I found this book "Statistical methods in atmospheric sciences" by Daniel Wilks in the library. Do you think it is good for learning statistical methods in general? The examples are as you might know or expect, from atmospheric sciences but discussion about the statistical methods is quite good.
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$\begingroup$ I know you said "for learning statistical methods in general" but if you specify exactly what level of learning that you're at or aiming for (e.g. first year undergrad, masters, etc.) then it may be easier for people to leave you good / more specific advice. Essentially, some books are good for people at certain stages of learning - and not so useful to people at other stages. $\endgroup$– Graeme WalshCommented Jun 15, 2013 at 15:21
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The introductory chapters on foundations of statistics are very very cursory, and do not pay much attention to explaining stuff or providing exercises on deriving formulas or describing pitfalls of various approaches (it's only "compute this, calculate that"). A good thing is presence of material on Extreme Value Distributions (4.4.5). Unfortunately, the order of presentation is not that logical: in the part about Univariate statistics the author starts talking about spatial correlation and I fail to see any stuff on random fields and spatial statistics. Matrix algebra chapter looks like an afterthought. Classification and cluster analysis are slapped onto the book after forecasting... The most glaring is, however, VERY superficial discussion of ensemble forecasts. Run-of-the-mill Kalman filter is briefly mentioned (NOT explained) on 2 pages, Ensemble Kalman Filter discussed on one page and a half.
It is good bedtime reading, I would venture to say, but not sufficient for learning stats even on the first pass.
