Introduction and comments on books

Physics of Climate (Peixoto and Oort)

The subject is the science of the global atmosphere and hydrosphere in a physical perspective (as in another book by HARTMANN (1994) [see my notes]).

Understanding of the climate system in terms of physical principles has been advanced in the 20th century by prognostic approach, that is, to predict the state of the atmosphere by using physical principles. This approach is introduced in this book to some extent.

The expertise of the authors is, however, in the diagnostic approach. Here, the most reliable physical principles are taken. These are laws of conservation of mass (particularly of mass of the water substance H2O), energy and angular momentum. These laws are formulated as equations, and each term of the equations are evaluated with observational data. After confirming that the data consistently represent the actual balance, we can discuss what process is mostly responsible for increasing or decreasing the conserved quantity at a certain part of the atmosphere. Both of the authors were members of the project that first developed this approach, which was lead by Prof. Victor STARR at the Massachusetts Institute of Technology in the 1940s and 1950s (e.g. STARR & PEIXOTO 1958). The formulation of equations are described in detail and it is helpful for those who want to do diagnosis themselves.

Nowadays when we apply the diagnosic approach we use products of data assimilation (see KALNAY 2003 [my notes]), which in turn involves prognostic approach (a numerical weather preciction model). The authors take, however, a purely diagnostic approach. Most of the numbers are taken from the statistics of OORT (1983), that uses observational data (mainly by radiosondes) but no prognostic model. (My paper published in 1988 is a diagnosic work which used products of data assimilation. I am astonished by the fact that this book categorized it in "modeling works".) It should be taken into account that prognostic models of 1970s were much less reliable than present, and that even the present ones are not reliable in some aspects. Sometimes we have to go back to observation-only statistics. For numerical presentation of the state of the atmosphere, however, we usually prefer figures based on data assimilation products, rather than the figures in this book.

Another point that makes this book inconvenient to be used as a reference is that the scale of the figures is different even between those printed on the same page. It is because most of them are direct copies of those which had appeared in various publications during a decade of time.


Thermodynamics of the climate system is not adiabatic, and it should be better understood in terms of entropy production. This book contains an attempt of diagnostic study (original work of PEIXOTO and his collaborators) in Chapter 15, but it is the entropy balance of "dry atmosphere", and I think it inadequate to separately discuss thermodynamics of "dry atmosphere" and water vapor actually occupying the same space and having the same temperature (even though the convention works well for energy balance). Understanding of entropy production in the climate system has recently been advanced (e.g. OZAWA et al. 2003; KLEIDON and LORENZ 2005). As far as I understand, however, there is no adequate framework yet for entropy budgets of moist atmosphere involving phase changes of water. It is a research frontier for those who are interested.


Discussion of the balance of angular momentum in the atmosphere is a subject which OORT has himself had great contribution. But the discussion is limited to the component of rotation around a single axis -- "the axis of the rotation of the earth" -- which is assumed fixed. Recently, study of all three components of the angular momentum has advanced, as reviewed by EGGER et al. (2007). This seems to be another research front of earth system science which need to combine knowledge of the atmosphere, the hydrosphere and the solid earth. As EGGER et al. mention, quantitative three-dimensional evaluation became possible with data assimilation (combination of observational data and prognostic models) rather than just diagnosis of observational data.


2004-Nov-25; latest revisions 2008-Apr-24; moved here 2009-Feb-09

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