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Mukut B. Mathur
,
H. S. Bedi
,
T. N. Krishnamurti
,
Masao Kanamitsu
, and
Jack 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 their intensifies were considerably reduced.

Results from incorporation of the modified convective scheme in the global data-assimilation system within the NMC forecast model are also discussed. The analysis, the subsequent 72-h forecast circulation, and the rainfall amounts are improved with the use of this scheme.

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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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Sid-Ahmed Boukabara
,
Isaac Moradi
,
Robert Atlas
,
Sean P. F. Casey
,
Lidia Cucurull
,
Ross N. Hoffman
,
Kayo Ide
,
V. Krishna Kumar
,
Ruifang Li
,
Zhenglong Li
,
Michiko Masutani
,
Narges Shahroudi
,
Jack Woollen
, and
Yan Zhou

Abstract

A modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.

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Fedor Mesinger
,
Geoff DiMego
,
Eugenia Kalnay
,
Kenneth Mitchell
,
Perry C. Shafran
,
Wesley Ebisuzaki
,
Dušan Jović
,
Jack Woollen
,
Eric Rogers
,
Ernesto H. Berbery
,
Michael B. Ek
,
Yun Fan
,
Robert Grumbine
,
Wayne Higgins
,
Hong Li
,
Ying Lin
,
Geoff Manikin
,
David Parrish
, and
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 project's 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, NCEP's 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 improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979–2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP–Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability.

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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

Abstract

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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