Earth System Modeling, Data Assimilation and Predictability

‘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