Monthly Seasonal Weather Outlook
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Monthly Seasonal Weather Outlook
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Author :
language : en
Publisher:
Release Date : 1982
Monthly Seasonal Weather Outlook written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Long-range weather forecasts categories.
Monthly Seasonal Weather Outlook
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Author : Climate Analysis Center (U.S.)
language : en
Publisher:
Release Date : 1989
Monthly Seasonal Weather Outlook written by Climate Analysis Center (U.S.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Long-range weather forecasts categories.
Average Monthly Weather Outlook
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Author :
language : en
Publisher:
Release Date : 1970
Average Monthly Weather Outlook written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with Long-range weather forecasts categories.
Monthly Seasonal Weather Outlook
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Author :
language : en
Publisher:
Release Date : 1993
Monthly Seasonal Weather Outlook written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Long-range weather forecasts categories.
Climate Risk Management In Agriculture
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Author : U. C. Mohanty
language : en
Publisher: Springer Nature
Release Date :
Climate Risk Management In Agriculture written by U. C. Mohanty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Average Monthly Weather Resume And Outlook
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Author :
language : en
Publisher:
Release Date :
Average Monthly Weather Resume And Outlook written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Long-range weather forecasts categories.
Making Climate Forecasts Matter
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 1999-05-27
Making Climate Forecasts Matter written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-27 with Science categories.
El Nino has been with us for centuries, but now we can forcast it, and thus can prepare far in advance for the extreme climatic events it brings. The emerging ability to forecast climate may be of tremendous value to humanity if we learn how to use the information well. How does society cope with seasonal-to-interannual climatic variations? How have climate forecasts been usedâ€"and how useful have they been? What kinds of forecast information are needed? Who is likely to benefit from forecasting skill? What are the benefits of better forecasting? This book reviews what we know about these and other questions and identifies research directions toward more useful seasonal-to-interannual climate forecasts. In approaching their recommendations, the panel explores: Vulnerability of human activities to climate. State of the science of climate forecasting. How societies coevolved with their climates and cope with variations in climate. How climate information should be disseminated to achieve the best response. How we can use forecasting to better manage the human consequences of climate change.
Monthly Weather Review
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Author :
language : en
Publisher:
Release Date : 1978
Monthly Weather Review written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Electronic journals categories.
Economic Value Of Weather And Climate Forecasts
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Author : Richard W. Katz
language : en
Publisher: Cambridge University Press
Release Date : 1997
Economic Value Of Weather And Climate Forecasts written by Richard W. Katz and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Business & Economics categories.
Weather and climate extremes can significantly impact the economics of a region. This book examines how weather and climate forecasts can be used to mitigate the impact of the weather on the economy. Interdisciplinary in scope, it explores the meteorological, economic, psychological, and statistical aspects to weather prediction. The contributors encompass forecasts over a wide range of temporal scales, from weather over the next few hours to the climate months or seasons ahead, and address the impact of these forecasts on human behaviour. Economic Value of Weather and Climate Forecasts seeks to determine the economic benefits of existing weather forecasting systems and the incremental benefits of improving these systems, and will be an interesting and essential reference for economists, statisticians, and meteorologists.
The Stochastic Seasonal To Interannual Prediction System
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Author : Lenin Del Rio Amador
language : en
Publisher:
Release Date : 2021
The Stochastic Seasonal To Interannual Prediction System written by Lenin Del Rio Amador and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
"This thesis proposes the new Stochastic Seasonal to Interannual Prediction System (StocSIPS) model of the atmospheric temperature in the macroweather regime, i.e. time scales longer than the lifetime of planetary sized structures (≈10 days). StocSIPS is stochastic and respects two conservation principles: energy balance and scale invariance. The scale-invariance of the fluctuations implies the existence a huge memory in the system that can be exploited for macroweather forecasts and the low intermittency justifies using well-established (Gaussian) techniques. Here, we present StocSIPS, discuss its statistics, use it to perform long-term forecasts and compare it with forecasts from conventional general circulation models (GCMs).GCMs are initial value problems and each has its own climate, requiring complex post-processing correction schemes. In comparison, StocSIPS is a past value problem based on real world historical data that effectively forces predictions to converge to the real-world climate. It extracts the internal variability (weather noise) directly from past data and does not suffer from model drift. It models the temperature as the high-frequency limit of the (fractional) energy balance equation which governs radiative equilibrium processes when the relevant equilibrium relaxation processes are power law, rather than exponential.StocSIPS was first developed as an improvement over the previous ScaLIng Macroweather Model (SLIMM) for monthly and seasonal forecast of globally averaged temperature. The validity of the model is checked through statistical testing and by comparing the theoretically expected skill scores with actual skill scores obtained from hindcast verification. A detailed comparison with the Canadian Seasonal to Interannual Prediction System (CanSIPS) shows that StocSIPS is just as accurate for one-month forecasts, but significantly more accurate for longer lead times.The scaling symmetry, which is the basis of StocSIPS, also holds at the regional level (here, 2.5°×2.5°). This allows applications for predicting the spatially resolved temperature field by treating each grid point as an independent time series. We obtain monthly and seasonal predictions of the surface temperature and show some preliminary comparison with multi-model ensemble (MME) GCM results. For one month lead times, this single pixel based stochastic model shows skill scores similar to the much more complex conventional (GCM) deterministic models.To explore the possibility of improving the predictions at a given place using past temperatures from other grid points, we developed the comprehensive multivariate version of StocSIPS (m-StocSIPS) as a full space-time process. m-StocSIPS allows to show that the regional memory-based StocSIPS forecasts are optimal in this stochastic framework. It also helps to untangle the usually complicated relationship between correlations and causality thanks to the precise notion of Granger causality. For a given position, past information from other locations cannot be used to improve on the forecast obtained as an optimal linear combination of past data: those correlations "were already used" to build the past at that position. By using m-StocSIPS we are able to reproduce the empirical cross-correlation structure of the temperature field over a wide range of time lags. This is made more convincing by making simulations that display numerous realistic but emergent model properties including spatial teleconnection networks and realistic El Niño patterns and indices"--