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Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes
Authors:Christopher M Johnson  Xingang Fan  Rezaul Mahmood  Chris Groves  Jason S Polk  Jun Yan
Institution:1.Department of Geography and Geology,Western Kentucky University,Bowling Green,USA;2.Kentucky Climate Center,Western Kentucky University,Bowling Green,USA;3.Crawford Hydrology Laboratory,Western Kentucky University,Bowling Green,USA;4.Center for Human GeoEnvironmental Studies,Western Kentucky University,Bowling Green,USA
Abstract:Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land–atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.
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