MACAv2-METDATA Monthly Summaries: University of Idaho, Multivariate Adaptive Constructed Analogs Applied to Global Climate Models (IDAHO_EPSCOR/MACAv2_METDATA_MONTHLY)
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.
This version contains monthly summaries.
| Name | Description | Gee Unit |
|---|---|---|
| tasmax | Monthly average of maximum daily temperature near surface | K |
| tasmin | Monthly average of minimum daily temperature near surface | K |
| huss | Monthly average of mean daily specific humidity near surface | kg/kg |
| pr | Total monthly precipitation amount at surface | mm |
| rsds | Monthly average of mean daily downward shortwave radiation at surface | W/m^2 |
| was | Monthly average of mean daily near surface wind speed | 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 - 12/30/2099, 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 | month |
| 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"},{"name":"month","description":"The index of the month in the year, ie 1-12","type":"DOUBLE"} |