An assessment of regional vulnerability of rice to climate change in India

A simulation analysis was carried out using the InfoCrop-rice model to quantify impacts and adaptation gains, as well as to identify vulnerable regions for irrigated and rain fed rice cultivation in future climates in India. Climates in A1b, A2, B1 and B2 emission scenarios as per a global climate model (MIROC3.2.HI) and a regional climate model (PRECIS) were considered for the study. On an aggregated scale, the mean of all emission scenarios indicate that climate change is likely to reduce irrigated rice yields by ~4 % in 2020 (2010–2039), ~7 % in 2050 (2040–2069), and by ~10 % in 2080 (2070–2099) climate scenarios. On the other hand, rainfed rice yields in India are likely to be reduced by ~6 % in the 2020 scenario, but in the 2050 and 2080 scenarios they are projected to decrease only marginally (<2.5 %). However, spatial variations exist for the magnitude of the impact, with some regions likely to be affected more than others. Adaptation strategies comprising agronomical management can offset negative impacts in the near future—particularly in rainfed conditions—but in the longer run, developing suitable varieties coupled with improved and efficient crop husbandry will become essential. For irrigated rice crop, genotypic and agronomic improvements will become crucial; while for rainfed conditions, improved management and additional fertilizers will be needed. Basically climate change is likely to exhibit three types of impacts on rice crop: i) regions that are adversely affected by climate change can gain in net productivity with adaptation; ii) regions that are adversely affected will still remain vulnerable despite adaptation gains; and iii) rainfed regions (with currently low rainfall) that are likely to gain due to increase in rainfall can further benefit by adaptation. Regions falling in the vulnerable category even after suggested adaptation to climate change will require more intensive, specific and innovative adaptation options. The present analysis indicates the possibility of substantial improvement in yields with efficient utilization of inputs and adoption of improved varieties.     

Observed variability and trends in extreme temperature indices and rice–wheat productivity over two districts of Bihar, India—a case study

The purpose of this paper is to analyze the trends and variability in extreme temperature indices and its impact on rice–wheat productivity over two districts of Bihar, India, which is part of the middle Indo-Gangetic Basin. Mann–Kendall non-parametric test was employed for detection of trend and Sen slope was determined to quantify the magnitude of such trends. We have analyzed 10 extreme temperature indices for monthly and seasonally. The influence of extreme temperature indices on rice–wheat productivity was determined using correlation analysis. As far as Patna is concerned, if the number of cool days during September ≥10, the rice productivity will increase due to the availability of sufficient duration to fill up the grain. However, higher warm days during all the months except June will affect the productivity. A significant negative correlation was noticed between maximum value of minimum temperature during September and rice productivity. Highly significant positive correlation was noticed between number of cool days during September with rice productivity while it was highly significant negative correlation in the case of number of warm days during the same month. As far as Samastipur is concerned, a negative correlation was noticed between wheat productivity and maximum value of maximum temperature (TXx) during February, but not statistically significant. The higher temperature may affect the kernel weight and thereby yield. It is seen that a critical value of TXx ≥29.2 °C will be harmful to wheat crop during February. A significant positive correlation of number of cool nights with wheat productivity also supports the above relationship. The critical values of extreme temperature indices during rice and wheat growing months provide an indicator to assess the vulnerability of rice–wheat productivity to temperature for Patna and Samastipur districts and there is a need to prepare an adaptive strategy and also develop thermo-insensitive rice–wheat high yielding varieties suitable for this region to sustain rice–wheat productivity under projected climate change situation.     

Non-Kyoto radiative forcing in long-run greenhouse gas emissions and climate change scenarios

Climate policies must consider radiative forcing from Kyoto greenhouse gases, as well as other forcing constituents, such as aerosols and tropospheric ozone that result from air pollutants. Non-Kyoto forcing constituents contribute negative, as well as positive forcing, and overall increases in total forcing result in increases in global average temperature. Non-Kyoto forcing modeling is a relatively new component of climate management scenarios. This paper describes and assesses current non-Kyoto radiative forcing modeling within five integrated assessment models. The study finds negative forcing from aerosols masking (offsetting) approximately 25 % of positive forcing in the near-term in reference non-climate policy projections. However, masking is projected to decline rapidly to 5–10 % by 2100 with increasing Kyoto emissions and assumed reductions in air pollution—with the later declining to as much as 50 % and 80 % below today’s levels by 2050 and 2100 respectively. Together they imply declining importance of non-Kyoto forcing over time. There are however significant uncertainties and large differences across models in projected non-Kyoto emissions and forcing. A look into the modeling reveals differences in base conditions, relationships between Kyoto and non-Kyoto emissions, pollution control assumptions, and other fundamental modeling. In addition, under climate policy scenarios, we find air pollution and resulting non-Kyoto forcing reduced to levels below those produced by air pollution policies alone—e.g., China sulfur emissions fall an additional 45–85 % by 2050. None of the models actively manage non-Kyoto forcing for climate implications. Nonetheless, non-Kyoto forcing may be influencing mitigation results, including allowable carbon dioxide emissions, and further evaluation is merited.     

Heterogeneous effects of warming and drought on selected wheat variety yields

Climate change is likely to significantly impact agricultural production in the Great Plains region of the Central United States. This study estimated the impact of changes in temperature and precipitation on wheat (triticum aestivum) variety yield distributions using the moment-based maximum entropy (MBME) model. This approach allows for quantification of potential weather impacts on the yield distribution, and allows these effects to vary across varieties. The unique data set matches wheat variety trial data for 1985 to 2011 with weather data from the exact trial site for 11 locations throughout Kansas. Ten widely-planted varieties with a range of biotic and abiotic characteristics were included for comparison. Weather scenarios were simulated for baseline, increased temperature (one-degree Celsius warming), decreased precipitation (tenth-percentile rainfall outcome), and a combination warming and drought scenario. Warming resulted in an 11 % yield reduction, drought a 22 % reduction, and warming and drought a cumulative 33 % reduction. These effects vary across varieties. Alternative measures of yield risk (e.g. yield variance and coefficient of variation) were also constructed under each scenario and a similar pattern of heterogeneous impacts emerges. The key findings are that (i) exposure to warming and drought lead to mean yield reductions coupled with increased yield risk for all varieties, and (ii) newer (post 2005) seed varieties have a yield advantage over older varieties, however this advantage is reduced under warming and drought conditions.     

Climate change impacts on regional rice production in China

Rice (Oryza sativa L.) production is an important contributor to China’s food security. Climate change, and its impact on rice production, presents challenges in meeting China’s future rice production requirements. In this study, we conducted a comprehensive analysis of how rice yield responds to climate change under different scenarios and assessed the associated simulation uncertainties of various regional-scale climate models. Simulation was performed based on a regional calibrated crop model (CERES-Rice) and spatially matched climatic (from 17 global climate models), soil, management, and cultivar parameters. Grain-filling periods for early rice were shortened by 2–7 days in three time slices (2030s, 2050s, and 2070s), whereas grain-filling periods for late rice were shortened by 10–19 days in three time slices. Most of the negative effects of climate change were predicted to affect single-crop rice in central China. Average yields of single-crop rice treated with CO₂ fertiliser in central China were predicted to be reduced by 10, 11, and 11% during the 2030s, 2050s, and 2070s, respectively, compared to the 2000s, if planting dates remained unchanged. If planting dates were optimised, single-crop rice yields were predicted to increase by 3, 7, and 11% during the 2030s, 2050s, and 2070s, respectively. In response to climate changes, early and single-crop rice should be planted earlier, and late rice planting should be delayed. The predicted net effect would be to prolong the grain-filling period and optimise rice yield.     

The effects of increased stream temperatures on juvenile steelhead growth in the Yakima River Basin based on projected climate change scenarios

Stakeholders within the Yakima River Basin expressed concern over impacts of climate change on mid-Columbia River steelhead (Oncorhynchus mykiss), listed under the Endangered Species Act. We used a bioenergetics model to assess the impacts of changing stream temperatures—resulting from different climate change scenarios—on growth of juvenile steelhead in the Yakima River Basin. We used diet and fish size data from fieldwork in a bioenergetics model and integrated baseline and projected stream temperatures from down-scaled air temperature climate modeling into our analysis. The stream temperature models predicted that daily mean temperatures of salmonid-rearing streams in the basin could increase by 1–2 °C and our bioenergetics simulations indicated that such increases could enhance the growth of steelhead in the spring, but reduce it during the summer. However, differences in growth rates of fish living under different climate change scenarios were minor, ranging from about 1–5 %. Because our analysis focused mostly on the growth responses of steelhead to changes in stream temperatures, further work is needed to fully understand the potential impacts of climate change. Studies should include evaluating changing stream flows on fish activity and energy budgets, responses of aquatic insects to climate change, and integration of bioenergetics, population dynamics, and habitat responses to climate change.     

Simulation of leaf blast infection in tropical rice agro-ecology under climate change scenario

Assessing disease risk has become an important component in the development of climate change adaptation strategies. Here, the infection ability of leaf blast (Magnaporthe oryzae) was modeled based on the epidemiological parameters of minimum (T _min), optimum (T _opt), and maximum (T _max) temperatures for sporulation and lesion development. An infection ability response curve was used to assess the impact of rising temperature on the disease. The simulated spatial pattern of the infection ability index (IAI) corresponded with observed leaf blast occurrence in Indo-Gangetic plains (IGP). The IAI for leaf blast is projected to increase during the winter season (December–March) in 2020 (2010–2039) and 2050 (2040–2069) climate scenarios due to temperature rise, particularly in lower latitudes. However, during monsoon season (July–October), the IAI is projected to remain unchanged or even reduce across the IGP. The results show that the response curve may be successfully used to assess the impact of climate change on leaf blast in rice. The model could be further extended with a crop model to assess yield loss.     

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     

气候变化对我国江南双季稻生产可能影响的数值模拟研究

在利用田间试验资料对双季稻生长动力（态）模拟模型进行验证的基础上,将基于GCMs的输出和历史气候资料相结合的气候变化情景与双季稻模式相连接,就气候变暖对我国江南双季稻主产区水稻生产的可能影响进行网格化定量模拟和客观评估,并就调整对策（改变播种日期和种植品种）在减缓气候变暖对双季稻生产影响中的作用作了初步的探讨。结果表明,在未来可能的气候变化情景下,若维持目前的品种和生产技术措施,双季稻产量将有不同程度的下降。产量变化的地域分布既有一定的规律性,又体现出气候变化影响的复杂性。适应对策分析表明,改种长生育期的     

The Effect of Spatial Scale of Climatic Change Scenarios on Simulated Maize, Winter Wheat, and Rice Production in the Southeastern United States

We use the CERES family of crop models to assess the effect of different spatial scales of climate change scenarios on the simulated yield changes of maize (Zea mays L.), winter wheat (Triticum aestivum L.),and rice (Oryza sativa L.) in the Southeastern United States. The climate change scenarios were produced with the control and doubled CO₂ runs of a high resolution regional climate model anda coarse resolution general circulation model, which provided the initial and lateral boundary conditions for the regional model. Three different cases were considered for each scenario: climate change alone, climate change plus elevated CO₂, and the latter with adaptations. On the state level,for most cases, significant differences in the climate changed yields for corn were found, the coarse scale scenario usually producing larger modeled yield decreases or smaller increases. For wheat, however, which suffered large decreases in yields for all cases, very little contrast in yield based on scale of scenario was found. Scenario scale resulted in significantly different rice yields, but mainly because of low variability in yields. For maize the primary climate variable that explained the contrast in the yields calculated from the two scenarios is the precipitation during grain fill leading to different water stress levels. Temperature during vernalization explains some contrasts in winter wheat yields. With adaptation, the contrasts in the yields of all crops produced by the scenarios were reduced but not entirely removed. Our results indicate that spatial resolution of climate change scenarios can be an important uncertainty in climate change impact assessments, depending on the crop and management conditions.     

Climate change scenarios for global impacts studies

We describe a set of global climate change scenarios that have been used in a series of studies investigating the global impacts of climate change on several environmental systems and resources — ecosystems, food security, water resources, malaria and coastal flooding. These scenarios derive from modelling experiments completed by the Hadley Centre over the last four years using successive versions of their coupled ocean–atmosphere global climate model. The scenarios benefit from ensemble simulations (made using HadCM2) and from an un-flux-corrected experiment (made using HadCM3), but consider only the effects of increasing greenhouse gas concentrations. The effects of associated changes in sulphate aerosol concentrations are not considered. The scenarios are presented for three future time periods — 30-year means centred on the 2020s, the 2050s and the 2080s — and are expressed with respect to the mean 1961–1990 climate. A global land observed climatology at 0.5° latitude/longitude resolution is used to describe current climate. Other scenario variables — atmospheric CO₂ concentrations, global-mean sea-level rise and non-climatic assumptions relating to population and economy — are also provided. We discuss the limitations of the created scenarios and in particular draw attention to sources of uncertainty that we have not fully sampled.     

Assessing the impact of climate changes on the potential yields of maize and paddy rice in Northeast China by 2050

Northeast China is the main crop production region in China, and future climate change will directly impact crop potential yields, so exploring crop potential yields under future climate scenarios in Northeast China is extremely critical for ensuring future food security. Here, this study projected the climate changes using 12 general circulation models (GCMs) under two moderate Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and 6.0) from 2015 to 2050. Then, based on the Global Agro-ecological Zones (GAEZ) model, we explored the effect of climate change on the potential yields of maize and paddy rice in Northeast China during 2015–2050. The annual relative humidity increased almost throughout the Northeast China under two RCPs. The annual precipitation increased more than 400 mm in some west, east, and south areas under RCP 4.5, but decreased slightly in some areas under RCP 6.0. The annual wind speed increased over 2 m/s in the west region. The annual net solar radiation changes varied significantly with latitude, but the changes of annual maximum temperature and minimum temperature were closely related to the terrain. Under RCP 4.5, the average maize potential yield increased by 34.31% under the influence of climate changes from 2015 to 2050. The average rice potential yield increased by 16.82% from 2015 to 2050. Under RCP 6.0, the average maize and rice potential yields increased by 25.65% and 6.34% respectively. The changes of maize potential yields were positively correlated with the changes of precipitation, wind speed, and net solar radiation (the correlation coefficients were > 0.2), and negatively correlated with the changes of relative humidity, minimum and maximum temperature under two RCPs. The changes of rice potential yields were positively correlated with the changes of precipitation (correlation coefficient = 0.15) under RCP 4.5. Under RCP 6.0, it had a slight positive correlation with net solar radiation, relative humidity, and wind speed.     

Spatial modelling of rice yield losses in Tanzania due to bacterial leaf blight and leaf blast in a changing climate

Rice is the most rapidly growing staple food in Africa and although rice production is steadily increasing, the consumption is still out-pacing the production. In Tanzania, two important diseases in rice production are leaf blast caused by Magnaporthe oryzae and bacterial leaf blight caused by Xanthomonas oryzae pv. oryzae. The objective of this study was to quantify rice yield losses due to these two important diseases under a changing climate. We found that bacterial leaf blight is predicted to increase causing greater losses than leaf blast in the future, with losses due to leaf blast declining. The results of this study indicate that the effects of climate change on plant disease can not only be expected to be uneven across diseases but also across geographies, as in some geographic areas losses increase but decrease in others for the same disease.     

Evaluating observed and projected future climate changes for the Arctic using the K?ppen-Trewartha climate classification

The ecosystems in the Arctic region are known to be very sensitive to climate changes. The accelerated warming for the past several decades has profoundly influenced the lives of the native populations and ecosystems in the Arctic. Given that the K?ppen-Trewartha (K-T) climate classification is based on reliable variations of land-surface types (especially vegetation), this study used the K-T scheme to evaluate climate changes and their impact on vegetation for the Arctic (north of 50°N) by analyzing observations as well as model simulations for the period 1900–2099. The models include 16 fully coupled global climate models from the Intergovernmental Panel on Climate Change Fourth Assessment. By the end of this century, the annual-mean surface temperature averaged over Arctic land regions is projected to increase by 3.1, 4.6 and 5.3°C under the Special Report on Emissions Scenario (SRES) B1, A1b, and A2 emission scenarios, respectively. Increasing temperature favors a northward expansion of temperate climate (i.e., Dc and Do in the K-T classification) and boreal oceanic climate (i.e., Eo) types into areas previously covered by boreal continental climate (i.e., Ec) and tundra; and tundra into areas occupied by permanent ice. The tundra region is projected to shrink by ?1.86?×?10⁶?km² (?33.0%) in B1, ?2.4?×?10⁶?km² (?42.6%) in A1b, and ?2.5?×?10⁶?km² (?44.2%) in A2 scenarios by the end of this century. The Ec climate type retreats at least 5° poleward of its present location, resulting in ?18.9, ?30.2, and ?37.1% declines in areal coverage under the B1, A1b and A2 scenarios, respectively. The temperate climate types (Dc and Do) advance and take over the area previously covered by Ec. The area covered by Dc climate expands by 4.61?×?10⁶?km² (84.6%) in B1, 6.88?×?10⁶?km² (126.4%) in A1b, and 8.16?×?10⁶?km² (149.6%) in A2 scenarios. The projected redistributions of K-T climate types also differ regionally. In northern Europe and Alaska, the warming may cause more rapid expansion of temperate climate types. Overall, the climate types in 25, 39.1, and 45% of the entire Arctic region are projected to change by the end of this century under the B1, A1b, and A2 scenarios, respectively. Because the K-T climate classification was constructed on the basis of vegetation types, and each K-T climate type is closely associated with certain prevalent vegetation species, the projected large shift in climate types suggests extensive broad-scale redistribution of prevalent ecoregions in the Arctic.     

Sea water surface energy balance in the Arctic fjord (Hornsund,SW Spitsbergen) in May–November 2014

Maize is grown by millions of smallholder farmers in South Asia (SA) under diverse environments. The crop is grown in different seasons in a year with varying exposure to weather extremes, including high temperatures at critical growth stages which are expected to increase with climate change. This study assesses the impact of current and future heat stress on maize and the benefit of heat-tolerant varieties in SA. Annual mean maximum temperatures may increase by 1.4–1.8 °C in 2030 and 2.1–2.6 °C in 2050, with large monthly, seasonal, and spatial variations across SA. The extent of heat stressed areas in SA could increase by up to 12 % in 2030 and 21 % in 2050 relative to the baseline. The impact of heat stress and the benefit from heat-tolerant varieties vary with the level of temperature increase and planting season. At a regional scale, climate change would reduce rainfed maize yield by an average of 3.3–6.4 % in 2030 and 5.2–12.2 % in 2050 and irrigated yield by 3–8 % in 2030 and 5–14 % in 2050 if current varieties were grown under the future climate. Under projected climate, heat-tolerant varieties could minimize yield loss (relative to current maize varieties) by up to 36 and 93 % in 2030 and 33 and 86 % in 2050 under rainfed and irrigated conditions, respectively. Heat-tolerant maize varieties, therefore, have the potential to shield maize farmers from severe yield loss due to heat stress and help them adapt to climate change impacts.     

Effects of climate change on grain maize yield potential in the european community

Grain maize yield in the main arable areas of the European Community (E.C.) was calculated with a simulation model, WOFOST, using historical weather data and average soil characteristics. The sensitivity of the model to individual weather variables was determined. Subsequent analyses were made using climate change scenarios with and without the direct effects of increased atmospheric CO₂. The impact of crop management (sowing date, irrigation and cultivar type) in a changed climate was also assessed. Scenario climate change generally results in larger grain yields for the northern E.C., similar or slightly smaller yields for the central E.C. and considerably smaller yields for the southern E.C. The various climate change scenarios used appear to give considerably different changes in grain yield, both for each location and for the E.C. as a whole. Management analyses show that for both current and scenario climates the largest grain yield will be attained by varieties with an early start of grain filling, that average irrigation requirements to attain potential grain yield in the E.C. will increase with climate change but will decrease with both increased CO₂ and climate change, and that sowing at both current and scenarios climate should occur as early as possible.The U.S. Government right to retain a nonexclusive, royalty-free licence in and to any copyright is acknowledged.     

Coral reef ecosystems protect shore from high-energy waves under climate change scenarios

Coral reefs and other coastal ecosystems such as seagrasses and mangroves are widely recognized to provide protection against the devastating effects of strong waves associated with tsunamis and storms. The predicted warming climate brings to fore the role of these ecosystems in providing protection against stronger typhoons that can result in more devastating waves of greater amplitude. We performed a model simulation of storm generated waves on a Philippine reef, which is located along the path of tropical storms, i.e., at least 10 typhoons on the average pass through the study site yearly. A model to simulate wave propagation was developed using Simulating Waves Nearshore (SWAN) and DELFT3D-WAVE computer simulation software. Scenarios involving local monsoonal wind forcing and storm conditions were simulated. In addition, as climate change may also result to increased relative sea level, a 0.3 m and 1 m rise in sea level scenarios were also used in the wave model simulations. Results showed that the extensive reef system in the site helped dissipate wave energy that in turn reduced wave run-up on land. A significant reduction in wave energy was observed in both climate change, i.e., stronger wind and higher sea level, and non-climate change scenarios. This present study was conducted in a reef whose coral cover is in excellent condition (i.e., 50 to 80% coral cover). Estimates of coral reef growth are in the same order of magnitude as estimates of relative sea level rise based on tide gauge and satellite altimeter data, thus it is possible that the role of reefs in attenuating wave energy may be maintained if coral reef growth can keep up with the change in sea level. Nonetheless, to maintain reef growth, it is imperative to manage coral reef ecosystems sustainably and to eliminate the stressors that are within human control. Minimizing activities such as illegal and destructive blast and poison fishing methods, pollution and siltation, is crucial to minimize the impacts of high-energy waves that may increase with climate change.     

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.     

Projections of high resolution climate changes for South Korea using multiple-regional climate models based on four RCP scenarios. Part 1: surface air temperature

We projected surface air temperature changes over South Korea during the mid (2026-2050) and late (2076-2100) 21st century against the current climate (1981-2005) using the simulation results from five regional climate models (RCMs) driven by Hadley Centre Global Environmental Model, version 2, coupled with the Atmosphere- Ocean (HadGEM2-AO), and two ensemble methods (equal weighted averaging, weighted averaging based on Taylor’s skill score) under four Representative Concentration Pathways (RCP) scenarios. In general, the five RCM ensembles captured the spatial and seasonal variations, and probability distribution of temperature over South Korea reasonably compared to observation. They particularly showed a good performance in simulating annual temperature range compared to HadGEM2-AO. In future simulation, the temperature over South Korea will increase significantly for all scenarios and seasons. Stronger warming trends are projected in the late 21st century than in the mid-21st century, in particular under RCP8.5. The five RCM ensembles projected that temperature changes for the mid/late 21st century relative to the current climate are +1.54°C/+1.92°C for RCP2.6, +1.68°C/+2.91°C for RCP4.5, +1.17°C/+3.11°C for RCP6.0, and +1.75°C/+4.73°C for RCP8.5. Compared to the temperature projection of HadGEM2-AO, the five RCM ensembles projected smaller increases in temperature for all RCP scenarios and seasons. The inter-RCM spread is proportional to the simulation period (i.e., larger in the late-21st than mid-21st century) and significantly greater (about four times) in winter than summer for all RCP scenarios. Therefore, the modeled predictions of temperature increases during the late 21st century, particularly for winter temperatures, should be used with caution.     

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.