Sampling Errors of SSM/I and TRMM Rainfall Averages Comparison with Error Estimates from Surface Data and a Simple Model

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote sensing error and, especially in the case of low-orbiting satellites, sampling error due to the li...

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Published inJournal of applied meteorology (1988) Vol. 40; no. 5; pp. 938 - 954
Main Authors Bell, Thomas L., Kundu, Prasun K., Kummerow, Christian D.
Format Journal Article
LanguageEnglish
Published Boston, MA American Meteorological Society 01.01.2001
Subjects
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ISSN0894-8763
1520-0450
1520-0450
DOI10.1175/1520-0450(2001)040<0938:seosia>2.0.co;2

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Abstract Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote sensing error and, especially in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that rms random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain gauge and radar data. This relationship is examined using Special Sensor Microwave Imager (SSM/I) satellite data obtained over the western equatorial Pacific during the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment. Rms error inferred directly from SSM/I rainfall estimates is found to be larger than was predicted from surface data and to depend less on local rain rate than was predicted. Preliminary examination of Tropical Rainfall Measuring Mission (TRMM) microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be computed directly from the satellite data.
AbstractList Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote sensing error and, especially in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that rms random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain gauge and radar data. This relationship is examined using Special Sensor Microwave Imager (SSM/I) satellite data obtained over the western equatorial Pacific during the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. Rms error inferred directly from SSM/I rainfall estimates is found to be larger than was predicted from surface data and to depend less on local rain rate than was predicted. Preliminary examination of Tropical Rainfall Measuring Mission (TRMM) microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be computed directly from the satellite data.
Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote sensing error and, especially in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that rms random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain gauge and radar data. This relationship is examined using Special Sensor Microwave Imager (SSM/I) satellite data obtained over the western equatorial Pacific during the Tropical Ocean and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. Rms error inferred directly from SSM/I rainfall estimates is found to be larger than was predicted from surface data and to depend less on local rain rate than was predicted. Preliminary examination of Tropical Rainfall Measuring Mission (TRMM) microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be computed directly from the satellite data. (Author)
Author Kundu, Prasun K.
Bell, Thomas L.
Kummerow, Christian D.
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Issue 5
Keywords Sampling error
DMSP satellite
Rain
Error estimation
Marine atmosphere
Space remote sensing
Random error
Satellite observation
Models
Rain gauge
TRMM satellite
Rainfall rate
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SubjectTerms Arithmetic mean
Artificial satellites
Datasets
Earth, ocean, space
Error rates
Exact sciences and technology
External geophysics
Geophysics. Techniques, methods, instrumentation and models
Marine
Radar
Radar data
Rain
Sampling errors
Statistical variance
Statistics
Subtitle Comparison with Error Estimates from Surface Data and a Simple Model
Title Sampling Errors of SSM/I and TRMM Rainfall Averages
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