Toward the credibility of northeast United States summer precipitation projections in CMIP5 and NARCCAP simulations

Abstract

Precipitation projections for the northeast United States and nearby Canada (Northeast) are examined for 15 Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) models. A process-based evaluation of atmospheric circulation features associated with wet Northeast summers is performed to examine whether credibility can be differentiated within the multimodel ensemble. Based on these evaluations, and an analysis of the interannual statistical properties of area-averaged precipitation, model subsets were formed. Multimodel precipitation projections from each subset were compared to the multimodel projection from all of the models. Higher-resolution North American Regional Climate Change Assessment Program (NARCCAP) regional climate models (RCMs) were subjected to a similar evaluation, grouping into subsets, and examination of future projections. CMIP5 models adequately simulate most large-scale circulation features associated with wet Northeast summers, though all have errors in simulating observed sea level pressure and moisture divergence anomalies in the western tropical Atlantic/Gulf of Mexico. Relevant large-scale processes simulated by the RCMs resemble those of their driving global climate models (GCMs), which are not always realistic. Future RCM studies could benefit from a process analysis of potential driving GCMs prior to dynamical downscaling. No CMIP5 or NARCCAP models were identified as clearly more credible, but six GCMs and four RCMs performed consistently better. Among the “Better” models, there is no consistency in the direction of future summer precipitation change. CMIP5 projections suggest that the Northeast precipitation response depends on the dynamics of the North Atlantic anticyclone and associated circulation and moisture convergence patterns, which vary among “Better” models. Even when model credibility cannot be clearly differentiated, examination of simulated processes provides important insights into their evolution under greenhouse warming.