Probabilistic climate change projections using neural networks

Anticipated future warming of the climate system increases the need for accurate climate projections. A central problem are the large uncertainties associated with these model projections, and that uncertainty estimates are often based on expert judgment rather than objective quantitative methods. Further, important climate model parameters are still given as poorly constrained ranges that are partly inconsistent with the observed warming during the industrial period. Here we present a neural network based climate model substitute that increases the efficiency of large climate model ensembles by at least an order of magnitude. Using the observed surface warming over the industrial period and estimates of global ocean heat uptake as constraints for the ensemble, this method estimates ranges for climate sensitivity and radiative forcing that are consistent with observations. In particular, negative values for the uncertain indirect aerosol forcing exceeding –1.2 Wm^–2 can be excluded with high confidence. A parameterization to account for the uncertainty in the future carbon cycle is introduced, derived separately from a carbon cycle model. This allows us to quantify the effect of the feedback between oceanic and terrestrial carbon uptake and global warming on global temperature projections. Finally, probability density functions for the surface warming until year 2100 for two illustrative emission scenarios are calculated, taking into account uncertainties in the carbon cycle, radiative forcing, climate sensitivity, model parameters and the observed temperature records. We find that warming exceeds the surface warming range projected by IPCC for almost half of the ensemble members. Projection uncertainties are only consistent with IPCC if a model-derived upper limit of about 5 K is assumed for climate sensitivity.     

Evaluation of water and energy budgets in regional climate models applied over Europe

This study presents a model intercomparison of four regional climate models (RCMs) and one variable resolution atmospheric general circulation model (AGCM) applied over Europe with special focus on the hydrological cycle and the surface energy budget. The models simulated the 15 years from 1979 to 1993 by using quasi-observed boundary conditions derived from ECMWF re-analyses (ERA). The model intercomparison focuses on two large atchments representing two different climate conditions covering two areas of major research interest within Europe. The first is the Danube catchment which represents a continental climate dominated by advection from the surrounding land areas. It is used to analyse the common model error of a too dry and too warm simulation of the summertime climate of southeastern Europe. This summer warming and drying problem is seen in many RCMs, and to a less extent in GCMs. The second area is the Baltic Sea catchment which represents maritime climate dominated by advection from the ocean and from the Baltic Sea. This catchment is a research area of many studies within Europe and also covered by the BALTEX program. The observed data used are monthly mean surface air temperature, precipitation and river discharge. For all models, these are used to estimate mean monthly biases of all components of the hydrological cycle over land. In addition, the mean monthly deviations of the surface energy fluxes from ERA data are computed. Atmospheric moisture fluxes from ERA are compared with those of one model to provide an independent estimate of the convergence bias derived from the observed data. These help to add weight to some of the inferred estimates and explain some of the discrepancies between them. An evaluation of these biases and deviations suggests possible sources of error in each of the models. For the Danube catchment, systematic errors in the dynamics cause the prominent summer drying problem for three of the RCMs, while for the fourth RCM this is related to deficiencies in the land surface parametrization. The AGCM does not show this drying problem. For the Baltic Sea catchment, all models similarily overestimate the precipitation throughout the year except during the summer. This model deficit is probably caused by the internal model parametrizations, such as the large-scale condensation and the convection schemes.     

Recent Rapid Regional Climate Warming on the Antarctic Peninsula

The Intergovernmental Panel on Climate Change (IPCC) confirmed that mean global warming was 0.6 ± 0.2 °C during the 20th century and cited anthropogenic increases in greenhouse gases as the likely cause of temperature rise in the last 50 years. But this mean value conceals the substantial complexity of observed climate change, which is seasonally- and diurnally-biased, decadally-variable and geographically patchy. In particular, over the last 50 years three high-latitude areas have undergone recent rapid regional (RRR) warming, which was substantially more rapid than the global mean. However, each RRR warming occupies a different climatic regime and may have an entirely different underlying cause. We discuss the significance of RRR warming in one area, the Antarctic Peninsula. Here warming was much more rapid than in the rest of Antarctica where it was not significantly different to the global mean. We highlight climate proxies that appear to show that RRR warming on the Antarctic Peninsula is unprecedented over the last two millennia, and so unlikely to be a natural mode of variability. So while the station records do not indicate a ubiquitous polar amplification of global warming, the RRR warming on the Antarctic Peninsula might be a regional amplification of such warming. This, however, remains unproven since we cannot yet be sure what mechanism leads to such an amplification. We discuss several possible candidate mechanisms: changing oceanographic or changing atmospheric circulation, or a regional air-sea-ice feedback amplifying greenhouse warming. We can show that atmospheric warming and reduction in sea-ice duration coincide in a small area on the west of the Antarctic Peninsula, but here we cannot yet distinguish cause and effect. Thus for the present we cannot determine which process is the probable cause of RRR warming on the Antarctic Peninsula and until the mechanism initiating and sustaining the RRR warming is understood, and is convincingly reproduced in climate models, we lack a sound basis for predicting climate change in this region over the coming century.     

The Origins and Consequences of democratic citizens' Policy Agendas: A Study of Popular Concern about Global Warming

This article proposes and tests a model of the causes and consequences of Americans’ judgments of the national seriousness of global warming. The model proposes that seriousness judgments about global warming are a function of beliefs about the existence of global warming, attitudes toward it, the certainty with which these beliefs and attitudes are held, and beliefs about human responsibility for causing global warming and people’s ability to remedy it. The model also proposes that beliefs about whether global warming is a problem are a function of relevant personal experiences (with the weather) and messages from informants (in this case, scientists), that attitudes toward global warming are a function of particular perceived consequences of global warming, and that certainty about these attitudes and beliefs is a function of knowledge and prior thought. Data from two representative sample surveys offer support for all of these propositions, document effects of national seriousness judgments on support for ameliorative efforts generally and specific ameliorative policies, and thereby point to psychological mechanisms that may be responsible for institutional and elite impact on the public’s assessments of national problem importance and on public policy preferences.     

Is aerosol scattering in the stratosphere a safety technology preventing global warming?

In accordance with numerous investigations, global climate warming due to the increased greenhouse gas content in the atmosphere can significantly influence the environment already in the near decades. In order to mitigate or prevent possible adverse consequences of this warming the technologies on reducing greenhouse gas emissions as well as a deliberate interference with climate, including its control, are under consideration. Let us analyze the present investigations on the estimate of the influence of a simultaneous increase in the atmospheric CO₂ concentration and in the stratospheric aerosol on the global and regional climate, ozone layer, and World Ocean acidification. It is noted that the production and subsequent maintenance of the artificial aerosol layer in the stratosphere could, in principle, eliminate or retard climate warming, but it would be accompanied by a decrease in the global precipitation, especially in the tropical zone. Furthermore, the stratospheric aerosol screen does not solve the problem of the atmospheric CO₂ increase, which in turn results in the further World Ocean acidification, and thus has an adverse effect on the marine part of the biosphere. Political and ethic issues connected with the deliberate global man interference with the natural environment are also under considerations.     

全球变暖对甘肃省经济、社会和生态环境的影响及其对策

根据相关资料,分析了全球变暖的事实以及在全球变暖的大背景下对甘肃省生态环境和社会、经济的影响,并提出了应对气候变化、实现可持续发展的对策。这些对策对甘肃省而言,归纳起来主要是两个问题：一是用好水、管好水、节约用水,开发利用祁连山空中云水资源,实施人工增雨(雪);二是沙的问题。关键是遏制沙漠化进程,使用“区域气候—生态模式”,根据各地的地形、地貌、气候、水文、土壤等生态环境,定量计算各地林、草种植的品种、布局、走向、承载力,以提出恢复植被的最优方案。     

Underestimation of the Warming Trend over the Tibetan Plateau during 1998–2013 by Global Land Data Assimilation Systems and Atmospheric Reanalyses

Accurate surface air temperature (T2m) data are key to investigating eco-hydrological responses to global warming. Because of sparse in-situ observations, T2m datasets from atmospheric reanalysis or multi-source observation-based land data assimilation system (LDAS) are widely used in research over alpine regions such as the Tibetan Plateau (TP). It has been found that the warming rate of T2m over the TP accelerates during the global warming slowdown period of 1998–2013, which raises the question of whether the reanalysis or LDAS datasets can capture the warming feature. By evaluating two global LDASs, five global atmospheric reanalysis datasets, and a high-resolution dynamical downscaling simulation driven by one of the global reanalysis, we demonstrate that the LDASs and reanalysis datasets underestimate the warming trend over the TP by 27%–86% during 1998–2013. This is mainly caused by the underestimations of the increasing trends of surface downward radiation and nighttime total cloud amount over the southern and northern TP, respectively. Although GLDAS2.0, ERA5, and MERRA2 reduce biases of T2m simulation from their previous versions by 12%-94%, they do not show significant improvements in capturing the warming trend. The WRF dynamical downscaling dataset driven by ERA-Interim shows a great improvement, as it corrects the cooling trend in ERA-Interim to an observation-like warming trend over the southern TP. Our results indicate that more efforts are needed to reasonably simulate the warming features over the TP during the global warming slowdown period, and the WRF dynamical downscaling dataset provides more accurate T2m estimations than its driven global reanalysis dataset ERA-Interim for producing LDAS products over the TP.     

美国公众对全球变暖的认知和对气候政策的支持

利用民意调查数据,以相关研究作为补充,分析美国公众对全球变暖的认知、减缓行为和气候政策的支持等。分析表明,大部分美国民众认为全球在变暖,但很多人不了解全球变暖与温室气体的关系,把全球变暖混为大气污染和臭氧层耗竭等;不到一半的公众认为全球变暖对个人和美国是现实威胁,更多的公众认为全球变暖对后代和发展中国家是严重威胁;大部分公众认为减缓全球变暖需要改变现有的生活方式和行为,他们愿意选择较容易从事和成本低的行为减少碳排放,但不愿意从根本上改变生活方式,改变自驾车、乘飞机长途旅游这些碳排放量更大的行为;公众普遍支持政府采取措施限制温室气体排放,但不希望所采取的措施对就业和经济带来不利影响;支持通过技术进步和减免税收等措施提高能效,减少碳排放,但大部分反对为节能而提高能源税收。     

Insights into the Microwave Instruments Onboard the Fengyun 3DSatellite: Data Quality and Assimilation in theMet Office NWP System

正1Met Office, Exeter EX1 3PB, UK2National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China     

Climate change in mountains: a review of elevation-dependent warming and its possible causes

Available observations suggest that some mountain regions are experiencing seasonal warming rates that are greater than the global land average. There is also evidence from observational and modeling studies for an elevation-dependent climate response within some mountain regions. Our understanding of climate change in mountains, however, remains challenging owing to inadequacies in observations and models. In fact, it is still uncertain whether mountainous regions generally are warming at a different rate than the rest of the global land surface, or whether elevation-based sensitivities in warming rates are prevalent within mountains. We review studies of four high mountain regions – the Swiss Alps, the Colorado Rocky Mountains, the Tibetan Plateau/Himalayas, and the Tropical Andes – to examine questions related to the sensitivity of climate change to surface elevation. We explore processes that could lead to enhanced warming within mountain regions and possible mechanisms that can produce altitudinal gradients in warming rates on different time scales. A conclusive understanding of these responses will continue to elude us in the absence of a more comprehensive network of climate monitoring in mountains.     

European temperatures in CMIP5: origins of present-day biases and future uncertainties

European temperatures and their projected changes under the 8.5 W/m² Representative Concentration Pathway scenario are evaluated in an ensemble of 33 global climate models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Respective contributions of large-scale dynamics and local processes to both biases and changes in temperatures, and to the inter-model spread, are then investigated from a recently proposed methodology based on weather regimes. On average, CMIP5 models exhibit a cold bias in winter, especially in Northern Europe. They overestimate summer temperatures in Central Europe, in association with a greater diurnal range than observed. The projected temperature increase is stronger in summer than in winter, with the highest summer warming occurring over Mediterranean regions. Links between biases and sensitivities are evidenced in winter, suggesting a potential influence of snow cover biases on the projected surface warming. A brief analysis of daily temperature extremes suggests that the intra-seasonal variability is projected to decrease (slightly increase) in winter (summer). Then, in order to understand model discrepancies in both present-day and future climates, we disentangle effects of large-scale atmospheric dynamics and regional physical processes. In particular, in winter, CMIP5 models simulate a stronger North-Atlantic jet stream than observed and, in contrast with CMIP3 results, the majority of them suggests an increased frequency of the negative phase of the North-Atlantic Oscillation under future warming. While large-scale circulation only has a minor contribution to ensemble-mean biases or changes, which are primarily dominated by non-dynamical processes, it substantially affects the inter-model spread. Finally, other sources of uncertainties, including the North-Atlantic warming and local radiative feedbacks related to snow cover and clouds, are briefly discussed.     

近44年南京温度变化的特征及其可能原因的分析

利用1957～2000年的气候观测资料,研究南京的平均温度、平均最高温度、平均最低温度和平均日较差及炎热日和寒冷日的变化趋势和特点,并分析可能的原因;以滁县和溧阳为对比城市站,分析了三种不同类型城市温度变化的异同.结果表明,近44年来南京平均温度显著上升,其中冬季增暖幅度最大,但夏季呈变凉趋势.与全国平均温度相比,线性变化趋势大体相似,但也存在一定差别.最高温度趋势与平均温度一致,夏季降温更为明显;最低温度除夏季外增暖都非常显著,表明气候变暖在最低温度上表现更加明显;年和各季日较差均明显减小;炎热日和寒冷日趋于减少,其开始和结束时间较以前有明显提前.大气环流系统的变异和调整可能是温度显著升高的直接原因.同样,长江中下游夏季降水天气增多、云量增加、日照时间减少以及伴随的温度下降可能也与环流系统的调整有关.南京与滁县、溧阳的温度差值分别为减小趋势或趋势变化不明显.三种类型城市增暖幅度的相对大小存在着年代际差异.由于不同类型城市间温度变化差异的复杂特点及其所反映出的城市化影响的复杂性,在研究温度变化和考虑城市化的影响时,不仅要考虑大城市,还应该充分注意中、小城市的发展所带来的影响.     

BCC_CSM1.1(m) 模式对热带太平洋潜热通量的评估

利用1979—2005年OAFlux (Objectively Analyzed air-sea Fluxes) 观测资料以及CMIP5的15个耦合模式的模拟结果,评估了BCC_CSM1.1(m) 模式对热带太平洋年平均潜热通量气候态和变化趋势的模拟能力,并分析造成趋势偏差的可能原因。结果表明:BCC_CSM1.1(m) 模式模拟热带太平洋年平均潜热通量气候态在各纬度上差异较大, 其中在赤道的模拟能力较佳,而在10°N和8°S附近模拟偏差较大;BCC_CSM1.1(m) 模式对热带太平洋年平均潜热通量趋势的模拟能力一般,造成趋势偏差的主要原因是该模式低估了风速对潜热通量的局地贡献以及它对风速的非局地贡献的模拟存在较大偏差。此外,该模式未能较好地模拟出风速对全球变暖响应。因此,BCC_CSM1.1(m) 模式对热带太平洋年平均潜热通量趋势模拟的改进需加强其对风速模拟的改进。     

Public concern over global warming correlates negatively with national wealth

It has been shown previously that the awareness and concern of the general public about global warming is not only a function of scientific information. Both psychological and sociological factors affect the willingness of laypeople to acknowledge the reality of global warming, and to support climate policies of their home countries. In this paper, I analyse a cross-national dataset of public concern about global warming, utilising data from 46 countries. Based on earlier results at the national and regional level, I expect concern to be negatively correlated to national measures of wealth and carbon dioxide emissions. I find that gross domestic product is indeed negatively correlated to the proportion of a population that regards global warming as a serious problem. There is also a marginally significant tendency that nations’ per capita carbon dioxide emissions are negatively correlated to public concern. These findings suggest that the willingness of a nation to contribute to reductions in greenhouse gas emissions decreases with its share of these emissions. This is in accordance with psychological findings, but poses a problem for political decision-makers. When communicating with the public, scientists ought to be aware of their responsibility to use a language that is understood by laypeople.     

Institutions,climate change and cultural theory: towards a common analytical framework

Institutions are the multitude of means for holding society together, for giving it a sense of purpose and for enabling it to adapt. Institutions help to define climate change both as a problem and a context, through such socialised devices as the use of scientific knowledge, culturally defined interpretation of scientific findings, and politically tolerable adaptation strategies. This paper briefly reviews the origins and current status of the ‘new’ institutional theories that have recently developed within the social sciences. The conclusion is that they are based on such contradictory interpretations of human behaviour that, although appealing, a complete synthesis will never be possible. In effect, there is a fundamental institutional ‘failure’ over the interpretation and resolution of climate change. Cultural theory helps to explain why this is the case by throwing light on the inherent contradictions that beset us all when confronted with global warming.     

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.     

The role of natural climatic variation in perturbing the observed global mean temperature trend

Controversy continues to prevail concerning the reality of anthropogenically-induced climatic warming. One of the principal issues is the cause of the hiatus in the current global warming trend. There appears to be a widely held view that climatic change warming should exhibit an inexorable upwards trend, a view that implies there is no longer any input by climatic variability in the existing climatic system. The relative roles of climatic change and climatic variability are examined here using the same coupled global climatic model. For the former, the model is run using a specified CO₂ growth scenario, while the latter consisted of a multi-millennial simulation where any climatic variability was attributable solely to internal processes within the climatic system. It is shown that internal climatic variability can produce global mean surface temperature anomalies of ±0.25?K and sustained positive and negative anomalies sufficient to account for the anomalous warming of the 1940s as well as the present hiatus in the observed global warming. The characteristics of the internally-induced negative temperature anomalies are such that if this internal natural variability is the cause of the observed hiatus, then a resumption of the observed global warming trend is to be expected within the next few years.     

北太平洋的年代际振荡与全球变暖

通过回顾和总结前人工作,特别是有关北太平洋年代际振荡的研究,针对近50年来北太平洋中纬度海温变冷的现象进行了分析与讨论。从全球气候变化的角度,总结了影响北太平洋中纬度海温变冷现象的几种可能机制,推测了全球气温变暖可能会对北太平洋的直接或间接影响,归纳指出了研究该问题的复杂性与目前面临的困难。     

Who remembers a hot summer or a cold winter? The asymmetric effect of beliefs about global warming on perceptions of local climate conditions in the U.S.

This paper explores the phenomenon of local climate perception and the extent to which public perceptions match climate conditions as recorded in instrumental climate data. We further examine whether perceptions of changes in local climates are influenced by prior beliefs about global warming, through the process of motivated reasoning. Using national survey data collected in the United States in 2011, we find that subjective experiences of seasonal average temperature and precipitation during the previous winter and summer were related to recorded conditions during each season. Beliefs about global warming also had significant effects on subjective experiences with above-normal temperatures, particularly among those who believed that global warming is not happening. When asked about the summer of 2010, those who believed that global warming is not happening were significantly less likely to report that they had experienced a warmer-than-normal summer, even when controlling for demographics and local climate conditions. These results suggest that the subjective experience of local climate change is dependent not only on external climate conditions, but also on individual beliefs, with perceptions apparently biased by prior beliefs about global warming.     

Impacts of climate change on growth, migration and recruitment success of Japanese sardine (Sardinops melanostictus) in the western North Pacific

We developed a multi-trophic level ecosystem model by coupling physical, biogeochemical-plankton and fish models. An oceanic general circulation model was coupled with a lower trophic level ecosystem model and a Japanese sardine migration model, and applied to the western North Pacific. To investigate the impact of global warming on the pelagic fish ecosystem, such as Japanese sardine, we conducted numerical experiments of growth and migration of Japanese sardine using physical fields for the present day and future with a global warming scenario simulated by a high-resolution climate model. The model results demonstrated possible impacts of global warming on the growth and migration pattern of Japanese sardine. The growths of fish in the current main spawning region under the global warming scenario were significantly slower than those under the present climate scenario. Fish in this region will be at disadvantage for their recruitment under the global warming condition. Prey conditions in the spawning region were projected not to markedly change under global warming condition while water temperature increased. As a result sardine spawning ground was projected to shift towards more north areas. During the feeding migration period in summer, geographical distribution of juveniles fish was projected to shift northwards by one to two degrees latitude under the global warming condition following the change in the distribution of optimal temperature region for feeding. However, this northwards shift of the optimal temperature for feeding was minimized adjacent to the western North Pacific by the cooler water supply by the intensification of the Oyashio.