Statistical downscaling for hydrological and environmental applications

✍ Scribed by Lee, Taesam; Singh, Vijay P

• Publisher: CRC Press
• Year: 2019
• Tongue: English
• Leaves: 179
• Category: Library

✦ Synopsis

This book presents statistical downscaling techniques in a practical manner so that readers can easily adopt the techniques for hydrological applications and designs in response to climate change. It also provides numerous examples and background information on reliability of impact assessments of climate change and what the results imply.;#t 1. Introduction -- ǂt 2. Statistical Background -- ǂt 3. Data and Format Description -- ǂt 4. Bias Correction -- ǂt 5. Regression Downscalings -- ǂt 6. Weather Generator Downscaling -- ǂt 7. Weather-Type Downscaling -- ǂt 8. Temporal Downscaling -- ǂt 9. Spatial Downscaling

✦ Table of Contents

Cover......Page 1
Half Title......Page 2
Title Page......Page 4
Copyright Page......Page 5
Dedication......Page 6
Contents......Page 8
Preface......Page 12
List of Abbreviations......Page 14
Authors......Page 16
1.2 Climate Models......Page 18
1.3 Statistical Downscaling......Page 19
1.4 Selection of Model Scheme......Page 20
1.5 Structure of Chapters......Page 23
1.6 Summary and Conclusion......Page 24
2.1.1.2 Descriptors of Random Variables......Page 26
2.1.2 Discrete Probability Distributions......Page 27
2.1.2.2 Binomial Distribution......Page 28
2.1.3.1 Normal Distribution and Lognormal Distributions......Page 29
2.1.3.2 Exponential and Gamma Distributions......Page 30
2.1.3.3 Generalized Extreme Value and Gumbel Distribution......Page 32
2.1.4.2 Maximum Likelihood Estimation......Page 33
2.1.5 Histogram and Empirical Distribution......Page 36
2.2.1 Multivariate Normal Distribution and Its Conditional Distribution......Page 39
2.3.1 Monte Carlo Simulation and Uniform Random Number......Page 41
2.3.2 Simulation of Probability Distributions......Page 43
2.4.1 Harmony Search......Page 44
2.5 Summary and Conclusion......Page 48
3.1 GCM Data......Page 50
3.3 RCM Data......Page 51
3.4 Summary and Conclusion......Page 55
4.2 Occurrence Adjustment for Precipitation Data......Page 56
4.3 Empirical Adjustment (Delta Method)......Page 58
4.4.1 General Quantile Mapping......Page 60
4.4.2 Nonparametric Quantile Mapping......Page 63
4.4.3 Quantile Delta Mapping......Page 64
4.5 Summary and Comparison......Page 67
5.1.1 Simple Linear Regression......Page 70
5.1.1.1 Significance Test......Page 72
5.1.2 Multiple Linear Regression......Page 75
5.2.1 Stepwise Regression......Page 87
5.2.2 Least Absolute Shrinkage and Selection Operator......Page 91
5.3.1 Artificial Neural Network......Page 104
5.4 Summary and Conclusion......Page 109
6.1.2 Multivariate Autoregressive Model......Page 112
6.1.3 Markov Chain......Page 115
6.2 Weather Generator......Page 117
6.2.1.2 Weather Variables (T[sub(max)], T[sub(min)], SR)......Page 118
6.2.2.2 Weather Variables (T[sub(max)], T[sub(min)], SR)......Page 124
6.2.3 Implementation of Downscaling......Page 126
6.3 Nonparametric Weather Generator......Page 128
6.3.1 Simulation under Current Climate......Page 129
6.4 Summary and Conclusion......Page 132
7.1.2 Objective Weather Type......Page 134
7.2 Generation of Daily Rainfall Sequences......Page 138
7.4 Summary and Conclusion......Page 140
8.1.1 K-Nearest Neighbor Resampling......Page 142
8.2 Daily to Hourly Downscaling......Page 144
8.3 Summary and Conclusion......Page 152
9.1.2 Nearest Neighbor Interpolation......Page 154
9.2 Bias Correction and Spatial Downscaling......Page 155
9.3 Bias Correction and Constructed Analogues......Page 160
9.4 Bias Correction and Stochastic Analogue......Page 163
9.5 Summary and Comparison......Page 169
References......Page 172
Index......Page 176

✦ Subjects

Hydrometeorology--Statistical methods;Multiscale modeling;Hydrometeorology -- Statistical methods