Extended Abstract (164K)P14.1
Rainfall variability and its effect on rainfall measurements
Matthias Steiner, Princeton University, Princeton, NJ; and J. A. Smith, R. Uijlenhoet, and Z. Hou
Rainfall is highly variable in space and time, depending on the synoptic- and mesoscale forcing. This variability affects our capability to measure rainfall from an in-situ as well as remote-sensing perspective. In particular, the variability of rainfall within the range of sensor resolution differences has a significant effect on the comparison between observations made by instruments with differing resolutions in space and time. For example, a radar and rain gauge may both measure rainfall perfectly and accurately, from an instrument and retrieval perspective, yet they are not telling the same story. In reality, the rainfall amounts estimated by both instruments will likly be burdened by measurement limitations and uncertainties. The question is thus how much of the observed variance between radar and gauge observations can be explained simply by sensor resolution differences combined with space-time variability of rainfall?
Thirty major storms that passed over the highly-instrumented Goodwin Creek research watershed in northern Mississippi are analyzed to answer the above question. These storms, each contributing at least 10 mm of storm total rainfall, accumulated approximately 785 mm of rain, which corresponds to about half the average annual rainfall for this area. Extensive quality control of the radar and rain gauge data, drop spectrometer and lightning data, storm cell tracking and sensitivity to data processing analyses are combined to study differences in radar-estimated and gauge-measured rainfall amounts, and how these relate to storm structure and movement, and storm microphysics. Clearly, differences increase with increasing variability of rainfall.
Poster Session 14, Quantitative Rainfall—Single-Parameter Approaches
Monday, 23 July 2001, 2:00 PM-3:30 PM
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