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DTSTART:19700308T020000
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DTSTAMP:20230124T171522Z
LOCATION:C141
DTSTART;TZID=America/Chicago:20221113T113000
DTEND;TZID=America/Chicago:20221113T120000
UID:submissions.supercomputing.org_SC22_sess421_ws_drbsd106@linklings.com
SUMMARY:What Can Real Information Content Tell Us about Compressing Climat
 e Model Data?
DESCRIPTION:Workshop\n\nWhat Can Real Information Content Tell Us about Co
 mpressing Climate Model Data?\n\nSather, Pinard, Baker, Hammerling\n\nThe 
 massive data volumes produced by climate simulation models create an urgen
 t need for data reduction. Lossy compression is one solution that can sign
 ificantly reduce storage requirements, however, as the amount of compressi
 on applied increases, the scientific integrity of the data decreases. One 
 metric for gauging the quality of compression is the percentage of real in
 formation present in the original data that is preserved in the compressed
  data. We compute bitwise real information content for several climate var
 iables from the Community Earth System Model Large Ensemble provided by th
 e National Center for Atmospheric Research and investigate the amount of c
 ompression that can be applied to each of these climate variables using tw
 o popular compression algorithms designed for floating-point data while pr
 eserving 99% of the real information content. Finally, we demonstrate how 
 the real information content can be used in a straightforward manner to de
 termine compressor settings for our data.\n\nSession Format: Recorded\n\nR
 egistration Category: Workshop Reg Pass
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