Methods in Short-Term Climate Prediction

Abstract

The purpose of this chapter is to list the more common accepted methods used in short-term climate prediction, explain how they are designed, how they are supposed to work, what level of skill can be expected and the references to find more about them. The emphasis is on methodology but aspects of verification and cross-validation will be mentioned as well. Most methods will be accompanied by an example. We will also mention some of the less common methods, but with less detail. We even list some methods that are not used, to delineate which are acceptable and which are not. Sections 8.1–8.6 and 8.8 are easy to read, but Sections 8.7 and 8.9 are more difficult. It will become clear by the end of the climatology section (8.1), that only the departure from climatology, the so-called anomalies, are considered worthy forecast targets. The climatology itself, including such empirically established facts as “days are warmer than nights”, and “winters are colder than summer”, is considered too obvious to be a forecast target. This is not to say that a quantitative explanation of the Earth’s climate, including daily and annual cycle, is easy. But in professionally honest verification no points are given for forecasting a correct climatology. This chapter is thus about forecasting aspects of the geophysical system that are not so obvious and more difficult. The daily and annual cycle are periodic variations controlled by external forcings such as the solar heating. Implicit in identifying a periodic phenomenon as such is that the forecast of the phenomenon is easy out to infinity. This explains a widespread search for “cycles” in early meteorological research, but very little has been found other than the obvious daily and annual cycles. By removing a climatology that accounts for daily and annual variations we in effect remove the known easy periodic part of the system. In the absence of any other information climatology is the best information available. As many travelers can attest, somebody visiting an unfamiliar location 6 months from now is well served by inspecting climatological tables.