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IMAGe Theme-of-the-Year (T-O-Y)
The Theme-of-the-Year is a program to focus on specific areas of research that will benefit from intense collaborative effort. The topics will be selected by the IMAGe external advisory panel and will be coordinated by a Visiting Co-director.
Theme for 2007: Statistics for Numerical Models
Numerical models are vital to simulate geophysical, chemical
and ecological processes and to understand the relationship among
components in the Earth system. As models have become larger and
more complex, their construction, validation and analysis are no
longer amenable to simple approaches and statistical summaries.
Statistical science in the past 20 years has advanced to handle
the interpretation of complicated multivariate, spatial and
temporal data sets and it is well suited to tackle the massive
outputs from numerical experiments that are now the norm in the
geosciences. This theme is undertaken with the goal of matching
cutting edge statistical methods to the needs of geophysical model
development and to make statisticial scientists aware of the
particular scientific issues and research in the geophysical
Workshops II and III will be more traditional conferences but will include a blend of tutorial and research talks. In each workshop, ample time will be reserved for discussion and also for presentations on progress on the specific modeling project initiated in the first workshop.
The summer graduate workshop will be in partnership with MSRI and focuses on the mathematical tools such as inverse methods and data assimilation to estimate the surface sources of carbon dioxide. The determination of sources of carbon in the Earths' atmosphere is an important area of biogeochemistry and crucial in quantifying human emissions of greenhouse gases. The summer graduate workshop will build off of the successful model that was held July 2006 at MSRI and will feature morning tutorial lectures with reinforcing afternoon computational exercises and projects. The Data Assimilation Research Testbed (DART) will be used as a software framework for the mathematical and statistical methods.