Reanalysis at NCEP: Past, Present and Future
Robert Kistler1, NCEP Staff, Contractors, andVisiting Scientists, Past and Present2
1

NCEP/SAIC, USA
2

NCEP, USACorrespondence: robert.kistler@noaa.gov
Introduction to Reanalysis
It was 1990. Ron McPherson was the Director of the National Meteorological Center (NMC now NCEP, see
the Appendix for an explanation of acronyms), Eugenia Kalnay was the Chief of the Development Division (now theEnvironmental Modeling Center, EMC) , David Rodenhuis, the Chief of the Climate Analysis Center (CAC now CPC) ,and Masao Kanamitsu was the Development Division Modeling Branch Chief. The National Atmospheric and Oceanic
Administration (NOAA) had just replaced two Cyber 205’s with a Cray YMP-8 in record time due to the insolvency ofthe Cyber’s parent company. Along with the Cray came its UNIX like UNICOS operating system which eventuallywould permeate every NCEP computer system.
In the fall of 1990 Eugenia asked me to prepare a set of specifications for a major research project thatRodenhuis and the staff of CAC saw as the solution to the problem of trying to extract climate signals from the NMC
Global Data Assimilation System (GDAS). An example of a problematic time series, originally from Kalnay et al., 1996,
is shown in Figure 1. CPC staff was proposing a separate, frozen system to be known as the Climate Data Assimilation
System (CDAS). However, they realized that CDAS
would need to be extended backward as far as sufficient
observations were available, and, more importantly,
would need to be created in a timely manner. My initial
reaction, which I kept to myself, was “You can’t beserious!” I soon confirmed with tests on the newly
acquired Cray YMP8 that the computational
requirements dictated the acquisition of another YMP8,
which seemed absolutely unobtainable. Assuming wewere able to obtain the unobtainable, my two decades ofexperience were fraught with non-robust numericalsystems, error prone observations, manual storage
systems and a funding environment where development
projects were the first to be cut when the inevitablebudget crisis arose. All that was about to change.
An analysis of NCEP’s strengths andweaknesses revealed a need for partners to obtain quality
controlled historical observations and to distribute themultiple decades of output. Further inquiries revealed
that NCAR could service both functions. A formal
partnership was arranged in which Eugenia and Roy Jenne, NCAR, served as the principle investigators. A workshop
was held at NMC April 25-26, 1991 (Kalnay and Jenne, 1991) to announce the project and get feedback regarding theinitial planning. The issue of system robustness had been addressed by the advent of a 3D-VAR type analysis at NMC(Derber, Parrish and Lord, 1991). Stable funding was to be supplied by NOAA’s Office of Global Programs (OGP) andoverseen by Mike Coughlin. The storage issues were addressed by the acquisition of a robotic silo and Cray’s tapemanagement system. A pilot test, Mo et al., 1995, showed that we had assembled a viable system. A plan, NMC Office
Note 401, was in place. We began in April 1994, started CDAS in 1995, and completed 50 years of reanalysis in
mid-1997.
The visionary decision to seek a broad distribution via CD-ROM’s, first published along with the twoNCEP/NCAR Reanalysis BAMS articles (Kalnay et al., 1996 and Kistler et al., 2001), and thereafter by NCAR, wasaffirmed in 2003. Eugenia received an email from the ISI Web of Science noting that the 1996 paper was the most cited
paper in Geosciences in the last decade, and that the 2001 paper was among leading paper in the previous year.
According to Chi Fan of NCAR, by 2004 868 orders had been received from 54 countries and 11508 CD-ROMS hadbeen delivered.

In 2001, the every-fifth-day frequency of 16.5 day 0000 GMT forecasts was increased to 1xdaily, and thesequence of daily forecasts was extended back to 1996. This enabled month-by-month assessments of the performanceof the operational GFS compared to the CDAS forecasts. Figure 2a compares yearly NH and SH scores since theinception of GFS scoring in the mid -1980’s, and Figure 2c plots the improvement of the GFS by plotting GFS minus
CDAS along with the trend lines for each hemisphere.

Anomaly Correlation
500 mb 5 Day Forecasts

Anomaly Correlation
500 mb 5 Day Forecasts

90

Annual Avg 1982-2005_R2
R1
NH 72.3 70.5
SH 63.3 61.9

908080NH GFSSH GFS
NH CDAS/R1
SH CDAS/R170

NH CFS R2
SH CFS R2
NH CDAS/R1
SH CDAS/R1706060505040401982

1987

1992

1997

2002

2007

1982

1987

1992500 mb AC NH SH
GFS - CDAS

199720022007

Anomaly Correlation
500 mb 5 Day Forecasts

Annual Avg 1982-2005
CFSRR R2
NH 74.672.3
SH 71.1
63.3

2090

1580

NH CFSRR T62
SH CFSRR T62
NH CFS R2
SH CFS R2

1070

NH5SH
Linear (NH)Linear (SH)6001990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

50-5401982

198719921997

2002-10Figure 2. Northern Hemisphere (NH) and Southern Hemisphere (SH) yearly averaged anomaly correlation scores(x100) at day 5 between 1992 and 2007; a) top left, GFS vs. GR1; b)top right, CFS R2 vs. GR1; c) bottom left (GFSminus GR1) and trend lines; d) CFSRR vs. CFS GR2

NCEP/DOE Global Reanalysis 2 (GR2)
The inevitable problems that arose from GR1’s being a pioneering endeavor motivated a follow-up effort with astart in 1979, the NCEP/DOE Reanalysis, GR2 (Kanamitsu et al., 2002). By securing time on the DOE computers atLawrence Livermore, GR2 could begin to repeat the problematic GR1 years. A summary of GR1 vs. GR2 is found inTable1. Two of the items should be highlighted since they would carry forward into the future. First, the errors in theGR1 observational database were corrected, creating a quality controlled set of observations. In hindsight, the mostsignificant modeling innovation of GR2 was the replacement of soil moisture relaxation to climatology with rainfall

from CMAP pentads, the first of a continuing effort in what has come to be known as Land Data Assimilation (LDAS).
As will be noted in following sections, GR2 has served as the foundation of several subsequent NCEP
developments. Forecasts from GR2 were not made until the development of the CFS (Saha et al., 2006). Figure 2bcompares scores from the T62L28 GR1 with the T62L64 CFS model initialized from GR2 for the period 1982-2005; thelatter system makes a slight improvement in the SH, and a larger one in the NH, which may be attributed to theimproved parameterizations, higher vertical resolution, and more realistic soil moisture working over the continentalareas.

Table 1. Comparison of GR1 and GR2

NCEP/NCAR
R1 vs R2
Similarities…
1) same spatial and temporal resolution as R-1—T62L28, 6 hour cycle2) similar raw observational data(some additional data after 1993);
3) Special Sensor Microwave Imager (SSM/I) data not used
4) same NESDIS temperature retrievals;5) similar output variables and file formats(GRIB and BUFR).
New system components:
1) simple rainfall assimilation over land2) smoothed orography3) treatment of snow.
Model physics improvements:
1) implementation of planetary boundary layer that utilizes nonlocal
diffusion2) new shortwave radiation
3) minor tuning of convective parameterization;4) more realistic cloud-top cooling5) updated cloud-tuning coefficients for stratus clouds6) radiation on full Gaussian grid7) radiation run hourly vs 3h in R-1.

Error fixes from R-1 to R-2(after R-1 system was frozen)
1) fixed Southern Hemisphere bogus data (PAOBS) problem (1979–92),2) fixed snow cover analysis error (1974–94),
3) fixed humidity diffusion to remove“spectral snow” problem,4) fixed oceanic albedo (entire period),5) removed discontinuities in relative humidity/cloudiness relationshiptable at 0° and 180° (entire period)6) fixed snowmelt term (entire period).

Fixed field improvements:
1) improved desert albedo
2) sea-ice and SST fields (AMIP-II, provided by PCMDI)
3) new ozone climatology
4) Northern Hemisphere snow cover analysis (interpolated fromweekly to daily values)5) CO2 set to 350 ppmv (AMIP-II specified constant).
Improvement to the diagnostics:
1) better diagnostic fields of clouds2) fixed snow–water budget diagnostics.

North American Regional Reanalysis (NARR)
The period from 1997, the end of GR1, to 2003, the next NCEP reanalysis, NARR, was a period of rapidtransformations. Several crises (Cray fire, asbestos in FOB 4, and the terrorist attacks) prompted a rapid transition from
Cray to IBM massive parallel machines, a stable contract for future upgrades, and reliable mirrored machine
configurations at commercially maintained sites. The marked improvement and convergence of NH and SH GFS scoresin this period in Fig 2a are attributed to the 1) direct assimilation of radiances and other 3D-VAR advances, 2)
replacement of RTOVS with ATOVS instruments, and 3) increased model resolution and improved physicalparameterizations. As originally envisioned by Dave Rodenhuis in 1990, Wesley Ebisuzaki of CPC became thecaretaker of both GR1 and GR2 running in CDAS mode.
While resources were readily available, they were limited, so it was decided to focus global climate modelingon the development of the coupled CFS, and devote the next reanalysis to a regional effort using the NCEP ETA modelat 32 km and 45 levels. By focusing over the data rich North American area, it would be possible to exploit the newly
introduced Noah land surface model, and directly assimilate observed precipitation as noted in Mesinger et al., 2004.
Lastly, the 3dVAR analysis which covered a significant portion of the Atlantic and Pacific would use the newly
developed direct assimilation of radiances.
One question posed by NARR was the ability to access historical NESDIS radiances. Jack Woollen began aworking relation with NESDIS and its Class archive to offload historical radiances in bulk, which NARR was the firstbeneficiary. NARR also benefited from the first IBM upgrade, using a robust “just replaced” system to run 4

consecutive streams and complete the 1979-2003 period in just 3 months. The NARR took advantage of the GR2
quality controlled observational database as well as the GR2 analyses to drive the boundaries of the limited area ETA
model. NARR output had two notable upgrades. Its BAMS article was accompanied by a DVD, and users could accessarchive files via the internet from NCDC’s NOMAD servers.

Historical Northeast US Snowstorms
In 2002, the director of NCEP, Dr. Louis Uccellini, visited ECMWF and saw ERA 40 depictions of Northeast
U.S. snowstorms, which had far greater detail than the analyses produced by the lower resolution GR1. Independently,
EMC was rerunning past storm cases with the newly upgraded T254L64 GFS/GDAS systems. Feb 2003 was the 25thanniversary of the Boston Blizzard of 1978 (Brown and Olson, 1979), and I reran the case based on the success we hadin GR1 with the Appalachian storm of Nov, 1950. When Dr Uccellini saw the resulting maps, he proposed thereanalysis of the historical 73 cases for the period 1947 - 2003 that comprise the contents of the two volume monograph(Kocin and Uccellini, 2004) using the current global system.
Additional motivations for revisiting the historical cases were provided by the Jan 2004 symposiums for Fred
Sanders and Norm Phillips at the annual AMS meeting in Seattle, WA. In tribute to each, we targeted 2 storms toreanalyze and reforecast: the December 1947 NYC record storm, when Fred Sanders was a forecaster at LaGuardia
Airport, and the November 1950 Great Appalachian Storm, when the early numerical forecasts of Norm and Jules
Charney are attributed to the advent of operational NWP in the United States.
The AMS website (http://ams.confex.com/ams/84Annual/techprogram/meeting_84Annual.htm) contains thepresentations. In addition, the Sanders presentation has been expanded and included in an AMS Monograph (Uccelliniet al., 2008)
Climate Forecast System Reanalysis and Reforecasts (CFSRR)
As noted previously, NCEP climate modeling efforts earlier this decade concentrated on building a coupled
ocean-atmosphere prediction system for monthly and seasonal forecasts. This effort came to fruition in 2004 when theClimate Forecast System (CFS) became operational in August (Saha et al., 2006), and as noted in that paper, “The CFS

CFSRR at NCEP
Climate Forecast System
GDAS
GSI

6hr

24hr

LDAS

Atmospheric Model
GFS (2007)
T382 64 levels
6hr

Land Model

Ice Model

Ocean Model
MOMv4
fully global
1/2ox1/2o (1/4o in tropics)
40 levels

Ice Ext
6hr

GODAS
3DVAR

Figure 3. Climate Forecast System Reanalysis and Reforecasts (CFSRR)
includes a comprehensive set of retrospective runs that are used to calibrate and evaluate the skill of its forecasts. Eachrun is a full 9-month integration. The retrospective period covers all 12 calendar months in the 24 years from 1981 to2004. Runs are initiated from 15 initial conditions that span each month, amounting to a total of 4320 runs. Since eachrun is a 9-month integration, the CFS was run for an equivalent of 3240 yr!”Those retrospective runs were possible because of the existence of a set of consistent initial conditions provided
by GR2. In order to upgrade the CFS in 2010, it will be necessary to replace the GR2 initial conditions with a newreanalysis from 1979-2009 and rerun the reforecasts for 1981-2009. The atmospheric and land assimilation of CFSRR
reanalysis will be based on the NCEP GDAS to be implemented into operations in 2008, and will be coupled with theGODAS reanalysis. Reforecasts will be run with a coupled land-ocean-ice-atmosphere system.
A more complete report on the CFSRR system and plans is given in this volume under the title “the New
Reanalysis and Reforecast of the NCEP Climate Forecast System (CFSRR) by S. Saha et al.” (G5-513). A schematic of
the CFRSS coupled system is shown in Figure 3. One preliminary result is available from a “Practice System” test
which ran 29 streams (1 per year) through the entire period 1979-2007 using a reduced resolution version of the GDAS,
T62L64, without the ocean component, and a preliminary version of the SST analyses. Figure 2d compares the yearly
averaged hemispheric 5 day forecasts scores with the comparable CFS forecasts using R2 as the initial condition. While
the scores for the CFSRR are better in both hemispheres, the improvement in the SH make the scores relatively closer tothose for the NH, as is seen in the last several years of the GFS as noted earlier in Figure 2a. Since the CFSRR system iscomparable in resolution to the GFS system of 2007, we expect the skill of the initial conditions of the CFSRR to becomparable to the present GFS for the 1999-2007 ATOVS period, but to be somewhat lower during the1979-1998
RTOVS period.
Future Reanalyses
A fundamental change in the allocation of computer resources for future NCEP reanalyses and reforecasts isincluded in the EMC plans for the future, as early as the next upgrade cycle (see Figure 4). With the CFS operational
since 2004, and its continued improvement depending upon a set upgraded reanalyses and reforecasts, future NCEP
production job suites will have dedicated time and computational nodes devoted to the running of reanalyses andreforecasts. In addition, upgrades to the NARR will alternate with the global system.
Future systems will also benefit from the collaboration that has begun between NCEP/EMC and theNASA/GMAO MEERA project. (See the extended abstract by Schubert, et. al. V1-104). Both systems share the NCEP
GSI analysis program and common observation databases.

Figure 4. NCEP Production Suite including Reanalysis/Reforecasts in the next computer upgrade
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February1978. Bull. Amer. Meteor. Soc., 59, 562–575
Kalnay, E. and R. Jenne, 1991: Summary of the NMC/NCAR reanalysis workshop of April 1991. Bull. Amer. Meteor.

Soc., 72, 1897-1904.
Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y.
Zhu, A. Leetmaa, B. Reynolds, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. Mo, C. Ropelewski, J. Wang, R.
Jenne, and D. Joseph, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.
Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.K. Yang, J.J. Hnilo, M. Fiorino, and G.L. Potter, 2002: NCEP–DOE
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Meteor. Monogr., 22, No. 44, 280 pp.
Kocin, P. J., and L. W. Uccellini, 2004: Northeast Snowstorms. 2004. Meteor. Monogr. 32, No. 54, 818 pp
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Berbery, M.B. Ek, Y. Fan, R. Grumbine, W. Higgins, H. Li, Y. Lin, G. Manikin, D. Parrish, and W. Shi, 2006: North
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Saha, S., S. Nadiga, C. Thiaw, J. Wang, W. Wang, Q. Zhang, H.M. Van den Dool, H.L. Pan, S. Moorthi, D. Behringer, D.
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Climate, 19, 3483–3517.
Uccellini, Louis W., Paul J. Kocin, Joseph Sienkiewicz, Robert Kistler, Michael Baker, 2008: Fred Sander’s Roles in theTransformation of Synoptic Meteorology, the Prediction of Rapid Cyclogenisis, The Prediction of Marine Cyclones, andthe Forecast of New York City’s ”Big Snow” of 1947, AMS Monograph, in press.

AppendixAcronyms
AMIP Atmospheric Model Intercomparison Project
ATOVS Advanced TIROS Operational Vertical
BAMS Bulletin of the American MeteorologicalSociety
BUFR Binary Universal Form for the Representationof meteorological data
CDAS Climate Data Assimilation SystemCFS
Climate Forecast System
CFSRR Climate Forecast System Reanalysis andReforecasts
CDROM Compact Disc read-only memory
CMAP CPC Merged Analysis of Precipitation
CPCClimate Prediction Center
DVD Digital Versatile DiscECMWF European Center for Medium Range WeatherForecasts
EMC Environmental Modeling Center
FOB 4 Federal Office Build 4, Suitland MD
GR1 Global Reanalysis 1 (NCEP/NCAR Reanalysis)
GR2
Global Reanalysis 2 (NCEP-DOE Reanalysis)
GRIB GRIdded Binary
GDAS Global Data Assimilation System
GFS
Global Forecast System
GMAO Global Modeling and Assimilation Office
GODAS Global Ocean Data Assimilation System

GFDL Geophysical Fluid Dynamics Laboratory
GSI Gridded Statistical Interpolation
LDAS Land Data Assimilation System
MEERA Modern Era Retrospective-Analysis for
Research and Applications
MOM GFDL Modular Ocean Model
NARR North American Regional Reanalysis
NASA National Aeronautical and Space
Administration
NCAR National Center for Atmospheric Research
NCDC National Climatic Data Center
NCEP National Centers for Environmental Prediction
NESDIS National Environmental Satellite, Data andInformation Service
NMC National Meteorological Center
NOAA National Oceanic and Atmospheric
Administration
NOMADS NOAA Operational Model Archive andDistribution System
PCMDI Program for Climate Model Diagnosis andIntercomparison
RTOVS Revised TIROS Operational Vertical Sounder
SST Sea Surface Temperature
TIROS Television and InfraRed Observation SatelliteSounder