LOCA Statistical Downscaling (Localized Constructed Analogs)

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Basic Information
Full Title: 
LOCA Statistical Downscaling (Localized Constructed Analogs). Statistically downscaled CMIP5 climate projections for North America.

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).

David W. Pierce
Scripps Institution of Oceanography
Spatial Resolution: 
1/16th degree
Temporal Coverage: 
Date Issued: 

Several links listed here for data downloading, including Cal-Adapt, LLNL Green Data Oasis, NASA OpenNEX, and the USGS Geo Data Portal.

Parameters / Choices
A dataset often contains many geodata layers representing the same kind of measurement, but for different values of some parameters - time periods, models or scenarios, different species, etc. A value must be chosen for each such parameter in order to select a specific layer or raster which associated a single value with each geographic location (cell). The parameters or choices relevant to selecting layers from this dataset are described here.
Time Units: 
Multi-year Ranges: 
1950-2005, 2006-2100