UCCWS 2013 - Third Annual Workshop on Understanding Climate Change from Data

Third Annual Workshop on Understanding Climate Change from Data
August 15-16 | Northwestern University, Evanston, IL
http://climatechange.cs.umn.edu/annual.php
OVERVIEW
Climate science has experienced a rapid transformation from a data-poor to a data-rich environment. In particular, climate related observations from remote sensors on satellites and weather radars, in situ measurements and sensor networks, as well as outputs of climate or Earth system models from large-scale computational platforms, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer huge potential for advancing the science of climate change and assessments of climate change impacts.
This workshop will bring together researchers who are advancing the computational analysis methods necessary for addressing key challenges in climate science. A major focus of the workshop is on computational data science tools that can extract patterns, trends, and predictive insights from climate data that capture the complex dependencies among climate variables, including transient phenomena and extreme events.
The program will include invited talks by leading experts in the field, panel discussions, and a poster session. Additional details will be posted on the workshop website as they become available.
CALL FOR PARTICIPATION
If you are interested in presenting your research at a poster session on the evening of August 15, 2013, please send a short abstract (~ 250 words) to uccws-AT-umn.edu with subject line “UCC12 Workshop Abstract Submission” no later than Friday, July 1. Limited travel support will be available for students and postdocs, see website for instructions.
For details, including a list of invited speakers, participants, program and travel arrangements, please visit the workshop website, linked below.
You can also find the program from last year’s workshop here: http://climatechange.cs.umn.edu/annual_2011.php
Topics include but not limited to:
? Climate change & impacts ? Spatiotemporal data mining
? Model evaluation & combination ? Extreme values & rare events
? Uncertainty assessments ? Associations & causalities
? Climate variability & attribution ? Predictive modeling
? Informing adaptation & policy ? Change & anomaly detection
Program Contact
Shyam Boriah
uccws-AT-umn.edu
Local Arrangements
Laura Connor
uccdata-AT-umn.edu