Authors: Karsten Shein*, University of Illinois, Michael Timlin, University of Illinois, Travis Ashby, University of Illinois, Zoe Zaloudek, University of Illinois
Topics: Climatology and Meteorology, Spatial Analysis & Modeling, Quantitative Methods
Keywords: climate change, data, spatial interpolation
Session Type: Virtual Lightning Paper
Start / End Time: 1:30 PM / 2:45 PM
Room: Virtual 28
Presentation File: Download
Growing attention on climate inequity across US communities has prompted increased research on the impacts of climate change at the community to sub-community level. Many social science datasets used to research and assess these effects are based on US Census Tract geographies. However, climate data are historically available either as point source or gridded datasets, requiring additional steps to accurately reconcile the two data sources prior to analysis. This paper describes the methodology and testing used by the Midwestern Regional Climate Center to remap daily gridded temperature data from NOAA’s 5 km x 5 km nClimGrid-Daily dataset to 2010 US Census Tract units, using a combination of spatial interpolation methods, to produce a spatially-consistent daily temperature dataset that can be directly evaluated at the scale of individual Census tracts. Data are made available via the Midwestern Regional Climate Center's data access system (mrcc.illinois.edu) as well as via NOAA's National Centers for Environmental Information (ncei.noaa.gov).