9312686 Katz The modeling and analysis of the climate system is a complex problem that challenges the statistical, mathematical, and geophysical sciences. Increased collaboration among these sciences would result in more efficient analyses and more accurate interpretation of data from the climate system and its models, and in a more reliable assessment of accompanying uncertainties. It is proposed that a team of statistical scientist be assembled at the National Center for Atmospheric Research (NCAR) to help foster such a collaboration. NCAR, basefunded by the National Sciences Foundation, is a focal point for basic research on the atmosphere and has strong links to universities throughout North America. With the addition of more statistical and mathematical expertise, it could serve as well as a focal point for promoting collaboration among geophysical, statistical, and other mathematical sciences. The general objective is to develop and utilize new techniques of data analysis that arise from the collective understanding of physical scientists, mathematicians, and statisticians. The climate system has a very large number of degrees of freedom and exhibits some chaotic behavior. Consequently, the specific focus of the collaborative research would be on the development of inferential methods appropriate for high-resolution analysis of the climate system. Such analyses are appropriate both because realistic models of the climate system require the treatment of smaller scale phenomena, and because assessments of societal impact of climate require information on regional or smaller scales. Besides the immediate benefits to the scientific fields directly involved, improved understanding of the climate system would result in potential benefits to society that would be accrued indefinitely into the future. For instance, it could lead to improved weather and climate forecasts over a wide range of time scales from hours to seasons in advance, as well as to more realistic scenarios of future changes in climate. Such improvements would be of substantial value to decision makers and policy analysts.
