National Center for Atmospheric Research (NCAR) in Boulder, CO.
The development of new approaches to the creation of bias-corrected land surface air temperature datasets has the potential to improve the interpretation of historical surface temperature observations. This is a problem of high scientific and societal relevance as the temperature record forms a backbone for the scientific characterization of climate variability over the past century. It is also a challenge that is inherently statistical / mathematical in nature and where input from these communities is of paramount import.
This summer program, jointly sponsored by the Statistical and Applied Mathematical Sciences Institute (SAMSI) and by the Institute for Mathematics Applied to Geosciences (IMAGe) at the National Center for Atmospheric Research (NCAR), will bring together experts from the disciplines of climate science, statistics and applied mathematics with the goal of testing, comparing and perhaps extending methods. Applications will be considered from researchers in any of these disciplines, including junior researchers and graduate students.
For more details including a registration page to apply for the program, click here.