A Case Study Of The Persistence Of Weather Forecast Model Errors

This thesis describes performance measures and ensemble architectures for deterministic and probabilistic forecasts using the application example of wind power forecasting and proposes a novel scheme for the situation-dependent aggregation of forecasting models. For performance measures, error scores for deterministic as well as probabilistic forecasts are compared, and their characteristics are shown in detail. For the evaluation of deterministic forecasts, a categorization by basic error measure and normalization technique is introduced that simplifies the process of choosing an appropriate error measure for certain forecasting tasks. Furthermore, a scheme for the common evaluation of different forms of probabilistic forecasts is proposed. Based on the analysis of the error scores, a novel hierarchical aggregation technique for both deterministic and probabilistic forecasting models is proposed that dynamically weights individual forecasts using multiple weighting factors such as weather situation and lead time dependent weighting. In the experimental evaluation it is shown that the forecasting quality of the proposed technique is able to outperform other state of the art forecasting models and ensembles.

With contributions by leading experts, including an unpublished paper by Ed Lorenz, this book, first published in 2006, covers many topics in weather and climate predictability. It will interest those in the fields of environmental science and weather and climate forecasting, from graduate students to researchers, by examining theoretical and practical aspects of predictability.

Extreme Weather Forecasting reviews current knowledge about extreme weather events, including key elements and less well-known variables to accurately forecast them. The book covers multiple temporal scales as well as components of current weather forecasting systems. Sections cover case studies on successful forecasting as well as the impacts of extreme weather predictability, presenting a comprehensive and model agnostic review of best practices for atmospheric scientists and others who utilize extreme weather forecasts. Reviews recent developments in numerical prediction for better forecasting of extreme weather events Covers causes and mechanisms of high impact extreme events and how to account for these variables when forecasting Includes numerous case studies on successful forecasting, outlining why they worked

A quantitative introduction to atmospheric science for students and professionals who want to understand and apply basic meteorological concepts but who are not ready for calculus.

The Multiscale Global Monsoon System is the 4th and most up-to-date edition of the global monsoon book series produced by a group of leading international experts invited by the World Meteorological Organization's Working Group on Tropical Meteorology Research. The contents reflect the state of the knowledge of all scales of monsoon in the world's monsoon regions. It includes 31 chapters in five parts: Regional Monsoons, Extreme Weather, Intraseasonal Variations, Climate Change, and Field Experiments.