BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Sagy Ephrati (University of Twente) DTSTART:20230920T111500Z DTEND:20230920T120000Z DTSTAMP:20260417T003327Z UID:cam/3 DESCRIPTION:Title: Stoc hastic modeling for coarse computational geophysical fluid dynamics\nb y Sagy Ephrati (University of Twente) as part of CAM seminar\n\nLecture he ld in MV:L14.\n\nAbstract\nStochasticity has been employed systematically in geophysical fluid dynamics (GFD) to model uncertainty. Additionally\, f ully resolving geophysical flows is computationally expensive due to the l arge range of scales of motion present in these flows. These computational costs are efficiently mitigated by performing GFD simulations on coarse c omputational grids and modeling the effects of unresolved scales on resolv ed scales. On such grids\, the uncertainty due to unresolved small-scale m otions has to be taken into account as well as the loss of accuracy due to poorly resolved spatial derivatives. In this presentation\, we discuss ho w data assimilation methods can be used to derive data-driven stochastic f orcing for coarse computational GFD. We will show that a straightforward a lgorithm\, based on several simplifying assumptions\, already leads to qua litatively accurate outcomes at strongly reduced computational costs.\n LOCATION:https://researchseminars.org/talk/cam/3/ END:VEVENT END:VCALENDAR