| 数据题名: | Projected Future LOCA Statistical Downscaling (Localized Constructed Analogs) Statistically downscaled CMIP5 climate projections for North America |
| 作者: | GCIS
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| 出版者: | GCIS
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| 出版（发布）日期: | 2016
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| 语种: | 英语
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| 国别: | 美国
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| 学科领域: | 全球变化
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| 英文摘要: | LOCA is a statistical downscaling technique that uses past history to add improved fine-scale detail to global climate models. We have used LOCA to downscale 32 global climate models from the CMIP5 archive at a 1/16th degree spatial resolution, covering North America from central Mexico through Southern Canada. The historical period is 1950-2005, and there are two future scenarios available: RCP 4.5 and RCP 8.5 over the period 2006-2100 (although some models stop in 2099). The variables currently available are daily minimum and maximum temperature, and daily precipitation. |
| URL: | http://loca.ucsd.edu/
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| 资源类型: | 科学数据
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/117589
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| Appears in Collections: | 全球变化的国际研究计划
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| Recommended Citation: | |
GCIS. Projected Future LOCA Statistical Downscaling (Localized Constructed Analogs) Statistically downscaled CMIP5 climate projections for North America .GCIS. 2016-01-01.
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