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In this paper we only discuss global reanalyses. There has been one regional reanalysisconducted at NCEP, namely the North American Regional Reanalysis (NARR), seeMesinger et al. 2006, but this type of activity is outside the scope of this paper. However,it is worth noting that the CFSR has a global horizontal resolution of ~38km that nearlymatches the 32km resolution of NARR over the limited area of the US.It has become increasingly clear over the last two decades that a single reanalysis will notsuffice. Not only is the data ingest subject to continual improvements, but the modelsused to create the guess field improve continually, and so do the data assimilationsystems. Bengtsson et al (2007) advocate the idea of a permanent, or ongoing, analysis ofthe Earth system. These efforts would not only utilize state-of-the-art forecast and dataassimilation methods, but in some configurations, the observations may even be reducedto whatever was available continuously over a century. Such kinds of reanalyses wouldbe homogeneous over time (Compo et al. 2006) and could be used for climate studies atlonger time scales.New data assimilation techniques have been introduced since the mid 1990s, rangingfrom three dimensional variational (3DVAR), to four dimensional variational (4DVAR),and/or ensembles of analyses (EnKF) that produce not only an ensemble mean analysis,but also a measure of the uncertainty (spread), see Compo et al(2006) and Anderson etal(2009).Although reanalyses may primarily be intended for climate studies, they also generateinitial states that can be used to start integrations by a numerical weather predictionmodel, either for weather or climate, in real time or from some historical state. The desireto generate hindcasts (sometimes called Reforecasts or Retrospective forecasts) tocalibrate subsequent real time forecasts, generated by the same model, have been underconsiderable development since the 1990s, and the availability of a reanalysis is key forthese efforts to succeed (Hamill et al. 2006). For instance, when NCEP operationallyimplemented its first global coupled seasonal forecast system, namely the ClimateForecast System (Saha et al 2006) in August 2004 (hereafter referred to as CFS v1), a- 6 -
complete Reforecast dataset was created over the period 1981-present to calibrate the realtime operational forecasts. The initial states for this Reforecast effort were taken from R2for the atmosphere and land, and from the Global Ocean Data Assimilation System(GODAS, forced by fluxes from R2) for the ocean. This relatively quick effort wouldhave been inconceivable without R2 being available.Since the operational CFS v1 implementation in 2004 (Saha et al. 2006), CPC and manyother users have utilized the four times daily seasonal integrations for their monthly andseasonal forecast products. However, the system has many internal inconsistencies. Forinstance, the R2 atmospheric initial states are made with technology from the 1990s,while the atmospheric model component of CFS is from a decade later. Thus the initialstates and forecast model are inconsistent; a situation which leads to loss of skill duringthe early part of the integrations. One of the major goals of executing the new CFSR wasto create initial states for the atmosphere, ocean, land and sea-ice which are both state-ofthe-art,and as consistent as possible with the next version of the CFS v2 which is to beimplemented operationally at NCEP in 2010. Given the pace of model and dataassimilation development, such a reanalysis will be needed roughly every 5-10 years.We have now completed the CFSR for the 31-year period 1979-2009. It took almost twoyears to accomplish this feat. The primary novelties of this latest reanalysis are a)coupling to the ocean during the generation of the 6 hour guess field, b) an interactivesea-ice model, and c) assimilation of satellite radiances for the entire period. In addition,the much higher horizontal and vertical resolution (T382L64) of the atmosphere, modeland assimilation improvements over the last 10-15 years, and the use of prescribed CO 2concentrations as a function of time, should make for substantial improvements over R1and R2 (which were at T62L28 resolution). Another major advance was the real timemonitoring that took place during the execution of the CFSR. Thousands of graphicalplots were generated automatically at the end of each reanalyzed month, and displayed onthe CFSR website in real time. Many scientists from both CPC and EMC monitoreddifferent aspects of the reanalysis during this 2 year process. There were many times that- 7 -
Page 2 and 3: ABSTRACTThe NCEP Climate Forecast S
Page 4 and 5: 1. IntroductionThe first reanalysis
Page 8 and 9: the reanalysis was halted to addres
Page 10 and 11: online archive of data for reanalys
Page 12 and 13: density MESONET data is included in
Page 14 and 15: The 1B datasets were calibrated usi
Page 16 and 17: MetOp is Europe's first polar-orbit
Page 20 and 21: The third GSI feature enabled in th
Page 22 and 23: the hydrostatic assumption. Soon af
Page 24 and 25: esolution with 28 sigma layers in t
Page 26 and 27: SW and LW radiations at one-hour in
Page 28 and 29: SST data. The other uses AVHRR and
Page 30 and 31: y Gent and McWilliams (1990; see al
Page 32 and 33: from the Global Temperature-Salinit
Page 34 and 35: through the end of the data set in
Page 36 and 37: The passive microwave weather filte
Page 39 and 40: from the sea ice/ocean back to the
Page 41 and 42: weight is assigned to the gauge ana
Page 43 and 44: Stream 6: 1 Jan 1994 to 31 Mar 1999
Page 45 and 46: in the mid 1990’s, the period whe
Page 47: e due to a change over the oceans (
Page 52 and 53: In Figure 49, we show the temporal
Page 54 and 55: distributed in time and space. Desp
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forecast model at a lower resolutio
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Appendix A: AcronymsAER Atmospheric
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ONPCMDIPIRATAPROFLRQBOQuikSCATR1R2R
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TMP2M 2m air temperature 24 / 473TM
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Appendix C: The Data AccessTo addre
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Figure 26 shows the global total bi
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Argo Science Team, 2001: The global
Page 70 and 71:
Compo, G.P., J.S. Whitaker, and P.D
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ozone Mapping and Profiler Suite (O
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Global Forecast System. Manuscript
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and climate models. Atmos. Chem. Ph
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performance Earth system modeling w
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with mesoscale numerical weather pr
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experiments using SSM/I wind speed
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Figure 21: Same as Figure 2, but fo
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Figure 45: The fit of 6-hour foreca
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Figure 1: Diagram illustrating CFSR
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Figure 3: Same as in Figure 2, but
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Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
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Page 103 and 104:
Figure 15: Radiance instruments on
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Figure 17: Same as in Figure 16, bu
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Figure 19: Global average Tb first
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Figure 21: Same as in Figure 16, bu
Page 111:
Figure 23: Comparisons of the SSU b
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Figure 26: The global total bias fo
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Figure 28: The yearly total of trop
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Figure 30: The vertical structure o
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Figure 32: The global number of tem
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Figure 34: The same as Figure 33, b
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Figure 36: Monthly mean Sea ice ext
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Figure 38: 2-meter volumetric soil
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Figure 40: Schematic of the executi
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Figure 42: Yearly averaged Southern
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Figure 44: Monthly mean hourly surf
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Figure 46: Global mean temperature
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Figure 48: Zonal mean total ozone d
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Figure 50: The subsurface temperatu
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Figure 52: Vertical profiles of the
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Figure 54: Zonal surface velocities
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ProgramPREVENTSACQCACAR_CQCCQCCQCVA
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Satellite Starting date Ending Date
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