Special Sensor Microwave/Imager (SSM/I)

Precipitation

Overview

• 1.1 Data Sets Description:

  NOAA/NESDIS/Office of Research and Applications has developed a new set of 2.5-degree global rainfall statistics based on its SSM/I rainfall algorithms. All are monthly statistics and span the period from July 1987 through June 2005 (see section 2.1 for more current products), except a 18-month period from July 1990 to December 1991 during which no valid SSM/I data was available. Prior to 1992, only a single satellite was used, and since the beginning of 1992 two satellites have been used. The following list of files shows these statistics:

• 1.2 Data Access:

  ftp ftp.orbit.nesdis.noaa.gov
  use anonymous as username and your email as password)
  cd pub/corp/scsb/rferraro/precipitation/
  Then use "get" command in binary mode to get the data sets.
  There is a text file readme.txt which describe the data sets. Please get this file and read it.

• 2.1 Data Sets Description:

  Prior to the rainfall statistics described above, NOAA/NESDIS/ORA has been routinely generating monthly rainfall, fractional rain coverage, and SSM/I sampling fraction data sets on the 1-degree and/or 2.5-degree scale. The 2.5-degree version of these previous data sets can be replaced by the new sets. However, we continue to provide the older products to support users who have been using and wish to continue using them. For users new to both data sets, we recommend using the newer products.

  The 2.5 degree rainfall also denotes regions of indeterminate rainfall due to the presence of snow and ice cover and denotes these regions are values between -1 and -100.

  Due to the failure of the 85 GHz channels during the period of July 1990 to December 1991, no reliable retrievals can be made using the current algorithm. However, an alternate algorithm, which uses a 37 GHz scattering index over land and emission only over ocean can be used.

  In addition to monthly rainfall estimates, the mean fractional coverage of rain (within a grid cell) can also be computed, which gives an indication of the relative frequency of rainfall. Finally, because the SSM/I measurements are made from a polar orbiting satellite, the estimates are subjected to sampling errors. As such, we provide maps of the SSM/I sampling frequency for the month, which can be used to assess this sampling error.

  The table below summarizes the old monthly rainfall products:

• 2.2 Data Access:

  ftp.orbit.nesdis.noaa.gov
  use anonymous as username and your email as password)
  cd pub/corp/scsb/rferraro/ncdc (1-degree data sets
  cd pub/corp/scsb/rferraro/25deg (2.5-degree data sets)

3. The Algorithms:

The SSM/I rainfall algorithm developed at NOAA utilizes the 85V GHz channel to detect the scattering of upwelling radiation by precipitation sized ice particles within the rain layer. The scattering technique is applicable over land and ocean. Rain rate can be derived indirectly based on the relationship between the amount of ice in the rain layer to the actual rain fall on the surface. Care must be taken to remove anomalous surface scattering features (e.g., deserts and snow). Additionally, over ocean, an emission rain algorithm, based upon the absorption of the upwelling radiation by rain and cloud water (at 19 and 37 GHz) is blended with the scattering algorithm.

A scattering-based, global rainfall algorithm developed at the NOAA/NESDIS/ORA is used by the World Climate Research Programme/Global Precipitation Climatology Project (WCRP/GPCP)for land rainfall estimation. Monthly rainfall at 100 km and 250 km grids have been produced for the period of July 1987 to present. Additionally, the instantaneous rain rate produced from this algorithm is run operationally by the Fleet Numerical Meteorology and Oceanography Center (FNMOC).

References

Ferraro, R.R., N.C. Grody, and G.F. Marks, 1994: Effects of surface conditions on rain identification using the SSM/I, Rem. Sens. Rev., 11, 195-209.

Ferraro, R.R. and G.F. Marks, 1995: The development of SSM/I rain rate retrieval algorithms using ground based radar measurements. J, Atmos. and Ocean. Tech, 12, 755-770.

Ferraro, R. and Q. Li, 2002: Detailed analysis of the error associated with the rainfall retrieved by the NOAA/NESDIS SSM/I Algorithm, Part II: Rainfall Over land.  In Press, J. Geophys. Res.

Ferraro, R.R., 1997: SSM/I derived global rainfall estimates for climatological applications. J. Geophys. Res., 102, 16,715-16,735.

Grody, N.C., 1991: Classification of snow cover and precipitation using the Special Sensor Microwave/Imager (SSM/I). J. of Geophys. Res., 96, 7423-7435.

Li, Q., R. Ferraro and N.C. Grody, 1998: Detailed analysis of the error associated with the rainfall retrieved by the NOAA/NESDIS SSM/I Rainfall Algorithm: Part I. Tropical oceanic rainfall. J. Geophys. Res., 103, 11,419-11,427.

McCollum, J., W. Krajewski, R. Ferraro and M. Ba, 2002: Evaluation of biases of Satellite Rainfall Estimation algorithms over the continental U.S.  In Press, J. Appl. Meteor.

Weng, F., R.R. Ferraro, and N.C. Grody, 1994: Global precipitation estimations using DMSP F-10 and F-11 Special Sensor Microwave Imager (SSM/I) data, J. Geophys. Res., 99, 14493- 14502.

Weng, F. and N.C. Grody, 1994: Retrieval of cloud liquid water using the special sensor microwave imager (SSM/I). J. Geophys. Res., 99, 25535-25551.

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