Uncertainties In Numerical Weather Prediction

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

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.

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.

Numerical Weather Prediction (NWP) is the current state-of-art methodology to provide weather prediction at different spatial and time scales to serve user community. The NWP uses a modeling system built up adopting the mathematical equations governing atmospheric motion, incorporating the physical processes through parameterization methods, solved applying numerical methods and carrying out large number-crunching calculations on high speed computers. The NWP products have their application in agriculture, aviation, transport, tourism, sports, industry, health, energy and many other social sectors. Several decision support systems of disaster management and risk assessment are dependent on meteorological information from NWP products. The purpose of this book is to present the basics of NWP in lucid form to those who seek an overview of the science of modern weather prediction. Print edition not for sale in South Asia (India, Sri Lanka, Nepal, Bangladesh, Pakistan or Bhutan).

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.

This textbook provides a comprehensive yet accessible treatment of weather and climate prediction, for graduate students, researchers and professionals. It teaches the strengths, weaknesses and best practices for the use of atmospheric models. It is ideal for the many scientists who use such models across a wide variety of applications. The book describes the different numerical methods, data assimilation, ensemble methods, predictability, land-surface modeling, climate modeling and downscaling, computational fluid-dynamics models, experimental designs in model-based research, verification methods, operational prediction, and special applications such as air-quality modeling and flood prediction. This volume will satisfy everyone who needs to know about atmospheric modeling for use in research or operations. It is ideal both as a textbook for a course on weather and climate prediction and as a reference text for researchers and professionals from a range of backgrounds: atmospheric science, meteorology, climatology, environmental science, geography, and geophysical fluid mechanics/dynamics.

This book offers a complete primer, covering the end-to-endprocess of forecast production, and bringing together a descriptionof all the relevant aspects together in a single volume; withplenty of explanation of some of the more complex issues andexamples of current, state-of-the-art practices. Operational Weather Forecasting covers the whole processof forecast production, from understanding the nature of theforecasting problem, gathering the observational data with which toinitialise and verify forecasts, designing and building a model (ormodels) to advance those initial conditions forwards in time andthen interpreting the model output and putting it into a form whichis relevant to customers of weather forecasts. Included is thegeneration of forecasts on the monthly-to-seasonal timescales,often excluded in text-books despite this type of forecastinghaving been undertaken for several years. This is a rapidly developing field, with a lot of variations inpractices between different forecasting centres. Thus theauthors have tried to be as generic as possible when describingaspects of numerical model design and formulation. Despitethe reliance on NWP, the human forecaster still has a big part toplay in producing weather forecasts and this is described, alongwith the issue of forecast verification – how forecastcentres measure their own performance and improve upon it. Advanced undergraduates and postgraduate students will use thisbook to understand how the theory comes together in the day-to-dayapplications of weather forecast production. In addition,professional weather forecasting practitioners, professional usersof weather forecasts and trainers will all find this new member ofthe RMetS Advancing Weather and Climate series avaluable tool. Provides an end-to-end description of the weather forecastingprocess Clearly structured and pitched at an accessible level, the bookdiscusses the practical choices that operational forecastingcentres have to make in terms of what numerical models they use andwhen they are run. Takes a very practical approach, using real life case-studiesto contextualize information Discusses the latest advances in the area, including ensemblemethods, monthly to seasonal range prediction and use of‘nowcasting’ tools such as radar and satelliteimagery Full colour throughout Written by a highly respected team of authors with experiencein both academia and practice. Part of the RMetS book series ‘Advancing Weather andClimate’