Improving Seasonal to Annual 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, e.g., NINO3 and PDO. In this work, a methodology called basin-specific climate prediction (BSCP) is proposed to improve hydroclimatic predictions. The method analyzes the statistically unique relationships between sea surface temperatures (SSTs) and a basin's hydroclimate. The oceanic region which maximizes the correlation is subsequently used as a predictor for hydroclimate. BSCP is used to perform hindcasts for the hydroclimate in the Little Colorado River basin and the results are compared to those using standard climate indices as predictors.