What question did this study set out to answer?

This research aims to evaluate the dependence of sampling error on monthly averaged rain rates from satellite data and to review existing models.

Dependence of Satellite Sampling Error on Monthly Averaged Rain Rates:Comparison of Simple Models and Recent Studies

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Review of models estimating sampling error in rain rates, emphasizing variability and statistical analysis implications.

This research aims to evaluate the dependence of sampling error on monthly averaged rain rates from satellite data and to review existing models.
Reviewed recent studies estimating sampling error, focusing on methods like 'resampling by shifts'.
Analyzed variability in sampling-error estimates and their relationship with average rain rates using statistical models.
Examined the relationship between sampling error and average rain rate, particularly the proportionality constant across different sites.
Sampling error is found to vary and cannot be captured by a single value.
Statistical models indicate that sampling error is inversely proportional to the square root of average rain rate (R−1/2).
The proportionality constant varies from site to site but can be derived from satellite estimates when retrieval errors are uncorrelated.

Bell et al. (2000) studied this question.

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View Full Paper

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Authors

Review of models estimating sampling error in rain rates, emphasizing variability and statistical analysis implications.

This research aims to evaluate the dependence of sampling error on monthly averaged rain rates from satellite data and to review existing models.
Reviewed recent studies estimating sampling error, focusing on methods like 'resampling by shifts'.
Analyzed variability in sampling-error estimates and their relationship with average rain rates using statistical models.
Examined the relationship between sampling error and average rain rate, particularly the proportionality constant across different sites.
Sampling error is found to vary and cannot be captured by a single value.
Statistical models indicate that sampling error is inversely proportional to the square root of average rain rate (R−1/2).
The proportionality constant varies from site to site but can be derived from satellite estimates when retrieval errors are uncorrelated.

Bell et al. (2000) studied this question.

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