Problems And Prospects In Long And Medium Range Weather Forecasting

Forecasting the weather for the long and medium range is a difficult and scientifically challenging problem. Since the first operational weather prediction by numerical methods was carried out (on the BESK computer in Stockholm, Sweden, 1954) . there has been an ever accelerating development in computer technology. Hand in hand has followed a tremendous increase in the complexity of the atmospheric models used for weather prediction. The ability of these models to predict future states of the atmosphere has also increased rapidly, both due to model development and due to more accurate and plentiful observations of the atmosphere to define the initial . state for model integrations. It may however be argued on theoretical grounds that even if we have an almost perfect model with almost perfect initial data, we will never be able to make an accurate weather prediction more than a few weeks ahead. This is due to the inherent instability of the atmosphere and work in this field was pioneered by E. Lorenz. It is generally referred to as atmospheric predict ability and in the opening chapter of this book Professor Lorenz gives us an overview of the problem of atmospheric predictability. The contributions to this book were originally presented at the 1981 ECMWF Seminar (ECMWF - European Centre for Medium Range Weather Forecasts) which was held at ECMWF in Reading, England, in September 1981.

This book provides an overview of the early years of the European Centre for Medium-Range Weather Forecasts, and reviews the work of the institute over the past 30 years, describing along the way the European approach to medium-range weather forecasting. Its combination of historical view and scientific insight is unique.

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

Selected papers from the International Conference "Global Environmental Change: Challenges for Science and Society in South-Eastern Europe" held 19-21 May 2008 in Sofia, Bulgaria. Covers changes in climate, land use, carbon and water cycles, air quality, etc.

PREFACE xv LIST OF LECTURERS xix LIST OF PARTICIPANTS xx]. VOLUME I PART I - DESIGN AND DEVELOPMENT OF PHYSICALLY-BASED MODELS OF THE ATMOSPHERE Section 1 - Introduction GATES, W. L. - Climate and the Climate System 3 SIMMONS, A. J. and L. BENGTSSON - Atmospheric General Circulation Models: Their Design and Use for Climate Studies 23 Section 2 - Numerical Methods for Large-Scale Dynamics ARAKAWA, A. - Finite-Difference Methods in Climate Modeling 79 BOURKE, W. - Spectral Methods in Global Climate and Weather Prediction Models 169 Section 3 - Parameterization of Subgrid-Scale Physical Processes FOUQUART, Y. - Radiative Transfer in Climate Models 223 LAVAL, K. - Land Surface Processes 285 SELLERS, P. J. , Y. MINTZ, Y. C. SUD and A. DALCHER - A Brief Description of the Simple Biosphere Model (SiB) 307 SOMMERIA, G. - Parameterization of the Planetary Boundary Layer in Large-Scale Atmospheric Models 331 x TABLE OF CONTENTS TIEDTKE, M. - Parameterization of Cumulus Convection in Large-Scale Models 375 SUNDQVIST, H. - Parameterization of Condensation and Associated Clouds in Models for Weather Prediction and General Circulation Simulation 433 PART II - DESIGN AND DEVELOPMENT OF PHYSICALLY-BASED MODELS OF THE OCEAN AND SEA ICE HAN, Y. -J. - Modelling and Simulation of the General Circulation of the Ocean 465 HIBLER, W. D. - Modelling Sea Ice Thermodynamics and Dynamics in Climate Studies 509 PART III - METHODS OF COUPLING ATMOSPHERE, OCEAN AND ICE MODELS BRYAN, K.