The prediction of hydrometeorological processes is hindered by the limited capabilities of integrated models that properly handle land surface physics in complex terrain. A key issue for improved intraseasonal simulations in western North America is capturing the variability in land surface conditions in mountain areas. Two of these areas – central Rocky Mountains in U.S. and Sierra Madre Occidental in Mexico – provide ideal areas for developing hydrometeorological model improvements as they span a clear hydroclimate gradient from cold to warm-season dominated regimes. Two related questions need to be addressed to enhance warm-season hydrometeorological forecasts in mountain regions: How do land surface conditions and their memory enhance or surpress convective precipitation in mountain regions? and How do variations in climate and vegetation along the continental hydroclimate gradient impact the relations between land surface physical processes and convective precipitation? Both questions are fundamental to understanding intraseasonal climate processes and improving operational models and their reanalysis products in the region.
Our proposal focuses on improved process simulations using hydrometeorological models in two mountain regions as proxies for similar systems across the North American hydroclimate gradient. We are especially interested in demonstrating how regional topographic features interact with the land surface state and its memory (soil moisture and temperature, vegetation and irrigation/reservoirs) to modify intraseasonal precipitation characteristics that control hydrologic response (flooding and drought). The study focuses on regions with low intraseasonal predictability in convective precipitation, soil moisture and streamflow, thus requiring new physical insight obtained from field data, remote sensing and numerical modeling. We will take advantage of intense observation and forecasting periods carried out by the proponents and an existing network of research and operational instruments. Our efforts are aimed towards improved characterization of intraseasonal variability in precipitation, land surface conditions and streamflow through use of two versions of a coupled hydrometeorological modeling system.
To address the science questions outlined above, we propose the following project elements: (1) Hydrometeorological data collection and diagnostic analysis in the two mountain areas to define the characteristic behavior of the regional hydrometeorology and land surface conditions and construct an observational/reanalysis archive for model testing; (2) Conduct idealized hydrometeorological modeling experiments that mimic local topographic conditions and explore the impact of prescribed (and perturbed) land surface state variations in space and time on convective precipitation and its characteristics; and (3) Three-dimensional hindcast and forecast experiments using a coupled hydrometeorological model that incorporates key findings of the idealized model runs to demonstrate how different land surface physics in each region yield important up-scaled impacts on precipitation and streamflow variability at intraseasonal time scales. Comparison of the two mountainous regions along the hydroclimate gradient will allow a direct test of the relevance of land surface memory on intraseasonal precipitation variability.