Downscaling the North America Monsoon using CWRF: Model resolution and the depiction of precipitation climate and variability

The North American Monsoon (NAM) provides more than half of the annual rainfall to many areas of southwest North America. Coarse-resolution climate models predict a drier NAM with more extreme precipitation events in the future, which will stress the people and ecosystems of the region. However, the resolution of these models is too low to accurately portray mesoscale processes that are known to be crucial to the NAM precipitation climate. This study aims to use the Weather Research and Forecasting with the Climate Extension (CWRF) to dynamically downscale general circulation model (GCM) simulations for more realistic prediction of climate change over the NAM domain. The CWRF will initially be nested in reanalyses (NCEP/NCAR, ECMWF, MERRA) down to 25 km resolution over the NAM domain and run 1998-2008 to assess its ability to determine the sensitivity to differing boundary conditions. The resolution will be adjusted to qualitatively determine the best balance between resolution and computing resources. Various convective schemes will also be tested via additional model runs. All results will be compared to observed satellite- and gauge-based rainfall datasets to quantitatively determine skill improvement at diurnal, synoptic, intraseasonal, seasonal, and interannual timescales. Because dynamic downscaling improves the resolution of topography, it is expected to more accurately depict orographic influences on precipitation and the precipitation diurnal cycle when compared to GCMs, such that the precipitation climate is better represented and predicted. Results will also be compared with surface and upper-air observations to see how well the CWRF portrays NAM spatiotemporal processes and interactions, including physical mechanisms linking tropical easterly waves, the Madden-Julian Oscillation, tropical cyclones, and gulf surges to precipitation, which have been suggested in previous studies.