About the Book
Since the publication of the first edition of this highly regarded textbook, the value of data assimilation has become widely recognized across the Earth sciences and beyond. Data assimilation methods are now being applied to many areas of prediction and forecasting, including extreme weather events, wildfires, infectious disease epidemics, and economic modeling. This second edition provides a broad introduction to applications across the Earth systems and coupled Earth–human systems, with an expanded range of topics covering the latest developments of variational, ensemble, and hybrid data assimilation methods. New toy models and intermediate-complexity atmospheric general circulation models provide hands-on engagement with key concepts in numerical weather prediction, data assimilation, and predictability. The inclusion of computational projects, exercises, lecture notes, teaching slides, and sample exams makes this textbook an indispensable and practical resource for advanced undergraduate and graduate students, researchers, and practitioners who work in weather forecasting and climate prediction.
Table of Contents:
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.
About the Author :
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. Safa Mote is Assistant Professor of Computational and Applied Mathematics at Portland State University and Visiting Assistant Professor of Atmospheric and Oceanic Sciences at the University of Maryland who has worked on a wide range of challenging interdisciplinary problems. He has two Ph.D. degrees in Physics and in Applied Mathematics and Statistics, and Scientific Computing from the University of Maryland. He designs mathematical models to propose and assess holistic policies that lead to sustainability in interconnected environmental, economic, climate, and health systems. He develops computational methods based on Dynamical Systems, Machine Learning, and Data Assimilation to forecast extreme weather and climate events, improve subseasonal to seasonal predictions, and create projections for the coupled energy–water–food nexus. Cheng Da works on Coupled Data Assimilation as a postdoctoral research associate at the University of Maryland and the Global Modeling and Assimilation Office at NASA's Goddard Space Flight Center. Supported by the NASA Earth and Space Science Fellowship, he earned his Ph.D. degree under the supervision of Professor Kalnay at the University of Maryland, focusing on the assimilation of precipitation and nonlocal observations in the ensemble data assimilation system and coupled data assimilation. Before this, he earned his bachelor's and Master's degrees in Meteorology at Florida State University, working on radiance assimilation from spaceborne sensors.
Review :
'The first edition is a classic, the definitive text on the subject written by an essential contributor to data assimilation theory and to operational weather forecasting. The second edition is better: broader, expanding to earth system models, and deeper, including the advances of the past decades, right up to machine learning. The presentation is honed by decades of teaching this material, making complex topics clear. The inclusion of models with two-way coupling between the human and climate systems opens a new research direction. The methodology of combining models and data is broadly applicable beyond climate science and this is the place to learn it. This is one of the few science texts that is a great book.' Mark Cane, Emeritus, Lamont-Doherty Earth Observatory of Columbia University
'Since first publication 22 years ago by the world's preeminent expert on data assimilation, modelling and prediction of weather and climate have evolved from atmospheric models to complex earth system models with interactions between the atmosphere, biosphere, and hydrosphere. This second edition is an indispensable update, at just the right time for students, researchers, and practitioners. It introduces readers to the emerging field of interactions between earth and human systems - an understanding of which is critical for the sustainability of human societies.' Jagadish Shukla, Center for Ocean-Land-Atmosphere Studies, George Mason University
Review of previous edition: '… a frisson of excitement accompanied the rumour that Eugenia Kalnay was writing a new book. Expectations were high, since she is a renowned expert in the field. She has not disappointed us.' Science and Technology
Review of previous edition: '… quite wonderful, achieving a tremendous balance between comprehensiveness and readability. I am especially pleased with the numerical analysis part, which is crystal clear and shows the benefits of classroom testing. I also like the tiny little touches, like the stepped-on butterfly story and the mention that Poincaré knew about chaos in celestial mechanics. Your book fills an enormous hole in the literature of NWP [numerical weather prediction].' Richard C. J. Somerville, Scripps Institution of Oceanography, San Diego
Review of previous edition: 'Fantastic … in content, format and practicability.' Kelvin K. Droegemeier, Regents' Professor of Meteorology, and Director, Center for Analysis and Prediction of Storms, University of Oklahoma
Review of previous edition: 'I admire the clarity and pedagogic superiority of [this] presentation.' Anders Persson, Swedish Meteorological and Hydrological Institute (SMHI)
Review of previous edition: '… much better for learning about data assimilation than anything else currently available.' Richard Swinbank, United Kingdom Meteorological Office
Review of previous edition: '… the presentation is impeccable and is very accessible to non-meteorologists like me.' Eric Kostelich, University of Arizona
Review of previous edition: '… what a great wealth of historical information.' Lawrence Takacs, NASA, Data Assimilation Office
Review of previous edition: '… a delight to read … It will be of great assistance to our community and should greatly encourage young scientists who may be thinking of entering the field … the book will be of considerable value to people who are unable or unwilling to cope with mathematical technicalities. They can gain much by studying the expository sections of the text.' Peter Lynch, Assistant Director, Irish Weather Service
Review of previous edition: '… the method in the data assimilation section of starting with 'baby' examples, and then working up through the full analysis, is great for understanding. On the predictability part, the history, and the explanations of how the unstable perturbations grow is the best I've seen.' Alexander E. MacDonald, Director, NOAA Forecast Systems Lab
Review of previous edition: '… this book … is extremely useful, informative, and well-written … there are many instances where items that were only marginally familiar beforehand have now become very clear.' Brian O. Blanton, Senior Scientist/Oceanographer, University of North Carolina, Chapel Hill
