Description

Book Synopsis

Improving weather and climate prediction with better representation of fast processes in atmospheric models

Many atmospheric processes that influence Earth's weather and climate occur at spatiotemporal scales that are too small to be resolved in large scale models. They must be parameterized, which means approximately representing them by variables that can be resolved by model grids.

Fast Processes in Large-Scale Atmospheric Models: Progress, Challenges and Opportunities explores ways to better investigate and represent multiple parameterized processes in models and thus improve their ability to make accurate climate and weather predictions.

Volume highlights include:

  • Historical development of the parameterization of fast processes in numerical models
  • Different types of major sub-grid processes and their parameterizations
  • Efforts to unify the treatment of individual processes and their interactions
  • To

    Table of Contents

    List of contributors vii

    Preface xi

    1 Progress in Understanding and Parameterizing Fast Physics in Large-Scale Atmospheric Models 1
    Yangang Liu and Pavlos Kollias

    Part I Processes and Parameterizations

    2 Radiative Transfer and Atmospheric Interactions 13
    Yu Gu and Kuo-Nan Liou

    3 AerosolsandClimateEffects 53
    Xiaohong Liu

    4 Entrainment, Mixing, and Their Microphysical Influences 87
    Chunsong Lu, Yangang Liu, Xiaoqi Xu, Sinan Gao, and Cheng Sun

    5 Deep Convection and Convective Clouds 121
    Leo J. Donner

    6 Stratus, Stratocumulus, and Remote Sensing 141
    Xiquan Dong and Patrick Minnis

    7 Planetary Boundary Layer and Processes 201
    Virendra P. Ghate and David B. Mechem

    8 Human Impacts on Land Surface-Atmosphere Interactions 213
    Michael Barlage and Fei Chen

    9 Gravity Wave Drag Parameterizations for Earth’s Atmosphere 229
    Christopher G. Kruse, Jadwiga H. Richter, M. Joan Alexander, Julio T. Bacmeister, Christopher Heale, and Junhong Wei

    Part II Unifying Efforts

    10 Higher-Order Equations Closed by the Assumed PDF Method: Suitability for Parameterizing Cumulus Convection 259
    Vincent E. Larson

    11 An Introduction to the Eddy–Diffusivity/Mass–Flux (EDMF) Approach: A Unified Turbulence and ConvectionParameterization 271
    João Teixeira, Kay Suselj, and Marcin J. Kurowski

    12 Application of Machine Learning to Parameterization Emulation and Development 283
    Vladimir Krasnopolsky and Alexei Belochitski

    13 Top-DownApproachestotheStudyofCloudSystems 313
    Graham Feingold and Ilan Koren

    Part III Measurements, Model Evaluation, and Model-measurement Integration

    14 Ground-Based Remote-Sensing of Key Properties 329
    Katia Lamer, Pavlos Kollias, Vassilis Amiridis, Eleni Marinou, Ulrich Loehnert, Sabrina Schnitt, and Allison McComiskey

    15 Satellite and Airborne Remote Sensing of Clouds and Aerosols 361
    Alexander Marshak and Anthony B. Davis

    16 In Situ and Laboratory Measurements of Cloud Microphysical Properties 399
    Kamal Kant Chandrakar and Raymond A. Shaw

    17 Frameworks for Testing and Evaluating Fast Physics: Parameterizations in Climate and Weather Forecasting Models 425
    Wuyin Lin and Shaocheng Xie

    18 Future Research Outlook: Challenges and Opportunities 445
    Yangang Liu and Pavlos Kollias

    Index 451

Fast Processes in LargeScale Atmospheric Models

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      Description

      Book Synopsis

      Improving weather and climate prediction with better representation of fast processes in atmospheric models

      Many atmospheric processes that influence Earth's weather and climate occur at spatiotemporal scales that are too small to be resolved in large scale models. They must be parameterized, which means approximately representing them by variables that can be resolved by model grids.

      Fast Processes in Large-Scale Atmospheric Models: Progress, Challenges and Opportunities explores ways to better investigate and represent multiple parameterized processes in models and thus improve their ability to make accurate climate and weather predictions.

      Volume highlights include:

      • Historical development of the parameterization of fast processes in numerical models
      • Different types of major sub-grid processes and their parameterizations
      • Efforts to unify the treatment of individual processes and their interactions
      • To

        Table of Contents

        List of contributors vii

        Preface xi

        1 Progress in Understanding and Parameterizing Fast Physics in Large-Scale Atmospheric Models 1
        Yangang Liu and Pavlos Kollias

        Part I Processes and Parameterizations

        2 Radiative Transfer and Atmospheric Interactions 13
        Yu Gu and Kuo-Nan Liou

        3 AerosolsandClimateEffects 53
        Xiaohong Liu

        4 Entrainment, Mixing, and Their Microphysical Influences 87
        Chunsong Lu, Yangang Liu, Xiaoqi Xu, Sinan Gao, and Cheng Sun

        5 Deep Convection and Convective Clouds 121
        Leo J. Donner

        6 Stratus, Stratocumulus, and Remote Sensing 141
        Xiquan Dong and Patrick Minnis

        7 Planetary Boundary Layer and Processes 201
        Virendra P. Ghate and David B. Mechem

        8 Human Impacts on Land Surface-Atmosphere Interactions 213
        Michael Barlage and Fei Chen

        9 Gravity Wave Drag Parameterizations for Earth’s Atmosphere 229
        Christopher G. Kruse, Jadwiga H. Richter, M. Joan Alexander, Julio T. Bacmeister, Christopher Heale, and Junhong Wei

        Part II Unifying Efforts

        10 Higher-Order Equations Closed by the Assumed PDF Method: Suitability for Parameterizing Cumulus Convection 259
        Vincent E. Larson

        11 An Introduction to the Eddy–Diffusivity/Mass–Flux (EDMF) Approach: A Unified Turbulence and ConvectionParameterization 271
        João Teixeira, Kay Suselj, and Marcin J. Kurowski

        12 Application of Machine Learning to Parameterization Emulation and Development 283
        Vladimir Krasnopolsky and Alexei Belochitski

        13 Top-DownApproachestotheStudyofCloudSystems 313
        Graham Feingold and Ilan Koren

        Part III Measurements, Model Evaluation, and Model-measurement Integration

        14 Ground-Based Remote-Sensing of Key Properties 329
        Katia Lamer, Pavlos Kollias, Vassilis Amiridis, Eleni Marinou, Ulrich Loehnert, Sabrina Schnitt, and Allison McComiskey

        15 Satellite and Airborne Remote Sensing of Clouds and Aerosols 361
        Alexander Marshak and Anthony B. Davis

        16 In Situ and Laboratory Measurements of Cloud Microphysical Properties 399
        Kamal Kant Chandrakar and Raymond A. Shaw

        17 Frameworks for Testing and Evaluating Fast Physics: Parameterizations in Climate and Weather Forecasting Models 425
        Wuyin Lin and Shaocheng Xie

        18 Future Research Outlook: Challenges and Opportunities 445
        Yangang Liu and Pavlos Kollias

        Index 451

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