We approximated the influence of global climate change on the energy consumption of maize by a simulation model in Keszthely, referring to the average July weather. The period of 1961–1990 was considered as the basic run. We quantified the changes of the close past on the basis of the decade between 1997 and 2006. The other 6 scenarios were elaborated on the one hand by downscaling the IPCC (2007) report (A2 and B2), on the other hand by taking into account a more serious weather change. At determining plant and soil characteristics of the individual scenarios we applied the principle of analogy being extensively used in meteorological practice; in this method we selected the values of that year from the observation data series of almost 30 years that were the closest to the year to be simulated. The ratio of latent heat decreased by 4.8% only at doubling CO2 concentration. The largest difference in the ratio of sensible and latent heat was in the case of the run containing the highest warming up and largest precipitation decrease, where the ratio of latent heat increased by 8.8%.
One of the causes of global warming is the raised CO2 concentration narrowed the stoma openings by 14.3% in itself; it is the quantified value of the positive impact of global warming on plant evaporation, referring to Keszthely. Warming up over 6 °C raised the latent heat compared to the basic run in a statistically justifiable way in the case of each scenario; according to this, in Keszthely, assuming an average July, even in the case of a temperature rise of 6 °C there are some humidity reserves that can be used for transpiration by maize plant. Precipitation loss of 30% associated with warming up of 9 °C, however, reduced this reserve to a minimum. In our opinion, water seems to be the bottleneck of the future; farmers have to prepare to face the lack of water, even in the case if nowadays the forecast of precipitation changes is rather volatile.
Anda, A. 2006. Modeling maize response to climate modification in Hungary. Commun. Biometry Crop Sci. 1(2):90–98.
Bartholy, J., Pongrácz, R., Gelybó, Gy. 2007. Regional climate change in Hungary for 2071–2100. Applied Ecology and Environment Research 5:1–17.
Goudriaan, J., van Laar, H.H. 1994. Modelling Potential Crop Growth Processes. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 58–67.
IPCC 2007. Summary for Policymakers. In: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, H.L., Miller, G. (eds), Climate Change — The Physical Science Basis. Contribution of Working Group I. to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p. 254.
Jackson, R.B., Sala, O.E., Field, C.B., Mooney, H.A. 1994. CO2 alters water use, carbon gain, and yield for dominant species in a natural grassland. Oecologia 98:257–262.
Long, S.P., Answorth, E.A., Leakey, A.D.B., Donald, J.N., Ort, R. 2006. Food for thought: Lower-than-expected crop yield stimulation with rising CO2 concentrations. Science 30:1918–1921.
Mika, J. 2007. Regionális éghajlati forgatókőnyvek előkészítése statisztikus módszerekkel (Preparation of climatic scenarios by using statistical methods). DSc Thesis, Budapest
Mera, R.J., Niyogi, D., Buol, G.S., Wilkerson, G.G., Semazzi, F.H.M. 2006. Potential individual versus simultaneous climate change effects on soybean (C3) and maize (C4) crops: an agrotechnology model based study. Global and Planetary Change 54:163–182.
STATA 5.0 (1996) Stata Corporation LP Texas, USA. Available online: www.stata.com
Van de Geijn, S.C., Goudriaan, J. 1996. The effects of elevated CO2 and temperature change on transpiration and crop water use. In: Bazzaz, F., Sombroek, W. (eds), Global Climate Change and Agricultural Production. FAO and John Wiley & Sons, New York, pp. 101–122.
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Dióssy, L., Anda, A. Energy Based Approach of Local Influence of Global Climate Change in Maize Stand. CEREAL RESEARCH COMMUNICATIONS 36, 591–600 (2008). https://doi.org/10.1556/CRC.36.2008.4.8
- sensible heat
- latent heat
- simulation model