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the hydrostatic assumption. Soon after CFSR production began, it was noticed thatstreams 2 and 3 (see section 8 for execution layout), completely missed the QBO windtransition. This was unexpected based on the ability of R1, R2 and CFSR streams 1 and 4(starting in 1979 and 2004 respectively) to capture the QBO wind patterns. Whilesearching for a comprehensive solution, it was noted that the ERA-40 tropicalstratospheric wind profiles were readily available for the streams in question, includedthe stratospheric layers needed, and, qualitatively, adequately depicted both the QBO andsemi-annual oscillation. In order that the streams could proceed with a reasonable QBOsignature it was decided to use the ERA-40 stratospheric wind profiles as bogusobservations for the period from Jul 1, 1981 to Dec 31, 1998.Streams 1 and 4 had a common denominator. Both had more vertically resolved andtemporally complete tropical radiosonde wind observations at the beginning of the stream,than those in stream 2. Stream 1 benefited from the enhanced FGGE observation system,and stream 4 from the automation of modern radiosonde data collection which results inmore reports reaching the GTS, and more stratospheric levels in the individual reports.The solution to this problem became apparent from consultations with several GMAOMERRA team members, after determining that the MERRA reanalysis, which uses thesame GSI assimilation component, depicted the QBO very well. Prior to starting theMERRA project, GMAO had experienced a similar problem analyzing the QBO in anearlier grid point analysis system. The problem was resolved by enlarging the horizontallength scale of the zonal wind correlation function in the tropical stratosphere (Gaspari,et.al, 2006). When the GMAO assimilation system was switched to the GSI, the tropicalstratospheric stream function variances of the background error reflected the changesmade to fix the problem in the earlier system. When comparable background errorvariances were tested in the GSI for a case where the CFSR had failed to capture theQBO, the wind transition was successfully analyzed (not shown).3.1.6 Tropical Cyclone Processing- 22 -
As global prediction models have become increasingly more highly resolved and haveincluded more realistic boundary layer, water cycle and radiative parameterizations, thegenesis and evolution of tropical storms has dramatically improved. Equally importantare the ability of improved observing systems and analysis procedures to depict thedetails of tropical storm circulations and their accompanying steering flow.The first global reanalysis to assimilate historical tropical storm information was theJRA-25 reanalysis (Onogi, et.al. 2007). It assimilated synthetic wind profiles (Fiorino,2002) surrounding the historical storm locations of Newman, 1999.A unique feature of the CFSR is its approach to the analysis of historical tropical stormlocations. The CFSR applied the NCEP tropical storm relocation package (Liu et. al.,1999), a key component of the operational GFS analysis and prediction of tropical storm.By relocating a tropical storm vortex to its observed location prior to the assimilation ofstorm circulation observations, distortion of the circulation by the mismatch of guess andobserved locations is avoided. Fiorino (personal communication) provided the CFSRwith the historical set of storm reports converted into the operational format provided toNCEP by the NOAA/NWS National Hurricane Center and the US Navy Joint TyphoonWarning Center. Figure 28 shows the yearly total of tropical storm reports stacked by the8 geographical basins.A measure of the ability of assimilation to depict observed tropical storms is to quantifywhether or not a reported storm is detected in the assimilation guess. Figure 29 shows thetime series of the percentage of detected tropical storms plotted globally and for selectedNorthern Hemisphere basins: the Atlantic-Caribbean (ATL), the western Pacific (W Pac),and Eastern Pacific (E Pac). A noticeable improvement starts in 2000 coincident with thefull utilization of the ATOVS satellite instruments, such that between 90-95% of reportedtropical storms are detected.3.2 The Atmospheric Forecast ModelThe first NCEP/NCAR Reanalysis (R1, Kalnay et al., 1996; Kistler et al., 2001) was basedon the operational medium range forecast model of January 1995. R1 had a T62 horizontal- 23 -
Page 2 and 3: ABSTRACTThe NCEP Climate Forecast S
Page 4 and 5: 1. IntroductionThe first reanalysis
Page 6 and 7: In this paper we only discuss globa
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 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
Page 56 and 57: forecast model at a lower resolutio
Page 58 and 59: Appendix A: AcronymsAER Atmospheric
Page 60 and 61: ONPCMDIPIRATAPROFLRQBOQuikSCATR1R2R
Page 62 and 63: TMP2M 2m air temperature 24 / 473TM
Page 64 and 65: Appendix C: The Data AccessTo addre
Page 66 and 67: Figure 26 shows the global total bi
Page 68 and 69: Argo Science Team, 2001: The global
Page 70 and 71: Compo, G.P., J.S. Whitaker, and P.D
Page 72 and 73:
ozone Mapping and Profiler Suite (O
Page 75 and 76:
Global Forecast System. Manuscript
Page 77 and 78:
and climate models. Atmos. Chem. Ph
Page 79 and 80:
performance Earth system modeling w
Page 81 and 82:
with mesoscale numerical weather pr
Page 83 and 84:
experiments using SSM/I wind speed
Page 85 and 86:
Figure 21: Same as Figure 2, but fo
Page 87 and 88:
Figure 45: The fit of 6-hour foreca
Page 89 and 90:
Figure 1: Diagram illustrating CFSR
Page 91 and 92:
Figure 3: Same as in Figure 2, but
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Figure 15: Radiance instruments on
Page 105 and 106:
Figure 17: Same as in Figure 16, bu
Page 107 and 108:
Figure 19: Global average Tb first
Page 109 and 110:
Figure 21: Same as in Figure 16, bu
Page 111:
Figure 23: Comparisons of the SSU b
Page 114 and 115:
Figure 26: The global total bias fo
Page 116 and 117:
Figure 28: The yearly total of trop
Page 118 and 119:
Figure 30: The vertical structure o
Page 120 and 121:
Figure 32: The global number of tem
Page 122 and 123:
Figure 34: The same as Figure 33, b
Page 124 and 125:
Figure 36: Monthly mean Sea ice ext
Page 126 and 127:
Figure 38: 2-meter volumetric soil
Page 128 and 129:
Figure 40: Schematic of the executi
Page 130 and 131:
Figure 42: Yearly averaged Southern
Page 132 and 133:
Figure 44: Monthly mean hourly surf
Page 134 and 135:
Figure 46: Global mean temperature
Page 136 and 137:
Figure 48: Zonal mean total ozone d
Page 138 and 139:
Figure 50: The subsurface temperatu
Page 140 and 141:
Figure 52: Vertical profiles of the
Page 142 and 143:
Figure 54: Zonal surface velocities
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ProgramPREVENTSACQCACAR_CQCCQCCQCVA
Page 146:
Satellite Starting date Ending Date
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