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Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling

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David W. Pierce, Tapash Das, Daniel R. Cayan, Edwin P. Maurer, Norman L. Miller, Yan Bao, M. Kanamitsu, Kei Yoshimura, Mark A. Snyder, Lisa C. Sloan, Guido Franco, and Mary Tyree, Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling: Climate Dynamics, v. 40, iss. 3-4.

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Abstract (from http://link.springer.com/article/10.1007%2Fs00382-012-1337-9): Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly [...]

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  • National and Regional Climate Adaptation Science Centers
  • Southwest CASC

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journalClimate Dynamics
parts
typedoi
value10.1007/s00382-012-1337-9
typestartPage
value839
typeendPage
value856
typevolume
value40
typeissue
value3-4
typeissn
value0930-7575

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