Simulation And Prediction Of Intra Seasonal Variablity Of Intra Seasonal Variability With Emphasis On The Mjo


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Intraseasonal Variability in the Atmosphere-Ocean Climate System


Intraseasonal Variability in the Atmosphere-Ocean Climate System

Author: William K.-M. Lau

language: en

Publisher: Springer Science & Business Media

Release Date: 2011-10-25


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Improving the reliability of long-range forecasts of natural disasters, such as severe weather, droughts and floods, in North America, South America, Africa and the Asian/Australasian monsoon regions is of vital importance to the livelihood of millions of people who are affected by these events. In recent years the significance of major short-term climatic variability, and events such as the El Nino/Southern Oscillation in the Pacific, with its worldwide effect on rainfall patterns, has been all to clearly demonstrated. Understanding and predicting the intra-seasonal variability (ISV) of the ocean and atmosphere is crucial to improving long range environmental forecasts and the reliability of climate change projects through climate models. In the second edition of this classic book on the subject, the authors have updated the original chapters, where appropriate, and added a new chapter that includes short subjects representing substantial new development in ISV research since the publication of the first edition.

Assessment of Intraseasonal to Interannual Climate Prediction and Predictability


Assessment of Intraseasonal to Interannual Climate Prediction and Predictability

Author: National Research Council

language: en

Publisher: National Academies Press

Release Date: 2010-09-08


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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.