BOOK-CHAPTER

The Practice of Short-Term Climate Prediction

Huug van den Dool

Year: 2006 Oxford University Press eBooks   Publisher: Oxford University Press

Abstract

While previous chapters were about methods and their formal backgrounds, we here present a description of the process of making a forecast and the protocol surrounding it. A look in the kitchen. It is difficult to find literature on the subject, presumably because a real-time forecast is not a research project and potential authors (the forecasters) work in an ever-changing environment and may never feel the time is right to write an overview of what they are doing. Moreover, it may be very difficult to describe real-time forecasts and present a complete picture. Nearly all of the material presented here specifically applies to the seasonal prediction made at the NWS in the USA, but should be relevant elsewhere. A real-time operational forecast setting lacks the logic and methodical approach one should strive for in science. This is for many reasons. There is pressure, time schedules are to be met, input data sets could be missing or incorrect, and one can feel the suspense, excitement and disappointment associated with a forecast in real time. There are habits that are carried over from years past—forecasters are partly set in their ways or find it difficult to make major changes in mid-stream. The interaction with the user influences the forecast, and/or the way the information is conveyed. Psychology enters the forecast. Assumptions about what users want or understand do play a role. Generally speaking a forecast is thus a mix of what is scientifically possible on the one hand and what is presumably useful to the customer on the other. The CPC/NWS forecasts are moreover for the general user, not one user specifically. Users for short-term climate forecasts range from the highly sophisticated (energy traders, selling of weather derivatives, hydrologists) via the (wo)man in the street to entertainment. The seasonal forecast has been around a long time in the USA. Jerome Namias started in-house seasonal forecasts at the NWS in 1958. After 15 years of testing, his successor Donald Gilman made the step to public release in 1973.

Keywords:
Disappointment Set (abstract data type) Computer science Term (time) Process (computing) Operations research Data science Engineering Psychology Social psychology

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Topics

Meteorological Phenomena and Simulations
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

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