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The Choice of First-Order Impact Models

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Abstract

The quantitative estimation of crop responses to climatic variations is a fundamental requirement for the studies reported in this volume. It is the procedure that translates a climatic perturbation (described by a climatic scenario) into a tangible first-order, biophysical effect (on crop production). Such a result can subsequently be used to evaluate further higher-order effects on agriculture and the wider economy. The quantitative tools that are used to evaluate the influence of climate on crops are termed agroclimatic models.

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References

  • Baier, W. (1977). Crop-weather models and their use in yield assessments. WMO Technical Note No. 151 ,World Meteorological Organization, Geneva, 48 pp.

    Google Scholar 

  • Baier, W. (1982). Agroclimatic modeling: An overview. In D.F. Cusack (ed.), Agroclimatic Information for Development: Reviving the Green Revolution ,Westview, Boulder, Colorado, pp. 57–82.

    Google Scholar 

  • Biswas, A.K. (1980). Crop-climate models: A review of the state of the art. In J. Ausubel and A. Biswas (eds.), Climatic Constraints and Human Activities ,Volume 10, IIASA Proceedings Series, Pergamon, Oxford, pp. 75–92.

    Google Scholar 

  • Draper, N. and Smith, H. (1981). Applied Regression Analysis. 2nd Edition, Wiley, New York.

    Google Scholar 

  • Duckham, A.N. (1963). The Farming Year. Chatto and Windus, London.

    Google Scholar 

  • FAO (1978). Crop Calendars. FAO Plant Production and Protection Paper No. 12, Food and Agriculture Organization, Rome.

    Google Scholar 

  • Katz, R.W. (1979). Sensitivity analysis of statistical crop-weather models. Agric. Meteorol. ,20, 291–300.

    Article  Google Scholar 

  • Lyons, T.C. (1982). Deterministic models for the ecological simulation of crop agricultural environments. In G. Golubev and I. Shvytov (eds.), Modeling Agricultural-Environmental Processes in Crop Production ,IIASA Collaborative Proceedings Series, CP-82-S5, International Institute for Applied Systems Analysis, Laxen burg, Austria.

    Google Scholar 

  • Nix, H.A. (1985). Agriculture. In R.W. Kates, J.H. Ausubel and M. Berberian (eds.), Climate Impact Assessment: Studies of the Interaction of Climate and Society ,SCOPE 27, Wiley, Chichester, pp. 105–130.

    Google Scholar 

  • Parry, M.L. and Carter, T.R. (eds.), (1984). Assessing the Impact of Climatic Change in Cold Regions. Summary Report, SR-84–1, International Institute for Applied Systems Analysis, Laxenburg, Austria.

    Google Scholar 

  • Robertson, G.W. (ed.), (1983). Guidelines on Crop-Weather Models. Task Force on Crop-Weather Models, World Meteorological Organization, Geneva.

    Google Scholar 

  • Rosenberg, N.J. (1982). The increasing CO2 concentration in the atmosphere and its implication on agricultural productivity. II. Effects through CO2-induced climatic change. Climatic Change ,4, 239–254.

    Google Scholar 

  • Sakamoto, C.M. (1981). Climate-crop regression yield model: An appraisal. In A. Berg (ed.), Application of Remote Sensing to Agricultural Production Forecasting ,Balkema, Rotterdam, pp. 131–138.

    Google Scholar 

  • Thorn, H.C.S. (1954a). The rational relationship between heating degree days and temperature. Mon. Wea. Rev. ,82, 1–6.

    Article  Google Scholar 

  • Thom, H.C.S. (1954b). Normal degree days below any base. Mon. Wea. Rev. ,82, 111–115.

    Article  Google Scholar 

  • Warrick, R.A. and Gifford, R.M., with Parry, M.L. (1986). CO2, climatic change and agriculture. Assessing the response of food crops to the direct effects of increased CO2 and climatic change. In B. Bolin, B.R. Döös, J. Jäger and R.A. Warrick (eds.), The Greenhouse Effect, Climatic Change, and Ecosystems ,SCOPE 29, Wiley, Chichester, pp. 393–473.

    Google Scholar 

  • WMO (1985). Report of the WMO/UNEP/ICSU-SCOPE Expert Meeting on the Reliability of Crop-Climate Models for Assessing the Impacts of Climatic Change and Variability ,WCP-90, World Meteorological Organization, Geneva, 31 pp.

    Google Scholar 

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© 1988 International Institute for Applied Systems Analysis and United Nations Environment Program

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Carter, T., Konijn, N., Watts, R. (1988). The Choice of First-Order Impact Models. In: Parry, M.L., Carter, T.R., Konijn, N.T. (eds) The Impact of Climatic Variations on Agriculture. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-2943-2_2

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  • DOI: https://doi.org/10.1007/978-94-009-2943-2_2

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-277-2701-5

  • Online ISBN: 978-94-009-2943-2

  • eBook Packages: Springer Book Archive

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