Understanding the Mesoscale Response to Climate Change Using a Regional Climate Model Ensemble

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As the name suggests, global warming is a planet-wide response to the energy imbalance caused by increases in greenhouse gases, which spread out and mix to a uniform concentration around the globe. But despite its global nature the effects of global warming can vary even within small regions, depending on local contrasts in topography, ground cover, wind direction, and other factors. Such local effects can be be studied with global climate models (GCMs), but global models have limited ability to represent small-scale effects. Even when GCM results are robust and physically reasonable they can still be misleading if physical mechanisms occurring on scales too small to be adequately represented by GCMs turn out to be more influential than the larger-scale effects that they do capture. An alternative strategy is to use a regional climate model (RCM), which simulates weather and climate over a limited area using information from the global model to connect that region to the rest of the world. The RCM can represent processes on smaller scales than the GCM, and a mismatch between GCM and RCM results can indicate a "mesoscale surprise", in which a local climate change expected from large-scale considerations is upstaged by smaller-scale processes (mesoscale is a technical term referring to spatial scales which are smaller than frontal weather systems but larger than individual cumulus clouds).This project seeks to understand the role of mesoscale physical processes in shaping climate change in the Pacific Northwest (PNW), where the combination of mountainous terrain, proximity to the coast, and alternation of onshore and offshore wind patterns creates an ideal natural laboratory for studying mesoscale surprises. As one example, GCMs suggest that the greatest increase in flooding will occur in river basins in which runoff comes from a mix of rain and snow-melt, since warming reduces snowpack and snowpack has a moderating effect on streamflow. But in RCM simulations, which are better suited to representing precipitation in mountainous regions, the greatest increase in flood risk happens in low-elevation, rain-dominated river basins. These basins are more exposed to heavy rain, thus they are more susceptible to the increase in precipitation intensity that occurs as climate warms.Work performed here uses an ensemble of RCM simulations, each one performed using output from a different GCM simulation, to examine the effects of global warming on the weather and climate of the PNW. The RCM used in the study is the Weather Research and Forecasting (WRF) model, and GCM simulations are taken from the Coupled Model Intercomparison Project (CMIP). The use of an ensemble allows an assessment of the sensitivity of results to differences in model formulation, and ensures that the research focuses on the robust model behaviors which are most likely to have simple physical explanations. A key concern in the research is the effect of biases on GCM projections for future climate change. For instance the loss of snowpack has strong implications for local climate and hydrology, thus a model which incorrectly simulates snowpack in a region which is not typically snow covered will likely overestimate sensitivity to warming in that region. The project also uses the RCM ensemble to look at the likelihood that climate change will increase the risk of wildfires in the PNW.The work is of societal as well as scientific interest as much of the effort in responding to climate change occurs at the local level. The Principal Investigators are engaged with a number of local organizations involved in planning for climate change, including the King County Department of Natural Resources, the US Forest Service, and Seattle City Light. The project involves undergraduate students through the Bothell campus of the University of Washington, which is a primarily undergraduate institution. It also supports a postdoctoral associate, thereby providing for the future scientific workforce in this research area.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.