (d) <NTCA>.
160

Number

<HISACE>

Decade

10

20

30

40

50

60

(a) 50s60s70s80s90s00s10s Number

<LISNSD>

Decade

5

0

10

15

20

(b) 50s60s70s80s90s00s10sNumber

<NHD>

Decade

10

0

20

30

40

(c) 50s60s70s80s90s00s10s Number

<NMHD>

Decade

10

0

20

(d) 50s60s70s80s90s00s10s

Figure 78. Decadal variations for (a) <HISACE>, (b) <LISNSD>, (c) <NHD>, 

and (d) <NMHD>.

For PWS, there was a decrease from the 1950s to the 1970s, a flattening from the 1970s to the 

1990s, and an increase in the 2000s. Does this mean that the decade of the 2010s will see storms with 

higher PWS, or will PWS flatten near 135 kt, a la the 1950s?129 For <PWS>, it shows a decrease from 

the 1950s to the 1970s and continued flattening near 70 kt (seasonal average) through the decade of 

the 2000s.

<ACE>, <NSD>, <HISACE>, <LISNSD>, <NHD>, <NMHD>, and <NTCA> all show 

a decrease from the 1950s to the 1970s. From the 1970s through the 2000s, an increase has been 

underway to levels typical of the 1950s, if not higher, especially for <ACE>, <NSD>, and <NTCA>.

Figures 79–81 depict the decadal variations for the 14 surface air temperature and ENSOrelated parameters. For <AT>, it has been increasing since the decade of the 1970s. The first 2 yr of 

the present decade have an average <AT> = 9.53 °C, above the long-term mean of 9.48 °C. Because 

yearly <AT> correlates strongly with yearly measures of atmospheric carbon dioxide obtained at 

Mauna Loa, Hawaii, and because the trend of atmospheric carbon dioxide is upward, it may be that 

<AT> will continue to increase during the present decade.130,131 However, if <AT> is more greatly 
161

influenced by <AMO> and/or <AMM>, its behavior may be more reflective of a cyclic variation 

(with an embedded global warming component), perhaps, decreasing slightly in the near term. Degrees

<AT>

Decade

9

9.5

8.5

10

10.5

11

(a) 50s60s70s80s90s00s10s

Number

<SOI>

Decade

–10

–5

0

5

10

50s60s70s80s90s00s10s (b)

Degrees

<ONI>

Decade

–1.0

–0.5

0

0.5

1.0

50s60s70s80s90s00s10s (c)

NumberNumber

<NAO>

Decade

–1

–0.5

0

0.5

1

50s60s70s80s90s00s10s (d)

<QBO>

Decade

–20

–10

0

10

20

50s60s70s80s90s00s10s (e)

Figure 79. Decadal variations for (a) <AT>, (b) <SOI>, (c) <ONI>, (d) <NAO>, 

and (e) <QBO>.
162

<JMASSTM>

Decade Decade

26

25

24

27

(e) 50s 60s 70s 80s 90s 00s 10s

0

DegreesDegrees

DegreesDegrees

Number

<PDO>

Decade

–1

–2

0

1

2

(a) 50s 60s 70s 80s 90s 00s 10s

<TNI>

Decade Decade

3

2

1

0

–1

–2

–3

(b) 50s 60s 70s 80s 90s 00s 10s

<MEI>

1.5

1

0.5

–0.5

–1

–1.5

(c) 50s 60s 70s 80s 90s 00s 10s

<GSSTEI>

0.5

0

–0.5

(d) 50s 60s 70s 80s 90s 00s 10s

Figure 80. Decadal variations for (a) <PDO>, (b) <TNI>, (c) <MEI>, (d) <GSSTEI>, 

and (e) <JMASSTM>.
163

Number

<AMO>

Decade

–0.5

0

0.5

50s 60s 70s 80s 90s 00s 10s (c)

Number

<AMM>

Decade

–5

0

5

50s 60s 70s 80s 90s 00s 10s (d)

Degrees

<NTA>

Decade

–0.5

0

0.5

50s 60s 70s 80s 90s 00s 10s (a)

Degrees

<CAR>

Decade

–0.5

0

0.5

50s 60s 70s 80s 90s 00s 10s (b)

Figure 81. Decadal variations for (a) <NTA>, (b) <CAR>, (c) <AMO>, and (d) <AMM>.

Similar to the decadal <AT> movements are the decadal movements of <NTA>, <CAR>, 

<AMO>, and <AMM>, with values expected to remain positive (i.e., warmer, on average) during 

the current decade. The decadal movement of <NAO> appears to be negative for the current decade 

as are the decadal movements of <PDO> and <TNI>. The decadal <QBO> is always negative. The 

decadal <JMASSTM> appears to be increasing over time (to warmer temperatures). The decadal 

movements of <ONI>, <MEI>, and <GSSTEI> are quite similar with anomalous values in the 

decade of the 2000s down from peak values in the decade of the 1990s (although still of positive 

value, but near zero). The decadal movement of <SOI> varies inversely with the decadal movement 

of <ONI>.
164

2.10.4 The 34 Strongest Tropical Cyclones and the Distributions of PWS, ISACE, ISNSD, ISNHD, 

ISNMHD, N. LAT, and W. LONG

Table 26 (see appendix) lists the 34 strongest tropical cyclones (based on PWS) of the North 

Atlantic basin during the interval since 1945. At the top of the list are Camille 1969 and Allen 1980, 

both having PWS = 165 kt, both having onset dates in August, and both being US landfalling hurricanes (Camille as a category 5 storm). While Camille formed in the Gulf of Mexico area, Allen 

formed in the lower Atlantic-Cape Verde area. Allen had an LP lower than Camille, a higher individual storm ACE, and a longer individual storm NSD.

Of the 34 strongest tropical cyclones of the North Atlantic basin, only 4 attained PWS ≥160kt, 

10 had PWS of 150 and 155 kt, 12 had PWS of 140 and 145 kt, and 7 had PWS of 135 kt. Only 

4 storms had LP less than 900 mbar, with Wilma 2005 having the lowest observed LP 

(882mbar). Until Ivan came along in 2004, Donna 1960 had held the record for being 

the individual storm having the highest ACE for more than 40 yr (Donna had individual storm accumulated cyclone energy (ISACE) = 64.6 and Ivan had ISACE 

= 70.4). While Carrie 1957 has the longest individual storm number of storm days (ISNSD) on the 

list (19.5 days), it is not the record holder; that distinction belongs to Ginger 1971 (PWS = 95 kt and 

ISNSD = 21.25 days).

Only 3 of the strongest storms were birthed in group 1, the Gulf of Mexico area (Camille 

1969, Anita 1977, and Ethel 1960); only 2 of the strongest storms were birthed in group 3, the east 

coast area (Rita 2005 and Katrina 2005); and none were birthed in group 5, the open Atlantic area. 

By far, the largest number of strongest storms were birthed in group 2 (the Caribbean area), accounting for 9 storms, and group 4 (the lower Atlantic-Cape Verde area), accounting for 20 storms. Only 

5 of the strongest storms were birthed outside of the months of August and September (Emily 2005 

in July; Wilma 2005, Mitch 1998, and Hattie 1961 in October; and Lenny 1999 in November).

Tables 27–33 (see appendix) provide the distributions of PWS, ISACE, ISNSD, ISNHD, 

ISNMHD, N. LAT, and W. LONG, respectively, for the tropical cyclones in the North Atlantic basin 

during the interval 1945–2010. The largest grouping of tropical cyclone PWS is PWS = 45–54 kt, 

accounting for 136 of the 715 storms (19%). Only 97 storms had PWS ≥ 115 kt (13.6%) and only 

34 had PWS ≥135 kt (4.8%; they are identified by name in the comments, being the storms listed 

in table 26). More than two-thirds of the storms had ISACE ≤9.9 (494 of 715 storms, 69.1%) and 

more than 90% had ISACE ≤29.9 (667/715 = 93.3%). Only 24 of the storms had ISACE ≥40 (5.6%; 

they are identified by name in the comments). About half the tropical cyclones had ISNSD ≤4 days 

(373/715 = 52.2%), with the largest single grouping being ISNSD = 1.1–2 days duration (125/715 

= 17.5%). Some 76 storms, however, had ISNSD >10 days (76/715 = 10.6%; they are identified by 

name in the comments). Some 306 storms had zero ISNHD and more than half of the storms had 

ISNHD ≤1 day (386/715 = 54%). Only 23 storms had ISNHD ≥10 days (23/715 = 3.2%; they are 

identified by name in the comments). Some 536 storms had zero ISNMHD and more than 80% had 

ISNMHD ≤1 day (603/715 = 84.3%). Only two storms (Donna 1960 and Ivan 2004) had ISNMHD 

≥10 days. About one-fourth of the storms formed at N. LAT <15 deg (179/715 = 25%) and only 

4 storms formed at N. LAT ≥40 deg. Interesting is that the four lowest N. LAT formation storms 

occurred recentlysince 1990. Finally, about 60% of the storms formed at W. LONG ≥60 deg, with 

only 4 storms forming at W. LONG = 10–19.9 deg.
165

3. SUMMARY

In this investigation, examined were the statistical aspects of the 715 tropical cyclones that 

formed in the North Atlantic basin during the interval 1945–2010, including 306 storms of only 

tropical storm strength, 409 storms of hurricane strength, 179 storms of major or intense hurricane 

strength, and 108 storms that struck the US coastline at hurricane strength. The interval 1995–2010 

was found, on average, to be about 54% more active than the previous interval 1945–1994 in terms of 

the number of tropical cyclones that formed in a season, about 73% more active in terms of tropical 

cyclones that attained only tropical storm strength, about 41% more active in terms of the number 

storms of hurricane strength, about 62% more active in terms of the number of storms of major 

hurricane strength, and about 20% more active in terms of storms that made landfall along the US 

coastline at hurricane strength. Also found was that, on average, the PWS of a tropical cyclone during a season has increased by about 5%, although the <PWS> has slightly decreased by about 2%. 

Additionally, the seasonal ACE was found to have increased during the current, more active interval, on average, by more than 63%, as did the seasonal NSD by more than 75%, the seasonal NHD 

by about 45%, the seasonal NMHD by about 77%, and the seasonal NTCA index by about 59%. 

HISACE and LISNSD, likewise, were found to have increased, on average, by about 28% and 17%, 

respectively, and strong correlations were found to exist, in particular, between the 10-yma tropical 

cyclone parametric values and those of the Armagh Observatory (Northern Ireland) surface air temperature, the AMO index, the AMM index, and the NAO index, in addition to those of the ONI and 

QBO indices.

Poisson probability distributions were determined for the overall interval 1945–2010, as well 

as strictly for the current, more active interval, 1995–2010. For the overall interval, NTC = 10 ± 1 

(35.3%), NTC <9 (25%), and NTC >11 (39.7%); NTS = 4 ± 1 (52.3%), NTS <3 (16.3%), and NTS 

>5 (31.4%); NH = 6 ± 1 (45.7%), NH <5 (25.9%), and NH >7 (28.4%); NMH = 2 ± 1 (64.7%), NMH 

= 0 (6.7%), and NMH >3 (28.6%); and NUSLFH = 1 ± 1 (78.3%) and NUSLFH >2 (21.7%). For 

the current, more active interval, NTC = 14 ± 1 (30.4%), NTC <13 (27.3%), and NTC >15 (42.3%); 

NTS = 6 ± 1 (43.6%), NTS <5 (19.2%), and NTS >7 (37.2%); NH = 7 ± 1 (40.6%), NH <6 (20.1%), 

and NH >8 (39.3%); NMH = 3 ± 1 (56%), NMH <2 (10.7%), and NMH >4 (33.2%); and NUSLFH 

= 1 ± 1 (70.4%) and NUSLFH >2 (29.6%). Therefore, dependent upon whether the 2012 hurricane 

season is more akin to the overall interval or to the current, more active interval, one predicts the 

central ±1 storm intervals to be either NTC = 10 ± 1 (35.3%, overall interval) or NTC = 14 ± 1 

(30.4%, current, more active interval), and so forth, with greater chance for NTC >11 and NTC >15, 

respectively, than NTC <9 and NTC <13, respectively, and with the bulk of the storms occurring 

during the months of August through October.

Accounting for the ENSO condition during the overall interval, when the season is classified as ENY, NTC = 9 ± 1 (38.2%), NTC <8 (30.9%), and NTC >10 (31%); NTS = 4 ± 1 (53.9%), 

NTS <3 (19.6%), and NTS >5 (26.5%); NH = 4 ± 1 (50.8%), NH <3 (14.2%), and NH >5 (35.1%); 

NMH = 2 ± 1 (72.2%), NMH = 0 (13.5%), and NMH >3 (14.3%); and NUSLFH = 1 ± 1 (89.4%) 
166

and NUSLFH >2 (10.6%). When the season is classified as LNY, NTC = 11 ± 1 (34.1%), NTC <10 

(27.2%), and NTC >12 (38.6%); NTS = 4 ± 1 (51.8%), NTS <3 (15.5%), and NTS >5 (32.6%); NH 

= 7 ± 1 (42.8%), NH <6 (30.1%), and NH >8 (27.1%); NMH = 3 ± 1 (59.2%), NMH <2 (13.9%), 

and NMH >4 (26.9%); and NUSLFH = 2 ± 1 (70.9%), NUSLFH = 0 (11.1%), and NUSLFH >3 

(18.1%). When the season is classified as NY, NTC = 11 ± 1 (34.7%), NTC <10 (31.3%), and NTC 

>12 (34%); NTS = 4 ± 1(51%), NTS <3 (14.6%), and NTS >5 (34.4%); NH = 6 ± 1 (44.9%), NH 

<5 (22.5%), and NH >7 (32.6%); NMH = 2 ± 1 (64.5%), NMH = 0 (6.7%), and NMH >3 (28.8%); 

and NUSLFH = 1 ± 1 (77.6%) and NUSLFH >2 (22.4%). Therefore, dependent upon what the 

ENSO condition will be for 2012, one predicts the central ±1 storm intervals to be either NTC = 9 

± 1 (38.2%, ENY), NTC = 11 ± 1 (34.1%, LNY), or NTC = 11 ± 1 (34.7%, NY) and so forth, with 

higher probabilities for increased frequencies expected if the 2012 hurricane season is classified as 

non-ENY.

For the yearly <AT> ≥9.48 °C (i.e., the long-term mean surface air temperature at Armagh 

Observatory, Northern Ireland), NTC = 12 ± 1 (32.8%), NTC <11 (27.9%), and NTC >13 (39.3%); 

NTS = 5 ± 1 (46.5%), NTS <4 (15.6%), and NTS >6 (37.9%); NH = 6 ± 1 (43.5%), NH <5 (18.9%), 

and NH >7 (37.6%); NMH = 3 ± 1 (59.9%), NMH <2 (14.9%), and NMH >4 (25.2%); and 

NUSLFH = 2 ± 1 (71.6%), NUSLFH = 0 (12.3%), and NUSLFH >3 (16.1%). For the yearly <AT> 

<0.48 °C, NTC = 9 ± 1 (37.9%), NTC <8 (28.1%), and NTC >10 (34%); NTS = 3 ± 1 (57.3%), NTS 

<2 (11.8%), and NTS >4 (30.9%); NH = 5 ± 1 (47.4%), NH <4 (18%), and NH >6 (34.6%); NMH 

= 2 ± 1 (70.9%), NMH = 0 (11.2%), and NMH >3 (17.9%); and NUSLFH = 1 ± 1 (86.4%) and 

NUSLFH >2 (13.6%). Therefore, dependent upon whether or not the yearly <AT> for 2012 exceeds 

its long-term average, one predicts either NTC = 12 ± 1 (32.8%, above average) or NTC = 9 ± 1 

(37.9%, below average), and so forth. Because the yearly <AT> is expected to exceed its long-term 

average in 2012, one anticipates higher frequencies during the 2012 hurricane season, with NTC ≥11 

(72.1%), NTS ≥4 (84.4%), NH ≥5 (81.1%), NMH ≥2 (85.1%), and NUSLFH ≥1 (87.7%).

For the yearly <AMO> being of positive value, NTC = 12 ± 1 (33.3%), NTC <11 (31.1%), 

and NTC >13 (35.7%); NTS = 5 ± 1 (49.3%), NTS <4 (22.9%), and NTS >6 (27.8%); NH = 7 ± 1 

(42.8%), NH <6 (28.9%), and NH >8 (28.3%); NMH = 3 ± 1 (59.1%), NMH <2 (13.8%), and NMH 

>4 (27.1%); and NUSLFH = 1 ± 1 (73.3%) and NUSLFH >2 (26.7%). For the yearly <AMO> 

being of negative value, NTC = 9 ± 1 (37.9%), NTC <8 (28.2%), and NTC >10 (33.9%); NTS = 3 

± 1 (54.1%), NTS <2 (9.4%), and NTS >4 (36.5%); NH = 5 ± 1 (48.8%), NH <4 (21.3%), and NH >6 

(29.8%); NMH = 1 ± 1 (68.6%) and NMH >2 (31.4%); and NUSLFH = 1 ± 1 (83.4%) and NUSLFH 

>2 (16.7%). Therefore, dependent upon whether the yearly <AMO> is of positive or negative value 

for 2012, one predicts either NTC = 12 ± 1 (33.3%, positive) or NTC = 9 ± 1 (37.9%, negative), and 

so forth. Because the yearly <AMO> is expected to be of positive value in 2012, one anticipates 

higher frequencies during the 2012 hurricane season, with NTC ≥11 (68.9%), NTS ≥4 (77.1%), NH 

≥6 (71.1%), NMH ≥2 (86.2%), and NUSLFH ≥1 (83.3%).

For the yearly <AMM> being of positive value, NTC = 12 ± 1 (33.2%), NTC <11 (30.7%), 

and NTC >13 (36.1%); NTS = 5 ± 1 (49.7%), NTS <4 (25.7%), and NTS >6 (24.7%); NH = 7 ± 1 

(42.4%), NH <6 (25.9%), and NH >8 (31.6%); NMH = 3 ± 1 (56.7%), NMH <2 (11.3%), and NMH 

>4 (32.1%); and NUSLFH = 1 ± 1 (73.9%) and NUSLFH >2 (26.1%). For the yearly <AMM> 

being of negative value, NTC = 9 ± 1 (38.2%), NTC <8 (31.1%), and NTC >10 (30.7%); NTS 
167

= 4 ± 1 (54.5%), NTS <3 (21.8%), and NTS >5 (23.7%); NH = 4 ± 1 (49.5%), NH <3 (12.8%), and 

NH >5 (37.7%); NMH = 1 ± 1 (80.9%) and NMH >2 (19.1%); and NUSLFH = 1 ± 1 (83.6%) and 

NUSLFH >2 (16.4%). Therefore, dependent upon whether the yearly <AMM> is of positive or 

negative value for 2012, one predicts either NTC = 12 ± 1 (33.2%, positive) or NTC = 9 ± 1 (38.2%, 

negative), and so forth. Because the yearly <AMM> is expected to be of positive value in 2012, one 

anticipates higher frequencies during the 2012 hurricane season, with NTC ≥11 (69.3%), NTS ≥4 

(74.3%), NH ≥6 (74.1%), NMH ≥2 (88.7%), and NUSLFH ≥1 (83%).

For the yearly <ONI> being of positive value, NTC = 10 ± 1 (35.8%), NTC <9 (27.2%), 

and NTC >11 (37%); NTS = 4 ± 1 (52.3%), NTS <3 (16.3%), and NTS >5 (31.4%); NH = 5 ± 1 

(45.7%), NH <4 (15.4%), and NH >6 (38.9%); NMH = 2 ± 1 (69.1%), NMH = 0 (9.4%), and NMH 

>3 (21.5%); and NUSLFH = 1 ± 1 (80.9%) and NUSLFH >2 (19.1%). For the yearly <ONI> being 

of negative value, NTC = 11 ± 1 (34.7%), NTC <10 (31%), and NTC >12 (34.4%); NTS = 4 ± 1 

(51.5%), NTS <3 (15.1%), and NTS >5 (33.3%); NH = 6 ± 1 (44.6%), NH <5 (21.5%), and NH >7 

(33.9%); NMH = 3 ± 1 (61.5%), NMH <2 (19%), and NMH >4 (19.5%); and NUSLFH = 1 ± 1 

(78.1%) and NUSLFH >2 (21.9%). Therefore, dependent upon whether the yearly <ONI> is of positive or negative value for 2012, one predicts either NTC = 10 ± 1 (35.8%, positive) or NTC = 11 ± 1 

(34.7%, negative), and so forth. Because an EN is expected to recur in late 2012, the yearly <ONI> 

is expected to be of positive value in 2012; hence, one anticipates lower frequencies during the 2012 

hurricane season, with NTC ≤11 (63%), NTS ≤5 (68.6%), NH ≤6 (61.1%), NMH ≤3 (68.5%), and 

NUSLFH ≤2 (80.9%). On the other hand, if an EN event fails to recur during the hurricane season, 

while the value of <ONI> might be positive for the year, 2012 would be classified as non-ENY (more 

specifically, NY), thereby, potentially allowing for increased frequencies during the 2012 hurricane 

season.

For the yearly <NAO> being of positive value, NTC = 10 ± 1 (36%), NTC <9 (28.4%), 

and NTC >11 (35.7%); NTS = 4 ± 1 (50.2%), NTS <3 (13.5%), and NTS >5 (36.3%); NH = 5 ± 1 

(48.1%), NH <4 (19.3%), and NH >6 (32.7%); NMH = 2 ± 1 (72.2%), NMH = 0 (13.5%), and NMH 

>3 (14.3%); and NUSLFH = 1 ± 1 (79.9%) and NUSLFH >2 (20.1%). For the yearly <NAO> 

being of negative value, NTC = 11 ± 1 (34.7%), NTC <10 (31%), and NTC >12 (34.4%); NTS = 4 

± 1 (53%), NTS <3 (17.5%), and NTS >5 (29.5%); NH = 6 ± 1 (43.6%), NH <5 (19.2%), and NH 

>7 (37.2%); NMH = 3 ± 1 (60.6%), NMH <2 (16.4%), and NMH >4 (23%); and NUSLFH = 1 

± 1 (79.1%) and NUSLFH >2 (20.9%). Therefore, dependent upon whether the yearly <NAO> is of 

positive or negative value for 2012, one predicts either NTC = 10 ± 1 (36%, positive) or NTC = 11 

± 1 (34.7%, negative), and so forth. Because the yearly <NAO> is expected to be of positive value 

in 2012, one anticipates lower frequencies during the 2012 hurricane season, with NTC ≤11 (64.3%), 

NTS ≤5 (63.7%), NH ≤6 (67.3%), NMH ≤3 (85.7%), and NUSLFH ≤2 (79.9%).

For the yearly <QBO> being of positive value, NTC = 11 ± 1 (34.6%), NTC <10 (30.3%), 

and NTC >12 (35.1%); NTS = 4 ± 1 (50.2%), NTS <3 (13.5%), and NTS >5 (36.3%); NH = 6 ± 1 

(45%), NH <5 (22.6%), and NH >7 (32.4%); NMH = 3 ± 1 (61.5%), NMH <2 (19.3%), and NMH 

>4 (19.2%); and NUSLFH = 1 ± 1 (73.1%) and NUSLFH >2 (26.9%). For the yearly <QBO> 

being of negative value, NTC = 10 ± 1 (35.6%), NTC <9 (26.3%), and NTC >11 (38%); NTS = 4 

± 1 (52.9%), NTS <3 (17.4%), and NTS >5 (29.7%); NH = 6 ± 1 (45.8%), NH <5 (26.4%), and NH 

>7 (27.8%); NMH = 2 ± 1 (66.9%), NMH = 0 (7.8%), and NMH >3 (25.3%); and NUSLFH = 1 
168

± 1 (81.6%) and NUSLFH >2 (18.4%). Therefore, dependent upon whether the yearly <QBO> is of 

positive or negative value for 2012, one predicts either NTC = 11 ± 1 (34.6%, positive) or NTC = 10 

± 1 (35.6%, negative), and so forth. Because the yearly <QBO> is expected to be of negative value in 

2012, one anticipates lower frequencies during the 2012 hurricane season, with NTC ≤11 (62%), NTS 

≤5 (70.3%), NH ≤7 (72.2%), NMH ≤3 (74.7%), and NUSLFH ≤2 (81.6%).

Thus, as can be seen from above, three of the parameters (<AT>, <AMO>, and <AMM>) 

each suggest that the 2012 hurricane season, likely, will be one described as being of above long-term 

average activity. On the other hand, three other parameters (<ONI>, <NAO>, and <QBO>) each 

suggest that the 2012 season, likely, will be one described as being of below long-term average activity. This presents a dilemma. Certainly, the early predictions of the 2012 hurricane season being one 

that is of near average to below average activity seems very plausible, especially, if EN returns later 

this year. However, if EN fails to return later this year, the predictions probably will underestimate 

the actual level of activity.

Since 1995, there have been 5 yr classified as ENY, including 1997, 2002, 2004, 2006, and 

2009. During these years NTC has measured, respectively, 8, 12, 15, 10, and 9; NTS has measured, 

respectively, 5, 8, 6, 5, and 6; NH has measured, respectively, 3, 4, 9, 5, and 3; NMH has measured 

respectively, 1, 2, 6, 2, and 2; and NUSLFH has measured, respectively, 1, 1, 6, 0, and 0. Hence, if 

2012 turns out to be classified as ENY, as is anticipated, then, based on these ENY, one expects NTC 

= 8–13, NTS = 5–7, NH = 3–7, NMH = 1–5, and NUSLFH = 0–4 for the 2012 hurricane season. 

On the other hand, if 2012 turns out to be a non-ENY, then one expects NTC = 12–21, NTS = 5–11, 

NH = 7–12, NMH = 3–6, and NUSLFH = 0–4.

Based on decadal trends, surface air temperature, as measured by <AT>, has increased 

steadily from about 9.15 °C in the 1970s to 10.08 °C in the 2000s, an increase of nearly 1 °C 

over the past three decades (i.e., about 0.31 °C per decade). Ocean temperature, as measured by

<JMSSTM>, likewise, has increased from about 25.37 °C in the 1970s to 25.78 °C in the 2000s, 

an increase of 0.41 °C (i.e., about 0.14 °C per decade). Increases have also been seen in <NTA>, 

<CAR>, <AMO>, <AMM>, and <ONI> over the same time interval. For example, <NTA> 

increased from –0.161 °C in the 1970s to 0.315 °C in the 2000s, an increase of 0.476 °C (i.e., 0.159 °C 

per decade); <CAR> increased from –0.145 °C in the 1970s to 0.163 °C in the 2000s, an increase of 

0.308 °C (i.e., about 0.103 °C per decade); <AMO> increased from –0.25 °C in the 1970s to 0.174 °C 

in the 2000s, an increase of 0.424 °C (i.e., about 0.141 °C per decade); <AMM> has increased from 

–1.26 in the 1970s to 1 in the 2000s, an increase in index value of 2.26 units (i.e., about 0.75 units per 

decade); and <ONI> has increased from –0.29 °C in the 1970s to 0.1 °C in the 2000s, an increase of 

0.39 °C (i.e., about 0.13 °C per decade). If these increases continue through the 2010s, then, undoubtedly, one would anticipate continued above average activity during this decade’s hurricane seasons. 

On the other hand, if cyclic effects begin to dominate and manifest themselves during the present 

decade (in particular, those associated with <AMO> and <AMM>), then one should expect a lessening in hurricane activity towards long-term averages. (Note added in proof: The official NOAA 

forecast132 was released on May 24, 2012. Because of current and projected conditions in the atmosphere and ocean in the North Atlantic basin this season, NOAA has announced that this favors a 

near normal hurricane season for this year. NOAA’s Climate Prediction Center states that there is a 

70% chance of seeing 9–15 tropical cyclones, of which 4–8 will strengthen into hurricanes and 1–3 
169

will become major hurricanes. Based on the interval 1981–2010, the average hurricane season in the 

North Atlantic basin produces 12 tropical cyclones, with 6 becoming hurricanes including 3 becoming major hurricanes. Also, it should be noted that the first and second tropical cyclones of the 2012 

North Atlantic basin hurricane season formed in late May off the eastern coast of the US (group 3). 

Alberto formed on May 19 off the coast of South Carolina, attained tropical storm strength only, 

and was no longer a tropical storm as of May 22. Subtropical storm Beryl formed on May 25 off the 

coasts of South Carolina, Georgia, and northern Florida, moving slowly westward. It remains active 

at the time of this writing.)
170

APPENDIX

Tables 1–33 provide the basic data upon which the figures are derived.
171

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov>.
172

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
173

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
174

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
175

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
176

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
177

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
178

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
179

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
180

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
181

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
182

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
183

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
184

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
185

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
186

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
187

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
188

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
189

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
190

Table 1. Listing of North Atlantic basin tropical cyclones for the interval 1945–2010, based on 

National Hurricane Center ‘best tracks’ archival database, available online at <http://

www.nhc.noaa.gov> (Continued).
191

Table 2. Yearly tropical cyclone parametric values. 
192

Table 3. 10-yma values of tropical cyclone parameters

Year NTC NTS NH NMH NUSLFH <N. LAT> <W. LONG> PWS <PWS> LP <LP> ACE NSD ACE/NSD HISACE LISNSD <NSD> NHD NMHD NTCA

1950 10.4 3.7 6.7 3.7 2.3 19.5 68.3 131.5 80.3 949.1 973.8 115.4 55.23 2.00 35.6 10.61 5.24 28.23 8.11 128.3

1951 10.5 3.5 7.0 3.9 2.3 19.5 67.3 133.3 81.8 946.2 972.7 123.7 57.94 2.05 37.7 11.05 5.44 30.23 8.83 135.4

1952 10.6 3.7 6.9 3.9 2.2 19.7 67.3 133.3 82.3 945.0 973.2 123.9 57.88 2.08 38.7 11.49 5.43 30.23 8.89 135.9

1953 10.6 3.7 6.9 4.0 2.0 19.8 67.1 134.3 82.7 943.5 973.3 123.2 57.34 2.09 38.4 11.48 5.37 29.95 8.98 136.0

1954 10.5 3.5 6.9 4.0 1.9 20.0 67.2 135.0 79.5 941.8 973.2 122.9 56.41 2.12 38.8 11.38 5.30 30.05 9.05 136.1

1955 10.1 3.5 6.6 3.6 1.9 20.4 68.1 133.5 82.0 940.5 973.7 114.1 51.88 2.16 39.4 11.41 5.08 28.01 8.56 127.3

1956 9.9 3.7 6.2 3.4 1.9 20.5 68.5 133.0 81.5 937.1 973.8 109.8 49.10 2.21 40.3 11.64 4.94 26.51 8.94 123.8

1957 9.8 3.7 6.1 3.4 1.9 20.8 68.1 132.0 81.1 936.6 973.3 110.7 48.88 2.21 40.4 11.83 4.92 26.48 9.43 124.8

1958 9.5 3.5 6.0 3.2 1.7 21.1 67.4 130.3 80.6 939.1 973.2 108.8 47.38 2.21 40.9 11.80 4.91 26.84 9.11 121.5

1959 9.3 3.4 5.9 3.3 1.7 21.2 66.8 130.8 81.4 940.0 972.9 112.4 47.98 2.24 41.8 11.99 5.06 28.38 9.39 123.9

1960 9.0 3.4 5.6 3.3 1.6 21.4 66.6 130.8 80.9 941.6 973.8 109.5 47.04 2.24 41.8 12.26 5.12 27.98 9.18 120.4

1961 8.9 3.4 5.5 3.1 1.6 21.5 65.7 130.5 80.2 941.7 974.7 108.3 46.58 2.26 43.4 12.75 5.21 28.46 8.99 118.0

1962 9.0 3.2 5.8 3.1 1.6 21.3 63.6 131.3 80.5 939.3 974.4 114.3 49.28 2.27 44.1 12.88 5.44 30.69 9.23 122.3

1963 8.9 3.0 5.9 2.8 1.6 21.6 63.3 128.3 79.6 939.8 974.7 112.0 49.19 2.22 42.3 12.56 5.50 30.53 8.70 118.2

1964 9.2 3.2 6.0 2.7 1.6 22.0 63.4 127.3 78.7 939.1 975.0 112.6 50.66 2.17 41.0 12.80 5.50 30.50 8.34 117.6

1965 9.7 3.4 6.3 2.8 1.5 22.2 63.0 128.0 78.7 937.5 975.5 114.6 53.26 2.08 38.1 12.81 5.52 30.83 8.01 120.4

1966 9.9 3.7 6.2 2.5 1.5 22.6 63.5 126.0 76.9 939.3 977.6 106.8 52.85 1.93 34.8 12.81 5.37 29.31 6.40 112.4

1967 10.1 4.0 6.1 2.2 1.7 23.3 64.4 125.0 75.0 939.2 979.8 101.9 52.83 1.86 35.0 13.24 5.29 28.14 5.20 105.5

1968 10.2 4.2 6.0 2.1 1.7 24.0 65.1 123.3 73.8 938.9 980.9 99.0 52.59 1.81 33.8 13.10 5.24 26.56 4.84 102.0

1969 10.1 4.4 5.7 1.8 1.5 24.3 65.6 121.8 72.5 939.2 982.3 90.6 50.48 1.72 31.4 12.66 5.08 23.79 3.98 93.9

1970 10.2 4.5 5.7 1.7 1.3 24.6 65.9 120.8 72.1 938.4 983.4 85.0 49.38 1.65 29.4 12.24 4.91 22.00 3.19 89.1

1971 10.3 4.5 5.8 1.8 1.3 25.1 66.2 118.8 72.3 939.7 983.2 81.4 49.01 1.60 26.8 11.84 4.81 20.81 2.55 86.7

1972 10.1 4.4 5.7 1.7 1.2 25.7 67.6 118.0 72.1 941.3 983.4 74.0 46.14 1.56 23.9 11.13 4.51 18.50 1.95 81.3

1973 10.2 4.6 5.6 1.8 1.2 25.9 68.3 120.8 72.2 940.5 983.9 70.3 44.46 1.55 22.5 10.68 4.25 17.11 1.90 80.4

1974 10.0 4.7 5.3 1.8 1.2 25.6 67.7 122.3 72.1 940.6 983.8 67.4 42.68 1.56 23.6 10.58 4.22 16.29 2.04 78.4

1975 9.6 4.4 5.2 1.6 1.2 25.4 66.6 124.3 72.5 939.2 983.2 69.2 42.00 1.62 26.4 10.71 4.35 16.95 2.31 77.8

1976 9.6 4.1 5.5 1.7 1.1 25.2 65.2 125.8 73.2 937.1 982.1 74.8 43.81 1.67 27.4 10.53 4.52 18.21 2.76 81.9

1977 9.5 4.0 5.5 1.9 0.9 24.7 65.0 125.8 73.8 937.5 982.1 74.2 43.41 1.68 26.0 9.86 4.49 17.89 2.96 82.7

1978 9.2 3.8 5.4 1.9 0.9 24.6 65.8 127.0 74.3 937.9 981.7 71.8 41.55 1.69 25.3 9.51 4.35 17.53 3.03 81.7

1979 9.1 3.7 5.4 1.9 0.9 24.9 66.0 126.3 74.2 939.0 981.8 71.0 41.35 1.68 24.6 9.41 4.34 17.39 2.85 80.4

1980 9.3 3.8 5.5 1.8 1.2 24.8 66.2 125.8 73.6 939.1 982.0 72.4 42.64 1.67 24.4 9.54 4.36 17.63 2.76 81.0

1981 9.2 3.8 5.4 1.7 1.5 24.7 66.9 125.3 73.2 939.2 982.8 70.7 41.55 1.67 23.9 9.30 4.28 16.94 2.80 79.2

1982 9.1 3.9 5.2 1.6 1.5 24.2 66.1 122.5 72.1 941.9 983.9 68.7 41.35 1.62 23.4 9.46 4.37 16.06 2.73 76.8

1983 9.1 4.0 5.1 1.7 1.6 23.6 65.1 122.5 71.4 940.6 983.8 71.3 42.64 1.62 24.0 10.03 4.53 16.31 2.98 78.4

1984 9.2 4.0 5.2 1.7 1.6 23.4 64.7 124.0 71.9 937.6 983.1 75.5 43.80 1.66 24.6 10.15 4.58 17.20 3.45 81.3

1985 9.5 4.3 5.2 1.7 1.6 23.1 64.3 120.5 71.1 940.4 983.7 75.1 45.31 1.61 23.2 10.01 4.61 17.13 3.34 81.1

1986 9.4 4.4 5.0 1.6 1.6 23.1 64.3 117.5 69.1 943.2 984.2 69.3 43.74 1.56 21.4 9.68 4.46 15.84 2.90 76.8

1987 9.3 4.4 4.9 1.5 1.7 23.4 63.9 119.3 70.1 941.8 983.7 68.2 42.74 1.56 21.4 9.74 4.47 15.63 2.89 75.5

1988 9.5 4.4 5.1 1.5 1.7 23.2 62.6 121.0 70.0 940.3 983.5 71.4 44.60 1.57 22.6 10.34 4.61 16.44 3.03 78.0

1989 9.4 4.4 5.0 1.5 1.7 22.4 61.9 120.0 69.5 941.3 983.8 69.8 43.55 1.56 22.9 10.54 4.59 16.20 3.01 76.8

1990 9.5 4.4 5.1 1.5 1.4 21.8 61.4 119.3 69.6 942.4 983.6 74.4 45.23 1.56 24.1 10.66 4.63 17.65 3.35 80.4

1991 10.3 4.7 5.6 1.9 1.2 21.0 60.6 121.3 70.1 940.0 982.5 87.5 51.51 1.60 27.2 11.10 4.83 21.38 4.38 93.9

1992 10.7 4.9 5.8 2.2 1.2 21.0 60.9 123.0 70.6 937.1 981.4 94.3 53.93 1.65 29.4 11.30 4.86 23.38 5.11 102.1

1993 10.8 4.7 6.1 2.2 1.3 21.3 61.1 122.8 70.9 937.4 981.2 98.5 55.60 1.66 30.5 11.34 4.90 25.01 5.21 105.1

1994 11.0 4.6 6.4 2.4 1.4 21.2 61.2 122.3 72.1 938.1 980.4 104.6 58.29 1.66 30.8 11.35 5.04 26.80 5.44 110.2

1995 11.1 4.7 6.4 2.6 1.4 21.2 62.0 122.8 72.9 937.3 979.5 107.8 58.86 1.69 31.4 11.69 5.05 27.53 5.85 114.4

1996 11.5 4.8 6.7 2.8 1.4 21.1 62.5 124.0 73.5 935.9 979.1 112.5 61.00 1.71 32.4 12.29 5.11 28.69 6.20 119.9

1997 12.1 5.2 6.9 3.0 1.3 20.8 63.1 123.3 73.0 935.9 979.6 120.7 64.04 1.77 32.3 12.76 5.13 29.25 6.33 124.6

1998 12.7 5.6 7.1 3.1 1.4 20.8 63.7 124.3 72.7 934.3 979.7 132.1 68.04 1.85 34.0 13.15 5.19 30.09 7.10 131.7

1999 13.5 6.0 7.5 3.5 1.7 21.0 63.6 129.0 74.0 929.0 978.4 148.7 74.48 1.95 39.1 13.56 5.40 33.14 9.01 147.9

2000 14.4 6.4 8.0 3.9 2.2 21.2 63.6 133.0 74.9 924.2 977.4 159.7 78.25 2.01 41.4 13.66 5.41 34.46 10.43 160.5

2001 14.7 6.7 8.0 3.8 2.3 21.7 63.5 133.5 74.4 923.4 978.0 156.5 77.99 1.97 39.4 13.44 5.34 32.69 10.18 158.2

2002 14.9 6.9 8.0 3.7 2.2 21.7 63.0 134.5 74.3 922.6 978.4 153.8 77.65 1.96 38.6 13.19 5.30 31.64 9.81 155.3

2003 15.3 7.3 8.0 3.8 2.2 21.5 63.1 135.0 74.4 922.1 978.4 153.5 78.18 1.96 39.0 13.20 5.21 30.84 9.91 157.3

2004 15.3 7.6 7.7 3.8 2.1 21.6 62.8 132.5 72.8 924.7 979.7 145.2 75.85 1.91 38.2 13.24 5.01 28.49 9.30 151.4

2005 15.3 7.7 7.6 3.7 1.9 21.5 62.0 132.3 72.0 925.0 980.6 141.3 79.43 1.85 37.6 12.73 5.12 27.36 9.08 150.7

Table 3. 10-yma values of tropical cyclone parameters.
193

Table 4. Differences of tropical cyclone parametric values (d=x – 10-yma). Table 4. Differences of tropical cyclone parametric values ( d = x - 10-yma)

Year NTC NTS NH NMH NUSLFH <N. LAT> <W. LONG> PWS <PWS> LP <LP> ACE NSD ACE/NSD HISACE LISNSD <NSD> NHD NMHD NTCA

1950 2.6 -1.7 4.3 4.3 0.7 0.2 -6.2 28.5 20.1 5.9 -9.8 127.4 42.77 0.48 27.0 3.89 2.30 31.27 10.39 118.7

1951 -0.5 -1.5 1.0 1.1 -2.3 0.2 -4.0 6.7 7.2 17.8 -8.7 12.8 -0.19 0.31 -0.6 -1.30 0.34 6.02 -0.58 12.6

1952 -3.6 -2.7 -0.9 -0.9 -1.2 -3.3 -3.4 -3.3 9.8 -11.0 3.5 -36.8 -18.13 0.11 -11.9 -3.24 0.25 -7.48 -1.89 -32.8

1953 3.4 4.3 -0.9 0.0 1.0 -1.0 -0.9 -4.3 -9.5 -14.5 6.0 -19.8 7.16 -0.49 -12.0 0.77 -0.76 -11.95 -2.23 -16.4

1954 0.5 -0.5 1.1 -2.0 1.1 1.8 2.5 -15.0 -4.0 -4.8 -1.2 -9.7 -9.66 0.30 2.5 -0.88 -1.05 1.45 0.45 -3.7

1955 1.9 -0.5 2.4 2.4 1.1 -1.8 -8.1 16.5 10.1 -26.5 -22.3 85.2 30.87 -0.01 3.7 -0.41 1.82 18.74 8.44 79.0

1956 -1.9 0.3 -2.2 -1.4 -0.9 1.5 10.9 -13.0 -7.7 16.9 13.1 -55.6 -19.10 -0.40 -13.9 -2.39 -1.19 -13.76 -6.19 -56.1

1957 -1.8 1.3 -3.1 -1.4 -0.9 2.8 7.6 3.0 -8.6 8.4 5.7 -26.9 -10.88 0.00 22.2 7.67 -0.17 -5.48 -2.93 -39.1

1958 0.5 -0.5 1.0 1.8 -0.7 -3.2 -7.0 9.7 8.9 -5.1 3.8 12.1 8.12 -0.03 -8.9 -2.80 0.64 3.41 0.39 23.0

1959 1.7 0.6 1.1 -1.3 1.3 3.3 9.1 -10.8 -10.5 10.0 10.2 -35.0 -7.98 -0.30 -7.0 -1.49 -1.42 -6.38 -5.14 -27.8

1960 -2.0 -0.4 -1.6 -1.3 0.4 0.0 4.6 9.2 1.2 -9.6 -2.1 -21.5 -17.54 0.74 22.8 1.49 -0.91 -9.73 0.57 -27.5

1961 2.1 -0.4 2.5 3.9 -0.6 -2.0 -4.2 19.5 17.5 -21.7 -17.7 97.2 24.17 0.64 8.8 2.25 1.22 19.04 15.51 112.4

1962 -4.0 -1.2 -2.8 -2.1 -1.6 1.4 -6.2 -31.3 -5.5 28.7 0.4 -78.8 -27.03 -0.67 -30.4 -6.13 -0.99 -19.94 -8.73 -81.4

1963 0.1 -1.0 1.1 -0.8 -0.6 -1.9 -3.2 -3.3 1.5 4.2 3.4 5.8 2.81 0.05 7.1 0.69 0.28 6.72 -1.70 -2.0

1964 2.8 2.8 0.0 3.3 2.4 -0.1 -0.7 7.7 3.4 1.9 -6.8 57.4 20.59 0.22 -3.3 0.45 0.44 12.50 6.41 66.3

1965 -3.7 -1.4 -2.3 -1.8 -0.5 0.6 0.5 7.0 -2.0 3.5 -2.2 -30.2 -13.76 0.06 8.9 0.94 1.06 -3.58 -0.51 -34.5

1966 1.1 0.3 0.8 0.5 0.5 -1.7 -6.1 4.0 -2.8 -10.3 6.0 38.0 11.15 0.33 19.5 3.44 0.45 12.69 2.10 -73.2

1967 -2.1 -2.0 -0.1 -1.2 -0.7 -3.2 -8.1 15.0 4.4 -16.2 -4.0 11.9 5.17 0.10 12.9 1.76 1.96 8.11 0.30 -4.7

1968 -2.2 -1.2 -1.0 -2.1 -0.7 3.1 7.8 -48.3 -10.0 26.1 5.2 -53.8 -18.84 -0.47 -13.5 -5.85 -1.02 -14.81 -4.84 -54.8

1969 7.9 1.6 6.3 3.2 0.5 -0.4 -0.2 43.2 7.5 -34.2 -2.7 74.7 40.77 0.09 0.2 4.34 -0.01 16.21 2.52 87.3

1970 -0.2 0.5 -0.7 0.3 -0.3 -0.2 8.1 -10.8 0.4 6.6 2.6 -44.8 -19.13 -0.32 -21.1 -4.74 -1.88 -15.25 -2.19 -24.9

1971 2.7 2.5 0.2 -0.8 1.7 0.0 3.1 21.2 -1.9 3.3 1.4 15.2 12.74 -0.04 17.4 9.41 -0.06 7.94 -1.55 11.2

1972 -3.1 -0.4 -2.7 -1.7 -0.2 6.5 -0.1 -28.0 -7.8 2.7 7.5 -28.1 -15.39 -0.07 0.2 -2.13 -0.12 -12.50 -1.95 -46.2

1973 -2.2 -0.6 -1.6 -0.8 -1.2 -3.1 -4.5 -20.8 -3.4 21.5 0.4 -19.9 -5.71 -0.25 -7.6 -2.43 0.59 -6.61 -1.65 -26.8

1974 1.0 2.3 -1.3 0.2 -0.2 -0.9 1.8 7.7 -4.4 -12.6 6.4 0.9 -0.43 0.06 2.0 -1.08 -0.38 -2.04 2.21 4.7

1975 -0.6 -1.4 0.8 1.4 -0.2 2.3 -4.8 -4.3 11.4 -0.2 -11.3 4.7 4.50 -0.03 -7.2 -1.71 0.82 3.30 -0.06 13.6

1976 0.4 -0.1 0.5 0.3 -0.1 -0.2 0.0 -20.8 -3.2 19.9 -0.3 9.4 5.94 0.02 2.6 2.47 0.46 7.04 -1.76 4.3

1977 -3.5 -3.0 -0.5 -0.9 0.1 3.4 12.4 24.2 5.4 -11.5 0.1 -48.8 -28.66 0.04 -13.2 -5.86 -2.03 -11.14 -1.96 -38.0

1978 2.8 3.2 -0.4 0.1 -0.9 -1.1 -1.2 -7.0 -8.0 9.1 6.2 -11.0 1.95 -0.29 -6.1 -0.26 -0.72 -4.03 0.47 3.4

1979 -0.1 -0.7 0.6 0.1 2.1 -4.4 -2.8 23.7 1.9 -15.0 -4.4 20.9 4.40 0.33 19.4 3.59 0.74 4.36 2.90 23.4

1980 1.7 -1.8 3.5 0.2 -0.2 -1.0 -12.1 39.2 9.6 -40.1 -5.9 76.0 19.61 0.71 26.6 4.71 1.30 20.62 4.49 49.3

1981 2.8 1.2 1.6 1.3 -1.5 -1.5 -5.6 -10.3 1.8 6.8 -1.0 29.4 24.45 -0.15 -1.7 1.45 1.22 5.56 0.95 33.4

1982 -3.1 0.1 -3.2 -0.6 -1.5 -0.4 4.6 -7.5 -1.3 8.1 -0.7 -37.2 -22.85 0.08 -5.2 -3.21 -1.29 -10.31 -1.48 -39.1

1983 -5.1 -3.0 -2.1 -0.7 -0.6 5.0 10.8 -22.5 1.1 22.4 1.7 -53.9 -28.89 -0.35 -17.6 -6.03 -1.09 -12.81 -2.73 -47.9

1984 3.8 4.0 -0.2 -0.7 -0.6 1.9 -1.7 -9.0 -10.0 11.4 6.1 8.0 19.45 -0.34 -5.1 1.60 0.29 1.05 -2.70 -1.0

1985 1.5 -0.3 1.8 1.3 4.4 2.1 7.3 4.5 7.1 -20.4 -6.3 12.9 5.94 0.11 -2.0 -0.76 0.05 4.12 0.66 24.7

1986 -3.4 -2.4 -1.0 -1.6 0.4 1.2 5.0 -27.5 -1.6 35.8 8.6 -33.5 -20.49 -0.02 -1.7 -1.68 -0.58 -5.34 -2.90 -40.0

1987 -2.3 -0.4 -1.9 -0.5 -0.7 -4.2 -7.1 -9.3 -10.8 16.2 8.6 -33.7 -5.49 -0.63 -9.6 2.51 0.85 -11.63 -2.39 -30.6

1988 2.5 2.6 -0.1 1.5 -0.7 -1.6 2.0 39.0 2.9 -52.3 -7.3 31.4 2.15 0.63 10.2 1.91 -0.71 4.81 5.97 39.0

1989 1.6 -0.4 2.0 0.5 1.3 -4.3 -5.1 16.0 9.1 -18.3 -7.3 64.6 23.20 0.48 19.8 1.96 1.39 15.55 6.74 53.0

1990 4.5 1.6 2.9 -0.5 -1.4 -2.2 -9.3 -14.3 -4.2 13.1 3.5 22.6 27.27 -0.22 -0.8 1.34 0.55 9.10 -2.35 19.9

1991 -2.3 -0.7 -1.6 0.1 -0.2 5.6 3.4 -6.3 -2.0 6.0 -0.9 -51.8 -27.26 -0.13 -13.2 -4.85 -1.80 -13.13 -3.13 -36.2

1992 -3.7 -1.9 -1.8 -1.2 -0.2 6.5 -2.3 27.0 10.8 -15.1 -7.0 -20.0 -13.68 0.20 -2.9 0.79 0.89 -7.63 -1.61 -35.4

1993 -2.8 -0.7 -2.1 1.8 -0.3 -0.9 2.0 -22.8 -10.3 22.6 8.7 -60.3 -26.35 -0.34 -8.4 -1.09 -1.24 -15.26 -4.46 -53.6

1994 -4.0 -0.6 -3.4 -2.4 -1.4 -2.9 0.9 -27.3 -7.1 33.9 9.2 -73.2 -31.54 -0.49 -20.4 -1.85 -0.93 -19.55 -5.44 -74.9

1995 7.9 3.3 4.6 2.4 0.6 -2.4 -0.3 7.2 3.4 -18.3 -5.1 118.2 62.39 -0.14 22.1 2.31 1.33 33.72 5.65 107.0

1996 1.5 -0.8 2.3 3.2 0.6 -4.9 -0.3 1.0 6.5 -2.9 -6.3 53.7 18.00 0.39 16.9 -0.29 0.97 16.31 6.80 72.3

1997 -4.1 -0.2 -3.9 -2.0 -0.3 6.3 6.7 -13.3 -17.4 10.1 11.2 -81.0 -34.29 -0.44 -5.7 -0.51 -1.41 -19.75 -4.08 -70.9

1998 1.3 -1.6 2.9 -0.1 1.6 -1.6 -6.2 30.7 10.5 -29.3 -7.0 49.6 19.71 0.22 5.4 -0.15 1.08 18.41 2.15 36.2

1999 -1.5 -2.0 0.5 1.5 1.3 -3.5 0.5 6.0 17.3 -8.0 -13.8 27.7 4.02 0.30 3.2 -1.56 1.14 7.11 4.99 32.5

2000 0.6 0.6 0.0 -0.9 -2.2 -0.2 -1.3 -13.0 -4.9 16.8 4.3 -40.6 -7.00 -0.34 -4.5 5.59 -0.66 -1.71 -5.43 -27.0

2001 0.3 -0.7 1.0 0.2 -2.3 0.7 0.3 -8.5 1.3 10.6 1.3 -47.3 -9.74 -0.37 -19.3 -2.44 -0.79 -7.19 -5.93 -23.1

2002 -2.9 1.1 -4.0 -1.7 -1.2 4.5 6.9 -9.5 -10.5 11.4 6.6 10.2 -20.65 0.92 -19.6 3.56 -0.55 -21.89 -6.81 -72.7

2003 0.7 1.7 -1.0 -0.8 -0.2 0.5 1.6 10.0 -3.8 -7.1 3.4 22.5 14.32 -0.06 24.3 0.05 0.57 1.66 6.84 21.3

2004 -0.3 -1.6 1.3 2.2 3.9 -1.6 -5.0 12.5 9.5 -12.7 -8.5 80.9 16.40 0.54 32.2 1.51 1.14 17.01 12.95 80.0

2005 12.7 5.3 7.4 3.3 4.1 1.0 4.0 27.7 4.8 -43.0 -6.2 109.0 51.82 0.06 1.3 -1.98 -0.43 22.14 8.42 127.6

n+ 29 21 28 28 21 25 26 28 29 30 29 30 29 29 26 27 29 29 25 26

n- 27 35 28 28 35 31 30 28 27 26 27 26 27 27 30 29 27 27 31 30

n+r 19 16 15 18 14 15 17 16 18 14 13 15 16 17 15 15 15 15 14 14

mean 0.1 0.0 0.1 0.1 0.0 0.0 -0.1 0.8 0.6 -0.9 -0.4 4.2 1.3 0.02 0.8 -0.06 0.03 0.81 0.39 2.0

sd 3.3 1.9 2.4 1.7 1.4 2.8 5.6 19.5 8.2 19.3 7.4 51.8 22.0 0.36 14.3 3.25 1.05 13.42 5.05 53.1
194

Table 5. First-differences of tropical cyclone parametric values based on 10-yma values. Table 5. First-differences of tropical cyclone parametric values based on 10-yma values

Year NTC NTS NH NMH NUSLFH <N. LAT> <W. LONG> PWS <PWS> LP <LP> ACE NSD ACE/NSD HISACE LISNSD <NSD> NHD NMHD NTCA

1950 0.1 -0.2 0.3 0.2 0.0 0.0 -1.0 1.8 1.5 -2.9 -1.1 8.3 2.71 0.05 2.1 0.44 0.20 2.00 0.72 7.1

1951 0.1 0.2 -0.1 0.0 -0.1 0.2 0.0 0.0 0.5 -1.2 0.5 0.2 -0.06 0.03 1.0 0.44 -0.01 0.00 0.06 0.5

1952 0.0 0.0 0.0 0.1 -0.2 0.1 -0.2 1.0 0.4 -1.5 0.1 -0.7 -0.54 0.01 -0.3 -0.01 -0.06 -0.28 0.09 0.1

1953 -0.1 -0.2 0.0 0.0 -0.1 0.2 0.1 0.7 -3.2 -1.7 -0.1 -0.3 -0.93 0.03 0.4 -0.10 -0.07 0.10 0.07 0.1

1954 -0.4 0.0 -0.3 -0.4 0.0 0.4 0.9 -1.5 2.5 -1.3 0.5 -8.8 -4.53 0.04 0.6 0.03 -0.22 -2.04 -0.49 -8.8

1955 -0.2 0.2 -0.4 -0.2 0.0 0.1 0.4 -0.5 -0.5 -3.4 0.1 -4.3 -2.78 0.05 0.9 0.23 -0.14 -1.50 0.38 -3.5

1956 -0.1 0.0 -0.1 0.0 0.0 0.3 -0.4 -1.0 -0.4 -0.5 -0.5 0.9 -0.22 0.00 0.1 0.19 -0.02 -0.03 0.49 1.0

1957 -0.3 -0.2 -0.1 -0.2 -0.2 0.3 -0.7 -1.7 -0.5 2.5 -0.1 -1.9 -1.50 0.00 0.5 -0.03 -0.01 0.36 -0.32 -3.3

1958 -0.2 -0.1 -0.1 0.1 0.0 0.1 -0.6 0.5 0.8 0.9 -0.3 3.6 0.60 0.03 0.9 0.19 0.15 1.54 0.28 2.4

1959 -0.3 0.0 -0.3 0.0 -0.1 0.2 -0.2 0.0 -0.5 1.6 0.9 -2.9 -0.94 0.00 0.0 0.27 0.06 -0.40 -0.21 -3.5

1960 -0.1 0.0 -0.1 -0.2 0.0 0.1 -0.9 -0.3 -0.7 0.1 0.9 -1.2 -0.46 0.02 1.6 0.49 0.09 0.48 -0.19 -2.4

1961 0.1 -0.2 0.3 0.0 0.0 -0.2 -2.1 0.8 0.3 -2.4 -0.3 6.0 2.70 0.01 0.7 0.13 0.23 2.23 0.24 4.3

1962 -0.1 -0.2 0.1 -0.3 0.0 0.3 -0.3 -3.0 -0.9 0.5 0.3 -2.3 -0.09 -0.05 -1.8 -0.32 0.06 -0.16 -0.53 -4.1

1963 0.3 0.2 0.1 -0.1 0.0 0.4 0.1 -1.0 -0.9 -0.7 0.3 0.6 1.47 -0.05 -1.3 0.24 0.00 -0.03 -0.36 -0.6

1964 0.5 0.2 0.3 0.1 -0.1 0.2 -0.4 0.7 0.0 -1.6 0.5 2.0 2.60 -0.09 -2.9 0.01 0.02 0.33 -0.33 2.8

1965 0.2 0.3 -0.1 -0.3 0.0 0.4 0.5 -2.0 -1.8 1.8 2.1 -7.8 -0.41 -0.15 -3.3 0.00 -0.15 -1.52 -1.61 -8.0

1966 0.2 0.3 -0.1 -0.3 0.2 0.7 0.9 -1.0 -1.9 -0.1 2.2 -4.9 -0.02 -0.07 0.2 0.43 -0.08 -1.17 -1.20 -6.9

1967 0.1 0.2 -0.1 -0.1 0.0 0.7 0.7 -1.7 -1.2 -0.3 1.1 -2.9 -0.24 -0.05 -1.2 -0.14 -0.05 -1.58 -0.36 -3.5

1968 -0.1 0.2 -0.3 -0.3 -0.2 0.3 0.5 -1.5 -1.3 0.3 1.4 -8.4 -2.11 -0.09 -2.4 -0.44 -0.16 -2.77 -0.86 -8.1

1969 0.1 0.1 0.0 -0.1 -0.2 0.3 0.3 -1.0 -0.4 -0.8 1.1 -5.6 -1.10 -0.07 -2.0 -0.42 -0.17 -1.79 -0.79 -4.8

1970 0.1 0.0 0.1 0.1 0.0 0.5 0.3 -2.0 0.2 1.3 -0.2 -3.6 -0.37 -0.05 -2.6 -0.40 -0.10 -1.19 -0.64 -2.4

1971 -0.2 -0.1 -0.1 -0.1 -0.1 0.6 1.4 -0.8 -0.2 1.6 0.2 -7.4 -2.87 -0.04 -2.9 -0.71 -0.30 -2.31 -0.60 -5.4

1972 0.1 0.2 -0.1 0.1 0.0 0.2 0.7 2.8 0.1 -0.8 0.5 -3.7 -1.68 -0.01 -1.4 -0.45 -0.26 -1.39 -0.05 -0.9

1973 -0.2 0.1 -0.3 0.0 0.0 -0.3 -0.6 1.5 -0.1 0.1 -0.1 -2.9 -1.78 0.01 1.1 -0.10 -0.03 -0.82 0.14 -2.0

1974 -0.4 -0.3 -0.1 -0.2 0.0 -0.2 -1.1 2.0 0.4 -1.4 -0.6 1.8 -0.68 0.06 2.8 0.13 0.13 0.66 0.27 -0.6

1975 0.0 -0.3 0.3 0.1 -0.1 -0.2 -1.4 1.5 0.7 -2.1 -1.1 5.6 1.81 0.05 1.0 -0.18 0.17 1.26 0.45 4.1

1976 -0.1 -0.1 0.0 0.2 -0.2 -0.5 -0.2 0.0 0.6 0.4 0.0 -0.6 -0.40 0.01 -1.4 -0.67 -0.03 -0.32 0.20 0.8

1977 -0.3 -0.2 -0.1 0.0 0.0 -0.1 0.8 1.2 0.5 0.4 -0.4 -2.4 -1.86 0.01 -0.7 -0.35 -0.14 -0.36 0.07 -1.0

1978 -0.1 -0.1 0.0 0.0 0.0 0.3 0.2 -0.7 -0.1 1.1 0.1 -0.8 -0.20 -0.01 -0.7 -0.10 -0.01 -0.14 -0.18 -1.3

1979 0.2 0.1 0.1 -0.1 0.3 -0.1 0.2 -0.5 -0.6 0.1 0.2 1.4 1.29 -0.01 -0.2 0.13 0.02 0.24 -0.09 0.6

1980 -0.1 0.0 -0.1 -0.1 0.3 -0.1 0.7 -0.5 -0.4 0.1 0.8 -1.7 -1.09 0.00 -0.5 -0.24 -0.08 -0.69 0.04 -1.8

1981 -0.1 0.1 -0.2 -0.1 0.0 -0.5 -0.8 -2.8 -1.1 2.7 1.1 -2.0 -0.20 -0.05 -0.5 0.16 0.09 -0.88 -0.07 -2.4

1982 0.0 0.1 -0.1 0.1 0.1 -0.6 -1.0 0.0 -0.7 -1.3 -0.1 2.6 1.29 0.00 0.6 0.57 0.16 0.25 0.25 1.6

1983 0.1 0.0 0.1 0.0 0.0 -0.2 -0.4 1.5 0.5 -3.0 -0.7 4.2 1.16 0.04 0.6 0.12 0.05 0.89 0.47 2.9

1984 0.3 0.3 0.0 0.0 0.0 -0.3 -0.4 -3.5 -0.8 2.8 0.6 -0.4 1.51 -0.05 -1.4 -0.14 0.03 -0.07 -0.11 -0.2

1985 -0.1 0.1 -0.2 -0.1 0.0 0.0 0.0 -3.0 -2.0 2.8 0.5 -5.8 -1.57 -0.05 -1.8 -0.33 -0.15 -1.29 -0.44 -4.3

1986 -0.1 0.0 -0.1 -0.1 0.1 0.3 -0.4 1.8 1.0 -1.4 -0.5 -1.1 -1.00 0.00 0.0 0.06 0.01 -0.21 -0.01 -1.3

1987 0.2 0.0 0.2 0.0 0.0 -0.2 -1.3 1.7 -0.1 -1.5 -0.2 3.2 1.86 0.01 1.2 0.60 0.14 0.81 0.14 2.5

1988 -0.1 0.0 -0.1 0.0 0.0 -0.8 -0.7 -1.0 -0.5 1.0 0.3 -1.6 -1.05 -0.01 0.3 0.20 -0.02 -0.24 -0.02 -1.2

1989 0.1 0.0 0.1 0.0 -0.3 -0.6 -0.5 -0.7 0.1 1.1 -0.2 4.3 1.68 0.00 1.2 0.12 0.04 1.45 0.34 3.6

1990 0.8 0.3 0.5 0.4 -0.2 -0.8 -0.8 2.0 0.5 -2.4 -1.1 13.4 6.28 0.04 3.1 0.44 0.20 3.73 1.03 13.5

1991 0.4 0.2 0.2 0.3 0.0 0.0 0.3 1.7 0.5 -2.9 -1.1 6.8 2.42 0.05 2.2 0.20 0.03 2.00 0.73 8.2

1992 0.1 -0.2 0.3 0.0 0.1 0.3 0.2 -0.2 0.3 0.3 -0.2 4.2 1.67 0.01 1.1 0.04 0.04 1.63 0.10 3.0

1993 0.2 -0.1 0.3 0.2 0.1 -0.1 0.1 -0.5 1.2 0.7 -0.8 6.1 2.69 0.00 0.3 0.01 0.14 1.79 0.23 5.1

1994 0.1 0.1 0.0 0.2 0.0 0.0 0.8 0.5 0.8 -0.8 -0.9 3.2 0.57 0.03 0.6 0.34 0.01 0.73 0.41 4.2

1995 0.4 0.1 0.3 0.2 0.0 -0.1 0.5 1.2 0.6 -1.4 -0.4 4.7 2.14 0.02 1.0 0.60 0.06 1.16 0.35 5.5

1996 0.6 0.4 0.2 0.2 -0.1 -0.3 0.6 -0.7 -0.5 0.0 0.5 8.2 3.04 0.06 -0.1 0.47 0.02 0.56 0.13 4.7

1997 0.6 0.4 0.2 0.1 0.1 0.0 0.6 1.0 -0.3 -1.6 0.1 11.4 4.00 0.08 1.7 0.39 0.06 0.84 0.77 7.1

1998 0.8 0.4 0.4 0.4 0.3 0.2 -0.1 4.7 1.3 -5.3 -1.3 16.6 6.44 0.10 5.1 0.41 0.21 3.05 1.91 16.2

1999 0.9 0.4 0.5 0.4 0.5 0.2 0.0 4.0 0.9 -4.8 -1.0 11.0 3.77 0.06 2.3 0.10 0.01 1.32 1.42 12.6

2000 0.3 0.3 0.0 -0.1 0.1 0.5 -0.1 0.5 -0.5 -0.8 0.6 -3.2 -0.26 -0.04 -2.0 -0.22 -0.07 -1.77 -0.25 -2.3

2001 0.2 0.2 0.0 -0.1 -0.1 0.0 -0.5 1.0 -0.1 -0.8 0.4 -2.7 -0.34 -0.01 -0.8 -0.25 -0.04 -1.05 -0.37 -2.9

2002 0.4 0.4 0.0 0.1 0.0 -0.2 0.1 0.5 0.1 -0.5 0.0 -0.3 0.53 0.00 0.4 0.01 -0.09 -0.80 0.10 2.0

2003 0.0 0.3 -0.3 0.0 -0.1 0.1 -0.5 -2.5 -1.6 2.6 1.3 -8.3 -2.33 -0.05 -0.8 0.04 -0.20 -2.35 -0.61 -5.9

2004 0.0 0.1 -0.1 -0.1 -0.2 -0.1 -0.8 -0.2 -0.8 0.3 0.9 -3.9 3.58 -0.06 -0.6 -0.51 0.11 -1.13 -0.22 -0.7

n+ 34 41 30 34 38 34 27 28 25 25 31 24 24 34 31 34 29 25 29 26

n- 21 14 25 21 17 21 28 27 30 30 24 31 31 21 24 21 26 30 26 29

n+r 10 7 9 11 11 8 9 10 13 12 11 10 11 7 8 9 8 10 10 11

mean 0.1 0.1 0.0 0.0 0.0 0.0 -0.1 0.2 -0.2 -0.4 0.1 0.5 0.44 0.00 0.0 0.04 0.00 -0.02 0.02 0.4

sd 0.3 0.2 0.2 0.2 0.1 0.3 0.7 2.2 1.0 1.8 0.8 5.5 2.16 0.05 1.6 0.32 0.12 1.38 0.58 5.1
195

Table 6. Poisson probability distributions for Atlantic basin tropical cyclones: (a) 1945–2010 

and (b) 1995–2010.

A. 1945-2010

 P(r)

 NTC NTS NH NMH NUSLFH

 r (m = 10.8) (m = 4.6) (m = 6.2) (m = 2.7) (m = 1.6)

 0 0.00002 0.01005 0.00203 0.06721 0.20190

 1 0.00022 0.04624 0.01258 0.18145 0.32303

 2 0.00119 0.10635 0.03901 0.24496 0.25843

 3 0.00428 0.16307 0.08061 0.22047 0.13783

 4 0.01156 0.18753 0.12495 0.14882 0.05513

 5 0.02498 0.17253 0.15494 0.08036 0.01764

 6 0.04496 0.13227 0.16012 0.03616 0.00470

 7 0.06937 0.08692 0.14180 0.01395 0.00108

 8 0.09365 0.04998 0.10990 0.00471 0.00022

 9 0.11238 0.02554 0.07571 0.00141 0.00004

10 0.12137 0.01175 0.04694 0.00038 0.00001

11 0.11916 0.00491 0.02646 0.00009 0.00000

12 0.10724 0.00188 0.01367 0.00002

13 0.08909 0.00067 0.00652 0.00000

14 0.06873 0.00022 0.00289

15 0.04949 0.00007 0.00119

16 0.03340 0.00002 0.00046

17 0.02122 0.00001 0.00017

18 0.01273 0.00000 0.00006

19 0.00724 0.00002

20 0.00391 0.00001

21 0.00201 0.00000

22 0.00099

23 0.00046

24 0.00021

25 0.00009

26 0.00004

27 0.00001

28 0.00001

29 0.00000

B. 1995-2010

Poisson probability distributions for Atlantic basin tropical 

cyclones, 1995-2010

 P(r)

 NTC NTS NH NMH NUSLFH

 r (m = 14.8) (m = 6.8) (m = 7.9) (m = 3.8) (m = 1.9)

 0 0.00000 0.00111 0.00037 0.02237 0.14957

 1 0.00001 0.00757 0.00293 0.08501 0.28418

 2 0.00004 0.02575 0.01157 0.16152 0.26997

 3 0.00020 0.05837 0.03047 0.20459 0.17098

 4 0.00075 0.09923 0.06017 0.19436 0.08122

 5 0.00221 0.13495 0.09507 0.14771 0.03086

 6 0.00545 0.15294 0.12517 0.09355 0.00977

 7 0.01153 0.14857 0.14126 0.05079 0.00265

 8 0.02133 0.12628 0.13950 0.02412 0.00063

 9 0.03508 0.09541 0.12245 0.01019 0.00013

10 0.05192 0.06488 0.09673 0.00387 0.00000

11 0.06985 0.04011 0.06947 0.00134

12 0.08615 0.02273 0.04574 0.00042

13 0.09808 0.01189 0.02779 0.00012

14 0.10368 0.00577 0.01568 0.00003

15 0.10230 0.00262 0.00826 0.00001

16 0.09463 0.00111 0.00408 0.00000

17 0.08238 0.00045 0.00190

18 0.06773 0.00017 0.00083

19 0.05276 0.00006 0.00035

20 0.03904 0.00002 0.00014

21 0.02752 0.00001 0.00005

22 0.01851 0.00000 0.00002

23 001191 000001
196

21 0.00201 0.00000

22 0.00099

23 0.00046

24 0.00021

25 0.00009

26 0.00004

27 0.00001

28 0.00001

29 0.00000

B. 1995-2010

Poisson probability distributions for Atlantic basin tropical 

cyclones, 1995-2010

 P(r)

 NTC NTS NH NMH NUSLFH

 r (m = 14.8) (m = 6.8) (m = 7.9) (m = 3.8) (m = 1.9)

 0 0.00000 0.00111 0.00037 0.02237 0.14957

 1 0.00001 0.00757 0.00293 0.08501 0.28418

 2 0.00004 0.02575 0.01157 0.16152 0.26997

 3 0.00020 0.05837 0.03047 0.20459 0.17098

 4 0.00075 0.09923 0.06017 0.19436 0.08122

 5 0.00221 0.13495 0.09507 0.14771 0.03086

 6 0.00545 0.15294 0.12517 0.09355 0.00977

 7 0.01153 0.14857 0.14126 0.05079 0.00265

 8 0.02133 0.12628 0.13950 0.02412 0.00063

 9 0.03508 0.09541 0.12245 0.01019 0.00013

10 0.05192 0.06488 0.09673 0.00387 0.00000

11 0.06985 0.04011 0.06947 0.00134

12 0.08615 0.02273 0.04574 0.00042

13 0.09808 0.01189 0.02779 0.00012

14 0.10368 0.00577 0.01568 0.00003

15 0.10230 0.00262 0.00826 0.00001

16 0.09463 0.00111 0.00408 0.00000

17 0.08238 0.00045 0.00190

18 0.06773 0.00017 0.00083

19 0.05276 0.00006 0.00035

20 0.03904 0.00002 0.00014

21 0.02752 0.00001 0.00005

22 0.01851 0.00000 0.00002

23 0.01191 0.00001

24 0.00735 0.00000

25 0.00435

26 0.00248

27 0.00136

28 0.00072

29 0.00037

30 0.00018

31 0.00009

32 0.00004

Table 6. Poisson probability distributions for Atlantic basin tropical cyclones: (a) 1945–2010 

and (b) 1995–2010 (Continued).

33 0.00002

34 0.00001

35 0.00000
197

Table 7. Comparison of observed and expected first differences. Table 7. Comparison of observed 

and expected first differences

 NTC

Year OBS EXP RES

1950 0.1 -0.2 0.3

1951 0.1 -0.2 0.3

1952 0.0 -0.1 0.1

1953 -0.1 -0.1 0.0

1954 -0.4 -0.1 -0.3

1955 -0.2 -0.1 -0.1

1956 -0.1 -0.1 0.0

1957 -0.3 -0.1 -0.2

1958 -0.2 -0.1 -0.1

1959 -0.3 -0.1 -0.2

1960 -0.1 -0.1 0.0

1961 0.1 -0.1 0.0

1962 -0.1 -0.1 0.0

1963 0.3 0.0 0.3

1964 0.5 0.0 0.5

1965 0.2 0.0 0.2

1966 0.2 0.0 0.2

1967 0.1 0.0 0.1

1968 -0.1 0.0 -0.1

1969 0.1 0.0 0.1

1970 0.1 0.0 0.1

1971 -0.2 0.0 -0.2

1972 0.1 0.0 0.1

1973 -0.2 0.1 -0.3

1974 -0.4 0.1 -0.5

1975 0.0 0.1 -0.1

1976 -0.1 0.1 -0.2

1977 -0.3 0.1 -0.4

1978 -0.1 0.1 -0.2

1979 0.2 0.1 0.1

1980 -0.1 0.1 -0.2

1981 -0.1 0.1 -0.2

1982 0.0 0.1 -0.1

1983 0.1 0.1 0.0

1984 0.3 0.2 0.1

1985 -0.1 0.2 -0.3

1986 -0.1 0.2 -0.3

1987 0.2 0.2 0.0

1988 -0.1 0.2 -0.3

1989 0.1 0.2 -0.1

1990 0.8 0.2 0.6

1991 0.4 0.2 0.2

1992 0.1 0.2 -0.1

1993 0.2 0.2 0.0

1994 0.1 0.2 -0.1

1995 0.4 0.3 0.1

1996 0.6 0.3 0.3

1997 0.6 0.3 0.3

1998 0.8 0.3 0.5

1999 0.9 0.3 0.6

2000 0.3 0.3 0.0

2001 0.2 0.3 -0.1

2002 0.4 0.3 0.1

2003 0.0 0.3 -0.3

2004 0.0 0.3 -0.3

n+ 30

n- 25

n+r 12

z -1.17

cl <90%

random? yes
198

Table 8. Monthly counts of the number of tropical cyclone onsets

Year JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Sum

1945 1 1 4 3 2 11

1946 1 1 1 1 2 6

1947 1 2 3 3 9

1948 1 1 2 3 1 1 9

1949 3 7 2 1 13

1950 4 3 6 13

1951 1 3 3 3 10

1952 1 2 2 2 7

1953 1 3 4 4 1 1 14

1954 1 1 2 4 1 1 1 11

1955 1 4 5 2 12

1956 1 1 1 4 1 8

1957 2 1 4 1 8

1958 1 4 4 1 10

1959 1 2 2 1 3 2 11

1960 1 2 2 2 7

1961 1 6 2 2 11

1962 2 1 2 5

1963 2 5 2 9

1964 1 1 3 5 1 1 12

1965 1 2 2 1 6

1966 1 4 1 4 1 11

1967 1 4 3 8

1968 3 1 3 1 8

1969 1 5 6 5 1 18

1970 1 1 3 3 2 10

1971 1 4 6 1 1 13

1972 1 1 2 2 1 7

1973 2 2 2 2 8

1974 1 1 4 4 1 11

1975 1 1 2 3 1 1 9

1976 1 1 5 2 1 10

1977 1 3 2 6

1978 1 1 4 3 3 12

1979 1 2 3 2 1 9

1980 3 5 1 2 11

1981 1 1 2 5 1 2 12

1982 2 1 2 1 6

1983 2 2 4

1984 4 6 1 1 1 13

1985 2 3 3 2 1 11

1986 2 1 2 1 6

1987 3 3 1 7

1988 3 7 1 1 12

1989 1 2 4 2 1 1 11

1990 2 6 2 4 14

1991 1 1 3 3 8

1992 1 1 4 1 7

1993 1 4 3 8

1994 1 2 2 2 7

1995 1 4 7 3 4 19

1996 1 2 4 2 3 1 13

1997 1 4 1 2 8

1998 1 4 6 2 1 14

1999 1 4 3 3 1 12

2000 4 7 4 15

2001 1 3 4 4 3 15

2002 1 3 8 12

2003 1 1 2 3 4 3 2 16

2004 8 4 2 1 15

2005 2 5 5 5 7 3 1 28

2006 1 2 3 4 10

2007 1 1 1 2 8 1 1 15

2008 1 3 4 4 3 1 16

2009 4 2 2 1 9

2010 1 1 4 8 5 19

Sum 1 1 2 10 38 62 188 245 125 35 8 715

*********************************************************

Table 8. Monthly counts of the number of tropical cyclone onsets.
199

Table 9. Monthly counts of the number of tropical cyclones that attained only 

tropical storm strength. Table 9. Monthly counts of the number of tropical cyclones that

attained only tropical storm strength

Year JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Sum

1945 1 3 2 6

1946 1 1 1 3

1947 1 2 1 4

1948 1 1 1 3

1949 1 3 1 1 6

1950 2 2

1951 1 1 2

1952 1 1

1953 1 1 1 3 1 1 8

1954 1 1 1 3

1955 1 1 1 3

1956 1 3 4

1957 1 1 2 1 5

1958 1 1 1 3

1959 1 1 1 1 4

1960 1 1 1 3

1961 1 1 1 3

1962 1 1 2

1963 1 1 2

1964 1 1 2 1 1 6

1965 1 1 2

1966 1 3 4

1967 1 1 2

1968 1 2 3

1969 1 1 2 2 6

1970 1 2 2 5

1971 1 2 2 1 1 7

1972 1 1 1 1 4

1973 1 1 1 1 4

1974 1 1 2 2 1 7

1975 1 1 1 3

1976 1 1 1 1 4

1977 1 1

1978 1 1 2 1 2 7

1979 1 1 1 3

1980 2 2

1981 1 1 1 1 1 5

1982 1 1 1 1 4

1983 1 1

1984 4 4 8

1985 1 2 1 4

1986 1 1 2

1987 2 2 4

1988 3 3 1 7

1989 1 1 1 1 4

1990 1 4 1 6

1991 1 2 1 4

1992 1 2 3

1993 1 3 4

1994 1 1 2 4

1995 3 3 2 8

1996 1 1 2 4

1997 1 2 2 5

1998 1 1 2 4

1999 1 1 1 1 4

2000 2 2 3 7

2001 1 3 2 6

2002 1 3 4 8

2003 1 1 1 1 3 2 9

2004 3 2 1 6

2005 2 2 3 3 2 1 13

2006 1 2 2 5

2007 1 1 1 1 4 1 9

2008 1 1 2 2 2 8

2009 3 1 2 6

2010 1 2 4 7

Sum 1 1 2 8 26 35 78 84 52 13 6 306

********************************************************
200

Table 10. Monthly counts of the number of tropical cyclones that attained hurricane 

storm strength. Table 10. Monthly counts of the number of tropical cyclones that

attained hurricane storm strength

Year JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Sum

1945 1 1 1 2 5

1946 1 1 1 3

1947 2 1 2 5

1948 1 3 1 1 6

1949 2 4 1 7

1950 4 3 4 11

1951 1 2 2 3 8

1952 2 2 2 6

1953 2 3 1 6

1954 1 2 3 1 1 8

1955 3 5 1 9

1956 1 1 1 1 4

1957 1 2 3

1958 3 3 1 7

1959 1 2 3 1 7

1960 1 2 1 4

1961 1 5 1 1 8

1962 1 2 3

1963 2 4 1 7

1964 1 4 1 6

1965 2 1 1 4

1966 1 3 1 1 1 7

1967 1 3 2 6

1968 2 1 1 1 5

1969 4 4 3 1 12

1970 1 1 1 2 5

1971 2 4 6

1972 1 1 1 3

1973 1 1 1 1 4

1974 2 2 4

1975 1 2 3 6

1976 4 1 1 6

1977 1 3 1 5

1978 2 2 1 5

1979 1 2 2 1 6

1980 3 3 1 2 9

1981 1 5 1 7

1982 1 1 2

1983 2 1 3

1984 2 1 1 1 5

1985 1 3 1 1 1 7

1986 1 1 1 1 4

1987 1 1 1 3

1988 4 1 5

1989 1 4 1 1 7

1990 1 2 2 3 8

1991 1 1 2 4

1992 1 2 1 4

1993 1 3 4

1994 1 2 3

1995 1 1 4 3 2 11

1996 2 3 2 1 1 9

1997 2 1 3

1998 3 4 2 1 10

1999 3 2 2 1 8

2000 2 5 1 8

2001 4 2 3 9

2002 4 4

2003 2 2 3 7

2004 5 4 9

2005 3 2 5 4 1 15

2006 1 4 5

2007 1 4 1 6

2008 2 2 2 1 1 8

2009 1 1 1 3

2010 1 2 4 5 12

Sum 2 12 27 110 161 73 22 2 409

*********************************************************
201

Table 11. Monthly counts of the number of tropical cyclones that attained major or intense 

hurricane storm strength. Table 11. Monthly counts of the number of tropical cyclones that

attained major or intense hurricane storm strength

Year JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Sum

1945 1 1 1 3

1946 1 1

1947 1 1 2

1948 1 2 1 4

1949 1 2 3

1950 4 2 2 8

1951 1 2 2 5

1952 1 1 1 3

1953 1 3 4

1954 1 1 2

1955 2 3 1 6

1956 1 1 2

1957 1 1 2

1958 3 2 5

1959 2 2

1960 1 1 2

1961 1 5 1 7

1962 1 1

1963 1 1 2

1964 1 4 1 6

1965 1 1

1966 1 1 1 3

1967 1 1

1968 0

1969 3 2 5

1970 1 1 2

1971 1 1

1972 0

1973 1 1

1974 2 2

1975 1 2 3

1976 2 2

1977 1 1

1978 1 1 2

1979 2 2

1980 1 1 2

1981 3 3

1982 1 1

1983 1 1

1984 1 1

1985 1 1 1 3

1986 0

1987 1 1

1988 2 1 3

1989 1 1 2

1990 1 1

1991 1 1 2

1992 1 1

1993 1 1

1994 0

1995 2 2 1 5

1996 1 2 2 1 6

1997 1 1

1998 1 1 1 3

1999 2 2 1 5

2000 1 2 3

2001 2 1 1 4

2002 2 2

2003 1 2 3

2004 3 3 6

2005 2 1 2 2 7

2006 2 2

2007 1 1 2

2008 1 1 1 1 1 5

2009 1 1 2

2010 2 3 5

Sum 1 3 5 61 85 19 5 179

*********************************************************
202

Table 12. Monthly counts of the number of tropical cyclones that became US landfalling 

hurricanes. Table 12. Monthly counts ofthe number of tropical cyclones that

became US land-falling hurricanes

Year JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Sum

1945 1 1 1 3

1946 1 1

1947 1 1 1 3

1948 2 1 3

1949 2 1 3

1950 1 1 1 3

1951 0

1952 1 1

1953 2 1 3

1954 1 1 1 3

1955 2 1 3

1956 1 1

1957 1 1

1958 1 1

1959 2 1 3

1960 1 1 2

1961 1 1

1962 0

1963 1 1

1964 1 2 1 4

1965 1 1

1966 1 1 2

1967 1 1

1968 1 1

1969 1 1 2

1970 1 1

1971 3 3

1972 1 1

1973 0

1974 1 1

1975 1 1

1976 1 1

1977 1 1

1978 0

1979 1 2 3

1980 1 1

1981 0

1982 0

1983 1 1

1984 1 1

1985 1 2 1 1 1 6

1986 1 1 2

1987 1 1

1988 1 1

1989 1 1 1 3

1990 0

1991 1 1

1992 1 1

1993 1 1

1994 0

1995 1 1 2

1996 1 1 2

1997 1 1

1998 2 1 3

1999 1 1 1 3

2000 0

2001 0

2002 1 1

2003 1 1 2

2004 4 2 6

2005 2 1 2 1 6

2006 0

2007 1 1

2008 1 1 1 3

2009 0

2010 0

Sum 5 12 38 40 12 1 108
203

Table 13. Poisson probabilities by onset month, June–November, 1945–2010. 

A. NTC

 June July August September October November

 r (m = 0.58) (m = 0.94) (m = 2.85) (m = 3.71) (m = 1.89) (m = 0.53)

 0 0.5599 0.3906 0.0578 0.0245 0.1511 0.5856

 1 0.3247 0.3672 0.1649 0.0908 0.2855 0.3120

 2 0.0942 0.1726 0.2349 0.1685 0.2698 0.0827

 3 0.0182 0.0541 0.2232 0.2083 0.1700 0.0146

 4 0.0026 0.0127 0.1590 0.1932 0.0803 0.0019

 5 0.0003 0.0024 0.0906 0.1434 0.0304 0.0002

 6 0.0000 0.0004 0.0431 0.0886 0.0096 0.0000

 7 0.0001 0.0175 0.0470 0.0026

 8 0.0000 0.0062 0.0218 0.0006

 9 0.0020 0.0090 0.0001

10 0.0006 0.0033 0.0000

11 0.0001 0.0011

12 0.0000 0.0003

13 0.0001

14 0.0000

B. NTS

 June July August September October November

 r (m = 0.39) (m = 0.53) (m = 1.18) (m = 1.27) (m = 0.79) (m = 0.20)

 0 0.6771 0.5886 0.3073 0.2808 0.4538 0.8187

 1 0.2641 0.3120 0.3626 0.3567 0.3585 0.1637

 2 0.0515 0.0827 0.2139 0.2265 0.1416 0.0164

 3 0.0067 0.0146 0.0841 0.0959 0.0373 0.0011

 4 0.0007 0.0019 0.0248 0.0304 0.0074 0.0001

 5 0.0001 0.0002 0.0059 0.0077 0.0012 0.0000

 6 0.0000 0.0000 0.0012 0.0016 0.0002

 7 0.0002 0.0003 0.0000

 8 0.0000 0.0000

C. NH

 June July August September October November

 r (m = 0.18) (m = 0.41) (m = 1.67) (m = 2.44) (m = 1.11) (m = 0.33)

 0 0.8353 0.6637 0.1882 0.0872 0.3296 0.7189

 1 0.1503 0.2721 0.3144 0.2127 0.3658 0.2372

 2 0.0135 0.0558 0.2625 0.2595 0.2030 0.0391

 3 0.0008 0.0076 0.1461 0.2110 0.0751 0.0043

 4 0.0000 0.0008 0.0610 0.1287 0.0208 0.0004

 5 0.0001 0.0204 0.0628 0.0046 0.0000

 6 0.0057 0.0255 0.0009

 7 0.0014 0.0089 0.0001

 8 0.0003 0.0027 0.0000

 9 0.0001 0.0007

10 0.0000 0.0002

11 0.0000

D. NMH

 June July August September October November

 r (m = 0.05) (m = 0.08) (m = 0.92) (m = 1.29) (m = 0.29) (m = 0.08)

 0 0.9512 0.9231 0.3985 0.2753 0.7483 0.9231

 1 0.0476 0.0738 0.3666 0.3551 0.2170 0.0738

 2 0.0012 0.0030 0.1687 0.2290 0.0315 0.0030

 3 0.0000 0.0001 0.0517 0.0985 0.0030 0.0001

 4 0.0000 0.0119 0.0318 0.0002 0.0000

 5 0.0022 0.0082 0.0000

 6 0.0003 0.0018

 7 0.0000 0.0003

 8 0.0001

 9 0.0000

E. NUSLFH

 June July August September October November

 r (m = 0.08) (m = 0.18) (m = 0.58) (m = 0.61) (m = 0.18) (m = 0.02)

 0 0.9231 0.8353 0.5599 0.5434 0.8353 0.9802

 1 0.0738 0.1503 0.3247 0.3314 0.1503 0.0196

 2 0.0030 0.0135 0.0942 0.1011 0.0135 0.0002

 3 0.0001 0.0008 0.0182 0.0206 0.0008 0.0000

 4 0.0000 0.0000 0.0026 0.0031 0.0000

 5 0.0003 0.0004

 6 0.0000 0.0000
204

Table 14. Yearly US hurricane landstrikes by state. Table 14. Yearly US hurricane landstrikes by state

 State

Year IAL AL CT AFL BFL CFL DFL IGA GA LA MA MD ME MS INC NC NH NY RI SC ATX BTX CTX VA Total

1945 1 1 1 3

1946 1 1

1947 1 2 1 1 1 1 1 8

1948 1 2 1 4

1949 1 1 1 3

1950 1 1 1 3#

1951 0&

1952 1 1

1953 1 1 1 3

1954 1 1 1 1 2 1 1 1 9#

1955 3 1 4#

1956 1 1 2#

1957 1 1 2&

1958 1 1

1959 2 1 3

1960 1 1 1 1 1 1 1 1 1 1 10

1961 1 1

1962 0

1963 1 1&

1964 1 2 1 1 5#

1965 1 1 2&

1966 1 1 2

1967 1 1

1968 1 1 2

1969 1 1 1 3&

1970 1 1#

1971 1 1 1 3#

1972 1 1 1 3&

1973 0#

1974 1 1#

1975 1 1 2#

1976 1 1

1977 1 1

1978 0

1979 1 1 1 1 1 1 1 7

1980 1 1

1981 0

1982 0&

1983 1 1

1984 1 1

1985 1 1 2 1 2 1 1 1 1 1 1 13#

1986 1 1 2&

1987 1 1&

1988 1 1#

1989 1 1 2 4 

1990 0

1991 1 1 1 1 4&

1992 1 1 1 3

1993 1 1

1994 0&

1995 1 2 1 4

1996 2 2

1997 1 1 2&

1998 1 1 1 1 4#

1999 1 1 1 3#

2000 0

2001 0

2002 1 1&

2003 1 1 1 3

2004 1 2 3 3 1 2 2 14&

2005 1 1 1 3 2 3 1 1 1 14

2006 0&

2007 1 1 2

2008 2 1 1 4

2009 0&

2010 0#

Total 2 7 5 16 16 18 5 1 2 23 3 1 5 7 1 22 2 6 3 10 5 4 12 2 178

Note: # means year classified as a LNY and & means year classified as an ENY, based on the ONI being in the 

prescribed

ENSO condition for 4 or more months during June-November
205

Table 15. Poisson probabilities by geographical grouping, 1945–2010.

A. NTC

 Group 1 Group 2 Group 3 Group 4 Group 5

 r (m = 2.3) (m = 1.7) (m = 2.5) (m = 3.0) (m = 1.4)

 0 0.1003 0.1827 0.0821 0.0498 0.2466

 1 0.2306 0.3106 0.2052 0.1494 0.3452

 2 0.2652 0.2640 0.2565 0.2240 0.2417

 3 0.2033 0.1496 0.2138 0.2240 0.1128

 4 0.1169 0.0636 0.1336 0.1680 0.0395

 5 0.0538 0.0216 0.0668 0.1008 0.0111

 6 0.0206 0.0061 0.0278 0.0504 0.0026

 7 0.0068 0.0015 0.0099 0.0216 0.0005

 8 0.0019 0.0003 0.0031 0.0081 0.0001

 9 0.0005 0.0001 0.0009 0.0027 0.0000

10 0.0001 0.0000 0.0002 0.0008

11 0.0000 0.0000 0.0002

12 0.0001

13 0.0000

B. NTS

 Group 1 Group 2 Group 3 Group 4 Group 5

 r (m = 1.3) (m = 0.5) (m = 1.2) (m = 1.0) (m = 0.6)

 0 0.2725 0.6065 0.3012 0.3679 0.5488

 1 0.3543 0.3033 0.3614 0.3679 0.3293

 2 0.2303 0.0758 0.2169 0.1839 0.0988

 3 0.0998 0.0126 0.0867 0.0613 0.0198

 4 0.0324 0.0016 0.0260 0.0153 0.0030

 5 0.0084 0.0002 0.0062 0.0031 0.0004

 6 0.0018 0.0000 0.0012 0.0005 0.0000

 7 0.0003 0.0002 0.0001

 8 0.0001 0.0000 0.0000

 9 0.0000

C. NH

 Group 1 Group 2 Group 3 Group 4 Group 5

 r (m = 0.9) (m = 1.2) (m = 1.3) (m = 2.0) (m = 0.7)

 0 0.4066 0.3012 0.2725 0.1353 0.4966

 1 0.3659 0.3614 0.3543 0.2707 0.3476

 2 0.1647 0.2169 0.2303 0.2707 0.1217

 3 0.0494 0.0867 0.0998 0.1804 0.0284

 4 0.0111 0.0260 0.0324 0.0902 0.0050

 5 0.0020 0.0062 0.0084 0.0361 0.0007

 6 0.0003 0.0012 0.0018 0.0120 0.0001

 7 0.0000 0.0002 0.0003 0.0034 0.0000

 8 0.0000 0.0001 0.0009

 9 0.0000 0.0002

10 0.0000

D. NMH

 Group 1 Group 2 Group 3 Group 4 Group 5

 r (m = 0.3) (m = 0.7) (m = 0.3) (m = 1.4) (m = 0.1)

 0 0.7408 0.4966 0.7408 0.2466 0.9048

 1 0.2222 0.3476 0.2222 0.3452 0.0905

 2 0.0333 0.1217 0.0333 0.2417 0.0045

 3 0.0033 0.0284 0.0033 0.1128 0.0002

 4 0.0003 0.0050 0.0003 0.0395 0.0000

 5 0.0000 0.0007 0.0000 0.0111

 6 0.0001 0.0026

 7 0.0000 0.0005

 8 0.0001

 9 0.0000

E. USLFH

 Group 1 Group 2 Group 3 Group 4

 r (m = 0.5) (m = 0.4) (m = 0.3) (m = 0.5)

 0 0.6065 0.6703 0.7408 0.6065

 1 0.3033 0.2681 0.2222 0.3033

 2 0.0758 0.0464 0.0333 0.0758

 3 0.0126 0.0072 0.0033 0.0126

 4 0.0016 0.0001 0.0003 0.0016

 5 0.0002 0.0000 0.0000 0.0002

 6 0.0000 0.0000

 7
206

Table 16. Yearly surface air temperature and ENSO parametric values.

Table 16. Yearly surface-air temperature and ENSO Parametric Values

Year <AT> <SOI> <ONI> <NAO> <PDO> <TNI> <MEI> <GSSTEI> <JMASSTM> <NTA> <CAR> <QBO> <AMO> <AMM> 

Comments

1945 10.29 4.6 - - -0.19 1.125 - 0.018 - - - - - -

1946 9.23 -6.7 - - -0.58 -0.926 - 0.011 - - - - - - 

1947 9.15 2.3 - - 0.50 -0.356 - 0.064 - - - - - -

1948 9.71 -1.2 - - -0.87 -0.455 - -0.003 - - - -6.25 0.017 0.72

1949 10.32 -1.1 - - -1.23 0.026 - -0.191 25.0 - - -9.16 0.097 -0.30

1950# 9.17 15.4 -1.06 -0.12 -1.81 0.516 -1.094 -0.349 24.9 - - -6.43 -0.004 0.76 (1)

1951& 8.95 -0.7 0.09 -0.01 -0.77 1.243 0.053 -0.072 26.2 0.086 -0.039 -3.05 0.208 1.35

1952 8.81 -2.3 -0.03 -0.43 -0.87 -0.454 -0.015 -0.108 25.5 -0.021 0.224 -5.38 0.300 1.47

1953 9.87 -6.8 0.42 -0.02 -0.16 0.154 0.345 0.038 26.0 0.144 0.082 -0.55 0.269 1.64

1954# 9.15 4.1 -0.63 0.00 -0.29 -1.044 -0.916 -0.167 24.7 -0.286 -0.143 -10.31 0.048 -0.17

1955# 9.49 10.6 -1.24 -0.40 -1.95 0.403 -1.607 -0.317 24.5 0.059 -0.141 4.45 0.197 2.50 (2)

1956# 9.37 10.7 -0.80 -0.04 -1.80 0.685 -1.281 -0.253 24.9 -0.172 -0.141 -9.60 -0.014 0.92

1957& 9.83 -3.9 0.69 -0.20 0.23 0.856 0.634 0.105 26.3 -0.136 0.133 1.50 0.045 -0.36

1958 9.45 -3.2 0.61 -0.59 0.64 -0.378 0.805 0.145 25.9 0.501 0.337 -8.12 0.219 4.42

1959 10.20 0.0 -0.06 0.35 -0.03 -0.134 0.131 0.043 25.5 -0.207 0.075 -1.48 0.058 -0.23

1960 9.44 3.8 -0.19 -0.41 0.06 -0.269 -0.283 0.028 25.4 -0.084 0.154 -7.76 0.241 1.14

1961 9.58 0.8 -0.23 0.04 -0.82 0.017 -0.257 -0.129 25.3 0.014 0.048 4.42 0.105 0.66

1962 8.76 5.4 -0.47 -0.34 -1.16 -0.448 -0.763 -0.091 25.2 0.165 0.189 -7.73 0.077 2.01

1963& 8.57 -2.0 0.40 -0.42 -0.69 -0.384 0.058 0.216 26.0 0.039 0.070 -8.75 0.010 -0.48

1964# 9.49 6.3 -0.62 -0.04 -0.77 -0.437 -0.791 0.073 24.9 -0.101 -0.037 2.38 -0.090 0.45

1965& 8.82 -8.4 0.64 -0.13 -0.31 1.017 0.718 0.198 26.3 -0.239 -0.148 -11.93 -0.154 -1.77

1966 9.38 -4.2 0.26 -0.33 -0.46 -1.510 0.275 0.228 25.5 0.157 -0.009 1.29 0.010 1.07

1967 9.40 3.2 -0.35 0.37 -0.73 -1.040 -0.634 -0.133 25.1 -0.170 -0.179 0.93 -0.092 -0.04

1968 9.32 3.0 -0.03 -0.94 -0.40 -0.957 -0.313 0.068 25.4 -0.124 -0.092 -14.41 -0.161 -0.82

1969& 8.93 -5.4 0.69 -0.06 -0.10 -0.311 0.530 0.383 26.3 0.545 0.178 4.81 0.015 1.82

1970# 9.28 3.9 -0.36 -0.25 -0.40 -1.027 -0.570 0.088 24.8 0.240 -0.083 -13.76 -0.098 2.28

1971# 9.72 11.0 -0.95 0.01 -1.29 0.366 -1.426 -0.165 24.7 -0.246 -0.256 4.80 -0.307 -1.36

1972& 8.74 -7.4 0.84 0.51 -0.92 0.990 0.882 0.225 26.7 -0.304 -0.123 -8.10 -0.348 -4.02

1973# 9.33 7.3 -0.64 -0.09 -0.80 -0.044 -0.472 0.100 25.0 -0.060 -0.031 4.40 -0.211 -3.13

1974# 8.94 9.9 -0.97 0.18 -0.41 1.299 -1.178 -0.183 25.0 -0.495 -0.312 -13.42 -0.416 -4.13 (3)

1975# 9.69 13.6 -1.14 -0.07 -1.10 1.413 -1.306 -0.250 24.7 -0.414 -0.256 1.25 -0.294 -1.88

1976 9.33 1.1 -0.15 0.19 0.01 1.499 -0.115 -0.001 25.8 -0.322 -0.332 0.85 -0.359 -0.85 (4)

1977 8.92 -9.9 0.45 -0.34 0.23 -1.207 0.622 0.106 25.8 -0.189 -0.066 -11.27 -0.184 -1.34

1978 9.21 -1.7 -0.15 0.32 0.24 -0.707 0.123 0.041 25.3 0.027 0.044 6.81 -0.175 0.72

1979 8.35 -1.9 0.16 0.14 0.34 -0.052 0.516 0.133 25.9 0.149 -0.037 -13.16 -0.105 1.09 (5)

1980 9.11 -3.1 0.14 -0.41 0.60 -1.161 0.544 0.203 25.7 0.174 0.164 5.27 -0.013 2.34

1981 9.09 1.8 -0.32 -0.24 0.92 -0.688 0.059 0.122 25.3 0.095 0.058 -1.91 -0.071 1.84

1982& 9.43 -13.1 0.95 0.43 0.11 -0.483 1.095 0.306 26.8 -0.097 0.035 -6.44 -0.207 -1.50 (6)

1983 9.77 -8.3 0.47 0.31 1.65 3.096 1.594 0.395 26.7 0.234 0.150 1.15 -0.065 -0.30 (7)

1984 9.29 -0.1 -0.45 0.25 0.84 0.461 -0.152 0.117 25.2 -0.148 -0.135 -17.02 -0.201 -2.86

1985# 8.70 0.9 -0.58 -0.18 0.45 -0.543 -0.401 0.005 25.0 -0.197 -0.066 9.63 -0.259 -1.91 (8)

1986& 8.57 -2.4 0.28 0.50 1.24 -1.010 0.448 0.173 25.9 -0.295 -0.075 -0.98 -0.265 -3.82

1987& 9.07 -13.1 1.29 -0.12 1.82 -0.568 1.650 0.474 26.8 0.324 0.167 -6.25 0.071 0.00 (9)

1988# 9.65 7.8 -0.83 -0.01 0.53 -0.049 -0.531 0.187 24.7 0.228 -0.012 1.56 0.005 0.09

1989 10.07 6.8 -0.63 0.70 -0.18 0.758 -0.550 -0.077 25.2 -0.082 -0.080 -10.70 -0.073 -1.08

1990 9.93 -2.2 0.25 0.59 -0.36 -1.668 0.384 0.076 25.8 0.157 0.155 5.28 -0.026 0.27

1991& 9.42 -8.8 0.80 0.27 -0.42 -1.524 0.800 0.179 26.3 -0.128 -0.010 -3.24 -0.122 -2.35

1992 9.45 -10.4 0.76 0.58 0.93 -0.628 1.305 0.216 26.3 -0.070 -0.081 -7.61 -0.211 -0.50

1993 9.27 -9.5 0.47 0.18 1.42 -0.533 1.086 0.222 26.1 -0.101 -0.059 3.90 -0.201 -3.04

1994& 9.32 -11.9 0.62 0.80 -0.15 -1.759 0.725 0.133 25.8 -0.286 0.020 -13.67 -0.160 -3.51

1995 10.22 -2.3 0.08 -0.08 0.64 -1.064 0.198 0.208 25.4 0.314 0.180 7.82 0.120 1.24

1996 9.22 5.7 -0.29 -0.21 0.64 -1.069 -0.351 0.129 25.2 0.242 -0.051 -16.06 -0.047 0.86

1997& 10.32 -11.7 1.26 -0.16 1.46 1.722 1.547 0.280 27.4 0.364 0.075 7.86 0.064 1.08 (10)

1998# 10.09 -1.1 0.09 -0.48 0.25 2.985 0.847 0.253 26.2 0.555 0.384 -12.83 0.389 1.84 (11)

1999# 10.18 8.0 -1.06 0.39 -1.06 0.986 -0.928 -0.198 24.8 0.012 0.156 10.17 0.140 0.32

2000 9.93 7.8 -0.74 0.21 -0.59 0.733 -0.532 -0.149 25.2 0.023 -0.031 -6.49 0.047 -0.45

2001 9.57 0.5 -0.12 -0.18 -0.56 -0.957 -0.157 -0.058 25.5 0.223 0.170 -15.24 0.141 1.16

2002& 10.20 -6.1 0.78 0.04 0.22 -1.872 0.580 0.160 26.3 0.210 0.202 8.72 0.086 -0.28

2003 10.02 -3.1 0.48 0.10 0.97 -2.149 0.452 0.207 25.9 0.348 0.241 -13.81 0.252 0.32

2004& 10.21 -4.8 0.56 0.24 0.35 -2.246 0.413 0.083 25.9 0.454 0.208 6.60 0.226 2.85 (12)

2005 10.24 -3.6 0.21 -0.27 0.38 -1.692 0.317 0.076 25.7 0.624 0.265 -17.13 0.312 3.67 (13)

2006& 10.43 -1.9 0.25 -0.21 0.19 -0.562 0.307 0.118 26.1 0.412 0.164 4.47 0.287 1.73

2007 10.59 1.5 -0.30 0.17 -0.20 -1.444 -0.337 0.068 25.2 0.281 0.181 -15.91 0.169 1.25 (14)

2008 9.78 10.2 -0.56 -0.38 -1.27 1.857 -0.682 -0.058 25.6 0.264 0.035 6.97 0.160 0.70

2009& 9.83 -0.2 0.47 -0.24 -0.61 -0.514 0.397 0.183 26.4 0.182 0.198 -3.49 0.062 -0.98

2010# 8.74 9.8 -0.15 -1.15 -0.31 -0.452 -0.429 0.165 25.5 0.915 0.237 -7.95 0.375 4.98 (15)

Mean 9.48 -0.1 -0.01 -0.03 -0.13 -0.190 0.039 0.062 25.6 0.063 0.033 -3.65 -0.002 0.13

 sd 0.53 6.8 0.62 0.37 0.83 1.128 0.768 0.171 0.6 0.280 0.159 7.94 0.191 1.94

Comments:

 (1) Most positive <SOI>; most negative <GSSTEI>

 (2) Most negative <ONI>; most negative <PDO>; most negative <MEI>; lowest <JMASSTM>

 (3) Most negative <NTA>; most negative <AMO>; most negative <AMM>

 (4) Most negative <CAR>

 (5) Lowest <AT>

 (6) Most negative <SOI>

 (7) Most positive <TNI>; most positive <MEI>

 (8) Most positive <QBO>

 (9) Most negative <SOI>; most positive <ONI>; most positive <PDO>; most positive <GSSTEI>

 (10) Highest <JMASSTM>

 (11) Most positive <CAR>; most positive <AMO>

 (12) Most negative <TNI>

 (13) Most negative <QBO>

 (14) Highest <AT>

 (15) Most negative <NAO>; most positive <NTA>; most positive <AMM>
207

Table 17. 10-yma of surface air temperature and ENSO parametric values. Table 17. 10-yma of surface-air temperature and ENSO parametric values

Year <AT> <SOI> <ONI> <NAO> <PDO> <TNI> <MEI> <GSSTEI> <JMASSTM> <NTA> <CAR> <QBO> <AMO> <AMM>

1950 9.43 1.06 - - -0.72 -0.053 - -0.093 - - - - - -

1951 9.39 2.23 - - -0.86 -0.009 - -0.123 - - - - - -

1952 9.43 2.79 - - -0.94 0.132 - -0.134 - - - - - -

1953 9.45 2.38 - - -0.88 0.197 - -0.124 - - - -4.57 0.126 1.04

1954 9.44 2.34 - - -0.74 0.193 - -0.105 25.42 - - -4.28 0.135 1.23

1955 9.44 1.81 -0.16 -0.16 -0.59 0.145 -0.254 -0.075 25.47 - - -3.96 0.145 1.25

1956 9.49 1.31 -0.13 -0.17 -0.50 0.045 -0.229 -0.059 25.45 -0.015 0.058 -3.66 0.152 1.23

1957 9.52 1.77 -0.17 -0.17 -0.51 -0.016 -0.282 -0.061 25.39 -0.010 0.061 -3.40 0.136 1.23

1958 9.45 2.39 -0.19 -0.18 -0.55 -0.043 -0.334 -0.051 25.37 -0.005 0.059 -3.93 0.112 1.15

1959 9.40 2.74 -0.19 -0.20 -0.61 -0.039 -0.342 -0.030 25.38 -0.001 0.063 -3.70 0.092 1.07

1960 9.38 1.90 -0.10 -0.19 -0.55 0.022 -0.219 0.008 25.48 -0.007 0.068 -3.89 0.067 0.89

1961 9.35 0.21 0.05 -0.19 -0.40 -0.057 -0.025 0.058 25.60 -0.006 0.075 -4.16 0.051 0.68

1962 9.33 -0.19 0.05 -0.18 -0.38 -0.262 -0.011 0.070 25.57 0.009 0.066 -3.65 0.045 0.71

1963 9.30 0.48 -0.03 -0.17 -0.48 -0.386 -0.130 0.054 25.49 -0.024 0.029 -3.99 0.019 0.46

1964 9.23 0.52 -0.03 -0.21 -0.53 -0.423 -0.166 0.067 25.50 -0.017 0.012 -3.99 -0.002 0.30

1965 9.16 0.26 0.00 -0.22 -0.56 -0.470 -0.160 0.087 25.51 0.036 0.006 -3.98 -0.021 0.46

1966 9.16 0.77 -0.04 -0.21 -0.61 -0.491 -0.233 0.088 25.45 0.040 -0.022 -4.26 -0.058 0.42

1967 9.17 0.64 -0.01 -0.17 -0.62 -0.401 -0.209 0.102 25.50 0.003 -0.052 -4.26 -0.100 0.01

1968 9.20 0.47 0.00 -0.11 -0.61 -0.312 -0.154 0.112 25.52 -0.025 -0.073 -3.62 -0.133 -0.42

1969 9.21 1.11 -0.07 -0.08 -0.60 -0.209 -0.199 0.094 25.48 -0.050 -0.092 -3.75 -0.160 -0.78

1970 9.23 2.39 -0.18 -0.07 -0.62 -0.102 -0.320 0.059 25.40 -0.078 -0.111 -3.88 -0.183 -1.02

1971 9.27 3.76 -0.29 -0.04 -0.64 0.068 -0.441 0.025 25.34 -0.111 -0.132 -3.24 -0.209 -1.12

1972 9.24 3.37 -0.27 -0.05 -0.57 0.210 -0.397 0.025 25.39 -0.136 -0.143 -3.88 -0.232 -1.28

1973 9.21 2.48 -0.23 -0.02 -0.49 0.215 -0.313 0.036 25.42 -0.129 -0.131 -3.42 -0.237 -1.27

1974 9.18 2.42 -0.26 0.05 -0.43 0.240 -0.292 0.022 25.39 -0.142 -0.134 -3.26 -0.244 -1.23

1975 9.14 2.24 -0.27 0.05 -0.28 0.246 -0.237 0.015 25.42 -0.165 -0.133 -3.21 -0.245 -1.26

1976 9.10 1.43 -0.21 0.03 -0.20 0.187 -0.107 0.035 25.49 -0.151 -0.105 -2.59 -0.229 -1.10

1977 9.11 0.69 -0.17 0.02 -0.04 0.061 -0.022 0.054 25.53 -0.124 -0.081 -2.85 -0.211 -0.81

1978 9.16 -0.38 -0.11 0.03 0.14 0.144 0.092 0.072 25.62 -0.099 -0.064 -2.92 -0.196 -0.54

1979 9.20 -1.66 -0.03 0.05 0.32 0.259 0.247 0.102 25.71 -0.066 -0.046 -3.27 -0.178 -0.34

1980 9.17 -2.80 0.02 0.05 0.46 0.119 0.343 0.130 25.74 -0.038 -0.028 -3.03 -0.166 -0.28

1981 9.08 -3.61 0.07 0.06 0.60 -0.104 0.417 0.151 25.76 -0.026 -0.006 -2.70 -0.159 -0.43

1982 9.05 -3.94 0.14 0.09 0.74 -0.197 0.496 0.179 25.81 0.001 0.019 -2.54 -0.142 -0.51

1983 9.08 -3.63 0.15 0.08 0.84 -0.133 0.515 0.204 25.83 0.037 0.028 -2.55 -0.120 -0.47

1984 9.19 -2.72 0.07 0.10 0.82 -0.059 0.429 0.201 25.77 0.035 0.023 -2.69 -0.109 -0.61

1985 9.32 -2.24 0.04 0.17 0.75 -0.044 0.368 0.184 25.74 0.023 0.020 -2.57 -0.108 -0.82

1986 9.37 -2.72 0.10 0.25 0.64 -0.111 0.397 0.181 25.79 0.011 0.016 -2.63 -0.112 -1.14

1987 9.39 -3.12 0.15 0.28 0.61 -0.160 0.444 0.179 25.82 0.001 0.007 -2.76 -0.114 -1.30

1988 9.37 -3.04 0.14 0.28 0.64 -0.349 0.429 0.166 25.76 -0.014 -0.009 -2.68 -0.121 -1.38

1989 9.34 -3.69 0.19 0.30 0.58 -0.641 0.448 0.158 25.76 -0.038 -0.012 -2.38 -0.126 -1.55

1990 9.42 -4.44 0.28 0.34 0.54 -0.778 0.522 0.169 25.81 -0.019 0.008 -2.30 -0.105 -1.43

1991 9.53 -4.20 0.28 0.31 0.52 -0.807 0.512 0.177 25.80 0.033 0.022 -3.14 -0.075 -1.04

1992 9.62 -3.72 0.25 0.27 0.47 -0.696 0.466 0.165 25.79 0.062 0.018 -3.19 -0.065 -0.75

1993 9.71 -4.10 0.30 0.24 0.44 -0.430 0.530 0.159 25.90 0.080 0.034 -3.21 -0.046 -0.61

1994 9.74 -4.48 0.32 0.20 0.38 -0.267 0.580 0.156 25.95 0.101 0.065 -2.88 -0.016 -0.45

1995 9.74 -3.92 0.25 0.17 0.32 -0.135 0.516 0.139 25.90 0.099 0.068 -2.43 -0.002 -0.42

1996 9.75 -2.96 0.15 0.13 0.31 0.013 0.422 0.115 25.83 0.110 0.067 -3.62 0.015 -0.28

1997 9.79 -2.28 0.11 0.08 0.26 -0.021 0.338 0.101 25.79 0.142 0.090 -3.40 0.043 -0.09

1998 9.87 -2.19 0.11 0.05 0.20 -0.164 0.270 0.097 25.78 0.178 0.120 -3.47 0.081 0.09

1999 9.95 -1.07 0.11 0.02 0.21 -0.269 0.223 0.094 25.78 0.238 0.144 -3.34 0.123 0.58

2000 10.00 -0.78 0.11 -0.02 0.22 -0.325 0.213 0.085 25.80 0.290 0.158 -3.57 0.151 1.02

2001 10.06 -1.22 0.14 -0.03 0.18 -0.331 0.252 0.078 25.86 0.314 0.173 -3.79 0.178 1.18

2002 10.13 -0.94 0.09 -0.02 0.08 -0.464 0.190 0.067 25.79 0.318 0.189 -3.96 0.200 1.23

2003 10.13 -0.63 -0.02 -0.01 -0.08 -0.678 0.020 0.040 25.65 0.300 0.177 -4.16 0.193 1.18

2004 10.10 0.44 0.03 -0.02 -0.13 -0.810 0.010 0.044 25.70 0.294 0.161 -3.85 0.178 1.06

2005 10.02 0.13 0.04 -0.12 -0.10 -0.944 0.081 0.079 25.80 0.347 0.177 -4.60 0.191 1.27
208

Table 18. Differences of surface air and ENSO parametric values (d = x – 10-yma). Table 18. Differences of surface-air and ENSO parametric values ( d = x - 10-yma)

Year <AT> <SOI> <ONI> <NAO> <PDO> <TNI> <MEI> <GSSTEI> <JMASSTM> <NTA> <CAR> <QBO> <AMO> <AMM>

1950 -0.26 14.34 - - -1.09 0.569 - -0.256 - - - - - -

1951 -0.44 -2.93 - - 0.09 1.252 - 0.051 - - - - - -

1952 -0.62 -5.09 - - 0.07 -0.586 - 0.026 - - - - - -

1953 -0.58 -9.18 - - 0.72 -0.043 - 0.162 - - - 4.02 0.143 0.60

1954 -0.26 1.76 - - 0.45 -1.237 - -0.062 -0.72 - - -6.03 -0.087 -1.40

1955 0.05 8.79 -1.08 -0.24 -1.36 0.258 -1.353 -0.242 -0.97 - - 8.41 0.052 1.25

1956 -0.12 9.39 -0.67 0.13 -1.30 0.640 -1.052 -0.194 -0.55 -0.157 -0.199 -5.94 -0.166 -0.31

1957 0.31 -5.67 0.86 -0.03 0.74 0.872 0.916 0.166 0.91 -0.126 0.072 4.90 -0.091 -1.59

1958 0.00 -5.59 0.80 -0.41 1.19 -0.335 1.139 0.196 0.53 0.506 0.278 -4.19 0.107 3.27

1959 0.80 -2.74 0.13 0.55 0.58 -0.095 0.473 0.073 0.12 -0.206 0.012 2.22 -0.034 -1.30

1960 0.06 1.90 -0.09 -0.22 0.61 -0.291 -0.064 0.020 -0.08 -0.077 0.086 -3.87 0.174 0.25

1961 0.23 0.59 -0.28 0.23 -0.42 0.074 -0.232 -0.187 -0.30 0.020 -0.027 8.58 0.054 -0.02

1962 -0.57 5.59 -0.52 -0.16 -0.78 -0.186 -0.752 -0.161 -0.37 0.156 0.123 -4.08 0.032 1.30

1963 -0.73 -2.48 0.43 -0.25 -0.21 0.002 0.188 0.162 0.51 0.063 0.041 -4.76 -0.009 -0.94

1964 0.26 5.78 -0.59 0.17 -0.24 -0.014 -0.625 0.006 -0.60 -0.084 -0.049 6.37 -0.088 0.15

1965 -0.34 -8.66 0.64 0.09 0.25 1.487 0.878 0.111 0.79 -0.275 -0.154 -7.95 -0.133 -2.23

1966 0.22 -4.97 0.30 -0.12 0.15 -0.660 0.508 0.140 0.05 0.117 0.013 5.55 0.068 0.65

1967 0.23 2.56 -0.34 0.54 -0.11 -0.639 -0.425 -0.235 -0.40 -0.173 0.231 5.19 0.008 -0.05

1968 0.12 2.53 -0.03 -0.83 0.21 -0.645 -0.159 -0.044 -0.12 -0.099 -0.019 -10.79 -0.028 -0.40

1969 -0.28 -6.51 0.76 0.02 0.50 -0.102 0.729 0.289 0.82 0.595 0.270 8.56 0.175 2.60

1970 0.05 1.51 -0.18 -0.18 0.22 -0.925 -0.250 0.029 -0.60 0.318 0.028 -9.88 0.085 3.30

1971 0.45 7.24 -0.66 0.05 -0.65 0.298 -0.985 -0.190 -0.64 -0.135 -0.124 8.04 -0.098 -0.24

1972 -0.50 -10.77 1.11 0.56 -0.35 0.780 1.279 0.200 1.31 -0.168 0.020 -4.22 -0.116 -2.74

1973 0.12 4.82 -0.41 -0.07 -0.31 -0.259 -0.159 0.064 -0.42 0.069 0.100 7.82 0.026 -1.86

1974 -0.24 7.48 -0.71 0.13 0.02 1.059 -0.886 -0.205 -0.39 -0.353 -0.178 -10.16 -0.172 -2.90

1975 0.55 11.36 -0.87 -0.12 -0.82 1.167 -1.069 -0.265 -0.72 -0.249 -0.123 4.46 -0.049 -0.62

1976 0.23 -0.33 -0.36 0.16 0.21 1.312 -0.008 -0.036 0.31 -0.171 -0.227 3.44 -0.130 0.25

1977 -0.19 -10.59 0.62 -0.36 0.27 -1.268 0.644 0.052 0.27 -0.065 0.015 -8.42 0.027 -0.53

1978 0.05 -1.32 -0.04 0.29 0.10 -0.851 0.031 -0.031 -0.32 0.126 0.108 9.73 0.021 1.26

1979 -0.85 -0.24 0.19 0.09 0.02 -0.311 0.269 0.031 0.19 0.215 0.009 -9.89 0.073 1.43

1980 -0.06 -0.30 0.12 -0.46 0.14 -1.280 0.201 0.073 -0.04 0.212 0.192 8.30 0.153 2.62

1981 0.01 -1.81 -0.39 -0.30 0.32 -0.584 -0.358 -0.029 -0.46 0.121 0.064 0.79 0.088 2.27

1982 0.38 -9.16 0.81 0.34 -0.63 -0.286 0.599 0.127 0.99 -0.098 0.016 -3.90 -0.065 -0.99

1983 0.69 4.67 0.32 0.23 0.81 3.229 1.079 0.191 0.87 0.197 0.122 3.70 0.055 0.17

1984 0.10 -2.82 -0.52 0.15 0.02 0.520 -0.581 -0.084 -0.57 -0.183 -0.158 -14.33 -0.092 -2.25

1985 -0.62 -1.34 -0.62 -0.35 -0.30 -0.499 -0.769 -0.179 -0.74 -0.220 -0.086 12.20 -0.151 -1.09

1986 -0.80 0.32 0.18 0.25 0.60 -0.899 0.051 -0.008 0.11 -0.306 -0.059 1.65 -0.153 -2.68

1987 -0.32 -9.98 1.14 -0.40 1.21 -0.408 1.206 0.295 0.98 0.323 0.160 -3.49 0.185 1.30

1988 0.28 10.84 -0.97 -0.29 -0.11 0.300 -0.960 0.021 -1.06 0.242 -0.003 4.24 0.126 1.47

1989 0.73 10.49 -0.82 0.40 -0.76 1.399 -0.998 -0.235 -0.56 -0.044 -0.068 -8.32 0.053 0.47

1990 0.51 2.24 -0.03 0.25 -0.90 -0.890 -0.138 -0.093 -0.01 0.176 0.147 2.98 0.079 1.70

1991 -0.11 -4.60 0.52 -0.04 -0.94 -0.717 0.288 0.002 0.50 -0.161 -0.032 -0.10 -0.047 -1.31

1992 -0.17 -6.68 0.51 0.31 0.46 0.068 0.839 0.051 0.51 -0.132 -0.099 -4.42 -0.146 0.25

1993 -0.44 -5.40 0.17 -0.06 0.78 -0.103 0.556 0.063 0.20 -0.181 -0.093 7.11 -0.155 -2.43

1994 -0.42 -7.42 0.30 0.60 -0.53 -1.492 0.145 -0.023 -0.15 -0.387 -0.045 -10.79 -0.144 -3.06

1995 0.48 1.62 -0.17 -0.25 0.32 -0.929 -0.318 0.069 -0.50 0.215 0.112 10.25 0.122 1.66

1996 -0.53 8.66 -0.44 -0.34 0.33 -1.082 -0.773 0.014 -0.63 0.132 -0.118 -12.44 -0.062 1.14

1997 0.53 -9.42 1.15 -0.24 1.20 1.743 1.209 0.179 1.61 0.222 -0.015 11.26 0.021 1.17

1998 0.22 1.09 -0.02 -0.53 0.05 3.149 0.577 0.156 0.42 0.377 0.264 -9.36 0.308 1.75

1999 0.23 9.07 -1.17 0.37 -1.27 1.255 -1.151 -0.292 -0.98 -0.226 0.012 13.51 0.017 -0.26

2000 -0.07 8.58 -0.85 0.23 -0.81 1.059 -0.745 -0.234 -0.60 -0.267 -0.189 -2.92 -0.104 -1.47

2001 -0.49 1.72 -0.26 -0.15 -0.74 -0.626 -0.409 -0.136 -0.36 -0.091 -0.003 -11.45 -0.037 -0.02

2002 0.07 -5.16 0.69 0.06 0.14 -1.408 0.390 0.093 0.51 -0.108 0.013 12.68 -0.114 -1.51

2003 -0.11 -2.47 0.50 0.11 1.05 -1.471 0.432 0.167 0.25 0.048 0.064 -9.65 0.059 -0.86

2004 0.11 -5.24 0.53 0.26 0.48 -1.436 0.403 0.039 0.20 0.160 0.047 10.45 0.048 1.79

2005 0.22 -3.73 0.17 -0.15 0.48 -0.748 0.236 -0.003 -0.10 0.277 0.088 -12.53 0.121 2.40

n+ 30 26 24 26 34 22 26 32 23 23 22 27 28 26

n- 26 30 27 25 22 34 25 24 29 27 28 26 25 27

n+r 14 12 12 17 11 11 11 12 12 11 11 23 13 15

mean -0.03 -0.14 0.00 0.00 0.00 -0.015 0.001 -0.002 -0.02 0.003 0.013 0.40 0.002 0.03

sd 0.40 6.45 0.61 0.31 0.65 1.057 0.713 0.150 0.62 0.226 0.123 8.06 0.109 1.65
209

Table 19. First differences of surface air temperature and ENSO parametric values

based on 10-yma values. Table 19. First differences of surface-air temperature and ENSO parametric values based on 10-yma values

Year <AT> <SOI> <ONI> <NAO> <PDO> <TNI> <MEI> <GSSTEI> <JMASSTM> <NTA> <CAR> <QBO> <AMO> <AMM>

1950 -0.04 1.17 - - -0.14 0.044 - -0.030 - - - - - -

1951 0.04 0.46 - - -0.08 0.141 - -0.014 - - - - - -

1952 0.02 -0.41 - - 0.06 0.065 - 0.010 - - - - - -

1953 -0.01 -0.04 - - -0.14 -0.004 - 0.019 - - - 0.29 0.009 0.19

1954 0.00 -0.53 - - 0.15 -0.048 - 0.030 0.05 - - 0.32 0.010 0.02

1955 0.05 -0.50 0.03 -0.01 0.09 -0.100 0.025 0.016 -0.02 - - 0.30 0.007 -0.02

1956 0.03 0.46 -0.04 0.00 -0.01 -0.061 -0.053 -0.002 -0.06 0.005 0.003 0.26 -0.016 0.00

1957 -0.07 0.62 0.02 -0.01 -0.04 -0.027 -0.052 0.010 -0.02 0.005 -0.002 -0.53 -0.024 -0.08

1958 -0.05 0.35 0.00 -0.02 -0.06 0.004 -0.008 0.021 0.01 0.004 0.004 0.23 -0.020 -0.08

1959 -0.02 -0.84 0.09 0.01 0.06 0.061 0.123 0.038 0.10 -0.006 0.005 -0.19 -0.025 -0.18

1960 -0.03 -1.69 0.15 0.00 0.15 -0.079 0.194 0.050 0.12 0.001 0.007 -0.27 -0.016 -0.21

1961 -0.02 -0.40 0.00 0.01 0.02 -0.205 0.014 0.012 -0.03 0.015 -0.009 0.51 -0.006 0.03

1962 -0.03 0.67 -0.08 0.01 -0.10 -0.124 -0.119 -0.016 -0.08 -0.033 -0.037 -0.34 -0.026 -0.25

1963 -0.07 0.04 0.00 -0.04 -0.05 -0.037 -0.036 0.013 0.01 0.007 -0.017 0.00 -0.021 -0.16

1964 -0.07 -0.26 0.03 -0.01 -0.03 -0.047 0.006 0.020 0.01 0.053 -0.006 0.01 -0.019 0.16

1965 0.00 0.51 -0.04 0.01 -0.05 -0.021 -0.073 0.001 -0.06 0.004 -0.028 -0.28 -0.037 -0.04

1966 0.01 -0.13 0.03 0.04 -0.01 0.090 0.024 0.014 0.05 -0.037 -0.030 0.00 -0.042 -0.41

1967 0.03 -0.17 0.01 0.06 0.01 0.089 0.055 0.010 0.02 -0.028 -0.021 0.64 -0.033 -0.43

1968 0.01 0.64 -0.07 0.03 0.01 0.103 -0.045 -0.018 -0.04 -0.025 -0.019 -0.13 -0.027 -0.36

1969 0.02 1.28 -0.11 0.01 -0.02 0.107 -0.121 -0.035 -0.08 -0.028 -0.019 -0.13 -0.023 -0.24

1970 0.04 1.37 -0.11 0.03 -0.02 0.170 -0.121 -0.034 -0.06 -0.033 -0.012 0.64 -0.026 -0.10

1971 -0.03 -0.39 0.02 -0.01 0.07 0.142 0.044 0.000 0.05 -0.025 -0.011 -0.64 -0.023 -0.16

1972 -0.03 -0.89 0.04 0.03 0.08 0.005 0.084 0.011 0.03 0.007 0.012 0.46 -0.005 0.01

1973 -0.03 -0.06 -0.03 0.07 0.06 0.025 0.021 -0.014 -0.03 -0.013 -0.003 0.16 -0.007 0.04

1974 -0.04 -0.18 -0.01 0.00 0.15 0.006 0.055 -0.007 0.03 -0.023 0.001 0.05 -0.001 -0.03

1975 -0.04 -0.81 0.06 -0.02 0.08 -0.059 0.130 0.020 0.07 0.014 0.028 0.62 0.016 0.16

1976 0.01 -0.74 0.04 -0.01 0.16 -0.126 0.085 0.019 0.04 0.027 0.024 -0.26 0.018 0.29

1977 0.05 -1.07 0.06 0.01 0.18 0.083 0.114 0.018 0.09 0.025 0.017 -0.07 0.015 0.27

1978 0.04 -1.28 0.08 0.02 0.18 0.115 0.155 0.030 0.09 0.033 0.018 -0.35 0.018 0.20

1979 -0.03 -1.14 0.05 0.00 0.14 -0.140 0.096 0.028 0.03 0.028 0.018 0.24 0.012 0.06

1980 -0.09 -0.81 0.05 0.01 0.14 -0.223 0.074 0.021 0.02 0.012 0.022 0.33 0.007 -0.15

1981 -0.03 -0.33 0.07 0.03 0.14 -0.093 0.079 0.028 0.05 0.027 0.013 0.16 0.017 -0.08

1982 0.03 0.31 0.01 -0.01 0.10 0.064 0.019 0.025 0.02 0.036 0.009 -0.01 0.022 0.04

1983 0.11 0.91 -0.08 0.02 -0.02 0.074 -0.086 -0.003 -0.06 -0.002 -0.005 -0.14 0.011 -0.14

1984 0.13 0.48 -0.03 0.07 -0.07 0.015 -0.061 -0.017 -0.03 -0.012 -0.003 0.12 0.001 -0.21

1985 0.05 -0.48 0.06 0.08 -0.11 -0.067 0.029 -0.003 0.05 -0.012 -0.004 -0.06 -0.004 -0.32

1986 0.02 -0.40 0.05 0.03 -0.03 -0.049 0.047 -0.002 0.03 -0.010 -0.009 -0.13 -0.002 -0.16

1987 -0.02 0.08 -0.01 0.00 0.03 -0.189 -0.015 -0.013 -0.06 -0.015 -0.016 0.08 -0.007 -0.08

1988 -0.03 -0.65 0.05 0.02 -0.06 -0.292 0.019 -0.008 0.00 -0.024 -0.003 0.30 -0.005 -0.17

1989 0.08 -0.75 0.09 0.04 -0.04 -0.137 0.074 0.011 0.05 0.019 0.020 0.08 0.021 0.12

1990 0.11 0.24 0.00 -0.03 -0.02 -0.029 -0.010 0.008 -0.01 0.052 0.014 -0.84 0.030 0.39

1991 0.09 0.48 -0.03 -0.04 -0.05 0.111 -0.046 -0.012 -0.01 0.029 -0.004 -0.05 0.010 0.29

1992 0.09 -0.38 0.05 -0.03 -0.03 0.266 0.064 -0.006 0.11 0.018 0.016 -0.02 0.019 0.14

1993 0.03 -0.38 0.02 -0.04 -0.06 0.163 0.050 -0.003 0.05 0.021 0.031 0.33 0.030 0.16

1994 0.00 0.56 -0.07 -0.03 -0.06 0.132 -0.064 -0.017 -0.05 -0.002 0.003 0.45 0.014 0.03

1995 0.01 0.96 -0.10 -0.04 -0.01 0.122 -0.094 -0.024 -0.07 0.011 -0.001 -1.19 0.017 0.14

1996 0.04 0.68 -0.04 -0.05 -0.05 -0.034 -0.084 -0.014 -0.04 0.032 0.023 0.22 0.028 0.19

1997 0.08 0.09 0.00 -0.03 -0.06 -0.143 -0.068 -0.004 -0.01 0.036 0.030 -0.07 0.038 0.18

1998 0.08 1.12 0.00 -0.03 0.01 -0.105 -0.047 -0.003 0.00 0.060 0.024 0.13 0.042 0.49

1999 0.05 0.29 0.00 -0.04 0.01 -0.056 -0.010 -0.009 0.02 0.052 0.014 0.23 0.028 0.44

2000 0.06 -0.44 0.03 -0.01 -0.03 -0.006 0.039 -0.007 0.06 0.024 0.015 -0.22 0.027 0.16

2001 0.07 0.28 -0.05 0.01 -0.10 -0.133 -0.062 -0.009 -0.07 0.004 0.016 -0.17 0.022 0.05

2002 0.00 0.31 -0.11 0.01 -0.16 -0.214 -0.170 -0.027 -0.14 -0.018 -0.012 -0.20 -0.007 -0.05

2003 -0.03 1.07 0.05 -0.01 -0.05 -0.132 -0.010 0.004 0.05 -0.006 -0.016 0.31 -0.015 -0.12

2004 -0.08 -0.31 0.01 -0.10 0.03 -0.134 0.071 0.035 0.10 0.053 0.016 -0.75 0.013 0.21

n+ 33 26 33 28 24 24 27 28 30 30 26 28 27 27

n- 22 29 17 22 31 31 23 27 21 19 23 24 25 25

n+r 6 10 11 7 8 6 10 7 11 8 8 14 4 9

mean 0.01 -0.02 0.00 0.00 0.01 -0.017 0.007 0.003 0.01 0.007 0.002 0.003 0.002 0.004

sd 0.05 0.70 0.06 0.03 0.09 0.117 0.079 0.019 0.06 0.026 0.017 0.372 0.021 0.208
210

Table 20. Tropical cyclone parametric means and standard deviations based on the yearly 

ENSO phase condition.

Table 20. Tropical cyclone parametric means based on the yearly ENSO phase condition

A. Frequencies

 Condition NTC NTS NH NMH NUSLFH 

 ENY(16) 9.1(3.4) 4.3(1.7) 4.8(2.8) 2.0(1.8) 1.1(1.5)

 LNY(15) 11.7(2.7) 4.7(1.7) 7.0(2.6) 3.5(2.1) 2.2(1.7)

 NY(35) 11.3(4.6) 4.8(2.7) 6.5(2.4) 2.7(1.7) 1.6(1.3)

ONI>0.0(30) 10.6(5.0) 4.6(2.6) 6.0(3.2) 2.7(2.4) 1.5(1.5)

ONI<0.0(31) 11.3(3.0) 4.7(2.1) 6.6(2.1) 3.1(2.0) 1.6(1.5)

B. Other aspects

 Condition <N. LAT> <w. LONG> PWS <PWS> ACE NSD NTCA 

 ENY(16) 23.0(3.8) 64.0(6.4) 119.7(20.8) 70.6(9.1) 85.2(60.1) 44.50(22.82) 86.8(57.0)

 LNY(15) 21.9(3.2) 65.9(6.1) 133.0(17.9) 79.4(9.5) 121.6(62.8) 66.92(40.42) 135.3(63.1)

 NY(35) 21.6(3.2) 64.9(7.0) 124.7(27.2) 74.9(8.2) 104.1(54.9) 56.04(26.54) 114.7(55.8)

ONI>0.0(30) 22.6(3.7) 63.4(6.7) 127.5(22.5) 73.1(8.6) 102.0(67.0) 53.58(30.52) 105.6(65.4)

ONI<0.0(31) 21.9(3.1) 65.1(5.6) 126.0(20.0) 77.1(9.7) 108.6(52.6) 59.51(31.18) 122.2(56.1)
211

Table 21. Poisson probability distributions for North Atlantic basin tropical cyclones 

based on ENSO phase condition.

A. ENY

 NTC NTS NH NMH NUSLFH

 r (m = 9.13) (m = 4.31) (m = 4.81) (m = 2.00) (m = 1.13)

 0 0.0001 0.0134 0.0081 0.1353 0.3230

 1 0.0010 0.0579 0.0392 0.2707 0.3650

 2 0.0045 0.1248 0.0943 0.2707 0.2062

 3 0.0137 0.1793 0.1511 0.1804 0.0777

 4 0.0314 0.1931 0.1817 0.0902 0.0219

 5 0.0573 0.1665 0.1748 0.0361 0.0050

 6 0.0872 0.1196 0.1401 0.0120 0.0009

 7 0.1137 0.0736 0.0963 0.0034 0.0002

 8 0.1298 0.0397 0.0579 0.0009 0.0000

 9 0.1316 0.0190 0.0309 0.0002

10 0.1202 0.0082 0.0149 0.0000

11 0.0998 0.0032 0.0065

12 0.0759 0.0012 0.0026

13 0.0533 0.0004 0.0010

14 0.0348 0.0001 0.0003

15 0.0212 0.0000 0.0001

16 0.0121 0.0000

17 0.0065

18 0.0033

19 0.0016

20 0.0007

21 0.0003

22 0.0001

23 0.0000

B. LNY

 NTC NTS NH NMH NUSLFH

 r (m = 11.67) (m = 4.67) (m = 7.00) (m = 3.47) (m = 2.20)

 0 0.0000 0.0094 0.0009 0.0311 0.1108

 1 0.0001 0.0438 0.0064 0.1080 0.2438

 2 0.0006 0.1022 0.0223 0.1873 0.2681

 3 0.0023 0.1591 0.0521 0.2167 0.1966

 4 0.0066 0.1857 0.0912 0.1880 0.1082

 5 0.0154 0.1735 0.1277 0.1305 0.0476

 6 0.0300 0.1350 0.1490 0.0754 0.0174

 7 0.0500 0.0901 0.1490 0.0374 0.0055

 8 0.0729 0.0526 0.1304 0.0162 0.0015

 9 0.0945 0.0273 0.1014 0.0063 0.0004

10 0.1103 0.0127 0.0710 0.0022 0.0001

11 0.1171 0.0054 0.0452 0.0007 0.0000

12 0.1138 0.0021 0.0263 0.0002

13 0.1022 0.0008 0.0142 0.0001

14 0.0852 0.0003 0.0071 0.0000

15 0.0663 0.0001 0.0033

16 0.0483 0.0000 0.0014

17 0.0332 0.0006

18 0.0215 0.0002

19 0.0132 0.0001

20 0.0077 0.0000

21 0.0043

22 0.0023

23 0.0012

24 0.0006

25 0.0003

26 0.0001

27 0.0000

C. NY

 NTC NTS NH NMH NUSLFH

 r (m = 11.26) (m = 4.77) (m = 6.49) (m = 2.71) (m = 1.63)

 0 0.0000 0.0085 0.0015 0.0665 0.1959

 1 0.0001 0.0405 0.0099 0.1803 0.3194

2 0.0008 0.0965 0.0320 0.2443 0.2603
212

13 0.0967 0.0009 0.0088

14 0.0778 0.0003 0.0041

15 0.0584 0.0001 0.0018

16 0.0411 0.0000 0.0007

17 0.0272 0.0003

18 0.0170 0.0001

19 0.0101 0.0000

20 0.0057

21 0.0030

22 0.0016

23 0.0008

24 0.0004

25 0.0002

26 0.0001

27 0.0000

Table 21. Poisson probability distributions for North Atlantic basin tropical cyclones 

based on ENSO phase condition (Continued).

18 0.0215 0.0002

19 0.0132 0.0001

20 0.0077 0.0000

21 0.0043

22 0.0023

23 0.0012

24 0.0006

25 0.0003

26 0.0001

27 0.0000

C. NY

 NTC NTS NH NMH NUSLFH

 r (m = 11.26) (m = 4.77) (m = 6.49) (m = 2.71) (m = 1.63)

 0 0.0000 0.0085 0.0015 0.0665 0.1959

 1 0.0001 0.0405 0.0099 0.1803 0.3194

 2 0.0008 0.0965 0.0320 0.2443 0.2603

 3 0.0031 0.1534 0.0692 0.2207 0.1414

 4 0.0086 0.1829 0.1123 0.1495 0.0576

 5 0.0194 0.1745 0.1457 0.0810 0.0188

 6 0.0365 0.1387 0.1576 0.0366 0.0051

 7 0.0586 0.0945 0.1461 0.0142 0.0012

 8 0.0825 0.0564 0.1185 0.0048 0.0002

 9 0.1033 0.0299 0.0855 0.0014 0.0000

10 0.1163 0.0143 0.0555 0.0004

11 0.1190 0.0062 0.0327 0.0001

12 0.1117 0.0025 0.0177 0.0000
213

Table 22. Comparison of surface air temperature and ENSO-related parametric values 

for different ENSO phase conditions. Table 22. Comparison of surface-air temperature and ENSO-related parametric 

values for different ENSO phase conditions

Parameter ENY(16) LNY(15) NY(35) <ONI> >0.0(30) <ONI> <0.0(31)

<AT> 9.42(0.65) 9.40(0.43) 9.55(0.51) 9.49(0.60) 9.44(0.45)

<ONI> 0.66(0.33) -0.73(0.37) -0.01(0.39)* 0.52(0.32) -0.52(0.36)

<SOI> -6.36(4.44) 7.88(4.51) -0.66(5.05) -5.71(3.94) 5.49(4.48)

<NAO> 0.08(0.34) -0.15(0.35) -0.02(0.39)* 0.02(0.36) -0.07(0.38)

<PDO> 0.10(0.80) -0.72(0.80) 0.01(0.75) 0.29(0.74) -0.49(0.75)

<TNI> -0.338(1.205) 0.337(1.060) -0.349(1.081) -0.374(1.380) -0.025(0.878)

<MEI> 0.677(0.453) -0.806(0.599) 0.121(0.584)* 0.671(0.429) -0.573(0.465)

<GSSTEI> 0.197(0.126) -0.067(0.200) 0.056(0.130) 0.188(0.110) -0.047(0.146)

<JMASSTM> 26.34(0.41) 24.95(0.41) 25.57(0.39)# 26.15(0.43) 25.13(0.32)

<NTA> 0.071(0.292) 0.003(0.382)$ 0.087(0.218)* 0.138(0.275) -0.011(0.270)$

<CAR> 0.066(0.120) -0.050(0.195)$ 0.054(0.150)* 0.092(0.137) -0.027(0.158)$

<QBO> -2.00(7.06) -0.67(8.86) -5.51(7.75)% -3.06(7.74) -3.97(8.41)

<AMO> -0.011(0.182) -0.036(0.242) 0.019(0.172)% 0.019(0.192) -0.026(0.196)

<AMM> -0.64(2.10) 0.104(2.35) 0.52(1.56)% 0.08(2.14) 0.17(1.83)

* means no data for 1945-1949

# means no data for 1945-1948

$ means no data for 1950

% means no data for 1945-1947
214

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages.
215

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages (Continued).
216

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages (Continued).
217

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages (Continued).
218

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages (Continued).
219

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages (Continued).
220

Table 23. Poisson probability distributions for North Atlantic basin tropical cyclones based on 

yearly parametric values being either above (+) or below (–) long-term parametric 

averages (Continued).
221

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value.
222

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
223

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
224

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
225

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
226

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
227

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
228

Table 24. Inferred linear regression equations using 10-yma parametric values for the intervals 

1950–2005 and 1990–2005, arranged by r value (Continued).
229

Table 25. Lising of North Atlantic basin tropical cyclones for the year 2011 Table 25. Listing of North Atlantic basin tropical cyclones for the year 2011.

 Genesis Location

Year SNBR Name Class. FSD LSD N. Lat W. Long. Group PWS LP ACE NSD NHD NMHD USLFH

2011 1447 Arlene TS 06/28 06/30 20.7 93.5 1 55 993 1.9 2.25 - -

 1448 Bret TS 07/18 07/21 27.5 78.1 3 60 995 3.3 4.00 - -

 1449 Cindy TS 07/20 07/22 33.4 57.0 5 60 994 2.3 2.50 - -

 1450 Don TS 07/27 07/30 22.0 86.7 1 45 997 1.6 2.50 - -

 1451 Emily TS 08/02 08/07 14.9 61.4 2 45 1003 2.3 3.25 - -

 1452 Franklin TS 08/13 08/13 37.6 61.1 3 40 1004 0.3 0.50 - -

 1453 Gert TS 08/14 08/16 27.7 62.3 3 55 1000 1.9 2.25 - -

 1454 Harvey TS 08/19 08/22 15.9 83.4 2 55 994 1.5 2.00 - -

 1455 Irene MH 08/21 08/28 15.0 59.0 4 105 942 18.8 8.00 6.25 0.50 NC1

 1456 Jose TS 08/27 08/28 27.9 63.4 3 40 1006 0.8 1.50 - -

 1457 Katia MH 08/30 09/10 11.0 29.6 4 120 942 27.0 11.50 9.50 1.25

 1458 Unnamed TS 09/01 09/02 37.4 63.7 3 40 1002 0.8 1.50 - -

 1459 Lee TS 09/02 09/05 27.2 91.4 1 50 986 1.8 2.75 - -

 1460 Maria H 09/07 09/16 11.9 37.5 4 70 983 9.2 9.00 1.00 -

 1461 Nate H 09/07 09/11 20.3 92.9 1 65 994 4.4 4.50 0.50 -

 1462 Ophelia MH 09/21 10/03 12.5 39.7 4 120 940 18.7 9.75 3.50 2.00

 1463 Philippe H 09/24 10/08 11.1 26.1 4 80 976 15.9 13.75 2.50 -

 1464 Rina MH 10/24 10/28 16.0 81.9 2 100 966 10.1 4.75 2.75 0.75

 1465 Sean TS 11/08 11/11 27.7 69.8 3 55 982 3.7 3.75 - - 

Summary: NTC = 19, NTS = 12, NH = 7, NMH = 4, NUSLFH = 1, PWS = 120, <PWS> = 66.3, LP = 940, <LP> = 984.2,

 <N. Lat.> = 22.0, <W. Long.> = 65.2, <ACE> = 6.6, Sum ACE = 126.3, <NSD> = 4.74, Sum NSD = 90.00,

 Sum NHD = 26.00, Sum NMHD = 4.50, NTCA = 145.0%, ACE/NSD = 1.39, HISACE = 27.0, LISNSD = 13.75
230

Table 26. The 34 strongest tropical cyclones, ranked by PWS (135–165 kt) from earliest to latest. Table 26. The 34 strongest tropical cyclones, ranked by PWS (135-165 kt) from earliest to latest

Storm Name PWS LP ISACE ISNSD Group Onset Mo

Camille 1969* 165 905 23.5 6.00 1 AUG

Allen 1980* 165 899 51.0 9.50 4 AUG

Dog 1950 160 - 62.6 12.50 4 AUG

Gilbert 1988 160 888 32.8 8.00 2 SEP

Wilma 2005* 160 882 38.9 8.75 2 OCT

Mitch 1998 155 905 35.9 10.75 2 OCT

Rita 2005* 155 897 25.1 6.50 3 SEP

Janet 1955 150 914 38.1 8.75 4 SEP

Carla 1961* 150 931 30.0 8.00 2 SEP

Anita 1977 150 926 12.8 4.00 1 AUG

David 1979* 150 924 44.0 11.50 4 AUG

Andrew 1992* 150 922 26.5 9.75 4 AUG

Katrina 2005* 150 902 20.0 6.00 3 AUG

Dean 2007 150 907 35.2 8.50 4 AUG

Felix 2007 150 930 18.0 4.25 4 SEP

Isabel 2003* 145 915 63.3 13.25 4 SEP

Ivan 2004* 145 910 70.4 14.75 4 SEP

Unnamed 1947* 140 947 62.6 16.25 4 SEP

Easy 1951 140 - 37.1 9.75 4 SEP

Cleo 1958 140 948 32.0 9.00 4 AUG

Donna 1960* 140 932 64.6 13.75 4 AUG

Ethel 1960* 140 981 5.3 2.25 1 SEP

Hattie 1961 140 920 21.7 5.00 2 OCT

Beulah 1967* 140 923 47.9 15.00 2 SEP

Edith 1971* 140 943 16.4 9.75 2 SEP

Hugo 1989* 140 918 42.7 11.25 4 SEP

Emily 2005 140 929 32.9 9.25 4 JUL

Carrie 1957 135 945 62.6 19.50 4 SEP

Cleo 1964* 135 950 37.7 13.25 4 AUG

Betsy 1965* 135 941 47.0 12.75 2 AUG

Georges 1998* 135 937 39.4 13.00 4 SEP

Floyd 1999* 135 921 29.4 9.25 4 SEP

Lenny 1999 135 933 19.9 6.75 2 NOV

Igor 2010 135 924 41.9 12.25 4 SEP

* means USLFH
231

Table 27. Frequency distribution of PWS. Table 27. Frequency distribution of PWS

Year 35-44 45-54 55-64 65-74 75-84 85-94 95-104 105-114 115-124 125-134 135-144 145-154 155-164 165+ Total Comment

1945 1 4 1 2 1 2 11

1946 3 1 1 1 6

1947 2 2 1 1 1 1 1 9 Unnamed

1948 1 2 2 2 2 9

1949 2 4 1 2 1 1 1 1 13

1950 1 1 1 3 4 2 1 13 Dog

1951 2 2 4 1 1 10 Easy

1952 1 1 1 1 2 1 7

1953 2 2 4 1 2 2 1 14

1954 1 1 1 3 3 1 1 11

1955 1 2 1 2 1 3 1 1 12 Janet

1956 2 2 1 1 1 1 8

1957 1 2 2 1 1 1 8 Carrie

1958 2 1 2 1 1 2 1 10 Cleo

1959 3 1 4 1 1 1 11

1960 2 1 1 1 2 7 Donna, Ethel

1961 1 2 1 1 2 1 1 1 1 11 Carla, Hattie

1962 1 1 1 2 5

1963 2 2 2 1 1 1 9

1964 2 3 1 1 1 1 2 1 12 Cleo

1965 2 1 1 1 1 6 Betsy

1966 4 3 1 2 1 11

1967 2 4 1 1 8 Beulah

1968 1 2 4 1 8

1969 1 2 3 2 3 2 2 2 1 18 Camille

1970 1 4 2 1 2 10

1971 1 6 1 3 1 1 13 Edith

1972 1 3 1 1 1 7

1973 1 3 1 2 1 8

1974 4 3 1 2 1 11

1975 1 2 1 1 2 1 1 9

1976 2 2 1 1 2 1 1 10

1977 1 3 1 1 6 Anita 

1978 1 5 1 1 1 1 2 12

1979 1 2 2 1 1 1 1 9 David

1980 1 1 3 1 3 1 1 11 Allen

1981 3 2 1 2 1 1 1 1 12

1982 4 1 1 6

1983 1 2 1 4

1984 1 5 2 2 1 1 1 13

1985 1 3 1 3 2 1 11

1986 2 1 2 1 6

1987 1 3 2 1 7

1988 2 3 2 2 2 1 12 Gilbert

1989 3 1 1 2 2 1 1 11 Hugo

1990 2 1 3 3 3 1 1 14

1991 1 3 1 1 1 1 8

1992 1 2 1 2 1 7 Andrew

1993 2 2 2 1 1 8

1994 2 2 1 1 1 7

1995 2 2 4 2 2 4 2 1 19

1996 2 1 1 3 3 1 1 1 13

1997 4 1 2 1 8

1998 1 1 2 1 2 4 1 1 1 14 Georges,

 Mitch

1999 1 3 2 1 1 2 2 12 Floyd, Lenny

2000 3 2 2 2 2 1 1 2 15

2001 1 2 3 3 1 1 1 1 1 1 15

2002 2 5 1 1 1 1 1 12

2003 2 3 4 2 1 1 1 1 1 16 Isabel

2004 1 4 1 2 1 2 3 1 15 Ivan

2005 3 5 5 4 3 1 2 1 1 1 2 28 Emily,

 Katrina, 

 Rita, Wilma

2006 3 2 1 2 2 10

2007 4 5 3 1 2 15 Dean, Felix

2008 2 1 5 2 1 1 1 3 16

2009 1 4 1 1 1 1 9

2010 3 2 2 1 2 4 1 2 1 1 19 Igor

Total 68 136 104 88 68 54 49 51 33 30 17 10 5 2 715
232

Table 28. Frequency distribution of ISACE. Table 28. Frequency distribution of ISACE

Year 0.1-9.9 10.0-19.9 20.0-29.9 30.0-39.9 40.0-49.9 50.0-59.9 60.0-69.9 70.0+ Total Comment

1945 9 1 1 11

1946 6 6

1947 5 3 1 9 Unnamed

1948 5 2 1 1 9

1949 9 3 1 13

1950 4 5 2 1 1 13 Dog

1951 4 4 1 1 10

1952 3 3 1 7

1953 11 2 1 14

1954 7 3 1 11 Hazel

1955 5 2 3 1 1 12 Connie

1956 6 1 1 8

1957 7 1 8 Carrie

1958 4 5 1 10

1959 9 1 1 11

1960 6 1 7 Donna

1961 4 1 3 2 1 11 Esther

1962 3 2 5

1963 5 2 1 1 9 Flora

1964 7 1 1 3 12

1965 4 1 1 6 Betsy

1966 7 2 1 1 11 Faith, 

Inez

1967 4 2 1 1 8 Beulah

1968 7 1 8

1969 13 2 2 1 18

1970 10 10

1971 11 1 1 13 Ginger

1972 6 1 7

1973 7 1 8

1974 9 1 1 11

1975 5 4 9

1976 7 2 1 10

1977 5 1 6

1978 9 3 12

1979 6 1 1 1 9 David

1980 8 1 1 1 11 Allen

1981 7 4 1 12

1982 5 1 6

1983 4 4

1984 9 4 13

1985 8 2 1 11

1986 5 1 6

1987 5 2 7

1988 9 1 2 12

1989 7 2 1 1 11 Hugo

1990 11 2 1 14

1991 7 1 8

1992 4 1 2 7

1993 7 1 8

1994 6 1 7

1995 11 3 4 1 19 Luis

1996 7 2 3 1 13 Edouard

1997 7 1 8

1998 9 1 2 2 14

1999 4 4 3 1 12 Gert

2000 12 1 1 1 15

2001 10 4 1 15

2002 9 3 12

2003 13 1 1 1 16 Fabian, 

Isabel

2004 7 4 2 1 1 15 

Frances, Ivan

2005 19 5 2 2 28

2006 8 2 10

2007 13 1 1 15

2008 12 2 1 1 16

2009 8 1 9

2010 14 2 2 1 19 Igor

Total 494 115 58 24 14 4 5 1 715
233

Table 29. Frequency distribution of ISNSD. Table 29. Frequency distribution of ISNSD

Year 0.1-1.0 1.1-2.0 2.1-3.0 3.1-4.0 4.1-5.0 5.1-6.0 6.1-7.0 7.1-8.0 8.1-9.0 9.1-10.0 10.1+ Total Comment

1945 1 5 2 1 1 1 11

1946 1 1 4 6

1947 1 1 1 2 3 1 9 Unnamed

1948 2 1 1 2 1 2 9 Unnamed, unnamed

1949 2 2 2 1 1 4 1 13

1950 2 1 2 2 1 1 2 2 13 Charlie, Dog

1951 1 1 2 2 2 1 1 10

1952 1 2 2 1 1 7

1953 1 2 5 3 1 1 1 14 Alice

1954 3 1 1 1 2 1 1 1 11 Hazel

1955 1 1 1 1 1 1 1 2 3 12 Connie, Diane, Ione

1956 3 1 1 1 1 1 8

1957 3 2 1 1 1 8 Carrie

1958 2 1 2 3 1 1 10

1959 2 2 3 1 1 1 1 11 Hannah

1960 1 2 1 1 1 1 7 Donna

1961 2 1 1 2 1 1 1 2 11 Debbie, Esther

1962 1 2 1 1 5

1963 1 1 2 1 1 1 2 9 Flora, Ginny

1964 1 2 2 1 2 4 12 Cleo, Dora, Ethel, 

 Gladys

1965 2 2 2 6 Betsy, Carol

1966 1 3 1 1 1 2 2 11 Faith, Inez

1967 2 1 1 1 3 8 Beulah, Chloe, Heidi

1968 1 1 2 2 1 1 8

1969 1 4 1 2 2 4 1 1 2 18 Debbie, Inga

1970 1 3 2 2 1 1 10

1971 6 3 1 1 1 1 13 Ginger

1972 2 1 1 1 1 1 7

1973 1 3 1 1 1 1 8

1974 1 1 3 1 3 1 1 11

1975 1 3 1 1 1 2 9

1976 2 2 1 1 1 2 1 10 Emmy

1977 1 1 2 2 6

1978 2 2 2 2 1 1 1 1 12

1979 4 1 1 1 2 9 David, Frederic

1980 1 1 1 2 3 1 1 1 11 Frances

1981 1 2 1 1 1 2 1 2 1 12 Emily

1982 3 1 1 1 6

1983 2 2 4

1984 3 1 2 1 1 1 1 1 2 13 Josephine, Lili

1985 1 4 1 3 1 1 11

1986 1 3 1 1 6

1987 1 3 1 1 1 7 Arlene

1988 3 3 2 1 1 2 12 Helene, Joan

1989 2 2 1 1 1 1 1 2 11 Gabrielle, Hugo

1990 1 1 2 2 2 2 1 1 1 1 14 Isidore

1991 3 2 2 1 8

1992 1 3 1 1 1 7 Bonnie

1993 1 1 3 1 1 1 8 Emily

1994 1 3 1 1 1 7

1995 1 2 3 1 2 2 1 4 3 19 Felix, Iris, Luis

1996 1 2 2 1 2 2 3 13 Edouard, Fran, Lili

1997 3 3 1 1 8 Erika

1998 2 2 1 2 1 1 1 4 14 Bonnie, Danielle, 

 Georges, Mitch

1999 1 1 1 2 1 1 1 1 3 12 Cindy, Dennis, Gert

2000 1 3 2 3 1 2 1 1 1 15 Alberto

2001 3 3 2 2 2 1 1 1 15 Erin

2002 1 3 3 1 1 1 1 1 12 Kyle

2003 2 1 4 2 2 2 3 16 Fabian, Isabel, Kate

2004 4 1 2 2 1 1 4 15 Frances, Ivan, Jeanne,

 Lisa

2005 6 3 3 1 1 5 2 2 2 2 1 28 Ophelia

2006 1 2 2 1 2 1 1 10 Helene

2007 5 3 3 1 1 1 1 15

2008 1 3 5 2 1 1 1 2 16 Bertha, Ike

2009 1 4 1 2 1 9

2010 2 4 3 4 1 1 2 2 19 Earl, Igor

Total 52 125 110 86 73 54 43 35 33 28 76 715
234

Table 30. Frequency distribution of ISNHD. Table 30. Frequency distribution of ISNHD

Year 0.0 0.1-1.0 1.1-2.0 2.1-3.0 3.1-4.0 4.1-5.0 5.1-6.0 6.1-7.0 7.1-8.0 8.1-9.0 9.1-10.0 10.1+ Total Comment

1945 6 3 1 1 11

1946 3 2 1 6

1947 4 1 1 2 1 9 unnamed

1948 3 1 1 1 2 1 9 unnamed

1949 6 2 3 1 1 13

1950 2 1 2 2 2 1 2 1 13 Dog

1951 2 1 1 1 1 2 1 1 10

1952 1 2 1 2 1 7

1953 8 1 2 2 1 14

1954 3 2 1 1 3 1 11

1955 3 1 1 3 2 2 12

1956 4 1 1 1 1 8

1957 5 1 1 1 8 Carrie

1958 3 2 3 1 1 10

1959 4 3 2 1 1 11

1960 3 1 1 1 1 7 Donna

1961 3 1 2 1 1 1 2 11

1962 2 1 2 5

1963 2 2 2 1 1 1 9 Flora

1964 6 1 1 2 1 1 12 Gladys

1965 2 2 2 6 Betsy, Carol

1966 4 1 1 2 1 2 11 Faith, Inez

1967 2 1 1 1 1 2 8 Beulah, Chloe

1968 3 1 2 1 1 8

1969 6 2 3 3 2 1 1 18 Inga

1970 5 2 2 1 10

1971 7 1 3 1 1 13 Ginger

1972 4 2 1 7

1973 4 1 2 1 8

1974 7 1 1 1 1 11

1975 3 3 2 1 9

1976 4 1 2 1 1 1 10

1977 1 3 1 1 6

1978 7 2 1 1 1 12

1979 3 3 1 1 1 9

1980 2 1 2 2 1 1 1 1 11 Frances

1981 5 2 2 1 1 1 12

1982 4 1 1 6

1983 1 1 2 4

1984 8 1 1 1 1 1 13

1985 4 2 2 1 1 1 11

1986 2 2 1 1 6

1987 4 1 2 7

1988 7 2 1 1 1 12

1989 4 2 1 1 1 1 1 11

1990 6 2 1 2 1 1 1 14

1991 4 1 1 1 1 8

1992 3 1 1 1 1 7

1993 4 2 1 1 8

1994 4 1 1 1 7

1995 8 1 4 1 2 1 1 1 19 Luis

1996 4 3 1 1 1 1 1 1 13 Edouard

1997 5 1 1 1 8

1998 4 2 1 1 1 1 2 1 1 14 Georges

1999 4 2 1 1 2 1 1 12

2000 7 1 4 1 1 1 15 Alberto

2001 6 3 2 2 1 1 15

2002 8 1 1 2 12

2003 9 3 1 1 1 1 16 Isabel

2004 6 2 1 2 2 2 15 Frances, Ivan

2005 13 3 2 2 3 3 1 1 28

2006 5 1 1 1 1 1 10

2007 9 4 1 1 15

2008 8 1 2 2 1 1 1 16

2009 6 2 1 9

2010 7 2 4 2 1 1 1 1 19

Total 306 80 70 59 47 35 27 20 22 12 14 23 715
235

Table 31. Frequency distribution of ISNMHD. Table 31. Frequency distribution of ISNMHD

Year 0.0 0.1-1.0 1.1-2.0 2.1-3.0 3.1-4.0 4.1-5.0 5.1-6.0 6.1-7.0 7.1-8.0 8.1-9.0 9.1-10.0 Total Comment

1945 8 1 1 1 11

1946 5 1 6

1947 7 1 1 9

1948 5 1 2 1 9

1949 10 1 1 1 13

1950 5 4 1 1 1 1 13

1951 5 3 1 1 10

1952 4 2 1 7

1953 10 2 1 1 14

1954 9 1 1 11

1955 6 1 2 1 1 1 12

1956 6 2 8

1957 6 1 1 8

1958 5 1 3 1 10

1959 9 1 1 11

1960 5 1 1 7 Donna

1961 4 2 2 1 1 1 11

1962 4 1 5

1963 7 1 1 9

1964 6 1 1 2 2 12

1965 5 1 6

1966 8 1 1 1 11

1967 7 1 8

1968 8 8

1969 13 3 1 1 18

1970 8 2 10

1971 12 1 13

1972 7 7

1973 7 1 8

1974 9 1 1 11

1975 6 2 1 9

1976 8 2 10

1977 5 1 6

1978 10 1 1 12

1979 7 1 1 9

1980 9 1 1 11

1981 9 1 2 12

1982 5 1 6

1983 3 1 4

1984 12 1 13

1985 8 1 2 11

1986 6 6

1987 6 1 7

1988 9 1 1 1 12

1989 9 1 1 11

1990 13 1 14

1991 6 2 8

1992 6 1 7

1993 7 1 8

1994 7 7

1995 14 3 1 1 19

1996 7 3 2 1 13

1997 7 1 8

1998 11 1 2 14

1999 7 3 1 1 12

2000 12 1 1 1 15

2001 11 3 1 15

2002 10 2 12

2003 13 1 2 16

2004 9 3 1 1 1 15 Ivan

2005 21 2 2 1 2 28

2006 8 1 1 10

2007 13 1 1 15

2008 11 3 1 1 16

2009 7 1 1 9

2010 14 2 1 1 1 19

Total 536 67 45 21 17 9 5 7 5 1 2 715
236

Table 32. Frequency distribution of onset location N. LAT. Table 32. Frequency distribution of Onset Location N. LAT

Year 5.0-9.9 10.0-14.9 15.0-19.9 20.0-24.9 25.0-29.9 30.0-34.9 35.0-39.9 40.0+ Total Comment

1945 2 7 1 1 11

1946 1 3 2 6

1947 2 4 2 1 9

1948 2 4 2 1 9

1949 2 6 3 2 13

1950 1 6 4 2 13

1951 4 2 1 2 1 10

1952 1 5 1 7

1953 3 3 8 14

1954 2 1 5 2 1 11

1955 2 7 1 2 12

1956 1 5 2 8

1957 1 4 3 8

1958 3 3 3 1 10

1959 1 4 4 2 11

1960 2 4 1 7

1961 4 3 1 1 2 11

1962 2 1 1 1 5

1963 3 3 1 2 9

1964 3 2 3 1 3 12

1965 1 1 2 1 1 6

1966 3 3 3 1 1 11

1967 2 1 4 1 8

1968 2 1 1 3 1 8

1969 5 2 2 4 3 2 18

1970 1 1 4 2 1 1 10

1971 4 1 4 2 1 1 13 Unnamed

1972 1 1 3 2 7

1973 2 1 2 1 1 1 8

1974 2 2 1 1 3 2 11

1975 1 1 2 4 1 9 ST2

1976 1 1 1 5 2 10

1977 1 2 2 1 6

1978 3 1 3 3 1 1 12

1979 3 1 3 1 1 9

1980 3 2 1 1 2 2 11

1981 2 5 2 1 2 12

1982 1 2 3 6

1983 3 1 4

1984 3 1 3 2 2 2 13

1985 1 1 4 2 2 1 11

1986 1 2 2 1 6

1987 2 2 1 2 7

1988 5 1 2 2 1 1 12 Alberto

1989 3 4 2 2 11

1990 1 4 4 2 1 2 14

1991 1 1 4 2 8

1992 1 1 2 3 7

1993 3 1 3 1 8

1994 4 2 1 7

1995 6 5 4 3 1 19

1996 7 4 1 1 13

1997 1 1 2 4 8

1998 6 2 2 3 1 14

1999 5 4 1 2 12

2000 4 3 4 2 2 15

2001 4 3 6 2 15

2002 1 1 1 3 5 1 12

2003 4 2 4 4 2 16

2004 1 6 1 2 1 4 15

2005 5 5 7 7 3 1 28

2006 3 2 2 1 1 1 10 Unnamed

2007 5 2 2 2 2 2 15

2008 4 7 2 1 1 1 16

2009 4 2 1 1 1 9

2010 1 9 4 4 1 19

Total 4 175 146 144 128 82 32 4 715
237

Table 33. Frequency distribution of onset location W. LONG. Table 33. Frequency distribution of Onset Location W. LONG

Year 10.0-19.9 20.0-29.9 30.0-39.9 40.0-49.9 50.0-59.9 60.0-69.9 70.0-79.9 80.0-89.9 90.0-99.9 Total

1945 3 1 1 4 2 11

1946 3 2 1 6

1947 1 1 3 3 1 9

1948 1 2 1 2 1 2 9

1949 1 2 1 4 1 3 1 13

1950 1 3 4 4 1 13

1951 1 1 1 2 2 2 1 10

1952 4 1 2 7

1953 2 1 2 2 3 3 1 14

1954 2 2 2 2 3 11

1955 2 2 3 1 1 2 1 12

1956 1 3 1 3 8

1957 1 2 3 2 8

1958 1 2 2 2 1 1 1 10

1959 1 2 3 3 2 11

1960 1 2 1 1 2 7

1961 1 1 2 1 1 2 2 1 11

1962 1 1 1 2 5

1963 2 5 1 1 9

1964 1 1 3 1 1 1 3 1 12

1965 1 2 1 1 1 6

1966 1 2 5 1 1 1 11

1967 1 1 1 1 2 1 1 8

1968 1 2 2 2 1 8

1969 2 3 2 6 5 18

1970 1 1 1 2 5 10

1971 1 2 3 5 1 1 13

1972 1 2 3 1 7

1973 1 1 2 2 2 8

1974 2 3 5 1 11

1975 1 3 1 3 1 9

1976 2 3 1 1 3 10

1977 2 1 3 6

1978 1 3 1 3 1 3 12

1979 2 1 1 2 3 9

1980 3 1 2 2 2 1 11

1981 1 2 1 5 1 2 12

1982 1 1 1 2 1 6

1983 1 2 1 4

1984 1 1 3 4 3 1 13

1985 1 3 3 3 1 11

1986 2 1 2 1 6

1987 2 1 1 1 1 1 7

1988 1 1 1 2 2 3 2 12

1989 3 1 2 1 1 3 11

1990 1 3 3 3 1 1 2 14

1991 1 2 1 3 1 8

1992 1 1 1 2 2 7

1993 1 1 1 3 1 1 8

1994 1 2 1 3 7

1995 1 3 2 4 1 3 3 2 19

1996 1 3 1 1 1 1 4 1 13

1997 1 3 3 1 8

1998 1 1 4 1 1 1 1 4 14

1999 1 1 1 3 2 3 1 12

2000 2 1 2 2 4 3 1 15

2001 1 2 3 5 3 1 15

2002 1 3 5 2 1 12

2003 3 2 1 3 2 2 3 16

2004 1 4 1 1 4 2 1 1 15

2005 2 1 5 2 5 6 3 4 28

2006 1 1 1 3 2 1 1 10

2007 1 2 2 1 2 3 1 3 15

2008 2 2 1 1 4 1 4 1 16

2009 2 2 2 1 2 9

2010 3 3 2 1 2 2 5 1 19

Total 4 41 62 80 102 106 120 124 76 715
238

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Standard Form 298 (Rev. 8-98)

Prescribed by ANSI Std. Z39-18

Statistical Aspects of Tropical Cyclone Activity 

in the North Atlantic Basin, 1945–2010

Robert M. Wilson

George C. Marshall Space Flight Center

Huntsville, AL 35812

National Aeronautics and Space Administration

Washington, DC 20546–0001

Unclassified-Unlimited

Subject Category 47

Availability: NASA CASI (443–757–5802)

Prepared by the Science & Research Office, Science & Technology Office

M–1341

Technical Publication

NASA/TP—2012–217465

tropical cyclones, hurricanes, ENSO, climatic change, multidecadal variation, Armagh Observatory, forecasts, ONI, SOI, PDO, 

MEI, NAO, GSSTEI, JMASSTM, AMO, AMM, NTA, TNI, CAR, QBO, surface air temperature, SST, ACE

01–08–2012

UU 272

NASA

U U U

Examined are statistical aspects of the 715 tropical cyclones that formed in the North Atlantic basin during the 

interval 1945–2010. These 715 tropical cyclones include 306 storms that attained only tropical storm strength, 409 

hurricanes, 179 major or intense hurricanes, and 108 storms that struck the US coastline as hurricanes. Comparisons 

made using 10-yma values between tropical cyclone parametric values and surface air and ENSO-related parametric 

values indicate strong correlations to exist, in particular, against the Armagh Observatory (Northern Ireland) surface 

air temperature, the AMO index, the AMM index, and the NAO index, in addition to the ONI and QBO indices. 

Also examined are the decadal variations of the tropical cyclone parametric values and a look ahead towards the 

2012 hurricane season and beyond.

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