Data Assimilation methods are now applied to many areas of prediction and forecasting. This second edition introduces readers to applications across Earth systems and coupled Earth-Human Systems. It's indispensable for advanced undergraduate and graduate students, researchers, and practitioners working in weather forecasting and climate prediction.
Data Assimilation methods are now applied to many areas of prediction and forecasting. This second edition introduces readers to applications across Earth systems and coupled Earth-Human Systems. It's indispensable for advanced undergraduate and graduate students, researchers, and practitioners working in weather forecasting and climate prediction.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Eugenia Kalnay completed her Ph.D. at the Massachusetts Institute of Technology (MIT) under Jule Charney and became the first woman on the faculty in the Department of Meteorology. In 1979, she moved to NASA's Goddard Space Flight Center, where she developed the fourth-order global numerical model and led experiments in the new science called 'data assimilation.' In 1984, she became Head of NASA's Global Modeling and Simulation Branch. In 1987, she became Director of the National Oceanic and Atmospheric Administration's Environmental Modeling Center, where many improvements of models and data assimilation were developed for the National Weather Service forecasts. Her paper 'The NCEP/NCAR 40-year reanalysis project' (Kalnay et al., 1996) is the most cited paper in geosciences. In 1997, Kalnay became Lowry Chair at the University of Oklahoma and in 1999 became Atmospheric and Ocean Sciences Department Chair and professor at the University of Maryland, where she was later elected a Distinguished University Professor.
Inhaltsangabe
Dedication Preface to the Second Edition Reviews and Comments on the First Edition Foreword to the first edition Acknowledgement in the First Edition List of Variables List of Abbreviations 1. An overview of numerical weather prediction 2. The continuous equations 3. Numerical discretization of the equations of motion 4. Introduction to the parameterization of subgrid-scale physical processes 5. Data assimilation 6. Atmospheric predictability and ensemble forecasting A. Coding and checking the tangent linear and the adjoint models B. Post-processing of numerical model output to obtain station weather fore-casts.
Dedication Preface to the Second Edition Reviews and Comments on the First Edition Foreword to the first edition Acknowledgement in the First Edition List of Variables List of Abbreviations 1. An overview of numerical weather prediction 2. The continuous equations 3. Numerical discretization of the equations of motion 4. Introduction to the parameterization of subgrid-scale physical processes 5. Data assimilation 6. Atmospheric predictability and ensemble forecasting A. Coding and checking the tangent linear and the adjoint models B. Post-processing of numerical model output to obtain station weather fore-casts.
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