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  • Improving Climate Projections Through the

    Assessment of Model Uncertainty and Bias in the

    Global Water Cycle

    by

    Noel C. Baker

    A Dissertation Presented in Partial Fulfillment

    of the Requirements for the Degree

    Doctor of Philosophy

    Approved July 2013 by the

    Graduate Supervisory Committee:

    Huei-Ping Huang, Chair

    James Anderson

    Amanda Clarke

    Steven Trimble

    Ronald Calhoun

    ARIZONA STATE UNIVERSITY

    August 2013

  • i

    ABSTRACT

    The implications of a changing climate have a profound impact on human life,

    society, and policy making. The need for accurate climate prediction becomes

    increasingly important as we better understand these implications. Currently, the most

    widely used climate prediction relies on the synthesis of climate model simulations

    organized by the Coupled Model Intercomparison Project (CMIP); these simulations are

    ensemble-averaged to construct projections for the 21 st century climate. However, a

    significant degree of bias and variability in the model simulations for the 20 th

    century

    climate is well-known at both global and regional scales. Based on that insight, this study

    provides an alternative approach for constructing climate projections that incorporates

    knowledge of model bias. This approach is demonstrated to be a viable alternative which

    can be easily implemented by water resource managers for potentially more accurate

    projections. Tests of the new approach are provided on a global scale with an emphasis

    on semiarid regional studies for their particular vulnerability to water resource changes,

    using both the former CMIP Phase 3 (CMIP3) and current Phase 5 (CMIP5) model

    archives. This investigation is accompanied by a detailed analysis of the dynamical

    processes and water budget to understand the behaviors and sources of model biases.

    Sensitivity studies of selected CMIP5 models are also performed with an atmospheric

    component model by testing the relationship between climate change forcings and model

    simulated response. The information derived from each study is used to determine the

    progressive quality of coupled climate models in simulating the global water cycle by

    rigorously investigating sources of model bias related to the moisture budget. As such,

  • ii

    the conclusions of this project are highly relevant to model development and potentially

    may be used to further improve climate projections.

  • iii

    ACKNOWLEDGMENTS

    I would like to thank my advisor, Huei-Ping Huang, for the incredible amount of

    time and effort he spent to help me bring this project into fruition. I also appreciate the

    contributions of my committee members James Anderson, Amanda Clarke, Steven

    Trimble, and Ronald Calhoun, who provided valuable assistance through their comments

    and suggestions. Finally, I would like to thank the Office of Science (BER), U.S.

    Department of Energy, for granting financial support through the duration of this project.

  • iv

    TABLE OF CONTENTS

    Page

    LIST OF TABLES ................................................................................................................. vii

    LIST OF FIGURES .............................................................................................................. viii

    CHAPTER

    1 INTRODUCTION ............................................................................................... 1

    2 BACKGROUND ................................................................................................. 4

    2.1 The hydrological cycle .............................................................................. 4

    2.2 Observational data sets ............................................................................. 5

    2.2.1 NCEP/NCAR Reanalysis data ................................................... 8

    2.2.2 GPCP precipitation data ............................................................. 8

    2.2.3 CMAP precipitation data............................................................ 9

    2.2.4 Selection of observational datasets .......................................... 10

    2.3 Introduction to numerical climate modeling ........................................... 11

    2.3.1 Basic model equations .............................................................. 11

    2.3.2 Vertical coordinate system ....................................................... 17

    2.3.3 Physical atmospheric processes ............................................... 17

    2.4 Background of the IPCC and CMIP ........................................................ 20

    2.4.1 Details of the CMIP model ensembles .................................... 21

    2.4.2 Scenarios for climate change research ..................................... 26

    3 SCIENTIFIC ISSUES AND GOALS............................................................... 32

    3.1 Relevance of the water cycle and precipitation ...................................... 32

    3.2 Sources of model bias .............................................................................. 33

  • v

    3.2.1 Quantifying uncertainty: internal versus model variability .... 34

    3.2.2 Flux corrections ........................................................................ 35

    3.2.3 Parameterization schemes of moisture processes .................... 35

    3.3 Goals of the study .................................................................................... 36

    4 EXPLORING TECHNIQUES FOR CONSTRUCTING CLIMATE

    PROJECTIONS ........................................................................................... 38

    4.1 Introduction .............................................................................................. 39

    4.2 Absolute change: discussion of equal and unequal weighting ............... 39

    4.2.1 The classical scheme ................................................................ 39

    4.2.2 Unequal weighting and further motivation .............................. 41

    4.3 Relative change and relation to unequal weighting ................................ 46

    4.4 Results and discussions ............................................................................ 47

    5 APPLICATION OF AN ALTERNATIVE METHOD FOR ENSEMBLE

    AVERAGING CLIMATE MODELS ........................................................ 55

    5.1 Introduction .............................................................................................. 56

    5.2 Approach and averaging techniques ....................................................... 58

    5.2.1 Model data ................................................................................ 58

    5.2.2 Methodology............................................................................. 59

    5.3 Results and discussion ............................................................................. 60

    5.3.1 Global trends ............................................................................ 60

    5.3.2 Regional trends ......................................................................... 65

    5.4 Conclusions .............................................................................................. 68

    6 COMPARING PERFORMANCE OF MODEL ENSEMBLES ..................... 70

  • vi

    6.1 Introduction .............................................................................................. 71

    6.2 Methods and analysis ............................................................................... 72

    6.3 Regional comparisons of ensemble quality ............................................ 74

    6.3.1 Southwestern US ...................................................................... 74

    6.3.2 Mediterranean ........................................................................... 82

    6.4 Conclusions ............................................................................................. 88

    7 EXAMINING MODEL QUALITY IN SIMULATING GLOBAL

    MOISTURE TRANSPORT ....................................................................... 97

    7.1 Introduction .............................................................................................. 97

    7.2 Calculating the mean flux of water vapor transport................................ 99

    7.3 The moisture transport term .................................................................. 107

    7.4 Calculation of the divergence of moisture flux ..................................... 110

    7.5 Decomposition of the moisture convergence trend .............................. 112

    8 IDENTIFYING MODEL RESPONSE TO CLIMATE CHANGE ............... 116

    8.1 Introduction ............................................................................................ 116

    8.2 Numerical experiments .......................................................................... 118

    8.3 Global precipitation response to SST trend .......................................... 120

    8.4 Regional prec

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