While not strictly cryosphere, I thought this webinar (and community) would be of interest to many of those in the Cryosphere community. IS-GEO aims to support an emerging community of researchers in geosciences (GEO) and intelligent systems (IS). This research coordination network will enable advances in our understanding of Earth systems through innovative applications of intelligent and information systems to fundamental geosciences problems.
---------- Forwarded message ---------
From: Daniel Garijo <[hidden email]>
Date: Tue, Sep 26, 2017 at 4:31 AM
Subject: [Is-geo] REMINDER: Join the monthly IS-GEO Telecon - Tuesday, October 3rd at 12pm PT
To: <[hidden email]>
Hello IS-GEO Researchers,AGENDA
Next week, on Tuesday, October 3rd we will host the 6th IS-GEO monthly teleconference call. You can find the links for the call in numbers and online portion of the call at the end of this message.
Call topics will include updates on the IS-GEO network activities and opportunities to participate. The invited speaker, Dr Juan M. Restrepo, will present "How Warm is it Getting?" and Other Tales in Uncertainty Quantification
You can find an Agenda for the call here: https://docs.google.com/document/d/1GiYFKJ2SzjK9wRaLCPqPe-YltJJ0M8uqv-ei247CHgw/
We look forward to talking with you all and catching up on network events and news together!Daniel
Brief Welcome and General Updates (Suzanne Pierce – 5 minutes)
Update IS/GEO RCN collaborative publications (Imme Ebert-Uphoff – 5 minutes)
Updates on IS-GEO Paper (Yolanda)
Events, Conferences, and News: (Suzanne Pierce)
Selected Topics from Working Groups:
Invited Presentation Series (30 minutes):
"How Warm is it Getting?" and Other Tales in Uncertainty Quantification
In the statistics community “Big Data” science is meant to suggest the combining of inferential and computational thinking.
We also speak of big data in the geosciences. However, the problems we pursue are often extreme in the number of degrees of freedom, and in many instances, non-stationary in its statistics. This usually means that we are working with sparse observational data sets, even if the number of observations is large. The Bayesian framework is a natural inferential data assimilation strategy in geosciences, to some extent because the degrees of freedom in the problem vastly outnumber observations but more critically, because the models we use to represent nature have considerable predictive power.
Looking toward the future, we expect improvements in computational efficiency and finer resolutions in models, as well as improved field measurements. This will force us to contend with physics and statistics across scales and thus to think of ways to couple multiphysics and computational resolution, as well as to develop efficient methods for adaptive statistics and statistical marginalization.
How this coupling is exploited to improve estimates that combine model outcomes and data will be described in tracking hurricanes and improving the prediction of the time and place of coastal flooding due to ocean swells. Estimating the trend of Earth’s temperature from sparse multi-scale data will be used as an example of adaptivity in time series analysis.
Other open challenges in non-stationary big data problems will be described, where progress could result from “Big Data Geoscience,” the tighter integration of geoscience, computation, and inference.
Call Connection Information:
Join from PC, Mac, Linux, iOS or Android: https://zoom.us/j/675166710
Or iPhone one-tap (US Toll): <a href="tel:+1%20408-638-0968" value="+14086380968" target="_blank">+14086380968,675166710# or <a href="tel:+1%20646-558-8656" value="+16465588656" target="_blank">+16465588656,675166710#
Dial: <a href="tel:+1%20408-638-0968" value="+14086380968" target="_blank">+1 408 638 0968 (US Toll) or <a href="tel:+1%20646-558-8656" value="+16465588656" target="_blank">+1 646 558 8656 (US Toll)
Meeting ID: 675 166 710
International numbers available: https://zoom.us/zoomconference?m=z_Ou3c1kmecPqLel21HI1i6xG-N0X73n
Upcoming Call Dates:
Oct 3, 2017 2:00 PM - Speaker: Juan M. Restrepo
Nov 6, 2017 2:00 PM - Speaker: Victor Pankratius
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