Collaborative Proposal: FRG: Statistical Analysis of Uncertainty in Climate Change

点击翻译按钮获取中文摘要

Proposal Ids: DMS - 0204232; DMS - 0139948; DMS - 0139903PIs: L. Mark Berliner; Richard A. Levine; Christopher K. WikleTitle: FRG: Statistical Analysis of Uncertainty in Climate ChangeABSTRACTThere is a growing consensus among scientists that aspects of our planet's climate are changing due to human influences, though the scientific community acknowledges that substantial uncertainty exists regarding the forms, levels, and impacts of change. Quantifying these uncertainties requires new statistical research informed by climate science. Effective solutions to climate change problems will rely on new methods for combining the information content of models and data in a fashion that quantitatively manages uncertainty. The research team will rely extensively on Bayesian hierarchical modeling and analysis strategies. Specific projects will include (1) developing new probabilistic climate change assessments based on an extensive suite of climate simulations; (2) statistical procedures for combining different climate models to produce climate projections; and (3) assessing regional and local impacts of global climate behavior.Describing the Earth's climate and predicting its responses to human influences are critical problems in science and public policy. The research team of statisticians and climate modeling experts from the National Center for Atmospheric Research will develop new statistical strategies that combine observations with the information present in computer models for the climate system, while managing the uncertainties implicit in both. Assessing potential impacts of climate change on the environment and human activities is also fraught with uncertainty. The research team will develop integrated methods for predicting climate impacts on regional and local phenomena. These methods will be applied in predicting the El Nino-Southern Oscillation and properties of tornado occurrence in the Central United States.