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Heinke, J., Ostberg, S., Schaphoff, S., Frieler, K., Müller, C., Gerten, D., et al. (2013). A new climate dataset for systematic assessments of climate change impacts as a function of global warming. Geosci. Model Dev., 6(5), 1689–1703.
Abstract: In the ongoing political debate on climate change, global mean temperature change (Delta T-glob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of Delta T-glob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of Delta T-glob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere-Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs’ climate change properties, even though they, necessarily, utilise a simplified relationships between Delta T-glob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.
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Sanz-Cobena, A., Lassaletta, L., Gamier, J., Smith, P., Sanz-Cobena, A., Lassaletta, L., et al. (2017). Mitigation and quantification of greenhouse gas emissions in Mediterranean cropping systems. Agriculture, Ecosystems & Environment, 238, 1–4.
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Trnka, M., Feng, S., Semenov, M. A., Olesen, J. E., Kersebaum, K. C., Roetter, R. P., et al. (2019). Mitigation efforts will not fully alleviate the increase in water scarcity occurrence probability in wheat-producing areas. Sci. Adv., 5(9), eaau2406.
Abstract: Global warming is expected to increase the frequency and intensity of severe water scarcity (SWS) events, which negatively affect rain-fed crops such as wheat, a key source of calories and protein for humans. Here, we develop a method to simultaneously quantify SWS over the world’s entire wheat-growing area and calculate the probabilities of multiple/sequential SWS events for baseline and future climates. Our projections show that, without climate change mitigation (representative concentration pathway 8.5), up to 60% of the current wheat-growing area will face simultaneous SWS events by the end of this century, compared to 15% today. Climate change stabilization in line with the Paris Agreement would substantially reduce the negative effects, but they would still double between 2041 and 2070 compared to current conditions. Future assessments of production shocks in food security should explicitly include the risk of severe, prolonged, and near- simultaneous droughts across key world wheat-producing areas.
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Gabaldón-Leal, C., Lorite, I. J., Mínguez, M. I., Lizaso, J. I., Dosio, A., Sanchez, E., et al. (2015). Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain. Clim. Res., 65, 159–173.
Abstract: Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme T-max damages in all locations, with the exception of Granada, where losses were limited to 8%.
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Graß, R., Thies, B., Kersebaum, K. - C., & Wachendorf, M. (2015). Simulating dry matter yield of two cropping systems with the simulation model HERMES to evaluate impact of future climate change. European Journal of Agronomy, 70, 1–10.
Abstract: Regionalized model calculations showed increased rainfall and temperatures in winter and less precipitation and higher temperatures in summer due to climate change effects in the future for numerous countries in the northern hemisphere. Furthermore, model simulations predicted enhanced weather variability with an increased risk of yield losses and reduced yield stability. Recently, double cropping systems (DCS) were suggested as an environmental friendly and productive adaptation strategy with increased yield stability. This paper reviews the potential benefit of four DCS (rye (Secale cereale L.) as first crop and maize (Zea mays L.), sunflower (Helianthus annuus L.), sorghum (Sorghum sudanense L. x Sorghum bicolor L.) and sudan grass (S. sudanense L.) as second crops) in comparison with four conventional sole cropping systems (SCS) (maize, sunflower, sorghum and sudan grass) with regard to dry matter (DM) yield and soil water under conditions of climate change. We used the agro-ecosystem model HERMES for simulating these variables until the year 2100. The investigated crops sunflower, sorghum and sudan grass were parameterised first for HERMES achieving a satisfying performance. Results showed always higher DM yields per year of DCS compared with SCS. This was mainly caused by yield increases of the first crop winter rye harvested at the stage of milk ripeness. As a winter hardy crop, rye will benefit from increased precipitation and higher temperatures during winter months as well as from extended growth periods with an earlier onset in spring and an increase of growing days. Furthermore, rye is able to use the increased winter humidity for its spring growth in an efficient way. By contrast, model simulations showed that summer crops will be affected by reduced precipitation and higher temperatures during summer month for periods from 2050 onwards with the consequence of reduced yields. This yield reduction was found for all summer crops both in conventional sole crop and in DCS. Preponed harvesting of first crop winter rye as a consequence of earlier onset of growth period in spring under prospective climatic conditions lead to yield decrease, which could not be equalised by preponed sowing of second crops and extension of their growth period. Hence, total annual yield of both crops together decreased. The modification of sowing and harvesting dates as an adaptation strategy requires further research with the use of more holistic simulation models. To summarize, DCS may provide a promising adaptation strategy to effects of climate change with a substantial stabilisation of crop yields.
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