Relationships of Rainy Season Precipitation and Temperature to Climate Indices in California: Long-Term Variability and Extreme Events
| Autor: | Yi Chin Liu, Shu-Hua Chen, Pingkuan Di, J. DaMassa |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Wet season
Atmospheric Science 010504 meteorology & atmospheric sciences Anomaly (natural sciences) 0208 environmental biotechnology Northern Hemisphere Extreme events Time lag 02 engineering and technology 01 natural sciences Pacific ocean 020801 environmental engineering Term (time) 13. Climate action Climatology Environmental science Precipitation 0105 earth and related environmental sciences |
| Zdroj: | Journal of Climate. 31:1921-1942 |
| ISSN: | 1520-0442 0894-8755 |
| DOI: | 10.1175/jcli-d-17-0376.1 |
| Popis: | 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. It is found 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 pattern, Pacific decadal oscillation, North Pacific pattern, and Pacific–North American pattern at zero time lag via changes in the lower-tropospheric temperature advections. Regression analysis suggests a combination of important climate indices would improve predictability for precipitation and minimum temperature statewide and subregionally compared to the use of a single climate index. While California’s precipitation currently is primarily projected by ENSO, this study suggests that using the combination of the TNH and ENSO indices results in better predictability than using ENSO indices only. |
| Databáze: | OpenAIRE |
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