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Daniel S. Wilks has been a member of the Atmospheric Sciences faculty at Cornell University since 1987. His research focuses on the application of statistical methods for 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 author or coauthor of more than 100 peer-reviewed research articles.

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Statistical Methods in the Atmospheric Sciences, 4^th edition

An essential resource for students and researchers new to working with atmospheric and climate data.

Professor, Department of Earth & Atmospheric Sciences, Cornell University, Itaca, NY, USA

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.

• Provides a strong yet concise introduction to applied statistics, specific to atmospheric science
• Revised and expanded sections on nonparametric tests, test multiplicity, and quality uncertainty descriptors
• New sections on ANOVA, quantile regression, the lasso and other regularization methods, regression trees, changepoint detection, ensemble forecasting, and exponential smoothing

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.