climate models covering the coterminous USA. The Multivariate Adaptive
Constructed Analogs (MACA) method is a statistical downscaling
method which utilizes a training dataset (i.e. a meteorological
observation dataset) to remove historical biases and match spatial
patterns in climate model output.
The MACA method was used to downscale the model output from 20
global climate models (GCMs) of the Coupled Model Inter-Comparison
Project 5 (CMIP5) for the historical GCM forcings (1950-2005) and
the future Representative Concentration Pathways (RCPs) RCP 4.5
and RCP 8.5 scenarios (2006-2100) from the native resolution of
the GCMS to 4km.
Version 2
The MACAv2-METDATA dataset is a collection of 20 global
climate models covering the coterminous USA. The Multivariate Adaptive
Constructed Analogs (MACA) method is a statistical downscaling
method which utilizes a training dataset (i.e. a meteorological
observation dataset) to remove historical biases and match spatial
patterns in climate model output.
The MACA method was used to downscale the model output from 20
global climate models (GCMs) of the Coupled Model Inter-Comparison
Project 5 (CMIP5) for the historical GCM forcings (1950-2005) and
the future Representative Concentration Pathways (RCPs) RCP 4.5
and RCP 8.5 scenarios (2006-2100) from the native resolution of
the GCMS to 4km.
Name | Description | Gee Unit |
---|---|---|
tasmax | Maximum daily temperature near surface | K |
tasmin | Minimum daily temperature near surface | K |
rhsmax | Maximum daily relative humidity near surface, not present in models CCSM4 or NorESM1-M | % |
rhsmin | Minimum daily relative humidity near surface, not present in models CCSM4 or NorESM1-M | % |
huss | Average daily specific humidity near surface | kg/kg |
pr | Average daily precipitation amount at surface | mm |
rsds | Average daily downward shortwave radiation at surface | W/m^2 |
uas | Average daily eastward component of wind near surface | m/s |
vas | Average daily northward component of wind near surface | m/s |
Providers | |
---|---|
University of Idaho (producer, licensor) | |
Google Earth Engine (host) | |
STAC Version | 0.6.0 |
Keywords | climate, conus, geophysical, idaho, maca, monthly |
License | proprietary |
Temporal Extent | 12/31/1899, 4:00:00 PM - 12/30/2100, 4:00:00 PM |
Citation | Abatzoglou J.T. and Brown T.J., A comparison of statistical downscaling methods suited for wildfire applications, International Journal of Climatology(2012) doi: [https://doi.org/10.1002/joc.2312](https://doi.org/10.1002/joc.2312). |
Type | image_collection |
GSD | arc minutesm |
Cadence | day |
Asset schema | {"name":"scenario","description":"Name of the CMIP5 scenario, one of 'rcp85', 'rcp45', or 'historical'","type":"STRING"},{"name":"model","description":"Name of the CMIP5 model, eg 'inmcm4'","type":"STRING"},{"name":"ensemble","description":"Either 'r1i1p1' or 'r6i1p1'","type":"STRING"} |