The More Extreme Nature of North American Monsoon Precipitation in the Southwestern United States (Invited Presentation)

Most severe weather in the Southwestern United States occurs during the North American monsoon. This research examines how monsoon extreme weather events will change with respect to occurrence and intensity. A new technique to severe weather event projection has been developed, using convective perimitting regional atmospheric modeling of days with highest instabilty and atmospheric moisture. The guiding principle is to use a weather forecast based approach to climate change project, with a modeling paradigm in which organized convective structures and their behavior are explicitly physically represented in the simulation design. Of particular interest is the simulation of severe weather events caused by mesoscale convective systems (MCSs), which account for a greater proportion of monsoon rainfall downwind of the Mogollon Rim in Arizona, in the central and southwestern portions of the state. The convective-permitting model simulations are performed for identified severe weather event days for both historical and future climate projections, similar to an operational weather forecast.

There have been significant long-term changes in atmospheric thermodynamic and dynamic conditions that have occurred over the past sixty years. Monsoon thunderstorms are tending to be more 'thermodynamically dominated' with less tendency to organize and propagate. Though there are tending to be a fewer number of strong, organized MCS-type convective events during the monsoon, when they do occur their associated precipitation is now tending to be more intense. The area of central and southwestern Arizona, corresponding to the area of the state most impacted by MCSs during the monsoon, appears to be a local hot spot where precipitation and downdraft winds are becoming more intense. These types of changes are very consistent with the historical observed precipitation data and model projections of historical and future climate, from dynamically downscaled CMIP3 and CMIP5 models.