Data fusion in remote sensing in the ARM program using Python

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Tuesday, 4 February 2014: 11:30 AM
Room C302 (The Georgia World Congress Center )
Scott Collis, ANL, Argonne, IL

ARM uses a vast range of sensors; in-situ, column and volumetric remote sensing. The overarching goal of the program is to build a process level understanding of processes pertinent to the improvement of climate models. To achieve this goal modular software and a flexible development architecture is required to bring a variety of sensors to bear on this problem. This presentation will focus on the understanding of the physical processes surrounding precipitation rocesses and will cover a wide range of topics from operational implementation of retrieval algorithms on mid to large scale resources (> 40 cores) to using forward models integrated within the retrieval framework for both quality control and experiment design purposes. Finally this presentation will underscore the vital role of community-based software in serving the research community in building sustainable long lifecycle code.