On this page: Temporal Coverage | Spatial Coverage | Levels | Update Schedule | Download/Plot Data | Analysis Tools
Restrictions | Details | Caveats | File Naming | Citation | References | Original Source | Contact

Twentieth Century Reanalysis (V2): Monthly Mean Pressure Level Data

Please read about a potential issue if you acquired daily 2m air temperature files between 8/14/2014 and 11/7/2014.
We have transitioned the data files from netCDF3 to netCDF4-classic format (transition date: Aug 14th).
[ Data Type: Pressure Level | Single Level | Subsurface | Monthly Mean Pressure Level | Monthly Mean Single Level | Monthly Mean Subsurface ]

Brief Description:

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

Temporal Coverage:

  • 6-hourly values for 1871/01/01 0Z to 2012/12/31 18Z.

Spatial Coverage:

  • 2.0 degree latitude x 2.0 degree longitude global grid (180x91).
  • 90N - 90.0S, 0.0E - 358.E.

Levels:

  • pressure level and single level files. 24 pressure levels (hPa): 1000 , 950 , 900 , 850 , 800 , 750 , 700 , 650 , 600 , 550 , 500 , 450 , 400 , 350 , 300 , 250 , 200 , 150 , 100 , 70 , 50 , 30 , 20 , 10

Update Schedule:

  • Additional years will be added after the end of each year.

Usage Restrictions:

  • None

Detailed Description:

  • The analysis is performed with the Ensemble Filter as described in Compo et al. (2010) based on the method of Whitaker and Hamill (2002). The fields containing the mean and the spread (i.e., standard deviation) of the analysis ensemble are archived here. 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 (ACRE) 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). he analysis is performed with the Ensemble Filter as described in Compo et al. (2010) based on the method of Whitaker and Hamill (2002).
    • 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. Br�nnimann, M. Brunet, R.I. Crouthamel, A.N. Grant, P.Y. Groisman, P.D. Jones, M. Kruk, A.C. Kruger, G.J. Marshall, M. Maugeri, H.Y. Mok, �. Nordli, T.F. Ross, R.M. Trigo, X.L. Wang, S.D. Woodruff, and S.J. Worley, 2011: The Twentieth Century Reanalysis Project. Quarterly J. Roy. Meteorol. Soc., 137, 1-28. DOI: 10.1002/qj.776.
    • 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.

Caveats:

Note: We have removed the monthly wind speed files. They were calculated using ensmeble means rather than individual ensemble members, averaged. This could result in an underestimation of average wind speeds, particurlay in certain places. We may recalculate these at a later date.

Download/Plot Data:

Variable Statistic Level Download File Create Plot/Subset
Air Temperature Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/air.mon.mean.nc plot
Air Temperature Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/air.mon.ltm.nc plot
Air Temperature Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/air.mon.mean.nc plot
Air Temperature Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/air.mon.ltm.nc plot
Geopotential Height Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/hgt.mon.mean.nc plot
Geopotential Height Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/hgt.mon.ltm.nc plot
Geopotential Height Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/hgt.mon.mean.nc plot
Geopotential Height Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/hgt.mon.ltm.nc plot
Omega Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/omega.mon.mean.nc plot
Omega Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/omega.mon.ltm.nc plot
Omega Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/omega.mon.mean.nc plot
Omega Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/omega.mon.ltm.nc plot
Relative Humidity Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/rhum.mon.mean.n plot
Relative Humidity Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/rhum.mon.ltm.nc plot
Relative Humidity Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/rhum.mon.mean.nc plot
Relative Humidity Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/rhum.mon.ltm.nc plot
Specific Humidity Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/shum.mon.mean.nc plot
Specific Humidity Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/shum.mon.ltm.nc plot
Specific Humidity Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/shum.mon.mean.nc plot
Specific Humidity Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/shum.mon.ltm.nc plot
Zonal Wind Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/uwnd.mon.mean.nc plot
Zonal Wind Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/uwnd.mon.ltm.nc plot
Zonal Wind Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/uwnd.mon.mean.nc plot
Zonal Wind Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/uwnd.mon.ltm.nc plot
Meridional Wind Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/vwnd.mon.mean.nc plot
Meridional Wind Long Term Monthly Mean 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure/vwnd.mon.ltm.nc plot
Meridional Wind Monthly Mean Ensemble Spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/vwnd.mon.mean.nc plot
Meridional Wind Long Term Monthly Mean Ensemble spread 1000-10mb ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Derived/Monthlies/pressure_sprd/vwnd.mon.ltm.nc plot

Related File Naming & Structure Information:

File Names:

  • 4-times daily /Datasets/20thC_ReanV2/pressure/filename
  • 4-times daily /Datasets/20thC_ReanV2/pressure_sprd/filename
  • Daily /Datasets/20thC_ReanV2/pressure/filename
  • Daily /Datasets/20thC_ReanV2/pressure_sprd/filename
  • Monthly /Datasets/20thC_ReanV2/Monthlies/pressure/filename
  • Monthly /Datasets/20thC_ReanV2/Monthlies/pressure_sprd/filename

Dataset Format and Size:

Missing Data:

  • Missing data is flagged with a value of 9.36e36f.

OpenDap File Names:

  • http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/20thC_ReanV2/Monthlies/pressure/filename
  • http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/20thC_ReanV2/pressure_sprd/filename

FTP File Names:

  • ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure/ *
  • ftp.cdc.noaa.gov/Datasets/20thC_ReanV2/Monthlies/pressure_sprd/*

Citation:

  • Please note: If you acquire 20th Century Reanalysis data products from PSD, we ask that you acknowledge us in your use of the data. This may be done by including text such as 20th Century Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/ in any documents or publications using these data. We would also appreciate receiving a copy of the relevant publications. This will help PSD to justify keeping the 20th Century Reanalysis data set freely available online in the future. Thank you!
  • The Twentieth Century Reanalysis Project used resources of the National Energy Research Scientific Computing Center managed by Lawrence Berkeley National Laboratory and of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which are supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 and Contract No. DE-AC05-00OR22725, respectively.

    Papers using the Twentieth Century Reanalysis Project dataset are requested to include the following text in their acknowledgments: "Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office."

    • 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. 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, and S.J. Worley, 2011: The Twentieth Century Reanalysis Project. Quarterly J. Roy. Meteorol. Soc., 137, 1-28. DOI: 10.1002/qj.776 Free and Open Access.
    • 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.
    • 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.

References:

Original Source:

  • Data are Data are courtesy of Gilbert Compo1,2 , Jeff Whitaker2, and Prashant Sardeshmukh1,2 . University of Colorado CIRES-Climate Diagnostics Center 2. NOAA Earth System Research Laboratory - Physical Sciences Division.
  • The Twentieth Century Reanalysis Project used resources of the National Energy Research Scientific Computing Center managed by Lawrence Berkeley National Laboratory and of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which are supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 and Contract No. DE-AC05-00OR22725, respectively.

  • Papers using the Twentieth Century Reanalysis Project dataset are requested to include the following text in their acknowledgments: "Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office."

Other Sources:

Contact:

  • For help with the dataset please contact Gil Compo, Research Scientist, CIRES University of Colorado Email: compo@colorado.edu
  • Physical Sciences Division: Data Management
    NOAA/ESRL/PSD
    325 Broadway
    Boulder, CO 80305-3328
    esrl.psd.data@noaa.gov