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:20210916T132454Z
LOCATION:Jean-Jacques Rousseau
DTSTART;TZID=Europe/Stockholm:20210708T180000
DTEND;TZID=Europe/Stockholm:20210708T183000
UID:submissions.pasc-conference.org_PASC21_sess196_msa327@linklings.com
SUMMARY:Improving Predictions of the Terrestrial Water Cycle by Integrated
  Modelling, Data Assimilation and HPC
DESCRIPTION:Minisymposium\n\nImproving Predictions of the Terrestrial Wate
 r Cycle by Integrated Modelling, Data Assimilation and HPC\n\nHendricks-Fr
 anssen, Keller, Ghasemi, Goergen, Caviedes-Voullieme...\n\nThe modelling o
 f the terrestrial water and energy cycles is important for weather predict
 ion, climate scenarios, water resources assessment and for agricultural ap
 plications. We use the coupled terrestrial  systems model TSMP which simul
 ates the water and energy cycles from the deep subsurface to the upper atm
 osphere across terrestrial compartments. It is important to calculate at a
  high spatial resolution in order to capture small scale processes like ru
 noff generation at hill slopes. At the same time, predictions with such in
 tegrated models are affected by significant uncertainty related to unknown
  model parameters, initial conditions and boundary conditions. Data assimi
 lation allows to quantify and reduce this uncertainty by assimilating obse
 rvations and merging them with model predictions. The Parallel Data Assimi
 lation Framework (PDAF) was coupled to the Terrestrial Modelling Platform 
 (TSMP) for data assimilation. Computations with TSMP-PDAF are very compute
  intensive related to the high spatial resolution of the models covering l
 arge areas, and the large number of parallel model runs which are needed i
 n the context of data assimilation. Therefore massively parallel computati
 on is used for the model runs, with a good scalability, even for tens of t
 housands of processors. Recently, part of the TSMP-code has been ported to
  GPU-nodes. The TSMP-model is used for different applications like the 30 
 years long-term runs over the EUROCORDEX-domain, and the assimilation of s
 oil moisture data at the catchment or continental scale. The examples show
  how terrestrial systems modelling and data assimilation can improve hydro
 logical predictions at different spatial scales.\n\nDomain: CS and Math, E
 merging Applications, Climate and Weather
END:VEVENT
END:VCALENDAR