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Summer Graduate School

Climate Change - Summer Graduate Workshop July 14, 2008 - August 01, 2008
Organizers Christopher Jones (UNC Chapel Hill and U Warwick, UK), Inez Fung (U.C. Berkeley), Eric Kostelich (Arizona State University), K.K. Tung (U. Washington), and Mary Lou Zeeman (Bowdoin College), Charles D. Camp (Cal Poly, San Luis Obispo), Rachel Kuske (Univ British Columbia)
Lecturer(s) No Lecturers Assigned Yet.
Speaker(s) No Speakers Assigned Yet.
Description The goal of the workshop will be to discern ways in which mathematics can contribute and to expose new researchers to some of the key areas that we believe will form the basis of serious mathematical considerations of climate change issues. It is part of a larger 3 week program to bring both graduate students and researchers together to jointly study ways to engage in meaningful collaborations. See Climate Change Summer School . Mathematical contributions are needed at two levels. Addressing climate change presents daunting challenges to the scientific community. It involves scientists with expertise varying from concrete engineering design to those formulating economic and political policies. Mathematical analysis of models plays a key coordinating role in making these models as effective as possible. Mathematicians are needed to formulate and refine models, understand their limitations and optimize the underlying computational strategies. At the same time, there is considerable basic research that needs to be done to properly ground the modeling, and resulting predictions. Mathematical input is badly needed to delineate the limits of reasonable predictability and quantify inherent uncertainties. Since the underlying models are highly nonlinear, complex evolving systems with stochastic inputs, there are considerable, and exciting basic research contributions to be made at a deep mathematical level. We shall emphasize this latter aspect in the summer program. Three themes will drive the workshop: Prediction and uncertainty The issues of prediction and uncertainty bring the mathematical areas of dynamical systems and stochastic processes to the fore. Dynamical systems concerns itself with the functioning of evolving systems, and thus of prediction in models. The quantification of uncertainty can be formulated in terms of an evolving probability density function, which underlies the study of stochastic processes. These two mathematical areas are foundational in our approach to mathematical climate change research. Economic impact and decision-making As climate change research begins to have concrete impact, it has become clear that sociopolitical actions and decisions cannot be ignored, and models incorporating feedback to the climate of social actions are badly needed. At this stage, it is not as clear where such investigations will take us in the mathematical realm. Nevertheless, we see it is an important direction to investigate due to its importance and urgency, and the fact that complex, hybrid models will be formulated that will likely raise significant, and interesting, mathematical questions. Incorporating and assimilating data Data relevant to the climate is becoming increasingly available. The message from short range weather prediction is that incorporating that data into prognostic models is essential in making sensible predictions and robust models. This area of data assimilation is thriving in both the mathematics and statistics communities. Its adaptation to the complex climate models poses many deep challenges and it take a central role in the program. It fits well with the emphasis discussed above on prediction and uncertainty as it rests on the same concepts and calls into play the same foundational areas of dynamical systems and stochastics. Schedule 7/14 - 7/18 (PDF 132KB) In the first half of the summer school (July 14- July 23) there will be short courses in: Climate Modeling, Data Assimilation, Dynamical Systems, Stochastic Processes, Statistics, and Computation Methods which will be aimed at graduate strudents and postdocs. Students will also work on mentored research projects in teams. The second half of the summer school (July 24 - Aug 1) will involve brainstorming on mathematical issues in climate science. Working groups will be formed to address specific issues and formulate plans and concrete problems. This will be an exciting opportunity for students to be a part of high-level efforts to grapple with difficult questions and forge research directions that promise impact on climate change research as well as interesting mathematics. Students will be integrated into the work of the brainstorming workshop in several ways: they will present their projects aimed at defining a mathematical question in climate research, as starting points for further discussion; and they will be assigned a senior mentor who will work with them to draft the reports of each day’s activities. Meetings will then be held at the end of each day for the students to meet with each other and share their insights. We anticpate all the graduate students will stay for the whole miniprogram, i.e. three weeks. At most 40 students will be accepted into the program, but all will be fully funded for travel, lodging, and meals. If you are a student that is a member of our Academic Sponsors, please consult your institution's representative to see if you have been nominated for a position in this workshop. Successful applicants will be informed of their admission into the summer graduate workshop in the latter half of March. If you were a participant, we would appreciate your taking time to fill out the Check-Out Form [Microsoft Word .doc format]