CalAdapt.pyt
Download the UCLA Dynamically Downscaled Product Data as NetCDF files from the Cal-Adapt Data Server.
UCLA_Data (Climate Model, Climate Scenario, start year, {end year}, months, outLoc)
| Climate Model |
Global Climatic Models (GCM) you would like to query using the Cal-Adapt API. A list of GCMs from Cal-Adapt API (https://berkeley-gif.github.io/caladapt-docs/data-catalog.html#global-climate-models-gcm). |
|---|---|
| Climate Scenario |
To learn more about Representative Concentration Pathways (RCPs) go here. |
| start year |
Choose the first (or only) year to download (Historic: years available 1950-2013, RCP# years available 2006-2100) |
| end year (Optional) |
Choose the last year (if downloading a range) to download (Historic: years available 1950-2013, RCP# years available 2006-2100) |
| months |
Default value is 'all' the months in the year. You can specify an individual month (01 = Jan, 02 = Feb, etc) |
| outLoc |
Where would you like the data saved. |
Download the UCLA Dynamically Downscaled Product Data as NetCDF files from the Cal-Adapt Data Server.
The UCLA Center for Climate Science used the WRF regional climate model to dynamically downscale a 1991-2000 historical climate and five 2091-2100 future climates over California at 9km spatial resolution. The future period is based on the RCP8.5 “business-as-usual” greenhouse gas emissions scenario and contains results from 5 GCMs: CNRM-CM5, GFDL-CM3, INM-CM4, IPSL-CM5A-LR, and MPI-ESM-LR. Downscaled future climates are developed using the “psuedo-global warming technique”. In this technique, future boundary conditions are created by perturbing historical conditions with end-of-century changes from the GCMs and used to simulate high-resolution future climates within the interior of the boundaries. In this framework, variability is the same between the historical and future time periods, though a new mean climate exists in the future. 3-hourly SWE, Temp, and Precip are available for analysis from this dataset.