By Joseph Alcamo (auth.), Joseph Alcamo, Jerzy Bartnicki (eds.)
AND CONCLUSIONS OF THE WARSAW II assembly ON ATMOSPHERIC COMPUTATIONS to evaluate ACIDIFICATION IN EUROPE JOSEPH ALCAMO and JERZY BARTNICKI overseas Institute for utilized structures research Schlossplatz 1, A-2361 Laxenburg, Austria (Received June 1, 1988; revised June 20, 1988) summary. 3 issues are mentioned during this record: sensitivity/uncertainty research of lengthy diversity shipping types, the interface among atmospheric versions of other scales, and linkage among atmospheric and ecological types. In separate analyses oflong diversity shipping types, it was once came across that uncertainty of annual S deposition used to be typically tormented by uncertainty of wind pace, blending top and rainy deposition parameterization. doubtful parameters jointly brought on S deposition blunders of round 10-25% (coefficient of version) within the versions tested. The impact of interannual meteorological variability on computed annual S deposition was once particularly small. varied equipment have been offered for combining types of local and interregional scale. It was once stumbled on to be extra very important to incorporate interregional info in regional-scale versions for annual computations in comparison to episodic computations. a number of linkage difficulties have been famous among atmospheric and ecological types. The vertical distribution of toxins and 'forest fittering' of pollutant deposition have been chanced on to be very important in ecological effect calculations yet missing within the output of such a lot interregional atmospheric models.
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41, 427. Tilden, J. W. and Seinfeld, J. : 1982, Atmos. Envir. 16, 357. : 1983, Z. Meteorol. 33, 355. : 1985, Z. Meteorol. 35, 340. APPLICATION OF THE 'FAST'-METHOD TO A LONG TERM INTERREGIONAL AIR POLLUTION MODEL W. KLUG and B. G. (Received November 17, 1987; revised May 24, 1988) Abstract. The Fourier Amplitude Sensitivity Test (FAST) is applied to an interregional Air Pollution Model which simulates S02/S04-concentrations and -depositions as an annual average. The results are discussed and problems connected with the application of the FAST-method are reported.
The FAST method requires frequency distribution of model parameters as input data and provides the following results: (i) mean value of the model output, (ii) variance of the model output which characterizes the parameter uncertainty of the model, and (iii) partial variances of the model output which are the measures of the model sensitivity to uncertainties in individual input parameters. A mathematical formulation of the FAST method and approximations used in its computer implementation is presented.
1982) are listed in Table I together with the minimum number of model solutions r required for calculation of partial variances. The number r determined by condition (20) with N = 2 depends on the assumed frequency set and strongly grows with the number of input parameters m to be analyzed. However, for small m the number of model solutions determined in this way may appear to be too low in the presented application. Namely, if evaluation of output frequency distribution is desired the number r should be choosen high enough to obtain a set of model solutions sufficiently numerous for statistical analysis.