Climate data for adaptation and vulnerability assessments
Acronym
ClimAVA
Name
Climate data for adaptation and vulnerability assessments
Description
The ClimAVA (https://climate.usu.edu/climava/) dataset provides high-resolution (4km), bias-corrected, downscaled future climate projections derived from 17 CMIP6 General Circulation Models. It includes three key variables — precipitation, minimum, and maximum temperature — for three Shared Socioeconomic Pathways (SSP245, SSP370, SSP585) on a daily scale. Employing the Spatial Pattern Interactions Downscaling (SPID) method, ClimAVA ensures high-quality downscaling using machine learning models. These models capture the relationship between spatial patterns at Global Circulation Model (GCM) resolution and fine-resolution pixel values. Essentially, a random forest model is trained for each pixel, using the finer reference data as a predictand and nine pixels from the spatially resampled (coarser) version of the reference data as predictors. These models are then utilized to downscale the bias-corrected GCM data. Results from this method have proven to maintain climate realism and greatly represent extreme events.