NCEP Climate Forecast System Reanalysis (CFSR)

Topics

• Access
• Description
• Parameters
• Coverage, spatial and temporal resolution
• Data quality
• Contact person
• References
• Data citation and License

Access

UNRESTRICTED:

• Get CFSR data from NOAA

RESTRICTED: This link to the data set is only available for a restricted user group.  The data set is only accessible in CEN/MPI net or accessible from external nets with a customer account.  Please contact ICDC if you would like to access this data from outside the network.

• Data access via file system: /data/icdc/reanalyses/cfsr/

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Description

The CFSR was executed as global, high resolution, coupled atmosphere-ocean-land surface-sea ice system. It includes coupling of atmosphere and ocean during the generation of the 6 hour guess field, an interactive sea-ice model and assimilation of satellite radiances by the Grid-point Statistical Interpolation scheme over the period 1979 to 2009 (see references). Additional improvements are: the high horizontal and vertical resolution of the atmosphere (T382L64),  assimilation improvements over the last 10-15 years and the use of prescribed CO2 concentrations as a function of time.

CFSR is free of several inadequacies found in NCEP-R1 and R2 such as artificial changes introduced by ingesting data from constantly changing observational platforms or the constant CO2 of 330ppmv, rendering CFSR more useful  for climate change studies. CFSR is more accurate than NCEP-R1, while it includes analises of both the ocean and sea-ice with higher resolution in space and time.

CFSR employs the analysis systems:

1. operational Global Data Assimilation System (GDAS)
2. atmospheric GADAS- Gridded Statistical Interpolation (GSI)
3. ocean-ice GODAS
4. land GLDAS

• Atmospheric Model: operational Global Forecast system (GFS)
• Ocean Model: MOM4 Ocean (GFDL Modulal Ocean Model)
• Land Model: operational Noah Land Model
• Sea Ice model: from the GFDL Sea Ice Simulator

Last update of data set at ICDC:

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Parameters

Parameters of CFSR: Averages

Name	Description	Units
PRATE	Percipitation Rate	kg/m^2s
DLWRF_surface	Downward Long-Wave Radiative Flux	W/m^2
ULWRF_surface	Upward Long-Wave Radiative Flux	W/m^2
USWRF_surface	Upward Short-Wave Radiative Flux	W/m^2
DSWRF_surface	Downward Short-Wave Radiative Flux	W/m^2
SHTFL_surface	Sensible Heat Net Flux	W/m^2
LHTFL_surface	Latent Heat Net Flux	W/m^2

Parameters of CFSR: Forecast

Name	Description	Units
TMP_2maboveground	Temperature 2 m above ground	K
TMP_surface	Temperature at surface	K
TMP_0_0_1mbelowground	Temperature 0-0.1 m below ground	K
TMP_0_1_0_4mbelowground	Temperature 0.1-0.4 m below ground	K
TMP_0_4_1mbelowground	Temperature 0.4-1 m below ground	K
TMP_1_2mbelowground	Temperature 1-2 m below ground	K
ICEC_surface	Ice Cover	%
UGRD_10maboveground	U-Component of Wind 10 m above ground	m/s
VGRD_10maboveground	V-Component of Wind 10 m above ground	m/s
SPFH_2maboveground	Specific Humidity 2 m above ground	kg/kg
PRES_surface	Pressure at surface	Pa
ICETK_surface	Ice Thickness at surface	m
DLWRF_surface	Downward Long-Wave Radiative Flux	W/m^2
ULWRF_surface	Upward Long-Wave Radiative Flux	W/m^2
USWRF_surface	Upward Short-Wave Radiative Flux	W/m^2
DSWRF_surface	Downward Short-Wave Radiative Flux	W/m^2
SHTFL_surface	Sensible Heat Net Flux	W/m^2
LHTFL_surface	Latent Heat Net Flux	W/m^2

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Coverage, spatial and temporal resolution

Period and temporal resolution:

• from 1979 to 2009, 5-day averages and 6-hour forecasts

Coverage and spatial resolution:

• Global
• Spatial resolution: ~38 km (T382)
• Geographic longitude:0°E to 359.687°E
• Geographic latitude: -89.761°N to 89.761°N
• Altitudes: 64 Pressure levels, from surface to 0.26hPa and 40 from surface to 4737 m depth.

Format:

• NetCDF4

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Data quality

Biases arise when the observed radiances are compared to the simulated by CRTM. These biases are associated with instrument calibration, data processing and deficiencies in the radiative transfer model. Thus, before the radiances of a new instrument can be assimilated bias corrections are determined by a separate spin-up assimilation. For a detailed description of the data quality see Saha et al. 2010 supplement (see references).

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Contact

Remon Sadikni

ICDC / CEN / University of Hamburg
E-Mail: remon.sadikni@uni-hamburg.de<br />(remon.sadikni"AT"uni-hamburg.de)

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References

Literature:

• CLIMATE FORECAST SYSTEM REANALYSIS (CFSR), https://climatedataguide.ucar.edu/climate-data/climate-forecast-system-reanalysis-cfsr 
• Saha, S., et al. (2010) The NCEP Climate Forecast System Reanalysis. Bulletin of American Meteorological Society, 91, 1015-1057.
  http://dx.doi.org/10.1175/2010BAMS3001.1 

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Data citation, License, and Acknowledgments

Please cite the data as follows:

Saha et al., 2010. The NCEP Climate Forecast System Reanalysis, American Meteorological Society, 91, 1015-1057, doi:10.1175/2010BAMS3001.1..

and with the following acknowledgments:

Thanks to ICDC, CEN, University of Hamburg for data support.

License

Please see original data source for license informaton.

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