Statistical Methods in the Atmospheric Sciences, Fourth Edition, continues the tradition of trying to meet the needs of students, researchers and operational practitioners. This updated edition not only includes expanded sections built upon the strengths of the prior edition, but also provides new content where there have been advances in the field, including Bayesian analysis, forecast verification and a new chapter dedicated to ensemble forecasting.
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Daniel S. Wilks is a Professor Emeritus at Cornell University and has been a Member of the Atmospheric Sciences faculty since 1987. His research focuses on the application of statistical methods for the quantification and analysis of uncertainty in meteorological and climatological data and forecasts. Dr. Wilks has taught courses on statistics in the atmospheric sciences and has been an Author or Coauthor of more than 100 peer-reviewed research articles.
Statistical Methods in the Atmospheric Sciences, 4th edition
An essential resource for students and researchers new to working with atmospheric and climate data.
Daniel S. Wilks
Professor, Department of Earth & Atmospheric Sciences, Cornell University, Itaca, NY, USA
Statistical Methods in the Atmospheric Sciences has always strived, and succeeded, to meet the needs of students and instructors, in addition to supporting researchers and operational practitioners as a comprehensive, but still usable, reference. This newly revised 4th edition continues in that tradition. Updates, new topics and expanded sections build upon the strengths of the prior edition, while providing new content where there have been advances in the field, including Bayesian analysis, forecast verification and a new chapter dedicated to Ensemble Forecasting.
About the Author
Daniel Wilks has been a member of the Atmospheric Sciences faculty at Cornell University since 1987, where he is currently the Director of Graduate Studies for Atmospheric Science. His research focuses on applications of statistical methods for quantifying, analysis and dealing with uncertainty in meteorological and climatological data and forecasts. Dr. Wilks has taught a wide array of courses on statistics in the atmospheric science, and has been an editor on over 30 journals across his career.
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