Atmospheric Modeling, Data Assimilation and Predictability

Rating:
Summary: lacks coherence and the flow of a quality textbook
Review: I had this book for courses in numerical weather prediction and in data assimilation (DA), and was far from impressed.

While the historical overview in Chapter 1 is a pleasant read, the litany of errors in equations begins quickly in Chapter 2. Terms as simple as in the equations of motion are incorrect. Some things are unforgiveable in a textbook, and an error in a sophomore-level equation is one of them.

I can manage the mess of linear algebra in the text. However, Kalnay's writing style is more of one suited for lecture notes; she jumps around from topic to topic, and provides very little transition in some spots. Other locations in the notes that need further explanation (and probably would get it, if students could stop the author and ask questions), are left too vague. This is not the way to write a very good textbook, and I do not believe this book is anywhere near "very good."

I give it two stars, however, because it's the most current book in the field; there aren't many other places to turn for discussions on Kalman filters, etc. That said, if you are looking for a practical discussion of NWP or DA, or how to implement a DA scheme, you'll have a difficult time weeding it out of this book.

Rating:
Summary: Essential Guide for Data Assimilation
Review: This is a textbook for graduate atmospheric science students, but I found it useful even as an undergraduate. Lots of clear explanations along with historical background, written by one the leaders of the numerical weather prediction field. She was involved in the implementation at NCEP. There is heavy-duty linear algebra in some chapters but overall this is not a math-intensive book. Good reference and extensive bibliography.