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ESRL/PSD Seminar Series

PSD Flash Seminars: Using Ground-Based Observations to Validate Assumptions used in Satellite Rainfall Retrieval Algorithms

Christopher Williams
NOAA/ESRL PSD Weather and Climate Physics Branch


Rainfall retrieval algorithms often assume the raindrop size distribution (DSD) can be described by a gamma function using three mathematical DSD parameters. But, if only two independent measurements are available, as with the dual-frequency precipitation radar (DPR) on the Global Precipitation Mission (GPM) core satellite, then retrieval algorithms are under-constrained and need to make assumptions about the DSD parameters. Satellite rainfall algorithms reduce the number of free parameters by either assuming one DSD parameter is a constant (e.g., the DSD has an inverse exponential distribution), or, by assuming a mathematical relationship between two DSD parameters. Controversies exist over whether relationships between DSD parameters result from physical processes or mathematical artifacts due to high correlations between gamma DSD parameters.

This study uses ground-based observations to validate if either assumption occurs in nature. Without assuming a mathematical shape of the DSD, this study analyzes raindrop mass spectra to describe the DSD shape with a mean raindrop diameter and a normalized mass spectrum standard deviation. When mapped into the gamma DSD parameter space, ground-based rainfall observations show that keeping one parameter constant is not observed in nature. And, a mathematical relationship between two DSD parameters does provide an improved rainfall retrieval estimate. And since the two mass spectrum physical attributes are statistically independent, they are well suited for probabilistic rainfall retrieval algorithms as proposed for the GPM satellite program.

Wednesday, Apr 9
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