The impact of climate change on the risk of forest and grassland fires in Australia

We explore the impact of future climate change on the risk of forest and grassland fires over Australia in January using a high resolution regional climate model, driven at the boundaries by data from a transitory coupled climate model. Two future emission scenarios (relatively high and relatively low) are used for 2050 and 2100 and four realizations for each time period and each emission scenario are run. Results show a consistent increase in regional-scale fire risk over Australia driven principally by warming and reductions in relative humidity in all simulations, under all emission scenarios and at all time periods. We calculate the probability density function for the fire risk for a single point in New South Wales and show that the probability of extreme fire risk increases by around 25% compared to the present day in 2050 under both relatively low and relatively high emissions, and that this increases by a further 20% under the relatively low emission scenario by 2100. The increase in the probability of extreme fire risk increases dramatically under the high emission scenario by 2100. Our results are broadly in-line with earlier analyses despite our use of a significantly different methodology and we therefore conclude that the likelihood of a significant increase in fire risk over Australia resulting from climate change is very high. While there is already substantial investment in fire-related management in Australia, our results indicate that this investment is likely to have to increase to maintain the present fire-related losses in Australia.     

Modeling the impacts of climate change on nitrogen retention in a 4th order stream

Climate induced changes of temperature, discharge and nitrogen concentration may change natural denitrification processes in river systems. Until now seasonal variation of N-retention by denitrification under different climate scenarios and the impact of river morphology on denitrification have not been thoroughly investigated. In this study climate scenarios (dry, medium and wet) have been used to characterize changing climatic and flow conditions for the period 2050–2054 in the 4th order stream Weiße Elster, Germany. Present and future periods of nitrogen turnover were simulated with the WASP5 river water quality model. Results revealed that, for a dry climate scenario, the mean denitrification rate was 71% higher in summer (low flow period between 2050 and 2054) and 51% higher in winter (high flow period) compared to the reference period. For the medium and wet climate scenarios, denitrification was slightly higher in summer (3% and 4%) and lower in winter (9% and 3% for medium and wet scenarios, respectively). Additionally, the variability of denitrification rates was higher in summer compared to winter conditions. For a natural river section, denitrification was a factor of 1.22 higher than for a canalized river reach. Besides, weirs along the river decrease the denitrification rate by 16% in July for dry scenario conditions. In the 42 km study reach, N-retention through denitrification amounted to 5.1% of the upper boundary N load during summer low flow conditions in the reference period. For the future dry climate scenario this value increased up to 10.2% and for the medium climate scenario up to 5.4%. In our case study the investigated climate scenarios showed that future discharge changes may have a larger impact on denitrification rates than future temperature changes. Overall results of the study revealed the significance of climate change in regulating the magnitude, seasonal pattern and variability of nitrogen retention. The results provide guidance for managing nitrogen related environmental problems for present and future climate conditions.     

巴黎协定背景下全球减排博弈模拟研究

构建了具有7个国家集团的全球多国家集团气候博弈集成评估模拟系统,针对《巴黎协定》背景下各国至2050年以及2100年的减排目标,分别对减排博弈的纳什均衡、博弈不确定性以及外部政策对减排博弈的影响展开了模拟分析。研究发现：在基准情景下,全球各国将在2030年后均选择不减排策略,全球至2100年升温达到2.62℃;而模型参数的不确定性也未能突破全球零减排的纳什均衡;而仅当在全球范围内对不减排采取惩罚措施时,全球零减排的纳什均衡点被打破。但在当前《巴黎协定》减排承诺下,为达到2℃的温控目标,加大2030—2050年的减排幅度至关重要,否则全球将在2040年左右突破2℃阈值。     

The role of land surface processes in regional climate change: a case study of future land cover change over south western Australia

Summary Using a high resolution regional climate model we perform multiple January simulations of the impact of land cover change over western Australia. We focus on the potential of reforestation to ameliorate the projected warming over western Australia under two emission scenarios (A2, B2) for 2050 and 2100. Our simulations include the structural and physiological responses of the biosphere to changes in climate and changes in carbon dioxide. We find that reforestation has the potential to reduce the warming caused by the enhanced greenhouse effect by as much as 30% under the A2 and B2 scenarios by 2050 but the cooling effect declines to 10% by 2100 as CO₂-induced warming intensifies. The cooling effect of reforestation over western Australia is caused primarily by the increase in leaf area index that leads to a corresponding increase in the latent heat flux. This cooling effect is localized and there were no simulated changes in temperature over regions remote from land cover change. We also show that the more extreme emission scenario (A2) appears to lead to a more intense response in photosynthesis by 2100. Overall, our results are not encouraging in terms of the potential to offset future warming by large scale reforestation. However, at regional scales the impact of land cover change is reasonably large relative to the impact of increasing carbon dioxide (up to 2050) suggesting that future projections of the Australian climate would benefit from the inclusion of projections of future land cover change. We suggest that this would add realism and regional detail to future projections and perhaps aid detection and attribution studies.     

The impacts of climate change on the winter hardiness zones of woody plants in Europe

The potential impacts of climate change on potatoes cropping in the Peruvian highlands (Altiplano) is assessed using climate projections for 2071–2100, obtained from the HadRM3P regional atmospheric model of the Hadley Centre. The atmospheric model is run under two different special report on emission scenarios: high CO₂ concentration (A2) and moderate CO₂ concentration (B2) for four locations situated in the surroundings of Lake Titicaca. The two main varieties of potato cultivated in the area are studied: the Andean potato (Solanum tuberosum) and the bitter potato (Solanum juzepczukii). A simple process-oriented model is used to quantify the climatic impacts on crops cycles and yields by combining the effects of temperature on phenology, of radiation and CO₂ on maximum yield and of water balance on yield deficit. In future climates, air temperature systematically increases, precipitation tends to increase at the beginning of the rainy season and slightly decreases during the rest of the season. The direct effects of these climatic changes are earlier planting dates, less planting failures and shorter crop cycles in all the four locations and for both scenarios. Consequently, the harvesting dates occur systematically earlier: roughly in January for the Andean potato instead of March in the current situation and in February for the bitter potato instead of April. Overall, yield deficits will be higher under climate change than in the current climate. There will be a strong negative impact on yields for S. tuberosum (stronger under A2 scenario than under B2); the impact on S. juzepczukii yields, however, appears to be relatively mixed and not so negative.     

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.     

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.     

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.     

Future Climate Impact on the Productivity of Sugar Beet (Beta vulgaris L.) in Europe

The impact of future climate change on sugar beet yields is assessed over western Europe using future (2021–2050) climate scenario data from a General Circulation Model (GCM) and the Broom's Barn simulation model of rain-fed crop growth and yield. GCM output for the 1961–1990 period is first compared with observed climate data and shown to be reliable for regions west of 24° E. Comparisons east of this meridian were less reliable with this GCM (HadCM2) and so were omitted from simulations of crop yield. Climate change is expected to bring yield increases of around 1 t/ha of sugar in northern Europe with decreases of a similar magnitude in northern France, Belgium and west/central Poland, for the period 2021–2050. Averaged for the study area (weighted by current regional production), yields show no overall change due to changed climate. However, this figure masks significant increases in yield potential (due to accelerated growth in warmer springs) and in losses due to drought stress. Drought losses are predicted to approximately double in areas with an existing problem and to become a serious new problem in NE France and Belgium. Overall west and central Europe simulated average drought losses rise from 7% (1961–1990) to 18% (2021–2050). The annual variability of yield (as measured by the coefficient of variation) will increase by half, from 10% to 15% compared to 1961–1990, again with potentially serious consequences for the sugar industry. The importance of crop breeding for drought tolerance is further emphasised. These changes are independent of the 9% yield increase which we estimate, on the basis of work by Demmers-Derks et al. (1998), is the likely direct effect of the increase in atmospheric CO₂ concentration by 2021–2050.     

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.     

Mean, interannual variability and trends in a regional climate change experiment over Europe. II: climate change scenarios (2071–2100)

We present an analysis of climate change over Europe as simulated by a regional climate model (RCM) nested within time-slice atmospheric general circulation model (AGCM) experiments. Changes in mean and interannual variability are discussed for the 30-year period of 2071–2100 with respect to the present day period of 1961–1990 under forcing from the A2 and B2 IPCC emission scenarios. In both scenarios, the European region undergoes substantial warming in all seasons, in the range of 1–5.5°C, with the warming being 1–2°C lower in the B2 than in the A2 scenario. The spatial patterns of warming are similar in the two scenarios, with a maximum over eastern Europe in winter and over western and southern Europe in summer. The precipitation changes in the two scenarios also show similar spatial patterns. In winter, precipitation increases over most of Europe (except for the southern Mediterranean regions) due to increased storm activity and higher atmospheric water vapor loadings. In summer, a decrease in precipitation is found over most of western and southern Europe in response to a blocking-like anticyclonic circulation over the northeastern Atlantic which deflects summer storms northward. The precipitation changes in the intermediate seasons (spring and fall) are less pronounced than in winter and summer. Overall, the intensity of daily precipitation events predominantly increases, often also in regions where the mean precipitation decreases. Conversely the number of wet days decreases (leading to longer dry periods) except in the winter over western and central Europe. Cloudiness, snow cover and soil water content show predominant decreases, in many cases also in regions where precipitation increases. Interannual variability of both temperature and precipitation increases substantially in the summer and shows only small changes in the other seasons. A number of statistically significant regional trends are found throughout the scenario simulations, especially for temperature and for the A2 scenario. The results from the forcing AGCM simulations and the nested RCM simulations are generally consistent with each other at the broad scale. However, significant differences in the simulated surface climate changes are found between the two models in the summer, when local physics processes are more important. In addition, substantial fine scale detail in the RCM-produced change signal is found in response to local topographical and coastline features.     

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.     

两种气候变化情景下中国未来的粮食供给

全球温室气体排放导致的全球温度的上升一直是国际社会关注的重点问题之一。利用IPCC（政府间气候变化专门委员会）SRES（排放情景特别报告）的A2（中-高）和B2（中-低）温室气体排放情景，结合区域气候模式PRECIS和CERES作物模型模拟和分析了未来不同的温室气体排放情景下，中国未来2020年、2050年和2080年各个时段粮食的供需情景，并结合未来社会经济的发展分析了气候变化对未来粮食供求的影响，探讨了不同的气候变化程度对未来中国粮食供应的影响。结果表明：如果不考虑CO2的肥效作用，未来我国三种主要粮食作物（小麦、水稻和玉米）均以减产为主，灌溉可以部分地减少减产幅度，如果单考虑CO2的肥效作用，三种作物的产量变化以增产为主。若保持959／6的粮食自给率，人口按照SRESA2和B2情景增长，到2030年的技术进步可使粮食年单产递增0．79／6以上，维持目前的种植比例和种植面积，B2情景下，气候变化对我国的粮食安全问题将不会构成威胁，而A2情景下，气候变化将会对我国可持续发展的粮食安全造成威胁。     

未来气候变化对天津市办公建筑制冷采暖能耗的影响

利用能耗模拟软件（TRNSYS）模拟了1971—2010年天津市办公建筑制冷和采暖能耗,结合未来不同排放情景（低排放：B1;中等排放：A1B）下气候预估数据,定量评估了未来（2011—2100年）气候变化对办公建筑能耗的影响。结果表明,2011—2100年热负荷呈显著的下降趋势,而冷负荷显著上升,冷负荷的上升幅度高于热负荷的下降,导致总能耗呈微弱的上升趋势;低排放情景下热负荷的下降和冷负荷的上升幅度低于中等排放情景,总能耗的变化在两种排放情景下没有明显差异;与1971—2010年相比,低排放和中等排放两种情景下2011—2050年热负荷下降10%左右,而冷负荷上升约12%,总能耗增加超过2%;2051—2100年热负荷的下降和冷负荷的上升更为明显,尤其是冷负荷上升（约30%）,总能耗增加8%左右,冷负荷变化率在两种情景下相差较大。     

Creating regional climate change scenarios over southern South America for the 2020’s and 2050’s using the pattern scaling technique: validity and limitations

Dynamical downscaling of global climate simulations is the most adequate tool to generate regional projections of climate change. This technique involves at least a present climate simulation and a simulation of a future scenario, usually at the end of the twenty first century. However, regional projections for a variety of scenarios and periods, the 2020s or the 2050s, are often required by the impact community. The pattern scaling technique is used to estimate information on climate change for periods and scenarios not simulated by the regional model. We based our study on regional simulations performed over southern South America for present climate conditions and two emission scenarios at the end of the twenty first century. We used the pattern scaling technique to estimate mean seasonal changes of temperature and precipitation for the 2020s and the 2050s. The validity of the scalability assumptions underlying the pattern scaling technique for estimating near future regional climate change scenarios over southern South America is assessed. The results show that the pattern scaling works well for estimating mean temperature changes for which the regional changes are linearly related to the global mean temperature changes. For precipitation changes, the validity of the scalability assumption is weaker. The errors of estimating precipitation changes are comparable to those inherent to the regional model and to the projected changes themselves.     

Climate scenarios of sea level rise for the northeast Atlantic Ocean: a study including the effects of ocean dynamics and gravity changes induced by ice melt

Here we present a set of regional climate scenarios of sea level rise for the northeast Atlantic Ocean. In this study, the latest observations and results obtained with state-of-the-art climate models are combined. In addition, regional effects due to ocean dynamics and changes in the Earth’s gravity field induced by melting of land-based ice masses have been taken into account. The climate scenarios are constructed for the target years 2050 and 2100, for both a moderate and a large rise in global mean atmospheric temperature (2 °C and 4 °C in 2100 respectively). The climate scenarios contain contributions from changes in ocean density (global thermal expansion and local steric changes related to changing ocean dynamics) and changes in ocean mass (melting of mountain glaciers and ice caps, changes in the Greenland and Antarctic ice sheets, and (minor) terrestrial water-storage contributions). All major components depend on the global temperature rise achieved in the target periods considered. The resulting set of climate scenarios represents our best estimate of twenty-first century sea level rise in the northeast Atlantic Ocean, given the current understanding of the various contributions. For 2100, they yield a local rise of 30 to 55 cm and 40 to 80 cm for the moderate and large rise in global mean atmospheric temperature, respectively.     

利用随机天气模式及多种插值方法生成逐日气候变化情景的研究

针对目前大气环流模式在用于气候变化影响评估研究中时间分辨率较低的局恨性, 以及气候情景的要求和气候变化影响研究的需要, 结合GCM的模拟试验结果, 利用随机天气模式WGEN生成了中国东北地区未来气候变化的逐日情景, 其中包含了可能的气候变率信息, 可与作物动力模式等气候影响模式嵌套, 研究作物生长发育及其产量的可能变化, 及气候变率变化的可能影响等.     

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.     

2010—2100年淮河径流量变化情景预估

根据淮河流域14个气象站点1964—2007年观测降水量与温度数据和ECHAM5/MPI-OM模式在3种排放情景下对该流域2001—2100年的气候预估,利用人工神经网络模型预估淮河蚌埠站2010—2100年逐月径流量变化。计算结果表明:3种排放情景下2010—2100年淮河径流量年际变化幅度差异较大,SRES-A2情景总体处于波动上升趋势,其中2051—2085年上升趋势显著;SRES-A1B情景2024—2037年年平均流量显著降低;SRES-B1情景年平均流量的变率甚小。季节分析表明:春季径流量在2010—2100年变幅最小,距平百分率在-15.1%～18.6%之间小幅波动。夏季平均流量在2040年代前呈下降趋势,之后小幅波动上升。秋、冬季平均流量SRES-A2和SRES-A1B情景变幅显著,其中,秋季SRES-A2情景2060年代距平百分率下降达50.6%,为3种情景下各季节径流量降幅之最;冬季SRES-A1B情景2050年代其增幅达到54.7%,亦为上升幅度之最。     

Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003

An understanding of the relative impacts of the changes in climate variables on crop yield can help develop effective adaptation strategies to cope with climate change. This study was conducted to investigate the effects of the interannual variability and trends in temperature, solar radiation and precipitation during 1961–2003 on wheat and maize yields in a double cropping system at Beijing and Zhengzhou in the North China Plain (NCP), and to examine the relative contributions of each climate variable in isolation. 129 climate scenarios consisting of all the combinations of these climate variables were constructed. Each scenario contained 43 years of observed values of one variable, combined with values of the other two variables from each individual year repeated 43 times. The Agricultural Production Systems Simulator (APSIM) was used to simulate crop yields using the ensemble of generated climate scenarios. The results showed that the warming trend during the study period did not have significant impact on wheat yield potential at both sites, and only had significant negative impact on maize yield potential at Beijing. This is in contrast with previous results on effect of warming. The decreasing trend in solar radiation had a much greater impact on simulated yields of both wheat and maize crops, causing a significant reduction in potential yield of wheat and maize at Beijing. Although decreasing trends in rainfed yield of both simulated wheat and maize were found, the substantial interannual variability of precipitation made the trends less prominent.