Modelling daily temperature extremes: recent climate and future changes over Europe

Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries.     

Identifying future climate change and drought detection using CanESM2 in the upper Siem Reap River,Cambodia

Cambodia is one of the most vulnerable countries to climate change impacts such as floods and droughts. Study of future climate change and drought conditions in the upper Siem Reap River catchment is vital because this river plays a crucial role in maintaining the Angkor Temple Complex and livelihood of the local population since 12th century. The resolution of climate data from Global Circulation Models (GCM) is too coarse to employ effectively at the watershed scale, and therefore downscaling of the dataset is required. Artificial neural network (ANN) and Statistical Downscaling Model (SDSM) models were applied in this study to downscale precipitation and temperatures from three Representative Concentration Pathways (RCP 2.6, RCP 4.5 and RCP 8.5 scenarios) from Global Climate Model data of the Canadian Earth System Model (CanESM2) on a daily and monthly basis. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were adopted to develop criteria for dry and wet conditions in the catchment. Trend detection of climate parameters and drought indices were assessed using the Mann-Kendall test. It was observed that the ANN and SDSM models performed well in downscaling monthly precipitation and temperature, as well as daily temperature, but not daily precipitation. Every scenario indicated that there would be significant warming and decreasing precipitation which contribute to mild drought. The results of this study provide valuable information for decision makers since climate change may potentially impact future water supply of the Angkor Temple Complex (a World Heritage Site).     

On interpreting hydrological change from regional climate models

Although representation of hydrology is included in all regional climate models (RCMs), the utility of hydrological results from RCMs varies considerably from model to model. Studies to evaluate and compare the hydrological components of a suite of RCMs and their use in assessing hydrological impacts from future climate change were carried out over Europe. This included using different methods to transfer RCM runoff directly to river discharge and coupling different RCMs to offline hydrological models using different methods to transfer the climate change signal between models. The work focused on drainage areas to the Baltic Basin, the Bothnian Bay Basin and the Rhine Basin. A total of 20 anthropogenic climate change scenario simulations from 11 different RCMs were used. One conclusion is that choice of GCM (global climate model) has a larger impact on projected hydrological change than either selection of emissions scenario or RCM used for downscaling.     

Changes in frost, snow and Baltic sea ice by the end of the twenty-first century based on climate model projections for Europe

Changes in indices related to frost and snow in Europe by the end of the twenty-first century were analyzed based on experiments performed with seven regional climate models (RCMs). All the RCMs regionalized information from the same general circulation model (GCM), applying the IPCC-SRES A2 radiative forcing scenario. In addition, some simulations used SRES B2 radiative forcing and/or boundary conditions provided by an alternative GCM. Ice cover over the Baltic Sea was examined using a statistical model that related the annual maximum extent of ice to wintertime coastal temperatures. Fewer days with frost and snow, shorter frost seasons, a smaller liquid water equivalent of snow, and milder sea ice conditions were produced by all model simulations, irrespective of the forcing scenario and the driving GCM. The projected changes have implications across a diverse range of human activities. Details of the projections were subject to differences in RCM design, deviations between the boundary conditions of the driving GCMs, uncertainties in future emissions and random effects due to internal climate variability. A larger number of GCMs as drivers of the RCMs would most likely have resulted in somewhat wider ranges in the frost, snow and sea ice estimates than those presented in this paper.     

Evaluation of the CORDEX regional climate models performance in simulating climate conditions of two catchments in Upper Blue Nile Basin

This study was targeted at evaluating the performance of six Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX). The evaluation is on the bases of how well the RCMs simulate the seasonal mean climatology, interannual variability and annual cycles of rainfall, maximum and minimum temperature over two catchments in western Ethiopia during the period 1990–2008. Observed data obtained from the Ethiopian National Meteorological Agency was used for performance evaluation of the RCMs outputs. All Regional Climate Models (RCMs) have simulated seasonal mean annual cycles of precipitation with a significant bias shown on individual models; however, the ensemble mean exhibited better the magnitude and seasonal rainfall. Despite the highest biases of RCMs in the wet season, the annual cycle showed the prominent features of precipitation in the two catchments. In many aspects, CRCM5 and RACMO22 T simulate rainfall over most stations better than the other models. The highest biases are associated with the highest error in simulating maximum and minimum temperature with the highest biases in high elevation areas. The rainfall interannual variability is less evident in Finchaa with short rainy season experiencing a larger degree of interannual variability. The differences in performance of the Regional Climate Models in the two catchments show that all the available models are not equally good for particular locations and topographies. In this regard, the right regional climate models have to be used for any climate change impact study for local-scale climate projections.     

REGIONAL CLIMATE CHANGE SCENARIOS UNDER GLOBAL WARMING IN KAZAKHSTAN

The aim of this paper is to report on the development of regional climate change scenarios for Kazakhstan as the result of increasing of CO₂ concentration in the global atmosphere. These scenarios are used in the assessment of climate change impacts on the agricultural, forest and water resources of Kazakhstan. Climate change scenarios for Kazakhstan to assess both long-term (2× CO₂ in 2075) and short-term (2000, 2010 and 2030) impacts were prepared. The climate conditions under increasing CO₂ concentration were estimated from three General Circulation Models (GCM) outputs: the model of the Canadian Climate Center Model (CCCM), the model of the Geophysical Fluid Dynamics Laboratory (GFDL) and the 1% transient version of the GFDL model (GFDL-T). The near-term climate scenarios were obtained using the probabilistic forecast model (PFM) to the year 2010 and the results of GFDL-T for years 2000 and 2030. A baseline scenario representing the current climate conditions based on observations from 1951 to 1980 was developed. The assessment of climate change in Kazakhstan based on the analysis of 100-years observations is given too. As a result of comparisons of the current climate (based on observed climate) the 1× CO₂ output from GCMs showed that the GFDL model best matches the observed climate. The GFDL model suggests that the minimum increase in temperature is expected in winter, when most of the territory is expected to have temperatures 2.3–4.5 °C higher. The maximum (4.3 to 8.2 °C) is expected to be in spring. CCCM scenario estimates an extreme worming above 11 °C in spring months. GFDL-T outputs provide an intermediate scenario.     

中国北方农牧交错带气候变化特征及未来趋势

利用1951—2006年中国台站日平均观测资料对北方农牧带过去56a气候变化特征进行了分析,指出该农牧带年降水量具有明显的年际和年代际变化特征,近10a来呈明显的下降趋势;年平均气温在20世纪90年代前期变化幅度较小,1987年之后持续偏暖,与全球及中国温度变化趋势一致;降水和温度变化具有明显的季节和区域差异。在气候特征分析基础上,利用全球海气耦合模式嵌套区域气候模式在SRES A2排放情景下对未来30a（2001-2030年）的气候变化进行了预估,对照30a模式气候场（1961—1990年）,分析了未来30a北方农牧交错带降水和温度变化的可能趋势,结果表明,未来该区平均地面气温持续升高,升温幅度达0．3℃,温度日较差将明显减小;年降水量呈增加趋势,但增加幅度较小,且降水变化具有明显的季节和地域差异;未来黄河上游地区干旱的威胁仍十分严峻。     

Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations

The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.     

A study on combining global and regional climate model results for generating climate scenarios of temperature and precipitation for the Netherlands

Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate. In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty, while high resolution regional climate models (RCMs) are more suitable to quantify the third level. Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined statistical–dynamical downscaling approach, with the statistical relations based on regional model output.     

Future change in the frequency of warm and cold spells over Pakistan simulated by the PRECIS regional climate model

Climate change caused by anthropogenic activities has generated a variety of research focusing on investigating the past climate, predicting the future climate and quantifying the change in climate extreme events by using different climate models. Climate extreme events are valuable to evaluate the potential impact of climate change on human activities, agriculture and economy and are also useful to monitor the climate change on global scale. Here, a Regional Climate Model (RCM) simulation is used to study the future variations in the temperature extreme indices, particularly change in frequency of warm and cold spells duration over Pakistan. The analyses are done on the basis of simulating two 30 years simulations with the Hadley Center’s RCM PRECIS, at a horizontal resolution of 50 km. Simulation for the period 1961–1990 represents the recent climate and simulation for the period 2071–2100 represents the future climate. These simulations are driven by lateral boundary conditions from HadAM3P GCM of Hadley centre UK. For the validation of model, observed mean, maximum and minimum temperatures for the period 1961–1990 at all the available stations in Pakistan are first averaged and are then compared with the PRECIS averaged grid-box data. Also the observed monthly gridded data set of Climate Research Unit (UK) data is used to validate the model. Temperature indices in the base period as well as in future are then calculated and the corresponding change is observed. Percentile based spatial change of temperature shows that in summer, increase in daily minimum temperature is more as compared to the increase of daily maximum temperature whereas in winter, the change in maximum temperature is high. The occurrence of annual cold spells shows significantly decreasing trend while for warm spells there is slight increasing trend over Pakistan.     

The potential impact of climate change on Great Lakes international shipping

The higher temperatures of climate change may result in a fall in Great Lakes water levels. For vessels carrying imports into and exports out of the Great Lakes lower lake levels will lead to restrictions on vessel drafts and reductions in vessel cargos, increasing the number of trips and the cost of moving cargo. Estimates of these impacts are derived from simulations of a recent year??s international cargo movements, comparing a base case with no climate change to various climate change scenarios. The impacts vary from a 5% increase in vessel variable operating costs for a climate change scenario representing the possible climate in 2030 to over 22% for a scenario representing a doubling of atmospheric carbon dioxide. Impacts vary by commodity and route. For years of naturally occurring low water the impacts are up to 13% higher for even the most moderate climate change scenario. Climate change may also result in a shorter time of ice cover leading to an extension of the navigation season. Climate change is also expected to increase the threat of damage from aquatic invasive species, possibly leading to further requirements for ships to undertake preventive measures.     

Future changes in drought characteristics over South Korea using multi regional climate models with the standardized precipitation index

In this study, the projection of future drought conditions is estimated over South Korea based on the latest and most advanced sets of regional climate model simulations under the Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios, within the context of the national downscaling project of the Republic of Korea. The five Regional Climate Models (RCMs) are used to produce climate-change simulations around the Korean Peninsula and to estimate the uncertainty associated with these simulations. The horizontal resolution of each RCM is 12.5 km and model simulations are available for historical (1981-2010) and future (2021-2100) periods under forcing from the RCP4.5 and RCP8.5 scenarios. To assess the characteristics of drought on multiple time scales in the future, we use Standardized Precipitation Indices for 1-month (SPI- 1), 6-month (SPI-6) and 12-month (SPI-12). The number of drought months in the future is shown to be characterized by strong variability, with both increasing and decreasing trends among the scenarios. In particular, the number of drought months over South Korea is projected to increase (decrease) for the period 2041-2070 in the RCP8.5 (RCP4.5) scenario and increase (decrease) for the period 2071-2100 in the RCP4.5 (RCP8.5) scenario. In addition, the percentage area under any drought condition is overall projected to gradually decrease over South Korea during the entire future period, with the exception of SPI-1 in the RCP4.5 scenario. Particularly, the drought areas for SPI-1 in the RCP4.5 scenario show weakly positive long-term trend. Otherwise, future changes in drought areas for SPI-6 and SPI-12 have a marked downward trend under the two RCP scenarios.     

A Climate Change Scenario for the Tropics

This paper describes the construction of a climate change scenario for a region representing the extended Tropics – 30° N to 30° S – using a methodology that combines results from a simple climate model and a Global Climate Model (GCM) transient climate change experiment. The estimated date by which this climate change scenario might be realized ranges from as early as the end of the 2030s to as late as well into the 22nd century. The central estimate is for this scenario to describe the climate of the 2060s, which would represent a global warming rate of about 0.2 °C per decade, with associated atmospheric CO₂ concentrations estimated to be about 560 ppmv, 55% higher than 1990 levels. The role of anthropogenic aerosols in offsetting part of this future global warming and altering the regional character of the changes has not been considered. The paper presents changes in mean temperature; mean rainfall; rainfall seasonality, variability, frequency, and intensity and soil moisture. These patterns of change derive from only one GCM climate change experiment; different experiments would yield different patterns for the same global warming. There is also some discussion about possible changes in tropical cyclone (TC) activity, although since TCs remain poorly modelled in GCMs, the full range of possibilities (from reduced activity, through no change, to increased activity) should be considered in any impact assessment.     

Analysis of the change in temperature trends in Subansiri River basin for RCP scenarios using CMIP5 datasets

This study focuses on changes in the maximum and minimum temperature over the Subansiri River basin for different climate change scenarios. For the study, dataset from Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) (i.e., coupled model intercomparison project phase five (CMIP5) dataset with representative concentration pathway (RCP) scenarios) were utilized. Long-term (2011–2100) maximum temperature (T _max) and minimum temperature (T_min) time series were generated using the statistical downscaling technique for low emission scenario (RCP2.6), moderate emission scenario (RCP6.0), and extreme emission scenario (RCP8.5). Trends and change of magnitude in T _max, T _min, and diurnal temperature range (DTR) were analyzed for different interdecadal time scales (2011–2100, 2011–2040, 2041–2070, 2070–2100) using Mann-Kendall non-parametric test and Sen’s slope estimator, respectively. The temperature data series for the observed duration (1981–2000) has been found to show increasing trends in T _max and T _min at both annual and monthly scale. Trend analysis of downscaled temperature for the period 2011–2100 shows increase in annual maximum temperature and annual minimum temperature for all the selected RCP scenarios; however, on the monthly scale, T _max and T _min have been seen to have decreasing trends in some months.

     

Climate change projections for the Texas High Plains and Rolling Plains

Potential changes in future climate in the Texas Plains region were investigated in the context of agriculture by analyzing three climate model projections under the A2 climate scenario (medium–high emission scenario). Spatially downscaled historic (1971–2000) and future (2041–2070) climate datasets (rainfall and temperature) were downloaded from the North American Regional Climate Change Assessment Program (NARCCAP). Climate variables predicted by three regional climate models (RCMs) namely the Regional Climate Model Version3–Geophysical Fluid Dynamics Laboratory (RCM3-GFDL), Regional Climate Model Version3–Third Generation Coupled Global Climate Model (RCM3-CGCM3), and Canadian Regional Climate Model–Community Climate System Model (CRCM-CCSM) were evaluated in this study. Gaussian and Gamma distribution mapping techniques were employed to remove the bias in temperature and rainfall data, respectively. Both the minimum and maximum temperatures across the study region in the future showed an upward trend, with the temperatures increasing in the range of 1.9 to 2.9 °C and 2.0 to 3.2 °C, respectively. All three climate models predicted a decline in rainfall within a range of 30 to 127 mm in majority of counties across the study region. In addition, they predicted an increase in the intensity of extreme rainfall events in the future. The frost-free season as predicted by the three models showed an increase by 2.6–3.4 weeks across the region, and the number of frost days declined by 17.9 to 30 %. Overall, these projections indicate considerable changes to the climate in the Texas Plains region in the future, and these changes could potentially impact agriculture in this region.

     

High-resolution simulations for Vietnam - methodology and evaluation of current climate

To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (-60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.     

Changes of precipitation extremes over South Korea projected by the 5 RCMs under RCP scenarios

The change of extreme precipitation is assessed with the HadGEM2-AO - 5 Regional Climate Models (RCMs) chain, which is a national downscaling project undertaken cooperatively by several South Korean institutes aimed at producing regional climate change projection with fine resolution (12.5 km) around the Korean Peninsula. The downscaling domain, resolution and lateral boundary conditions are held the same among the 5 RCMs to minimize the uncertainties from model configuration. Climatological changes reveal a statistically significant increase in the mid-21st century (2046- 2070; Fut1) and the late-21st century (2076-2100; Fut2) precipitation properties related to extreme precipitation, such as precipitation intensity and average of upper 5 percentile daily precipitation, with respect to the reference period (1981-2005). Changes depending on the intensity categories also present a clear trend of decreasing light rain and increasing heavy rain. In accordance with these results, the change of 1-in-50 year maximum precipitation intensity over South Korea is estimated by the GEV method. The result suggests that the 50-year return value (RV50) will change from -32.69% to 72.7% and from -31.6% to 96.32% in Fut1 and from -31.97% to 86.25% and from -19.45% to 134.88% in Fut2 under representative concentration pathway (RCP) 4.5 and 8.5 scenarios, respectively, at the 90% confidence level. This study suggests that multi-RCMs can be used to reduce uncertainties and assess the future change of extreme precipitation more reliably. Moreover, future projection of the regional climate change contains uncertainties evoked from not only driving GCM but also RCM. Therefore, multi-GCM and multi-RCM studies are expected to provide more robust projection.     

气候变暖背景下羌塘自然保护区年冻融指数的变化特征

利用1971~2019年羌塘自然保护区5个气象站逐日平均气温和地表温度,通过线性回归和Mann-Kendall等方法,分析气候变暖背景下近49a自然保护区大气和地面冻融指数的时空变化特征,并预估了RCP4.5和RCP8.5两种排放情景下,未来80a（2021~2100年）大气和地面冻融指数的变化。结果表明:(1)自然保护区大气融化指数（ATI）、地面融化指数（GTI）总体上呈自西向东递减的分布,并随海拔升高而减少;大气冻结指数（AFI）和地面冻结指数（GFI）的分布规律不明显,但最大值均出现在安多站,最小值出现在不同站点。(2)近49a自然保护区AFI、GFI分别以?8.97℃·d·a?1、?10.45℃·d·a?1的速率显著减少,ATI、GTI则表现为显著增加趋势,增幅分别为7.05℃·d·a?1和11.38℃·d·a?1,地面冻融指数的变化率大于大气冻融指数的变化率。与青藏高原对比,自然保护区AFI、GFI减幅小,ATI增幅接近,GTI增幅大。(3) AFI、GFI在1970s~1990s为正距平,2000s~2010s为负距平,表现为逐年代递减的变化特征;而ATI、GTI相反,呈逐年代递增的变化特征。(4) AFI、ATI、GFI、GTI分别在2001年、1993年、1999年和1998年发生了突变,ATI突变时间最早,较AFI偏早8a。(5)自然保护区冻结指数FI减少,融化指数TI增加,与平均气温、平均最低气温显著升高、降水量增加、平均风速减小密切相关,还与积雪日数、最大积雪深度的减少有关。(6)未来80a,RCP4.5排放情景下自然保护区AFI、GFI分别将减少322.8℃·d、357.6℃·d,ATI、GTI依次增加262.2℃·d、419.7℃·d;RCP8.5排放情景下,冻融指数的变化率更大。      

不同气候变化情景下未来中国热相关死亡风险的预估

预估气候变化背景下中国未来近期、中期及远期温度热相关人群超额死亡风险,为未来热相关人群健康风险防范提供科学依据。基于中国网格化日均气温数据集与3种排放情景下未来日均气温数据、历史人口数据与3种生育率情景下未来人口数据以及死因数据资料计算的热效应暴露-反应关系,计算每日热相关死亡人数。结果表明:（1）未来中国平均气温将持续升高,且北方地区升温幅度较大。（2）1986—2005年中国热相关非意外总死亡人数约为7.1（95%置信区间:5.7—8.5）万。（3）RCP2.6、RCP4.5情景下未来中国热相关非意外总死亡人数均呈现先升后降的变化趋势。21世纪末,不同情景下的热相关非意外总死亡人数均高于基准年代。（4）未来不同情景下中国热相关非意外总死亡人数在黄淮海地区以及成渝地区均呈上升趋势,在RCP2.6、RCP4.5情景下北方地区热相关非意外总死亡人数呈下降趋势,东南沿海地区在21世纪30年代后开始呈下降趋势。总体而言在全球变暖的背景下未来中国热相关死亡风险将上升,而在RCP2.6情景下可以有效抑制其上升趋势。      

A projection of extreme climate events in the 21st century over east Asia using the community climate system model 3

A series of coupled atmosphere-ocean-land global climate model (GCM) simulations using the National Center for Atmospheric Research (NCAR) Community Climate System Model 3 (CCSM3) has been performed for the period 1870–2099 at a T85 horizontal resolution following the GCM experimental design suggested in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). First, a hindcast was performed using the atmospheric concentrations of three greenhouse gases (CO₂, CH₄, N₂O) specified annually and globally on the basis of observations for the period 1870–1999. The hindcast results were compared with observations to evaluate the GCM’s reliability in future climate simulations. Second, climate projections for a 100-year period (2000–2099) were made using six scenarios of the atmospheric concentrations of the three greenhouse gases according to the A1FI, A1T, A1B, A2, B1, and B2 emission profiles of the Special Report on Emissions Scenarios. The present CCSM simulations are found to be consistent with IPCC’s AR4 results in the temporal and spatial distributions for both the present-day and future periods. The GCM results were used to examine the changes in extreme temperatures and precipitation in East Asia and Korea. The extreme temperatures were categorized into warm and cold events: the former includes tropical nights, warm days, and heat waves during summer (June–July–August) and the latter includes frost days, cold days, and cold surges during winter (December–January–February). Focusing on Korea, the results predict more frequent heat waves in response to future emissions: the projected percentage changes between the present day and the late 2090s range from 294% to 583% depending on the emission scenario. The projected global warming is predicted to decrease the frequency of cold extreme events; however, the projected changes in cold surge frequency are not statistically significant. Whereas the number of cold surges in the A1FI emission profile decreases from the present-day value by up to 24%, the decrease in the B1 scenario is less than 1%. The frequency and intensity of extreme precipitation events year-round were examined. Both the frequency and the intensity of these events are predicted to increase in the region around Korea. The present results will be helpful for establishing an adaptation strategy for possible climate change nationwide, especially extreme climate events, associated with global warming.