Physics-guided Machine Learning for Prediction of Cloud Properties in Satellite-derived Solar Data PDF Download

Author: Grant Buster
Publisher:
ISBN:
Category : Cloud computing
Languages : en
Pages : 4

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Author: A. Pier Siebesma
Publisher:
ISBN: 9781107447738
Category : Clouds
Languages : en
Pages :

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"Clouds have always fascinated humans, but never has the need to understand them been so vital. As global surface temperature increases, human activities influence particulate matter in the atmosphere, and the properties of the land surface, clouds are expected to change, with manifold consequences for the climate. Clouds influence climate through their regulation of radiant energy transfer, through their role in convective energy transport, and in mediating the water cycle. Cloud research has never been so exciting. It is a topic with many new opportunities. New satellite observations from space with active instruments such as lidar and radar allow for the first time to reconstruct the three-dimensional distribution of clouds across Earth. Likewise, numerical simulations are beginning to globally resolve the three spatial dimensions of clouds as well as their dynamic evolution. This is enabling researchers, for the first time, to link the smallscale cloud processes and the basic laws that govern them to the general circulation of the atmosphere. These new types of observations, and simulation, are enabling researchers to distinguish how different cloud types influence the climate, and are guiding conceptual representations of their collective behaviour"--

Author: Wojciech Samek
Publisher: Springer Nature
ISBN: 3030289540
Category : Computers
Languages : en
Pages : 435

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Book Description
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

Author: Sue Ellen Haupt
Publisher: Springer Science & Business Media
ISBN: 1402091192
Category : Science
Languages : en
Pages : 418

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How can environmental scientists and engineers use the increasing amount of available data to enhance our understanding of planet Earth, its systems and processes? This book describes various potential approaches based on artificial intelligence (AI) techniques, including neural networks, decision trees, genetic algorithms and fuzzy logic. Part I contains a series of tutorials describing the methods and the important considerations in applying them. In Part II, many practical examples illustrate the power of these techniques on actual environmental problems. International experts bring to life ways to apply AI to problems in the environmental sciences. While one culture entwines ideas with a thread, another links them with a red line. Thus, a “red thread“ ties the book together, weaving a tapestry that pictures the ‘natural’ data-driven AI methods in the light of the more traditional modeling techniques, and demonstrating the power of these data-based methods.

Author: M. Sengupta
Publisher:
ISBN:
Category : Solar collectors
Languages : en
Pages : 0

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Author: Ian T. Jolliffe
Publisher: John Wiley & Sons
ISBN: 0470864419
Category : Science
Languages : en
Pages : 257

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This handy reference introduces the subject of forecastverification and provides a review of the basic concepts,discussing different types of data that may be forecast. Each chapter covers a different type of predicted quantity(predictand), then looks at some of the relationships betweeneconomic value and skill scores, before moving on to review the keyconcepts and summarise aspects of forecast verification thatreceive the most attention in other disciplines. The book concludes with a discussion on the most importanttopics in the field that are the subject of current research orthat would benefit from future research. An easy to read guide of current techniques with real life casestudies An up-to-date and practical introduction to the differenttechniques and an examination of their strengths andweaknesses Practical advice given by some of the world?s leadingforecasting experts Case studies and illustrations of actual verification and itsinterpretation Comprehensive glossary and consistent statistical andmathematical definition of commonly used terms

Author: Constantin Andronache
Publisher: Elsevier
ISBN: 012810550X
Category : Science
Languages : en
Pages : 302

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Mixed-Phase Clouds: Observations and Modeling presents advanced research topics on mixed-phase clouds. As the societal impacts of extreme weather and its forecasting grow, there is a continuous need to refine atmospheric observations, techniques and numerical models. Understanding the role of clouds in the atmosphere is increasingly vital for current applications, such as prediction and prevention of aircraft icing, weather modification, and the assessment of the effects of cloud phase partition in climate models. This book provides the essential information needed to address these problems with a focus on current observations, simulations and applications. - Provides in-depth knowledge and simulation of mixed-phase clouds over many regions of Earth, explaining their role in weather and climate - Features current research examples and case studies, including those on advanced research methods from authors with experience in both academia and the industry - Discusses the latest advances in this subject area, providing the reader with access to best practices for remote sensing and numerical modeling

Author: John F. Kolen
Publisher: John Wiley & Sons
ISBN: 9780780353695
Category : Technology & Engineering
Languages : en
Pages : 458

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Acquire the tools for understanding new architectures and algorithms of dynamical recurrent networks (DRNs) from this valuable field guide, which documents recent forays into artificial intelligence, control theory, and connectionism. This unbiased introduction to DRNs and their application to time-series problems (such as classification and prediction) provides a comprehensive overview of the recent explosion of leading research in this prolific field. A Field Guide to Dynamical Recurrent Networks emphasizes the issues driving the development of this class of network structures. It provides a solid foundation in DRN systems theory and practice using consistent notation and terminology. Theoretical presentations are supplemented with applications ranging from cognitive modeling to financial forecasting. A Field Guide to Dynamical Recurrent Networks will enable engineers, research scientists, academics, and graduate students to apply DRNs to various real-world problems and learn about different areas of active research. It provides both state-of-the-art information and a road map to the future of cutting-edge dynamical recurrent networks.

Author: John Monteith
Publisher: Butterworth-Heinemann
ISBN: 9780713129311
Category : Nature
Languages : en
Pages : 308

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Book Description
Thoroughly revised and up-dated edition of a highly successful textbook.

Author: K. N. Liou
Publisher: Academic Press
ISBN: 0124514510
Category : Nature
Languages : en
Pages : 599

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Book Description
Fundamentals of radiation for atmospheric applications -- Solar radiation at the top of the atmosphere -- Absorption and scattering of solar radiation in the atmosphere -- Thermal infrared radiation transfer in the atmosphere -- Light scattering by atmospheric particulates -- Principles of radiative transfer in planetary atmospheres -- Application of radiative transfer principles to remote sensing -- Radiation and climate.