Description

Praise for the First Edition: "I recommend this book, without hesitation, as either a reference or course text...Wilks' excellent book provides a thorough base in applied statistical methods for atmospheric sciences."--BAMS (Bulletin of the American Meteorological Society) Fundamentally, statistics is concerned with managing data and making inferences and forecasts in the face of uncertainty. It should not be surprising, therefore, that statistical methods have a key role to play in the atmospheric sciences. It is the uncertainty in atmospheric behavior that continues to move research forward and drive innovations in atmospheric modeling and prediction. This revised and expanded text explains the latest statistical methods that are being used to describe, analyze, test and forecast atmospheric data. It features numerous worked examples, illustrations, equations, and exercises with separate solutions. Statistical Methods in the Atmospheric Sciences, Second Edition will help advanced students and professionals understand and communicate what their data sets have to say, and make sense of the scientific literature in meteorology, climatology, and related disciplines.

Readership

Researchers and students in the atmospheric sciences, including meteorology, climatology, and other geophysical disciplines

Table of Contents

I Preliminaries
Chapter 1 Introduction
 1.1 What Is Statistics?
 1.2 Descriptive and Inferential Statistics
 1.3 Uncertainty about the Atmosphere

Chapter 2 Review of Probability
 2.1 Background
 2.2 The Elements of Probability
 2.3 The Meaning of Probability
 2.4 Some Properties of Probability
 2.5 Exercises

II Univariate Statistics
Chapter 3 Empirical Distributions and Exploratory Data Analysis
 3.1 Background
 3.2 Numerical Summary Measures
 3.3 Graphical Summary Devices
 3.4 Reexpression
 3.5 Exploratory Techniques for Paired Data
 3.6 Exploratory Techniques for Higher-Dimensional Data
 3.7 Exercises

Chapter 4 Parametric Probability Distributions
 4.1 Background
 4.2 Discrete Distributions
 4.3 Statistical Expectations
 4.4 Continuous Distributions
 4.5 Qualitative Assessments of the Goodness of Fit
 4.6 Parameter Fitting Using Maximum Likelihood
 4.7 Statistical Simulation
 4.8 Exercises

Chapter 5 Frequentist Statistical Inference
 5.1. Background
 5.2 Some Commonly Encountered Parametric Tests
 5.3 Nonparametric Tests
 5.4 Multiplicity and "Field Significance"
 5.5. Exercises

Chapter 6 Bayesian Inference
 6.1 Background
 6.2 The Structure of Bayesian Inference
 6.3 Conjugate Distributions
 6.4 Dealing With Difficult Integrals
 6.5 Exercises

Chapter 7 Statistical Forecasting
 7.1 Background
 7.2 Linear Regression
 7.3 Nonlinear Regression 
 7.4 Predictor Selection
 7.5 Objective Forecasts Using Traditional Statistical Methods
 7.6 Ensemble Forecasting
 7.7 Ensemble MOS
 7.8 Subjective Probability Forecasts
 7.9 Exercises

Chap

Details

No. of pages:
704
Language:
English
Copyright:
© 2011
Published:
Imprint:
Academic Press
Print ISBN:
9780123850225
Electronic ISBN:
9780123850232

About the editor

Daniel Wilks

Affiliations and Expertise

Cornell University, Ithaca, New York, U.S.A.

Reviews

"I would strongly recommend this book... To those who already posses the first edition and are satisfied users, you would be hard-pressed to do without the second edition."--Bulletin of the American Meteorological Society
"What makes this book specific to meterology, and not just to applied statistics, are it's extensive examples and two chapters on statistcal forecasting and forecast evaluation."--William (Matt) Briggs, Weill Medical College of Cornell University

"Wilks (earth and atmospheric sciences, Cornell U.) presents a textbook for an upper-division undergraduate or beginning graduate course for students who have completed a first course in statistics and are interested in learning further statistics in the context of atmospheric sciences. No mathematics beyond first-year calculus is required, nor any background in atmospheric science, though some would be helpful. He also has in mind researchers using the book as a reference. No dates are cited for previous editions, this one adds a chapter on Bayesian inference, updates the treatment throughout, and includes new references to recently published literature."--SciTech Book News