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This open access title presents atmospheric simulation chambers as effective tools for atmospheric chemistry research. State-of-the-art simulation chambers provide unprecedented opportunities for atmospheric scientists to perform experiments that address the most important questions in air quality and climate research. The book covers technical details about chamber preparation and practical guidelines on their usage, while also delivering relevant historical and contextual information. It not only serves as a key publication for knowledge transfer within the simulation chamber research community, but it also provides the global atmospheric science community with a unique resource that outlines best practice for the operation of simulation chambers. The authors summarize the latest advances in chamber interoperability and standard protocols in order to provide the research community and the next generations of scientists with a unique technical reference guide for the use of simulation chambers. The volume will be of great interest to researchers and graduates working in the fields of Atmospheric and Environmental Sciences.

This book is a comprehensive guide for agricultural and meteorological predictions. It presents advanced models for predicting target variables. The different details and conceptions in the modelling process are explained in this book. The models of the current book help better agriculture and irrigation management. The models of the current book are valuable for meteorological organizations. Meteorological and agricultural variables can be accurately estimated with this book's advanced models. Modelers, researchers, farmers, students, and scholars can use the new optimization algorithms and evolutionary machine learning to better plan and manage agriculture fields. Water companies and universities can use this book to develop agricultural and meteorological sciences. The details of the modeling process are explained in this book for modelers. Also this book introduces new and advanced models for predicting hydrological variables. Predicting hydrological variables help water resource planning and management. These models can monitor droughts to avoid water shortage. And this contents can be related to SDG6, clean water and sanitation. The book explains how modelers use evolutionary algorithms to develop machine learning models. The book presents the uncertainty concept in the modeling process. New methods are presented for comparing machine learning models in this book. Models presented in this book can be applied in different fields. Effective strategies are presented for agricultural and water management. The models presented in the book can be applied worldwide and used in any region of the world. The models of the current books are new and advanced. Also, the new optimization algorithms of the current book can be used for solving different and complex problems. This book can be used as a comprehensive handbook in the agricultural and meteorological sciences. This book explains the different levels of the modeling process for scholars.

Now in its second edition, this book clearly, concisely and comprehensively outlines the essence of turbulence. In view of the absence of a theory based on first principles and adequate tools to handle the problem, the “essence” of turbulence, i.e. what turbulence really is from a fundamental point of view, is understood empirically through observations from nature, laboratories and direct numerical simulations rather than explained by means of conventional formalistic aspects, models, etc., resulting in pertinent issues being described at a highly theoretical level in spite of the mentioned lack of theory.As such, the book highlights and critically reexamines fundamental issues, especially those of paradigmatic nature, related to conceptual and problematic aspects, key misconceptions and unresolved matters, and discusses why the problem is so difficult. As in the previous edition, the focus on fundamental issues is also a consequence of the view that without corresponding advances in fundamental aspects there is little chance of progress in any applications. More generally there is a desperate need for physical fundamentals of a great variety of processes in nature and technology in which turbulence plays a central role. Turbulence is omnipresent throughout the natural sciences and technology, but despite the vast sea of information available the book retains its brevity without oversimplifications, making it of interest to a broad audience.

This book provides an overview of several components of mesoscale modeling: boundary conditions, subgrid-scale parameterization, moisture processes, and radiation. Also included are mesoscale model comparisons using data from the U.S. Army's Project WIND (Winds in Non-uniform Domains).

This book is intended to give atmospheric scientists a basic understanding of the physical and mathematical foundations of stochastic Lagrangian models of turbulent diffusion. It presents the reader with the historical context of the topic, and it provides definitions, criteria and applications for stochastic diffusion.