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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
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
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.
As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.
Assessment of risk and uncertainty is crucial for natural hazard risk management, facilitating risk communication and informing strategies to successfully mitigate our society's vulnerability to natural disasters. Written by some of the world's leading experts, this book provides a state-of-the-art overview of risk and uncertainty assessment in natural hazards. It presents the core statistical concepts using clearly defined terminology applicable across all types of natural hazards and addresses the full range of sources of uncertainty, the role of expert judgement and the practice of uncertainty elicitation. The core of the book provides detailed coverage of all the main hazard types and concluding chapters address the wider societal context of risk management. This is an invaluable compendium for academic researchers and professionals working in the fields of natural hazards science, risk assessment and management and environmental science, and will be of interest to anyone involved in natural hazards policy.
A practical, authoritative guide to the assessment of wind resources for utility-scale wind projects authored by a team of experts from a leading renewable energy consultancy The successful development of wind energy projects depends on an accurate assessment of where, how often, and how strongly the wind blows. A mistake in this stage of evaluation can cause severe financial losses and missed opportunities for developers, lenders, and investors. Wind Resource Assessment: A Practical Guide to Developing a Wind Project shows readers how to achieve a high standard of resource assessment, reduce the uncertainty associated with long-term energy performance, and maximize the value of their project assets. Beginning with the siting, installation, and operation of a high-quality wind monitoring program, this book continues with methods of data quality control and validation, extrapolating measurements from anemometer height to turbine height, adjusting short-term observations for historical climate conditions, and wind flow modeling to account for terrain and surface conditions. In addition, Wind Resource Assessment addresses special topics such as: Worker safety Data security Remote sensing technology (sodar and lidar) Offshore resource assessment Impacts of climate change Uncertainty estimation Plant design and energy production estimatio Filled with important information ranging from basic fundamentals of wind to cutting-edge research topics, and accompanied by helpful references and discussion questions, this comprehensive text designed for an international audience is a vital reference that promotes consistent standards for wind assessment across the industry.
Decades of evolving U.S. policy have led to three sectors providing weather servicesâ€"NOAA (primarily the National Weather Service [NWS]), academic institutions, and private companies. This three-sector system has produced a scope and diversity of weather services in the United States second to none. However, rapid scientific and technological change is changing the capabilities of the sectors and creating occasional friction. Fair Weather: Effective Partnerships in Weather and Climate Services examines the roles of the three sectors in providing weather and climate services, the barriers to interaction among the sectors, and the impact of scientific and technological advances on the weather enterprise. Readers from all three sectors will be interested in the analysis and recommendations provided in Fair Weather.
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.
According to the United Nations, three out of five people will be living in cities worldwide by the year 2030. The United States continues to experience urbanization with its vast urban corridors on the east and west coasts. Although urban weather is driven by large synoptic and meso-scale features, weather events unique to the urban environment arise from the characteristics of the typical urban setting, such as large areas covered by buildings of a variety of heights; paved streets and parking areas; means to supply electricity, natural gas, water, and raw materials; and generation of waste heat and materials. Urban Meteorology: Forecasting, Monitoring, and Meeting Users' Needs is based largely on the information provided at a Board on Atmospheric Sciences and Climate community workshop. This book describes the needs for end user communities, focusing in particular on needs that are not being met by current urban-level forecasting and monitoring. Urban Meteorology also describes current and emerging meteorological forecasting and monitoring capabilities that have had and will likely have the most impact on urban areas, some of which are not being utilized by the relevant end user communities. Urban Meteorology explains that users of urban meteorological information need high-quality information available in a wide variety of formats that foster its use and within time constraints set by users' decision processes. By advancing the science and technology related to urban meteorology with input from key end user communities, urban meteorologists can better meet the needs of diverse end users. To continue the advancement within the field of urban meteorology, there are both short-term needs-which might be addressed with small investments but promise large, quick returns-as well as future challenges that could require significant efforts and investments.
The Gap Between Weather and Climate Forecasting: Sub-seasonal to Seasonal Prediction is an ideal reference for researchers and practitioners across the range of disciplines involved in the science, modeling, forecasting and application of this new frontier in sub-seasonal to seasonal (S2S) prediction. It provides an accessible, yet rigorous, introduction to the scientific principles and sources of predictability through the unique challenges of numerical simulation and forecasting with state-of-science modeling codes and supercomputers. Additional coverage includes the prospects for developing applications to trigger early action decisions to lessen weather catastrophes, minimize costly damage, and optimize operator decisions. The book consists of a set of contributed chapters solicited from experts and leaders in the fields of S2S predictability science, numerical modeling, operational forecasting, and developing application sectors. The introduction and conclusion, written by the co-editors, provides historical perspective, unique synthesis and prospects, and emerging opportunities in this exciting, complex and interdisciplinary field. - Contains contributed chapters from leaders and experts in sub-seasonal to seasonal science, forecasting and applications - Provides a one-stop shop for graduate students, academic and applied researchers, and practitioners in an emerging and interdisciplinary field - Offers a synthesis of the state of S2S science through the use of concrete examples, enabling potential users of S2S forecasts to quickly grasp the potential for application in their own decision-making - Includes a broad set of topics, illustrated with graphic examples, that highlight interdisciplinary linkages