Improving Surface Hydrometeorological Fields
Satellite data analysis, data assimilation and model application
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Satellite data is vital for understanding atmospheric properties, particularly those pertaining to cloud cover and its properties. Cloud cover is a key paremeter controlling and linking downward components of short-wave and long-wave surface radiation and precipitation on the land surface energy and water balance. On the other hand, hydrologists are now actively using the available high-resolution land and snow cover, topography, soil and vegetation characteristics data sets to parameterize distributed hydrologic models and to couple these models with atmospheric models. Adequate evaluation of...
Satellite data is vital for understanding atmospheric properties, particularly those pertaining to cloud cover and its properties. Cloud cover is a key paremeter controlling and linking downward components of short-wave and long-wave surface radiation and precipitation on the land surface energy and water balance. On the other hand, hydrologists are now actively using the available high-resolution land and snow cover, topography, soil and vegetation characteristics data sets to parameterize distributed hydrologic models and to couple these models with atmospheric models. Adequate evaluation of these coupled models will depend on the accurate estimation of fine-resolution surface variables. This book is focused on correcting the modeled cloud cover in an atmospheric model thus allowing the model radiation and precipitation codes to calculate the actual spatial variability generated by the observed clouds. The benefits of this work will not only enhance the realism of radiation in the model, but it may also increase the model's capability to predict the location and amount of precipitation.
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