Improving Seasonal Predictions of Climate Variability and Water Availability at the Catchment Scale

Abstract

In a water-stressed region, such as the southwestern United States, it is essential to improve current seasonal hydroclimatic predictions. Typically, seasonal hydroclimatic predictions have been conditioned by standard climate indices, for example, Niño-3 and Pacific decadal oscillation (PDO). In this work, the statistically unique relationships between sea surface temperatures (SSTs) and particular basins? hydroclimates are explored. The regions where global SSTs are most correlated with the Little Colorado River and Gunnison River basins? hydroclimates are located throughout the year and at varying time lags. The SSTs, from these regions of highest correlation, are subsequently used as hydroclimatic predictors for the two basins. This methodology, named basin-specific climate prediction (BSCP), is further used to perform hindcasts. The hydroclimatic hindcasts obtained using BSCP are shown to be closer to the historical record, for both basins, than using the standard climate indices as predictors.