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Bulletin of the American Meteorological Society | 1996

The NCEP/NCAR 40-Year Reanalysis Project

Eugenia Kalnay; Masao Kanamitsu; Robert Kistler; William D. Collins; Dennis G. Deaven; Lev S. Gandin; Mark Iredell; Suranjana Saha; Glenn Hazen White; John S. Woollen; Yunshan Zhu; Muthuvel Chelliah; Wesley Ebisuzaki; Wayne Higgins; John E. Janowiak; Kingtse C. Mo; Chester F. Ropelewski; Julian X. L. Wang; Ants Leetmaa; Richard W. Reynolds; Roy L. Jenne; Dennis Joseph

The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided by differe...


Bulletin of the American Meteorological Society | 2002

NCEP–DOE AMIP-II Reanalysis (R-2)

Masao Kanamitsu; Wesley Ebisuzaki; John S. Woollen; Shi-Keng Yang; J. J. Hnilo; M. Fiorino; G. L. Potter

The NCEP–DOE Atmospheric Model Intercomparison Project (AMIP-II) reanalysis is a follow-on project to the “50-year” (1948–present) NCEP–NCAR Reanalysis Project. NCEP–DOE AMIP-II re-analysis covers the “20-year” satellite period of 1979 to the present and uses an updated forecast model, updated data assimilation system, improved diagnostic outputs, and fixes for the known processing problems of the NCEP–NCAR reanalysis. Only minor differences are found in the primary analysis variables such as free atmospheric geopotential height and winds in the Northern Hemisphere extratropics, while significant improvements upon NCEP–NCAR reanalysis are made in land surface parameters and land–ocean fluxes. This analysis can be used as a supplement to the NCEP–NCAR reanalysis especially where the original analysis has problems. The differences between the two analyses also provide a measure of uncertainty in current analyses.


Bulletin of the American Meteorological Society | 2001

The NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation

Robert Kistler; Eugenia Kalnay; William D. Collins; Suranjana Saha; Glenn Hazen White; John S. Woollen; Muthuvel Chelliah; Wesley Ebisuzaki; Masao Kanamitsu; Vernon E. Kousky; Huug van den Dool; Roy L. Jenne; Michael Fiorino

The National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR) have cooperated in a project (denoted “reanalysis”) to produce a retroactive record of more than 50 years of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involved the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data. These data were then quality controlled and assimilated with a data assimilation system kept unchanged over the reanalysis period. This eliminated perceived climate jumps associated with changes in the operational (real time) data assimilation system, although the reanalysis is still affected by changes in the observing systems. During the earliest decade (1948–57), there were fewer upper-air data observations and they were made 3 h later than the current main synoptic times (e.g., 0300 UTC), and primarily in the Northern Hemisphere, so that the reanalysis is less reliable than for th later 40 years. The reanalysis data assimilation system continues to be used with current data in real time (Climate Data Assimilation System or CDAS), so that its products are available from 1948 to the present. The products include, in addition to the gridded reanalysis fields, 8-day forecasts every 5 days, and the binary universal format representation (BUFR) archive of the atmospheric observations. The products can be obtained from NCAR, NCEP, and from the National Oceanic and Atmospheric Administration/ Climate Diagnostics Center (NOAA/CDC). (Their Web page addresses can be linked to from the Web page of the NCEP–NCAR reanalysis at http:// wesley.wwb.noaa.gov/Reanalysis.html.) This issue of the Bulletin includes a CD-ROM with a documentation of the NCEP–NCAR reanalysis (Kistler et al. 1999). In this paper we present a brief summary and some highlights of the documentation (also available on the Web at http://atmos.umd.edu/ ~ekalnay/). The CD-ROM, similar to the one issued with the March 1996 issue of the Bulletin, contains 41 yr (1958–97) of monthly means of many reanalysis variables and estimates of precipitation derived from satellite and in situ observations (see the appenThe NCEP–NCAR 50-Year Reanalysis: Monthly Means CD-ROM and Documentation


Journal of Climate | 2011

MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications

Michele M. Rienecker; Max J. Suarez; Ronald Gelaro; Ricardo Todling; Julio T. Bacmeister; Emily Liu; Michael G. Bosilovich; Siegfried D. Schubert; Lawrence L. Takacs; Gi-Kong Kim; Stephen Bloom; Junye Chen; Douglas W. Collins; Austin Conaty; Arlindo da Silva; Wei Gu; Joanna Joiner; Randal D. Koster; Robert Lucchesi; Andrea Molod; Tommy Owens; Steven Pawson; Philip J. Pegion; Christopher R. Redder; Rolf H. Reichle; Franklin R. Robertson; Albert G. Ruddick; Meta Sienkiewicz; John S. Woollen

AbstractThe Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given.By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses i...


Bulletin of the American Meteorological Society | 2010

The NCEP Climate Forecast System Reanalysis

Suranjana Saha; Shrinivas Moorthi; Hua-Lu Pan; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; Robert Kistler; John S. Woollen; David Behringer; Haixia Liu; Diane Stokes; Robert Grumbine; George Gayno; Jun Wang; Yu-Tai Hou; Hui-Ya Chuang; Hann-Ming H. Juang; Joe Sela; Mark Iredell; Russ Treadon; Daryl T. Kleist; Paul Van Delst; Dennis Keyser; John Derber; Michael B. Ek; Jesse Meng; Helin Wei; Rongqian Yang; Stephen J. Lord

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global oceans latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice m...


Bulletin of the American Meteorological Society | 2006

NORTH AMERICAN REGIONAL REANALYSIS

Fedor Mesinger; Geoff DiMego; Eugenia Kalnay; Kenneth E. Mitchell; Perry C. Shafran; Wesley Ebisuzaki; Dusan Jovic; John S. Woollen; Eric Rogers; Ernesto H. Berbery; Michael B. Ek; Yun Fan; Robert Grumbine; Wayne Higgins; Hong Li; Ying Lin; Geoff Manikin; D. D. Parrish; Wei Shi

In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR projects Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEPs North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improv...


Monthly Weather Review | 1987

Experiments with a Three-dimensional statistical objective analysis scheme using FGGE data

Wayman E. Baker; Stephen Bloom; John S. Woollen; Mark S. Nestler; Eugenia Brin; Thomas W. Schlatter; Grant Branstator

Abstract A three-dimensional (3D), multivariate, statistical objective analysis scheme (referred to as optimum interpolation or OI) has been developed for use in numerical weather prediction studies with the FGGE data. Some novel aspects of the present scheme include 1) a multivariate surface analysis over the oceans, which employs an Ekman balance instead of the usual geostrophic relationship, to model the pressure-wind error cross correlations, and 2) the capability to use an error correlation function which is geographically dependent. A series of 4-day data assimilation experiments are conducted to examine the importance of some of the key features of the OI in terms of their effects on forecast skill, as well as to compare the forecast skill using the OI with that utilizing a successive correction method (SCM) of analysis developed earlier. For the three cases examined, the forecast skill is found to be rather insensitive to varying the error correlation function geographically. However, significant ...


Archive | 2010

Observing System Simulation Experiments

Michiko Masutani; Thomas W. Schlatter; Ronald M. Errico; Ad Stoffelen; Erik Andersson; William Lahoz; John S. Woollen; G. David Emmitt; Lars-Peter Riishojgaard; Stephen J. Lord

Observing System Simulation Experiments (OSSEs) are typically designed to use data assimilation ideas (see chapter Mathematical Concepts in Data Assimilation, Nichols) to investigate the potential impacts of prospective observing systems (observation types and deployments). They may also be used to investigate current observational and data assimilation systems by testing the impact of new observations on them. The information obtained from OSSEs is generally difficult, or in some contexts impossible, to obtain in any other way.


Monthly Weather Review | 1992

Use of satellite-derived rainfall for improving tropical forecasts

Mukut B. Mathur; H. S. Bedi; T. N. Krishnamurti; Masao Kanamitsu; John S. Woollen

Abstract Sparsity of conventional data over tropical oceans makes it difficult to analyze well the moisture and divergence fields, and therefore the diabatic forcing of the tropical atmosphere is not well predicted in numerical models. A nudging procedure to improve the precipitation forecast in the National Meteorological Center (NMC) Medium Range Forecast Model (MRF) is developed. The convective parameterization scheme is modified to adjust the predicted rainfall amounts toward the observations in this method. In the absence of conventional data, the rainfall estimates from the satellite measures of the outward-going longwave radiation are utilized as the observed precipitation. Several forecasts from the MRF are presented to show the improvements in intensity and location of the intertropical convergence zone and tropical disturbances with the application of the nudging procedure. Additionally, spurious cyclone and excessive rainfall that were predicted without this procedure either failed to form or t...


Journal of Atmospheric and Oceanic Technology | 2015

Impact of Different Satellite Wind Lidar Telescope Configurations on NCEP GFS Forecast Skill in Observing System Simulation Experiments

Zaizhong Ma; Lars Peter Riishojgaard; Michiko Masutani; John S. Woollen; George D. Emmitt

AbstractThe Global Wind Observing Sounder (GWOS) concept, which has been developed as a hypothetical space-based hybrid wind lidar system by NASA in response to the 2007 National Research Council (NRC) decadal survey, is expected to provide global wind profile observations with high vertical resolution, precision, and accuracy when realized. The assimilation of Doppler wind lidar (DWL) observations anticipated from the GWOS is being conducted as a series of observing system simulation experiments (OSSEs) at the Joint Center for Satellite Data Assimilation (JCSDA). A companion paper (Riishojgaard et al.) describes the simulation of this lidar wind data and evaluates the impact on global numerical weather prediction (NWP) of the baseline GWOS using a four-telescope configuration to provide independent line-of-sight wind speeds, while this paper sets out to assess the NWP impact of GWOS equipped with alternative paired configurations of telescopes. The National Centers for Environmental Prediction (NCEP) Gri...

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Michiko Masutani

National Oceanic and Atmospheric Administration

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Mark Iredell

Georgia Institute of Technology

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Suranjana Saha

National Oceanic and Atmospheric Administration

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Muthuvel Chelliah

National Oceanic and Atmospheric Administration

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Kingtse C. Mo

Goddard Space Flight Center

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Roy L. Jenne

National Center for Atmospheric Research

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Stephen J. Lord

National Oceanic and Atmospheric Administration

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Michael B. Ek

National Oceanic and Atmospheric Administration

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Russ Treadon

National Oceanic and Atmospheric Administration

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