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One important step in Numerical Weather/Climate Prediction is the combination of the model first guess with observations in a process called data assimilation. This important information is used both as the initial condition for the next forecast as well as to study weather and climate. However, as stated by NCEP scientists “ …These analyses are very inhomogeneous in time as there have been big improvements in the data assimilation systems. This played havoc with climate monitoring as these improvements were often produced changes in the apparent “climate”….” (Please, see next subsection for detailed information). The way found to improve this problem was to make analysis for the past years with a frozen global analysis system and use all available observations as some of them could not be assimilated in time on the daily operational forecasting ([#NCEP-NCAR Kalnay et al., 1996]). This process is called Reanalysis.

The NCEP/NCAR Reanalysis

If you want to search for Gridded Climate Data at PSD by:

1) Variable, dataset or both: Search for data by variable

2) Dataset: Search for data by dataset

Alternatively, you can get access to these data by clicking here

For information about how to read the Grib data, please Click here.

For other additional information click here.

More information about [“NCEP/NCAR Reanalysis”]


20th Century Reanalysis

Twentieth Century Reanalysis (V1)

The NCEP-NCAR Reanalysis product starts from 1948, leaving many important climate events uncovered. To expand the coverage of global gridded reanalyses, the 20th Century Reanalysis Project is an effort led by PSD and the University of Colorado CIRES Climate Diagnostics Center to produce a reanalysis dataset spanning the entire twentieth century, assimilating only surface observations of synoptic pressure, monthly sea surface temperature and sea ice distribution. The observations have been assembled through international cooperation under the auspices of the Atmospheric Circulation Reconstructions over the Earth initiative, and working groups of GCOS and WCRP. The Project uses a recently-developed Ensemble Filter data assimilation method which directly yields each six-hourly analysis as the most likely state of the global atmosphere, and also estimates uncertainty in that analysis. This dataset will provide the first estimates of global tropospheric and stratospheric variability spanning 1871 to present at six-hourly resolution. The first version has global coverage spanning 1908-1958, and two degree longitude-latitude horizontal resolution.

= Data =

20th Century Reanalysis contains objectively-analyzed 4-dimensional weather maps and their uncertainty for most of the 1900's:

-6-hourly,daily average and monthly values for 1908/01/01 to 1958/12/31 -Long term monthly means, derived from data for years 1921 - 1950

The spatial coverage is 2 .0 degree latitude x 2.0 degree longitude global grid (180×91) and 90N - 90.0S, 0.0E - 358.E.

The avaliable files are in NetCDF format and are:

-Daily and 4 times daily:

-Monthly :

To obtain data: 1) Go to the type of data you want ( 4 times daily, daily or monthly) 2) Click to the variable of interest. You will be redirected to a page where you can download the files. 3) Also you can download data from this ftp site

= References =

-Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmaa, and R. Reynolds 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.

-Compo,G.P., J.S. Whitaker, and P.D. Sardeshmukh, 2006: Feasibility of a 100 year reanalysis using only surface pressure data. Bull. Amer. Met. Soc., 87, 175-190.

-Kanamitsu, M, and Coauthors 1991: Recent changes implemented into the global forecast system at NMC. Wea. Forecasting, 6, 425-435. Moorthi, S., H.-L. Pan, and P. Caplan, 2001: Changes to the 2001 NCEP operational MRF/AVN global analysis/forecast system. NWS Tech. Procedures Bulletin 484, 14 pp. Available online here

-Rayner, N.A., D.E. Parker, E.B. Horton, C.K. Folland, L.V. Alexander, D.P. Rowell, E.C Kent, and A. Kaplan, 2003: Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.

-Saha, S. and Coauthors, 2006: The NCEP Climate Forecast System. J. Climate, 19, 3483-3517. Whitaker, J.S., G.P.Compo, X. Wei, and T.M. Hamill 2004: Reanalysis without radiosondes using ensemble data assimilation. Mon. Wea. Rev., 132, 1190-1200.

Web page

20th Century Reanalysis (V2)

The analysis is performed with the Ensemble Filter as described in Compo et al. (2010) based on the method of Whitaker and Hamill (2002). Observations of surface pressure and sea level pressure from the International Surface Pressure Databank station component version 2 (Yin et al. 2008), ICOADS (Woodruff et al. 2009), and the International Best Track Archive for Climatic Stewardship (IBTrACS, Kruk et al. 2010) were assimilated every six hours. The surface pressure observations have been made available through international cooperation facilitated by the Atmospheric Circulation Reconstructions over the Earth initiative and working groups of the Global Climate Observing System and World Climate Research Programme. The short-term forecast ensemble is generated in parallel from 56 9-hour integrations of a state-of-the-art atmospheric general circulation model, a 2008 updated experimental version of the atmospheric component of NCEP's operational Climate Forecast System model (Saha et al. 2006). Briefly, the model has a spatial resolution of nearly 200-km on an irregular Gaussian grid in the horizontal (corresponding to a spherical harmonic representation of model fields truncated at total wavenumber 62, T62). In the vertical, we use finite differencing of 28 levels. The model has a complete suite of physical parameterizations as described in Kanamitsu et al. (1991) with recent updates detailed in Moorthi et al. (2001). Additional updates to these parameterizations are described in Saha et al. and include revised solar radiation transfer, boundary layer vertical diffusion, cumulus convection, and gravity wave drag parameterizations. In addition, the cloud liquid water is a prognostic quantity with a simple cloud microphysics parameterization. The radiation interacts with a fractional cloud cover that is diagnostically determined by the predicted cloud liquid water. The 2008 experimental version of the model used for the 20th Century Reanalysis also includes the radiative effects of historical time-varying CO2 concentrations, volcanic aerosol and solar variations using the longwave radiation model of Mlawer et al. (1997) and shortwave radiation model of Hou et al. (2002). The specified boundary conditions needed to run the model in atmosphere-only mode are taken from the time-evolving sea surface temperature and sea ice concentration fields of the HadISST1.1 dataset obtained courtesy of the United Kingdom Met Office Hadley Centre (Rayner et al. 2003).

= Data =

20th Century Reanalysis V2 contains objectively-analyzed 4-dimensional weather maps and their uncertainty from the late 19th century to 21st century.

-6-hourly,daily average and monthly values for 1871/01/01 0z to 2012/12/31 18z.

The spatial coverage is 2.0 degree latitude x 2.0 degree longitude global grid (180×91) and 90N - 90.0S, 0.0E - 358.E.

The remote files are available from:

1) http://www.esrl.noaa.gov/psd/data/gridded/data.20thC_ReanV2.html

2) ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2

3) http://dss.ucar.edu/datasets/ds131.1/

Local data

/cfu/data/noaa/20thc_reanv2/

Available monthly mean variables

tas = near-surface (2m) air temperature [K], prlr = total precipitation [kg/m^2/s]

= References =

-Compo, G.P., J.S. Whitaker, P.D. Sardeshmukh, N. Matsui, R.J. Allan, X. Yin,B.E. Gleason, R.S. Vose, G. Rutledge, P. Bessemoulin, S. Brönnimann, M. Brunet, R.I. Crouthamel, A.N. Grant, P.Y. Groisman, P.D. Jones, M.C. Kruk, A.C. Kruger, G.J. Marshall, M. Maugeri, H.Y. Mok, Ø. Nordli, T.F. Ross, R.M. Trigo, X.L. Wang, S.D. Woodruff, S.J. Worley, 2009: The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc., submitted.

-Compo, G.P., J.S. Whitaker, and P.D. Sardeshmukh, 2006: Feasibility of a 100 year reanalysis using only surface pressure data. Bull. Amer. Met. Soc., 87, 175-190.

-Gleason, B.E., G.P. Compo, N. Matsui, X. Yin, and R.S. Vose, 2008: The International Surface Pressure Databank (ISPD) land component version 2.2, National Climatic Data Center, Asheville, NC, pp. 1-12. Available on line at ftp://ftp.ncdc.noaa.gov/pub/data/ispd/doc/ISPD2_2.pdf

-Hou, Y,. S. Moorthi and K. Compana, 2002: Parameterization of solar radiation transfer in NCEP models. NCEP Office Note #441. Available at [http:/www.emc.ncep.noaa.gov/officenotes/FullTOC.html#2000]

-Kanamitsu, M, and Coauthors 1991: Recent changes implemented into the global forecast system at NMC. Wea. Forecasting, 6, 425-435. Knapp K.R., M.C. Kruk, D.H. Levinson, H.J. Diamond, and C.J. Neumann, 2009: The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying tropical cyclone best track data. Bulletin of the American Meteorological Society: In Press, DOI: 10.1175/2009BAMS2755.1

-Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102(D14), 16,663-16,682

-Moorthi, S., H.-L. Pan, and P. Caplan, 2001: Changes to the 2001 NCEP operational MRF/AVN global analysis/forecast system. NWS Tech. Procedures Bulletin 484, 14 pp. Available online at http://www.nws.noaa.gov/om/tpb/484.htm

-Rayner, N.A., D.E. Parker, E.B. Horton, C.K. Folland, L.V. Alexander, D.P. Rowell, E.C Kent, and A. Kaplan, 2003: Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.

-Saha, S. and Coauthors, 2006: The NCEP Climate Forecast System. J. Climate, 19, 3483-3517.

-Whitaker, J. S., and T.M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913–1924.

-Woodruff, S.D., S.J.Worley, S.J. Lubker, Z. Ji, J.E. Freeman, D.I. Berry, P. Brohan, E.C. Kent, R.W. Reynolds, S.R. Smith, and C. Wilkinson, 2009: ICOADS release 2.5: Extensions and enhancements to the surface marine meteorological archive. Int. J. Climatol., submitted.


The ECMWF Reanalysis

The ERA Project

= ERA-40 =

To download data from ERA-40 click here. This website was made for easy use. Following are some steps that might help you get the data:

1) In the up right corner, choose the type of data you want: pressure levels or surface;

2) Select the time section;

3) Select the date by either writing the start and end dates or selecting a list of months;

4) Lastly, select time and variables that you need.

= ERA-Interim =

The procedures to download ERA-Interim data is almost the same. Click here to be redirected.

More information about the [“ECMWF Reanalysis”]

Japanese 25-year Reanalysis (JRA-25)

In order to get access to the JRA-25 data one must first apply in the following website.

The Japan Meteorological Agency (JMA) and the Central Research Institute of Electric Power Industry (CRIEPI) conducted a 26-year reanalysis project referred to as the Japanese 25-year Reanalysis (JRA-25). JMA and CRIEPI offer users JRA-25 products.

JMA has carried out the second reanalysis project named the Japanese 55-year Reanalysis (JRA-55) using a more sophisticated NWP system, which is based on the operational system as of December 2009, and newly prepared past observations. The analysis period is extended to 55 years starting from 1958, when the regular radiosonde observations became operational on the global basis. Many of deficiencies in JRA-25 have been diminished or reduced in JRA-55 because many improvements achieved after JRA-25 have been introduced. JRA-55 provides a consistent climate dataset over the last half century.

Data location

/cfu/data/jma/jra-55/

Available monthly mean variables

psl = mean sea level pressure [Pa], tas = near-surface (2m) air temperature [K], prlr = total precipitation [m/s], g200 = 200hPa geopotential [m^2/s^2], and g500 = 500hPa geopotential [m^2/s^2].

References

Onogi, K., J. Tsutsui, H. Koide, M. Sakamoto, S. Kobayashi, H. Hatsushika, T. Matsumoto, N. Yamazaki, H. Kamahori, K. Takahashi, S. Kadokura, K. Wada, K. Kato, R. Oyama, T. Ose, N. Mannoji and R. Taira (2007) : The JRA-25 Reanalysis. J. Meteor. Soc. Japan, 85, 369-432. - available at /cfu/data/jma/jra-55/docs/JRA-25_reanalysis.pdf

Ebita, A., S. Kobayashi, Y. Ota, M. Moriya, R. Kumabe, K. Onogi, Y. Harada, S. Yasui, K. Miyaoka, K. Takahashi, H. Kamahori, C. Kobayashi, H. Endo, M. Soma, Y. Oikawa, and T. Ishimizu, 2011: The Japanese 55-year Reanalysis “JRA-55”: an interim report, SOLA, 7, 149-152. - this is only an interim report of JRA-55 as of 2011 available at /cfu/data/jma/jra-55/docs/SOLA_2011_JRA-55.pdf

Ocean reanalysis

Ensembles

ECMWF Ensembles

Ocean data are in NetCDF format. To access to data downloading webpage click here.

Only monthly means for both analyses and forecasts are available in the common ocean archiving. Both 3-D fields and a small set of 2-D fields are archived. Vertical sections can be derived from the 3-D fields. The data are interpolated on a Levitus grid as defined in the ENACT conventions. Variable units are indicated in parentheses. The fields are expected to be CF-compliant. This point can be checked using the BADC CF-convention compliance checker. The 151 ECMWF local table version 2 has been used to reference the GRIB code of the variables, also in parentheses.

3-D fields: potential temperature (129.151, K) salinity (130.151, PSU) zonal velocity (131.151, m/s) meridional velocity (132.151, m/s) vertical velocity (133.151, m/s)

2-D fields: sea level (145.151, m) mixed layer depth (148.151, m) 20 C isotherm depth (163.151, m) average potential temperature in the upper 300m (164.151, K) Mike Davey suggested at RT1/RT2A meeting in June 2006 to update the common list of ocean variables with the ocean transports. They are expected to be computed in the ocean grid using daily model output, from which monthly means would be extracted and interpolated into the ENSEMBLES regular grid.

Sea Ice Reanalyses

PIOMAS

Data location

/cfu/data/psc/piomas

Reference

Zhang J, Rothrock DA (2003) Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates. Mon Wea Rev 131(5):681–697

UCL

Data location

/cfunas/exp/UCL

Reference

Mathiot P, Beatty CK, Fichefet T, Goosse H, Massonnet F, Vancoppenolle M (2012) Better constraints on the sea-ice state using global sea-ice data assimilation. Geosci Model Dev Discuss 5:1627–1667

data/reanalysis_data.txt · Last modified: 2015/05/26 17:17 (external edit)