Many of the dominant patterns of landscape variability arising from changes in terrain, vegetation, hydrology, are expressed at scales far below those of current climate models. These patterns, in ...part, control terrestrial hydroecology and biogeochemistry, which, in turn, is a significant modulator of the atmosphere. The goal of this project was to develop and implement a spatially-explicit framework for modeling land surface processes at length scales several multiples finer than those of parent atmospheric models. Recent results show that inclusion of sub-grid, spatially referenced representations of landscape features such as terrain, land cover and land use produce significant atmospheric responses under current climate scenarios. Model sensitivities are attributed to improved resolution of coastlines, differences in spatially aggregated fluxes and a much more realistic representation of topographic variations. The framework for representing sub-grid terrain features within the Community Land Model (CLM)-Community Climate System Model (CCSM) will be presented as will results from current climate simulations. Future issues related to the multi-scale coupling of CLM and CCSM will also be discussed.
The North American Monsoon (NAM) system is an annual weather pattern that brings summer rains to the dry regions of the United States southwest and northwestern Mexico. Broader effects are that NAM ...exerts substantial control on the warm‐season climate over North America and is responsible for the occurrence of many high‐impact weather and climate events such as floods and droughts. The North American Monsoon Experiment (NAME) Higgins et al., 2005 was developed and implemented in an effort to improve the low prediction skill of intraseasonal and seasonal forecasts of NAM behavior.
The North America Monsoon System (NAMS) is the principal feature of summer climate of Mexico and the Southwest U.S., and this study explores the development of statistically downscaled estimates of ...warm season precipitation over the core region of the North American Monsoon Experiment (NAME). Normalized accumulated daily-total summer precipitation anomalies for northwest Mexico for the period 1950 to 1998 are manipulated through a rotated empirical orthogonal function procedure in which three contiguous precipitation regions were realized. Hence, each of these sub regions is studied separately. Using output variables from a 1998 version of the National Centers for Environmental Predictions medium-range forecast (MRF) model, we sought to determine which variables are important predictors of the hydrometeorological and boundary layer features responsible for NAMS rainfall. Choice of MRF predictors is important. The K-Nearest Neighbor algorithm (KNN), an analog-type statistical downscaling technique, is applied to derive local-scale predictions of precipitation from specified MRF model variables. We evaluated the quality of downscaled product in terms of a standard suite of verification metric.
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