A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

Spatial Analysis of Environmental Change Impacts on Wheat Production in Mid-Lower North, South Australia

Three environmental change scenarios (the best scenario, the most likely scenario and the worst scenario) were used by the APSIM (Agricultural Production System sIMulator) Wheat module to study the possible impacts of future environmental change (climate change plus pCO₂ change) on wheat production in the Mid-Lower North of South Australia. GIS software was used to manage spatial-climate data and spatial-soil data and to present the results. Study results show that grain yield (kg ha⁻¹) was adversely affected under the worst environmental change scenario (−100% ∼ −42%) and the most likely environmental change scenario (−58% ∼ −3%). Grain nitrogen content (% N) either increased or decreased depending on the environmental change scenarios used and climate divisions (−25% ∼ +42%). Spatial variability was found for projected impact outcomes within climate divisions indicating the necessity of including the spatial distribution of soil properties in impact assessment.     

Changes of Accumulated Temperature, Growing Season and Precipitation in the North China Plain from 1961 to 2009

Using the high-quality observed meteorological data, changes of the thermal conditions and precipitation over the North China Plain from 1961 to 2009 were examined. Trends of accumulated temperature and negative temperature, growing season duration, as well as seasonal and annual rainfalls at 48 stations were analyzed. The results show that the accumulated temperature increased significantly by 348.5℃ day due to global warming during 1961-2009 while the absolute accumulated negative temperature decreased apparently by 175.3℃ day. The start of growing season displayed a significant negative trend of -14.3 days during 1961- 2009, but the end of growing season delayed insignificantly by 6.7 days. As a result, the length of growing season increased by 21.0 days. The annual and autumn rainfalls decreased slightly while summer rainfall and summer rainy days decreased significantly. In contrast, spring rainfall increased slightly without significant trends. All the results indicate that the thermal conditions were improved to benefit the crop growth over the North China Plain during 1961-2009, and the decreasing annual and summer rainfalls had no direct negative impact on the crop growth. But the decreasing summer rainfall was likely to influence the water resources in North China, especially the underground water, reservoir water, as well as river runoff, which would have influenced the irrigation of agriculture.     

Differences and sensitivities in potential hydrologic impact of climate change to regional-scale Athabasca and Fraser River basins of the leeward and windward sides of the Canadian Rocky Mountains respectively

Sensitivities to the potential impact of Climate Change on the water resources of the Athabasca River Basin (ARB) and Fraser River Basin (FRB) were investigated. The Special Report on Emissions Scenarios (SRES) of IPCC projected by seven general circulation models (GCM), namely, Japan’s CCSRNIES, Canada’s CGCM2, Australia’s CSIROMk2b, Germany’s ECHAM4, the USA’s GFDLR30, the UK’s HadCM3, and the USA’s NCARPCM, driven under four SRES climate scenarios (A1FI, A2, B1, and B2) over three 30-year time periods (2010–2039, 2040–2069, 2070–2100) were used in these studies. The change fields over these three 30-year time periods are assessed with respect to the 1961–1990, 30-year climate normal and based on the 1961–1990 European Community Mid-Weather Forecast (ECMWF) re-analysis data (ERA-40), which were adjusted with respect to the higher resolution GEM forecast archive of Environment Canada, and used to drive the Modified ISBA (MISBA) of Kerkhoven and Gan (Adv Water Resour 29(6):808–826, 2006). In the ARB, the shortened snowfall season and increased sublimation together lead to a decline in the spring snowpack, and mean annual flows are expected to decline with the runoff coefficient dropping by about 8% per °C rise in temperature. Although the wettest scenarios predict mild increases in annual runoff in the first half of the century, all GCM and emission combinations predict large declines by the end of the twenty-first century with an average change in the annual runoff, mean maximum annual flow and mean minimum annual flow of −21%, −4.4%, and −41%, respectively. The climate scenarios in the FRB present a less clear picture of streamflows in the twenty-first century. All 18 GCM projections suggest mean annual flows in the FRB should change by ±10% with eight projections suggesting increases and 10 projecting decreases in the mean annual flow. This stark contrast with the ARB results is due to the FRB’s much milder climate. Therefore under SRES scenarios, much of the FRB is projected to become warmer than 0°C for most of the calendar year, resulting in a decline in FRB’s characteristic snow fed annual hydrograph response, which also results in a large decline in the average maximum flow rate. Generalized equations relating mean annual runoff, mean annual minimum flows, and mean annual maximum flows to changes in rainfall, snowfall, winter temperature, and summer temperature show that flow rates in both basins are more sensitive to changes in winter than summer temperature.     

Assessing the impact of climate change on representative field crops in Israeli agriculture: a case study of wheat and cotton

Climate changes, associated with accumulation of greenhouse gases, are expected to have a profound influence on agricultural sustainability in Israel, a semi-arid area characterized by a cold wet winter and a dry warm summer. Accordingly this study explored economic aspects of agricultural production under projected climate-change scenarios by the “production function” approach, as applied to two representative crops: wheat, as the major crop grown in Israel’s dry southern region, and cotton, representing the more humid climate in the north. Adjusting outputs of the global climate model HadCM3 to the specific research locations, we generated projections for 2070–2100 temperatures and precipitations for two climate change scenarios. Results for wheat vary among climate scenarios; net revenues become negative under the severe scenario (change from −145 to −273%), but may increase under the moderate one (−43 to +35%), depending on nitrogen applied to the crop. Distribution of rain events was found to play a major role in determining yields. By contrast, under both scenarios cotton experiences a considerable decrease in yield with significant economic losses (−240 and −173% in A2 and B2 scenarios, respectively). Additional irrigation and nitrogen may reduce farming losses, unlike changes in seeding dates.     

North Sea – Caspian Pattern (NCP) – an upper level atmospheric teleconnection affecting the eastern Mediterranean – implications on the regional climate

Summary ?A calendar of the negative and positive phases of the North Sea – Caspian Pattern (NCP) for the period 1958–1998 was used to analyse the implication of the NCP upper level teleconnections on the regional climate of the eastern Mediterranean basin. Series of monthly mean air temperature and monthly total rainfall from 33 stations across Greece, Turkey and Israel, for the same period, were used. For each month, from October to April, averages of the monthly mean temperatures and the monthly rainfall totals as well as the standardized values of both parameters were calculated separately for the negative (NCP (−)) and the positive (NCP (+)) phases of the NCP. At all stations and in all months, temperature values were significantly higher during the NCP (−) as compared with the NCP (+). Furthermore, apart from very few exceptions, the absolute monthly mean maximum and monthly mean minimum values were obtained during the NCP (−) and the NCP (+) phases, respectively. The maximum impact of the NCP on mean air temperature was detected in the continental Anatolian Plateau, where the mean seasonal differences are around 3.5 °C. This influence decreases westwards and southwards. The influence on the rainfall regime is more complex. Regions exposed to the southern maritime trajectories, in Greece and in Turkey, receive more rainfall during the NCP (−) phase, whereas in the regions exposed to the northern maritime trajectories, such as Crete in Greece, the Black Sea region in Turkey, and in all regions of Israel, there is more rainfall during the NCP (+) phase. The accumulated rainfall differences between the two phases are over 50% of the seasonal average for some stations. A comparison of the capabilities of the NCP, the North Atlantic Oscillation (NAO) and the Southern Oscillation (SO) indices to differentiate between below and above normal temperatures was made. The results have placed the NCP, as the best by far of all three teleconnections in its ability to differentiate between below or above normal temperatures and as the main teleconnection affecting the climate of the Balkans, the Anatolian Peninsula and the Middle East. These results may serve to downscale General Circulation Model (GCM) scenarios to a regional scale and provide forecasts regarding eventual temperature and/or precipitation changes. Received June 25, 2001; revised February 25, 2002; accepted March 3, 2002     

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.     

A comparison of explicit and implicit spatial downscaling of GCM output for soil erosion and crop production assessments

Spatial downscaling of climate change scenarios can be a significant source of uncertainty in simulating climatic impacts on soil erosion, hydrology, and crop production. The objective of this study is to compare responses of simulated soil erosion, surface hydrology, and wheat and maize yields to two (implicit and explicit) spatial downscaling methods used to downscale the A2a, B2a, and GGa1 climate change scenarios projected by the Hadley Centre’s global climate model (HadCM3). The explicit method, in contrast to the implicit method, explicitly considers spatial differences of climate scenarios and variability during downscaling. Monthly projections of precipitation and temperature during 1950–2039 were used in the implicit and explicit spatial downscaling. A stochastic weather generator (CLIGEN) was then used to disaggregate monthly values to daily weather series following the spatial downscaling. The Water Erosion Prediction Project (WEPP) model was run for a wheat–wheat–maize rotation under conventional tillage at the 8.7 and 17.6% slopes in southern Loess Plateau of China. Both explicit and implicit methods projected general increases in annual precipitation and temperature during 2010–2039 at the Changwu station. However, relative climate changes downscaled by the explicit method, as compared to the implicit method, appeared more dynamic or variable. Consequently, the responses to climate change, simulated with the explicit method, seemed more dynamic and sensitive. For a 1% increase in precipitation, percent increases in average annual runoff (soil loss) were 3–6 (4–10) times greater with the explicit method than those with the implicit method. Differences in grain yield were also found between the two methods. These contrasting results between the two methods indicate that spatial downscaling of climate change scenarios can be a significant source of uncertainty, and further underscore the importance of proper spatial treatments of climate change scenarios, and especially climate variability, prior to impact simulation. The implicit method, which applies aggregated climate changes at the GCM grid scale directly to a target station, is more appropriate for simulating a first-order regional response of nature resources to climate change. But for the site-specific impact assessments, especially for entities that are heavily influenced by local conditions such as soil loss and crop yield, the explicit method must be used.     

Study on the Impacts of Climate Change on China's Agriculture

This paper measures the economic impacts of climate change on China's agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on China's agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios.     

Variations in Vegetation Net Primary Production in the Qinghai-Xizang Plateau, China, from 1982 to 1999

Vegetation net primary production (NPP) derived from a carbon model (Carnegie–Ames–Stanford Approach, CASA) and its interannual change in the Qinghai-Xizang (Tibetan) Plateau were investigated in this study using 1982–1999 time series data sets of normalized difference vegetation index (NDVI) and paired ground-based information on vegetation, climate, soil, and solar radiation. The 18-year averaged annual NPP over the plateau was 125 g C m⁻² yr⁻¹, decreasing from the southeast to the northwest, consistent with precipitation and temperature patterns. Total annual NPP was estimated between 0.183 and 0.244 Pg C over the 18 years, with an average of 0.212 Pg C (1 Pg = 10¹⁵ g). Two distinct periods (1982–1990 and 1991–1999) of NPP variation were observed, separated by a sharp reduction during 1990–1991. From 1982 to 1990, annual NPP did not show a significant trend, while from 1991 to 1999 a marked increase of 0.007 Pg C yr⁻² was observed. NPP trends for most vegetation types resembled that of the whole plateau. The largest annual NPP increase during 1991–1999 appeared in alpine meadows, accounting for 32.3% of the increment of the whole region. Changes in solar radiation and temperature significantly influenced NPP variation, suggesting that solar radiation may be one of the major factors associated with changes in NPP.     

Severe climate-induced water shortage and extremes in Crete

Climate change is expected to have a significant impact on the hydrologic cycle, creating changes in freshwater resources. The Intergovernmental Panel on Climate Change (IPCC) predicts that, as a result, floods and prolonged droughts will take place at increasingly frequent periods. The Mediterranean has been described as one of the main climate change “hot-spots”, with recent simulations showing a collective picture of substantial drying and warming. This effect appears more pronounced during warm periods, when the seasonal decrease of precipitation can exceed control climatology by 25–30%. Despite the decreasing annual rainfall trend, an increase in the amount and intensity of wintertime rainfall is evident. However, the scientific question on the quantitative impact of these signals to small scale coastal watersheds and Mediterranean islands has not been answered. The state-of-the-art Ensembles dataset was employed to assess the impact of the changing climate on the water availability of the island of Crete at basin scale. Here, the Ensembles precipitation and temperature data is used as input for a rainfall–runoff model previous calibrated for the whole island with the principle of regionalization. Data analysis for the period 1970–2100 reveals an overall decreasing precipitation trend which, combined with a temperature rise, leads to substantial reduction of water availability. Quantitative results of hydrological change provide the data required to improve knowledge and adaptation policy to water shortages.     

Projections of Extreme Rainfall in Hong Kong in the 21st Century

The possible changes in the frequency of extreme rainfall events in Hong Kong in the 21st century wereinvestigated by statistically downscaling 30 sets of the daily global climate model projections (involvinga combination of 12 models and 3 greenhouse gas emission scenarios,namely,A2,A1B,and B1) of theFourth Assessment Report of the Intergovernmental Panel on Climate Change.To cater for the intermittentand skewed character of the daily rainfall,multiple stepwise logistic regression and multiple stepwise linearregression were employed to develop the downscaling models for predicting rainfall occurrence and rainfallamount,respectively.Verification of the simulation of the 1971-2000 climate reveals that the models ingeneral have an acceptable skill in reproducing past statistics of extreme rainfall events in Hong Kong.Theprojection results suggest that,in the 21st century,the annual number of rain days in Hong Kong is expectedto decrease while the daily rainfall intensity will increase,concurrent with the expected increase in annualrainfall.Based on the multi-model scenario ensemble mean,the annual number of rain day is expected todrop from 104 days in 1980-1999 to about 77 days in 2090-2099.For extreme rainfall events,about 90% ofthe model-scenario combinations indicate an increase in the annual number of days with daily rainfall 100mm (R100) towards the end of the 21st century.The mean number of R100 is expected to increase from 3.5days in 1980-1999 to about 5.3 days in 2090-2099.The projected changes in other extreme rainfall indicesalso suggest that the rainfall in Hong Kong in the 21st century may also become more extreme with moreuneven distributions of wet and dry periods.While most of the model-emission scenarios in general projectconsistent trends in the change of rainfall extremes in the 21st century,there is a large divergence in theprojections among different model/emission scenarios.This reflects that there are still large uncertainties inmodel simulations of future extreme rainfall events.     

Projection of Extreme Temperatures in Hong Kong in the 21st Century

The possible changes in the frequency of extreme temperature events in Hong Kong in the 21st century were investigated by statistically downscaling 26 sets of the daily global climate model projections (a combination of 11 models and 3 greenhouse gas emission scenarios, namely A2, A1B, and B1) of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The models’ performance in simulating the past climate during 1971–2000 has also been verified and discussed. The verification revealed that the models in general have an acceptable skill in reproducing past statistics of extreme temperature events. Moreover, the models are more skillful in simulating the past climate of the hot nights and cold days than that of the very hot days. The projection results suggested that, in the 21st century, the frequency of occurrence of extremely high temperature events in Hong Kong would increase significantly while that of the extremely low temperature events is expected to drop significantly. Based on the multi-model scenario ensemble mean, the average annual numbers of very hot days and hot nights in Hong Kong are expected to increase significantly from 9 days and 16 nights in 1980–1999 to 89 days and 137 nights respectively in 2090–2099. On the other hand, the average annual number of cold days will drop from 17 days in 1980–1999 to about 1 day in 2090–2099. About 65 percent of the model-scenario combinations indicate that there will be on average less than one cold day in 2090–2099. While all the model-emission scenarios in general have projected consistent trends in the change of temperature extremes in the 21st century, there is a large divergence in the projections between difierent model/emission scenarios. This reflects that there are still large uncertainties in the model simulation of the future climate of extreme temperature events.     

Modelling the impacts of climate change on wheat yield and field water balance over the Murray�CDarling Basin in Australia

The study used a modelling approach to assess the potential impacts of likely climate change and increase in CO₂ concentration on the wheat growth and water balance in Murray?CDarling Basin in Australia. Impacts of individual changes in temperature, rainfall or CO₂ concentration as, well as the 2050 and 2070 climate change scenarios, were analysed. Along an E?CW transect, wheat yield at western sites (warmer and drier) was simulated to be more sensitive to temperature increase than that at eastern sites; along the S?CN transect, wheat yield at northern warmer sites was simulated to be more sensitive to temperature increase, within 1?C3°C temperature increase. Along the E?CW and S?CN transects, wheat at drier sites would benefit more from elevated [CO₂] than at wetter sites, but more sensitive to the decline in rainfall. The increase in temperature only did not have much impact on water balance. Elevated [CO₂] increased the drainage in all the sites, whilst rainfall reduction decreased evapotranspiration, runoff and drainage, especially at drier sites. In 2050, wheat yield would increase by 1?C10% under all climate change scenarios along the S?CN transect, except for the northernmost site (Dalby). Along the E?CW transect, the most obvious increase of wheat yields under all climate change scenarios occurred in cooler and wetter eastern sites (Yass and Young), with an average increase rate of 7%. The biggest loss occurred at the driest sites (Griffith and Swan Hill) under A1FI and B2 scenarios, ranging from ?5% to ?16%. In 2070, there would be an increased risk of yield loss in general, except for the cool and wet sites. Water use efficiency was simulated to increase at most of the study sites under all the climate change scenarios, except for the driest site. Yield variability would increase at drier sites (Ardlethan, Griffith and Swan Hill). Soil types would also impact on the response of wheat yield and water balance to future climate change.     

Modelling China’s potential maize production at regional scale under climate change

With the continuing warming due to greenhouse gases concentration, it is important to examine the potential impacts on regional crop production spatially and temporally. We assessed China’s potential maize production at 50 × 50 km grid scale under climate change scenarios using modelling approach. Two climate changes scenarios (A2 and B2) and three time slices (2011–2040, 2041–2070, 2071–2100) produced by the PRECIS Regional Climate Model were used. Rain-fed and irrigated maize yields were simulated with the CERES-Maize model, with present optimum management practices. The model was run for 30 years of baseline climate and three time slices for the two climate change scenarios, without and with simulation of direct CO₂ fertilization effects. Crop simulation results under climate change scenarios varied considerably between regions and years. Without the CO₂ fertilization effect, China’s maize production was predicted to suffer a negative effect under both A2 and B2 scenarios for all time slices, with greatest production decreases in today’s major maize planting areas. When the CO₂ fertilization effect is taken into account, production was predicted to increase for rain-fed maize but decrease for irrigated maize, under both A2 and B2 scenarios for most time periods.     

Future projections of winter rainfall in southeast Australia using a statistical downscaling technique

Much of southeast Australia has experienced rainfall substantially below the long-term average since 1997. This protracted drought is particularly noticeable in those parts of South Australia and Victoria which experience a winter (May through October) rainfall peak. For the most part, the recent meteorological drought has affected the first half of the rainfall season May–June–July (MJJ), while rainfall during the second half August–September–October (ASO) has been much closer to the long term average. The recent multi-year drought is without precedent in the instrumental record, and is qualitatively similar to the abrupt decline in rainfall which was observed in the southwest of Western Australia in the 1960 and 1970s. Using a statistical downscaling technique, the rainfall decline is linked to observed changes in large-scale atmospheric fields (mean sea level pressure and precipitable water). This technique is able to reproduce the statistical properties of rainfall in southeast Australia, including the interannual variability and longer time-scale changes. This has revealed that the rainfall recent decline may be explained by a shift to higher pressures and lower atmospheric precipitable water in the region. To explore the likely future evolution of rainfall in southeast Australia under human induced climate change, the same statistical downscaling technique is applied to five climate models forced with increasing greenhouse gas concentrations. This reveals that average rainfall in the region is likely to decline in the future as greenhouse gas concentrations increase, with the greatest decline occurring during the first half of winter. Projected declines vary amongst models but are generally smaller than the recent early winter rainfall deficits. In contrast, the rainfall decline in late winter–spring is larger in future projections than the recent rainfall deficits have been. We illustrate the consequences of the observed and projected rainfall declines on water supply to the major city of Melbourne, using a simple rainfall run-off relationship. This suggests that the water resources may be dramatically affected by future climate change, with percentage reductions approximately twice as large as corresponding changes in rainfall.     

Sensitivity of southern African maize yields to the definition of sowing dekad in a changing climate

Most African countries struggle with food production and food security. These issues are expected to be even more severe in the face of climate change. Our study examines the likely impacts of climate change on agriculture with a view to propose adaptation options, especially in hard hit regions. We use a crop model to evaluate the impact of various sowing decisions on the water satisfaction index (WSI) and thus the yield of maize crop. The crop model is run for 176 stations over southern Africa, subject to climate scenarios downscaled from 6 GCMs. The sensitivity of these simulations is analysed so as to distinguish the contributions of sowing decisions to yield variation. We compare the WSI change between a 20 year control period (1979–1999) and a 20 year future period (2046–2065) over southern Africa. These results highlight areas that will likely be negatively affected by climate change over the study region. We then calculate the contribution of sowing decisions to yield variation, first for the control period, then for the future period. This contribution (sensitivity) allows us to distinguish the efficiency of adaptation decisions under both present and future climate. In most countries rainfall in the sowing dekad is shown to contribute more significantly to the yield variation and appears as a long term efficient decision to adapt. We discuss these results and additional perspectives in order to propose local adaptation directions.     

Where are Germany’s gains from Kyoto? Estimating the effects of global warming on agriculture

Motivated by the high abatement costs of the Kyoto Protocol for Germany, this paper is estimating the economic impact of global warming on agriculture in that country. The hedonic approach is used as theoretical background. Stating that land prices are – among others – determined by climatic factors, this approach can consequently be used to value global warming. To avoid a priori restrictions stemming from functional forms, the land price function is modeled as quadratic Box–Cox function that nests a wide range of specifications. In a second step, the estimated results are used to forecast the impact of climate change. The results indicate that German farmers will be winners of climate change in the short run, with maximum gains occurring at a temperature increase of +0.6°C against current levels. In the long run, there may be losses from global warming. However, the net present value from climate change is under the most probable scenarios positive.     

Climate change and critical thresholds in China’s food security

Identification of ‘critical thresholds’ of temperature increase is an essential task for inform policy decisions on establishing greenhouse gas (GHG) emission targets. We use the A2 (medium-high GHG emission pathway) and B2 (medium-low) climate change scenarios produced by the Regional Climate Model PRECIS, the crop model – CERES, and socio-economic scenarios described by IPCC SRES, to simulate the average yield changes per hectare of three main grain crops (rice, wheat, and maize) at 50 km × 50 km scale. The threshold of food production to temperature increases was analyzed based on the relationship between yield changes and temperature rise, and then food security was discussed corresponding to each IPCC SRES scenario. The results show that without the CO₂ fertilization effect in the analysis, the yield per hectare for the three crops would fall consistently as temperature rises beyond 2.5 ^{^}C; when the CO₂ fertilization effect was included in the simulation, there were no adverse impacts on China’s food production under the projected range of temperature rise (0.9–3.9 ^{^}C). A critical threshold of temperature increase was not found for food production. When the socio-economic scenarios, agricultural technology development and international trade were incorporated in the analysis, China’s internal food production would meet a critical threshold of basic demand (300 kg/capita) while it would not under A2 (no CO₂ fertilization); whereas basic food demand would be satisfied under both A2 and B2, and would even meet a higher food demand threshold required to sustain economic growth (400 kg/capita) under B2, when CO₂ fertilization was considered.