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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...


Journal of Climate | 2014

The NCEP Climate Forecast System Version 2

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-Ya Chuang; Mark Iredell; Michael B. Ek; Jesse Meng; Rongqian Yang; Malaquias Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

AbstractThe second version of the NCEP Climate Forecast System (CFSv2) was made operational at NCEP in March 2011. This version has upgrades to nearly all aspects of the data assimilation and forecast model components of the system. A coupled reanalysis was made over a 32-yr period (1979–2010), which provided the initial conditions to carry out a comprehensive reforecast over 29 years (1982–2010). This was done to obtain consistent and stable calibrations, as well as skill estimates for the operational subseasonal and seasonal predictions at NCEP with CFSv2. The operational implementation of the full system ensures a continuity of the climate record and provides a valuable up-to-date dataset to study many aspects of predictability on the seasonal and subseasonal scales. Evaluation of the reforecasts show that the CFSv2 increases the length of skillful MJO forecasts from 6 to 17 days (dramatically improving subseasonal forecasts), nearly doubles the skill of seasonal forecasts of 2-m temperatures over the ...


Journal of Climate | 2006

The NCEP Climate Forecast System

Suranjana Saha; Sudhir Nadiga; C. Thiaw; Julian X. L. Wang; Wanqiu Wang; Qi Ming Zhang; H. M. van den Dool; Hua-Lu Pan; Shrinivas Moorthi; David Behringer; Diane Stokes; Malaquias Peña; Stephen J. Lord; Glenn Hazen White; Wesley Ebisuzaki; Pin-Yin Peng; Pingping Xie

Abstract The Climate Forecast System (CFS), the fully coupled ocean–land–atmosphere dynamical seasonal prediction system, which became operational at NCEP in August 2004, is described and evaluated in this paper. The CFS provides important advances in operational seasonal prediction on a number of fronts. For the first time in the history of U.S. operational seasonal prediction, a dynamical modeling system has demonstrated a level of skill in forecasting U.S. surface temperature and precipitation that is comparable to the skill of the statistical methods used by the NCEP Climate Prediction Center (CPC). This represents a significant improvement over the previous dynamical modeling system used at NCEP. Furthermore, the skill provided by the CFS spatially and temporally complements the skill provided by the statistical tools. The availability of a dynamical modeling tool with demonstrated skill should result in overall improvement in the operational seasonal forecasts produced by CPC. The atmospheric compon...


Bulletin of the American Meteorological Society | 2002

NCEP DYNAMICAL SEASONAL FORECAST SYSTEM 2000

Masao Kanamitsu; Arun Kumar; Hann-Ming Henry Juang; Jae-Kyung E. Schemm; Wanqui Wang; Fanglin Yang; Song-You Hong; Peitao Peng; Wilber Chen; Shrinivas Moorthi; Ming Ji

The new National Centers for Environmental Prediction (NCEP) numerical seasonal forecast system is described in detail. The new system is aimed at a next-generation numerical seasonal prediction in which focus is placed on land processes, initial conditions, and ensemble methods, in addition to the tropical SST forcing. The atmospheric model physics is taken from the NCEP–National Center for Atmospheric Research (NCAR) reanalysis model, which has more comprehensive land hydrology and improved physical processes. The model was further upgraded by introducing three new parameterization schemes: 1) the relaxed Arakawa–Schubert (RAS) convective parameterization, which improved middle latitude response to tropical heating; 2) Chous shortwave radiation, which corrected surface radiation fluxes; and 3) Chous longwave radiation scheme together with smoothed mean orography that reduced model warm bias. Atmospheric initial conditions were taken from the operational NCEP Global Data Assimilation System, allowing t...


Archive | 2011

NCEP Climate Forecast System Version 2 (CFSv2) 6-hourly Products

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-Ya Chuang; Mark Iredell; Michael B. Ek; Jesse Meng; Rongqian Yang; Malaquias Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

The National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) is initialized four times per day (0000, 0600, 1200, and 1800 UTC). NCEP upgraded their operational CFS to version 2 on March 30, 2011. This is the same model that was used to create the NCEP Climate Forecast System Reanalysis (CFSR), and the purpose of this dataset is to extend CFSR. The 6-hourly atmospheric, oceanic and land surface analyzed products and forecasts, available at 0.2, 0.5, 1.0, and 2.5 degree horizontal resolutions, are archived here beginning with January 1, 2011 as an extension of CFSR. The RDA is not archiving any of the CFS seasonal forecasts. For more information about CFS, please see http://cfs.ncep.noaa.gov/ [http://cfs.ncep.noaa.gov/].


Geoscientific Model Development | 2016

The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP

Cheng-Hsuan Lu; Arlindo da Silva; Jun Wang; Shrinivas Moorthi; Mian Chin; Peter R. Colarco; Youhua Tang; Partha S. Bhattacharjee; Shen-Po Chen; Hui-Ya Chuang; Hann-Ming Henry Juang; Jeffery T. McQueen; Mark Iredell

The NOAA National Centers for Environmental Prediction (NCEP) implemented NEMS GFS Aerosol Component (NGAC) for global dust forecasting in collaboration with NASA Goddard Space Flight Center (GSFC). NGAC Version 1.0 has been providing 5 day dust forecasts at 1°×1° resolution on a global scale, once per day at 00:00 Coordinated Universal Time (UTC), since September 2012. This is the first global system capable of interactive atmosphere aerosol forecasting at NCEP. The implementation of NGAC V1.0 reflects an effective and efficient transitioning of NASA research advances to NCEP operations, paving the way for NCEP to provide global aerosol products serving a wide range of stakeholders as well as to allow the effects of aerosols on weather forecasts and climate prediction to be considered.


Climate Dynamics | 2015

Evaluation of the CFSv2 CMIP5 decadal predictions

Rodrigo J. Bombardi; Jieshun Zhu; Lawrence Marx; Bohua Huang; Hua Chen; Jian Lu; Lakshmi Krishnamurthy; V. Krishnamurthy; Ioana Colfescu; James L. Kinter; Arun Kumar; Zeng-Zhen Hu; Shrinivas Moorthi; Patrick Tripp; Xingren Wu; Edwin K. Schneider

Abstract Retrospective decadal forecasts were undertaken using the Climate Forecast System version 2 (CFSv2) as part of Coupled Model Intercomparison Project 5. Decadal forecasts were performed separately by the National Center for Environmental Prediction (NCEP) and by the Center for Ocean-Land-Atmosphere Studies (COLA), with the centers using two different analyses for the ocean initial conditions the NCEP Climate Forecast System Reanalysis (CFSR) and the NEMOVAR-COMBINE analysis. COLA also examined the sensitivity to the inclusion of forcing by specified volcanic aerosols. Biases in the CFSv2 for both sets of initial conditions include cold midlatitude sea surface temperatures, and rapid melting of sea ice associated with warm polar oceans. Forecasts from the NEMOVAR-COMBINE analysis showed strong weakening of the Atlantic Meridional Overturning Circulation (AMOC), eventually approaching the weaker AMOC associated with CFSR. The decadal forecasts showed high predictive skill over the Indian, the western Pacific, and the Atlantic Oceans and low skill over the central and eastern Pacific. The volcanic forcing shows only small regional differences in predictability of surface temperature at 2m (T2m) in comparison to forecasts without volcanic forcing, especially over the Indian Ocean. An ocean heat content (OHC) budget analysis showed that the OHC has substantial memory, indicating potential for the decadal predictability of T2m; however, the model has a systematic drift in global mean OHC. The results suggest that the reduction of model biases may be the most productive path towards improving the model’s decadal forecasts.


Archive | 2010

NCEP Climate Forecast System Reanalysis (CFSR) Selected Hourly Time-Series Products, January 1979 to December 2010

Suranjana Saha; Shrinivas Moorthi; Hua-Lu Pan; Xingren Wu; Jie 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 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 National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) was initially completed over the 31-year period from 1979 to 2009 and has been extended to March 2011. NCEP has created selected time series products at hourly temporal resolution by combining either 1) the analysis and one- through five-hour forecasts, or 2) the one- through six-hour forecasts, for each initialization time. Please note that NCEP only created time series for parameter/level combinations that they thought would be most useful to users. Time series that do not exist in this dataset can be created from the full 6-hourly products dataset at http://rda.ucar.edu/datasets/ds093.0/ [http://rda.ucar.edu/datasets/ds093.0/].\n\n For more information about CFSR in general, please see this page [http://rda.ucar.edu/#!pub/cfsr.html]. For data to extend CFSR beyond March 2011, please see the Climate Forecast System Version 2 (CFSv2) datasets.


Archive | 2011

NCEP Climate Forecast System Version 2 (CFSv2) Selected Hourly Time-Series Products

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-Ya Chuang; Mark Iredell; Michael B. Ek; Jesse Meng; Rongqian Yang; Malaquias Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

The National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) is initialized four times per day (0000, 0600, 1200, and 1800 UTC). NCEP upgraded CFS to version 2 on March 30, 2011. This is the same model that was used to create the NCEP Climate Forecast System Reanalysis (CFSR).\n\nSelected CFS time series products are those that are expected to be most useful to users of the dataset, but the products here are by no means an exhaustive compilation of all of the possible products that could be created from the full 6-hourly CFS dataset.\n\nThe products here are available at 0.2, 0.5, 1.0, and 2.5 degree horizontal resolutions at hourly intervals by combining either 1) the analysis and one- through five-hour forecasts, or 2) the one- through six-hour forecasts, for each initialization time. Beginning with January 1, 2011, these data are archived as an extension of CFSR.\n\nThe files in this dataset are grouped by month, so data for a particular month are not available until a few days into the subsequent month. If you need data for the current month, please consult the CFSv2 dataset that contains the complete suite of 6-hourly products.\n\nFor more information about CFS, please see http://cfs.ncep.noaa.gov/ [http://cfs.ncep.noaa.gov/].


Archive | 2012

NCEP Climate Forecast System Version 2 (CFSv2) Monthly Products

Suranjana Saha; Shrinivas Moorthi; Xingren Wu; Jiande Wang; Sudhir Nadiga; Patrick Tripp; David Behringer; Yu-Tai Hou; Hui-Ya Chuang; Mark Iredell; Michael B. Ek; Jesse Meng; Rongqian Yang; Malaquias Mendez; Huug van den Dool; Qin Zhang; Wanqiu Wang; Mingyue Chen; Emily Becker

The National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) is initialized four times per day (0000, 0600, 1200, and 1800 UTC). NCEP upgraded their operational CFS to version 2 on March 30, 2011. This is the same model that was used to create the NCEP Climate Forecast System Reanalysis (CFSR). CFSv2 monthly atmospheric, oceanic and land surface output products are available at 0.3, 0.5, 1.0, 1.9, and 2.5 degree horizontal resolutions as 6-hourly diurnal monthly means (0000, 0600, 1200, and 1800 UTC) and regular full monthly means. For more information about CFS, please see http://cfs.ncep.noaa.gov/ [http://cfs.ncep.noaa.gov/].

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Hui-Ya Chuang

National Oceanic and Atmospheric Administration

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Mark Iredell

Georgia Institute of Technology

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David Behringer

National Oceanic and Atmospheric Administration

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Patrick Tripp

National Oceanic and Atmospheric Administration

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Sudhir Nadiga

National Oceanic and Atmospheric Administration

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Xingren Wu

National Oceanic and Atmospheric Administration

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Jesse Meng

National Oceanic and Atmospheric Administration

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Michael B. Ek

National Oceanic and Atmospheric Administration

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Rongqian Yang

National Oceanic and Atmospheric Administration

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Suranjana Saha

National Oceanic and Atmospheric Administration

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