4.7 Article

California Winter Precipitation Change under Global Warming in the Coupled Model Intercomparison Project Phase 5 Ensemble

期刊

JOURNAL OF CLIMATE
卷 26, 期 17, 页码 6238-6256

出版社

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-12-00514.1

关键词

North America; Climate change; Hydrology; Climate models

资金

  1. NOAA Climate Program Office Modeling, Analysis, Predictions and Projections (MAPP) Program as part of the CMIP5 Task Force [NA11OAR4310099]
  2. National Science Foundation [AGS-1102838]
  3. Directorate For Geosciences [1102838] Funding Source: National Science Foundation
  4. Div Atmospheric & Geospace Sciences [1102838] Funding Source: National Science Foundation

向作者/读者索取更多资源

Projections of possible precipitation change in California under global warming have been subject to considerable uncertainty because California lies between the region anticipated to undergo increases in precipitation at mid-to-high latitudes and regions of anticipated decrease in the subtropics. Evaluation of the large-scale model experiments for phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests a greater degree of agreement on the sign of the winter (December-February) precipitation change than in the previous such intercomparison, indicating a greater portion of California falling within the increased precipitation zone. While the resolution of global models should not be relied on for accurate depiction of topographic rainfall distribution within California, the precipitation changes depend substantially on large-scale shifts in the storm tracks arriving at the coast. Significant precipitation increases in the region arriving at the California coast are associated with an eastward extension of the region of strong Pacific jet stream, which appears to be a robust feature of the large-scale simulated changes. This suggests that effects of this jet extension in steering storm tracks toward the California coast constitute an important factor that should be assessed for impacts on incoming storm properties for high-resolution regional model assessments.

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