Yield Variability as Influenced by Climate: A Statistical Investigation

One of the issues with respect to climate change involves its influence on the distribution of future crop yields. Many studies have been done regarding the effect on the mean of such distributions but few have addressed the effect on variance. Furthermore, those that have been done generally report the variance from crop simulators, not from observations. This paper examines the potential effects of climate change on crop yield variance in the context of current observed yields and then extrapolates to the effects under projected climate change. In particular, maximum likelihood panel data estimates of the impacts of climate on year-to-year yield variability are constructed for the major U.S. agricultural crops. The panel data technique used embodies a variance estimate developed along the lines of the stochastic production function approach suggested by Just and Pope. The estimation results indicate that changes in climate modify crop yield levels and variances in a crop-specific fashion. For sorghum, rainfall and temperature increases are found to increase yield level and variability. On the other hand, precipitation and temperature are individually found to have opposite effects on corn yield levels and variability.     

Climate change,weather variability and corn yield at a higher latitude locale: Southwestern Quebec

Climate change has led to increased temperatures, and simulation models suggest that this should affect crop production in important agricultural regions of the world. Nations at higher latitudes, such as Canada, will be most affected. We studied the relationship between climate variability (temperature and precipitation) and corn yield trends over a period of 33 years for the Monteregie region of south-western Quebec using historical yield and climate records and statistical models. Growing season mean temperature has increased in Monterregie, mainly due to increased September temperature. Precipitation did not show any clear trend over the 33 year period. Yield increased about 118 kg ha⁻¹ year⁻¹ from 1973 to 2005 (under normal weather conditions) due mainly to changes in technology (genetics and management). Two climate variables were strongly associated with corn yield variability: July temperature and May precipitation. These two variables explain more than a half of yield variability associated with climate. In conclusion, July temperatures below normal and May precipitation above normal have negative effects on corn yield, and the growing seasons have warmed, largely due to increases in the September temperature.     

MEAN AND VARIANCE CHANGE IN CLIMATE SCENARIOS: METHODS, AGRICULTURAL APPLICATIONS, AND MEASURES OF UNCERTAINTY

Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2°C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO₂ doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO₂ experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.     

不完整气象资料下基于作物模型的产量预报方法

针对基于作物模型开展产量实时预报后期气象资料的获取问题,提出通过相似类比,从历史气象资料库中获取替代资料的方案,基于CERES-Rice模型系统评估了平均值处理方案和历史相似类比方案的可预报性和误差分布特征。结果表明:水稻产量对成熟前2个月内的气象条件较为敏感,基于气象资料和作物模型开展产量预测,在5%误差范围内可获得60%以上的预测概率;以多年气候平均值替代起报日后期气象资料,在成熟前2个月起报预测概率约为60%,成熟前1个月约为70%,但预报误差系统性偏高;采用气候相似类比方法,从历史气象资料中获取起报日后期替代资料,可有效降低预报误差的系统偏差,若引入后期气候趋势信息,成熟前2个月起报预测概率可达80%以上,较采用历史平均值有显著提高。研究结果为基于作物模型和气象观测及气候预测信息开展产量预报提供了技术方案。     

Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields

Climate change has the potential to be a source of increased variability if crops are more frequently exposed to damaging weather conditions. Yield variability could respond to a shift in the frequency of extreme events to which crops are susceptible, or if weather becomes more variable. Here we focus on the United States, which produces about 40% of the world’s maize, much of it in areas that are expected to see increased interannual variability in temperature. We combine a statistical crop model based on historical climate and yield data for 1950–2005 with temperature and precipitation projections from 15 different global circulation models. Holding current growing area constant, aggregate yields are projected to decrease by an average of 18% by 2030–2050 relative to 1980–2000 while the coefficient of variation of yield increases by an average of 47%. Projections from 13 out of 15 climate models result in an aggregate increase in national yield coefficient of variation, indicating that maize yields are likely to become more volatile in this key growing region without effective adaptation responses. Rising CO₂ could partially dampen this increase in variability through improved water use efficiency in dry years, but we expect any interactions between CO₂ and temperature or precipitation to have little effect on mean yield changes.     

Climate volatility and poverty vulnerability in Tanzania

Climate volatility could change in the future, with important implications for agricultural productivity. For Tanzania, where food production and prices are sensitive to climate, changes in climate volatility could have severe implications for poverty. This study uses climate model projections, statistical crop models, and general equilibrium economic simulations to determine how the vulnerability of Tanzania's population to impoverishment by climate variability could change between the late 20th Century and the early 21st Century. Under current climate volatility, there is potential for a range of possible poverty outcomes, although in the most extreme of circumstances, poverty could increase by as many as 650,000 people due to an extreme interannual decline in grain yield. However, scenarios of future climate from multiple climate models indicate no consensus on future changes in temperature or rainfall volatility, so that either an increase or decrease is plausible. Scenarios with the largest increases in climate volatility are projected to render Tanzanians increasingly vulnerable to poverty through impacts on staple grains production in agriculture, with as many as 90,000 additional people entering poverty on average. Under the scenario where precipitation volatility decreases, poverty vulnerability decreases, highlighting the possibility of climate changes that oppose the ensemble mean, leading to poverty impacts of opposite sign. The results suggest that evaluating potential changes in volatility and not just the mean climate state may be important for analyzing the poverty implications of climate change.     

Problems in Estimating Impacts of Future Climate Change on Midwestern Corn Yields

Recent studies of trends in Midwestern precipitation show marked increases over the last 50 years of the 20th Century, and most climate models project that future rainfall in the Corn Belt will be increased further. During five years, 1988–1991 and 1994, field tests were conducted on agricultural test plots in central Illinois, an area typical of the Corn Belt, to discern how corn yields reacted to varying levels of added rainfall (+10%, +25%, and +40%) during the growing season. The best treatment over the five years was a 40% rain increase, with an average yield increase of 9%. Its yield increase was up to 34% in a hot-dry year, but below that of natural rainfall in a wet year as were the yields of the other lesser increases. The average yield changes from the three treatments were not statistically significantly different. Major interannual yield differences were found in the yields for each rain treatment, reflecting how rain timing and temperatures also have major effects on yields. A 40% summer rain increase has little influence if natural rains do not occur in the high stress period of mid summer. The plots results show that only small average increases in corn yields occur from growing season rain additions in the 10% to 40% range, except in dry years. Weather-crop yield regression models incorporating the same rain increases predict greater yield increases than found in these field tests. This suggests that future yields projected for a wetter climate using yield-weather models may be over-estimated. The plot sample size is small but conditions sampled in the five years represented 43% of all past 97 growing seasons in central Illinois and extremely good and bad weather years, which resulted in large between-year yield differences. Hence, the experimental results provide useful information about how increased rainfall may affect future corn yields, especially since the sample included three of the five types of dry growing seasons found in the area's climate since 1900.     

Effects of drought on winter wheat yield in north China during 2012�C2100

Winter wheat is one of China’s most important staple food crops, and its production is strongly influenced by weather, especially droughts. As a result, the impact of drought on the production of winter wheat is associated with the food security of China. Simulations of future climate for scenarios A2 and A1B provided by GFDL-CM2, MPI_ECHAM5, MRI_CGCM2, NCAR_CCSM3, and UKMO_HADCM3 during 2001-2100 are used to project the influence of drought on winter wheat yields in North China. Winter wheat yields are simulated using the crop model WOFOST (WOrld FOod STudies). Future changes in temperature and precipitation are analyzed. Temperature is projected to increase by 3.9-5.5 for scenario A2 and by 2.9-5.1 for scenario A1B, with fairly large interannual variability. Mean precipitation during the growing season is projected to increase by 16.7 and 8.6 mm (10 yr)-1 , with spring precipitation increasing by 9.3 and 4.8 mm (10 yr)-1 from 2012-2100 for scenarios A2 and A1B, respectively. For the next 10-30 years (2012-2040), neither the growing season precipitation nor the spring precipitation over North China is projected to increase by either scenario. Assuming constant winter wheat varieties and agricultural practices, the influence of drought induced by short rain on winter wheat yields in North China is simulated using the WOFOST crop model. The drought index is projected to decrease by 9.7% according to scenario A2 and by 10.3% according to scenario A1B during 2012-2100. This indicates that the drought influence on winter wheat yields may be relieved over that period by projected increases in rain and temperature as well as changes in the growth stage of winter wheat. However, drought may be more severe in the near future, as indicated by the results for the next 10-30 years.     

THE IMPACT OF CLIMATE CHANGE ON WATER DEFICIT AND PRODUCTION OF WINTER WHEAT IN NORTH CHINA

The water deficits in different development stages and the whole growing season of winterwheat in North China under climate change scenarios are analyzed based on the meteorological da-ta,crop phenomenon and soil hydrological data of 30 weather stations.The results show that ifthe temperature rises,the potential evapotranspiration and crop maximum transpiration will in-crease 8%-10%;the actual evapotranspiration in whole growing season will increase about 1%-2%;and it seems to decrease in spring.Therefore the water deficit status would deteriorate.Theamount of water deficit in whole growing season would increase 14%-30%,and the water deficitisolines might shift southward with maximum shift distance being 190 km.As a result the climaticsuitability of winter wheat would change,and the variation rate of yield reduction will be 8%-20% of the present value which results in the declining output values.The irrigation amountwould increase 25%-33%,and the agriculture cost might increase owing to additional irrigation.     

Impacts of Present and Future Climate Variability On Agriculture and Forestry in the Humid and Sub-Humid Tropics

Although there are different results from different studies, most assessments indicate that climate variability would have negative effects on agriculture and forestry in the humid and sub-humid tropics. Cereal crop yields would decrease generally with even minimal increases in temperature. For commercial crops, extreme events such as cyclones, droughts and floods lead to larger damages than only changes of mean climate. Impacts of climate variability on livestock mainly include two aspects; impacts on animals such as increase of heat and disease stress-related death, and impacts on pasture. As to forestry, climate variability would have negative as well as some positive impacts on forests of humid and sub-humid tropics. However, in most tropical regions, the impacts of human activities such as deforestation will be more important than climate variability and climate change in determining natural forest cover.     

Changes in Soybean Yields in the Midwestern United States as a Result of Future Changes in Climate, Climate Variability, and CO2 Fertilization

This modeling study addresses the potential impacts of climate change and changing climate variability due to increased atmospheric CO₂ concentration on soybean (Glycine max (L.) Merrill) yields in theMidwestern Great Lakes Region. Nine representative farm locations and six future climate scenarios were analyzed using the crop growth model SOYGRO. Under the future climate scenarios earlierplanting dates produced soybean yield increases of up to 120% above current levels in the central and northern areas of the study region. In the southern areas, comparatively small increases (0.1 to 20%) and small decreases (–0.1 to–25%) in yield are found. The decreases in yield occurred under the Hadley Center greenhouse gas run (HadCM2-GHG), representing a greater warming, and the doubled climate variability scenario – a more extreme and variableclimate. Optimum planting dates become later in the southern regions. CO₂fertilization effects (555 ppmv) are found to be significant for soybean, increasing yields around 20% under future climate scenarios.For the study region as a whole the climate changes modeled in this research would have an overall beneficial effect, with mean soybean yield increases of 40% over current levels.     

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.     

21st century climate change in the Middle East

This study examined the performance and future predictions for the Middle East produced by 18 global climate models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. Under the Special Report on Emission Scenarios A2 emissions scenario the models predict an overall temperature increase of ~1.4 K by mid-century, increasing to almost 4 K by late-century for the Middle East. In terms of precipitation the southernmost portion of the domain experiences a small increase in precipitation due to the Northward movement of the Inter-Tropical Convergence Zone. The largest change however is a decrease in precipitation that occurs in an area covering the Eastern Mediterranean, Turkey, Syria, Northern Iraq, Northeastern Iran and the Caucasus caused by a decrease in storm track activity over the Eastern Mediterranean. Other changes likely to impact the region include a decrease of over 170,000 km² in viable rainfed agriculture land by late-century, increases in the length of the dry season that reduces the length of time that the rangelands can be grazed, and changes in the timing of the maximum precipitation in Northern Iran that will impact the growing season, forcing changes in cropping strategy or even crop types.     

Thermal Climate Variations and Potential Modification of the Cropping Pattern in Bangladesh

Summary Changes in the thermal climate due to inter-annual climatic variability can potentially modify existing cropping pattern by forcing farmers to rearrange transplanting and harvesting dates. In the present study, a crop climate model, the YIELD, has been applied to 12 meteorological stations located in major rice growing regions in Bangladesh to estimate the effect of thermal climate variations on the transplanting and harvesting dates of boro rice and the resultant potential changes in cropping pattern and spatial shift. The abnormal thermal climate scenarios have been created by synthetically perturbing mean air temperatures (T_air) up to −5 °C to +5 °C with an interval of 1 °C for each of these stations. Historical meteorological records of air temperature in Bangladesh have been used to prepare these scenarios. The study finds that under abnormally cool conditions transplanting dates will be pushed well into February to avoid plant injury and harvesting dates will be moved into the monsoon. The growing seasons will be longer under cooler than normal thermal conditions. Under abnormally warm conditions harvesting dates will be established well into March and will cause reduction of yield due to a shorter growing season. These conditions will also cause spatial shift in crop potential and changes in the cropping pattern. Due to a longer boro rice growing season farmers will lose a significant amount of cropping land which is usually used for low and deep water rice cultivation. New crops will need to be introduced during the beginning of a year to overcome the loss of production under abnormally cool conditions. Wheat and potato can be good options for the farmers for such conditions. New aus rice variety needs to be introduced after the boro harvesting under warmer than the normal conditions to overcome the loss of yield due to a shorter growing season. Received September 16, 1996 Revised September 8, 1997     

Agricultural impacts of climate change in Spain: developing tools for a spatial analysis

CERES-Wheat, a dynamic process crop growth model, is specified and validated for seven sites in the major wheat-growing regions of Spain. Variables explaining a significant proportion of simulated yield variance are crop water (sum of precipitation and irrigation) and temperature during the growing season. A multiple linear regression model is developed to represent simulated yield response to these variables. Seven agro-climatic regions are defined based on K-mean cluster analysis of temperature and precipitation data from 329 meteorological stations and provincial crop yield data. The yield functions derived from the validated crop model were then used with the gridded agro-climatic database to conduct a spatial analysis of climate change impacts on national wheat production. Climate change scenarios with and without sulfate aerosols developed from the Hadley Centre (HCGG and HCGS) and Canadian Climate Centre (CCGG and CCGC) are tested.     

Potential impact of future climate change on crop yield in northeastern China

We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China(NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5(CMIP5) under the Representative Concentration Pathway 4.5 scenario(RCP4.5), the projected maize yield changes for three future periods [2010–39(period 1), 2040–69(period 2), and 2070–99(period 3)] relative to the mean yield in the baseline period(1976–2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase(but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers.     

Observed and projected climate change in Taiwan

Summary This study examined the secular climate change characteristics in Taiwan over the past 100 years and the relationship with the global climate change. Estimates for the likelihood of future climate changes in Taiwan were made based on the projection from the IPCC climate models. In the past 100 years, Taiwan experienced an island-wide warming trend (1.0–1.4 °C/100 years). Both the annual and daily temperature ranges have also increased. The warming in Taiwan is closely connected to a large-scale circulation and SAT fluctuations, such as the “cool ocean warm land” phenomenon. The water vapor pressure has increased significantly and could have resulted in a larger temperature increase in summer. The probability for the occurrence of high temperatures has increased and the result suggests that both the mean and variance in the SAT in Taiwan have changed significantly since the beginning of the 20th century. Although, as a whole, the precipitation in Taiwan has shown a tendency to increase in northern Taiwan and to decrease in southern Taiwan in the past 100 years, it exhibits a more complicated spatial pattern. The changes occur mainly in either the dry or rainy season and result in an enhanced seasonal cycle. The changes in temperature and precipitation are consistent with the weakening of the East Asian monsoon. Under consideration of both the warming effect from greenhouse gases and the cooling effect from aerosols, all projections from climate models indicated a warmer climate near Taiwan in the future. The projected increase in the area-mean temperature near Taiwan ranged from 0.9–2.7 °C relative to the 1961–1990 averaged temperature, when the CO₂ concentration increased to 1.9 times the 1961–1990 level. These simulated temperature increases were statistically significant and can be attributed to the radiative forcing associated with the increased concentration of greenhouse gases and aerosols. The projected changes in precipitation were within the range of natural variability for all five models. There is no evidence supporting the possibility of precipitation changes near Taiwan based on the simulations from five IPCC climate models. Received February 5, 2001 Revised July 30, 2001     

The effect of changes in daily and interannual climatic variability on CERES-Wheat: A sensitivity study

We investigate the effect of changes in daily and interannual variability of temperature and precipitation on yields simulated by the CERES-Wheat model at two locations in the central Great Plains. Changes in variability were effected by adjusting parameters of the Richardson daily weather generator. Two types of changes in precipitation were created: one with both intensity and frequency changed; and another with change only in persistence. In both types mean total monthly precipitation is held constant. Changes in daily (and interannual) variability of temperature result in substantial changes in the mean and variability of simulated wheat yields. With a doubling of temperature variability, large reductions in mean yield and increases in variability of yield result primarily from crop failures due to winter kill at both locations. Reduced temperature variability has little effect. Changes in daily precipitation variability also resulted in substantial changes in mean and variability of yield. Interesting interactions of the precipitation variability changes with the contrasting base climates are found at the two locations. At one site where soil moisture is not limiting, mean yield decreased and variability of yield increased with increasing precipitation variability, whereas mean yields increased at the other location, where soil moisture is limiting. Yield changes were similar for the two different types of precipitation variability change investigated. Compared to an earlier study for the same locations wherein variability changes were effected by altering observed time series, and the focus was on interannual variability, the present results for yield changes are much more substantial. This study demonstrates the importance of taking into account change in daily (and interannual) variability of climate when analyzing the effect of climate change on crop yields.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Expected changes in future agro-climatological conditions in Northeast Thailand and their differences between general circulation models

We have studied future changes in the atmospheric and hydrological environments in Northeast Thailand from the viewpoint of risk assessment of future cultural environments in crop fields. To obtain robust and reliable estimation for future climate, ten general circulation models under three warming scenarios, B1, A1B, and A2, were used in this study. The obtained change trends show that daily maximum air temperature and precipitation will increase by 2.6°C and 4.0%, respectively, whereas soil moisture will decrease by c.a. 1% point in volumetric water content at the end of this century under the A1B scenario. Seasonal contrasts in precipitation will intensify: precipitation increases in the rainy season and precipitation decreases in the dry season. Soil moisture will slightly decrease almost throughout the year. Despite a homogeneous increase in the air temperature over Northeast Thailand, a future decrease in soil water content will show a geographically inhomogeneous distribution: Soil will experience a relative larger decrease in wetness at a shallow depth on the Khorat plateau than in the surrounding mountainous area, reflecting vegetation cover and soil texture. The predicted increase in air temperature is relatively consistent between general circulation models. In contrast, relatively large intermodel differences in precipitation, especially in long-term trends, produce unwanted bias errors in the estimation of other hydrological elements, such as soil moisture and evaporation, and cause uncertainties in projection of the agro-climatological environment. Offline hydrological simulation with a wide precipitation range is one strategy to compensate for such uncertainties and to obtain reliable risk assessment of future cultural conditions in rainfed paddy fields in Northeast Thailand.