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Kingtse C. Mo, Eric Rogers, Wesley Ebisuzaki, R. Wayne Higgins, J. Woollen, and M. L. Carrera


During the 2004 North American Monsoon Experiment (NAME) field campaign, an extensive set of enhanced atmospheric soundings was gathered over the southwest United States and Mexico. Most of these soundings were assimilated into the NCEP operational global and regional data assimilation systems in real time. This presents a unique opportunity to carry out a series of data assimilation experiments to examine their influence on the NCEP analyses and short-range forecasts. To quantify these impacts, several data-withholding experiments were carried out using the global Climate Data Assimilation System (CDAS), the Regional Climate Data Assimilation System (RCDAS), and the three-dimensional variational data assimilation (3DVAR) Eta Model Data Assimilation System (EDAS) for the NAME 2004 enhanced observation period (EOP).

The impacts of soundings vary between the assimilation systems examined in this study. Overall, the influence of the enhanced soundings is concentrated over the core monsoon area. While differences at upper levels are small, the differences at lower levels are more substantial. The coarse-resolution CDAS does not properly resolve the Gulf of California (GoC), so the assimilation system is not able to exploit the additional soundings to improve characteristics of the Gulf of California low-level jet (GCLLJ) and the associated moisture transport in the GoC region. In contrast, the GCLLJ produced by RCDAS is conspicuously stronger than the observations, though the problem is somewhat alleviated with additional special NAME soundings. For EDAS, soundings improve the intensity and position of the Great Plains low-level jet (GPLLJ). The soundings in general improve the analyses over the areas where the assimilation system has the largest uncertainties and errors. However, the differences in regional analyses owing to the soundings are smaller than the differences between the two regional data assimilation systems.

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Masao Kanamitsu, Wesley Ebisuzaki, Jack Woollen, Shi-Keng Yang, J. J. Hnilo, M. Fiorino, and 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.

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J. Le Marshall, J . Jung, J. Derber, M. Chahine, R. Treadon, S J. Lord, M Goldberg, W Wolf, H C. Liu, J Joiner, J. Woollen, R. Todling, P. van Delst, and Y. Tahara
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D. H. Bromwich, A. B. Wilson, L. Bai, Z. Liu, M. Barlage, C.-F. Shih, S. Maldonado, K. M. Hines, S.-H. Wang, J. Woollen, B. Kuo, H.-C. Lin, T.-K. Wee, M. C. Serreze, and J. E. Walsh


The Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000–12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century–complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks.

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E. Kalnay, M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, Roy Jenne, and 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 different countries and organizations. The system has been designed with advanced quality control and monitoring components, and can produce 1 mon of reanalysis per day on a Cray YMP/8 supercomputer. Different types of output archives are being created to satisfy different user needs, including a “quick look” CD-ROM (one per year) with six tropospheric and stratospheric fields available twice daily, as well as surface, top-of-the-atmosphere, and isentropic fields. Reanalysis information and selected output is also available on-line via the Internet (http// A special CDROM, containing 13 years of selected observed, daily, monthly, and climatological data from the NCEP/NCAR Reanalysis, is included with this issue. Output variables are classified into four classes, depending on the degree to which they are influenced by the observations and/or the model. For example, “C” variables (such as precipitation and surface fluxes) are completely determined by the model during the data assimilation and should be used with caution. Nevertheless, a comparison of these variables with observations and with several climatologies shows that they generally contain considerable useful information. Eight-day forecasts, produced every 5 days, should be useful for predictability studies and for monitoring the quality of the observing systems.

The 40 years of reanalysis (1957–96) should be completed in early 1997. A continuation into the future through an identical Climate Data Assimilation System will allow researchers to reliably compare recent anomalies with those in earlier decades. Since changes in the observing systems will inevitably produce perceived changes in the climate, parallel reanalyses (at least 1 year long) will be generated for the periods immediately after the introduction of new observing systems, such as new types of satellite data.

NCEP plans currently call for an updated reanalysis using a state-of-the-art system every five years or so. The successive reanalyses will be greatly facilitated by the generation of the comprehensive database in the present reanalysis.

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


The 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 in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses.

Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).

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