Pre-processed data for Davenport and Diffenbaugh 2021

This dataset contains pre-processed data used in the paper "Using machine learning to analyze physical causes of climate change: a case study of U.S. Midwest extreme precipitation" by Davenport and Diffenbaugh (2021). Included files: - GHCN station data for Midwest region- daily 500-hPa geopotential height anomalies (with domain-average trend removed)- daily SLP anomalies- daily moisture flux- layerwise relevance propagation resultsCode and other data supporting the analysis is available at https://github.com/fdavenport/GRL2021