Relationships of rainy season precipitation and temperature to climate indices in California: long-term variability and extreme events

To better understand the change in California’s climate over the past century, the long-term variability and extreme events of precipitation as well as minimum, mean, and maximum temperatures during the rainy season (from November to March) are investigated using observations. Their relationships to 28 rainy season average climate indices with and without time lags are also studied. The precipitation variability is found to be highly correlated with the Tropical/Northern Hemisphere pattern (TNH) index at zero time lag with the highest correlation in Northern California and the Sierra, and the correlation decreasing southward. This is an important finding because there have been no conclusive studies on the dominant climate modes that modulate precipitation variability in Northern California. We find that the TNH modulates California precipitation variability through the development of a positive (negative) height anomaly and its associated low-level moisture fluxes over the northeast Pacific Ocean during the positive (negative) TNH phase. Temperature fields, especially minimum temperature, are found to be primarily modulated by the East Pacific/North Pacific Oscillation, Pacific Decadal Oscillation, North Pacific Pattern, and Pacific/North American teleconnection patterns at zero time lag via changes in the low-tropospheric temperature advections. Regression analysis suggests a combination of important climate indices would improve predictability for precipitation and minimum temperature statewide and sub-regionally compared to the use of a single climate index. While California’s precipitation currently is primarily projected by ENSO, our study suggests that using the combination of the TNH and ENSO indices results in better predictability than using ENSO indices only.