Editorial Type:
Article
Article Type:
Research Article

Nonsystematic Errors of Monthly Oceanic Rainfall Derived from SSM/I

Alfred T. C. Chang Hydrological Sciences Branch, Laboratory for Hydrospheric Processes, NASA/Goddard Space Flight Center, Greenbelt, Maryland

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Long S. Chiu Hydrological Sciences Branch, Laboratory for Hydrospheric Processes, NASA/Goddard Space Flight Center, Greenbelt, Maryland

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Print Publication:
01 Jul 1999
DOI:
https://doi.org/10.1175/1520-0493(1999)127<1630:NEOMOR>2.0.CO;2
Page(s):
1630–1638
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Abstract

About 10 yr (July 1987–December 1997 with December 1987 missing) of oceanic monthly rainfall based on data taken by the Special Sensor Microwave/Imager (SSM/I) on board the Defense Meteorological Satellite Program satellites have been computed. The technique, based on the work of Wilheit et al., includes improved parameterization of the beam-filling correction, a refined land mask and sea ice filter. Monthly means are calculated for both 5° and 2.5° latitude–longitude boxes.

Monthly means over the latitude band of 50°N–50°S and error statistics are presented. The time-averaged rain rate is 3.09 mm day−1 (std dev of 0.15 mm day−1) with an error of 38.0% (std dev of 3.0%) for the 5° monthly means over the 10-yr period. These statistics compare favorably with 3.00 mm day−1 (std dev of 0.19 mm day−1) and 46.7% (std dev of 3.4%) computed from the 2.5° monthly means for the period January 1992–December 1994. Examination of the different rain rate categories shows no distinct discontinuity, except for months with a large number of missing SSM/I data.

An independent estimate of the error using observations from two satellites shows an error of 31% (std dev of 2.7%), consistent with the 38% estimated using (a.m. and p.m.) data from one satellite alone. Error estimates (31%) based on the 5° means by averaging four neighboring 2.5° boxes are larger than those (23%) estimated by assuming the means for these neighboring boxes are independent, thus suggesting spatial dependence of the 2.5° means.

Multiple regression analyses show that the error varies inversely as the square root of the number of samples but exhibits a somewhat weaker dependence on the mean rain rate. Regression analyses show a power law dependence of −0.255 to −0.265 on the rain rate for the 5° monthly means using data from a single satellite and a dependence of −0.366 for the 5° monthly means and −0.337 for the 2.5° monthly means based on two satellite measurements. The latter estimate is consistent with that obtained by Bell et al. using a different rainfall retrieval technique.

* Current affiliation: Center for Earth Observing and Space Research, Institute for Computational Sciences and Informatics, George Mason University, Fairfax, Virginia.

Corresponding author address: Dr. Alfred T. Chang, Hydrological Sciences Branch, Laboratory for Hydrospheric Processes, Code 974, NASA/GSFC, Greenbelt, MD 20771.

Email: achang@rainfall.gsfc.nasa.gov

Abstract

About 10 yr (July 1987–December 1997 with December 1987 missing) of oceanic monthly rainfall based on data taken by the Special Sensor Microwave/Imager (SSM/I) on board the Defense Meteorological Satellite Program satellites have been computed. The technique, based on the work of Wilheit et al., includes improved parameterization of the beam-filling correction, a refined land mask and sea ice filter. Monthly means are calculated for both 5° and 2.5° latitude–longitude boxes.

Monthly means over the latitude band of 50°N–50°S and error statistics are presented. The time-averaged rain rate is 3.09 mm day−1 (std dev of 0.15 mm day−1) with an error of 38.0% (std dev of 3.0%) for the 5° monthly means over the 10-yr period. These statistics compare favorably with 3.00 mm day−1 (std dev of 0.19 mm day−1) and 46.7% (std dev of 3.4%) computed from the 2.5° monthly means for the period January 1992–December 1994. Examination of the different rain rate categories shows no distinct discontinuity, except for months with a large number of missing SSM/I data.

An independent estimate of the error using observations from two satellites shows an error of 31% (std dev of 2.7%), consistent with the 38% estimated using (a.m. and p.m.) data from one satellite alone. Error estimates (31%) based on the 5° means by averaging four neighboring 2.5° boxes are larger than those (23%) estimated by assuming the means for these neighboring boxes are independent, thus suggesting spatial dependence of the 2.5° means.

Multiple regression analyses show that the error varies inversely as the square root of the number of samples but exhibits a somewhat weaker dependence on the mean rain rate. Regression analyses show a power law dependence of −0.255 to −0.265 on the rain rate for the 5° monthly means using data from a single satellite and a dependence of −0.366 for the 5° monthly means and −0.337 for the 2.5° monthly means based on two satellite measurements. The latter estimate is consistent with that obtained by Bell et al. using a different rainfall retrieval technique.

* Current affiliation: Center for Earth Observing and Space Research, Institute for Computational Sciences and Informatics, George Mason University, Fairfax, Virginia.

Corresponding author address: Dr. Alfred T. Chang, Hydrological Sciences Branch, Laboratory for Hydrospheric Processes, Code 974, NASA/GSFC, Greenbelt, MD 20771.

Email: achang@rainfall.gsfc.nasa.gov

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