IN13B-1837
The Snow Data System at NASA JPL

Monday, 14 December 2015
Poster Hall (Moscone South)
Ross Laidlaw1, Thomas H Painter1, Chris A Mattmann1, Paul Ramirez1, Mary J. Brodzik2, Karl Rittger2, Kathryn J Bormann1, Annie Bryant Burgess3, Paul Zimdars1, Lewis John McGibbney1, Cameron E Goodale1 and Michael Joyce1, (1)Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States, (2)National Snow and Ice Data Center, Boulder, CO, United States, (3)University of Southern California, Computer Science, Los Angeles, CA, United States
Abstract:
The Snow Data System at NASA JPL includes a data processing pipeline built with open source software, Apache 'Object Oriented Data Technology' (OODT). It produces a variety of data products using inputs from satellites such as MODIS, VIIRS and Landsat. Processing is carried out in parallel across a high-powered computing cluster. Algorithms such as 'Snow Covered Area and Grain-size' (SCAG) and 'Dust Radiative Forcing in Snow' (DRFS) are applied to satellite inputs to produce output images that are used by many scientists and institutions around the world.

This poster will describe the Snow Data System, its outputs and their uses and applications, along with recent advancements to the system and plans for the future. Advancements for 2015 include automated daily processing of historic MODIS data for SCAG (MODSCAG) and DRFS (MODDRFS), automation of SCAG processing for VIIRS satellite inputs (VIIRSCAG) and an updated version of SCAG for Landsat Thematic Mapper inputs (TMSCAG) that takes advantage of Graphics Processing Units (GPUs) for faster processing speeds. The pipeline has been upgraded to use the latest version of OODT and its workflows have been streamlined to enable computer operators to process data on demand. Additional products have been added, such as rolling 8-day composites of MODSCAG data, a new version of the MODSCAG 'annual minimum ice and snow extent' (MODICE) product, and recoded MODSCAG data for the 'Satellite Snow Product Intercomparison and Evaluation Experiment' (SnowPEx) project.