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Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E. |
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Title |
Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century |
Type |
Journal Article |
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Year |
2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
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Volume |
134 |
Issue  |
1-2 |
Pages |
283-297 |
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Keywords |
regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes |
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Abstract |
Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management. |
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2016-10-31 |
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0165-0009 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4805 |
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Author |
Elsgaard, L.; Børgesen, C.D.; Olesen, J.E.; Siebert, S.; Ewert, F.; Peltonen-Sainio, P.; Rötter, R.P.; Skjelvåg, A.O. |
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Title |
Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe |
Type |
Journal Article |
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Year |
2012 |
Publication |
Food Additives & Contaminants: Part A |
Abbreviated Journal |
Food Addit. Contam. Part A |
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Volume |
29 |
Issue |
10 |
Pages |
1514-1526 |
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Keywords |
Agriculture/*economics/trends; Animals; Avena/chemistry/economics/*growth & development/microbiology; *Climate Change/economics; Crops, Agricultural/chemistry/economics/*growth & development/microbiology; Europe; *Food Safety; Forecasting/methods; Fungi/growth & development/metabolism; Humans; Models, Biological; Models, Economic; Mycotoxins/analysis/biosynthesis; Soil Pollutants/adverse effects/analysis; Spatio-Temporal Analysis; Triticum/chemistry/economics/*growth & development/microbiology; Uncertainty; Weather; Zea mays/chemistry/economics/*growth & development/microbiology |
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Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops. |
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1944-0049 1944-0057 |
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CropM |
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MA @ admin @ |
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4585 |
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Author |
Stratonovitch, P.; Semenov, M.A. |
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Title |
Heat tolerance around flowering in wheat identified as a key trait for increased yield potential in Europe under climate change |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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Volume |
66 |
Issue |
12 |
Pages |
3599-3609 |
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Keywords |
Adaptation, Physiological; *Climate Change; Computer Simulation; Europe; Flowers/*physiology; *Hot Temperature; *Quantitative Trait, Heritable; Time Factors; Triticum/*growth & development/*physiology; Downscaling; LARS-WG weather generator; Sirius wheat model.; heat stress; ideotype design; impact assessment |
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Abstract |
To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Projected climatic and environmental changes emphasize the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost, and drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, the Sirius wheat model was refined by incorporating the effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number, and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. The model was used to optimize wheat ideotypes for CMIP5-based climate scenarios for 2050 at six sites in Europe with diverse climates. The yield potential for heat-tolerant ideotypes can be substantially increased in the future (e.g. by 80% at Seville, 100% at Debrecen) compared with the current cultivars by selecting an optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, at two sites, Seville and Debrecen, the grain yields of heat-sensitive ideotypes were substantially lower (by 54% and 16%) and more variable compared with heat-tolerant ideotypes, because the extended grain filling required for the increased yield potential was in conflict with episodes of high temperature during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future. |
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0022-0957 1460-2431 |
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CropM, ft_macsur |
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MA @ admin @ |
Serial |
4578 |
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Author |
Żarski, J.; Dudek, S.; Kuśmierek-Tomaszewska, R.; Bojar, W.; Knopik, L.; Żarski, W. |
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Title |
Agroklimatologiczna ocena opadów atmosferycznych okresu wegetacyjnego w rejonie Bydgoszczy (Agro-climatological assessment of the growing season rainfall in the Bydgoszcz region) |
Type |
Journal Article |
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Year |
2014 |
Publication |
Infrastruktura i Ekologia Terenów Wiejskich (Infrastructure and Ecology of Rural Areas) |
Abbreviated Journal |
Infrastruktura i Ekologia Terenów Wiejskich (Infrastructure and Ecology of Rural Areas) |
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Volume |
Ii |
Issue |
3 |
Pages |
643-656 |
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Keywords |
rainfall; growing season; Bydgoszcz region; weather-yield model |
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Abstract |
The aim of the research was an agro-climatologic assessment of the amount of rainfall on a local scale, mainly aimed to identify trends in their changes and a possible rise in their variability over time. In the studies also we wanted to demonstrate the impact of the amount of rainfall in the region of Bydgoszcz on the yield of some crops. Material for the study consists of rainfall measurements, carried out in a stand- ard way in the years 1981-2010 at the Research Station of the University of Technology and Life Sciences in Bydgoszcz. Station is located in the village of Mochle, located approximately 20 km from the city centre (φ=53013’ N, λ=17051’E, h=98.5 m above sea level) in sparsely urbanized and industrialized area. We also used data of the yield of selected crops (potato, barley, corn for grain, legumes), from the production in the region of Kujawy and Pomorze as well as from our own experimental field. It has been shown that the average long-term rainfall during the growing season allows for classifying Bydgoszcz region as the area with the lowest rainfall in Poland. Analyzed rainfalls were characterized by a very high variability in time, resulting in climatic risk of plant growing. The largest temporal variability related to August. However, there was no extension of the time variability of rainfall totals in the period 1996-2010, as compared to the period 1981-1995. The sole significant growth trend during the period 1981-2010 was found in May. It appeared a tendency to a decline in summer rainfall totals (VI-VIII) in the annual rainfall total, which is consistent with the IPCC projections. Rainfall totals had highly signi cant impact on yields of selected crops. The highest correlation coefficients were found in relations crop-rainfall in the months of increased water needs of plants. Better correlations rainfall-crop were found using data from the production scale as compared with the scale of experimental field. |
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Polish |
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CropM, ft_macsur |
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MA @ admin @ |
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4643 |
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Author |
Dumont, B.; Leemans, V.; Ferrandis, S.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Assessing the potential of an algorithm based on mean climatic data to predict wheat yield |
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Journal Article |
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Year |
2014 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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Volume |
15 |
Issue |
3 |
Pages |
255-272 |
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Keywords |
stics model; yield prediction; real-time; proxy-sensing; stochastic weather generator; crop yield; mediterranean environment; simulation-model; variability; nitrogen; ensembles; forecasts; demeter; europe |
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Abstract |
The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days. |
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1385-2256 1573-1618 |
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CropM |
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MA @ admin @ |
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4621 |
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