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Statistical Methods in the Atmospheric Sciences - Softcover

 
9780128158234: Statistical Methods in the Atmospheric Sciences

Synopsis

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.

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

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About the Author

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.

From the Back Cover

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.

  • 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

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.

Related Elsevier Titles

  • Georgiev, Weather Analysis and Forecasting, 2nd ed., July 2016, 9780128001943
  • Hartmann, Global Physical Climatology, 2nd ed., December 2015, 9780123285317
  • Holton, An Introduction to Dynamic Meteorology, 5th ed., August 2012, 9780123848666
  • Marshall, Atmosphere, Ocean and Climate Dynamics, December 2007, 9780125586917

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