Probability-Weighted Ensembles Of U.S. County-Level Climate Projections For Climate Impact Modeling
Year: 2017
Type: article
Abstract: These are binned projections of daily weather (1981-2100) used in the study, “Estimating Economic Damage from Climate Change in the United States” by Hsiang et al., (forthcoming). They are from probability-weighted ensembles constructed in Rasmussen et al., (2016). The code used to generate these data is available on github: https://github.com/dmr2/acp_physical Weather Variables: Temperature (degrees C; bin width of 1 degree C): daily average temperature, daily maximum temperature, daily minimum temperature Precipitation (mm; bin width of 2 mm): total daily precipitation Probability Weights: The files labeled as <RCP>_2090_SMME.tsv contain probability weights and a global mean temperature trajectory (relative to the period 1981-2010) for each ensemble model. Please see Rasmussen et al., 2016 for an explanation of how the probability weights were calculated and how to use them. References: D.J. Rasmussen, M. Meinshausen, and R.E. Kopp, 2016: Probability-weighted ensembles of U.S. county-level climate projections for climate risk analysis. J. Appl. Met. Clim. 55 (10), 2301-2322 doi:10.1175/JAMC-D-15-0302.1
Authors: Rasmussen, D.J., Kopp, Robert E.
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W3206220438