Published May 22, 2017 | Version v1
Journal article Open

Probability-weighted ensembles of U.S. county-level climate projections for climate impact modeling

  • 1. Princeton University
  • 2. Rutgers University

Description

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

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