Land surface–precipitation interactions in the North American Monsoon: Sensitivity to land surface model initialization and coupling

Regions of western Mexico and the southwest United States receive 40-80% of their annual rainfall budget from precipitation associated with the North American Monsoon (NAM). Deep convection that is responsible for much of this precipitation has yet to be adequately resolved by models, suggesting that physical mechanisms controlling convection have not been properly represented. This study considers sensitivity of precipitation patterns during the monsoon observed by the North American Monsoon Experiment-2004 to different land surface treatments through the use of a high resolution modeling system that dynamically couples land surface and mesoscale meteorology models.

Synoptic-scale sources of moisture in the NAM have been identified as the Gulf of Mexico, the Gulf of California, and the Pacific Ocean, but ongoing work seeks to establish the contribution of local land surface features to low-level moisture and subsequent influences on precipitation processes. Factors such as local gradients in soil moisture, soil temperature, and evapotranspiration have been found to play a critical role in convective initiation over the Southern Plains of the United States, and likely play a critical role in the diurnal cycle of convection in the NAM as well. The Land Information System (LIS), developed by NASA, is run with the Noah land surface model (LSM) “offline” to create a high-resolution land surface dataset to initialize a run of the Weather Research and Forecasting model (WRF) for the 2004 monsoon season. Output from WRF, run with the Noah LSM and observationally enhanced datasets from the North American Regional Reanalysis (NARR), will be compared against output from LIS-initialized and fully LIS coupled WRF simulations. By conducting sensitivity studies using WRF and LIS-WRF, we aim to tie known spatial and temporal precipitation patterns to processes involving interaction of the land surface and atmosphere.