4.6 Article

Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections

期刊

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
卷 120, 期 7, 页码 2676-2688

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1002/2014JD022414

关键词

storm properties; NARCCAP RCMs; storm duration; interstorm period; storm intensity

资金

  1. Sulo and Aileen Maki Endowment
  2. National Science Foundation [DMS-1025417]
  3. National Science Foundation
  4. U.S. Department of Energy
  5. National Oceanic and Atmospheric Administration
  6. U.S. Environmental Protection Agency Office of Research and Development
  7. Division Of Mathematical Sciences
  8. Direct For Mathematical & Physical Scien [1460319] Funding Source: National Science Foundation

向作者/读者索取更多资源

Precipitation characteristics, such as intensity, frequency, duration, and event pattern, are changing due to the increases in greenhouse gases, transition of ocean oscillation phases, etc. In this paper, we evaluate the ability of 11 realizations from multiple regional climate model (RCM)/global climate model pairs in the North American Regional Climate Change Assessment Program (NARCCAP) to simulate the seasonal variability and magnitude of storm properties, including storm duration, interstorm period, and storm intensity. The results indicate that NARCCAP RCMs simulate the seasonal variability better in the Greater Sacramento and San Joaquin than in Las Vegas, which may be due to the RCMs' inability to simulate local convective precipitation associated with the North American Monsoon. We also investigate the impacts of climate change on these storm characteristics by comparing the percentage change and absolute change of storm properties determined from NARCCAP historical runs and future runs. We find that individual RCMs exhibit great uncertainty in the percentage changes in storm duration, interstorm period, and average storm intensity. The ensemble means of storm properties across 11 future NARCCAP RCM projections show different responses to climate change in different locations. Our analyses provide guidelines for selecting the appropriate RCMs for hydrologic studies related to storm properties and provide forecasters and water managers with detailed information of future changes in storm properties so that they can sustainably manage water resources. Our results may also contribute to the nonstationary precipitation scenario development by incorporating the percentage changes of storm properties caused by human-induced warming into the stochastic precipitation model. Key Points

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