CONCLUSIONS

1. Czech Republic POSTER: XY 0229 This study was conducted with support of the Czech National Agency for the Agricultural Research (project QG60051), 6th FP EU project Adagio (Adaptation of Agriculture in European Regions at Environmental Risk under Climate Change) SSPE-CT-2006-044210 and the research plan No. MSM6215648905 “Biological and technological aspects of sustainability of controlled ecosystems...“. Projection of uncertainties of the climate change scenarios into the estimates of future agrometeorological conditions and crop yields?M. Trnka (1,2), M. Dubrovský (1,2), P. Hlavinka (1), D. Semerádová (1,2), P. Štěpánek (3), J.Eitzinger (4), H. Formayer (4), Z. Žalud (1,2)1) Institute of Agrosystems and Bioclimatology, Mendel University of Agriculture and Forestry, Brno, Czech Republic, mirek_trnka@yahoo.com (2) Institute of Atmospheric Physics, Czech Academy of Sciences, Prague(3) Czech Hydrometeorological Institute, Czech Republic (4) Institute for Meteorology, University of Natural Resources and Applied Life Sciences (BOKU), Vienna, Austria Cold region Warm region References: with the authors AIMS RESULTS • To analyze sources of uncertainty in the estimates of future cereal productivity in the Central Europe with the focus on role of the emission scenarios (SRES), climate sensitivity and global circulation models (GCM). • To take into account the effects of the carbon dioxide concentration on the crop productivity as well as the factor of the scale for which the results are integrated. • To estimate the expected impact of the climate change on the future cereal productivity as well as on the overall agroclimatic conditions in the area. STUDY AREA STEPS OF THE STUDY Changes in the phenology The study region is centered in the Czech Republic but part of the analysis included also north-east part of Austria. In total 129 weather stations were available together with detail soil and land-use information. Figure 7: Mean maturity date of wheat under the present climate compared with the expected maturity date by 2050 (SRES A2 – high climate sensitivity). The maps document high uncertainty caused by the differences between three used GCMs. The differences between the GCMs are even more obvious when we compare the intra-model variability in the sowing date. The weather patterns in HadCM are characterized by high temperature increases leading to shorter developmental time. The NCAR model estimates higher precipitation during spring combined with decrease of solar radiation, which results into event longer developmental time than under the present climate. Figure 6: Mean sowing date of winter wheat under present climate compared with the expected sowing dates by 2050 (SRES A2 – high climate sensitivity). The Figure documents high uncertainty caused by the differences between three used GCMs. The weather conditions based on the HadCM are characterized by much higher soil temperature during August and September while NCAR model estimated significantly lower precipitation during September and October (Fig 5). Both projections are conducive to latter sowing dates. Figure 1:. Overview of the area orography and location of weather stations used in the study. Indirect effect of climate change – CO2 influence not accounted for Changes in the yield SPATIAL ANALYSIS CROP MODEL EVALUATION Comined effect of climate change – CO2 influence accounted for Figure 8: Estimated impact of climate change on the winter wheat yields in the Czech Republic. The figures show two main sources of uncertainties in the analysis i.e. differences between individual GCM and also the effect of CO2 which is responsible for the largest portion of the uncertainty. In the CERES models increase of the ambient CO2 concentration leads to 9-10% yield increase per 100 ppm increase of CO2 (under the Central European climate conditions). However the magnitude of the increase remains to be confirmed by ongoing FACE experiments. Figure :9 Uncertainty in the climate change impacts on the example of wheat yields for time frames centered around 2020 and 2050. The uncertainty is given by the differences in the used SRES scenario and climate sensitivity. The top maps represent model runs for SRES A2 and high climate sensitivity. The bottom maps represent simulation for SRES B1 and low climate sensitivity. Maps depict yield deviation from 1961-1990 means. PRESENT Figure 2:. Results of the CERES-Wheat and CERES-Barley simulations compared with the observed values. Figure 3. Methodology of the spatial analysis showing applied digital elevation model, weather stations, soil and land-use maps. Uncertainty of the scale Changes of the overall agro-climatic condtions SRES & SENSITIVITY GCM SELECTION Figure 11: Distribution of the production region under the present climate (above) based on 1961-1990 climate conditions. On the right: Estimated area of the production regions according under expected climate conditions for the time slice centered around 2020 (a,c,e) and 2050 (b,d,f). The Figures a) and b) are based on the HadCM SRES B1 with low climate sensitivity; the figures c) and d) on the HadCM SRES A2 with high climate sensitivity and the figures e) and f) are based on the NCAR SRES A2 with high climate sensitivity Figure 10: Estimated impact of climate change on the crop yields in 77 administrative districts (see Fig. 3. Landuse and stat. Data ) and the whole territory as a function of different SRES scenarios (top) and GCM (bottom). The regions are ordered according to the mean air temperature in the district under the present climate. QUESTIONS? • CONCLUSIONS • The range of uncertainty caused by the different projections within the set of used GCM is relatively large and is most pronounced in case of A2 SRES scenario in combination with the high climate system sensitivity. • Overall uncertainty of the estimates of the future cereal productivity is rather high (larger than 20% between individual GCM for 2050) and becomes even higher in case of spring cereals (compared to winter cereals).. • The effect of uncertainty within the available set of GCM-SRES-CS on the future national production levels is of the same magnitude as the effect of sub-regional differences. The overall uncertainty decreases with the level of integration. • The sensitivity of agrometeorological indicators to SRES-GCM-CS combination showed similar patterns as crop yields and some aspects of these changes especially their speed should be a reason for concern. MIROSLAV TRNKA mirek_trnka@yahoo.com Figure 5:. Expected changes of global radiation (SRAD), mean tempearture (TAVG) and precipitation (PREC) according to SRES A2 and SRES B1 at 2050 for the Czech Rep. Figure 4:. Dynamics of CO2 increase and sensitivity of the climate system to this change.