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Abstract:
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The human impacts of changes in heat events depend on changes in the joint behavior of temperature and humidity. Little is currently known about these complex joint changes, either in historical observations or projections from general circulation models (GCMs). Further, it is well understood that GCM output should not be used directly for future simulations for impacts assessments, because GCMs do not fully reproduce the observed historical climate distribution, implying a need for simulation methods that combine information from GCMs with observational data. We advocate for an observation-based, conditional quantile mapping approach to this problem. A temperature simulation is first produced by transforming historical observations to account for GCM-projected changes in mean and temporal covariance structure; given that, a humidity simulation is produced by transforming observations to account for projected changes in the conditional humidity distribution given temperature. We study changes in summertime temperature and humidity over North America within the Community Earth System Model Large Ensemble (CESM-LE), and the proposed method is applied using these changes.
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