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Titlebook: Atmospheric Computations to Assess Acidification in Europe; Summary and Conclusi Joseph Alcamo,Jerzy Bartnicki Book 1989 Kluwer Academic Pu

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期刊全稱Atmospheric Computations to Assess Acidification in Europe
期刊簡(jiǎn)稱Summary and Conclusi
影響因子2023Joseph Alcamo,Jerzy Bartnicki
視頻videohttp://file.papertrans.cn/165/164613/164613.mp4
圖書封面Titlebook: Atmospheric Computations to Assess Acidification in Europe; Summary and Conclusi Joseph Alcamo,Jerzy Bartnicki Book 1989 Kluwer Academic Pu
影響因子AND CONCLUSIONS OF THE WARSAW II MEETING ON ATMOSPHERIC COMPUTATIONS TO ASSESS ACIDIFICATION IN EUROPE JOSEPH ALCAMO and JERZY BARTNICKI International Institute for Applied Systems Analysis Schlossplatz 1, A-2361 Laxenburg, Austria (Received June 1, 1988; revised June 20, 1988) Abstract. Three topics are discussed in this report: sensitivity/uncertainty analysis of long range transport models, the interface between atmospheric models of different scales, and linkage between atmospheric and ecological models. In separate analyses oflong range transport models, it was found that uncertainty of annual S deposition was mostly affected by uncertainty of wind velocity, mixing height and wet deposition parameterization. Uncertain parameters collectively caused S deposition errors of around 10-25% (coefficient of variation) in the models examined. The effect of interannual meteorological variability on computed annual S deposition was relatively small. Different methods were presented for combining models of regional and interregional scale. It was found to be more important to include interregional information in regional-scale models for annual computations compared to episodic computati
Pindex Book 1989
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978-94-010-6904-5Kluwer Academic Publishers 1989
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Timed und stochastische Petri-Netze,e 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
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https://doi.org/10.1007/978-3-642-83801-9 of ‘coarse’ boundary values (provided by a coarse-grid model) in the fine-grid model is discussed theoretically and demonstrated by test calculations. It turns out that one should always prefer applying coarse information about external (with respect to the fine-grid model) sources to ignoring them
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https://doi.org/10.1007/978-3-642-83801-9t runs on a personal computer (RCDM) using an extended period of wind and precipitation data. The variability in historical temperature and precipitation data has been analyzed to assess the representativeness of the limited meteorological period used in the EMEP model (1978–1982). A match-up betwee
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Funktionale Grammatik und Sprachbeschreibunger the same period. The basis for classifying different types of atmospheric circulation or large-scale weather paterns [commonly known as Grosswettertypes (GWT-s) or Grosswetterlagen (GWL-n)] is the identification of the position of centers of cyclones, ridges and troughs. The linear regression bet
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