87th AMS Annual Meeting

Tuesday, 16 January 2007: 10:45 AM
An intercomparison between mean areal precipitation from gauges and a multisensor procedure
211 (Henry B. Gonzalez Convention Center)
Dennis D. VanCleve Jr., Florida State Univ., Tallahassee, FL; and H. E. Fuelberg
This paper will quantify differences between rain gauge-derived precipitation estimates and those from the National Weather Service's (NWS's) Multisensor Precipitation Estimator (MPE) which blends hourly gauge data with estimates from NWS radars onto a 44 km2 grid. The MPE scheme is used operationally by the NWS. We make comparisons between 1996-2003 on five watersheds within Florida that have a range of sizes and gauge densities. Most previous comparisons have compared radar-derived rainfall values with those from individual gauges. However, it is basin-wide precipitation that determines flooding and affects decisions regarding water management and water quality standards.

The basin-wide comparison statistics between MPE and gauges are found to improve during the eight year study period due to improvements in the number of rain gauges and their data quality. MPE hourly totals generally are less than gauge totals, and differences between MPE and gauge amounts (MPE-gauge) often are greater (more negative) for larger gauge values than smaller ones. Results also reveal that the larger the basin, the greater the volume differences and standard deviation of differences. Differences between MPE- and gauge-derived precipitation are found to depend greatly on gauge density within the basin which generally increases during the study period. The comparison statistics also are affected by the spatial and temporal variability of rainfall within the basins. Thus, a particular gauge distribution may adequately sample one rainfall scenario and not another. Examples of these sampling scenarios will be given.

Differences between MPE and gauge-derived precipitation are found to be related to the seasons because of the different types of precipitation generally associated with each in Florida. The two data types correlate better during the cold season than the warm season, and the standard deviations of differences are greater during the warm season. The tendency for MPE amounts to be less than gauge amounts (a negative mean difference) is more pronounced during the cold season. On the other hand, the trend for MPE amounts to be much less than gauge amounts for the greater gauge totals is more pronounced during the warm season. These seasonal differences are due to several characteristics of the rainfall and its sampling by the two products. The cold season consists of more low top rainfall events than the summer. Radars often overshoot this precipitation, leading to MPE amounts less than gauge amounts. Cold season rainfall tends to be larger in area and more likely to be sampled adequately by gauges. Conversely, warm season events are more small scale in character and may not be adequately sampled by gauges.

Results of this study hopefully will lead to wider use of multi-sensor precipitation data since the paper will quantify the differences that can be expected.

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