Quantification of Uncertainty in Operational and Experimental Fire-danger Forecasts

Quantification of Uncertainty in Operational and Experimental Fire-danger Forecasts PDF Author: Barbara G. Brown
Publisher:
ISBN:
Category : Fire weather
Languages : en
Pages : 230

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Quantification of Uncertainty in Operational and Experimental Fire-danger Forecasts

Quantification of Uncertainty in Operational and Experimental Fire-danger Forecasts PDF Author: Barbara G. Brown
Publisher:
ISBN:
Category : Fire weather
Languages : en
Pages : 230

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Verication of Experimental Probabilistic Spot Fire-weather Forecasts

Verication of Experimental Probabilistic Spot Fire-weather Forecasts PDF Author: Barbara G. Brown
Publisher:
ISBN:
Category : Fire weather
Languages : en
Pages : 76

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Completing the Forecast

Completing the Forecast PDF Author: National Research Council
Publisher: National Academies Press
ISBN: 0309180538
Category : Science
Languages : en
Pages : 124

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Book Description
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 Administration'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.

Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach

Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach PDF Author: Baranovskiy, Nikolay Viktorovich
Publisher: IGI Global
ISBN: 1799872521
Category : Technology & Engineering
Languages : en
Pages : 297

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Book Description
Forest fires cause ecological, economic, and social damage to various states of the international community. The causes of forest fires are rather varied, but the main factor is human activity in settlements, industrial facilities, objects of transport infrastructure, and intensively developed territories (in other words, anthropogenic load). In turn, storm activity is also a basic reason for forest fires in remote territories. Therefore, scientists across the world have developed methods, approaches, and systems to predict forest fire danger, including the impact of human and storm activity on forested territories. An important and comprehensive point of research is on the complex deterministic-probabilistic approach, which combines mathematical models of forest fuel ignition by various sources of high temperature and probabilistic criteria of forest fire occurrence. Forest Fire Danger Prediction Using Deterministic-Probabilistic Approach provides a comprehensive approach of forest fire danger prediction using mathematical models of forest fuel with consideration to anthropogenic load, storm activity, and meteorological parameters. Specifically, it uses the deterministic-probabilistic approach to predict forest fire danger and improve forest protection from fires. The chapters will cover various tree types, mathematical models, and solutions for reducing the destructive consequences of forest fires on ecosystems. This book is ideal for professionals and researchers working in the field of forestry, forest fire danger researchers, executives, computer engineers, practitioners, government officials, policymakers, academicians, and students looking for a new system to predict forest fire danger.

Quantification of Wildland Fire Risk Using Metamodeling of Fire Spread

Quantification of Wildland Fire Risk Using Metamodeling of Fire Spread PDF Author: Frédéric Allaire (auteur d'une thèse en mathématiques).)
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
This work addresses the quantification of wildfire risk by relying on simulations of fire spread. The objectives are to compute the probability distribution of burned surfaces that could result from wildfire ignition and quickly generate maps to assess which areas should receive focused protection against wildfires. This probability distribution should represent the uncertainty in the simulations. First, an ensemble of wildland fire spread simulations accounting for sources of uncertainty is generated following a Monte Carlo approach, and probabilistic evaluation of the predictions with observations is carried out. Then, the underlying probability distributions are calibrated based on the observations by adapting the Wasserstein distance to the comparison of burned surfaces to improve prediction performance in presence of uncertainty. Subsequently, a deep learning approach is followed to train a ``hybrid'' neural network with a convolutional part, thus building an emulator of ``potential'' fire size simulated by the fire spread model allowing to considerably reduce the computational time implied by the large amount of simulations required for high-resolution maps. Eventually, this emulator is applied to derive fire danger mapping from daily weather forecasts and applied to assess relatively large fire events.

Statistical Postprocessing of Ensemble Forecasts

Statistical Postprocessing of Ensemble Forecasts PDF Author: Stéphane Vannitsem
Publisher: Elsevier
ISBN: 012812248X
Category : Science
Languages : en
Pages : 364

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Book Description
Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture. - Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place - Provides real-world examples of methods used to formulate forecasts - Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner

Natural Hazard Uncertainty Assessment

Natural Hazard Uncertainty Assessment PDF Author: Karin Riley
Publisher: John Wiley & Sons
ISBN: 1119028094
Category : Science
Languages : en
Pages : 728

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Book Description
Uncertainties are pervasive in natural hazards, and it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties to inform modeling efforts. In this monograph we provide a broad, cross-disciplinary overview of issues relating to uncertainties faced in natural hazard and risk assessment. We introduce some basic tenets of uncertainty analysis, discuss issues related to communication and decision support, and offer numerous examples of analyses and modeling approaches that vary by context and scope. Contributors include scientists from across the full breath of the natural hazard scientific community, from those in real-time analysis of natural hazards to those in the research community from academia and government. Key themes and highlights include: Substantial breadth and depth of analysis in terms of the types of natural hazards addressed, the disciplinary perspectives represented, and the number of studies included Targeted, application-centered analyses with a focus on development and use of modeling techniques to address various sources of uncertainty Emphasis on the impacts of climate change on natural hazard processes and outcomes Recommendations for cross-disciplinary and science transfer across natural hazard sciences This volume will be an excellent resource for those interested in the current work on uncertainty classification/quantification and will document common and emergent research themes to allow all to learn from each other and build a more connected but still diverse and ever growing community of scientists. Read an interview with the editors to find out more: https://eos.org/editors-vox/reducing-uncertainty-in-hazard-prediction

Social Sciences in Forestry

Social Sciences in Forestry PDF Author:
Publisher:
ISBN:
Category : Forest policy
Languages : en
Pages : 486

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Quantification of Uncertainty in Weather Forecasts

Quantification of Uncertainty in Weather Forecasts PDF Author: W. Britt Evans
Publisher:
ISBN:
Category :
Languages : en
Pages : 206

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Current Procedures and Practices in Spot Fire-weather Forecasting

Current Procedures and Practices in Spot Fire-weather Forecasting PDF Author: B. G. Brown
Publisher:
ISBN:
Category :
Languages : en
Pages : 54

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Book Description