The preceding discussion has addressed a n u m b e r of questions concerning agroclimatic models and t h e i r applicability in climate impact analysis. Table 3 is an attempt t o fit together some of these points in t h e form of a model checklist.
This allows u s t o make o u r own assessment of a particular model on t h e basis of its component p a r t s a n d its operation.
5.1. Model Components
Three classes of model components are depicted:
a) h t a inputs
-
a list of variables which can be input directly although some may be derived internally by t h e model. These can be natural or anthropo- genic inputs.Table 3. An agroclimatic model checklist.
b) S U e q e c i f i c a t w n s -indicating whether a model is site- o r area-specific (if it is not, s e e 5.2.c).
c ) &rived o u t p u t s
-
ranging from suitability indices t o detailed crop yield com- ponents.5.2. Model Operation
We have identified t h r e e f e a t u r e s important in running a model:
a) S m d a t i o n of p r e s e n t - d a y conditions
-
indicating t h e time-step used dur- ing t h e growing season, w h e t h e r variables a r e updated from y e a r t o year, and t h e capability for responding t o sporadic events s u c h as frosts, floods.etc.
b) S m d a t i o n of c l i m a t i c change
-
whether this is modeled a s a step-like change of m e a n values or of a distribution of values; o r a s a transient change of t h e m e a n or of a drstribution.c) Response option -indicating whether it is possible t o adjust model inputs i.e. t o s i m u l a t e t h e choices of response t h a t a farmer m i g h t face.
In general, t h e s c h e m e a t t e m p t s t o include First those variables t h a t a r e m o r e commonly modeled, so t h a t t h e incorporation of variables towards t h e bottom of e a c h list indicates a n increased level of model sophistication. Like- wise, entries towards t h e r i g h t of t h e tableau indicate a m o r e detailed, higher resolution simulation capability.
In t h i s paper we have a t t e m p t e d t o outline some of t h e techniques t h a t can be employed t o assess t h e i m p a c t of climatic change on crop production.
We have proceeded from t h e premise (for which we p r e s e n t n u m e r o u s support- ing examples) t h a t fluctuations in c l i m a t e can induce significant biophysical responses in agricultural crops, affecting both t h e quality a n d quantity of t h e hamestable product.
I t
is is t h e s e "first-order" responses t o climate t h a t form t h e focus of o u r discussion, b u t clearly these may c o n s t i t u t e only t h e initial link in a chain of economic a n d social repercussions cascading through t h e farming system and beyond.There exists a broad s p e c t r u m of approaches for examining first-order crop responses t o climatic variations, which we have grouped u n d e r t h e head- ing of agroclimatic models. Each h a s been developed t o reflect certain features of t h e c r o p production system, a system t h a t we have characterized in t h e f o r m of a farm calendar. B e have stressed t h a t m o s t agroclimatic models were developed with a contemporary application in mind. The evaluation of crop responses t o climatic change, particularly longer-term changes of an amplitude lying well outside t h e p r e s e n t range, introduces new dimensions of complexity t o t h e modeling procedure. This merely s e r v e s t o spotlight t h e importance of detailed a n d thorough sensitivity testing a n d validation of models. Without t h e s e , and bearing in mind t h e inevitable uncertainties asso- ciated with e a c h s t a g e of t h e climate impact "cascade", t h e credibility a t t a c h e d t o e s t i m a t e s of crop response could be cast in serious doubt.
From t h e r e s u l t s of t h e two sensitivity experiments, we have illustrated how:
a)
I t
may not be necessary to operate models a t t h e most detailed (and costly) time resolution if satisfactory results can be obtained using a longer time-step.b) The short-term response of crops to a particular climatic anomaly may be quite different to t h e response over a longer period.
Finally, we have presented a method of assessing an agroclimatic model, by means of a checklist. As well as incorporating traditional model characteris- tics, the checklist also considers how a model handles climatic change and whether input variables can be adjusted t o represent possible farming responses to this change.
Baier, W.: 1981. 'Crop-weather analysis models' in k Berg (ed.), Application of Remote Sensing t o A g r i c d t u d h o d u c t i o n F o ~ e c a s t i n g , A A Balkema, Rotter- dam, pp. 105-118.
Baier, W.: 1982, 'Agroclimatic modeling: An overview' in D.F. Cusack (ed.), &o- c l i m a t i c
hf
o r m a t i o n f OT Development: Reviving the Oreen Revolution, West- view, Boulder, Colorado, pp. 57-82.Bergthorsson, P.: 1985, 'Sensitivity of Icelandic agriculture t o climatic variations' i n aim& C R a q e , ?(I) Special Issue: The Sensitivity of Natural Ecosystems and Agriculture t o Climatic Change, pp. 111-127 (in the press).
Biswas, AK.: 1980, 'Crop-climate models: A review of the state of the a r t ' in J. Ausu- be1 and AK. Biswas (eds.), Climatic C o n s t ~ a i n f s and Human Activities, Per- gamon Press, Oxford, pp. 75-92. IIASA Proceedings Series, No. 10.
Brooks, C.E.P.: 1943, 'Interpolation tables for daily values of meteorological ele- ments'. @ad. J. R. Met. S c . 69, 160-162.
Duckham, AN.: 1963, ?he Fhnning Y e w , Chatto and Windus, London.
Emanuel, W.R., H.H. Shugart, a n d
M.P.
Stevenson: 1985, 'Climate change and the broad scale distribution of terrestrial ecosystem complexes' in airnutic Change, 7(1) Special Issue: The Sensitivity of Natural Ecosystems and Agricul- t u r e to Climatic Change, pp. 29-43 (in the press).FAO: 1978, Ctop C a l e n d a ~ s , FA0 Plant Production and Protection Paper No. 12, Food and Agriculture Organization, Rome, Italy.
Hansen, J., A. Lacis, D. Rind, G. Russell. P. Stone, I. Fung, R. Ruedy, and J. Lerner:
1984, 'Climate sensitivity: Analysis of feedback mechanisms' in J.E. Hansen and T. Takahashi (eds.), CLzmale h o c e s s e s a n d Climate Sensitivity, Geophysical Monograph No. 29, American Geophysical Union, Washington,
D.C.,
pp. 130-163.Holdridge, L.R: 1947, 'Determination of world plant formations from simple climatic data', .%ence, N.Y. 105, 367-368.
Katz, R.W.: 1979. 'Sensitivity analysis of statistical c r o p w e a t h e r models'. &ric.
Met e o r o l . 20, 291-300.
Konijn, N.: 1984, 'A crop production and environment model for long-term conse- quences of agricultural production', IIASA Working k p e r WP-84-52, Interna- tional Institute for Applied Systems Analysis, Laxenburg. Austria.
Koppen, W.: 1936, 'Das Geographische System der Klimate' in W. K6ppen a n d
C.
Geiger, H a n d b u c h d e r K l i m a t o l o g i e 1 , Purt C, BorntrGger, Berlin.
Lorenz,
E.N.:
1968, 'Climatic Determinism', Meteor. Monographs 8(30), 1-3.Lyons, T.C.: 1982, 'Deterministic models for t h e ecological simulation of crop agri- cultural environments' in G. Golubev and 1. Shvytov (eds.), Modeling Agricultural-Environmental Processes in Crop Production, LlASA Collaborative P r o c e e d i n g s Series CP-82-S5, International Institute for Applied Systems Analysis, Laxenburg, Austria.
Mearns, L.O., R.W. Katz, and S.H. Schneider: 1984, 'Changes in the probabilities of extreme high temperature events with changes in global mean temperature'.
Parry, M.L.: 1978, C l i m a t i c C h a n g e , A g r i c u l t u r e a n d S e t t l e m e n t , Dawson, Folkestone.
Pitovranov. S., S. Pegov, and P. Homiakov: 1984, 'Modeling the impact of climatic change on regional ecosystems', IIASA C o l l a b o r a t i v e P u p e r CP-84-7, Interna- tional Institute for Applied Systems Analysis, Laxenburg, Austria.
Richardson, C.W.: 1981, 'Stochastic simulation of daily precipitation, t e m p e r a t u r e and solar radiation', Water R e s o u r c e s R e s e a r c h 17(1), 182-190.
Robertson, G.W. ( e d ) : 1983, W e l i n e s o n c r o p - w e a t h e r m o d e l s , Task Force on Crop-Weather Models, World Meteorological Organization, Geneva.
Rosenberg, N.J.: 1981, 'The increasing COZ concentration in the atmosphere and its implication on agricultural productiv~ty. 1. Effects on photosynthesis, t r a n - spiration and water use efficiency'. Climatic Change 3, 265-279.
Rosenberg,
N.J.:
1982, 'The increasing CO concentration in t h e atmosphere and its implication on agricultural produc%ivity. 11. Effects through C02-induced climatic change', Ceimafic Change 4, 239-254.Sakarnoto, C.M.: 1981, 'Climate-crop regression yield model: An appraisal' in k Berg (ed), AppLicdimL of R e m o t e Sensing t o &ricdtural Reduction f i r e c a s t i n g , AA. Balkema, Rotterdam, pp. 131-138.
Stewart,
R.:
Forthcoming, 'The impact of climate change on spring wheat produc- tion in Saskatchewan' in A s s e s s m e n t o f Ceimate I m p a c t s o n A g r i c u l t u r e , V o l u m e I ,h
Efigh L a t i t u d e R e g i o n s , Reidel, Dordrecht, t h e Netherlands.Waggoner, P.E.: 1983, 'Agriculture and a climate changed by more carbon dioxide' in National Research Council, Changing C l i m a t e , National Academy Press, Wash- ington, D.C.. pp. 383-418.
Watts,
R.G.:
1984, 'Predicting changes in crop yield due to C02-induced climatic change-
some cautionary comments', IIRSA Working h p e r H'P-84-15, Inter- national lnstitute for Applied Systems Analysis, Laxenburg, Austria.Wigley, T.M.L: 1984, 'The role of statistics in climate impact analysis', Proceedings of the Second International Meeting on Statistical Climatology, 26-30 Sep- tember, 1983, Lisbon, Portugal.