Increasing impacts of climate change upon ecosystems with increasing global mean temperature rise

In a meta-analysis we integrate peer-reviewed studies that provide quantified estimates of future projected ecosystem changes related to quantified projected local or global climate changes. In an advance on previous analyses, we reference all studies to a common pre-industrial base-line for temperature, employing up-scaling techniques where necessary, detailing how impacts have been projected on every continent, in the oceans, and for the globe, for a wide range of ecosystem types and taxa. Dramatic and substantive projected increases of climate change impacts upon ecosystems are revealed with increasing annual global mean temperature rise above the pre-industrial mean (ΔT_g). Substantial negative impacts are commonly projected as ΔT_g reaches and exceeds 2°C, especially in biodiversity hotspots. Compliance with the ultimate objective of the United Nations Framework Convention on Climate Change (Article 2) requires that greenhouse gas concentrations be stabilized within a time frame “sufficient to allow ecosystems to adapt naturally to climate change”. Unless ΔT_g is constrained to below 2°C at most, results here imply that it will be difficult to achieve compliance. This underscores the need to limit greenhouse gas emissions by accelerating mitigation efforts and by protecting existing ecosystems from greenhouse-gas producing land use change processes such as deforestation.     

Localized climate change scenarios of mean temperature and precipitation over Switzerland

There is a growing need of the climate change impact modeling and adaptation community to have more localized climate change scenario information available over complex topography such as in Switzerland. A gridded dataset of expected future climate change signals for seasonal averages of daily mean temperature and precipitation in Switzerland is presented. The basic scenarios are taken from the CH2011 initiative. In CH2011, a Bayesian framework was applied to obtain probabilistic scenarios for three regions within Switzerland. Here, the results for two additional Alpine sub-regions are presented. The regional estimates have then been downscaled onto a regular latitude-longitude grid with a resolution of 0.02° or roughly 2 km. The downscaling procedure is based on the spatial structure of the climate change signals as simulated by the underlying regional climate models and relies on a Kriging with external drift using height as auxiliary predictor. The considered emission scenarios are A1B, A2 and the mitigation scenario RCP3PD. The new dataset shows an expected warming of about 1 to 6 °C until the end of the 21st century, strongly depending on the scenario and the lead time. Owing to a large vertical gradient, the warming is about 1 °C stronger in the Alps than in the Swiss lowlands. In case of precipitation, the projection uncertainty is large and in most seasons precipitation can increase or decrease. In summer a distinct decrease of precipitation can be found, again strongly depending on the emission scenario.     

Impact of climate change and irrigation technology advancement on agricultural water use in China

The impact of climate change and irrigation technology advancement on agricultural water use in China is analyzed for the period of 1949–2005. The Palmer Drought Severity Index (PDSI) is adopted to characterize climate change, and the Gross Irrigation Quota (GIQ) is used to examine the relationship between agricultural water use and climate change in China. The results show that the GIQ correlates well with the PDSI in Chinese irrigated areas for the period of 1949–1990. A quantitative relationship between the GIQ and PDSI is statistically regressed; a new GIQ dataset is generated with the PDSI based on this relationship over the period 1949–2005. The generated GIQ data with climate-only information follow the pattern of the actual GIQ for the period 1949–1990. Since 1991, the actual GIQ becomes much smaller than the generated GIQ, indicating that irrigation technology advancement exerts a dominant impact on reducing agricultural water use intensity in China.     

Global river discharge and water temperature under climate change

Climate change will affect hydrologic and thermal regimes of rivers, having a direct impact on freshwater ecosystems and human water use. Here we assess the impact of climate change on global river flows and river water temperatures, and identify regions that might become more critical for freshwater ecosystems and water use sectors. We used a global physically based hydrological-water temperature modelling framework forced with an ensemble of bias-corrected general circulation model (GCM) output for both the SRES A2 and B1 emissions scenario. This resulted in global projections of daily river discharge and water temperature under future climate. Our results show an increase in the seasonality of river discharge (both increase in high flow and decrease in low flow) for about one-third of the global land surface area for 2071–2100 relative to 1971–2000. Global mean and high (95th percentile) river water temperatures are projected to increase on average by 0.8–1.6 (1.0–2.2) °C for the SRES B1–A2 scenario for 2071–2100 relative to 1971–2000. The largest water temperature increases are projected for the United States, Europe, eastern China, and parts of southern Africa and Australia. In these regions, the sensitivities are exacerbated by projected decreases in low flows (resulting in a reduced thermal capacity). For strongly seasonal rivers with highest water temperatures during the low flow period, up to 26% of the increases in high (95th percentile) water temperature can be attributed indirectly to low flow changes, and the largest fraction is attributable directly to increased atmospheric energy input. A combination of large increases in river temperature and decreases in low flows are projected for the southeastern United States, Europe, eastern China, southern Africa and southern Australia. These regions could potentially be affected by increased deterioration of water quality and freshwater habitats, and reduced water available for human uses such as thermoelectric power and drinking water production.     

Racing climate change: Collaboration and conflict in California's global climate change policy arena

Media accounts routinely refer to California's Assembly Bill 32 (AB 32), the Global Warming Solutions Act of 2006, as “landmark” climate change legislation. On its surface, this label is an accurate reflection of the state's forward-thinking stance across many environmental issues including pesticides, toxic substances, solid waste, and air quality. For all its promise, however, AB 32 can also be considered a low point in the landscape of conflict between state environmental regulators and California's environmental justice movement. While the legislation included several provisions to address the procedural and distributive dimensions of environmental justice, the implementation of AB 32 has been marked by heated conflict. The most intense conflicts over AB 32 revolve around the primacy of market mechanisms such as “cap and trade.” This article examines the drivers and the manifestations of these dynamics of collaboration and conflict between environmental justice advocates and state regulators, and pays particular attention to the scalar and racialized quality of the neoliberal discourse. The contentiousness of climate change politics in California offers scholars and practitioners around the world a cautionary tale of how the best intentions for integrating environmental justice principles into climate change policy do not necessarily translate into implementation and how underlying racialized fractures can upend collaboration between state and social movement actors.     

气候变化对跨境水资源影响的适应性评估与管理框架

气候变化增加了国际河流冲突的可能性,加强跨境水资源适应性管理是流域国可持续发展的必然选择。梳理了适应性相关研究的国内外最新进展,认识到适应性管理的关键问题是要发展一套科学评估未来气候变化影响及适应性策略的程序。通过论述气候变化下跨境水资源的适应性评估与管理框架,提出一个气候变化影响决策评估工具,包括信息收集、需求分析、对策分析、综合评估以及实施与调控5个阶段。该项研究将适应性管理与气候变化、定量化脆弱性及适应能力关联评价、成本效益分析、多目标优化决策和动态调控等有机结合,为从跨界层面制定具有针对性的适应性管理对策提供了思路与方法,有利于促进国际河流流域可持续发展。     

Impacts of 21st century climate change on global air pollution-related premature mortality

Climate change modulates surface concentrations of fine particulate matter (PM_2.5) and ozone (O₃), indirectly affecting premature mortality attributed to air pollution. We estimate the change in global premature mortality and years of life lost (YLL) associated with changes in surface O₃ and PM_2.5 over the 21st century as a result of climate change. We use a global coupled chemistry-climate model to simulate current and future climate and the effect of changing climate on air quality. Epidemiological concentration-response relationships are applied to estimate resulting changes in premature mortality and YLL. The effect of climate change on air quality is isolated by holding emissions of air pollutants constant while allowing climate to evolve over the 21st century according to a moderate projection of greenhouse gas emissions (A1B scenario). Resulting changes in 21st century climate alone lead to an increase in simulated PM_2.5 concentrations globally, and to higher (lower) O₃ concentrations over populated (remote) regions. Global annual premature mortality associated with chronic exposure to PM_2.5 increases by approximately 100 thousand deaths (95 % confidence interval, CI, of 66–130 thousand) with corresponding YLL increasing by nearly 900 thousand (95 % CI, 576–1,128 thousand) years. The annual premature mortality due to respiratory disease associated with chronic O₃ exposure increases by +6,300 deaths (95 % CI, 1,600–10,400). This climate penalty indicates that stronger emission controls will be needed in the future to meet current air quality standards and to avoid higher health risks associated with climate change induced worsening of air quality over populated regions.     

Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China

A statistical downscaling method (SDSM) was evaluated by simultaneously downscaling air temperature, evaporation, and precipitation in Haihe River basin, China. The data used for evaluation were large-scale atmospheric data encompassing daily NCEP/NCAR reanalysis data and the daily mean climate model results for scenarios A2 and B2 of the HadCM3 model. Selected as climate variables for downscaling were measured daily mean air temperature, pan evaporation, and precipitation data (1961–2000) from 11 weather stations in the Haihe River basin. The results obtained from SDSM showed that: (1) the pattern of change in and numerical values of the climate variables can be reasonably simulated, with the coefficients of determination between observed and downscaled mean temperature, pan evaporation, and precipitation being 99%, 93%, and 73%, respectively; (2) systematic errors existed in simulating extreme events, but the results were acceptable for practical applications; and (3) the mean air temperature would increase by about 0.7°C during 2011~2040; the total annual precipitation would decrease by about 7% in A2 scenario but increase by about 4% in B2 scenario; and there were no apparent changes in pan evaporation. It was concluded that in the next 30 years, climate would be warmer and drier, extreme events could be more intense, and autumn might be the most distinct season among all the changes.     

Impacts of socio-economic and climate change scenarios on wetlands: linking water resource and biodiversity meta-models

A meta-modelling approach has been adopted to link simulations of low and high water flows with simulations of suitable climate space for a selection of fen and bog species with differing drought and flood tolerance. The linked meta-models were used to examine the impacts of socio-economic and climate change scenarios on wetlands in two contrasting regions of the UK. The hydrological model shows that low and high flows are sensitive to climate change and to the regional distribution of abstractions and discharges. Where there are large changes in urbanisation, flows are more sensitive to socio-economic change. The changes in high flows have little impact on the species selected, but changes in low flows result in a number of areas becoming marginal or unsuitable due to dryness. At the regional scale, adaptation options appear to be limited and mostly involve, for surface water-influenced wetlands, increased water imports (either directly through increased non-consumptive water demand or indirectly through river augmentation), which may not be consistent with the socio-economic scenario or be feasible. This paper shows, therefore, that changes in hydrological regime are important for the future of wetlands and that these may depend as much on the future socio-economic situation as the projected changes in climate.     

Impacts of different types of temperature change on the growing season for maize

A magnetic tape containing 50 years of daily weather records was modified to synthesize new records representing three different types of temperature change. These data were used as input to a phenological response model for maize in a series of computer simulation studies. Results show cooling as much as 2°F through one type of change could reduce the freeze-free season by one month and severely affect the ability to grow corn and other warm season crops in the northern half of the U.S. Corn Belt. The same decrease with another type of change would not affect the freeze-free season. A trend for warming would increase the incidence of freezing in early planted fields and may result in spurious speculation that the climate is cooling.     

Arctic climate change with a 2 ∘C global warming: Timing, climate patterns and vegetation change

The signatories to United Nations Framework Convention on Climate Change are charged with stabilizing the concentrations of greenhouse gases in the atmosphere at a level that prevents dangerous interference with the climate system. A number of nations, organizations and scientists have suggested that global mean temperature should not rise over 2 ^°C above preindustrial levels. However, even a relatively moderate target of 2 ^°C has serious implications for the Arctic, where temperatures are predicted to increase at least 1.5 to 2 times as fast as global temperatures. High latitude vegetation plays a significant role in the lives of humans and animals, and in the global energy balance and carbon budget. These ecosystems are expected to be among the most strongly impacted by climate change over the next century. To investigate the potential impact of stabilization of global temperature at 2 ^°C, we performed a study using data from six Global Climate Models (GCMs) forced by four greenhouse gas emissions scenarios, the BIOME4 biogeochemistry-biogeography model, and remote sensing data. GCM data were used to predict the timing and patterns of Arctic climate change under a global mean warming of 2 ^°C. A unified circumpolar classification recognizing five types of tundra and six forest biomes was used to develop a map of observed Arctic vegetation. BIOME4 was used to simulate the vegetation distributions over the Arctic at the present and for a range of 2 ^°C global warming scenarios. The GCMs simulations indicate that the earth will have warmed by 2 ^°C relative to preindustrial temperatures by between 2026 and 2060, by which stage the area-mean annual temperature over the Arctic (60–90^°N) will have increased by between 3.2 and 6.6 ^°C. Forest extent is predicted by BIOME4 to increase in the Arctic on the order of 3 × 10⁶ km² or 55% with a corresponding 42% reduction in tundra area. Tundra types generally also shift north with the largest reductions in the prostrate dwarf-shrub tundra, where nearly 60% of habitat is lost. Modeled shifts in the potential northern limit of trees reach up to 400 km from the present tree line, which may be limited by dispersion rates. Simulated physiological effects of the CO₂ increase (to ca. 475 ppm) at high latitudes were small compared with the effects of the change in climate. The increase in forest area of the Arctic could sequester 600 Pg of additional carbon, though this effect is unlikely to be realized over next century.     

Regional water temperature characteristics of lakes subjected to climate change

A deterministic, validated, one-dimensional, unsteady-state lake water quality model was linked to a daily weather data base to simulate daily water temperature profiles in lakes over a period of twenty-five (1955–79) years. Twenty seven classes of lakes which are characteristic for the north-central U.S. were investigated. Output from a global climate model (GISS) was used to modify the weather data base to account for a doubling of atmospheric CO₂. The simulations predict that, after climate change, epilimnetic temperatures will be higher but increase less than air temperature, hypolimnetic temperatures in seasonally stratified dimictic lakes will be largely unchanged or even lower than at present, evaporative water loss will be increased by as much as 300 mm for the season, onset of stratification will occur earlier and overturn later in the season, and overall lake stability will become greater in spring and summer.     

The implications of climate policy for the impacts of climate change on global water resources

This paper assesses the implications of climate policy for exposure to water resources stresses. It compares a Reference scenario which leads to an increase in global mean temperature of 4 °C by the end of the 21st century with a Mitigation scenario which stabilises greenhouse gas concentrations at around 450 ppm CO₂e and leads to a 2 °C increase in 2100. Associated changes in river runoff are simulated using a global hydrological model, for four spatial patterns of change in temperature and rainfall. There is a considerable difference in hydrological change between these four patterns, but the percentages of change avoided at the global scale are relatively robust. By the 2050s, the Mitigation scenario typically avoids between 16 and 30% of the change in runoff under the Reference scenario, and by 2100 it avoids between 43 and 65%. Two different measures of exposure to water resources stress are calculated, based on resources per capita and the ratio of withdrawals to resources. Using the first measure, the Mitigation scenario avoids 8-17% of the impact in 2050 and 20-31% in 2100; with the second measure, the avoided impacts are 5-21% and 15-47% respectively. However, at the same time, the Mitigation scenario also reduces the positive impacts of climate change on water scarcity in other areas. The absolute numbers and locations of people affected by climate change and climate policy vary considerably between the four climate model patterns.     

Misperceptions of global climate change: information policies

Previous experimental studies have found that people generally misperceive the basic dynamics of renewable resources, and in particular the accumulation of greenhouse gases (GHGs) in the atmosphere. The purpose of the present laboratory experiment is to find out why people misperceive the dynamics of CO₂ accumulation and how misperceptions could be avoided. Using a simulator, 242 subjects were each asked to control total global emissions of CO₂ to reach a given target for the stock of CO₂ in the atmosphere. Consistent with previous investigations we find a strong tendency for people to overshoot the stated goal. Furthermore, our results point out that people need help to develop proper mental models of CO₂ accumulation and they need motivation to reconsider inappropriate decision heuristics. Based on these results and the literature on conceptual change a new information strategy is designed. To motivate, it imposes cognitive conflict; and to facilitate new understanding, it provides simple analogies. A new test shows promising learning effects. The results have important implications for the Intergovernmental Panel on Climate Change (IPCC), governments, and media covering the climatic change issue as well as for general education.     

气候变化背景下中国陆地水循环时空演变

水循环是气候系统各子系统相互作用过程中一个最活跃的枢纽,受气候变化影响显著。本文采用观测和多套再分析数据,系统分析了1979年以来中国及各大流域大气水汽含量、降水、蒸散发和地表径流等水循环要素年际变化。研究发现,1979-2018年,中国陆地整层大气水汽含量和水汽收支呈显著上升趋势;水汽收支除在松花江和西南诸河略有下降,其余流域均呈上升趋势;降水除西北诸河流域呈现显著上升趋势外,其余流域变化不显著;蒸散发整体呈微弱增加,但南方大部流域呈现显著的减小趋势;除西北诸河径流显著上升趋势外,北方大部分流域地表径流呈现减少趋势,而南方流域的径流变化趋势复杂多样。相对1979-2000年,21世纪以来中国年平均气温上升约0.63℃,年降水量、大气水汽含量分别增加0.5%和1.2%,水汽总输入和输出量均减小,降水再循环率增加10.9%。进入21世纪,中国陆地水资源一级分区内循环均较前20 a活跃,降水再循环率除松花江和辽河流域外,均有所增加。其中,海河、黄河、淮河和西北诸河流域的水汽和蒸发形成的降水都有所增加;辽河流域蒸发形成的降水有所增加,但输入水汽减少导致流域降水减少最多;松花江、长江、珠江和西南诸河流域蒸发形成的降水增加,输入水汽减少导致降水略有减少;东南诸河蒸发形成的降水略有增加,但整体变化不大。     

A global assessment of the impact of climate change on water scarcity

This paper presents a global scale assessment of the impact of climate change on water scarcity. Patterns of climate change from 21 Global Climate Models (GCMs) under four SRES scenarios are applied to a global hydrological model to estimate water resources across 1339 watersheds. The Water Crowding Index (WCI) and the Water Stress Index (WSI) are used to calculate exposure to increases and decreases in global water scarcity due to climate change. 1.6 (WCI) and 2.4 (WSI) billion people are estimated to be currently living within watersheds exposed to water scarcity. Using the WCI, by 2050 under the A1B scenario, 0.5 to 3.1 billion people are exposed to an increase in water scarcity due to climate change (range across 21 GCMs). This represents a higher upper-estimate than previous assessments because scenarios are constructed from a wider range of GCMs. A substantial proportion of the uncertainty in the global-scale effect of climate change on water scarcity is due to uncertainty in the estimates for South Asia and East Asia. Sensitivity to the WCI and WSI thresholds that define water scarcity can be comparable to the sensitivity to climate change pattern. More of the world will see an increase in exposure to water scarcity than a decrease due to climate change but this is not consistent across all climate change patterns. Additionally, investigation of the effects of a set of prescribed global mean temperature change scenarios show rapid increases in water scarcity due to climate change across many regions of the globe, up to 2 °C, followed by stabilisation to 4 °C.     

Multi-model assessment of global hydropower and cooling water discharge potential under climate change

Worldwide, 98% of total electricity is currently produced by thermoelectric power and hydropower. Climate change is expected to directly impact electricity supply, in terms of both water availability for hydropower generation and cooling water usage for thermoelectric power. Improved understanding of how climate change may impact the availability and temperature of water resources is therefore of major importance. Here we use a multi-model ensemble to show the potential impacts of climate change on global hydropower and cooling water discharge potential. For the first time, combined projections of streamflow and water temperature were produced with three global hydrological models (GHMs) to account for uncertainties in the structure and parametrization of these GHMs in both water availability and water temperature. The GHMs were forced with bias-corrected output of five general circulation models (GCMs) for both the lowest and highest representative concentration pathways (RCP2.6 and RCP8.5). The ensemble projections of streamflow and water temperature were then used to quantify impacts on gross hydropower potential and cooling water discharge capacity of rivers worldwide. We show that global gross hydropower potential is expected to increase between +2.4% (GCM-GHM ensemble mean for RCP 2.6) and +6.3% (RCP 8.5) for the 2080s compared to 1971–2000. The strongest increases in hydropower potential are expected for Central Africa, India, central Asia and the northern high-latitudes, with 18–33% of the world population living in these areas by the 2080s. Global mean cooling water discharge capacity is projected to decrease by 4.5-15% (2080s). The largest reductions are found for the United States, Europe, eastern Asia, and southern parts of South America, Africa and Australia, where strong water temperature increases are projected combined with reductions in mean annual streamflow. These regions are expected to affect 11–14% (for RCP2.6 and the shared socio-economic pathway (SSP)1, SSP2, SSP4) and 41–51% (RCP8.5–SSP3, SSP5) of the world population by the 2080s.     

气候变化情景下黄淮海区域热量资源及夏玉米温度适宜度

利用黄淮海区域90个站点1971—2000年逐日气象资料以及国家气候中心发布的未来气候变化情景(A1B)下区域气候模式(Reg CM3)模拟的黄淮海区域1951—2070年0.25°×0.25°格点气象资料,结合夏玉米主要生育期对温度的需求,构建了黄淮海区域的温度适宜度和变异系数模型,并对1951—2070年黄淮海区域热量资源、夏玉米主要生育期的温度适宜度及其变异系数的时空变化特征进行分析。结果表明:1)黄淮海区域≥10℃积温和80%保证率下日平均温度≥10℃的初日均呈现由北向南依次增加的趋势,且随时间推移,分别呈增加和提前趋势。2)黄淮海区域夏玉米播种—出苗期的温度适宜度随时间整体呈逐渐上升的变化趋势、其变异系数随时间呈降—升—降的变化趋势;出苗—抽雄期的温度适宜度随时间呈先降后升的变化趋势、其变异系数呈降—升—降—升的变化趋势;抽雄—成熟期的温度适宜度空间上呈现2010年前北低南高、未来情景下中部低四周高的分布趋势,时间上呈2010年前稳定、未来情景下先降后升的变化趋势,其变异系数呈相反变化趋势;3)黄淮海区域夏玉米温度适宜度及其变异系数从播种—出苗期—出苗—抽雄期—抽雄—成熟期均呈反相位的变化关系。     

The effect of global climate change, population distribution, and climate mitigation on building energy use in the U.S. and China

Climate change will affect the energy system in a number of ways, one of which is through changes in demands for heating and cooling in buildings. Understanding the potential effect of climate change on heating and cooling demands requires taking into account not only the manner in which the building sector might evolve over time, but also important uncertainty about the nature of climate change itself. In this study, we explore the uncertainty in climate change impacts on heating and cooling requirement by constructing estimates of heating and cooling degree days (HDD/CDDs) for both reference (no-policy) and 550 ppmv CO₂ concentration pathways built from three different Global Climate Models (GCMs) output and three scenarios of gridded population distribution. The implications that changing climate and population distribution might have for building energy consumption in the U.S. and China are then explored by using the results of HDD/CDDs as inputs to a detailed, building energy model, nested in the long-term global integrated assessment framework, Global Change Assessment Model (GCAM). The results across the modeled changes in climate and population distributions indicate that unabated climate change would cause building sector’s final energy consumption to decrease modestly (6 % decrease or less depending on climate models) in both the U.S. and China by the end of the century as decreased heating consumption more than offsets increased cooling using primarily electricity. However, global climate change virtually has negligible effect on total CO₂ emissions in the buildings sector in both countries. The results also indicate more substantial implications for the fuel mix with increases in electricity and decreases in other fuels, which may be consistent with climate mitigation goals. The variation in results across all scenarios due to variation of population distribution is smaller than variation due to the use of different climate models.