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No 

E 

POTENTIAL IMPACT OF REMOTE SENSING DATA ON SEA-STATE

ANALYSIS AND PREDICTION

Vincent J. Cardone

%.;eanweather Inc.

1: River Road

cos Cob, Conn. 06807

MAR1a94

RE^^IV E^

December, 1983

Final. ?deport

Prepared for

GODDARD SPACE FLIGHT CENTER

Greenbelt, Maryland 20771

(E84-10083) ,POTENTIAL .IMPACT OF REMOTE N84-19954

SENSING DATA ON SEA-STATE k VALYSIS AND

- PREDICTIUN final Report, 1 Mar. 1982 31

Dec. 1983 (Ocean Weather, Inc.) 105 P Unclas

HC A06/MF A01 CSCL 08C G3143 00083

N 
TECHNICAL REPORT STANDARD TITLE PAGE

. Report me. 2. Gevernto•M Accession Me. , 3, Recipient's Catalog Me.

blank ^^^

11 a an 3 u1iti I10 3. 

Report Veto

POTENTIAL IMPACT OF REMOTE SENSING DATA ON DECEMBER 1983

6. Perlorminp Organisa t ion Cede SEA-STATE ANALYSIS AND PREDICTION

blank

7. Author(%) {. performfnt Orgenisation RoPerf No.

Vincent J. Cardone

9. Performing Orgonisotion Herne ens Address 10, Work Unit Ne.

OCEANWEATHER INC. }dank

SUITE 1 11, Contract or Grant Me.

5 RIVER ROAD NAS5-26890

S COB CT 06$07 13. Type of Report and Period Covered

FINAL ,REPORT

12, Sporsotinq Agency Norse and Address

Goddard Space Flight Center 1 MAR 82 - 31 DEC 83

Greenbelt Road 1 4. Sponsoring Agency Code

rennbelt MD 20771 Iblank

15. Supplementory Notes

16, Abstract

A case study of the severe North Atlantic storm of September 9-

11, 1978 which damaged the ocean liner Queen Elizabeth 2 (QE2) is

performed to assess the impact of remotely sensed marines surface wind

data obtained by Seasat-A, on sea state specifications and forecasts.

Alternate representations of the surface wind field in the QE2 storm

were produced from the Seasat enhanced data base, and from operational

analyses based upon conventional data. The wind fields were used to

drive a high resolution spectral ocean surface wave prediction model.

It is demonstrated that sea-state analyses would have been vastly

improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. It is

also shown in this study tha-_ a modest improvement in operational

12-2u hour wave forecasts T,,ould have followed automatically from the

improved initial state specification made possible by the remote

sensing data in both numerical and sea state prediction models, but

that significantly improved 24-48 hour wave forecasts will require

in addition to remote sensing data, vefinement in the numerical and

physical as ects of weather prediction models.

17. Key Words (S. tected by Author( *)) Is. Distribution Statement

Ocean surface wave prediction blank

Seasat-A marine wind

explosive cyclogenesis

19. Security Clqssif, (of this report) 20. Security Clossif. (of this page) V. No. or Pages 22. Price•

105

__

For sale by the Clearinghouse for Federal Scientific and Technical Information, Springfield, Virginia 22151.

Figure 2. Technical Report Stcndard Title Page

"Made available under NASA sponsorshie

in the lot^rest of early and wide dis- K

semination of Earth Resources Survey

' program information and without liability

for any use made thereof."
iii

PREFACE

The primary objective of this study is to demonstrate that remotely

sensed marine surface wind and wave data can improve the operational analysis and prediction of surface winds and waves in intense marine extratropical cyclones. This objective was achieved through a case study of

the severe North Atlantic storm of September 9-11, 1978 which damaged

the ocean liner Queen Elizabeth 2 (QE2), and in which remotely sensed marine surface wind data were obtained by Seasat-A.

Alternate representations of the surface wind field in the QE2 storm

were produced in order to compare the specifications possible from the

Seasat enhanced data base with wind fields derived from operational analyses based upon conventional data. The operational analyses were found

to be very poor in the QE2 storm despite the fact that the storm formed

and moved through the active North Atlantic shipping lanes.

Detailed man-machine mix techniques were applied, to provide the most

accurate: surface wind fields possible from combined conventional and Seasat

data. The wind fields were used to drive a high resolution spectral ocean

surface wave prediction model. The model derived wave hindcasts provided

a basis for quantifying the errors in operationally produced wave analyses

and forecasts in the storm. It is demonstrated that sea-state analyses

would have been vastly improved during the period of storm formation and

explosive development had the remote sensing data been available in real

time. It is also shown in this study that a modest improvement in operational 12-24 hour wave forecasts would have followed automatically from the

improved initial state specification made possible by the remote sensing

data in both numerical and sea state prediction models, but that signifi.-

cantly improved 24-48 hour wave forecasts will require in addition to

remote sensing data, refinement in -the numerical and physical aspects of

weather prediction models.

This study also included an evaluation of the wave model used against

directional wave measurements made by an experimental airborne scanning

radar altimeter in a .separate intense North Atlantic cyclone. The model

validation confirmed the high accuracy of wave height specifications shown

1 *f

w
a iv

previously for the wave model but also revealed deficiencies in the treatment of directional processes. The high resolution directional wave measurements made by the scanning radar altimeter provide a basis for development

of improved empirically based treatments of directional wave processes and

should guide the development of improved theory. On an operational satellite 

the system would provide data which could directly update the sea state

directional spectrum representation carried in operational wave prediction

models. Improvements in the initial state alone could lead to significant

increases in skill of 12-24 hour sea state forecasts, and probably to

improved prediction at longer forecast ranges in wave regimes dominated by

swell.
Table of Contents

1. Introduction 1

2. Contemporary Wave Forecast Systems 5

3. Validation of ODGP/SAIL Models against ROWS Data 7

3.1 Introduction 7

3.2 ODGP and SAIL Model Attributes 7

3.3 Wind Field Preparation 9

3.4 ROWS Data 10

3.5 Hindcast Validation Against in-situ Tromsoflakket Daza 14

3.6 Comparison of Hindcast and ROWS Wave Data 17

4. QE2 Storm Study of Impact of SASS Winds on Sea State Specification 41

4.1 Storm Description 41

4.2 SASS Data 52

4.3 Wave Hindcast Experiments 56

4.3.1 Operational Wind Fields 62

4.3.2 Base Case Wind Fields 63

4.3.3 Comparison of Base Case and Operational Hindcasts 67

4.4 Wave Forecast Experiments 73

4.4.1 24-hour Forecasts from 1200 GRIT September D 73

4.4.2 24-hour Forecasts from 1200 GMT September 10 80

r

5. Conclusions 90

References "3

V

m- ...
vi

LIST OF FIGURES

page

Fi gure 3.1 Surface weather map for 1800 GMT November 2, 1978 of 11

northeastern N. Atlantic, showing track of storm (6-

hour positions shown).

Figure 3.2 Flight path of C 990 during Flight 9, 0800-1000 GMT 12

November 3, 1978, showing flight legs corresponding

to ROWS data files A through C, and locations of wave

hindcast model grid points near the flight path.

Figure 3.3 Comparison of measured and modelled surface winds at 15

Tromsoflakket ,location during period of C 990

Norwegian Sea experiment.

Figure 3.4 Comparison of measured and hindcast (grid point 212) 16

time history of significant wave height at

Tromsoflakket.

Figure 3.5 Comparison of hindcast and estimated frequency spectrum 18

(from wave rider data) at Tromsoflakket for Flight 6.

Figure 3.6 Same as Figure 3.5, except near time of Flight 7. 19

Figure 3.7 Same as Figure 3.5, except storm peak at Tromsoflakket. 20

t

Figure 3.8 Same as Figure 3.5, except near time of Flight 9. 21

Figure 3.9 Same as Figure 3.5, except near time of Flight 10. 22

Figure 3.10 Comparison of hindcast and estimated (from ROWS data 23

file A) frequency spectra in Flight 9.

Figure 3.11 Same as Figure 3.10, except for ROWS data file B. 24

Figure 3.12 Same as Figure 3.10, except for ROWS data file C. 25

Figure 3.13 Same as Figure 3.10, except for ROWS data file D. 26

Figure 3.14 Same as Figure 3.10, except for ROWS data file E. 27

-- Figure 3.15 Same as Figure 3.10, except for ROWS data file F. 28

.. Figure 3.16 Same as Figure 3.10, except for ROWS data file G. 29

Figure 3.17 Same as Figure 3.10, except for ROWS data file N. 30

c;

Figure 3.18 Same as Figure 3.10, except for ROWS data file I. 31
c vii

page

F

Figure 3.20 Comparison of ROWS frequency spectrum and estimated

spectrum from Tromsoflakket, for radar file A

Flight 9. (from Jackson, 1983).

Figure 3.21 Contour plots of directional spectra,shown in the plane

of the map,as estimated by ROWS in files A through J in

Flight 9, with the significant wave height (m) also

indicated for each measurement.

Figure 3.22 Comparison of ROWS and hindcast two dimensional

variance spectra for file A, in terms of contours on

spectral matrix representation in 15' directional

bands and 15 frequency bands used in the SOWM/ODGP

models. Contour levels are .02, .05, .08., .11,

.14 ft2.

Figure 3.23 Same as Figure 3.22, except for file B.

Figure 3.24 Same as Figure 3.22, except for file C.

Figure 4.1a-1 NMC final analysis surface weather maps at 6-hourly

intervals 0000 GMT 9 September 1978 - 1800 GMT

11 September 1978.

Figure 4.2 Distribution of surface ship reports (combined radiotelegraphed veports and ship lob, data) in N. Atlantic

at 1200 GMT September 10, 1983. Ship Euroliner is

near 43 0 N, 50 0 W. QE2 (call sign.GBTT) is near

50°N, 25°W.

Figure 4.3 Reanalysis of surface pressure for 1200 GMT September

10, 1978 based upon all ship data. Limits of swath

of SASS data in rev 1080 also shown.

Figure 4.4 Comparison of time history of central pressure and

maximum surface wind derived from NMC final analysis

and post-analysis based upon combined conventional and

SASS data.

Figure 4.5 (Cinematic analysis of surface wind field in QE2 storm

from conventional data alone for 1200 GMT September 11,

1978. Position of QE2 and limits of SASS data in

revs 1093/1094 also shown.

Figure 4.6 Relative tracks of QE2 storm center and QE2 (above)

and subjective analyses of significant wave height at

0600 GMT September 11, 1978 (below) (from James, 1979).

34

35

37

38

39

42 -

47

49

50

51

53

54
viii

page

Figure 4.7 Dealiased wind vectors in rev 1093 from SASS-1 algorithm 57

applied to SASS cell pairs.

Figure 4.8 Comparison of SASS wind speed and kinematic analysis 58

(from Figure 4.5) wind speed in rev 1-093.

Figure 4.9 Comparison of SASS wind direction and kinematic analysis 59

wind direction in rev 1093.

Figure 4.10 Comparison of SASS-1 wind speed and surface wind speed 60

reported by ships within SASS swath of revs 1093/1094. 

Figure 4.11 Grid system of ODGP and SAIL wave models used for QE2 61

storm simulations.

Figure 4.12 Kinematic analyses of surface wind field at 1200 GMT 65

September 10, 1978, Dashed lines are streamlines,

solid lines . are isotachs (labelled in knots). Ship

and buoy reports represented as wind barbs and

vectors from open circles; dealiased. SASS wind in y

100 km bins represented as wind barbs and vectors

from filled circles. SASS data from rev 1066.

Figure 4.13 Same as Figure 4.12, except analysis for 1200 GMT 66

' September 10 0 1978. SASS data from rev 1080.

Figure, 4.14 Comparison of (operational) surface wind field de- 68

rived from NMC final analysis pressure field (left)

and (base case) wind field from combined SASS and

conventional data (right) for 1200 GMT September

10, 1978.

Figure 4.15 Comparison of hindcast significant wave height 71

(contour interval is 5 feet) from simulated,

operational wind field (left) and wind field derived from SASS data (right) at 1200 GMT September

10, 1978. Location of storm center indicated as

C. Maximum hindcast significant wave height also

indicated.

Figure 4,16 Same as Figure 4.15, except for 1200 GMT September 72

11, 1978. Route of QE2 storm during encounter with 

storm seas indicated.

Figure 4.17 NOAA NMC wave height analysis for 1200 GMT September 74

111) 1978.. Wave height contours in feet.
t

Ix

Figure 4.18 FNWC (presently FNOC) model analyses at 1200 GMT

September 9, 1978 and 12-hour and 24-hour forecast

of sea level pressure fields (solid lanes are isobars at 4 mb intervals. Minimum central pressures

are also shown. (from Gyakum, 1983a).

Figure 4.19 24-hour forecast boundeey layer winds (streamlines

and isotachs, m/s) and sea level pressure (isobar

contour intervals 4 mb) in control experiment

#4 of Anthes et al. (1983). Forecast verification

time is 1200 GMT September 10, 1978.

Figure 4.20 24-hour forecast valid 1200 GMT September 10 0 1978

of significant wave height (contour interval is 5

feet) from FNWC sea level pressure forecast (Left)

and experiment #4 of Anthes et al. (1983) (r.ght).

Figure 4.21 24-hour NMC PE-model sea level pressure forecast

(contour interval is 4 mb) valid 1200 GMT September

11, 1978.

Figure 4.22 24-hour wave forecasts valid 1200 GMT September 11,

1978 of significant wave height (contour interval

is 5 feet). Forecast winds from NMC FE-model sea

level pressure forecast. Initial state (left)

taken from operational wave hindcast. Initial state

(right) taken from base case hindcast.

Figure 4.23 Actual 24-hour N. Atlantic wave height forecast map

issued by NOAA NMC, valid 1200 GMT September 11,

1978 (contour interval is 3 feet).

Figure 4.24 Actual 24-hour N. Atlantic wave height forecast map

issued by FNOC, valid 1200 GMT September 11, 1978

(contour interval is 3 feet).

page

75

79

84

85

87

88

89

r
X

List of Tables 

page

Table 4.1 Seasat orbits in QE2 storm. 55

Table 4.2 QE2 storm hindcast wind fields. 65

Table 4.3 Errors relative to base case hindcast in hindcast 70

` (operational) of surface wand and significant wave

height derived from conventional data alone. Base

case hindcast made from wind fields derived from

combined conventioanl and %'3S data. Mean errors

are computed as operational minus base case hindcast.

' Table 4.4 Errors relative to base case hindcast in 24-hour 77

forecast from 1200 GMT September 9 of surface

winds and significant wave heights based upon

operational FNOC surface pressure field forecasts.

Initial state for forecast specified from

operational hindcast.

Table 4.5 Errors relative to base case hindcast in 24-hour 78

forecast from 1200 GMT September 9, based upon

operational FNOC surface pressure field forecasts,

except forecast storm track adjusted to observed

track. Initial state for forecast specified

a from operational hindcast.

Table 4.6 Errors relative to base case hindcast in 24-hour 81

forecast from 1200 GMT September 9, based upon

sea level pressure forecasts in QE2 storm from

experiment #4 of Anthes et al. (1983). Initial

state for forecast specified from base case hindcast.

Table 4.7 Errors relative to base case hindcast in 24-hour 82

forecast from 1200 GMT September 10, based upon

NMC model sea level pressure forecast. Initial

f` state specified from operational hindcast.

Table 4.8 Errors relative to base case hindcast in 24-hour 83

forecast from 1200 GMT September 10, based upon

NMC model sea level pressure forecast. Initial

state specified from base case hindcast. 

x

n
I

1. introduction

$EASAT-A was launched on 26 June 1978 and stopped transmitting after

acquiring global data fro- ► t each instrument over a 99 day period. After a

period of extensive evaluation of limited data sets and tunin v- of algorithms which retrieve geophysical data from the sensor data, global data

sets for each instrument except the synthetic aperature radar (SAR) had

been p-ioduced for the entire experimental period. The success of the

scatterometer (SASS) experiment in demonstrating the ability to remotely

sense surface marine winds has by now been well documented. In a recent

review, Pierson (1983) cites r.m.s. differences between the SA 43 winds

end meteorological winds of 1.2 m/s in speed and 17 * in direction with

negligable bias.

A number of planning studies conducted prior to the launch of SEASAT

showed that tremendous economic and human benefits would accrue to the

marine community from improved short (12-48 hours) and medium range (3-5

days) operational wind and sea state forecasts. It is widely believed

that the global availability of remotely sensed marine winds on future

operational satellites shall have great .,ffects on weather and sea state

forecasts but to date only very limited research based on actual SEASAT-A

data has been reported to support this view.

Simulation studies using numerical weather prediction models (Cane

et al., 1981) suggest that improvements in the initial state provided by

SASS type data improve analyses and forecasts of surface pressure and

low and midtropospheric wind fields over both land and sea. To date these

results have not been confirmed in experiments involving real SASS data

but 

'

such experimental programs are underway at a number of centers,

including the NASA Goddard Space Flight Center and NOAA's National

Meteorological Center.

In this study, we attempt to document through a case study, the

potential impact of remote sensing wind data on the specification and

forecasting of sea states in a particularly dangerous class of meteorological phenomenon; the explosively deepening marine extratropical cyclones

or more simply "bombs" (Sanders and Gyakum, 1980). Such storms have be

 the focus of intense interest in recent years for several reasons.

------ ---- ----
2

First "bombs" are clearly a hazard to shipping and other offshore

interests and seem to be largely responsible for weather related loss of

life and shipping in the high seas, even in well travelled shipping lanes.

Two examples are the storm of August, 1979 in the eastern North Atlantic

which occurred during the Fo'.tnet yacht race, sinking 24 boats and killing

17 sailors, and the storm off the Grand Banks of Newfoundland of February,

1981, in which the drilling rig Ocean Ranger sank killing 84 crewmen. The

storm used for this case study occurred in early September, 1978 in the

western N. Atlantic, and was responsible for the loss of a fishing trawler

with all hands off Georges Bank and extensive damage to the oceanliner

Queen Elizabeth 11 along with injury to 20 of its passengers. This QE2

storm has been studied extensively by Gyakum (1983) and Anthes et al, (1983).

Bombs are interesting also because the physical mechanisms responsible

for their explosive development are not well understood. There is increasing evidence that an.important source of energy is convective beating;

bombs therefore bear some similarity energetically to tropical cyclones.

Finally, as pointed out by Leary (1971) and Sanders and Gyakum (1980),

operational numerical weather prediction models often fall to predict

explosive cyclogenesis over the oceans. Bombs therefore have not participated in the very significant improvements in skill in numerical weather

forecasting exhibited over the past two decades. Also, since bombs usually

form as very small scale but intense circulations, detection is more difficult and storms may not be resolved in analyses produced objectively to

initialize numerical weather prediction models.

For this study, we have assembled a comprehensive data set for the QE2

storm consisting of conventional surface s

hip reports, recently reprocessed

SASS data, and surface pressure and sea state analyses and forecasts prepared in real time by the NOAH National Meteorological Center (NMC) and the

U.S. Navy Fleet Numerical Oceanography Center (FNOC).

The data sets were used to develop alternate representations of the

surface wind over the western North Atlantic Ocean for the period of the

formation and intensification of the QE2 storm. As expected, the wind

fields developed from conventional data available in real time were found

to be quite deficient despite the fact that the storm formed and moved
a

It

-through a major shipping lane. On the other hand, the surface wind fields

developed from a combination of conv7 ,r., tional ship reports and SASS wind

data documented the rapid formation of gale force winds about the incipient

storm and the evolution of the -;ale and intensity of the surface wind

field over the 48-hour period between the formation of the rtorm and the

development of peak sea states in ti)e storm at about the time of the

encounter of the QE2 with the storm.

Since remote wave measurements were not made in the QE2 storm, a hindcast was made using a calibrated spectral /iave model and -the SASS based

surface wind fields. This hindcast provided a base case wave specification against which operationally produced wave analyses and forecasts in

this storm could be evaluated, Errors in conventional analyses and forecasts were extremely large, with peak sea states underestimated by as much

as a factor of four. Hindcasts made with the calibrated wave model but

driven by wind fields derived from conventional real time data showed

little improvement over NMC or. FNOC analyses, sup

porting the view that

errors in operational wave analyses and forecasts are mainly caused by wind

errors rather than wave model errors.

A series of three experiments were performed with the wave model to

assess the impact of the SASS data on sea state forecasts. In one experiment, we a simulated 24-hour wave forecast for the period of

explo g ivo development,for which forecast wind fields were derived from a

numerical weather prediction for the QE2 storm reported by Anthes et al

(1983). Their forecast was based upon an improved initial state specification derived from SASS data and a high resolution numerical weather prediction model. The numerical weather prediction captured only about 500

of the explosive deepening, in terms of minimum surface pressure, and

contained errors in the shape of the pressure field and in the location of

the strongest winds. Those errors translated into significant wave height

errors relative to the base case, though wave forecasts were much improved

overall.

The second and third forecast experiments covered the 24-hour period

prior to the QE2 encounter with the storm, a period in which the storm had

stopped deepening explosively but during which peak sea state growth

continued. Forecast wind fields for both experiments were derived from
rZ k

0

4

operational NMC surface pressure forecasts. The experiments differed in

the initial state specification. In one experiment, initial sea states

were *ec'.fled from the base case hindcast; in the other, initial sea

states were derived from hindcasts made from conventional. wind data alone.

These experiments showed that the improved initial state specifications resulted in improved forecasts at 12 hours, but that by 24 hours,

errors in forecast winds had largely eliminated the differences between

the two forecast runs. The tentative implication is that significant

improvements in sea state forecasts beyond 24 hours will follow principally

Zrom increases in skill in numerical weather prediction with the exception 4,

of forecasts of swell which would benefit from improved remote wind and

wave sensing systems even with numerical weather forecasts with current

levels of skill.

A new remote sensing instrument, the real-aperature scanning beam

Radar Ocean Wave Spectrometer (ROWS)( Jackson et al. 1983) has been

shown recently to be capable of obtaining global satellite measurements of

ocean wave directional spectra. Such data could be used in the specification of the initial state for wave forecasting systems, much like the

way atmospheric observations are used to initialize numerical weather prediction models. The forecast experiments just summarized above estimate

the impact on forecasts of such improved initial states for one storm type.

Wave prediction models are not perfect, and ROWS type data may also

provide the wave data necessary to validate and further refine such models.

In this study, the wave model used for the QE2 storm hindcasts, and an

alternate model, were used to hindcast a separate intense N. Atlantic storm

in which an airborn, ROWS obtained directional wave spectra. The comparison of hindcast and measured wave heights and directional spectra beneath

the flight path confirmed the skill on wave height specifications shown

for the -idopted wave model in prior studies but revealed certain deficiencies in the treatment of directional processes in the model theory.
2. Contemporary Wave Forecast Systems

In recent years there has been a shift at many forecast centers

(e.g. those of the U.K., Japan, Norway, France) to the use of numerical

spectral wave specification models to make operational wave height analyses

and forecasts. The models are run in hindcast/forecast cycle, usually

twice daily, from 0000 GMT and 1200 GMT initial states. The models are

driven exclusively by input wind fields; in wave forecasting, unlike numerical weather prediction, the initial wave conditions for a forecast

are not specified from wave measurements but are calculated by the wave

model run in a hindcast mode using wind fields derived from measurements.

The accuracy of wave forecasts therefore may '.)e limited by errors in the

initial state due to poor marine wind analysis, errors in forecast wind

fields derived from numerical weather forecast models, and possibly errors in the wave models themselves, though the latter effect may be

minimized through careful model development and calibration.

Contemporary wave prediction models were reviewed by Cardone and

Ross (1979). The models are based upon the spectral energy balance equation, usually applied in its simplest form, that is, to surface gravity

waves assumQd to propagate through water of infinite depth that is otherwise at rest. In this form, the equation is written

3

4

Tt E(f ' 9 ' ' t) + Cg(f,e) • 7E(f,9,-X*,t) = S(f'e'4'X't) 2.1

where E is the energy density of the wave field described as a function

O-a

. frequency, f, direction of propagation 0, position x, and time t;

CV 

is the deep water group velocity vector,and S, the source function

represents all physical processes that transfer energy to or from the

spectrum. Discrete type wave models represent the spectrum E in terms

of a number of spectral components (bands) of finite width, and successively simulate wave propagation (the homogeneous part of 2.1) and local

energy -transfers (the r.h.s. of 2.1) in a series of discrete time steps on

a grid representing the ocean basin of interest.

In this country, the only operational spectral wave forecast model

is the SOWM model of the U.S. Navy FNOC. The SOWM resolves the wave

spectrum into 180 spectral components representing 15 frequency and 12
6

direction bands. The SOWM is run operationally twice daily on a grid

which represents all major northern hemisphere basins. The SOWM

1* forecasts extend to 72 hours. Initial conditions, E(fO,x,t 0

are taken from a continuous hindcast history made with the same wave model

driven by 6-hourly wind fields produced at FNOC routinely by objective

analyses of ship reports of wind and sea-level pressure. In this report

we will refer to numerical surface pressure field forecasts and SOWM wave

analyses and forecasts for the North Atlantic Ocean in the QE2 storm.

In this study we have basically simulated the operational wave forecast system l ised at FNOC, in order to assess the potential impact of

remote sensing data Zor a case of explosive cyclogenesis. However, our

system differs from the FNOC system, in that: (1) analysis winds were produced in a "man-machine" mix procedure rather than through strictly computer-based analyses; (2) the wave model used here for the QE2 storm hindcasts is a newer version of the SOWM with improved calibration and higher

spectral and spatial resolution.
a

^ 7

3. Validation of ODGP/SAIL Models against MOWS Data

3..1 Introduction

In this section we present an evaluation of the wave model (ODGP)

used for the QS2 storm case study, in storm conditions against directional

wave measurements made by an aircraft mounted radar. The measurements

were obtained with the Goddard ROWS in the Norwegian Sea in a severe storm

which formed in late October, 1978. Conventional wave measurementswere

also made in the same storm from a waverider buoy, deployed in the area

of the experiment. There were a total of 5 flights over a 7 day period

during the experiment. The hindcast covered a 12 day period to encompass

all periods of data collection. The radar data have been thoroughly

analyzed however only for one of the flights, which sampled the most severe sea states in the experiment. Since the high resolution directional

wave measurements of the ROWS provide a rare opportunity to evaluate the

directional aspects of spectral wave model predictions, a model with an

k alternate source term treatment (SAIL) was also used and evaluated.

3.2 ODGP and SAIL Model Attributes

R The ODGP (Ocean Data Gathering Program) model, developed by Cardone,

Pierson and Ward (1976) is a part of the family of PTB discrete type

spectral models described by Pierson, Tick and Baer, (1966). Current

versions of the ODGP model use the propagation scheme proposed by Greenwood and Cardone (1977). Their scheme uses downstream interpolation to

propagate waves along great circle paths in an energy conserving manner.

The scheme is basically first order and therefore dispersive, a trait

intended to simulate the natural lateral and longitudinal spreading of .

finite bandwidth spectral components. The properties of the scheme are

described in more detail in the report of the wave model intercomparison

panel to the IUCRM Symposium on Wave Dynamics and Radio Probing of the

Sea Surface, Miami, Florida, May 1981 (SWAMP, 1983).

While the ODGP spectral growth/dissipation algorithm is of the PTB

type, significant differences between it and the U.S. Navy SOWM_model

(also a PTB type) evolved in the application and verification of the ODGP

model against measured wave spectra in hurricanes. An important difference

is in the calculation of the wave growth as a function of the angle be

p tween the wave direction and wind direction. In the SOWM, the energy in
8

a given frequency component summed within 190 0 of the local wind is the

quantity subjected to growth. The incremental growth is then spread out

over the same components. In the ODGP model each downwind spectra, component is grown separately and after computation of growth for all components within ±90 0 of the local wind direction, energy is redistributed

over angles. This algorithm leads to slower growth of wave height with

time in Z turning wand than in a wind of constant direction.

Recently, workers have attempted to ;investigate the response of the

wave spectrum to a turning wind from pitch/roll buoy data by studying

the response of the mean wave direction in individual frequency bands

Clearly, not enough detail is present in such data to observe the directional response in complicated wand fields, and considering the scant

field evidence, it is not surprising that the SWAMP group found large

differences in the directional relaxation rates between the ten spectral

wave hindcast models compared.

t The modelling of directional processes in the ODGP model is apparently sufficient to provide reasonably skilled simulation of the integrated properties of the directional spectrum of peak sea states in

storms characterized by „tationary or moving circular wind fields. In

w over 60 individual comparisons in 19 different storms, Reece and Cardone

(1982) found that the model exhibited negligible bias and rms errors of

less than 1m in, significant wave heigi±t and 1 second in peak spectral

period. Comparisons of hindcast and measured directional wave properties

are more limited. Forristall et al. (1978, 1980) shows comparisons in

two Gulf of Mexico tropical cyclones. The directional spectrum was estimated from surface elevation and orbital velocity measurements. Directional

properties were expressed in terms of the mean direction and spread as

a function of frequency. Good agreement was found in both storms.

The directional wave measurements obtained in this study provide the

first opportunity to check in great detail the predictions of the directional spectral shape. To accomplish this, the ODGP model was adapted

on a high resolution grid of 100 km spacing covering the eastern two-thirds

of the North Atlantic Ocean. The 100 km spacing dictates a time step of

3 hours for the spectral range modelled. For this hindcast, the frequency
4

9

banding of the 15 bands of the SOWM was adopted. However, a 15° directional

banding, rather than the SOWM's 30 0 banding was used.

The SAIL model is based upon a completely different spectral growth

algorithm from the ODGP model, but uses the name spectral resolution

propagation scheme and grid system. The basic formulation of the SAIL

model is described by Greenwood et al. (1983); its participation in the

wave model intercompari.son program is described in the SWAMP (1983) report.

The SAIL model has undergone much more limited validation than the

ODGP. The model is tuned basically through the adopted implied fetchwise energy growth law. For one particular tuning (SAIL II) the model

was found to nearly match the skill of the ODGP model in specification

of peak sea states in several hurricanes (Oceanweather, 1983).

A hindcast with the SAIL model is included here basically to check

whether the rather different treatment of directional processes from

that of the ODGP model leads to any discernible difference in the

specification of the full 2-d spectrum.

3.3 Wind Field Preparation

Cardone et al. (1980) describ, a and compare alternate marine wind

field analysis methods with particular emphasis on the impact of wind

field errors on wave specification. For typical mid and high latitude

storm scenarios, specification of surface winds from conventional surface

pressure analyses produced in real time at operational forecast centers

generally was found to lead to wave hindcasts (with the ODGP model) containing both large rms errors and systematic underestimation of peak sea

states, compared -to errors (e.g. Reece and Cardone, 1982) found in hindcasts when wand fields were s p ecified through reanlaysis of surface pressure

and wind fields using enhanced ship report data files, and kinematic

analysis techniques.

For this study, surface wind fields were specified at 6-hourly intervals over the period 0000 GMT 10/25/78-1800 GMT 11/07/78, over the

domain 40°N-80°N, 50°W-3,0 0 E. For model spinup and periods in-between

flights, winds were derived from the pressure analyses shown on the

6-hourly Northern Hemisphere Surface Analyses produced in real-time at
to

the NOAA National Metebrological Center. The procedure was to grid the

sea level pressures manually on a 2.5 0 latitude-longitude grid and then

objectively derive 19.5 meter level winds using the marine planetary boundary layer model of Cardone (1969). In that procedure, pressure gradients

are derived by centered differencing, resulting in a highly smoothed wind

field. For the critical periods, a complete reanalysis of the surface

pressure and wind field was performed. First, ship reports not available in real time were added from a file of punched ship log reports produced at the NOAH National Climatic Center and replotted by machine. An

example of replotted charts with reanalyzed isobaric and frontal analyses is shown in Figure 3.1. The number of ship reports shown overall in

the maps exceeds by at least a factor of 2, the number available in real

time. The number of reports from transient merchant ships decrease sharply north of about BO O N. The reanalysed pressure fields and the kinematic

analyses were digitized at a 2.5 0 spacing since the data density hardly

justified a finer, spacing.

The map shown, depicts the synoptic situation leading up to the

flight of interest on November 3. At 1800 GMT, November 2, a deep (958 mb)

cyclone center is just north of the North Cape of Norway. That storm formednear 40 O N, 50 O W on 30 October and moved eastward at first. On I November,

the storm turned northeastward, accelerated to a forward speed of 50 knots

and deepened rapidly, the center passing just east of Iceland between

1200 and 1800 GMT I November. The center turned eastward and slowed to

about 25 knots before passing north of the north coast of Norway earlyon 3 November. Maximum surface winds of 50-55 knots were measured by

several ships in the right semi-circle of the storm of November 2nd and

3rd.

3.4 ROWS Data

Flight 9, the flight of interest, was conducted between 0800 GMT and

1000 GMT on 3 November, generally in the area between the storm just

described, and a weaker frontal wave approachin g from the west. A weak

ridge of high pressure separated the two systems. The measured flight

level winds along the flight line showed a complicated fine structure in

the wind field near the ridge line. It is important to note that the
I 

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12

6-hourly 2.5 * synoptic :scale winds will not in general resolve such fine

structure, and that therefore even a "perfect" wave model will be unable

to resolve the details of the wave patterns along parts of the flight line.

Figure 3.2 shows 7U0 km by 150 km box pattern flown by the NASA

CU990 in the area between the two extratropical cyclones. The figure

also shows the wave model grid point locations in the vicinity of the

box, the ROWS data files denoted by letters, and the location of the weather

ship station TromsoflaRket near file A. The weather ship made 3-hourly

surface wind measurements,and 3-hourly frequency spectra were estimated

from measurements made by a wave rider buoy moored near the ship, The

ROWS used was the NASA Goddard airborne 13.9 Ghz pulse-compression

radar. The radar was equipped with a 6 rpm rotary antenna boresighted

to 16 0 incidence providing a conical scanning bean of about .5 km lateral

extent. A stable estimate'of the directional spectrum is built up from

data acquired over about 10 successive antenna rotations.

A full theoretical treatment of the principle of ROWS is giver) by

Jackson The directional selectivity results basically from the

radar ocean wave phase front matching across the lateral extent 

of 

the

beam spot, The reflectivity mechanism is basically geometrical for the

near vertical speoular scatter regimes In which ROWS operates.

The details 

of 

the data reduction for the fall 1,978 mission are given

by Jackson et al. (1982). That mission included not only the Norwegian

Sea flights, but flights over several North Pacific storms. During

the mission, 'ten spectrorri-iter files were coincident with surface wave measurements from buoys, including one comparison against a directional

spectrum estimated from a NOAA pitch/roll. buoy. The agreement in the

frequency spectrum was found to be excellent, and overall significant wave

height estimates derived from the volume under the 2-d spectrum were found

to be unbiased with an rms error of 0.16m. For the directional comparison,

the mean wave direction and spread as a function of frequency agreed to

within a few degrees.
13 ORIGINAL PADS 59

or pOOR QUAL'TY

750

—700

-650

Figure 3.2 Flight path of C-990 during Flight 9, 0800-1000 GMT

November 3, 1978, showing flight legs corresponding

to ROWS data files A through C, and locations of wave

hindcast model grid points near the flight path.

bq
14

3.5 Hindcast Validation Against 1n - Situ Tromsoflakket Data

Figure 3.3 compares the specified surface winds at grid points near

Tromsoflakket position and the measured winds. The periods for which kinematic analyses were produced are indicated. Measured winds are not available before October 30 because the station was not manned. The sequence

of measured winds shows the rapid wind shifts and wind speed changes

accompanying the several lows and frontal, troughs which passed the station

in the period modelled. The storm of 1-3 November was clearly the strongest system in the period studied, and flight 9 is sampling the mailing

part of the storm which is shown in the measured time history as a rapidly

decaying and shifting wind pattern.

The meastired and hindcast significant wave height time histories are

compared in Figure 3.4 in this and following figures, the ODGP model

hindcast is referred to as hindcast I, and the SAIL model hindcast as hindcast II. The decaying sea states between 29 October and 1 November

generally are well simulated by both models. Both hindcasts lead the

buildup of seas at the onset of the major storm on 1 November , but this

may be related to the positive: 5-7 knot bias in the analyzed wind speeds

seen in the Tromsoflakket wind comparisons during the same period. The

significant wave height at the model grid paint nearest Tromsoflakket

peaks at 2100 GMT 3 November at 10m in the ODGP model and Sm in the

SAIL model. hindcasts. The wave heights estimated from the buoy data

fluctuate rapidly near the storm peak between 3.5 and 11.5 meters. This

could be attributable to sampling variability, which for ''^he 17 min 4 sec

sampling period introduces an uncertainty in significant wave height of

about 10-15%, at the 90% confidence level. The rest of the time series

is generally well simulated by both models except for the period between

0000-1200 GMT on 6 November, when the ODGP model responds, to the strong

southeast winds which were measured early on the 6tb, but which apparently

did not lead to wave growth at the buoy loc4itIon. The SAIL model produces

a better match here but the comparison is made difficult by the poor resolution.even on the model grid spacing of 100 km, of the fetch at the

buoy location and the complicated shoreline geometry upwind for this

particular wind direction (about 140 0 ). In summary, both model hindcasts,
oRl,GjNAL PAGE 19

OF POOR QUALITY

( 64P) N01103810 ONIM

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hindcasting the significant wave height as shown in previous studies,

except that the SAIL model is lower than the ODGP model by about 20% in

specification of the peak significant wave height on 3 November.

Figures 3.5 through 3.9 show a number of comparisons of estimated

and hindcast frequency spectra at Tromsoflakket. Comparisons are shown

for a time near each flight during the experimental period and near the

storm peak on 3 November. The spectral comparisons are In a sense selected to produce favorable matches insignificant wave height; that is,

for a given compar l,son, the grid point and time step adjacent to the measured location and time respectively, giving the best agreement in H

1/3 s

was selected. The matches therefore are intended mainly to reveal errors

in spectral shape. The approximate 905 confidence limits on the estimated

spectra are 0.6 and 1.9 time the estimated value. The errors in hindcast spectral shape are evidently small. The spectral comparisons show

ilso that the differences between the models at the storm peak (figure

3.9) is in the forward (low-frequency) face of the spectrum, with the ODGP

apparently more correctly specifying the spectral peak frequency. It

should be noted however, that the SAIL model growth law could be adjusted

to produce better agreement though no specific tuning for this storm was

performed.

3.6 Comparison of Hindcast and ROWS Wave Data

Jackson et al. (1982) have reduced the radar data collected in Flight 9

in a number of formats. One format,prepared specifically for comparison

of the ROWS data with the hindcasts, involved the partitioning of estimated

spectral variance over the same frequency and directional bands used -,'Ln

the hindcast model. The 2-d variance spectrum so produced may then be

summed over frequency to compare the distribution of total energy over

direction, or summed over direction to compare frequency spectra.

The estimated and hindcast frequency spectra for the ten processed

ROWS files are compared in Figures 3.10 through 3.19. There is cvidently

a deficiency of low-frequency energy in the hindcast spectra at all sites,

with the SAIL hindcasts more deficient in this regard than the ODG? hind-
40

IA

uRIGINAL

OF POOR QUALITY

HS W FLIGHT 6

3.41 —-ESTIMATED 6TROMSO'

2025 GMT 10/30/76

3.17 -HINDCAST 1

3.20 -HINDCAST I[

30

E

z 20

W

L)

W

CL

Ln

10

0

0 110 .15 20

FREQUENCY (Hz)

Figure 3.5 Comparison of hinO4ast and estimated frequency spectrum

(from wave rider data) at Tromsoflakket for Flight 6.
19

E

z

W

C) 20

-j

I

41

X

W

a.

10

0 L

0 .10 .15 .20

FREQUENCY (HZ)

Figure 3.6 Same as Figure 3.5, except near time of Flight 7.
UHIGINAL PAC"-

OF POOR QUALIV,

200

190

180

j 170

160

150

140

—130

NE 120

>- 110

ti

z 100

' o

J 90

H 80

w

u

N 70

60

50

r 40

30

20

10

H, (m) NEAR STORM PEAK

9.9 ESTIMATED `TROMSO"

0230 GMT 11/03/78

9.56 -^HINOCAST I

Z93 HINDCAST a

1

I; 1 I' 1

II 1

l 1

1

r' 1

I

I

I

I

v IO I5 20

FREOUENCY (H2)

C

Figure 3.7 Same as Figure 3.5, except storm peak at Tromsoflakket.

f

i

^

_w 
21

1

ORIGINAL

OF POOR

r ,

y,

Hs W FLIGHT 9

7:18 ---- ESTIMATED *TROMSO*

1131 GMT 11/03/78

7.75 - HINDCAST I

7.27 HINDCAST II

{ u

I! NEU

y„

FZ 100 W0

J 90

Qi

F- 80

u

w

a; 70

60

50

40

30

20

10

O

.10 a5 ,20

FREQUENCY (Hz)

Figure 3.8 Same as Figure 3.5, except near time of Flight 9.
22

30

E

W

20 w

it

_j

w

a.

to

0

1F POOR

HS (m) FLIGHT 10

3.06 —-ESTIMATED OTROMSO*

0818 GMT 11/06/78

4.24 -HINDCAST 1

2.97 -HINOCAST 3E

fll

40

0 .10 15 120

FREOUENCY (Hz)

Figure 3.9 Same as Figure 3.5, except near time of Flight 10.

it

!4w,
23

ORIGINAL ^'ii 8 OF POOR (11,,17y

180

160

140

F

`' X120 N

N^

E

4 ^_ 100

S Z

W

J 80

Q

V

z Wa.W 60

k

40

r^

20

Q

A

GP 212 0900 GMT 11/03/78

• — MEASURED

--^- HINDCAST I

HINDCAST a

O .10 l5 zv

FREQUENCY (Hz)

Figure 3.10 Comparison of hindcast and estimated (from ROWS

data file A) frequency spectra in Flight 9.

M
24

1

OF POOR Qj.

8

GP 254 0900 GMT 11/03/78

MEASURED

HINDCAST I

HINDCAST IL

100

E ov

V)

Z

60

FW 40

20

0

FREQUENCY (Hz)

Figure 3.11 Same as Figure 3.10, except for ROWS data file S.

OW
2.5

ORIGINAL r—in.sm: ES

OF POC!,

C

GP 297 0600 GMT 11/03/78

MEASURED

HINDCAST I

HINDCAST n

_U 100

E

>- 80 H

U)

z

w

_j 60

f

^

Fv) 40

io

0

FREQUENCY (Hz)

Figure 3.12 Same as Figure 3.10, except for ROWS data file C.
OF POCR

D

GP 296 0600 GMT 11/03/78

•— MEASURED

^— HINDCAST I

HINDCAST II

26

1

c

`C

f

c 100

uv

N^

E

80

r

.p

z

0 60

J

Q

w 40

{ a

20

O

FREQUENCY (Hz)

Figure 3.,13 Same as Figure 3.10, except for ROWS data file D.

c
ORIGINAL PPE"

OF POOR QUALITY

! ^

} ^

( ^ ^

}

! \

| ^ ^

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k

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FREQUENCY m#

. Figure 3,1 Same as Figure $210 except for ROWS data file E.

27
28

4W

or.?,

0.^^ rs

ICINAL PA-w

- -IF POOR QuAL, IN

F

GP 342 1200 GMT 11/03/78

MEASURED

HINDCAST I

HINDCAST n

10C

8C

Z

w 60

U

uj 40

20

10 .15 .20

rKr.WWr.NLoT (MZJ

Figure 3.15 Same as Figure 3.10, except for ROWS data file F.
29

0 .10 .13 .20

FREQUENCY (Hz)

Figure 3.16 Same as Figure 3.10, escept for ROWS data file G.

0

100

V

v

NIcE

90

z

0 60

J

a

H

aWa 40

N

20
30

100

r

U

NE" 80

H

2WO 60

J

Q

Q:

W 40 • ^o

CL

20

r 

s /

^

Q :

0 .10 .15 .20

FREOUENCY (Hz)

Figure 3.17 Same as Figure 3.10, except for ROWS data file K.
31

120

100

so

La 0%;

aaQ

W 40 CLV)

20

0

ORIC,

OF POOR

I

GP 213 0900 GMT 11/03/78

MEASURED

HINDCAST I

HINDCAST IE

FREOUENCY (HZ)

Figure 3.18 Same as Figure 3.10, except for ROWS data file I.
32

a

#

100

c4z

E 80

to2

p 60

k

J

Q

FW 40

N

20

k

0

J

GP 213 0900 GMT 11/03/78

•— MEASURCD

-----* HINDCAST I

HINOCAST 3E
i ,w

33

casts. This type of difference was evident also in the wave rider comparison near the storm peak as well (Figure 3.2). Since the ROWS file

A frequency spectrum is in very close agreement with the corresponding

measured wave rider spectrum (Figure 3.20, Jackson, 1983) the deficiency

of low frequency energy in the flight 3 box at the time of the flight

is most likely an error in the hindcasts. T10<„; hindcast error could have

been caused by errors in the wind fields near the storm center earlier

in its history or possibly by deficiencies in the formulation or tuning

of the spectral growth algorithm.

The directional wave spectra provided by the ten ROWS files have

been displayed as contour plots laid out on a map of the Norwegian Sea

by Jackson (1983), as shown in Figure 3.21. The contour levels of each

plot represent energy levels relative to the peak values, with the estimated zero moment significant wave height values given numerically

(meters) beside each plot. This figure provides an unprecedented view of

the spatial distribution of the directional wave properties in the rear

quadrant of a fast-moving extratropical cyclone. Basically only two

nearly orthogonal wave trains are detected. In the northeastern corner

of the box, the ROWS file A sampled the 9.5m sea states southwest of

the area of peak storm generated seas in the right rear quadrant of the

storm. That is the area in which the highest sea states should be expected for a fast moving circular wind field. It is interesting that

at A, the surface wind had shifted from southwest ) to northwesterly

about 12 hours earlier but very little energy has been excited in the new

wind direction. ROWS files I and J also show only the northeasterly

directed wave energy generated in the long fetch of southwesterly winds

on the right side, relative to the track, of the cyclone.

i wind directions are referred to as "from which", wave directions are

referred to as "to which".
180.0

160.0

1-10.0-

120.0

M

100.0

2

ri 80.0

Z

60.0

40.0

20.0

0.0

34

FLT-9 TAPE36? F ILE I POT 0- ALPHA 1.18

0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20

HERTZ

Figure 3.20 Comparison of ROWS frequency spectrum and estimated

spectrum from Tromsoflakket, for radar file A

Flight 9. (from Jackson, 1983).

I I
35

^G

,

ql^ ^1

r g.2

i

62

4F ,

11.A

0

D

9y

rf 100 KM OF POOR QUALI

a

^

^N

,

® /i

%

B 0 D 0

E t 1

^O

5.7

15

a

C D

R

!3

f

Y

4

Figure 3.21 Contour plots of directional spectra. shown in the plane of the maps,

as estimated by ROWS in files A through J in Flight 9, with the significant wave height (m) also indicated, for each measurement. 
36

The northeasterly wave energy is evident also at all other ROWS files

in the flight box, where it is best described as "swell" or "dead sea"

Left behind by the fast moving wind field. It should be recalled that

the translation velocity of the wind field varied between 50 and 25 knots

between 1-3 November, while the group velocity of spectral components at

the spectral peak (- .068 hz) is only 22 knots.

The southeasterly directed wave energy seen at files B, C, D, F, G,

H apparently i3 a transient pulse of swell propagated into the box from

a generating area in the left rear quadrant of the storm as suggested in

the isobaric pattern of Figure 3.1. The most striking feature of Figure 3.21 is the absence of wave energy in the directions of the strongto-gale-force west northwesterly winds which were blowing at the time of

the flight in the northeastern half of the box.

To compare the hindcasts and ROWS directional wave spectra we have

juxtaposed contoured variance arrays presented in the FNOC/SOWM/ODGP

frequency-direction format. The comparisons for files A, B and C, shown

in Figures 3.22, 3.23 and 3.24 respectively, represent the kinds of

difference observed.

At file A, the ODGP model hindcast shows a relative maximum at a

frequency of .0806 and direction of 60 0 , in good agreement with the ROWS,

' but the hindcast also produced a second maximum at the same frequency but

travelling downwind 105 0 -120 0 , where the ROWS shows little energy. However for frequencies higher than about .10hz, the hindcast and the ROWS

show maximum energy travelling downwind.

At file B, the ROWS spectrum is distinctly bimodel in direction with 

one relative maximum in variance at a frequency of .0917 and direction

of 135 0 , and the other at a frequency of .0806 and direction of 45 0 -60 0 .

The corresponding ODGP spectrum shows both wave trains. Indeed, the two

spectra are in good agreFLlont except again for more downwind energy in

the hindcast than in the ROWS. Again the SAIL model spectrum is unimodal

about the local wind direction. The comparisons at file C are very much

like those of file B.

We conclude tentatively, that the directional characteristics of

the ODGPmodel hindcast are remarkably good considering that model development and tuning, was based exclusively on nondirectional wave data. There

Y.
ROWS 37

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FIGURE 3.22 COMPARISON OF ROWS AND HINDCAST TWO DIMENSIONAL VARIANCE

SPECTRA FOR FILE A, IN TERMS OF CONTOURS ON SPECTRAL

MATRIXREPRESENTATION IN 15 * DIRECTIONAL BANDS AND 15

FREQUENCY BANDS USED IN THE SOWM/ODGP MODELS. CONTOUR

LEVELS ARE .02, .05, .08, .11, .14 FTC.

OF POOR QUALITY

I 1

r
ORIGIN PI pp.:

ROWS OF PCGi2 QJ ALIV

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01.61 4.404, 0.(466 4. KJ6 a.0 H l 1111[,! 1.0771 1.1711 1. .i •.1+11, L u lr .1(49 :.00•/ t.7r91

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144. a 7.0001 t.: :641 i. 41110 0.G),+ 4.)1)1 1.1101 4.)114 .1711 /411 J 1. t: 1.111) :.60.1 O. Ill.

+01..1 7.4040 0. 0)•J 0. 4L f1 1.3449 1.0641 41.0 101 0.6011 074,]0• ... 1 10+4. 0.0 II 1.11,1( 1.44(1 41.4494 0.+00•

4.1.•4 4.3411 1.11(7 6.2491 4.0314 ).:041 1.1054 3.0611 1.a(/ 41111 11.6 1.. 4.1149 0.4911. 1.49., 7.1111 •.lore

121.11 0110): 1.11403 7.0::11.3041 010401 1.0011 6.0711 1. Ill 1.0)01 @.eon 8.01!1 e. 0)!t 1.5511 0.0,11!

A: 4112.11 4.53): :.: a1 CIA 0. C)C, 1.7611 0.0)01 7.003. 1.0:.1 0.61+1 1.41it! 4.11,• 0.0017 1.0011 1.4915 0.213. 7.0IH

141.64 4.41143 C.0 )c7 J. '.7 111 t.t 7L1 5.4.40 0.4)63 +.::311 •.0)+J 4.40,• 1.49 H 1.403. 0.01111 1.0017 0.0)0! 1.4640 9.4116

A 01.0) +.40:0 :.0:04 7. 46)10 1.[11: 4.113 )e 1.0433 ].:0441 1.0)16 0.:0 111 1.1117 1.1011 0.1301 e. 6141 0.6 109 1.4900 0.44,2

710.0) 0.,140 010101 ).:::1 1.11,413 1.3:11 ...:00 6.:346 1.1349 :. JO 11 6.0011 •.4911 1.60.1 0.4900 1.4304 0.0091 1.4,0•

i0). a 4.1243 c.c 4. , C.+Ili 0.14.1 )..0

01

18 t.90c) 1.4+44 1.6243 2.411441 ..0181 4.014, 1.6491 5.1491 1.4963 I.00n 1.0111

11.5. a a. c1 )c 0.(149 1.406: :.1 499 1.11 1.1344 r. JOJe L 0010 +.4241 •.104, 0.00!11 1.140, c. not L I1n .0004 0.1449

:•1.•1 i. 47+0 1.:474 <.::IC 911:0) (.44+1 1.240: 1.40 n L 1fa7 4.40411 1.1011 0. ::0. 0.0 409 9.3001 1.1324 •.4400 $:all)

Ir1..l 3.36+: C.41L) :. I.:: 1.(7U 4.14,1 0..40+ ).4130 0.0]111 i. JC U t.J+1. 9.030+ o.O 146 C.cn4 1.0,44 •.0008 1.9051

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311.•1 3.4430 1..707 ,.:0): 9.444) 0.4910 4.•),/ I. 4,31 1.1414 2.44,: :.:001 :. JOI. 1.41101 0. U n 1.1749 I. mo 0..301

1611.1 1. 1040 c.e )o, 4.1:16 4.1101 1.)911 0.1:49 :.) a ....Jr• 5.49.4 1.1,•1 1.4..0 6.1..1 :. a 1, 9.41 n t 9.11 n ,

et. /t n 3.40 0101 +.441 11.:1 0.+1 I.rl t. n 1.. a ,1.011 ++. a 1...• 1... ..117 1.+3 0. n I..,ol

FIGURE 3.23 SAME AS FIGURE 3.22, EXCEPT FOR FILE B.

4w J 
t 

^crNPL P1!^E 19 39

OF POOR QUALITY

ROWS

1981A 1 1. <0 10(41{ ...... 0.1,19 t.{f sf 1.9811 0.0000 0•f rfl /.1148 0.4000 4.8484 /•11,7 /. 131) 4.1117

{4011401

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;f .t• i.• :::-001c 4.(tl( [.l(1. 1.407. 1.001. O.OJ 10

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4

9.1(aa 9.4414 •.@ Na 0.0.37 9.018( ..t 110 0.09.3 4.4400 4.000, {. a U4 {.@498 1.11).

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INDCAST I

1).. 1 .1.. :Ir 111.. 1.,I I:Y: •

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1.1:.1.

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1, 1.710. .....1 148111 1.1//[ 1.1.11 6.6.4, 0.914! 4.1116 0.1011 1.1.,00 1.11., 1.1111 0. its) 4. 17.1 0.1041 r07,IL :I so(•

4 411

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I. call ..1 J(! 1.t 1001 @.1:13 •.7011 1.1411 00.1..1 t.0L...e t I, t.1soJ 0.7001 t.t 701 6.00It 0.011.

10.11 1.4481 •.101) 7. If :7 •.ten t. 1007 4.0711 1.1 41f^ . 7.98 9 J1;. 7.01.) 0.048 1 ..0411 ..)let 1 1 .11 7. J,J. 1.1798 7.048. C•13f. 1.:C 11 L.: 001. /fT 7,: t L•r I.IIso 1.0 1.1 0.71•• f.0aso 9408 lI 941 ,/1 N.11 0.11.• 0.4:13 !.C:O: •.1001 7447,. C 71t ).t•3. ^l ...t! .0 U. 1.lIN .n •4 4..1.1 4.1111 0.0139 1.71001

I

. .11 0.0)70 /.:348 !.[t J0 6.t:u 1.9011 C. .. !.1 1.:1 1..711 1.01!1 1.[141 t.: u, 1.11 4 1..1 4 1.1111

1.I1 7.1719 0.1717 I. ;G :1 8.8)11 /.,11. 1.1311 1.001, .1. 14 ).3.70 ,.1111 1.3110 4..100 9.91.4 9.0114 0.9181 I.i..1 4..11 4..711 1.401 1.:0:1 [.s Ht 0. .110 6.&331 7.001• .0111 a.01.. ..... ..e,N t. N.f 1.41.1 ..71,• Lso!• 0.1 .II

1.11.81 a. )c al t.17N l..aso 9.4)17 7.oi1a I.",. l.On l 11H t.t•1• t.11J1 0..111 .1111 1.01 , 7 1.:11. 1.GOIs a.l l..

141.11 14:04: t.t 747 1. :O0 t.c).-J ..1131 ..7[001 3.00). f. II 811, L N•1 .1111 I. 01•• 0.01.1 0400). 0.1101

III.11 •.:0)C t.soa) 0.]e )7 O. 1911 L .001 0.00.1 e. 7011 ,1711 f1! 0 I1f0 0.11 +I .8888 t. 011, h u 00 0.00:. 00.1 U ♦

111.11 1. o p . ..6817 .JC :1 e.c 107 ..so13 1. 900 ! e.IN L ON, .,•.1 1..1 L n f. 1.11.1 9..If! 7.0000 ..1111

161.11 O. c 07a I.. so 67 9.7071 1.c I1 7.011. a. I a • 1. I 1.0111 0.01+1 4.t l.o •1 9.9111 e. t0 rl L. n 13 0.0110 0041.,•

111.11 00.0: if @.0 )(• 9.14:. 0.. I01 :. Ie1• i. 131! 0.1 

I )

11 1!9.1011 1. 9C )i 0.00.1 O.000f O.0 14. I so.11 1.00)• ,.4307 LOOM t i so 7 7. )L 01 1.111. 1.013• [9011 L6t r / 1.44.1 444,1 1.1 e0. a. 00 J9 C..)OO 4..004 0.011.

111.11 0.0171 0.1000 Lea 71 J. 117 1. 7t 0t L Oate 1.0009 t.IOII I. Itaa .416)1 1.1111 I a I; ..1001 4.0036 0.0001 .. 1 1,0

11..71 ..$sit t. 1 a 10 1.1.11 1.9.01 ..tee. 7.100. 0. its/ 1.104 1.0!70 .403.4 1. ten 1.1100 I. 0000I a 3 a 3 0.03]1 1.1001

A.I.II I.f131 t.s:07 .•)416 I.1 )ea 1.000. •.lost J. g oal 0.0)11 I. I II I. soft 4.113. 9.4441 1.717. L 0coo 0.1011 1.111•

1 7 1 . 7.7141 I. 1 f al 1.:0)• 8.0174 t.)1 „ .061 .111 0 61 7 .. O..I , t ,.•110 ,.11.1 •.1,1 1 e. 161; e. 1111 7.1 7 .1

184/1

1

1I 1.11 G.O1 7. )) 4.17 1. :1 1 1 

1 7 1

.11 11..• 1.410 16 ..1 11.11 (t. 4 14.•7 .. 11 1.61 0.1 1 !. ....

NINDCAST II

,.)..III:. 776. 1.1 1+1 :•1 Lt I• I 1. I 10.G. I.IJ .:.) 6.10 . ,tt: 1 14. 11,... (,: 0 .. 9.1.1 .I 1 . 1.+9

r 4A 0.1 Ic1 0. J1 II c.4..1 ). I I.c 0.G11. ).]1:1 0.0111 7.011! O.1 a• 00.7„ t 0.10;1 0.11•r 0.{111 0.1111 t., 010 0. 3o 17 1a 1rfL

el /81,;04

1.13 0.)G]. 9.0 • ' 7.`4)0 0.0740 ).Coto 0.CJ01 e. oC01 C. 0301 a..... ...0 r1 e. 711. 041613 1.00001 O.c)0. 0.1001 e.0 )tl 11.01 644[:0 c. Ca01 7474 )[ 9.t7C1 ).)c)1 O.o1 . ' 0. 60 )1 0.0001 4.:41. 0498 It O..L , I.OJO• 0.0:01 c.9 )01 7. :0 )• 0.01 if )..n o. r. J1 0.0.01 ).)0000 {.13 a: 3.)004 Lo r. Ja:o 0.0601 0.000.1 0407 +r 0.4110 ..eon o. 00984 0.04,1 447011 0040 sot .9.13 6.00)0 ,.1303 1.004: 04,.03 ..7 v.•Lc J./

9 Alt a 6, 11 e 0or• 4 00)• 0 0,11

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7. 10[1 0.0064 0.006,1 848011 o. 1,98 ,.013. 0400,, 0.0098 J.1on 0.0 14

I•,+)

1.J:00 f.c)41 a.;o)e 0.:307 3. 1C )a 0.010: 1. 1c It 0.

e. 30014 9.1107 3. JO 7t O.C:17 7.)0 L. 1.1111 ..On2 y 1 0.17.1 o.uiV- Y"

weu • , t.. ...

H./1 • ..O IOr O.Oa tl 0.1111 7.:o )a L4)e) Lc13I 1..113 .1130 I.13c+ 0.011} 343,1 +t1 r I.InI 0.004 0.014 0.074 0.1400 1:•.11 7. ): J: 9.0)07 C. 1C )C L ,:C7 7.00 7/ (.07001 O. 00 r• ^ 111 .0111 1,0.11 1. 0+. 0.1)01 0.071A ..11. 9.1010 O.I. It 171.01 14.14 JO t. 1183 : .1041 0.0 )Cl 7. JC10 1.0 )al J. 701.00110 0. sot. 1..+. ...101 ...11 441.4 0.]00• t. 1301 11..11 D. 004:0 0.6 701 :.007. ).O 007 0.7077 e. 40[♦ 0

0 a01 e. 0011 2 0. 71,, ej^1.t.^r ...r•. 0404 00.014, 7443.4, 11..0! O. ::JO O.c:u Lcc 10 7.3731 ). cL 71 00.1]01 0.191• ).1341 T.altl 3.00) . ..n.. e.0 o:• 00.1,4 11+.11 O.O u 0 1.0013 L 9041 0.1)01 I Ica 1.O 0001 O. aco y 0..0 a. 40,00 11 t. 1111 .. a0 0.0111 0.000. 0.0101 t, 1 J 3 7. J0 JO e. 134 f. :7)t O.OeU Lac ]0 1.0301 0.0071 0.0011 0.00.1 0. 1 O. Ift1 ...... .. a 010 0.0311 7.0a a ..0111 111.01 o. JO IJ 0..011 o. 00)0 ..(30. o . 7000 0.0301 0.0030 o.000A a.a l l , 0.031. 7. sot. 1.0 a1. .. eo J.

11• 1 ]. JO JO t JC

0.0001 0.0070 0..117 , 11.11 e. l:)9 0.070) 7. IC ). 1.0)01 0.:0)0 0.0]11 a 0003 0.91:6 i. 0031 o.e]11 1.001, a. 0307 t. CC J) 1.0700 0.'.(700 0.0)11 .1. I: 70 O. :C 840401 ).7)70 0.0100) O.00n 0.000. 7.0910 O.Cilf 7.013, ,.00001 0.00]0 0.0100 0.7000 040081 711.11 O.:G JO 1.113) ). )0:1 3 O.LO )C 0.0 J7) ).;0300 t. 0:0) O.. C J, ..071, ..098. 0.0161 ]. oG ]0 C.0100 ).70 iC 0.0)1• 1 4411 0.)001 0.1781 4.)118 c.9 )G) e. 00)0 O.00aO 0.0071 /.0070. 0.0010 0.00710 c...0• e.. 7.0 . .... 0.00 P+0 0.)000 0.001. , 1 1,11 0.aso9 a. 130 0.001. t. 0,08 e.cc)a 0.0;:3 0.]00:1 a.e3n 0.)l i. 0.006. 0.4801 I..... c. 70980 O.O:Oi ..)070 00.11.4 l n .11 7.:030 i.ICO3 7. )C:1 I.Ie.. 1. 0(:I L G]:) 0.00)[ 0.00.0 1.300 a 0.0301 7.0101 14.,98 0.e 0900 0./0001 0.0000 L 00.1 980.4 /.340 4.0 37 .1.040 841304 1490). O.a:3o 0.64:, L13e1 00.7000 840700 1.414 L.ou 0.04:00 LaaOe 7400<. ..0413 111.11 7.0GJt 9.i )(1 c.3G )t 0.0 )I1 1.)0:0 0.0::0 0.000)0 0.1301 a. 303! 0.000. a....! ..... O.C9 )0 O.0 )07 6.70040 0.010• 3...1A 0. 00)) 4.1001 3.7:)1 C.1007 1.c c a a a.a a as 0.3031 I. 13)a 0. a 0a1 .. I01A t. toll L e a, O..OJO 0.0:07 0.1070 00.0 all

, C1•a 0.1071 O.OaO) .. OC OO 4.010... a. 11 ...all .. e./1 0..017 0.1111 /. H01 0. I!!1 O. ner 0.1..1 L 1744 0.0111

01.11 ; 1 3.31 e.Ci 0. 7• 0.01 7.41 I.rt 1.11 00.•1 I1. 01 1L H 11.11 11.•1 1.31 1. /t 0.11 I.• al

FIGURE 3.24 SAME AS FIGURE 3.22, EXCEPT FOR FILE C.
emu

4 4

is evidence, however that in nature, the growth of downwind wave energy

is suppressed relative to the growth rate modelled in the presence of a

significant background sea travelling off the local wind direction. There

is also a suggestion that the directional relaxation rate of wave energy

in a turning wind in the rear face of the spectrum is too fast in the

model. These deficiencies of the ODGP algorithm appear to be exagueraced in the SAIL model. That is, the adjustment of the spectrum on both

the forward and rear face to the local wind direction is so fast in the

SAIL model that the spectrum was almost always specified to have a unimodel directional distribution in the flight box. However, in the SAIL

model, the treatment of growth on the forward face and the directional

I

relaxation rate on the rear are readily tunable. ROWS type data provide

a hitherto unavailable and powerful basis for such model refinement.
41

0 4. QE2 Storm Study of Impact of SASS Winds on Sea State Specification.

4.1 Storm Description

The storm which battered the QE2 in September, 1978 has been the

subject of several intensive investigatians. Gyakum (1980) first collected ship logs and satellite images that allowed a far better definition

of the evolution of the storm from conventional data than was possible in

real time. In that study, he also began to investigate the physical mechanisms responsible for the development of the storm. Gyakum (1983 a, b)

hats recently completed a more comprehensive study of the dynamic and 

thermodynamic structure of the storm.

Cane and Cardone (1981) used the QE2 storm as the basis of a discussion of the potential value of SASS data in improving the detection and

forecasting of severe extratropical storms. As part of the evaluation

of SASS wind retrieval algorithms, Cardone provided an analysis of surface winds from conventional data alone in two orbit segments over the

E

QE2 storm (see Jones et al., 1982). The storm also was used in the

evaluation of SEASAT SMMA wind estimates (Cardone et al., 1983). Finally,

the storm scenario has been used to test various numerical weather forer

casting models. An extensive series of numerical experiments on the

QE2 storm was reported by Anthes et al. (1983).

A general picture of the evolution of the QE2 storm is depicted in

Figures 4.1 a-1, which are sections of the 6-hourly Northern Hemisphere

Surface Analyses prepared in real time at the NOAA National Meteorological

Center (NMC). The storm formed on a stationary front which extended from

the Great Lakes into the Atlantic near Delaware at OOOOGMT 9/9/78. A

small low on the New Jersey coast is shown on the front at 0600 GMT 9/9/78 F

as the first sign of development. By 1200 GMT the center had moved east-

;-- ward between two NOAA data buoys 44003 and 44004. At that time, buoy

`

44004 measured surface winds (at 5m) of 32 knots from the northwest, indicating that surface winds had already reached gale force. Winds also 

reached gale force on Georges Bank during the afternoon, where the fishing

dragger Captain Cosmo was lost.

The storm moved eastward at first early on the 10th then northeastward very rapidly, crossing the N. Atlantic shipping lanes on the 10th

owl 
VA. 

9

i

t

f2

R^' Jd

r

rr ^! 3s

^, •rri ^` • to _

Figure 4.1 a

OOOOGMT 09 September 1978

IN NO

1

b

.

y ^~

jI

i

^ ^ ^ ^^s• ^ ^` ^ Ifr Figure 4. 1 b

---t-_^_P57, 0600 GMT 09 September 1978

Figure 4.1 a-1. NMC final analysis surface weather maps at 6-hourly intervals.

0000 GMT 9 September 1978 - 1800 GMT 11 September 1978.

1

way
rl

y43

.

\ o,..

Figure 4.1 c

1200 "1T 09 September 1978

^`^',• "^` Figure 4.1 d

1800 GMT 09 September 1978

ORIGIN 4L PACE Ig

OF POOR QUALITY

I

6•
i 44

r.

yoo \ oll

j ^• z.

^ Sy

r

Figure 4.1 e

0000 GMT 10 September 1978

IT tyal^^

1 1

1 .

' Figure 4.1 f

// « 0600 GILT 10 September 1978

ORIGINAL RACE 19

OF POOR QOALIV
r^

•

V

r

1=^ 4 5

7

+v^

! ^

14

1. ,

'V.

s;♦oCC ^ ^

r^ f%r

^tt^^

rYe

— ^;'s+ ! ^;'•'i'=:^ Figure 4.1 g

1200 GMT 10 Se pte,.,ber 1978

tk

(u

Figure 4.1 h

1800 GMT 10 September 1978

UNIGINAL PAVE 19

OF POOR QUALITY
f ^^

11J^

N) ll`^

46

I0..

{

r

.tip A

:- Figure 4.1 i

0000 GMT 11 September 1978

♦ a4

f

Q

Figure 4.1 j

0600 GMT 11 September 1978

Ot?!GI"^.".L PAGE M

OF POOR QUALITY
v\ dam1

+ 47

v..;;

r p V

I . mot}

1

s^1 Figure 4.1 k

1200 SMT 11 September 1978

6 !'s

1

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Figure 4.1 1

i 1800 GMT 11 September 1978

OF POCR QIALIT
+ 48

.' and 11th before slowing and turning north late on the 11th, at which time

the size of the storm had grown to immense proportions, with its cyclonic

circulation covering almost all of the N. Atlantic Ocean north of 45 0N.

The NMC charts do not correctly depict the track and rate of 1*ntensification of the storm. Conventional data not available to the analyst in

real time however provide a reasonable estimate of the position and rate

of intensification as described by Gyakum (1980). Particularly useful

were DMSP satellite imagery and the synoptic reports and barograph received from the ship Euroliner. At 1200 GMT September 10, the Euroliner

observed a central pressure of 960,3 mb, winds of 58 knots and average

seas of 9 meters. The ship was located near 43 0 N,50'°W (see 4.1g), probably within 60 miles of the storm center,whieh was estimated to have a

central pressure of about 950 mb from an analysis of the barograph trace.

The corresponding NMC analyses shows a 980 mb low centered about 120 n.mi.

north of the ship.

+ Figure 4.2 shows the distribution of ship reports in the western

N. Atlantic available for 1200 GMT September 10 in the data base assembled

for this study. There are about a factor of two more reports in this

data base than available in real time. Figure 4.3 is an isobaric analysis constructed manually from the ship data. Such analyses constructed

at 6-hourly intervals through the storm evolution provided an excellent

initial estimate of storm wind field structure within which to incorporate

the SASS data. Figure 4.4 compares our final estimate of the time history

of central pressure and maximum surface wind in the QE2 storm with those

extracted from the NMC analyses. The maximum surface winds are derived

mainly from SASS data taken in orbits 1066, 1074, 1080, 1088, 1093/1094.

During the period of explosive development between 1200 GMT September ,9

and 1200 GMT September 10, cent'Pal pressure fell about 55 mb making -the

QE2 storm a "superbomb". Only modest deepening of the vortex was indicated on the NMC charts. It is thin period of explosive development that

was investigated intensively by Gyakum (1983) and Anthes et al, (1983).

On September 11, the day the QE2 actually encountered the storm, the central pressure and maximum winds in the storm had stabilized at near 976 tb

and 26 m/sec respectively. For the evaluation of the SASS wind retrieval
PAGE 19

JR QUALITY

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i 52

algorithm, Cardone composited all ship data within 12 hours of 1200 GMT

September. 11 with respect to the moving center and performed a detailed

kinematic analysis of the surface wind field for comparison with the SASS

data obtained in revs 1093 and 1094. Figure 4.5 shows a simplified streamline/isotach pattern, the location of the ship, the storm center and 

the boundaries of the SASS data. The QE2,travelling west-southwestward,

is shown entering the area of strongest winds, southeast of the storm

center. James (1979) has described the encounter of the vessel with the

storm. Figure 4.6, from James, gives a subjective analysis of the wave

height field in the storm and the tracks of the storm and the ship. The

avoidance maneuver taken by the Captain of the QE2 probably averted a

much greater threat to the ship.

4.2 SASS Data

Table 4.1 lists the revs used in this study. Coincidentally, each

rev segment occurred within 3 hours of the 0000 GMT and 1200 GMT standard

weather observation times. Only off-nadir SASS data were considered.

Schroeder et al; (1982) trace the development of various models

}! that relate surface winds from measurements of ocean normalized radar

,r

cross section (NRCS),measurements from initial versions based upon air-

,, craft data through to the final form used for the processing of the

entire SASS data set. That model was integrated into the SASS-1 algorithm.

SASS-1 provides estimates of the neutral stability wind vector at

the 19.5 m reference height. The concept of the neutral wind was introduced

by Cardone (1969); it is the wind speed that would result from a given wind

stress in a neutrally stratified atmosphere. The algorithm provided

estimates from so called cell pairs, each formed from a matching of measurements of NRCS from the forward and aft SASS antennas. 

Each SASS footprint represents an area 70 km by 17 km. The centers 

` of matched cells could be up to 35 km away. The NRCS pairs therefore may

represent approximately a 50 km circle, if the pairs are indeed colocated, 

or about 70 km, if they are separated by the maximum allowable distance.

For each cell pairing, the algorithm provides estimates of the true wind

sampled and up to three additional "aliases". Selection of the "true" b

wind estimate therefore requires an initial estimate of the wind direction,
53

i

r

ORIGINAL. PAG E 19

OF POOR QUALITY

60

20 ^T

+

t 55

\ / S^ORM \

/ F R I ^^

40

\\ E 2

/ I

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_ 20 40

+ \ / 

i

^ \ 2 \ I

/ 1 35

5

10 5

'b 50/ 45 / 40 ' \

y5/ \ \k

30 \o^g

\ \0

Figure 4.5 Kinematic analysis of surface wind field in QE2 storm

from conventional data alone for 1200 GMT September 11,

1978. Position of QE2 and limits of SASS data in revs

1093/1094 also shown.

I:
2/06 TORM

9 6

11 18 09 2

0•

06 976

I 18

/ •

.

60 0

13/ 0 r^ 11/0

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54

uHIG,NAL i AW

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SHIP

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20 •

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0 300

MOVE TS OF U N LIZABE H II A D STO M THA BATT RED

HER ITH WAVES

Track of the se%cre September storm in relation W the QUEEN ELIZABETH It. Notethedivcrsion

to the south that avoided the extreme naves.

60

H 'I

^%30'

20'

40 15'

60 . Io

S00

200

3 0 WAV CONDI q -on Z I I S PT 78

Significant wave height analysis for 0600 September 11, 1978.

Figure 4.6 Relative tracks of QE2 storm center and QE2 (above)

and subjective analyses of significant wave height at

0600 GMT September 11, 1978 (below) (from James, 1979).
55

TABLE 4.1 SEASAT Orbits in QE2 Storm

REV MODE DATE TIME (GMT)

1066

1074

1080

1088

1093

1094

Ascending

Descending

Ascending

Descending

Ascending

Ascending

September 09 1252-1257

September 10 0245-0250

September 10 1223-1228

September 11 0209-0219

September 11 1013-1023

September 11 1154-1202
56

though Wurtele et al. (1982) describe procedures based upon pattern 

recognition, for the selection of the true solution even in the absence

of in-situ data.

Figure 4.7 is an example of de-aliased SASS winds for rev 1093,

I

which viewed the eastern part of the QE2 storm. Figures 4.8 and 4.9

compare the wand speeds and direction from SASS for the selected solution and the winds provided by the kinematic analyses (Figure 4.5).

The data agree to within ±2 m/sec in wind speed and 16 0 in wind direction.

Figure 4.10 compares the SASS wind speeds and winds.observed by ships

within the area viewed by revs 1093/1094. Agreement is as good as could

be expected considering the errors at ships' wind observations.

The SASS data used in this study were provided by the Atmospheric

Environment Service, Canada. The data differ from the initial production

x processing of Seasat version data only in the use of cell grouping instead

of cell pairing. That is, the NRCS data are converted to winds after all

individual cells are binned over 100 km boxes. The binned data are believed to provide somewhat more accurate winds-, and to be more representative of the synoptic scale than winds derived from cell pairs,

though no evaluations of the reprocessed data have been reported to date.-

. 4.3 Wave Hindcast Experiments

Two numerical wave hindcasts of the QE2 storm were made. The first,

F ' or base case hindcast was intended to provide the most accurate specification of sea states possible. That hindcast used wind fields derived from

a combination of conventional and SASS wind data using the most accurate

wind field analysis techniques available. The second hindcast used wind

C} fields derived from the NMC surface analyses. This hindcast was intended

E to represent the best sea state specifications which could reasonably be

derived from operational data available in real time.

All QE2 hindcasts were made using tb- ODGP hindcast model adapted on

the two dimensional grid shown in Figure 4.11. The grid spacing is 1.250

in latitude and 2.5° in longitude, and extends basically from 20 O W to 80 0W

and 25 0 N to 67.5 0 N. The hindcasts simulated the 72.hour period beginning

at 0000 GMT September 9, which is 12 hours before the storm developed a

closed circulation south of Georges Bank.

t
TTT 4W

X11

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63

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206 308 707 70f 709 710 Ill 717 712 fl• fl y 7lf 717 flf flf 370 !7l 777 ]ff 77\ 775 7N >n 771 f71 7f0 ffl ff7 7f7 2>1 77

O

w

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LU'". I ! UUL

Figure 4.7 Dealiased wind sectors in rev 1093 from SASS-1

algorithm applied to SASS cell pairs.

URIC'%,^L PAG 9

OF POOH riJALITY
ORIGINAL PA!.:_ 19

OF POOR QUA-LiTY

58

30

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GROUND TRUTH WIND SPEED M/SEC

Figure 4.8 Comparison of SASS wind speed and kinematic

analysis (from Figure 4.5) wind speed in rev

1093.

M = . 8096

B = 1 •57q4

R = .8618

^, = QUALITY 1

. DUALITY 2

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GROUND TRUTH WIND DIRECTION DEG

Figure 4.9 Comparison of SASS wind direction and kinematic

analysis wind direction in rev 1093.
60

UR(GINAL PAC` 13

OF POOR QUHL;7y

30 -1 - 7-T—T-- T—r- T

SPOT RE PONT COMPARISON RCVS 1093/1091 V POI SIP

_ O RIAUFORT ISIIW71 (CORRECTED)

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SASS 1 AIGORITHM

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GROUND TRUTH WIND SPEED, -V'

I •

21 27 30

Figure 4.10 Comparison of SASS-1 wind speed and surface wind speed

reported by .hips within SASS swatF of revs 1093/1094.
C

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62 

4.3.1 Operational Wind fields

Wind fields for the. simulated operational sea state specification were

derived exclusively from the sea level pressure analyses shown on the 6-

hourly NMC Final Analyses Series (Figure 4.1). The procedure is objective

and is based upon the use of a model of the wind profile in the planetary

boundary layer (PBL) that relates the surface marine wind ­e loc,ty to the

local pressure gradient, the air-sea temperature differer, . nd the

atmosphere thermal advection.

The PBL model of Cardone (1969) was used. That model has been tested

in a number of studies, as reviewed by Cardone et al. (1980). The model

appears to be capable of providing unbiased estimates of the wind fields

from accurate pressure fields, to within ±2 m/sea and 20 0 (rms) in speed

and direction, respectively. In practice however, errors in the pressure

fields cause significantly larger wind field errors. For example, Overland

and Gemmill (1977) found the model to provide the most accurate wind fields

in the New York Bight of four methods tested. The specified winds were

: compared with winds measured at a NOAA data buoy over a period of five

F

.

months: for measured winds in excess of 12.5 m/s the PBL model winds had

rms errors of 2.9 m/s and negligible bias. Cardone et al. (1976b) used the

k

model to specify winds from N. Atlantic pressure analyses produced at FNOC

and found wind errors of 4.5 m /s. The increase in the errors from the New

York Bight and the open N. Atlantic reflects the greater errors in the

pressure fields for the open ocean area.

To provide pressure gradients for the PBL model for the QE2 storm, the

NMC isobaric analysis were digitized using a curve following digitizer.

' Pressures were interpolated to each wave model grid point from the digitized

pressures by fitting a polynomial surface locally at each point to the

nearest 8 points. Meridional and zonal pressure gradient components

were computed by centered differencing. The air-sea temperature difference

was specified at each point as a function of the local geostrophic wind

direction; the function provided maximum unstable stratification (Tair-sea

-8°C) for northerly winds and neutral stratification for southerly winds.

The thermal advection parameter was specified by assuming a mean airtemperature gradient.

w
FF

63

kg

4.3.2 Base Case Wind fields

The assimilation of SASS wind data in computer-based objective analysis

schemes remains a difficult problem because of the existence of multiple

wind solutions for each radar measurement. However, SASS data may be

readily assimilated using subjective kinematic analyses techniques provided there is sufficient conventional data to define a reasonably accurate

initial guess of the wind direction. The data base assembled from both

real time and non real time ship reports, as shown in Figure 4.2, provides

an excellent initial estimate of the streamline pattern about the QE2 storm.

The assimilation of SASS wind data was therefore straightforward. First,

maps such as Figure 4.2 were prepared at 12-hourly intervals, at the

standard Greenwich observing times nearest the time of the Seasat revs

(Table 4.2). Then the SASS multiple wind solutions were plotted at the

centers of the 100 km bins used for the cell grouping. The SASS wind

solution whose direction most nearly matched the direction of the initial

guess wind field was taken to be the "true" wind. Finally, a detailed

kinematic analysis was performed to the five maps containing the SASS winds.

The analyses procedure considered the slight time shift between the

SASS winds and ship data. The streamline/isotach analyses effectively

translated the SASS data into data void parts of the analyses by imposing

space/time continuity principles (see Cardone et al., 1980 for a more

complete discussion of kinematic analyses of surface marine wind fields).

Figures 4.12 and 4.13 are examples of the final kinematic analyses.

Figure 4.12 provides a view of the wind field about the QE2 storm at the

beginning of the 24 hour period of explosive deepening. SASS data from

both left and right side antennas were available. The data show the wind

field to be very asymmetric with respect to the center, with winds of

30-35 knots covering a large area west and south of the center. The center

of the storm is defined well by conventional ship and buoy data. The area

of very light winds extending northeastward from the center is confirmed

by both SASS and conventional data.

The kinematic analysis shown in Figure 4.13, defines the surface wind

field at the end of the period of explosive development. Only the left

side SASS scan was available for this rev but the wind field east of the

center was viewed about 12 hours earlier and later in revs 1074 and 1088
64

i 4'

TABLE 4.2 QE2 Storm Hindcast Wind Fields

Hour Date BASE CASE OPERATIONAL

k

GMT

0000 Sept 09 PBL NMC PBL/NMC Analyses

0600 Sept 09 Interpolated PBL/NMC Analyses

1200 Sept 09 Kinematic-rev 1066 PBL/NMC Analyses

1800 Sept 09 Interpolated PBL/NMC Analyses

0000 Sept 10 Kinematic-rev 1074 PBL/NMC Analyses

0600 Sept 10 Interpolated PBL/NMC Analyses

1200 Sept 10 Kinematic-rev 1080 PBL/NMC Analyses

1800 Sept 10 Interpolated PBL/NMC Analyses

r

0000 Sept 11 Kinematic-rev 1088 PBL/NMC Analyses

w 0600 Sept 11 Interpolated PBL/NMC Analyses

1200 Sept 11 Kinematic-rev 1093/94 PBL/NMC Analyses

1800 Sept 11 Interpolated PBL/NMC Analyses

0000 Sept 12 PBL/NMC PBL/NMC Analyses
I

65

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67

respectively. The streamline/isotach pattern shown in Figure 4.13 defines

the wind pattern after the storm has attained its minimum central pressure.

The asymmetric velocity pattern is basically maintained but maximum surface winds are about 58 knots west and south of the center. At this time,

however, winds of 50 knots or more also have extended into the NW quadrant

of the circulation.

In the following 24 hours, the kinematic analyses showed the storm

circulation expanding, with maximum winds slightly lower. At 1200 GMT

September 11, the SASS data from revs 1093/1094 allowed a further improvement of the fairly accurate initial guess wind field derived from postanalyses of conventional ship data (figure 4.5). Maximum surface winds

of 50-55 knots were observed by SASS mainly in the southern quadrant of

the storm, as depicted in the initial guess field, with the maximum wind

specified to be 54 knots.

The wave hindcast model is elviven by 6-hourly wind.fields. To pro-

. vide winds at the intermediate 6-hourly times (0600, 1800 GMT) from the

base case kinematic winds, a simple interpolation was performed which

averages grid point values of meridional and zonal wind components outside

the sphere of influence of the storm (defined by an effective radius of

the circulation specified externally); for grid points which lay inside

the radius of the circulation on the intermediate maps time, the winds

were averaged with respect to the storm center. This interpolation procedure effectively propagates the SASS data, available basically at 12-hour

intervals, to 6-hourly intervals as well.

4.3.3 Comparison of Base Case and Operational Hindcasts

The base case wind fields show that the surface wind field intensified.

without much change in shape, as the strongest winds were located consistently to the south of the center. Figure 4.4 compares the time history of

the maximum surface wind in the south quadrant of the circulation in the

alternate wind fields. The operational wind speeds are much lower south

of the center than the base case wind speeds until late in the history of

the storm on September 11 when the storm intensity is reasonably well

specified by conventional data.

Figure 4.14 compares the alternate surface wind fields in the storm
F

w 68

region at the time of maximum storm intensity (in terms of central pressure).

The conventional wind field has the storm center misplaced about 120 n.mi.

north of the true position, and the strongest winds northwest of the

center, while the SASS winds place the strongest winds south of the center.

The differences between the two wind fields are large and spatially coherent and therefore can be expected to induce larger differences in the

alternate wave hindcasts made from the two wind field series.

Such differences were indeed found. Table 4.3 gives mean and rms

differences i,n wind speed, wind direction and significant wave height

between the operational and base case hindcasts. The statistics were

completed only from data at grid points within the storm domain. The

domain specified expanded from approximately a 10 0 latitude by 150

longitude box centered on the storm early in the hindcast to a 20' latitude

by 30° longitude box at the end of the hindcast.

The wind speeds specified from conventional data were generally

• negatively biased with respect to the base case wind fields derived from

SASS data, with the largest errors found during the period of most rapid

• development. Mean differences in wind direction were small and rms differences were acceptably low, the latter a reflection of the ability to

specify the simple streamline pattern about a large cyclone from even

sparse conventional ship reports.

The errors in significant wave height given in Table 4.3 do not at

first glance appear excessive with mean errors generally under 1m. Of

more operational significance however are differences between the hindcasts in the specification of the location and severity of the maximum

storm generated sea states. Figure 4.15 compares the alternate significant wave height fields at 1200 GMT September 10. The wave height differences are very large _south of the center in the area of highest sea

states, where the operational hindcast is more than a factor of 2 low.

Twenty-four hours later (Figure 4.16) -the wave height pattern in the c

ventional hindcast is in better agreement with the base case hindcast but

peak significant wave heights are still much lower than the base case.

Figure 4.16b shows the 12-hour track of the QE2 during which the storm

encountered damaging sea states and veered to the south. The QE2 visual

....._ r: _.w.
69

TABLE 4.3

Errors relative to base case hindcast in hindcast

(operational) of surface wind and significant wave

height derived From conventional data alone. Base

case hindcast made from wind fields derived from

combined conventional and SASS data. Mean errors

are computed as operational minus base case hindcast.

Day/Hour

(GMT)

Sept 09 1200

Wind Speed

Mean RMS

(m/s)

-1.30 3.07

Wind

Direction

Mean RMS

(deg)

10.66 35.86

Significant

Wave Height

Mean RMS

(m)

- .43 .54

Sept 10 0000 -3.85 5.34 8.09 27.33 -1.09 1.19

r

` Sept 10 1200 -1.32 5.05 3.59 23.31 - .78 1.51

Y

Sept 11 0000 - .95 3.65 7.00 35.63 - .31 .93

Sept 11 1200 -1.43 4.01 8.19 36.58 - .30 .92

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wave height report of 39 feet average seas and individual wave heights in

excess of 50 feet, is entirely consistent with the location and level of

the maximum sea states of the base case hindcast.

The wave analyses available in real time considerably underestimated

the peak sea states in the QE2 storm even on September 11. Figure 4.17,

for example, is the NMC N. Atlantic wave height analyses for 1200 GMT

September 11. Peak sea states are a factor of four too low re.,lative to

the base case hindcast.

4.4 Wave Forecast Experiments

A series of experiments were performed with the ODGP wave model to

assess the impact of SASS data on sea state forecasts. Each experiment

consisted of the simulation of a 24-hour wave forecast starting from an

initial wave state specified from either the base case or operational hindcast. In all experiments, the simulated wave forecasts were verified

against the base case hindcast at 6-hourly intervals using the same regions

for the calculation of mean and rms errors in wind speed and significant

wave height specified for the comparison of the alternate hndcasts.

Five separate forecast runs were made. Three of the runs addressed

the 24-hour period of explosive development ending 1200 GMT September 10

from initial conditions specified for 1200 GMT September 9. Two of these

runs simulated wave forecasts made from operational pressure analyses and

forecasts, with the FNOC PE-model used to-to provide winds. The third

run used the base case hindcast initial state and pressure field forecasts ! 

reported by Anthes et al, (1983), who used SASS enhanced initial fields and

a high resolution numerical weather prediction model to simulate the period

of explosive development of the QE2 storm. The last two forecast runs

covered the 24-hour period prior to 1200 GMT September 11, at which time

peak storm sea states were indicated in the base case hindcast. These

two runs differed only in the initial state specification as described

below, with forecast winds provided from NMC PE-model surface pressure

field forecasts.

4.4.1 24-hour Forecasts from 1200 GMT September 9

Figure 4.18, (after Gyakum, 1983) shows the initial analysis and 12

and 24-hour forecast sea level pressure fields provided by the FNOC (formerly

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Figure 4.18 FNWC (presently FNOC) model analyses at

1200 GMT September 9, 1978 and 12-hour

and 24-hour forecast of sea level pressure

fields (solid lines are isobars at 4 mb

intervals). Minimum central pressures are

also shown. (from Gyakum, 1983a).
76

FNWC) PE-model in real time, for the period of explosive deepening. The

model captured less than 15% of the observed deepening, and moved the vortex too slowly. The center was forecast to 42 0 N, 61°W at 12 hours and 42°N,

57°W at 24 hours. Actual positions were 41°N, 57°W and 44 * N, 51°W, respectively.

One simulated forecast started from the initial wave state for 1200 GMT

September 9 calculated in the operational hindcast, with forecast winds

derived from the FNOC pressure fields using the same digitization scheme

and PBL model used for the operational hindcast. That forecast is compared

statistically to the base case hindcast in Table 4.4,. As expected large

negative biases characterize both the forecast wind speeds and wave heights

with rapid growth of wind speed errors in the first 12 hours and growth of

wave height errors to 24 hours.

A second run from the FNOC forecast pressure field was made but with

the forecast storm track adjusted to agree with the observed track. This

N procedure removed contributions to forecast errors from simple phase shifts k

in the forecast winds and wave height pattern. Table 4.5 gives the errors

found for this run. Much of the negative bias in the forecast fields

remains.

. Forecast winds for the third forecast covering this period were pro-

)

vided from experiment #4 of the series of QE2 storm numerical weather forecasts reported by Anthes et al, (1983). Figure 4.19 shows the properties

of that forecast at 24 hours. Experiment #4 was the control experiment in

Anthes et al. (1983) series. It used a numerical weather prediction model

with 90 km grid spacing, ten vexitical layers, simulation of the fluxes

of momentum, heat and water in the boundary layer, and a parameterization

for convective heating in the entire troposphere. Great care was taken in

their, study to provide as accurate an initial state as possible at 1200 GMT

September 9. Initial fields were provided by Gyakum (1983) from a combination of all conventional surface and upper air data and SASS winds over

the ocean from rev 1066.

The NWP model forecast provided a vortex with central pressure of

984mb at 24 hours at a position only 100 km from that observed, and maximum x

boundary layer winds of 32 m/s (estimated surface winds of 21 m/sec). We

a
{

77

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TABLE 4.4 

Errors relative to base case hindcast in 24-hour

forecast from 1200 GMT September 9 of surface

winds and significant wave heights based upon

operational FNOC surface pressure field forecasts.

Initial state for forecast specified from operational

hindcast. 

Day/Hour Forecast Wind Speed Wind Significant

(GMT) T Direction Wave Height

Mean RMS Mean RMS Mean RMS

(hours) (m/s) (deg) (m)

Sept 09 . 1200 0 -1.29 3.07 10.6 35.7 - .43 .54

' Sept 09 1800 6 -5.02 5.79 9.8 38.5 - .55 .66

Sept 10 OOOG 12 -7.02 8.08 3.0 50.2 -1.33 1.47

Sept 10 0600 18 -6.29 7.71 - 6.9 47.2 -1.74 2.09

Sept 10 1200 24 -6.67 8.36 - 9.4 65.3 -1.86 2.44
78

TABLE 4.5

Errors relative to base case hindcast, in 24 hour

forecast from 1200 GMT September 9, based upon

operational FNOC surface pressure field forecasts,

except forecast storm track adjusted to observed

track. Initial state for forecast specified from

operational hindcast.

Day /Hour Forecast 'Wind Speed Wind Significant

(GMT) T Direction Wave Height

Mean RMS Mean RMS Mean RMS

(hours (m /s) (deg) (m)

Sept 09 1200 0 -1.29 3.07 10.6 35.7 - .43 .54

Sept 09 1800 6 -4.46 5.67 12.7 33.6 - .57 ..71

Sept 10 0000 12 -5.52 6.95 - 1.1 30.0 -1.18 1.34

Sept 10 0600 18 -5.24 6.81 - 5.3 20.8 -1.50 1.89

Sept 10 1200 24 -4.80 6.81 - 7.7 37.1 -1.57 2.15
^k► ^t^v^^ t^ . M

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70• w 60' 50,

Figure 4.19 24-hour forecast boundary layer winds (streamlines

and isotachs, m/s) and sea level pressure (isobar

contour intervals 4 mb) in control experiment #4

of Anthes et al. (1983). Forecast verification

time is 1200 GMT September 10, 1978.

.0•

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30•
80

note that Anthes et al, (1983) were able to simulate almost all of the observed deepening in some sensitivity experiments through modification of

the numerics and physics of the models though usually at the expense of

accuracy of forecast track. For the purposes of our study, however, we

take their control experiment as representative of the impact of improved

initial state specification over the ocean (as may be provided by SASS)

on numerical forecasts of cyclogenesis with currect operational numerical

weather prediction models.

Table 4.6 gives the errors in sea state forecasts driven by the control experiment sea level pressure field forecasts. To be consistent with

the improved initial atmospheric states provided to the atmospheric model,

the initial wave state for the wave forecast was provided by the base case

hindcast. The errors are greatly reduced relative to the wave forecasts

made from operational atmospheric forecasts. Indeed at 24 hours, the

mean and rms wave height errors are comparable to errors achieved in hindcasts made from accurate wind fields. Maximum sea states are also reasonably well resolved, as shown in Figure 4.20, which compares the significant wave height fields at 24 hours derived from the FNOC and Anthes et al,

` atmospheric forecasts. Peak sea states however, in the latter forecast

were still about 20% lower than those of the base case hindcast peak.

4.4.2 24-hour Forecast from 1200 GMT September 10

Two forecast runs were made for the 24-hour period following the period

of explosive development, during which the storm pressure actually filled

(see Figure 4.4). For this period, sea level pressure forecasts were

taken from the operational NMC-PE atmospheric forecasts. Figure 4.21 shows

the 24-hour sea level pressure forecast from the NMC-PE model, The central

pressure is forecast to be about 20 mb higher than observed.

The two forecast runs both used wind fields derived from the NMC sea

level pressure field forecasts. 'One run, however, began with initial

states taken from the operational hindcast; for the second run the initial

state specification from the base case hindcast was used. Tables 4.7 and

4.8 give the errors for each run. The effect of the "perfect" initial state

is to provide a greatly improved forecast at 6-hours and 12 hours, but

the advantage in the initial state is largely lost by 24 hours. This is
8

OF P001f (:JALITY

TABLE 4.6

Errors relative to base case hindcast in 24 hour

forecast from 1200 GMT September 9, based upon sea

level pressure forecasts in QE2 storm from experiment #4 of Anthes et al. (1983). Initial state

for forecast specified from base case hindcast.

Day/Hour Forecast Wind Speed Wind Significant

(GMT) T Direction Wave Height

Mean RMS Mean RMS Mean RMS

(hours) (m/s) (deg) (m)

Sept 09 1200 0 0 0 0 0 0 0

Sept 09 1800 6 -1.15 2.90 7.64 23.7 -.07 .26

Sept 10 0000 12 5.03 7.58 29.4 -.26 .81

Sept 10 0600 18 -1.72 4.34 -1.54 13.9 -.19 1.04

Sept 10 1200 24 -2.30 5.46 -7.19 28.2 -.39 1.13
82

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TABLE 4.7

Errors relative to base case hindcast in 24 hour

forecast from 1200 GMT September 10, based upon

NMC model sea level pressure forecast. Initial

state specified from operational hindcast.

Day/Hour Forecast Wind Speed Wind Significant

(GMT) T Direction Wave Height

Mean RMS Mean RMS Mean RMS

( hours) (m/s) (deg) (m)

Sept 10 1200 0 -1.37 5.12 3.4 22.7 - .79 1.52

Sept 10 1800 6 -3.06 4.28 5.1 16.9 - .76 1.49

Sept 11 0000 12 -4.65 6.57 11.6 31.8 - .97 1.47

L

Sept 1.1 0600 18 -4.55 6.15 6.6 22.7 -1.40 2.02
83

OFTABLE 4.8

Errors relative to base case hindcast in 24 hour

forecast from 1200 . GMT September 10, based upon

NMC model sea level pressure forecast. Initial

state specified from base case hindcast.

x

Day/Hour Forecast Wind Speed Wind Significant

(GMT) T Direction Wave Height

Mean RMS Mean RMS Mean RMS

(hours) (m /s) (deg) (m)

Sept 10 1200 0 0 0 0 0 0 0

Sept 10 1800 6 -1.83 2.30 7.4 13.2 - .21 .29

Sept 11 0000 12 -4.65 6.57 11.6 31.8 - .71 .98

Sept 11 0600 18 -4.55 6.15 6.6 22.7 -1.16 1.64

Sept 11 1200 24 -3.95 6.03 2.6 44.8 -1.32 1.98

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86

seen also in the significant wave height Comparison for 24-hours shown in

Figures 4.22. Both forecasts show the maximum wave height to be about half

that specified in the base case hindcast. Thus, the effect of the improved

initial wave state is largely masked by large errors in ,forecast wands

after about 12 hours of forecast range.

The magnitude and location of the peak sea states specified in the

stimulated forecasts shown in Figure 4.22 is remarkably close to the

corresponding features of the 24-hour wave forecast used in real time by

the NMC and FNQC, as seen in their forecast wave contour analyses (Fig

ores 4.23 and 4.24). In view of those wave forecasts, which serve as

guidance to most operational marine warning and ship routing services, it

is not surprising that several merchant ships and the QE2 did not evade

the dangerous sea states generated by this storm.

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90 

5, Conclusions

1. The SEASAT-A SASS provided wind data with sufficient coverage in space

and time to allow the specification of the evoXution of the surface wind

field in the QE2 storm from an incipient vortex through the stage of

explosive deepening to the fully mature stage as a large N. Atlantic

extratropieal cyclone. The SASS data allowed identification of large

errors in wind fields derived from operational sea level pressure analyses

and therefore in the pressure fields themselves. There were large errors

found in the location of the center, in the location of the area of strongest

winds and in the magnitude of peak surface winds. Conventional ship data

aided greatly in the specification of the initial guess wind field used

for the selection of the correct SASS wind, but the conventional data base

assembled for this study consists of about twice the number of reports

available in real time. Future operational versions of SASS should provide far greater spatial and temporal coverage than SEASAT and should

therefore allow the detection of "bombs" in veryearly stages of development over the global oceans.

2. Ap?lication of a calibrated, validated spectral wave prediction model

to the QE2 storm together with alternate wind field histories showed that

extremely large errors can occur in wave analyses specified from conventional data alone. Given the probable errors in the surface wind history

derived from the SASS data (i 2 m/sec rms, negligible bias), the errors

in significant wave height in the base case hindcast are probably unbiased

with rms errors near-.75m. The hindcasts made from conventional data, however, were biased low by 1 m overall, but more significantly, that hind

cast underspecified the average wave heights in the area of highest waves

by a factor of 2 during the period of maximum deepening, and by about 30%

in the mature storm stage. An independent verification of the base case

hindcast from remote sensing data is not possible in the QE2 storm because

the 'Seasat-A altimeter war;; not operational during this period. However,

the wave hndcast model used for all the QE2 simulations has been extensively

validated against in-situ wave measurements in many severe historical storms,

including the storm in which ROWS directional spectra were acquired as
91

described in this report. The peak sea states specified in the base case

hindcast also agree well with visual wave height estimates made from the

QE2 during its encounter with the storm.

3. Simulated wave forecasts made from operational numerical weather pre

diction products agree closely with operational wave Forecasts issued

in real time from NMC and FNOC. Those forecasts seriously underpredicted

the wave heights in the area of maximum seas. Since three very different

wave forecast models produced very similar wave forecasts, it can be safely

concluded that errors in forecast wind fields are the dominant source of

errors in operational wave forecasts for storms of the type studied.

4. The degree to which SASS marine wind data can improve numerical weather forecasts remains a somewhat controversial issue. Most likely, the

SASS data will show beneficial impact if combined with conventional data

such that the sea level pressure field and the geopotential distribution

in the entire troposphere may be updated. Such a procedure was followed

a

for the numerical weather prediction experiments reported by Anthes et al.

(1983). They found significant improvements in atmospheric forecasts

of the explosive development, which were translated in this study to significantly improved sea state predictions.

5. Remote sensing wind data, augmented possibly by remote sensing wave

data, applied operationally with a calibrated numerical spectral ocean

wave model will allow accurate monitoring of the state of the sea globally.

The resulting improved initial state specification for wave forecast systems should alone cause greatly improved short range (1.2-24 hour,) wave '

forecasts in severe storms, and improved swell forecasts at larger range.

However, improved sea state forecasts in storms beyond 24 hours will

require improved operational numerical prediction of cyclogenesis and

cyclone intensification.

6. Finally, all of our conclusions must be qualified as tentative, because they are based upon study of just or,e case. The QE2 storm, however,

was special only in the sense that it was viewed by SASS during the short
92

Seasat experiment, and caused damage to a luxury oceanliner. Otherwise,

the QE2 storm was a typical strong bomb, and the errors observed in conventional analyses and Forecasts were quite typical of those observed in

most such storms (see e.g. Sanders and Gyakum, 1980). We can be therefore more confident that the improvements in sea state analyses and

forecasts to be derived from remote sensing data suggested by this ztudy,

would be realized routinely from data provided by an operational oceanographic remote sensing satellite system.
93

REFERENCES

R,A. Anthes, Y.H. Kuo and J.R. Gyakum. Numerical Simulations of a Case

of Explosive Marine Cyclogenesis. Monthly Weather Review, 111, 1983.

pp. 1174-1188.

M. Cane, V.J. Cardone, I. Halberstam, M. Halem. On the Sensitivity of

Numerical Weather Prediction to Remotely Sensed Surface Wind and

Temperature Data. A Simulation Study. Journal of Geophysical Research,

86, 1981. pp. 8093-8106.

M.A. Cane, V.J. Cardone. The Potential Impact of Scatterometry on Oceanography: A Wave Forecasuing Case. Oceanography From Space, Edited by

J.F.R. Gower, Plenum Publishing Corp., 1981. pp. 587-595.

V.J. Cardone. Specification of the Wind Field Distribution in the Marine

Boundary Layer for Wave Forecasting. Report TR-69-1, Geophys. Sci. Lab,

New York University. Available from NTIS AD#702-490, 1969.

V.J. Cardone, W.J. Pierson and E.G. Ward. Hindcasting the Directional

Spectrum of Hurricane Generated Waves. J. of Petrol. Tech., 28, 1976.

pp. 385-394.

V.J. Cardone, J.D. Young, W.J. Pierson, R.K. Moore, J.A. Greenwood,

C.V. Greenwood, A.K. Fung, R. Salfi, H.L. Chan, M. Afarani, M. Komen.

The Measurement of the Winds near the Ocean Surface with a RadiometerScatterometer on SKYLAB. 1976b. NASA Johnson Space Center, Houston, TX,

Final Report on EPN 550, Contract # NAS-9-13642.

V.J. Cardone, and D.B. Ross. State-of-the-art Wave Prediction Methods and

Data Requirements. Ocean Wave Climate, Edited by M.D. Earle and

A. Malahoff, Plenum Publishing Corporation, 1979. pp. 61-91.

V.J. Cardone, A.J. Broccoli, C.V. Greenwood and J.A. Greenwood. Error

Characteristics of Extratropical Storm Wind Fields Specified from

Historical Data. J. of Petrol Tech. 32, 1980. pp. 873-880.

V.J. Cardone, T. Chester and R. Lipes. Evaluation of SEASAT SMMR Wind

Speed Measurements. J. of Geophy. Res., 88, 1983. pp. 1709-,1726.

G.Z. Forristall, E.G. Ward, V.J. Cardone and L.E. Borgmau. The Directional

Spectra and Kinematics of Surface Waves in Tropical Storm Delia. J. of

Phys. Oceanogr., 8, 1978. pp. 888-909.

G.Z. Forristall, E.G. Ward and V.J. Cardone. Directional Wave Spectra

and Wave Kinematics in Hurricanes Carmen and Eloise. Seventeenth International Conference on Coastal Engineering. 1980.- Sydney, Australia.

J.A. Greenwood and V.J. Cardone. Development of a Global Ocean Wave'Propagation Algorithm. Final Report to U.S. Navy Fleet Numerical Weather Central,

Monterey, Calif., Contract N-00226-76-C-3081, 1977. 
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J.A. Greenwood, V.J. Cardone, L.M. Lawson. Intercomparison Test Version of

the SAIL Wave Model. 1983. To appear in proceedings of IUCRM Symposium on

Wave Dynamics and Radio Probing of the Ocean Surface, May 13-20, 1981,

Miami Beach, Florida.

J.R. Gyakum. On the Evolution of the QE II Storm. Preprints, Eighth

Weather Forecasting and Analysis Conference. AMS, Boston, 1980

PP• 23-28.

J.A. Gyakum. On the Evolution of the QE II Storm. I: Synoptic Aspects.

Mon. Wea. Rev.,111, 1983. pp. 1137-1155.

J.R. Gyakum. On the Evolution of the QE II Storm. II: Dynamic and

Thermodynamic Structure. Mon. Wea Rev.,111, 1983. pp. 1156-1173.

F.C. Jackson. An Analysis of Short Pulse and Dual Frequency Radar

Techniques for Measuring Ocean Wave Spectra from Satellites. Radio Sci.,

16, 1981. pp. 1485-1500.

F.C. Jackson, W.T. Walton and P.L. Baker. Aircraft and Satellite Measurement of Ocean Wave Directional Spectra using Scanning-Beam Microwave

Radars. NASA Technical Memorandum 84008, Goddard Space Flight Center,

Greenbelt, Maryland 20771, 1982.

F.C. Jackson. Microwave Radar Oceanographic Investigations. Proposal to

continue RTOP 161-80-22-20 submitted by NASA Goddard Space Flight Center

to Oceanic Processes Branch, NASA Headquarters, Washington D.C., July 18,

1983.

F.C. Jackson, W.T. Walton and P.L. Baker. Aircraft and Satellite Measurement of Ocean Wave Directional Spectra using Scanning Beam Microwave

Radars. In. Proc. Symp. Wave Dynamics and Radio Probing of the Ocean

Surface, edited by O.M. Phillips, Plenum Press, 1, 983. in press).

R.W. James. Anatomy of a Storm. Mara Wea.Log, 23, 1979. pp. 71-75.

W.L. Jones, L.C. Schroeder, D.H. Boggs, E.M. Bracalente, R.A. Brown,

G.J. Dame, W.J. Pierson, and F.J. Wentz. The SEASAT-A Satellite

Scatterometer: The Geophysical Evaluation of Remotely Sensed Wind

Vectors over the Ocean. J. Geophys. Res, 87, 1982. pp 3297-3317.

C. Leary. Systematic Errors in Operational National Meteorological Center

Primitive Equation Surface Prognoses. Mon. Wea. Rev., 99, pp. 409-413.

Oceanweather. Development and Evaluation of a Coupled Discrete Wave

Prediction Model. Final report submitted to NOAH AOML SAIL 1983.

Contract # NA80RA000038.

J.E. Overland and W.H. Gemmill. Marine Winds in the New York Bight.

Mon. 'Wea. Rev., 105, 1977. pp 1003-3,008.
98

W.J. Pierson, L.J. Tick and L. Baer. Computer based Procedures for

Preparing Global Wave Forecasts and Wind Field Analyses Capable of

Using Wave Data Obtained by a Spacecraft. In: Sixth Naval Hydrodynamics

Symposium, ACR-136, Office of Naval Research, Dept. of the Navy, Washington

D.C., 1966. pp. 499-832.

W.J. Pierson. Highlights of the SEASAT-SASS Program: A review. Satellite

Microwave Remote Sensing, edited by T.U. Allan, Publishers Ellis Horwo^d

Limited. 1983.

A.J. Reece and V.J. Cardone. Test of Wave Hindcast Model Results Against

Measurements during Four Different Meteorological Systems. OTC #4323.

14th Annual OTC in Houston, TX, May 3-6, 1982

F. Sanders and J.R. Gyakum. Synoptic-Dynamic Climatology of the "Bomb".

Mon. Wea. Rev., 108, 1980. pp. 1589-1606.

SWAMP (Sea Wave Modelling Project). An Intercomparison Study of Wind

Wave Prediction Models. The SWMAP Group, 24 authors. To appear in

Proceedings of IUCRM Symposium on Wave Dynamics and Radio Probing of

the Ocean Surface, May 13-20, 1981, Miami Beach, Florida. 1983.

L.C. Schroeder, D.H. Boggs, G. Dome; I.M. Halberstam; W.L. Jones,

W.J. Pierson, and F.J. Wentz. The Relationship between Wind Vector and

Normalized Radar Cross Sections used to derive SEASAT-A Satellite

Scatterometer Winds. Journal Geophys. Res., 87, 1982. pp. 3318-3336.

M.G. Wurtele, P.M. Woiceshyn, S. Peterherych, M. Borowski and W.S. Appleby.

Wind Direction Alias Removal Studies of SEASAT Scatterometer-derived

Wind fields. Journal of Geophys. Res., 87, 1982. pp. 3365-3377.

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