Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America

TLDR

Large volumes of gridded climate data exist, yet their varying spatial resolutions and the need for advanced GIS skills make extracting site‑specific values difficult for risk assessments and ecological studies. This study introduces ClimateNA, a user‑friendly software package that streamlines the extraction of climate data for resource managers, decision makers, and scientists. ClimateNA locally downscales monthly historical and future climate layers across North America, generates scale‑free point estimates and biologically relevant variables, and provides 104 years of historical data, three paleoclimatic periods, and future projections under multiple GCMs and RCP4.5/8.5.

Abstract

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data.