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Improving weather and climate prediction with better representation of fast processes in atmospheric modelsMany 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 modelsDifferent types of major sub-grid processes and their parameterizationsEfforts to unify the treatment of individual processes and their interactionsTop-down versus bottom-up approaches across multiple scalesMeasurement techniques, observational studies, and frameworks for model evaluationEmerging challenges, new opportunities, and future research directionsThe American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.
Yangang Liu, Brookhaven National Laboratory, USA.Pavlos Kollias, Brookhaven National Laboratory and Stony Brook University, USA.
List of contributors viiPreface xi1 Progress in Understanding and Parameterizing Fast Physics in Large-Scale Atmospheric Models 1Yangang Liu and Pavlos KolliasPart I Processes and Parameterizations2 Radiative Transfer and Atmospheric Interactions 13Yu Gu and Kuo-Nan Liou3 AerosolsandClimateEffects 53Xiaohong Liu4 Entrainment, Mixing, and Their Microphysical Influences 87Chunsong Lu, Yangang Liu, Xiaoqi Xu, Sinan Gao, and Cheng Sun5 Deep Convection and Convective Clouds 121Leo J. Donner6 Stratus, Stratocumulus, and Remote Sensing 141Xiquan Dong and Patrick Minnis7 Planetary Boundary Layer and Processes 201Virendra P. Ghate and David B. Mechem8 Human Impacts on Land Surface-Atmosphere Interactions 213Michael Barlage and Fei Chen9 Gravity Wave Drag Parameterizations for Earth’s Atmosphere 229Christopher G. Kruse, Jadwiga H. Richter, M. Joan Alexander, Julio T. Bacmeister, Christopher Heale, and Junhong WeiPart II Unifying Efforts10 Higher-Order Equations Closed by the Assumed PDF Method: Suitability for Parameterizing Cumulus Convection 259Vincent E. Larson11 An Introduction to the Eddy–Diffusivity/Mass–Flux (EDMF) Approach: A Unified Turbulence and ConvectionParameterization 271João Teixeira, Kay Suselj, and Marcin J. Kurowski12 Application of Machine Learning to Parameterization Emulation and Development 283Vladimir Krasnopolsky and Alexei Belochitski13 Top-DownApproachestotheStudyofCloudSystems 313Graham Feingold and Ilan KorenPart III Measurements, Model Evaluation, and Model-measurement Integration14 Ground-Based Remote-Sensing of Key Properties 329Katia Lamer, Pavlos Kollias, Vassilis Amiridis, Eleni Marinou, Ulrich Loehnert, Sabrina Schnitt, and Allison McComiskey15 Satellite and Airborne Remote Sensing of Clouds and Aerosols 361Alexander Marshak and Anthony B. Davis16 In Situ and Laboratory Measurements of Cloud Microphysical Properties 399Kamal Kant Chandrakar and Raymond A. Shaw17 Frameworks for Testing and Evaluating Fast Physics: Parameterizations in Climate and Weather Forecasting Models 425Wuyin Lin and Shaocheng Xie18 Future Research Outlook: Challenges and Opportunities 445Yangang Liu and Pavlos KolliasIndex 451
