Doug Nychka, Richard Katz, Joe Tribbia, National Center for Atmospheric Research, Climate and Global Dynamics Division, Geophysical Statistics Project, National Center for Atmospheric Research, Environmental and Societal Impacts Group, National Center for Atmospheric Research, Climate and Global Dynamics Division
The mission of the Geophysical Statistics Project (GSP) is to encourage the application and further development of statistical analysis to problems faced in the Earth sciences. GSP is an institution-wide effort at the National Center for Atmospheric Research (NCAR) and is funded by the Division of Mathematical Sciences of the National Science Foundation. Some major research areas of GSP are: extension of statistical methodology for spatial processes and space/time processes; application of modern regression and model selection to the analysis of geophysical data; deriving a statistical basis for forecasting including the assimilation of observational data with numerical models; modeling complicated physical processes through Bayesian hierarchical models; and understanding physical processes through the use of dynamical systems and nonlinear time series. The GSP attempts to serve as a bridge between the atmospheric-oceanographic and the statistical-probabilistic research communities. The project sponsors visits by statisticians at various levels, as well as postdoctoral positions. Datasets, reports, and software may be downloaded, and links are provided to useful statistics and atmospheric sites.
This description of a site outside SERC has not been vetted by SERC staff and may be incomplete or incorrect. If you
have information we can use to flesh out or correct this record let us know.
This resource originally cataloged at:
Subject: Geoscience:Geology, Atmospheric Science, Oceanography:Physical , Geoscience:Oceanography, Biology, Geoscience:Hydrology, Atmospheric Science:Climatology , Environmental Science:Ecosystems:Biogeochemical cycling Resource Type: Datasets and Tools:Datasets, Tools, Audio/Visual:Images/Illustrations, Maps Grade Level: Graduate/Professional Data Derived: Data Derived Data Source: Real-Time Data, Observational Data Science Background Required: Basic scientific background required Theme: Teach the Earth:Course Topics:Atmospheric Science, Hydrology/Hydrogeology, Teach the Earth:Incorporating Societal Issues:Climate Change, Teach the Earth:Course Topics:Oceanography, Environmental Science, Biogeoscience, Teach the Earth:Teaching Topics:Water