Random Errors of Oceanic Monthly Rainfall Derived from SSM/I Using Probability Distribution Functions

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  • 1 Hydrological Sciences, NASA/Goddard Space Flight Center, Greenbelt, Maryland
  • | 2 General Sciences Corporation, Laurel, Maryland
  • | 3 Meteorology Department, Texas A&M University, College Station, Texas
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Abstract

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50%–60% for each 5° × 5° box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8%, a correlation of 0.7, and an rms difference of 55%.

Abstract

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50%–60% for each 5° × 5° box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8%, a correlation of 0.7, and an rms difference of 55%.

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