Global rainbow distribution under current and future climates

Rainbows contribute to human wellbeing by providing an inspiring connection to nature. Because the rainbow is an atmospheric optical phenomenon that results from the refraction of sunlight by rainwater droplets, changes in precipitation and cloud cover due to anthropogenic climate forcing will alter rainbow distribution. Yet, we lack a basic understanding of the current spatial distribution of rainbows and how climate change might alter this pattern. To assess how climate change might affect rainbow viewing opportunities, we developed a global database of crowd-sourced photographed rainbows, trained an empirical model of rainbow occurrence, and applied this model to present-day climate and three future climate scenarios. Results suggest that the average terrestrial location on Earth currently has 117 ± 71 days per year with conditions suitable for rainbows. By 2100, climate change is likely to generate a 4.0–4.9 % net increase in mean global annual rainbow-days (i.e., days with at least one rainbow), with the greatest change under the highest emission scenario. Around 21–34 % of land areas will lose rainbow-days and 66–79 % will gain rainbow-days, with rainbow gain hotspots mainly in high-latitude and high-elevation regions with smaller human populations. Our research demonstrates that alterations to non-tangible environmental attributes due to climate change could be significant and are worthy of consideration and mitigation.     

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.     

Emission scenario dependencies in climate change assessments of the hydrological cycle

Anthropogenic global warming will lead to changes in the global hydrological cycle. The uncertainty in precipitation sensitivity per 1 K of global warming across coupled atmosphere-ocean general circulation models (AOGCMs) has been actively examined. On the other hand, the uncertainty in precipitation sensitivity in different emission scenarios of greenhouse gases (GHGs) and aerosols has received little attention. Here we show a robust emission-scenario dependency (ESD); smaller global precipitation sensitivities occur in higher GHG and aerosol emission scenarios. Although previous studies have applied this ESD to the multi-AOGCM mean, our surprising finding is that current AOGCMs all have the common ESD in the same direction. Different aerosol emissions lead to this ESD. The implications of the ESD of precipitation sensitivity extend far beyond climate analyses. As we show, the ESD potentially propagates into considerable biases in impact assessments of the hydrological cycle via a widely used technique, so-called pattern scaling. Since pattern scaling is essential to conducting parallel analyses across climate, impact, adaptation and mitigation scenarios in the next report from the Intergovernmental Panel on Climate Change, more attention should be paid to the ESD of precipitation sensitivity.     

Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates

A fully probabilistic, or risk, assessment of future regional climate changeand its impacts involves more scenarios of radiative forcing than can besimulated by a general (GCM) or regional (RCM) circulation model. Additionalscenarios may be created by scaling a spatial response pattern from a GCM bya global warming projection from a simple climate model. I examine thistechnique, known as pattern scaling, using a particular GCM (HadCM2).Thecritical assumption is that there is a linear relationship between the scaler(annual global-mean temperature) and the response pattern. Previous studieshave found this assumption to be broadly valid for annual temperature; Iextend this conclusion to precipitation and seasonal (JJA) climate. However,slight non-linearities arise from the dependence of the climatic response onthe rate, not just the amount, of change in the scaler. These non-linearitiesintroduce some significant errors into the estimates made by pattern scaling,but nonetheless the estimates accurately represent the modelled changes. Aresponse pattern may be made more robust by lengthening the period from whichit is obtained, by anomalising it relative to the control simulation, and byusing least squares regression to obtain it. The errors arising from patternscaling may be minimised by interpolating from a stronger to a weaker forcingscenario.     

Recent Progress in Studies of Climate Change in China

An overview of basic research on climate change in recent years in China is presented. In the past 100 years in China, average annual mean surface air temperature (SAT) has increased at a rate ranging from 0.03℃ (10 yr)-1 to 0.12℃ (10 yr)-1 . This warming is more evident in northern China and is more significant in winter and spring. In the past 50 years in China, at least 27% of the average annual warming has been caused by urbanization. Overall, no significant trends have been detected in annual and/or summer precipitation in China on a whole for the past 100 years or 50 years. Both increases and decreases in frequencies of major extreme climate events have been observed for the past 50 years. The frequencies of extreme temperature events have generally displayed a consistent pattern of change across the country, while the frequencies of extreme precipitation events have shown only regionally and seasonally significant trends. The frequency of tropical cyclone landfall decreased slightly, but the frequency of sand/dust storms decreased significantly. Proxy records indicate that the annual mean SAT in the past a few decades is the highest in the past 400-500 years in China, but it may not have exceeded the highest level of the Medieval Warm Period (1000-1300 AD). Proxy records also indicate that droughts and floods in eastern China have been characterized by continuously abnormal rainfall periods, with the frequencies of extreme droughts and floods in the 20th century most likely being near the average levels of the past 2000 years. The attribution studies suggest that increasing greenhouse gas (GHG) concentrations in the atmosphere are likely to be a main factor for the observed surface warming nationwide. The Yangtze River and Huaihe River basins underwent a cooling trend in summer over the past 50 years, which might have been caused by increased aerosol concentrations and cloud cover. However, natural climate variability might have been a main driver for the mean and extreme precipitation variations observed over the past century. Climate models generally perform well in simulating the variations of annual mean SAT in China. They have also been used to project future changes in SAT under varied GHG emission scenarios. Large uncertainties have remained in these model-based projections, however, especially for the projected trends of regional precipitation and extreme climate events.     

The Impacts of Socioeconomic Development and Climate Change on Severe Weather Catastrophe Losses: Mid-Atlantic Region (MAR) and the U.S.

One strand of research relates the magnitude of severe weather disasters to climatic and human development factors; another highlights dramatic growth in catastrophe losses. However, there have been few attempts to put the two strands together. Here we use an explicit modeling framework to determine the contribution of climate variability relative to human factors in reported catastrophe losses. We then examine how future climate change can be expected to affect losses from natural disasters. Simultaneous regression models are constructed from three equations in which the dependent variables are U.S. flood loss, U.S. hurricane loss and U.S. catastrophe loss. Then two kinds of simulation under two climate change scenarios explore how climate change would affect losses. The climate change scenarios respectively project 13.5% and 21.5% increases in annual precipitation. The first simulation increases only the mean value of annual precipitation; the second simulation assumes that the mean and standard deviation of annual precipitation change in the same proportion. Results show that the growth in reported losses from weather-related natural disasters is due mainly to three socioeconomic factors: inflation, population growth and growth in per capita real wealth. However, weather variables such as precipitation and the number of hurricanes per period also clearly affect losses. The three stage least squares (3SLS) simultaneous equation model shows that a 1% increase in annual precipitation would enlarge catastrophe loss by as much as 2.8%. These findings are suggestive as planning signals to decision makers.     

Seasonal to yearly assessment of temperature and precipitation trends in the North Western Mediterranean Basin by dynamical downscaling of climate scenarios at high resolution (1971–2050)

The complex topography and high climatic variability of the North Western Mediterranean Basin (NWMB) require a detailed assessment of climate change projections at high resolution. ECHAM5/MPIOM global climate projections for mid-21st century and three different emission scenarios are downscaled at 10 km resolution over the NWMB, using the WRF-ARW regional model. High resolution improves the spatial distribution of temperature and precipitation climatologies, with Pearson's correlation against observation being higher for WRF-ARW (0.98 for temperature and 0.81 for precipitation) when compared to the ERA40 reanalysis (0.69 and 0.53, respectively). However, downscaled results slightly underestimate mean temperature (≈1.3 K) and overestimate the precipitation field (≈400 mm/year). Temperature is expected to raise in the NWMB in all considered scenarios (up to 1.4 K for the annual mean), and particularly during summertime and at high altitude areas. Annual mean precipitation is likely to decrease (around ?5 % to ?13 % for the most extreme scenarios). The climate signal for seasonal precipitation is not so clear, as it is highly influenced by the driving GCM simulation. All scenarios suggest statistically significant decreases of precipitation for mountain ranges in winter and autumn. High resolution simulations of regional climate are potentially useful to decision makers. Nevertheless, uncertainties related to seasonal precipitation projections still persist and have to be addressed.     

Risk assessment of agricultural water requirement based on a multi-model ensemble framework,southwest of Iran

Water shortage and climate change are the most important issues of sustainable agricultural and water resources development. Given the importance of water availability in crop production, the present study focused on risk assessment of climate change impact on agricultural water requirement in southwest of Iran, under two emission scenarios (A2 and B1) for the future period (2025–2054). A multi-model ensemble framework based on mean observed temperature-precipitation (MOTP) method and a combined probabilistic approach Long Ashton Research Station-Weather Generator (LARS-WG) and change factor (CF) have been used for downscaling to manage the uncertainty of outputs of 14 general circulation models (GCMs). The results showed an increasing temperature in all months and irregular changes of precipitation (either increasing or decreasing) in the future period. In addition, the results of the calculated annual net water requirement for all crops affected by climate change indicated an increase between 4 and 10 %. Furthermore, an increasing process is also expected regarding to the required water demand volume. The most and the least expected increase in the water demand volume is about 13 and 5 % for A2 and B1 scenarios, respectively. Considering the results and the limited water resources in the study area, it is crucial to provide water resources planning in order to reduce the negative effects of climate change. Therefore, the adaptation scenarios with the climate change related to crop pattern and water consumption should be taken into account.

     

Biogeophysical impacts of land use on present-day climate: near-surface temperature change and radiative forcing

Changes in land cover affect climate through the surface energy and moisture budgets, but these biogeophysical impacts of land use have not yet been included in General Circulation Model (GCM) simulations of 20th century climate change. Here, the importance of these effects was assessed by comparing climate simulations performed with current and potential natural vegetation. The northern mid-latitude agricultural regions were simulated to be approximately 1–2 K cooler in winter and spring in comparison with their previously forested state, due to deforestation increasing the surface albedo by approximately 0.1 during periods of snow cover. Some other regions such as the Sahel and India experienced a small warming due to land use. Although the annual mean global temperature is only 0.02 K lower in the simulation with present-day land use, the more local temperature changes in some regions are of a similar magnitude to those observed since 1860. The global mean radiative forcing by anthropogenic surface albedo change relative to the natural state is simulated to be −0.2 Wm², which is comparable with the estimated forcings relative to pre-industrial times by changes in stratospheric and tropospheric ozone, N₂O, halocarbons, and the direct effect of anthropogenic aerosols. Since over half of global deforestation has occurred since 1860, simulations of climate since that date should include the biogeophysical effects of land use.     

A GCM study of future climate response to aerosol pollution reductions

We use the global atmospheric GCM aerosol model ECHAM5-HAM to asses possible impacts of future air pollution mitigation strategies on climate. Air quality control strategies focus on the reduction of aerosol emissions. Here we investigate the extreme case of a maximum feasible end-of-pipe abatement of aerosols in the near term future (2030) in combination with increasing greenhouse gas (GHG) concentrations. The temperature response of increasing GHG concentrations and reduced aerosol emissions leads to a global annual mean equilibrium temperature response of 2.18 K. When aerosols are maximally abated only in the Industry and Powerplant sector, while other sectors stay with currently enforced regulations, the temperature response is 1.89 K. A maximum feasible abatement applied in the Domestic and Transport sector, while other sectors remain with the current legislation, leads to a temperature response of 1.39 K. Increasing GHG concentrations alone lead to a temperature response of 1.20 K. We also simulate 2–5% increases in global mean precipitation among all scenarios considered, and the hydrological sensitivity is found to be significantly higher for aerosols than for GHGs. Our study, thus highlights the huge potential impact of future air pollution mitigation strategies on climate and supports the need for urgent GHG emission reductions. GHG and aerosol forcings are not independent as both affect and are influenced by changes in the hydrological cycle. However, within the given range of changes in aerosol emissions and GHG concentrations considered in this study, the climate response towards increasing GHG concentrations and decreasing aerosols emissions is additive.     

气候变化的归因与预估模拟研究

本文总结了近五年来中国科学院大气物理研究所在气候变暖的归因模拟与预估研究上的主要进展。研究表明,利用海温、太阳辐射和温室气体等实际强迫因子驱动大气环流模式,能够较为合理地模拟全球平均地表气温在20世纪的演变,但是难以模拟出包括北大西洋涛动／北极涛动和南极涛动在内的高纬度环流的长期变化趋势。利用温室气体和硫酸盐气溶胶等“历史资料”驱动气候系统模式,能够较好地模拟出20世纪后期的全球增暖,但如果要再现20世纪前期(1940年代)的变暖,还需同时考虑太阳辐射等自然外强迫因子。20世纪中国气温演变的耦合模式模拟技巧,较之全球平均情况要低;中国气候在1920年代的变暖机理目前尚不清楚。对于近50年中国东部地区“南冷北暖”、“南涝北旱”的气候变化,基于大气环流模式特别是区域气候模式的数值试验表明,夏季硫酸盐气溶胶的负辐射效应超过了温室气体的增暖效应,从而对变冷产生贡献。但现有的数值模拟证据,不足以说明气溶胶增加对“南涝北旱”型降水异常有贡献。20世纪中期以来,青藏高原主体存在明显增温趋势,温室气体浓度的增加对这种增暖有显著贡献。多模式集合预估的未来气候变化表明,21世纪全球平均温度将继续增暖,增温幅度因不同排放情景而异;中国大陆年均表面气温的增暖与全球同步,但增幅在东北、西部和华中地区较大,冬季升温幅度高于夏季、日最低温度升幅要强于日最高温度;全球增暖有可能对我国中东部植被的地理分布产生影响。伴随温室气体增加所导致的夏季平均温度升高,极端温度事件增多;在更暖的气候背景下,中国大部分地区总降水将增多,极端降水强度加大且更频繁发生,极端降水占总降水的比例也将增大。全球增暖有可能令大洋热盐环流减弱,但是减弱的幅度因模式而异。全球增暖可能不是导致北太平洋副热带－热带经圈环流自20世纪70年代以来变弱的原因。文章同时指出了模式预估结果中存在的不确定性。     

Growing stocks of buildings,infrastructures and machinery as key challenge for compliance with climate targets

Drastic reductions of greenhouse-gas (GHG) emissions are required to meet the goal of the 2015 Paris climate accord to limit global warming to 1.5–2.0 °C over pre-industrial levels. We introduce the material stock-flow framework as a novel way to develop scenarios for future GHG emissions using methods from social metabolism research. The basic assumption behind our exploratory scenario approach is that nearly all final energy is required to either expand and maintain stocks of buildings, infrastructures and machinery or to provide services by using them. Distinguishing three country groups, we develop GDP- and population-driven scenarios for the development of these material stocks and the corresponding energy requirements based on historically calibrated model parameters. We analyze the results assuming different future pathways of CO₂ emissions per unit of primary energy. The resulting cumulative carbon emissions from 2018 to 2050 range from 361 Gt C in the lower GDP-driven to 568 GtC in the higher population-driven scenario. The findings from the population-driven scenarios point towards the huge implications of a hypothetical convergence of per-capita levels of material stocks assuming current trajectories of technological improvements. Results indicate that providing essential services with a considerably lower level of material stocks could contribute to large reductions in global resource demand and GHG emissions. A comparison of different stock levels in 2050 demonstrates that complying with ambitious climate targets requires much faster declines of CO₂ emissions per unit of primary energy if growth of material stocks is not limited.     

Future changes and uncertainties in temperature and precipitation over China based on CMIP5 models

Climate changes in future 21 st century China and their uncertainties are evaluated based on 22 climate models from the Coupled Model Intercomparison Project Phase 5(CMIP5). By 2081–2100, the annual mean surface air temperature(SAT) is predicted to increase by 1.3℃± 0.7℃, 2.6℃± 0.8℃ and 5.2℃± 1.2℃ under the Representative Concentration Pathway(RCP) scenarios RCP2.6, RCP4.5 and RCP8.5, relative to 1986–2005, respectively. The future change in SAT averaged over China increases the most in autumn/winter and the least in spring, while the uncertainty shows little seasonal variation.Spatially, the annual and seasonal mean SAT both show a homogeneous warming pattern across China, with a warming rate increasing from southeastern China to the Tibetan Plateau and northern China, invariant with time and emissions scenario.The associated uncertainty in SAT decreases from northern to southern China. Meanwhile, by 2081–2100, the annual mean precipitation increases by 5% ± 5%, 8% ± 6% and 12% ± 8% under RCP2.6, RCP4.5 and RCP8.5, respectively. The national average precipitation anomaly percentage, largest in spring and smallest in winter, and its uncertainty, largest in winter and smallest in autumn, show visible seasonal variations. Although at a low confidence level, a homogeneous wetting pattern is projected across China on the annual mean scale, with a larger increasing percentage in northern China and a weak drying in southern China in the early 21 st century. The associated uncertainty is also generally larger in northern China and smaller in southwestern China. In addition, both SAT and precipitation usually show larger seasonal variability on the sub-regional scale compared with the national average.     

What future for primary aluminium production in a decarbonizing economy?

Aluminium is an energy intensive material with an environmental footprint strongly dependent on the electricity mix consumed by the smelting process. This study models prospective environmental impacts of primary aluminium production according to different integrated assessment modeling scenarios building on Shared Socioeconomic Pathways and their climate change mitigation scenarios. Results project a global average carbon intensity ranging between 8.6 and 18.0 kg CO₂ eq/kg in 2100, compared to 18.3 kg CO₂ eq/kg at present, that could be further reduced under mitigation scenarios. Co-benefits with other environmental indicators are observed. Scaling aluminium production impacts to the global demand shows total emission between 1250 and 1590 Gt CO₂ eq for baseline scenarios by 2050 while absolute decoupling is only achievable with stringent climate policy changing drastically the electricity mix. Achieving larger emission reductions will require circular strategies that go beyond primary material production itself and involve other stakeholders along the aluminium value chain.     

Exposure of global mountain systems to climate warming during the 21st Century

We provide an assessment of surface temperature changes in mountainous areas of the world using a set of climate projections at a 0.5° resolution for two 30-year periods (2040–2069 and 2070–2099), using four Intergovernmental Panel for Climate Change (IPCC) emission scenarios and five AOGCM. Projected average temperature changes varied between +3.2 °C (+0.4 °C/per decade) and +2.1 °C (+0.26 °C/per decade) for 2055 and +5.3 °C (+0.48 °C/per decade) and +2.8 °C for 2085 (+0.25 °C/per decade). The temperature is expected to rise by a greater amount in higher northern latitude mountains than in mountains located in temperate and tropical zones. The rate of warming in mountain systems is projected to be two to three times higher than that recorded during the 20th century. The tendency for a greater projected warming in northern latitude mountain systems is consistent across scenarios and is in agreement with observed trends. In light of these projections, warming is considered likely to affect biodiversity (e.g., species extinctions, changes in the composition of assemblages), water resources (e.g., a reduction in the extent of glaciated areas and snow pack), and natural hazards (e.g., floods). Accurate estimate of the effects of climate change in mountain systems is difficult because of uncertainties associated with the climate scenarios and the existence of non-linear feedbacks between impacts.     

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.     

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.     

中国各季节气候对热盐环流减弱的不同响应

使用CCSM3（community climate system model version 3）模式的＂淡水扰动试验＂结果,对热盐环流强度减弱后中国区域冬、夏气候的不同响应特征进行了研究。结果表明：CCSM3可较为准确地再现中国附近区域表面气温及降水量的量值和分布形态。当热盐环流年平均强度减弱约80%之后,中国区域冬、夏季的表面气温与降水量显著降低,但冬、夏季的降低幅度与空间分布形态存在显著的差异。冬季的降温幅度较大且分布较为一致,平均降温幅度可达2.2℃,最大的降温幅度可达4℃;夏季的降温幅度相对较小且南北差异较大,平均降温幅度为1.3℃,最大的降温幅度为3℃。冬、夏季降水量的降低幅度都在6%左右,但其成因及其分布形态都存在显著差异。     

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.     

Vegetation feedback under future global warming

It has been well documented that vegetation plays an important role in the climate system. However, vegetation is typically kept constant when climate models are used to project anthropogenic climate change under a range of emission scenarios in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios. Here, an atmospheric general circulation model, and an asynchronously coupled system of an atmospheric and an equilibrium terrestrial biosphere model are forced by monthly sea surface temperature and sea ice extent for the periods 2051?C2060 and 2090?C2098 as projected with 17 atmosphere?Cocean general circulation models participating in the IPCC Fourth Assessment Report, and by appropriate atmospheric carbon dioxide concentrations under the A2 emission scenario. The effects of vegetation feedback under future global warming are then investigated. It is found that the simulated composition and distribution of vegetation during 2051?C2060 (2090?C2098) differ greatly from the present, and global vegetation tends to become denser as expressed by a 21% (36%) increase in global mean leaf area index, which is most pronounced at the middle and high northern latitudes. Vegetation feedback has little effect on globally averaged surface temperature. On a regional scale, however, it induces statistically significant changes in surface temperature, in particular over most parts of continental Eurasia east of about 60°E where annual surface temperature is expected to increase by 0.1?C1.0?K, with an average of about 0.4?K for each future period. These changes can mostly be explained by changes in surface albedo resulting from vegetation changes in the context of future global warming.