Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data

Extreme weather conditions can strongly affect agricultural production, with negative impacts that can at times be detected at regional scales. In France, crop yields were greatly influenced by drought and heat stress in 2003 and by extremely wet conditions in 2007. Reported regional maize and wheat yields where historically low in 2003; in 2007 wheat yields were lower and maize yields higher than long-term averages. An analysis with a spatial version (10?×?10?km) of the EPIC crop model was tested with regards to regional crop yield anomalies of wheat and maize resulting from extreme weather events in France in 2003 and 2007, by comparing simulated results against reported regional crops statistics, as well as using remotely sensed soil moisture data. Causal relations between soil moisture and crop yields were specifically analyzed. Remotely sensed (AMSR-E) JJA soil moisture correlated significantly with reported regional crop yield for 2002–2007. The spatial correlation between JJA soil moisture and wheat yield anomalies was positive in dry 2003 and negative in wet 2007. Biweekly soil moisture data correlated positively with wheat yield anomalies from the first half of June until the second half of July in 2003. In 2007, the relation was negative the first half of June until the second half of August. EPIC reproduced observed soil dynamics well, and it reproduced the negative wheat and maize yield anomalies of the 2003 heat wave and drought, as well as the positive maize yield anomalies in wet 2007. However, it did not reproduce the negative wheat yield anomalies due to excessive rains and wetness in 2007. Results indicated that EPIC, in line with other crop models widely used at regional level in climate change studies, is capable of capturing the negative impacts of droughts on crop yields, while it fails to reproduce negative impacts of heavy rain and excessively wet conditions on wheat yield, due to poor representations of critical factors affecting plant growth and management. Given that extreme weather events are expected to increase in frequency and perhaps severity in coming decades, improved model representation of crop damage due to extreme events is warranted in order to better quantify future climate change impacts and inform appropriate adaptation responses.     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

First-order impacts on winter and summer crops assessed with various high-resolution climate models in the Iberian Peninsula

The first-order or initial agricultural impacts of climate change in the Iberian Peninsula were evaluated by linking crop simulation models to several high-resolution climate models (RCMs). The RCMs provided the daily weather data for control, and the A2 and B2 IPCC scenarios. All RCMs used boundary conditions from the atmospheric general circulation model (AGCM) HadAM3 while two were also bounded to two other AGCMs. The analyses were standardised to control the sources of variation and uncertainties that were added in the process. Climatic impacts on wheat and maize of climate were derived from the A2 scenario generated by RCMs bounded to HadAM3. Some results derived from B2 scenarios are included for comparisons together with impacts derived from RCMs using different boundary conditions. Crop models were used as impact models and yield was used as an indicator that summarised the effects of climate to quantify initial impacts and differentiate among regions. Comparison among RCMs was made through the choice of different crop management options. All RCM-crop model combinations detected crop failures for winter wheat in the South under control and future scenarios, and projected yield increases for spring wheat in northern and high altitude areas. Although projected impacts differed among RCMs, similar trends emerged for relative yields for some regions. RCM-crop model outputs compared favourably to others using European Re-Analysis data (ERA-15), establishing the feasibility of using direct daily outputs from RCM for impact analysis. Uncertainties were quantified as the standard deviation of the mean obtained for all RCMs in each location and differed greatly between winter (wheat) and summer (maize) seasons, being smaller in the latter.     

The effect of rate of change, variability, and extreme events on the pace of adaptation to a changing climate

When is it time to adopt different technologies, management strategies, and resource use practices as underlying climate change occurs? We apply risk and decision analysis to test hypotheses about the timing and pace of adaption in response to different profiles of climate change and extremes expressed as yield and income variation for a simulated dryland wheat farm in the United States Great Plains. Climate scenarios include gradual change with typical or increased noise (standard deviation), rapid and large change, and gradual change with extreme events stepped through the simulation. We test decision strategies that might logically be utilized by farmers facing a climate trend that worsens crop enterprise outcomes. Adaptation quickens with the rate of change, especially for decision strategies based on performance thresholds, but is delayed by larger climate variability, especially for decision strategies based on recognizing growing differential between adaptive and non-adaptive performance. Extreme events evoke adaptation sooner than gradual change alone, and in some scenarios extremes evoke premature, inefficient, adaptation.     

Climate change impact assessment: the role of climate extremes in crop yield simulation

This work was aimed at assessing the role of climate extremes in climate change impact assessment of typical winter and summer Mediterranean crops by using Regional Circulation Model (RCM) outputs as drivers of a modified version of the CropSyst model. More specifically, climate change effects were investigated on sunflower (Helianthus annuus L.) and winter wheat (Triticum aestivum L.) development and yield under the A2 and B2 scenarios of the IPCC Special Report on Emissions Scenarios (SRES). The direct impact of extreme climate events (i.e. heat stress at anthesis stage) was also included. The increase in both mean temperatures and temperature extremes under A2 and B2 scenarios (2071?C2100) resulted in: a general advancement of the main phenological stages, shortening of the growing season and an increase in the frequency of heat stress during anthesis with respect to the baseline (1961?C1990). The potential impact of these changes on crop yields was evaluated. It was found that winter and summer crops may possess a different fitting capacity to climate change. Sunflower, cultivated in the southern regions of the Mediterranean countries, was more prone to the direct effect of heat stress at anthesis and drought during its growing cycle. These factors resulted in severe yield reduction. In contrast, the lower frequency of heat stress and drought allowed the winter wheat crop to attain increased yields with respect to the baseline period. It can be concluded that the impact of extreme events should be included in crop-modelling approaches, otherwise there is the risk of underestimating crop yield losses, which in turn would result in the application of incorrect policies for coping with climate change.     

Possible impacts of climate change on extreme weather events at local scale in south–central Canada

Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south–central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century over south–central Canada under a changing climate. The implications of these increases need be taken into consideration and integrated into policies and planning for adaptation strategies, including measures to incorporate climate change into engineering infrastructure design standards and disaster risk reduction measures. This paper briefly summarized these climate change research projects, focusing on the modeling methodologies and results, and attempted to use plain language to make the results more accessible and interesting to the broader informed audience. These research projects have been used to support decision-makers in south–central Canada when dealing with future extreme weather events under climate change.     

Precipitation extremes in a karst region: a case study in the Guizhou province, southwest China

The topography of hilly landscapes modifies crop environment changing the fluxes of water and energy, increasing risk in these vulnerable agriculture systems, which could become more accentuated under climate change (drought, increased variability of rainfall). In order to quantify how wheat production in hilly terrain will be affected by future climate, a newly developed and calibrated micro-meteorological model for hilly terrain was linked to a crop growth simulation model to analyse impact scenarios for different European regions. Distributions of yield and growing length of rainfed winter wheat and durum wheat were generated as probabilistic indices from baseline and low (B2) and high (A2) emission climate scenarios provided from the Hadley Centre Regional Climate Model (HadRM3). We used site-specific terrain parameters for two sample catchments in Europe, ranging from humid temperate (southeast UK) to semi-arid Mediterranean (southern Italy). Results for baseline scenario show that UK winter wheat is mainly affected by annual differences in precipitation and yield distributions do not change with terrain, whilst in the southern Mediterranean climate yield variability is significantly related to a slope × elevation index. For future climate, our simulations confirm earlier predictions of yield increase in the UK, even under the high emission scenario. In the southern Mediterranean, yield reduction is significantly related to slope × elevation index increasing crop failure in drier elevated spots but not in wet years under baseline weather. In scenarios for the future, the likelihood of crop failure rises sharply to more than 60%, and even in wet years, yields are likely to decrease in elevated spots.     

气候变化国家评估报告（II）：气候变化的影响与适应

已经观测到的气候变化影响是显著的、多方面的。各个领域和地区都存在有利和不利影响,但以不利影响为主,未来的气候变暖将会对中国的生态系统、农业以及水资源等部门和沿海地区产生重大的不利影响。采取适应措施可以减轻气候变化的不利影响,应将适应气候变化的行动逐步纳入国民经济和社会发展的中长期规划中。由于我国科学研究的相对不足和科学认识能力的局限,目前的气候变化影响评估方法和结果还存在很大的不确定性。应当加强区域适应气候变化的案例研究、扩大研究领域、加强极端天气、气候事件影响的研究,以降低影响评估的不确定性,并提出切实可行的适应对策。     

Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia

Future climate projections and impact analyses are pivotal to evaluate the potential change in crop yield under climate change. Impact assessment of climate change is also essential to prepare and implement adaptation measures for farmers and policymakers. However, there are uncertainties associated with climate change impact assessment when combining crop models and climate models under different emission scenarios. This study quantifies the various sources of uncertainty associated with future climate change effects on wheat productivity at six representative sites covering dry and wet environments in Australia based on 12 soil types and 12 nitrogen application rates using one crop model driven by 28 global climate models (GCMs) under two representative concentration pathways (RCPs) at near future period 2021–2060 and far future period 2061–2100. We used the analysis of variance (ANOVA) to quantify the sources of uncertainty in wheat yield change. Our results indicated that GCM uncertainty largely dominated over RCPs, nitrogen rates, and soils for the projections of wheat yield at drier locations. However, at wetter sites, the largest share of uncertainty was nitrogen, followed by GCMs, soils, and RCPs. In addition, the soil types at two northern sites in the study area had greater effects on yield change uncertainty probably due to the interaction effect of seasonal rainfall and soil water storage capacity. We concluded that the relative contributions of different uncertainty sources are dependent on climatic location. Understanding the share of uncertainty in climate impact assessment is important for model choice and will provide a basis for producing more reliable impact assessment.     

Adapting dryland agriculture to climate change: Farming implications and research and development needs in Western Australia

The Western Australian wheat-belt has experienced more rainfall decline than any other wheat-cropping region in Australia. Future climate change scenarios suggest that the Western Australian wheat-belt is likely to see greater future reductions in rainfall than other regions, together with a further increase in temperatures. While these changes appear adverse for water-limited rain-fed agriculture, a close analysis of the changes and their impacts reveals a more complex story. Twentieth century changes in rainfall, temperature and atmospheric CO₂ concentration have had little or no overall impact on wheat yields. Changes in agricultural technology and farming systems have had much larger impacts. Contrary to some claims, there is no scientific or economic justification for any immediate actions by farmers to adapt to long-term climate change in the Western Australian wheat-belt, beyond normal responses to short-term variations in weather. Rather than promoting current change, the most important policy response is research and development to enable farmers to facilitate future adaptation to climate change. Research priorities are proposed.     

气候变化国家评估报告(Ⅱ):气候变化的影响与适应

Significant and various impacts of climate change have been observed in China, showing both positive and adverse effects, dominantly the latter, in different sectors and regions. It is very likely that future climate change would cause significant adverse impacts on the ecosystems, agriculture, water resources, and coastal zones in China. Adoption of adaptive measures to climate change can alleviate the adverse impact, therefore such measures should be incorporated into the medium-and long-term national economic and social development plans. Because China has done relatively limited research on impact assessment and our understanding of climate change is incomplete, the current impact assessment methodologies used and results obtained contain many uncertainties. To reduce the uncertainties and develop effective and practical climate change adaptive measures in China, it is necessary to emphasize regional case studies on adaptive measures, enlarge the scope of climate change research, and strengthen the assessment of the impacts resulted from extreme weather/climate events.     

Climate Change and Rice Yields in Diverse Agro-Environments of India. II. Effect of Uncertainties in Scenarios and Crop Models on Impact Assessment

Estimates of impact of climate change on crop production could be biased depending upon the uncertainties in climate change scenarios, region of study, crop models used for impact assessment and the level of management. This study reports the results of a study where the impact of various climate change scenarios has been assessed on grain yields of irrigated rice with two popular crop simulation models- Ceres-Rice and ORYZA1N at different levels of N management. The results showed that the direct effect of climate change on rice crops in different agroclimatic regions in India would always be positive irrespective of the various uncertainties. Rice yields increased between 1.0 and 16.8% in pessimistic scenarios of climate change depending upon the level of management and model used. These increases were between 3.5 and 33.8% in optimistic scenarios. At current as well as improved level of management, southern and western parts of India which currently have relatively lower temperatures compared to northern and eastern regions, are likely to show greater sensitivity in rice yields under climate change. The response to climate change is small at low N management compared to optimal management. The magnitude of this impact can be biased upto 32% depending on the uncertainty in climate change scenario, level of management and crop model used. These conclusions are highly dependent on the specific thresholds of phenology and photosynthesis to change in temperature used in the models. Caution is needed in using the impact assessment results made with the average simulated grain yields and mean changes in climatic parameters.     

在气候影响研究中引入随机天气发生器的方法和不确定性

通过采用不同的随机天气发生器生成一定气候背景下各种气候变率情景，许多学者在最近的研究中已经认识到气候变率对农作物生长发育影响的重要性。传统的气候影响评估方法直接以大气环流模式的模拟试验结果作为未来气候情景，这样不可能理解如上的重要性。本文着重评述将随机天气发生器应用于气候变化影响研究的一般方法框架，以及作者的具体个例研究方法。文中最后分析了目前该领域研究中还存在的一些不确定性。 在当前的气候变化影响研究中，有不同的方法用来研制一种称为WGEN的典型随机天气发生器的参数化方案及其随机试验方法。不同的研究者也有不同的参数调控方法。通常的思路是通过气候控制试验和2×CO2试验之间的气候变量平均值和方差的变化来扰动随机天气发生器的参数，以生成未来逐日气候变化情景。本文作者根据短期气候预测模式的输出产品建立了一套WGEN的参数化方案及其随机试验方法，并且在时间和空间两个尺度上检验和评估了此参数化方案下WGEN的模拟能力。另外，作者由未来降水的变化，调试随机天气发生器参数，生成了气候变率变化情景。这些参数调节可以产生各种不同类型和定性大小的气候变率变化，用于气候影响评估的敏感性分析。通过如上方法，作为一个个例，文中评估了未来气候变率变化     

气候变化对中国农业生产的影响研究进展

气候变化已成为当今科学界、各国政府和社会公众普遍关注的环境问题之一,气候变化可能对生态系统和社会经济产生灾难性影响,农业是受气候变化影响最直接的脆弱行业。因此,气候变化对农业生产的影响研究一直是气候变化研究领域中的热点问题之一。该文系统介绍了有关全球气候变化对中国农业生产影响研究的现状与进展,包括气候变化对农业影响的研究方法、大气中温室气体浓度增加对农作物的影响试验、气候变化对农业气候资源的影响、气候变化对农作物生长发育和产量的影响、气候变化对农业种植制度和品种布局的影响、气候变化对农作物气候生产潜力和气候资源利用率的影响等,指出当前在研究气候变化对农业影响评估中存在的问题,提出了今后应加强对气候变化情景和预测模式不确定性的研究、气候变化对农业影响的方法研究。此外,气候变化背景下极端天气气候事件对农业生产的影响以及气候变化对农业病虫害的影响研究等仍较薄弱,有待进一步加强和深入。     

Climate Risks and Their Impact on Agriculture and Forests in Switzerland

There is growing evidence that, as a result of global climate change, some of the most severe weather events could become more frequent in Europe over the next 50 to 100 years. The paper aims to (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from simulations with global circulation models, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts on agricultural systems and forests in Switzerland. Trends and scenarios project more frequent heavy precipitation during winter corresponding, for example, to a three-fold increase in the exceedance of today's 15-year extreme values by the end of the 21st century. This increases the risk of large-scale flooding and loss of topsoil due to erosion. In contrast, constraints in agricultural practice due to waterlogged soils may become less in a warmer climate. In summer, the most remarkable trend is a decrease in the frequency of wet days, and shorter return times of heat waves and droughts. This increases the risk of losses of crop yield and forage quality. In forests, the more frequent occurrence of dry years may accelerate the replacement of sensitive tree species and reduce carbon stocks, and the projected slight increase in the frequency of extreme storms by the end of the century could increase the risk of windthrow. Some possible measures to maintain goods and services of agricultural and forest ecosystems are mentioned, but it is suggested that more frequent extremes may have more severe consequences than progressive changes in means. In order to effectively decrease the risk for social and economic impacts, long-term adaptive strategies in agriculture and silviculture, investments for prevention, and new insurance concepts seem necessary.     

Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part I. The Uncertainty Due to Spatial Scale

We investigated the effect of two different spatial scales of climate change scenarios on crop yields simulated by the EPIC crop model for corn, soybean, and wheat, in the central Great Plains of the United States. The effect of climate change alone was investigated in Part I. In Part II (Easterling et al., 2001) we considered the effects ofCO₂ fertilization effects and adaptation in addition to climate change. The scenarios were formed from five years of control and 2 ×CO₂ runs of a high resolution regional climate model (RegCM) and the same from an Australian coarse resolution general circulation model (GCM), which provided the initial and lateral boundary conditions for the regional model runs. We also investigated the effect of two different spatial resolutions of soil input parameters to the crop models. We found that for corn and soybean in the eastern part of the study area, significantly different mean yield changes were calculated depending on the scenario used. Changes in simulated dryland wheat yields in the western areas were very similar, regardless of the scale of the scenario. The spatial scale of soils had a strong effect on the spatial variance and pattern of yields across the study area, but less effect on the mean aggregated yields. We investigated what aspects of the differences in the scenarios were most important for explaining the different simulated yield responses. For instance, precipitation changes in June were most important for corn and soybean in the eastern CSIRO grid boxes. We establish the spatial scale of climate changescenarios as an important uncertainty for climate change impacts analysis.     

Impacts of Present and Future Climate Variability on Agriculture and Forestry in the Temperate Regions: Europe

Agriculture and forestry will be particularly sensitive to changes in mean climate and climate variability in the northern and southern regions of Europe. Agriculture may be positively affected by climate change in the northern areas through the introduction of new crop species and varieties, higher crop production and expansion of suitable areas for crop cultivation. The disadvantages may be determined by an increase in need for plant protection, risk of nutrient leaching and accelerated breakdown of soil organic matter. In the southern areas the benefits of the projected climate change will be limited, while the disadvantages will be predominant. The increased water use efficiency caused by increasing CO₂ will compensate for some of the negative effects of increasing water limitation and extreme weather events, but lower harvestable yields, higher yield variability and reduction in suitable areas of traditional crops are expected for these areas. Forestry in the Mediterranean region may be mainly affected by increases in drought and forest fires. In northern Europe, the increased precipitation is expected to be large enough to compensate for the increased evapotranspiration. On the other hand, however, increased precipitation, cloudiness and rain days and the reduced duration of snow cover and soil frost may negatively affect forest work and timber logging determining lower profitability of forest production and a decrease in recreational possibilities. Adaptation management strategies should be introduced, as effective tools, to reduce the negative impacts of climate change on agricultural and forestry sectors.     

Adaptation to climate change through the choice of cropping system and sowing date in sub-Saharan Africa

Multiple cropping systems provide more harvest security for farmers, allow for crop intensification and furthermore influence ground cover, soil erosion, albedo, soil chemical properties, pest infestation and the carbon sequestration potential. We identify the traditional sequential cropping systems in ten sub-Saharan African countries from a survey dataset of more than 8600 households. We find that at least one sequential cropping system is traditionally used in 35% of all administrative units in the dataset, mainly including maize or groundnuts. We compare six different management scenarios and test their susceptibility as adaptation measure to climate change using the dynamic global vegetation model for managed land LPJmL. Aggregated mean crop yields in sub-Saharan Africa decrease by 6–24% due to climate change depending on the climate scenario and the management strategy. As an exception, some traditional sequential cropping systems in Kenya and South Africa gain by at least 25%. The crop yield decrease is typically weakest in sequential cropping systems and if farmers adapt the sowing date to changing climatic conditions. Crop calorific yields in single cropping systems only reach 40–55% of crop calorific yields obtained in sequential cropping systems at the end of the 21st century. The farmers’ choice of adequate crops, cropping systems and sowing dates can be an important adaptation strategy to climate change and these management options should be considered in climate change impact studies on agriculture.     

中国农业洪涝灾害研究进展

农业洪涝灾害是国内外灾害研究的重要分支领域。该文采用分类归纳总结已有研究成果并与观测事实相佐证的方法,从农业洪涝相关概念出发,系统阐述了中国农业洪涝灾害的研究进展,评述了气候变暖对中国农业洪涝灾害的影响。基于影响作物及发生时段,中国农业洪涝灾害可分为影响越冬作物的春涝、影响夏播夏收和夏季作物生长的夏涝及影响秋播秋收作物的秋涝。农业洪涝灾害的形成及强度,是天气气候、作物抗涝性、地形地貌、土壤结构及人类活动等多种因素综合作用的结果;气候变暖背景下,中国农业洪涝成灾率呈南方增强北部减缓的趋势,总体呈上升趋势;一方面与极端降水事件的变化有直接关系,另一方面受作物气候适宜性变化等的间接影响。农业洪涝灾害的致灾机理包括物理性破坏、生理性损伤及生态性危害。其影响包括对农业生产环境、作物生态生理和生长发育的影响及诱发病虫害等。气候变化背景下的农业洪涝综合性指标、基于灾变过程的综合风险评估及气候变暖对不同作物洪涝灾害的影响事实将是未来重点研究方向。