The selection of the two crop-weather models used in the impact analysis was lo some extent dictated by the spatial resolution of the GISS and BMO climate models. The BMO model has a grid length of approximately 330km, whereas the GISS model uses a grid spacing of 8° latitude by 10° longitude. Given this resolu-tion, there would have been little justification for conducting an impact analysis at the level of an indivi.dual E:uropean country. In order to make maximum use
Impacts of Qimatic Change on West FJu,ropean Agriculture 75
of the meteorological information available in the two climatic change scenarios (i.e. to accentuate the differences in the climatic change projected for different European areas), it was decided that the impact analysis should focus on the whole of the European Community.
This decision imposed some constraints on the selection of crop-weather models, as did model availability. The two models that eventually were chosen typified two fundamentally different approaches - empirical/statistical and sim-ple simulation modeling. Almost all previous impact studies with comparable objectives have concentrated exclusively on the empirical/statistical approach (using linear regression models), often devoting little attention to the statistical problems associated with the use of such models (Haigh, 1977; Katz, 1979).
In this study we sought to analyze possible statistical problems inherent in the linear regression approach, and to make a critical examination of the per-formance of a simple simulation model. Again (as for the case of the GCM selec -tion and scenario development), it must be stressed that the aim was the evaluation of basic-methodological problems associated with the use of such crop-weather models, and not simply the generation of yield change statistics.
The empirical/statistical model chosen was developed by Hanus for predict-ing yields of winter wheat, and is described in detail in an investigation con-ducted by Hanus ( 1978) for the European Community. It consists of a series of linear regression equations, for each of 42 European meteorological stations, using data for the seven months from January to July only. Each equation expresses an empirical relationship (derived using 20-30 years of yield and meteorological data) bet.ween nationally averaged winter wheat yield and the fol-lowing predictor variables:
• mean monthly temperature
• mean monthly maximum temperature
• mean monthly minimum temperature total monthly precipitation
time (the year is incorporated in each regression equation as a vari-able in order to describe the yield trend).
For the Federal Republic of Germany, the Hanus model has been validated with independent yield data over the period 196B-83, and produced an average error of the estimate over this period o:f less than 5% (Hanus, private communication).
The model has not been validated with independent yield data for other Euro-pean countries.
The simulation model employed in the impact analysis was developed by Briggs (1983) during the course of the European Ecological Mapping Project. The model was designed with the objective of evaluating the 'biomass potential' of the European Community - that is, the potential for producing energy from plant biomass. Since the concept of 'biomass potential plays an important role in the subsequent discussion of results, it is useful to present the definition of this term given by Briggs ( 1983):
The potential annual above-ground biomass production (as expressed, for example, in kg/ha/yr} by a standard crop under constant management conditions. This definition is adopted to avoid the short-term effects of differences in soil management procedures {e.g. in fertilizer practice, irrigation, pesticide usage} and cropping practice, and the
longer-term effects of differences in age, successional status, or environmental stability of the existing vegetation cover.
Thus 'biomass polenlial' is an abslract concept, expressing the lheorelically achievable biomass production of a uniform reference crop (in this case, a mixed-species grass sward) under lhe specific clima:lic and edaphic conditions prevailing in a given area (Figure 1)
IL should be emphasized that lhe Briggs model was not developed for the particular purposes of impact analysis. The use of lhe model in such a specific contexl has certain disadvantages. Briefly, these can be summarized as:
validation difficulties, due to the somewhal abstracl nature of biomass potential. and lhe use of a grass reference crop;
simplifications and empiricisms incorporaled in the actual slruclure of the model.
These issues are considered in detail elsewhere (Meinl et al., 1984), but are importanl enough lo deserve some mention here.
One problem encountered in lhe validation of lhe Briggs model relates to the difference between theoretically achievable 'biomass potential' and lhe biomass production actually attained. Such discrepancies are due to the neglect of specific factors in the model - i.e. inputs of fertilizers, the effect of irrigation, and the influence of pests and diseases. The use of grass as a reference crop pro-vides another explanation for possible discrepancies between actual biomass production and 'bi.amass potential'. Europe is not covered uniformly by a grass reference crop, thus making model validation difficult in areas where a mixed-species sward does not occur Briggs ( 1983) has attempted lo validate the model in England and \Vales, using data on grass yields at experimental sites. However, a rigorous validation of the model in other areas of the European Community has not been performed.
The major struclural simplifications in the model relate to the calculalion of actual and potential evapotranspiration, the estimation of available soil water capacity, the :neglect of Hortonian overland !low and rainfall interception by lhe vegetalion cover, and the assumption of a 5 °C threshold for the initialion of grass growth. The major model empiricism involves the use of a Lieth-Eox net primary productivity equation to convert 'effective evapotranspiration' to biomass potential.
This picture must be balanced by mentioning two of the advantages lhat the Briggs model offers the impact analyst. Firstly, it cons:iders differences in the edaphic environment (in terms of available soil water capacily) throughout the European study area. In other words, the capacity of a given area of land to produce plant. biomass is an explicit function of both soil and climatic charac-teristics. In contrast, areal differences in soil characteristics are only implicitly considered in the Hanus model.
Secondly, it would have been beyond the time and financial constraints of this project to attempt to use simulation models for a whole range of vegetation types and/ or crops (even if such models had been available). As Briggs ( 1983) points out, the use of a reference crop is defensible on the grounds that:
Atmospheric energy subsystem