Uncertainties in Numerical Weather Prediction is a comprehensive work on the most current understandings of uncertainties and predictability in numerical simulations of the atmosphere. It provides general knowledge on all aspects of uncertainties in the weather prediction models in a single, easy to use reference. The book illustrates particular uncertainties in observations and data assimilation, as well as the errors associated with numerical integration methods. Stochastic methods in parameterization of subgrid processes are also assessed, as are uncertainties associated with surface-atmosphere exchange, orographic flows and processes in the atmospheric boundary layer. Through a better understanding of the uncertainties to watch for, readers will be able to produce more precise and accurate forecasts. This is an essential work for anyone who wants to improve the accuracy of weather and climate forecasting and interested parties developing tools to enhance the quality of such forecasts. Provides a comprehensive overview of the state of numerical weather prediction at spatial scales, from hundreds of meters, to thousands of kilometers Focuses on short-term 1-15 day atmospheric predictions, with some coverage appropriate for longer-term forecasts Includes references to climate prediction models to allow applications of these techniques for climate simulations
|Author||: Pirkka Ollinaho|
|Release Date||: 2014|
|ISBN 10||: 9789516978232|
|Pages||: 329 pages|
This textbook provides a comprehensive yet accessible treatment of weather and climate prediction, for graduate students, researchers and professionals. It teaches the strengths, weaknesses and best practices for the use of atmospheric models. It is ideal for the many scientists who use such models across a wide variety of applications. The book describes the different numerical methods, data assimilation, ensemble methods, predictability, land-surface modeling, climate modeling and downscaling, computational fluid-dynamics models, experimental designs in model-based research, verification methods, operational prediction, and special applications such as air-quality modeling and flood prediction. This volume will satisfy everyone who needs to know about atmospheric modeling for use in research or operations. It is ideal both as a textbook for a course on weather and climate prediction and as a reference text for researchers and professionals from a range of backgrounds: atmospheric science, meteorology, climatology, environmental science, geography, and geophysical fluid mechanics/dynamics.
The five-volume set LNCS 11536, 11537, 11538, 11539 and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019. The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019 Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
|Release Date||: 2005|
|Pages||: 40 pages|
Decision makers could frequently benefit from information about the amount of uncertainty associated with a specific weather forecast. Automated numerical weather prediction models provide deterministic weather forecast values with no estimate of the likely error. This case study examines the day-to-day persistence of forecast errors of basic surface weather parameters for four sites in northern Utah. Although exceptionally low or high forecast errors on one day are more likely to be associated with a similar quality forecast the following day, the relationship is not considered strong enough to provide beneficial guidance to users without meteorological expertise. Days resulting in average forecast errors showed no persistence in the quality of the subsequent day's forecast. More sophisticated methods are needed to generate and portray weather forecast uncertainty information.
A quantitative introduction to atmospheric science for students and professionals who want to understand and apply basic meteorological concepts but who are not ready for calculus.
|Author||: National Research Council,Division on Earth and Life Studies,Board on Atmospheric Sciences and Climate,Committee on Estimating and Communicating Uncertainty in Weather and Climate Forecasts|
|Publisher||: National Academies Press|
|Release Date||: 2006-11-09|
|ISBN 10||: 0309102553|
|Pages||: 124 pages|
Uncertainty is a fundamental characteristic of weather, seasonal climate, and hydrological prediction, and no forecast is complete without a description of its uncertainty. Effective communication of uncertainty helps people better understand the likelihood of a particular event and improves their ability to make decisions based on the forecast. Nonetheless, for decades, users of these forecasts have been conditioned to receive incomplete information about uncertainty. They have become used to single-valued (deterministic) forecasts (e.g., "the high temperature will be 70 degrees Farenheit 9 days from now") and applied their own experience in determining how much confidence to place in the forecast. Most forecast products from the public and private sectors, including those from the National Oceanographic and Atmospheric Administrationâ€™s National Weather Service, continue this deterministic legacy. Fortunately, the National Weather Service and others in the prediction community have recognized the need to view uncertainty as a fundamental part of forecasts. By partnering with other segments of the community to understand user needs, generate relevant and rich informational products, and utilize effective communication vehicles, the National Weather Service can take a leading role in the transition to widespread, effective incorporation of uncertainty information into predictions. "Completing the Forecast" makes recommendations to the National Weather Service and the broader prediction community on how to make this transition.
Understanding climate change requires analysis of its effects in specific contexts, and the case studies in this volume offer examples of such issues. Its chapters cover tropical cyclones in East Asia, study of a fossil in Brazils Araripe Basin and the fractal nature of band-thickness in an iron formation of Canadas Northwest Territories. One chapter examines the presence of trace elements and palynomorphs in the sediments of a tropical urban pond. Examples of technologies used include RS- GIS to map lineaments for groundwater targeting and sustainable water-resource management, the ALADIN numerical weather-prediction model used to forecast weather and use of grids in numerical weather and climate models. Finally, one chapter models sea level rises resulting from ice sheets melting.
The topic of predictability in weather and climate has advanced significantly in recent years, both in understanding the phenomena that affect weather and climate and in techniques used to model and forecast them. This book, first published in 2006, brings together some of the world's leading experts on predicting weather and climate. It addresses predictability from the theoretical to the practical, on timescales from days to decades. Topics such as the predictability of weather phenomena, coupled ocean-atmosphere systems and anthropogenic climate change are among those included. Ensemble systems for forecasting predictability are discussed extensively. Ed Lorenz, father of chaos theory, makes a contribution to theoretical analysis with a previously unpublished paper. This well-balanced volume will be a valuable resource for many years. High-calibre chapter authors and extensive subject coverage make it valuable to people with an interest in weather and climate forecasting and environmental science, from graduate students to researchers.
This volume presents a survey of our state of knowledge of the physical and dynamical processes involved in the Asian monsoon. Although traditionally the main emphasis has been on the study of the atmospheric component, it has long been known that the oceans play a vitally important part in determining the occurrence of this spectacular seasonal event. A scientific study of this phenomenon involves a detailed investigation of the dynamical processes which occur in both the atmosphere and the ocean, on timescales on up to at least a year and on spatial scales from a few hundred kilometres or so up to that of the global atmospheric and oceanic circulations. The editors present a coherent survey of each of the meteorological, oceanographic and hydrological aspects and of their implications for weather forecasting and flood prediction. Monsoon Dynamics is a timely survey of a dramatic meteorological phenomenon which will interest meteorologists, climatologists and geophysicists.
|Author||: Alberto Troccoli|
|Release Date||: 2018-01-03|
|ISBN 10||: 3319684183|
|Pages||: 197 pages|
This open access book showcases the burgeoning area of applied research at the intersection between weather and climate science and the energy industry. It illustrates how better communication between science and industry can help both sides. By opening a dialogue, scientists can understand the broader context for their work and the energy industry is able to keep track of and implement the latest scientific advances for more efficient and sustainable energy systems. Weather & Climate Services for the Energy Industry considers the lessons learned in establishing an ongoing discussion between the energy industry and the meteorological community and how its principles and practises can be applied elsewhere. This book will be a useful guiding resource for research and early career practitioners concerned with the energy industry and the new field of research known as energy meteorology.