Abstract
Quantification of spatial and temporal patterns of rainfall is an important step toward developing regional hydrological models. However, traditionally used rain gauge data are sparse and do not always provide adequate spatial representation of rainfall. In this study, we evaluated the daily 1-degree resolution remotely-sensed atmospheric precipitation data provided by Global Precipitation Climatology Project (GPCP) as an alternative to rain gauge-measured data. We analyzed data from the watersheds of southern California during the period of 1996–2003, focusing on the comparison of patterns of spatial, seasonal, and interannual rainfall dynamics. We used Empirical Orthogonal Functions to discern the patterns of precipitation and atmospheric circulation at different time scales, from synoptic to interannual. The correlation between the daily rain gauge-measured and remotely-sensed precipitation was poor and the resulting patterns of remotely-sensed precipitation are different than the temporal patterns of precipitation accumulated by rain gauges. These differences likely result from the fact that the precipitable water concentration measured by satellites is not always highly correlated to rainfall reaching the earth surface. Differences in the spatial resolution and coverage of the two methods and the differential influence of orographic effects and wind patterns on each also contribute to low correlations. We conclude that daily remotely-sensed precipitation produced at GPCP is not currently appropriate for use in assessing fine-scale hydrological processes in arid zones like southern California, and would not be a recommended surrogate for event-based hydrologic modeling. At the same time, the interannual variabilities of remotely-sensed and gauge-measured precipitation were highly correlated and the regional patterns of gauge-measured and remotely-sensed precipitation variability were similar; though the total precipitation estimated from satellite data was substantially lower than the gauge-measured data. Therefore, remotely-sensed precipitation data may be appropriate for use in long-term regional hydrologic or climate modeling focused on trends and patterns of rainfall in southern California. Both data sets showed that precipitation generally decreases from the northern to the southern watersheds. At interannual time-scale, the rainfall is related to the ENSO cycle. At synoptic time-scales, the rainfall patterns in southern California result from atmospheric moisture transport from the south–southwest.
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