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CR 08:183-194 (1997)  -  DOI:

On the disaggregation of climatological means and anomalies

Gerd Bürger*

Potsdam Institut für Klimafolgenforschung, Postfach 601203, D-14412 Potsdam, Germany

The tool C2W (climate-to-weather disaggregator) is introduced which is aimed at disaggregating climatological means and anomalies into realistic weather processes. For the core variables of minimum and maximum temperature and precipitation, a probit normalization is conducted which transforms each quantity into one which is normally distributed with mean 0 and standard deviation 1. In this way, the total spatial and seasonal spectrum of climatological variability is filtered out, leaving a 3-dimensional process of 'normalized weather'. The climatology is contained in the set of parameters which define the probit function. In a second step, a first order autoregressive model is fitted to the normalized weather process which is then, by construction, globally applicable for any time of the year. The determination of probit parameters is achieved, roughly, by a parameterization of climate variability in terms of climate mean. By way of Monte-Carlo simulations, a universal map can be defined which transmits, in a 1-1 way, information between the climate mean and the probit function in such a way that the means of the simulated weather converge statistically, if simulated long enough, to the given climate mean. The simulated variability, however, is generally not preserved. Depending on the specific region and time of the year, C2W exhibits deviations from observed variability, with errors increasing in extreme climates; for most temperate climates, the simulated variability is comparable to the observed. The disaggregation of climatological means is then extended to include various aggregations, such as monthly or seasonal means, by interpreting them as anomalies from the mean. Besides being a simple and handy weather generator, C2W is best applied as a postprocessing scheme for gridded data sets, such as those from General Circulation Models (GCMs) or gridded climate maps. In that way, C2W works as a simple link between GCMs and, for example, dynamic global vegetation models. C2W is available as a Fortran program module.

Disaggregation · Weather generator · Climate change scenarios

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