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Uncertainties in Numerical Weather Prediction

Uncertainties in Numerical Weather Prediction
A Book

by Haraldur Olafsson,Jian-Wen Bao

  • Publisher : Elsevier
  • Release : 2020-12-08
  • Pages : 364
  • ISBN : 0128157100
  • Language : En, Es, Fr & De
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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

Modeling Uncertainty of Numerical Weather Predictions Using Learning Methods

Modeling Uncertainty of Numerical Weather Predictions Using Learning Methods
A Book

by Ashkan Zarnani,University of Alberta. Department of Electrical and Computer Engineering

  • Publisher : Unknown Publisher
  • Release : 2014
  • Pages : 127
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Weather forecasting is one of the most vital tasks in many applications ranging from severe weather hazard systems to energy production. Numerical weather prediction (NWP) systems are commonly used state-of-the-art atmospheric models that provide point forecasts as deterministic predictions arranged on a three-dimensional grid. However, there is always some level of error and uncertainty in the forecasts due to inaccuracies of initial conditions, the chaotic nature of weather, etc. Such uncertainty information is crucial in decision making and optimization processes involved in many applications. A common representation of forecast uncertainty is a Prediction Interval (PI) that determines a minima, maxima and confidence level for each forecast, e.g. [2°C, 15°C]-95%. In this study, we investigate various methods that can model the uncertainty of NWP forecasts and provide PIs for the forecasts accordingly. In particular, we are interested in analyzing the historical performance of the NWP system as a valuable source for uncertainty modeling. Three different classes of methods are developed and applied for this problem. First, various clustering algorithms (including fuzzy c-means) are employed in concert with fitting appropriate probability distributions to obtain statistical models that can dynamically provide PIs depending on the forecast context. Second, a range of quantile regression methods (including kernel quantile regression) are studied that can directly model the PI boundaries as a function of influential features. In the third class, we focus on various time series modeling approaches including heteroscedasticity modeling methods that can provide forecasts of conditional mean and conditional variance of the target for any forecast horizon. iv All presented PI computation methods are empirically evaluated using a developed comprehensive verification framework in a set of experiments involving real-world data sets of NWP forecasts and observations. A key component is proposed in the evaluation process that would lead to a considerably more reliable judgment. Results show that PIs obtained by the ARIMA-GARCH model (for up to 6-hour-ahead forecasts) and Spline Quantile Regression (for longer leads) provide interval forecasts with satisfactory reliability and significantly better skill. This can lead to improvements in forecast value for many systems that rely on the NWP forecasts.

Parametric Uncertainty in Numerical Weather Prediction Models

Parametric Uncertainty in Numerical Weather Prediction Models
A Book

by Pirkka Ollinaho

  • Publisher : Unknown Publisher
  • Release : 2014
  • Pages : 329
  • ISBN : 9789516978232
  • Language : En, Es, Fr & De
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High Resolution Numerical Weather Prediction, Distributed Hydrological Models and Uncertainty - Towards a Unified Approach

High Resolution Numerical Weather Prediction, Distributed Hydrological Models and Uncertainty - Towards a Unified Approach
A Book

by Philip M. Younger

  • Publisher : Unknown Publisher
  • Release : 2007
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Uncertainty Propagation in Complex Coupled Flood Risk Models Using Numerical Weather Prediction and Weather Radars

Uncertainty Propagation in Complex Coupled Flood Risk Models Using Numerical Weather Prediction and Weather Radars
A Book

by Yunqing Xuan

  • Publisher : Unknown Publisher
  • Release : 2007
  • Pages : 250
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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A Case Study of the Persistence of Weather Forecast Model Errors

A Case Study of the Persistence of Weather Forecast Model Errors
A Book

by Barbara Sauter

  • Publisher : Unknown Publisher
  • Release : 2005
  • Pages : 40
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Decision makers could frequently benefit from information about the amount of uncertainty associated with a specific weather forecast. Automated numerical weather prediction models provide deterministic weather forecast values with no estimate of the likely error. This case study examines the day-to-day persistence of forecast errors of basic surface weather parameters for four sites in northern Utah. Although exceptionally low or high forecast errors on one day are more likely to be associated with a similar quality forecast the following day, the relationship is not considered strong enough to provide beneficial guidance to users without meteorological expertise. Days resulting in average forecast errors showed no persistence in the quality of the subsequent day's forecast. More sophisticated methods are needed to generate and portray weather forecast uncertainty information.

Uncertainty in Mesoscale Numerical Weather Prediction

Uncertainty in Mesoscale Numerical Weather Prediction
Probabilistic Forecasting of Precipitation

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2015
  • Pages : 108
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Computational Science – ICCS 2019

Computational Science – ICCS 2019
19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings

by João M. F. Rodrigues,Pedro J. S. Cardoso,Jânio Monteiro,Roberto Lam,Valeria V. Krzhizhanovskaya,Michael H. Lees,Jack J. Dongarra,Peter M.A. Sloot

  • Publisher : Springer
  • Release : 2019-06-07
  • Pages : 663
  • ISBN : 3030227472
  • Language : En, Es, Fr & De
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The five-volume set LNCS 11536, 11537, 11538, 11539 and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019. The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019 Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Meteorology at the Millennium

Meteorology at the Millennium
A Book

by Robert P. Pearce

  • Publisher : Elsevier
  • Release : 2005-02-22
  • Pages : 333
  • ISBN : 008051149X
  • Language : En, Es, Fr & De
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Meteorology at the Millennium details recent advances in meteorology and explores its interfaces with science, technology, and society. Ways in which modern meteorology is contributing to the developments in other sciences are described, as well as how atmospheric scientists are learning from colleagues in related disciplines. Meteorology at the Millennium will serve as a point of reference for students and researchers of meteorology and climatology for many years to come. The areas covered include weather prediction at the millennium, climate variability and change, atmosphere-ocean coupling, the biogeochemical system, weather on other planets. This book is a compilation of the best invited papers presented at a conference celebrating the 150 years of the Royal Meteorological Society (RMS).

Mathematical Problems in Meteorological Modelling

Mathematical Problems in Meteorological Modelling
A Book

by András Bátkai,Petra Csomós,István Faragó,András Horányi,Gabriella Szépszó

  • Publisher : Springer
  • Release : 2016-11-08
  • Pages : 264
  • ISBN : 3319401572
  • Language : En, Es, Fr & De
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This book deals with mathematical problems arising in the context of meteorological modelling. It gathers and presents some of the most interesting and important issues from the interaction of mathematics and meteorology. It is unique in that it features contributions on topics like data assimilation, ensemble prediction, numerical methods, and transport modelling, from both mathematical and meteorological perspectives. The derivation and solution of all kinds of numerical prediction models require the application of results from various mathematical fields. The present volume is divided into three parts, moving from mathematical and numerical problems through air quality modelling, to advanced applications in data assimilation and probabilistic forecasting. The book arose from the workshop “Mathematical Problems in Meteorological Modelling” held in Budapest in May 2014 and organized by the ECMI Special Interest Group on Numerical Weather Prediction. Its main objective is to highlight the beauty of the development fields discussed, to demonstrate their mathematical complexity and, more importantly, to encourage mathematicians to contribute to the further success of such practical applications as weather forecasting and climate change projections. Written by leading experts in the field, the book provides an attractive and diverse introduction to areas in which mathematicians and modellers from the meteorological community can cooperate and help each other solve the problems that operational weather centres face, now and in the near future. Readers engaged in meteorological research will become more familiar with the corresponding mathematical background, while mathematicians working in numerical analysis, partial differential equations, or stochastic analysis will be introduced to further application fields of their research area, and will find stimulation and motivation for their future research work.

Air Traffic Management and Systems III

Air Traffic Management and Systems III
Selected Papers of the 5th ENRI International Workshop on ATM/CNS (EIWAC2017)

by Electronic Navigation Research Institute

  • Publisher : Springer
  • Release : 2019-06-21
  • Pages : 287
  • ISBN : 9811370869
  • Language : En, Es, Fr & De
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This proceedings provides novel concepts and techniques for air traffic management (ATM) and communications, navigation, and surveillance (CNS) systems. The volume consists of selected papers from the 5th ENRI International Workshop on ATM/CNS (EIWAC2017) held in Tokyo in November 2017, the theme of which was “Drafting Future Skies”. Included are key topics to realize safer and more efficient skies in the future, linked to the integrated conference theme consisting of long-term visions based on presentations from various fields. The proceedings is dedicated not only to researchers, academicians, and university students, but also to engineers in the industry, air navigation service providers (ANSPs), and regulators of aviation.

Masters of Uncertainty

Masters of Uncertainty
Weather Forecasters and the Quest for Ground Truth

by Phaedra Daipha

  • Publisher : University of Chicago Press
  • Release : 2015-11-17
  • Pages : 272
  • ISBN : 022629871X
  • Language : En, Es, Fr & De
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Though we commonly make them the butt of our jokes, weather forecasters are in fact exceptionally good at managing uncertainty. They consistently do a better job calibrating their performance than stockbrokers, physicians, or other decision-making experts precisely because they receive feedback on their decisions in near real time. Following forecasters in their quest for truth and accuracy, therefore, holds the key to the analytically elusive process of decision making as it actually happens. In Masters of Uncertainty, Phaedra Daipha develops a new conceptual framework for the process of decision making, after spending years immersed in the life of a northeastern office of the National Weather Service. Arguing that predicting the weather will always be more craft than science, Daipha shows how forecasters have made a virtue of the unpredictability of the weather. Impressive data infrastructures and powerful computer models are still only a substitute for the real thing outside, and so forecasters also enlist improvisational collage techniques and an omnivorous appetite for information to create a locally meaningful forecast on their computer screens. Intent on capturing decision making in action, Daipha takes the reader through engrossing firsthand accounts of several forecasting episodes (hits and misses) and offers a rare fly-on-the-wall insight into the process and challenges of producing meteorological predictions come rain or come shine. Combining rich detail with lucid argument, Masters of Uncertainty advances a theory of decision making that foregrounds the pragmatic and situated nature of expert cognition and casts into new light how we make decisions in the digital age.

The Emergence of Numerical Weather Prediction: Richardson's Dream

The Emergence of Numerical Weather Prediction: Richardson's Dream
A Book

by Peter Lynch

  • Publisher : Cambridge University Press
  • Release : 2006-11-02
  • Pages : 279
  • ISBN : 0521857295
  • Language : En, Es, Fr & De
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This book, first published in 2006, is a history of weather forecasting for researchers, graduate students and professionals in numerical weather forecasting.

Diagnosing the Downstream Impact of Extratropical Transition Using Multimodel Operational Ensemble Prediction Systems

Diagnosing the Downstream Impact of Extratropical Transition Using Multimodel Operational Ensemble Prediction Systems
A Book

by Julia Henriette Keller

  • Publisher : KIT Scientific Publishing
  • Release : 2012
  • Pages : 270
  • ISBN : 3866449844
  • Language : En, Es, Fr & De
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Communicating Uncertainties in Weather and Climate Information

Communicating Uncertainties in Weather and Climate Information
A Workshop Summary

by National Research Council,Division on Earth and Life Studies,Board on Atmospheric Sciences and Climate

  • Publisher : National Academies Press
  • Release : 2003-02-15
  • Pages : 68
  • ISBN : 0309085403
  • Language : En, Es, Fr & De
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The report explores how best to communicate weather and climate information by presenting five case studies, selected to illustrate a range of time scales and issues, from the forecasting of weather events, to providing seasonal outlooks, to projecting climate change.

The Oxford Handbook of Economic Forecasting

The Oxford Handbook of Economic Forecasting
A Book

by Michael P. Clements,David F. Hendry

  • Publisher : Oxford University Press
  • Release : 2011-06-29
  • Pages : 744
  • ISBN : 9780199875511
  • Language : En, Es, Fr & De
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This Handbook provides up-to-date coverage of both new and well-established fields in the sphere of economic forecasting. The chapters are written by world experts in their respective fields, and provide authoritative yet accessible accounts of the key concepts, subject matter, and techniques in a number of diverse but related areas. It covers the ways in which the availability of ever more plentiful data and computational power have been used in forecasting, in terms of the frequency of observations, the number of variables, and the use of multiple data vintages. Greater data availability has been coupled with developments in statistical theory and economic analysis to allow more elaborate and complicated models to be entertained; the volume provides explanations and critiques of these developments. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models, as well as models for handling data observed at mixed frequencies, high-frequency data, multiple data vintages, methods for forecasting when there are structural breaks, and how breaks might be forecast. Also covered are areas which are less commonly associated with economic forecasting, such as climate change, health economics, long-horizon growth forecasting, and political elections. Econometric forecasting has important contributions to make in these areas along with how their developments inform the mainstream.

Completing the Forecast

Completing the Forecast
Characterizing and Communicating Uncertainty for Better Decisions Using Weather and Climate Forecasts

by National Research Council,Division on Earth and Life Studies,Board on Atmospheric Sciences and Climate,Committee on Estimating and Communicating Uncertainty in Weather and Climate Forecasts

  • Publisher : National Academies Press
  • Release : 2006-10-09
  • Pages : 124
  • ISBN : 9780309180535
  • Language : En, Es, Fr & De
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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.

Monthly Weather Review

Monthly Weather Review
A Book

by Anonim

  • Publisher : Unknown Publisher
  • Release : 2004
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Atmospheric Science

Atmospheric Science
An Introductory Survey

by John M. Wallace,Peter V. Hobbs

  • Publisher : Elsevier
  • Release : 2006-03-24
  • Pages : 504
  • ISBN : 9780080499536
  • Language : En, Es, Fr & De
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Atmospheric Science, Second Edition, is the long-awaited update of the classic atmospheric science text, which helped define the field nearly 30 years ago and has served as the cornerstone for most university curricula. Now students and professionals alike can use this updated classic to understand atmospheric phenomena in the context of the latest discoveries, and prepare themselves for more advanced study and real-life problem solving. This latest edition of Atmospheric Science, has been revamped in terms of content and appearance. It contains new chapters on atmospheric chemistry, the Earth system, the atmospheric boundary layer, and climate, as well as enhanced treatment of atmospheric dynamics, radiative transfer, severe storms, and global warming. The authors illustrate concepts with full-color, state-of-the-art imagery and cover a vast amount of new information in the field. Extensive numerical and qualitative exercises help students apply basic physical principles to atmospheric problems. There are also biographical footnotes summarizing the work of key scientists, along with a student companion website that hosts climate data; answers to quantitative exercises; full solutions to selected exercises; skew-T log p chart; related links, appendices; and more. The instructor website features: instructor’s guide; solutions to quantitative exercises; electronic figures from the book; plus supplementary images for use in classroom presentations. Meteorology students at both advanced undergraduate and graduate levels will find this book extremely useful. Full-color satellite imagery and cloud photographs illustrate principles throughout Extensive numerical and qualitative exercises emphasize the application of basic physical principles to problems in the atmospheric sciences Biographical footnotes summarize the lives and work of scientists mentioned in the text, and provide students with a sense of the long history of meteorology Companion website encourages more advanced exploration of text topics: supplementary information, images, and bonus exercises

Improving Medium-range Streamflow Forecasting Across U.S. Middle Atlantic Region

Improving Medium-range Streamflow Forecasting Across U.S. Middle Atlantic Region
A Book

by Ridwan Siddique

  • Publisher : Unknown Publisher
  • Release : 2017
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Short- to medium-range (forecast lead times from 0 to 14 days) streamflow forecasts are subject to uncertainties from various sources. A major source of uncertainty is due to the weather or meteorological forcing. In turn, the uncertainties from the meteorological forcing are propagated into the streamflow forecasts when using the meteorological forecasts (i.e., the outputs from a Numerical Weather Prediction (NWP) model) as forcing to hydrological models. Additionally, the hydrological models themselves are another important source of uncertainty, where uncertainty arises from model structure, parameters, initial and boundary conditions. To advance the science of hydrological modeling and forecasting, these uncertainties need to be quantified and modeled, using novel statistical techniques and robust verification strategies, with the goal of improving the skill and reliability of streamflow forecasts. This, ultimately, may allow generating in advance (i.e., with longer lead times) more informative forecasts, which could eventually translate into better emergency preparedness and response.The main research goal of this dissertation is to develop, implement and verify a new regional hydrological ensemble prediction system (RHEPS), comprised by a numerical weather prediction (NWP) model, different hydrological models and different statistical bias-correction techniques. To implement and verify the new RHEPS, the U.S. middle Atlantic region (MAR) is selected as the study area. This is a region of high socio-economic value with populated cities and, at the same time, vulnerable to floods and other natural disasters. To meet my research goal, the following objectives are carried out: Objective 1 (O1) - To choose a relevant NWP model or system by evaluating and verifying the outputs from different meteorological forecasting systems (i.e., the outputs or forecasts from their underlying NWP models); Objective 2 (O2) - To verify streamflow forecasts generated by forcing a distributed hydrological model with meteorological ensembles, and to develop and evaluate a statistical postprocessor to quantify the uncertainty and adjust biases in the streamflow forecasts; Objective 3 (O3) - To develop, implement and rigorously verify a multimodel approach for short- to medium-range streamflow forecasting. The overarching hypothesis of this dissertation is that the combination and configuration of the different system components in the streamflow forecasting system can have a significant influence on forecast uncertainty and that hydrological multimodeling is able to significantly enhance the quality of streamflow forecasts. The RHEPS is used to test this hypothesis.To meet O1, precipitation ensemble forecasts from two different NWP models are verified. The two NWP models are the National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2) and the 21-member Short Range Ensemble Forecast (SREF) system. The verification results for O1 reveal the quality of the meteorological forcing and serve to inform the decision of selecting a NWP model for O2. As part of O2, the meteorological outputs from the GEFSRv2 are used to force the NOAAs Hydrology Laboratory-Research Distributed Hydrological Model (HL-RDHM) and generate short- to medium-range (1-7 days) ensemble streamflow forecasts for different basins in the MAR. The streamflow forecasts are postprocessed (bias-corrected) using a time series model. The verification results from O2 show that the ensemble streamflow forecasts remain skillful for the entire forecast cycle of 7 days. Additionally, postprocessing increases forecast skills across lead times and spatial scales, particularly for the high flow conditions. Lastly, with O3, a multimodel hydrological framework is tested for medium-range ensemble streamflow forecasts. The results show that the multimodel consistently improves short- to medium-range streamflow forecasts across different basin sizes compared to the single model forecasts.