BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20190719T085743Z
LOCATION:HG D 1.1
DTSTART;TZID=Europe/Stockholm:20190612T153000
DTEND;TZID=Europe/Stockholm:20190612T160000
UID:submissions.pasc-conference.org_PASC19_sess147_msa209@linklings.com
SUMMARY:Advancing U.S. Weather Prediction Capabilities with Exascale HPC
DESCRIPTION:Minisymposium\nClimate and Weather\n\nAdvancing U.S. Weather P
 rediction Capabilities with Exascale HPC\n\nGovett\n\nA new revolution in 
 computing, modeling, data handling and software development is needed to a
 dvance U.S. weather prediction capabilities in the Exascale computing era.
  An estimated 1000 to 10000 times more computing is needed to advance pred
 iction models to cloud-resolving, 1KM resolution scales. However, existing
  models are not capable of exploiting exascale systems with tens to hundre
 ds of millions of processors. Weather prediction systems must be rewritten
  to incorporate new scientific algorithms, improved software design, and u
 tilize new technologies such as deep learning to speed up model execution,
  data processing, and information processing. This presentation will offer
  a critical assessment of key technologies and developments needed to adva
 nce U.S. operational weather prediction in the next decade.
END:VEVENT
END:VCALENDAR