Predictability of Weather and Climate

Predictability of Weather and Climate
Author: Tim Palmer
Publisher: Cambridge University Press
Total Pages: 693
Release: 2006-07-27
Genre: Science
ISBN: 1139458205

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With contributions by leading experts, including an unpublished paper by Ed Lorenz, this book, first published in 2006, covers many topics in weather and climate predictability. It will interest those in the fields of environmental science and weather and climate forecasting, from graduate students to researchers, by examining theoretical and practical aspects of predictability.

Monsoon Dynamics

Monsoon Dynamics
Author: James Lighthill
Publisher: Cambridge University Press
Total Pages: 768
Release: 1981-03-19
Genre: Nature
ISBN: 9780521224970

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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.

Sub-seasonal to Seasonal Prediction

Sub-seasonal to Seasonal Prediction
Author: Andrew Robertson
Publisher: Elsevier
Total Pages: 588
Release: 2018-10-19
Genre: Science
ISBN: 012811715X

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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

Improving the Scientific Foundation for Atmosphere-Land-Ocean Simulations

Improving the Scientific Foundation for Atmosphere-Land-Ocean Simulations
Author: National Research Council
Publisher: National Academies Press
Total Pages: 84
Release: 2005-05-12
Genre: Science
ISBN: 030909609X

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The National Academies' Board on Atmospheric Sciences and Climate (BASC) held a workshop to explore and evaluate current efforts to model physical processes of coupled atmosphere-land-ocean (A-L-O) models. Numerical models of the atmosphere and ocean are central to weather prediction, research, and education. Although great strides have been made over the past few decades in understanding the atmosphere and ocean, modeling capabilities, and numerical A-L-O simulations, some unresolved processes in the models do not adequately represent knowledge of the underlying physics. Moreover, there is evidence that further progress in numerical simulations is being impeded by the slow pace of improvement in the representation of key physical processes in the models and the fact that geophysical flow models are not receiving the attention needed to make these tools more useful and accurate. These models often are used to predict future events, so it is imperative that their underlying physical processes be represented as robustly as possible. During the workshop, the parameterization of physical processes in A-L-O models was addressed, including associated errors, testing, and efforts to improve the use of parameterizations. Participants also examined intellectual and scientific challenges in modeling and highlighted the idea that some of the key impediments to progress in representing physical processes are primarily cultural in nature.

Assessment of Intraseasonal to Interannual Climate Prediction and Predictability

Assessment of Intraseasonal to Interannual Climate Prediction and Predictability
Author: National Research Council
Publisher: National Academies Press
Total Pages: 193
Release: 2010-09-08
Genre: Science
ISBN: 0309161347

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More accurate forecasts of climate conditions over time periods of weeks to a few years could help people plan agricultural activities, mitigate drought, and manage energy resources, amongst other activities; however, current forecast systems have limited ability on these time- scales. Models for such climate forecasts must take into account complex interactions among the ocean, atmosphere, and land surface. Such processes can be difficult to represent realistically. To improve the quality of forecasts, this book makes recommendations about the development of the tools used in forecasting and about specific research goals for improving understanding of sources of predictability. To improve the accessibility of these forecasts to decision-makers and researchers, this book also suggests best practices to improve how forecasts are made and disseminated.