Combining Weather Data for a Dataset Sufficient for Generating High-Resolution Weather Prediction Models

摘要: Assessments of the effects climate change typically require information at scales 10 km or less. In regions with complex terrain, much spatial variability in (temperature, precipitation, and snow water) occurs on below km. Since typical global model simulations grid size is more than 200 km, it necessary to develop models higher resolution. Unfortunately, no datasets currently produced are both highly accurate provide data a sufficiently high As result, current forced ignore important variations that occur scale. This predicament prompted creation hybrid dataset for temperature, relative humidity. The resulting illustrated importance having high-resolution gives clear proof terrain fine resolution give an represent ion their climatology. For example, Andes Mountains Chile cause temperature shift 25C within same area as single 2.5 cell from NCEP dataset. Fortunately CRU, U.D., GPCP, datasets, when hybridized, able precisionmore » satisfactory coverage. composite will enable development quality empirical downscaling methods--both which scientists accurately predict change. Without long-term forecasts, climatologists policy makers not have tools they need effectively reduce negative human activity earth.« less