Abstract
Abstract : Climatology traditionally obtained by mission planners consists of primarily basic statistics derived from a long-term mean of a data set of station observations or large-scale numerical weather prediction (NWP) analyses. These statistics (e.g., long-term means, max./min. value, and standard deviation) are static in nature; once computed they do not change. These statistics are useful; however, they flatten out the climate anomalies and are unable to represent a range of climatic conditions of a local area. It is desirable that the climate statistics used by mission planners reflect the climate anomalies, recent trends, mesoscale characteristics (high resolution), and up-to-date information. We recommend that we fulfill these mission planner needs by generating on-demand mesoscale/regional climate statistics for any given area and for a specific time period. This project has successfully demonstrated how these mission planning needs can be fulfilled by using the NWP downscaling technique. It is estimated that the on-demand climatology can be generated in one to two months depending on the specific needs and coverage of the domain and time.
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