Projecting and Forecasting Winter Precipitation Extremes and Meteorological Drought in California Using the North Pacific High Sea Level Pressure Anomaly

Abstract Large-scale climatic indices have been used as predictors of precipitation totals and extremes in many studies and are used operationally in weather forecasts to circumvent the difficulty in obtaining robust dynamical simulations of precipitation. The authors show that the sea level pressure North Pacific high (NPH) wintertime anomaly, a component of the Northern Oscillation index (NOI), provides a superior covariate of interannual precipitation variability in Northern California, including seasonal precipitation totals, drought, and extreme precipitation intensity, compared to traditional ENSO indices such as the Southern Oscillation index (SOI), the multivariate ENSO index (MEI), Niño-3.4, and others. Furthermore, the authors show that the NPH anomaly more closely reflects the influence of Pacific basin conditions over California in general, over groups of stations used to characterize statewide precipitation in the Sierra Nevada range, and over the southern San Francisco Bay region (NASA Ames Research Center). This paper uses the term prediction to refer to the estimation of precipitation (the predictand) from a climate covariate (the predictor), such as a climate index, or atmospheric moisture. In this sense, predictor and predictand are simultaneous in time. Statistical models employed show the effectiveness of the NPH winter anomaly as a predictor of total winter precipitation and daily precipitation extremes at the Moffett Field station. NPH projected by global climate models is also used in conjunction with atmospheric humidity [atmospheric specific humidity (HUS) at the 850-hPa level] to obtain projections of mean and extreme precipitation. The authors show that future development of accurate forecasts of NPH anomalies issued several months in advance is important for forecasting total winter precipitation and is expected to directly benefit water resource management in California. Therefore, the authors suggest that investigating the lead-time predictability of NPH anomalies is an important direction for future research.