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爸爸去哪儿第一季,第一工作组,第一会所,第一财经

时间:2013-10-04 来源: 康兴达文摘网

2013年9月24日 - ????9月23日,联合国政府间气候变化专门委员会 (IPCC)第五次评估报告(AR5)第一工作组第12次会议暨IPCC第36次全会在瑞典斯德哥尔摩召开.中国...

气候变化 2013 自然科学基础 决策者摘要 WG I 政府间气候变化专门委员会 第五次评估报告 第一 工作组报告 封面图片:挪威南峡湾高原上的福尔格冰川(60°03’ N - 6°20’ E)? Yann Arthus-Bertrand / Altitude. IPCC 2013年10月于瑞士印刷。本决策者摘要的电子版见IPCC网站www.ipcc.ch和IPCC WGI AR5网站 www.climatechange2013.org。

? 2013 政府间气候变化专门委员会 气候变化2013 自然科学基础 政府间气候变化专门委员会 第五次评估报告 第一工作组报告 决策者摘要 编辑 Thomas F. Stocker 第一工作组联合主席 伯尔尼大学 秦大河 第一工作组联合主席 中国气象局 Judith Boschung 行政助理 Pauline M. Midgley 组长 ian-Kasper Plattner Melinda M.B. Tignor G Simon K. Allen 科学主任 业务主任 高级科学官 Alexander Nauels Yu Xia Vincent Bex 科学助理 科学官 IT官 第一工作组技术支持小组 1 SPM Summary for Policymakers Drafting Authors: Lisa V. Alexander (Australia), Simon K. Allen (Switzerland/New Zealand), Nathaniel L. Bindoff (Australia), Fran?ois-Marie Bréon (France), John A. Church (Australia), Ulrich Cubasch (Germany), Seita Emori (Japan), Piers Forster (UK), Pierre Friedlingstein (UK/Belgium), Nathan Gillett (Canada), Jonathan M. Gregory (UK), Dennis L. Hartmann (USA), Eystein Jansen (Norway), Ben Kirtman (USA), Reto Knutti (Switzerland), Krishna Kumar Kanikicharla (India), Peter Lemke (Germany), Jochem Marotzke (Germany), Valérie Masson-Delmotte (France), Gerald A. Meehl (USA), Igor I. Mokhov (Russian Federation), Shilong Piao (China), Gian-Kasper Plattner (Switzerland), Qin Dahe (China), Venkatachalam Ramaswamy (USA), David Randall (USA), Monika Rhein (Germany), Maisa Rojas (Chile), Christopher Sabine (USA), Drew Shindell (USA), Thomas F. Stocker (Switzerland), Lynne D. Talley (USA), David G. Vaughan (UK), ShangPing Xie (USA) Draft Contributing Authors: Myles R. Allen (UK), Olivier Boucher (France), Don Chambers (USA), Jens Hesselbjerg Christensen (Denmark), Philippe Ciais (France), Peter U. Clark (USA), Matthew Collins (UK), Josefino C. Comiso (USA), Viviane Vasconcellos de Menezes (Australia/Brazil), Richard A. Feely (USA), Thierry Fichefet (Belgium), Arlene M. Fiore (USA), Gregory Flato (Canada), Jan Fuglestvedt (Norway), Gabriele Hegerl (UK/Germany), Paul J. Hezel (Belgium/USA), Gregory C. Johnson (USA), Georg Kaser (Austria/Italy), Vladimir Kattsov (Russian Federation), John Kennedy (UK), Albert M. G. Klein Tank (Netherlands), Corinne Le Quéré (UK), Gunnar Myhre (Norway), Timothy Osborn (UK), Antony J. Payne (UK), Judith Perlwitz (USA), Scott Power (Australia), Michael Prather (USA), Stephen R. Rintoul (Australia), Joeri Rogelj (Switzerland/Belgium), Matilde Rusticucci (Argentina), Michael Schulz (Germany), Jan Sedlá?ek (Switzerland), Peter A. Stott (UK), Rowan Sutton (UK), Peter W. Thorne (USA/Norway/UK), Donald Wuebbles (USA) This Summary for Policymakers should be cited as: IPCC, 2013: Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 1 1 SPM 决策者摘要 撰稿作者:

Lisa Alexander(澳大利亚)、Simon Allen(瑞士/新西兰)、Nathaniel L. Bindoff(澳大利亚)、Fran?ois-Marie Bréon(法国)、John A. Church(澳 大利亚)、Ulrich Cubasch(德国)、Seita Emori(日本)、Piers Forster (英国)、Pierre Friedlingstein(英国/比利时)、Nathan Gillett(加拿 大)、Jonathan M. Gregory(英国)、Dennis L. Hartmann(美国)、Eystein Jansen(挪威)、Ben Kirtman(美国)、Reto Knutti(瑞士)、Krishna Kumar Kanikicharla(印度)、Peter Lemke(德国)、Jochem Marotzke (德国)、Valerie Masson-Delmotte(法国)、Gerald A. Meehl(美国)、 Igor I. Mokhov(俄罗斯)、朴世龙(中国)、Gian-Kasper Plattner (瑞士)、秦大河(中国)、Venkatachalam Ramaswamy(美国)、David Randall(美国)、Monika Rhein(德国)、Maisa Rojas(智利)、Christopher Sabine(美国)、Drew Shindell(美国)、Thomas F. Stocker(瑞士)、Lynne D. Talley(美国)、David G. Vaughan(英国)、谢尚平(美国) 撰稿贡献作者:

Myles R. Allen(英国)、Olivier Boucher(法国)、Don C h a m b e r s ( 美 国)、Jens Hesselbjerg Christensen(丹麦)、Philippe Ciais(法国)、 Peter U. Clark(美国)、Matthew Collins(英国)、Josefino C. Comiso (美国)、Viviane Vasconcellos de Menezes(澳大利亚/巴西)、Richard A. Feely(美国)、 Thierry Fichefet (比利时)、Arlene M. Fiore (美国)、Gregory Flato(加拿大)、Jan Fuglestvedt(挪威)、Gabriele Hegerl(英国/德国)、Paul J. Hezel(比利时/美国)、Gregory C. Johnson (美国)、Georg Kaser(奥地利/意大利)、Vladimir Kattsov(俄罗斯联 邦)、John Kennedy(英国)、Albert M. G. Klein Tank(荷兰)、Corinne Le Quéré(英国)、Gunnar Myhre(挪威)、Tim Osborn(英国)、Antony J. Payne(英国)、Judith Perlwitz(美国)、Scott Power(澳大利亚)、Michael Prather (美国)、Stephen R. Rintoul(澳大利亚)、Joeri Rogelj(瑞士/ 比利时)、Matilde Rusticucci(阿根廷)、Michael Schulz(德国)、Jan Sedlá?ek(瑞士)、Peter A. Stott(英国)、Rowan Sutton(英国)、Peter W. Thorne(美国/挪威/英国)、Donald Wuebbles(美国) 本决策者摘要的引用格式如下:

IPCC, 2013:决策者摘要。政府间气候变化专门委员会第五次评估报告第一工作组报告——气 候变化2013:自然科学基础。[Stocker, T.F., 秦大河, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex 和 P.M. Midgley (编辑)]。剑桥大学出版 社,英国剑桥和美国纽约。 1 Summary for Policymakers A. Introduction The Working Group I contribution to the IPCC’s Fifth Assessment Report (AR5) considers new evidence of climate change based on many independent scientific analyses from observations of the climate system, paleoclimate archives, theoretical studies of climate processes and simulations using climate models. It builds upon the Working Group I contribution to the IPCC’s Fourth Assessment Report (AR4), and incorporates subsequent new findings of research. As a component of the fifth assessment cycle, the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) is an important basis for information on changing weather and climate extremes. This Summary for Policymakers (SPM) follows the structure of the Working Group I report. The narrative is supported by a series of overarching highlighted conclusions which, taken together, provide a concise summary. Main sections are introduced with a brief paragraph in italics which outlines the methodological basis of the assessment. The degree of certainty in key findings in this assessment is based on the author teams’ evaluations of underlying scientific understanding and is expressed as a qualitative level of confidence (from very low to very high) and, when possible, probabilistically with a quantified likelihood (from exceptionally unlikely to virtually certain). Confidence in the validity of a finding is based on the type, amount, quality, and consistency of evidence (e.g., data, mechanistic understanding, theory, models, expert judgment) and the degree of agreement1. Probabilistic estimates of quantified measures of uncertainty in a finding are based on statistical analysis of observations or model results, or both, and expert judgment2. Where appropriate, findings are also formulated as statements of fact without using uncertainty qualifiers. (See Chapter 1 and Box TS.1 for more details about the specific language the IPCC uses to communicate uncertainty). The basis for substantive paragraphs in this Summary for Policymakers can be found in the chapter sections of the underlying report and in the Technical Summary. These references are given in curly brackets. SPM B. Observed Changes in the Climate System Observations of the climate system are based on direct measurements and remote sensing from satellites and other platforms. Global-scale observations from the instrumental era began in the mid-19th century for temperature and other variables, with more comprehensive and diverse sets of observations available for the period 1950 onwards. Paleoclimate reconstructions extend some records back hundreds to millions of years. Together, they provide a comprehensive view of the variability and long-term changes in the atmosphere, the ocean, the cryosphere, and the land surface. Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased (see Figures SPM.1, SPM.2, SPM.3 and SPM.4). {2.2, 2.4, 3.2, 3.7, 4.2–4.7, 5.2, 5.3, 5.5–5.6, 6.2, 13.2} 1 In this Summary for Policymakers, the following summary terms are used to describe the available evidence: limited, medium, or robust;

and for the degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g., medium confidence. For a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence (see Chapter 1 and Box TS.1 for more details). In this Summary for Policymakers, the following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely: 95–100%, more likely than not >50–100%, and extremely unlikely 0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, e.g., very likely (see Chapter 1 and Box TS.1 for more details). 2 2 决策者摘要 A. 引言 IPCC第五次评估报告(AR5)第一工作组报告考虑了气候变化的新证据,这些新证据建立在对气候系统观 测、古气候档案、气候过程理论研究和气候模式模拟等的独立科学分析基础之上。本报告以IPCC第四次 SPM 评估报告(AR4)第一工作组报告为基础,并吸收了后续研究中的新发现。作为第五次评估周期的一部 分,IPCC《管理极端事件和灾害风险,推进气候变化适应特别报告》(SREX)是本报告有关极端天气和气 候事件变化信息的一个重要基础。

本《决策者摘要》(SPM)沿用了第一工作组报告的结构。内容叙述得到了加底色突出的一系列总体结论的 支持,这些总体结论可以一起构成一份简明摘要。本摘要每个主要部分均以斜体字起始段对该部分的评估 方法基础进行了简要介绍。

本评估报告根据作者团队对基础科学认知水平的评估给出各重要发现的确定性程度,以信度水平(从很 低到很高)来定性表述,并在可能的条件下,使用概率来量化表述出现的可能性(从极不可能到几乎确 定)。某一发现有效性信度的基础是证据的类型、数量、质量和一致性(如:数据、对机理的认识、理 论、模式、专家判断)及其一致性的程度1。对某一发现不确定性概率的定量估计建立在对观测或模式结果 或对两者的统计分析以及专家判断2的基础之上。在合适的情况下,对作为事实陈述的某些发现,不使用不 确定性词语。(关于IPCC不确定性表述所使用的特定语言,详见第1章和文框TS.1) 本《决策者摘要》中实质性段落的依据来自本评估报告全文的相关章节和《技术摘要》,并在大括号中给 出了索引信息。 B. 观测到的气候系统变化 气候系统的观测基于直接测量和卫星及其它平台的遥感手段。器测时代对全球尺度温度和其它变量的 观测始于19世纪中叶,1950年以来的观测更为全面和丰富。古气候重建可使一些记录延伸到几百年乃 至几百万年前。以上信息提供了有关大气、海洋、冰冻圈和地表的变率和长期变化的综合视角。 气候系统的变暖是毋庸置疑的。自20世纪50年代以来,观测到的许多变 化在几十年乃至上千年时间里都是前所未有的。大气和海洋已变暖,积雪 和冰量已减少,海平面已上升,温室气体浓度已增加。(见图SPM.1、 SPM.2、SPM.3和SPM.4)。{2.2, 2.4, 3.2, 3.7, 4.2-4.7, 5.2, 5.3, 5.5-5.6, 6.2, 13.2} 1 在本《决策者摘要》中,使用下列术语描述证据的可获得性:有限、中等,或确凿;对于证据的一致性使用:低、中等或高。用五个限定词 表述信度水平:很低、低、中等、高和很高,并用斜体字标出,如:中等信度。对于某一给定的证据和一致性的陈述,可以赋予不同的信度 水平,但随着证据增多、一致性程度提高,相应的信度也增加(详见第1章和文框TS.1)。

在本《决策者摘要》中,使用下列术语来评估某一成果或结果的可能性:几乎确定的概率为99–100%、很可能的概率为90–100%、可能的概 率为66–100%、或许可能的概率为33–66%、不可能的概率为0–33%、很不可能的概率为0–10%、几乎不可能的概率为0–1%。还可酌情使用 其它术语(极可能的概率为95–100%、多半可能的概率为>50–100%,以及极不可能的概率为0–5%)。可能性的评估均采用斜体字,如:

很 可能(详见第1章和文框TS.1)。 2 2 Summary for Policymakers B.1 Atmosphere Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decade since 1850 (see Figure SPM.1). In the Northern Hemisphere, 1983–2012 was likely the warmest 30-year period of the last 1400 years (medium confidence). {2.4, 5.3} SPM ? The globally averaged combined land and ocean surface temperature data as calculated by a linear trend, show a warming of 0.85 [0.65 to 1.06] °C3, over the period 1880 to 2012, when multiple independently produced datasets exist. The total increase between the average of the 1850–1900 period and the 2003–2012 period is 0.78 [0.72 to 0.85] °C, based on the single longest dataset available 4 (see Figure SPM.1). {2.4} ? For the longest period when calculation of regional trends is sufficiently complete (1901 to 2012), almost the entire globe has experienced surface warming (see Figure SPM.1). {2.4} ? In addition to robust multi-decadal warming, global mean surface temperature exhibits substantial decadal and interannual variability (see Figure SPM.1). Due to natural variability, trends based on short records are very sensitive to the beginning and end dates and do not in general reflect long-term climate trends. As one example, the rate of warming over the past 15 years (1998–2012;

0.05 [–0.05 to 0.15] °C per decade), which begins with a strong El Ni?o, is smaller than the rate calculated since 1951 (1951–2012;

0.12 [0.08 to 0.14] °C per decade)5. {2.4} ? Continental-scale surface temperature reconstructions show, with high confidence, multi-decadal periods during the Medieval Climate Anomaly (year 950 to 1250) that were in some regions as warm as in the late 20th century. These regional warm periods did not occur as coherently across regions as the warming in the late 20th century (high confidence). {5.5} ? It is virtually certain that globally the troposphere has warmed since the mid-20th century. More complete observations allow greater confidence in estimates of tropospheric temperature changes in the extratropical Northern Hemisphere than elsewhere. There is medium confidence in the rate of warming and its vertical structure in the Northern Hemisphere extra-tropical troposphere and low confidence elsewhere. {2.4} ? Confidence in precipitation change averaged over global land areas since 1901 is low prior to 1951 and medium afterwards. Averaged over the mid-latitude land areas of the Northern Hemisphere, precipitation has increased since 1901 (medium confidence before and high confidence after 1951). For other latitudes area-averaged long-term positive or negative trends have low confidence (see Figure SPM.2). {TS TFE.1, Figure 2;

2.5} ? Changes in many extreme weather and climate events have been observed since about 1950 (see Table SPM.1 for details). It is very likely that the number of cold days and nights has decreased and the number of warm days and nights has increased on the global scale6. It is likely that the frequency of heat waves has increased in large parts of Europe, Asia and Australia. There are likely more land regions where the number of heavy precipitation events has increased than where it has decreased. The frequency or intensity of heavy precipitation events has likely increased in North America and Europe. In other continents, confidence in changes in heavy precipitation events is at most medium. {2.6} 3 In the WGI contribution to the AR5, uncertainty is quantified using 90% uncertainty intervals unless otherwise stated. The 90% uncertainty interval, reported in square brackets, is expected to have a 90% likelihood of covering the value that is being estimated. Uncertainty intervals are not necessarily symmetric about the corresponding best estimate. A best estimate of that value is also given where available. Both methods presented in this bullet were also used in AR4. The first calculates the difference using a best fit linear trend of all points between 1880 and 2012. The second calculates the difference between averages for the two periods 1850–1900 and 2003–2012. Therefore, the resulting values and their 90% uncertainty intervals are not directly comparable. {2.4} Trends for 15-year periods starting in 1995, 1996, and 1997 are 0.13 [0.02 to 0.24] °C per decade, 0.14 [0.03 to 0.24] °C per decade, and, 0.07 [–0.02 to 0.18] °C per decade, respectively. See the Glossary for the definition of these terms: cold days/cold nights, warm days/warm nights, heat waves. 4 5 6 3 决策者摘要 B.1 大气 过去三个十年的地表已连续偏暖于1850年以来的任何一个十年。在北半 球,1983-2012年可能是过去1400年中最暖的30年(中等信度)。{2.4, 5.3} SPM ? 全球平均陆地和海洋表面温度的线性趋势计算结果表明,在1880-2012年期间(存在多套独立制作的数 据集)温度升高了0.85[0.65至1.06]°C3。基于现有的一个单一最长数据集4,1850-1900年时期和20032012年时期的平均温度之间的总升温幅度为0.78 [0.72至0.85]°C。(见图SPM.1){2.4} ? 在有足够完整的资料以计算区域趋势的最长时期内(1901-2012年),全球几乎所有地区都经历了地表 增暖。(见图SPM.1){2.4} ? 除 了 存 在 确 凿 的 多 年 代 际 变 暖 外 , 全 球 地 表 平 均 温 度 还 表 现 出 明 显 的 年 代 际 和 年 际 变 化 ( 见 图 SPM1)。由于自然变率,选取不同的起止期,对短期记录趋势的计算是非常敏感的,而且一般不能反 映长期气候趋势。例如,始于强厄尔尼诺事件的过去15年间的升温速率(1998-2012年;每十年温度升 高0.05[-0.05至+0.15]°C)小于1951年以来的升温速率(1951-2012年;每十年温度升高0.12[0.08至 0.14]°C)5。{2.4} ? 大陆尺度的地表温度重建表明:具有高信度的是,在中世纪气候异常期(950至1250年)中的多个年代 内一些区域的温暖程度与20世纪后期相当,但是这些区域性暖期并没有像20世纪后期的变暖那样出现区 域一致性(高信度)。{5.5} ? 几乎确定的是,自20世纪中叶以来,在全球范围内对流层已变暖。更完整的观测使北半球热带以外地区 的对流层温度变化的估算值比其它地区具有更高的信度。北半球热带以外对流层的变暖速率及其垂直结 构变化具有中等信度,而在其它地区只具有低信度。{2.4} ? 1901年以来,全球陆地区域平均降水变化在1951年之前为低信度,之后为中等信度。1901年以来,北半球 中纬度陆地区域平均降水已增加(在1951年之前为中等信度,之后为高信度)。对于其它纬度,区域平 均降水的增加或减少的长期趋势只具有低信度。(见图SPM.2)。{TSTFE.1, 图2;2.5} ? 约自1950年以来,已观测到了许多极端天气和气候事件的变化(详见表SPM.1)。很可能的是,在全球 尺度上冷昼和冷夜的天数已减少,而暖昼和暖夜的天数已增加6。在欧洲、亚洲和澳大利亚的大部分地 区,热浪的发生频率可能已增加。与降水减少的区域相比,更多陆地区域出现强降水事件的数量可能已 增加。在北美洲和欧洲,强降水事件的频率或强度可能均已增加。在其它各洲,强降水事件变化的信度 最高为中等。{2.6} 3 在第五次评估报告第一工作组报告中,除非另有说明,不确定性用90%不确定性区间进行量化。方括号内给出的90%不确定性区间表示这一区 间预计有90%的可能性涵盖了估算值。不确定性区间与相应最佳估算值之间不一定是对称关系。只要有最佳估算值则给出。

在第四次评估报告中也采用了这一要点中提到的两种方法。第一种方法利用1880-2012年间所有点的最佳拟合线性趋势计算温度差。第二种方 法计算1850-1900年和2003-2012年两个时期的平均温度差。因此,这两种方法得出的值及其90%不确定性区间不具有直接的可比性(2.4)。

从1995年、1996年和1997年开始的三个15年期的趋势分别为每十年温度升高0.13[0.02至0.24] °C、0.14[0.03至0.24] °C和0.07[–0.02至 0.18]°C。

这些术语的定义见术语表:冷昼/冷夜、暖昼/暖夜、热浪。 4 5 6 3 Summary for Policymakers (a) 0.6 SPM Observed globally averaged combined land and ocean surface temperature anomaly 1850–2012 Annual average 0.4 Temperature anomaly (°C) relative to 1961–1990 0.2 0.0 ?0.2 ?0.4 ?0.6 0.6 0.4 0.2 0.0 ?0.2 ?0.4 ?0.6 1850 1900 Decadal average Year 1950 2000 (b) Observed change in surface temperature 1901–2012 ?0.6 ?0.4 ?0.2 0 0.2 0.4 0.6 0.8 1.0 1.25 1.5 1.75 2.5 (°C) Figure SPM.1 | (a) Observed global mean combined land and ocean surface temperature anomalies, from 1850 to 2012 from three data sets. Top panel: annual mean values. Bottom panel: decadal mean values including the estimate of uncertainty for one dataset (black). Anomalies are relative to the mean of 1961?1990. (b) Map of the observed surface temperature change from 1901 to 2012 derived from temperature trends determined by linear regression from one dataset (orange line in panel a). Trends have been calculated where data availability permits a robust estimate (i.e., only for grid boxes with greater than 70% complete records and more than 20% data availability in the first and last 10% of the time period). Other areas are white. Grid boxes where the trend is significant at the 10% level are indicated by a + sign. For a listing of the datasets and further technical details see the Technical Summary Supplementary Material. {Figures 2.19–2.21;

Figure TS.2} 4 决策者摘要 (a) 0.6 0.4 SPM ?????????????????????? –?? ?? 0.2 ?????!–!!??????+ 0.0 ?0.2 ?0.4 ?0.6 0.6 0.4 0.2 0.0 ?0.2 ?0.4 ?0.6 1850 1900 ???? ? 1950 2000 (b) ?????????????!–?? ?0.6 ?0.4 ?0.2 0 0.2 0.4 0.6 0.8 1.0 1.25 1.5 1.75 2.5 (°C) 图SPM.1:(a)观测到的全球平均陆地和海表温度距平(1850-2012年),源自三个资料集。上图:年均值,下图:十年均值, 包括一个资料集(黑色)的不确定性估计值。各距平均相对于1961–1990年均值。(b)观测到的地表温度变化(1901-2012 年),温度变化值是通过对某一资料集(图a中的橙色曲线)进行线性回归所确定的趋势计算得出的。只要可用资料能够得出确 凿估算值,均对其趋势作了计算(即仅限于该时期前10%和后10%时段内,观测记录完整率超过70%并且资料可用率大于20%的格 点),其它地区为白色。凡是趋势达到10%显著性的格点均用“+”号表示。有关资料集清单和更多技术细节,详见技术摘要的 补充材料{图2.19–2.21;图TS.2} 4 Table SPM.1 | Extreme weather and climate events: Global-scale assessment of recent observed changes, human contribution to the changes, and projected further changes for the early (2016–2035) and late (2081–2100) 21st century. Bold indicates where the AR5 (black) provides a revised* global-scale assessment from the SREX (blue) or AR4 (red). Projections for early 21st century were not provided in previous assessment reports. Projections in the AR5 are relative to the reference period of 1986–2005, and use the new Representative Concentration Pathway (RCP) scenarios (see Box SPM.1) unless otherwise specified. See the Glossary for definitions of extreme weather and climate events. Assessment of a human contribution to observed changes Early 21st century Likely {11.3} Virtually certain Virtually certain? {10.6} Virtually certain Virtually certain Not formally assessedb {11.3} Very likely Very likely {7.6, 10.6} Likely over many land areas {11.3} Very likely over most of the mid-latitude land masses and over wet tropical regions Likely over many areas Very likely over most land areas {10.6} Low confidenceg {11.3} Likely (medium confidence) on a regional to global scaleh Medium confidence in some regions Likelye Low confidence {11.3} More likely than not in the Western North Pacific and North Atlantic j More likely than not in some basins Likely Likely l {13.7} Very likely l {13.7} Very likely m Likely {14.6} {12.4} {12.4} Very likely {12.4} Likely {11.3} Virtually certain {12.4} Phenomenon and direction of trend Late 21st century Virtually certain {12.4} Very likely {10.6} Likely Likely {2.6} Likely Likely (nights only) {2.6} Not formally assessed More likely than not Medium confidence Medium confidence More likely than not Low confidence Medium confidencef More likely than not {2.6} Low confidence More likely than not {3.7} Likely More likely than not k k Assessment that changes occurred (typically since 1950 unless otherwise indicated) Likelihood of further changes Warmer and/or fewer cold days and nights over most land areas Very likely Very likely {2.6} Very likely Very likely Warmer and/or more frequent hot days and nights over most land areas Likelya {10.6} Very likely Very likely Very likely Warm spells/heat waves. Frequency and/or duration increases over most land areas Medium confidence on a global scale Likely in large parts of Europe, Asia and Australia Medium confidence in many (but not all) regions Likely Heavy precipitation events. Increase in the frequency, intensity, and/or amount of heavy precipitation Likely more land areas with increases than decreasesc {2.6} Likely more land areas with increases than decreases Likely over most land areas Increases in intensity and/or duration of drought Low confidencei {10.6} Low confidence on a global scale Likely changes in some regionsd {2.6} 5 Likely k {3.7} Medium confidence in some regions Likely in many regions, since 1970e Increases in intense tropical cyclone activity Low confidence in long term (centennial) changes Virtually certain in North Atlantic since 1970 Low confidence Likely in some regions, since 1970 Increased incidence and/or magnitude of extreme high sea level Likely (since 1970) Likely (late 20th century) Likely Summary for Policymakers * The direct comparison of assessment findings between reports is difficult. For some climate variables, different aspects have been assessed, and the revised guidance note on uncertainties has been used for the SREX and AR5. The availability of new information, improved scientific understanding, continued analyses of data and models, and specific differences in methodologies applied in the assessed studies, all contribute to revised assessment findings. Notes: a Attribution is based on available case studies. It is likely that human influence has more than doubled the probability of occurrence of some observed heat waves in some locations. b Models project near-term increases in the duration, intensity and spatial extent of heat waves and warm spells. c In most continents, confidence in trends is not higher than medium except in North America and Europe where there have been likely increases in either the frequency or intensity of heavy precipitation with some seasonal and/or regional variation. It is very likely that there have been increases in central North America. d The frequency and intensity of drought has likely increased in the Mediterranean and West Africa, and likely decreased in central North America and north-west Australia. e AR4 assessed the area affected by drought. f SREX assessed medium confidence that anthropogenic influence had contributed to some changes in the drought patterns observed in the second half of the 20th century, based on its attributed impact on precipitation and temperature changes. SREX assessed low confidence in the attribution of changes in droughts at the level of single regions. g There is low confidence in projected changes in soil moisture. h Regional to global-scale projected decreases in soil moisture and increased agricultural drought are likely (medium confidence) in presently dry regions by the end of this century under the RCP8.5 scenario. Soil moisture drying in the Mediterranean, Southwest US and southern African regions is consistent with projected changes in Hadley circulation and increased surface temperatures, so there is high confidence in likely surface drying in these regions by the end of this century under the RCP8.5 scenario. i There is medium confidence that a reduction in aerosol forcing over the North Atlantic has contributed at least in part to the observed increase in tropical cyclone activity since the 1970s in this region. j Based on expert judgment and assessment of projections which use an SRES A1B (or similar) scenario. k Attribution is based on the close relationship between observed changes in extreme and mean sea level. l There is high confidence that this increase in extreme high sea level will primarily be the result of an increase in mean sea level. There is low confidence in region-specific projections of storminess and associated storm surges. m SREX assessed it to be very likely that mean sea level rise will contribute to future upward trends in extreme coastal high water levels. SPM 表SPM.1:极端天气和气候事件:近期观测到的变化在全球尺度上的评估、人类因素对这些变化的贡献,以及预估的21世纪初(2016-2035年)和世纪末(2081-2100年)的进一步变化。粗体字表示第五 次评估报告(AR5)(黑色)与《管理极端事件和灾害风险,推进气候变化适应特别报告》(SREX)(蓝色)或第四次评估报告(AR4)(红色)就全球尺度评估所作的修订*。在以前的评估报告中没有提 供对21世纪初的预估。除非另有说明,第五次评估报告中各项预估是相对于1986-2005年的参照期,并使用新的典型浓度路径(RCP)情景(见文框SPM.1)。有关极端天气和气候事件的定义见术语表。

评估人类因素对观测 到的变化的贡献 21世纪初 {10.6} 趋势的现象和方向 21世纪末 {11.3} {2.6} 评估发生的变化(特别是自1950 年以来,除非另有说明) 很可能 ? {12.4} 未来变化的可能性 大部分陆地区域更暖 和/或更少冷昼和冷夜 可能 可能 {2.6} 很可能 几乎确定 几乎确定 {10.6} 可能 几乎确定 {12.4} 很可能 很可能 很可能 {11.3} 大部分陆地区域更暖和/ 或更频繁的热昼和热夜 可能 可能(仅为热夜) 可能a b 很可能 几乎确定 几乎确定 很可能 {11.3} {10.6} 没有正式评估 可能 几乎确定 很可能 很可能 没有正式评估 在全球尺度为中等信度 在欧洲、亚洲和澳大利亚的大部分地区可能 {2.6} {12.4} 暖期/热浪。

大部分陆地区域的频率 和/或持续时间增加 多半可能 中等信度 {2.6} {7.6, 10.6} {11.3} 在许多陆地区域可能 在许多(但并非所有)区域为中等信度 c 可能 很可能 很可能 大多数中纬度陆地地区和潮湿的热带地区很可能 {12.4} 许多地区可能 大部分陆地区域很可能 区域到全球尺度可能(中等信度)h {12.4} 可能增加的陆地区域大于减少的区域 中等信度 多半可能 低信度 {10.6} 强降水事件。

强降水的频率、强 度和/或雨量增加 低信度 g {11.3} 可能增加的陆地区域大于减少 大部分陆地区域可能 5 e 干旱的强度和/或 持续时间增加 中等信度f 多半可能 {2.6} {10.6} 全球尺度为低信度 可能某些区域有变化 d {2.6} 某些区域为中等信度 自1970年以来在许多区域e为可能 可能e 低信度 {11.3} 某些区域为中等信度 强热带气旋活动增加 低信度 多半可能 {3.7} 长期(百年)变化为低信度 北大西洋自1970年以来几乎确定 低信度 i 在西北太平洋和北大西洋地区多半可能 j {14.6} 低信度 可能 {3.7} k 某些流域多半可能 自1970年以来在某些区域可能 可能(自1970年后) 可能 k 多半可能 可能 k 可能 l {13.7} 很可能 l 很可能 可能 m 极端高海平面事件的 频繁和/或程度增加 {13.7} 可能(20世纪末期) 可能 决策者摘要 * 很难将各份报告的评估结果进行直接比较。目前已对某些气候变量的不同方面进行了评估,SREX和AR5已经使用了修订后的不确定性指导说明。新信息的提供、更深入的科学理解、资料和模式的持续分析、评估研究中所用方法的特殊差异,所有这些都有助于改 进评估结果。

注:

a 归因基于已有的案例研究。人类活动可能使一些地点观测到的热浪发生的可能性提高了一倍。

b 各模式预估的热浪和暖期的持续时间、强度和空间范围会出现短期的增加。

c 除北美和欧洲外,大多数大洲的趋势信度不高于中等,而在这两个洲强降水的频率或强度可能出现了上升,但有季节性或区域性变化。北美洲中部很可能出现了上升。

d 在地中海和西非干旱的频率和强度可能已经增加,在北美洲中部和澳大利亚西北部可能已经减小。

e AR4评估了受干旱影响的地区。

f SREX评估认为由于人为影响对降水和温度变化有作用,所以造成了20世纪后半叶观测到的干旱形势发生了一些变化,该结论为中等信度。SREX评估认为一些地区层面的干旱变化的归因为低信度。

g 预估的土壤湿度变化为低信度。

h 在RCP8.5情景下,根据区域到全球尺度的预估,到本世纪末在目前的干燥区域土壤湿度可能会降低,农业干旱可能会增加(中等信度)。在地中海、美国西南部和非洲南部,土壤湿度降低,这与哈得莱环流的预估变化和地表温度增加相一致。因此,具有高信度 的是,在RCP8.5情景下到本世纪末这些区域地表可能变干。

i 具有中等信度的是:北大西洋气溶胶强迫的降低至少对该地区1970年代后观测到的热带气旋活动的增加有部分作用。. j 基于专家判断和使用SRES A1B(或相似情景)的预估评估。

k 归因以观测到的极端海平面变化和平均海平面变化之间的紧密关系为基础。

l 具有高信度的是:极端高海平面的增加主要是由于平均海平面上升造成的。具体区域的风暴程度和相关风暴潮的预估为低信度。

m SREX评估认为平均海平面上升很可能将加剧未来海岸带极端高水位事件呈上升趋势。 SPM Summary for Policymakers Observed change in annual precipitation over land 1901– 2010 1951– 2010 SPM ?100 ?50 ?25 ?10 ?5 ?2.5 0 2.5 5 10 25 50 100 (mm yr-1 per decade) Figure SPM.2 | Maps of observed precipitation change from 1901 to 2010 and from 1951 to 2010 (trends in annual accumulation calculated using the same criteria as in Figure SPM.1) from one data set. For further technical details see the Technical Summary Supplementary Material. {TS TFE.1, Figure 2;

Figure 2.29} B.2 Ocean Ocean warming dominates the increase in energy stored in the climate system, accounting for more than 90% of the energy accumulated between 1971 and 2010 (high confidence). It is virtually certain that the upper ocean (0?700 m) warmed from 1971 to 2010 (see Figure SPM.3), and it likely warmed between the 1870s and 1971. {3.2, Box 3.1} ? On a global scale, the ocean warming is largest near the surface, and the upper 75 m warmed by 0.11 [0.09 to 0.13] °C per decade over the period 1971 to 2010. Since AR4, instrumental biases in upper-ocean temperature records have been identified and reduced, enhancing ? confidence in the assessment of change. {3.2} ? It is likely that the ocean warmed between 700 and 2000 m from 1957 to 2009. Sufficient observations are available for the period 1992 to 2005 for a global assessment of temperature change below 2000 m. There were likely no significant observed temperature trends between 2000 and 3000 m for this period. It is likely that the ocean warmed?from 3000 m to the bottom for this period, with the largest warming observed in the Southern Ocean. {3.2} ? More than 60% of the net energy increase in the climate system is stored in the upper ocean (0–700 m) during the relatively well-sampled 40-year period from 1971 to 2010, and about 30% is stored in the ocean below 700 m. The increase in upper ocean heat content during this time period estimated from a linear trend is likely 17 [15 to 19] × 1022 J 7 (see Figure SPM.3). {3.2, Box 3.1} ? It is about as likely as not that ocean heat content from 0–700 m increased more slowly during 2003 to 2010 than during 1993 to 2002 (see Figure SPM.3). Ocean heat uptake from 700–2000 m, where interannual variability is smaller, likely continued unabated from 1993 to 2009. {3.2, Box 9.2} ? It is very likely that regions of high salinity where evaporation dominates have become more saline, while regions of low salinity where precipitation dominates have become fresher since the 1950s. These regional trends in ocean salinity provide indirect evidence that evaporation and precipitation over the oceans have changed (medium confidence). {2.5, 3.3, 3.5} ? There is no observational evidence of a trend in the Atlantic Meridional Overturning Circulation (AMOC), based on the decade-long record of the complete AMOC and longer records of individual AMOC components. {3.6} 7 A constant supply of heat through the ocean surface at the rate of 1 W m–2 for 1 year would increase the ocean heat content by 1.1 × 1022 J. 6 决策者摘要 ????????????? 1901– 2010 1951– 2010 SPM ?100 ?50 ?25 ?10 ?5 ?2.5 0 2.5 5 10 25 50 100 (mm yr-1 per decade) 图SPM.2: 观测到的1901-2010年和1951-2010年期间的降水变化图,基于一个数据集的计算而得(逐年累积趋势的计算标准同 图SPM.1)。有关技术细节,详见技术摘要的补充材料。{TS TFE.1; 图2;图2.29} B.2 海洋 海洋变暖在气候系统储存能量的增加中占主导地位,1971-2010年间累积能量的90%以上 可由此加以解释(高信度)。几乎确定的是,1971-2010年,海洋上层(0-700米)已经变 暖;19世纪70年代至1971年间,海洋上层可能已变暖。{3.2,文框3.1} ? 全球尺度上,海洋表层温度升幅最大。1971-2010年期间,在海洋上层75米以上深度的海水温度升幅为 每十年0.11 [0.09至0.13]°C。自第四次评估报告以来,已发现并减少了海洋上层温度记录中的仪器测 量偏差,增强了评估变化的信度水平。{3.2} ? 1957-2009年间,海洋在700米和2000米深度之间可能已经变暖。1992-2005年期间,已有充分的观测可 用于评估全球2000米以下海水温度的变化。在此期间,可能的是,2000-3000米之间的海洋没有观测到 显著的温度趋势。在这一时期,从3000米至洋底海洋可能已经变暖,在南大洋观测到的海水温度升幅最 大。{3.2} ? 在观测数据相对充足的1971-2010年这40年间,气候系统增加的净能量中有60%以上储存在海洋上层 (0–700米),另有大约30%储存在700米以下。通过线性趋势估算,在此时期,海洋上层的热含量可能 增加了17 [15 to 19] x 1022焦耳7(图SPM.3)。{3.2, 文框3.1} ? 多半可能 的是,与1993-2002年相比,2003-2010年间海洋上层(0–700米)热含量的增速较为缓慢 (见图SPM.3)。1993-2009年间,在年际变率较小的700-2000米深处,海洋吸收的热量可能 没有减 少。{3.2, 文框9.2} ? 很可能的是,自20世纪50年代以来,以蒸发为主的高盐度海区的海水已变得更咸,而以降水为主的低盐 度海区的海水已变得更淡。这些区域性海洋盐度的变化趋势间接表明,海洋表面的蒸发和降水已发生变 化(中等信度)。{2.5, 3.3, 3.5} ? 根据完整的大西洋经向翻转环流(AMOC)十年期记录和有关AMOC各分量的更长记录,尚无观测证据表明 AMOC出现变化趋势。{3.6} 7 海洋表面平均1Wm-2的加热速率可使海洋热含量每年增加1.1 x1022焦耳。 6 Summary for Policymakers B.3 Cryosphere Over the last two decades, the Greenland and Antarctic ice sheets have been losing mass, glaciers have continued to shrink almost worldwide, and Arctic sea ice and Northern Hemisphere spring snow cover have continued to decrease in extent (high confidence) (see Figure SPM.3). {4.2–4.7} SPM ? The average rate of ice loss8 from glaciers around the world, excluding glaciers on the periphery of the ice sheets9, was very likely 226 [91 to 361] Gt yr?1 over the period 1971 to 2009, and very likely 275 [140 to 410] Gt yr?1 over the period 1993 to 200910. {4.3} ? The average rate of ice loss from the Greenland ice sheet has very likely substantially increased from 34 [–6 to 74] Gt yr–1 over the period 1992 to 2001 to 215 [157 to 274] Gt yr–1 over the period 2002 to 2011. {4.4} ? The average rate of ice loss from the Antarctic ice sheet has likely increased from 30 [–37 to 97] Gt yr–1 over the period 1992–2001 to 147 [72 to 221] Gt yr–1 over the period 2002 to 2011. There is very high confidence that these losses are mainly from the northern Antarctic Peninsula and the Amundsen Sea sector of West Antarctica. {4.4} ? The annual mean Arctic sea ice extent decreased over the period 1979 to 2012 with a rate that was very likely in the range 3.5 to 4.1% per decade (range of 0.45 to 0.51 million km2 per decade), and very likely in the range 9.4 to 13.6% per decade (range of 0.73 to 1.07 million km2 per decade) for the summer sea ice minimum (perennial sea ice). The average decrease in decadal mean extent of Arctic sea ice has been most rapid in summer (high confidence);

the spatial extent has decreased in every season, and in every ? successive decade since 1979 (high confidence) (see Figure SPM.3). There is medium confidence from reconstructions that over the past three decades, Arctic summer sea ice retreat was unprecedented and sea surface temperatures were anomalously high in at least the last 1,450 years. {4.2, 5.5} ? It is very likely that the annual mean Antarctic sea ice extent increased at a rate in the range of 1.2 to 1.8% per decade (range of 0.13 to 0.20 million km2 per decade) between 1979 and 2012. There is high confidence that there are strong regional differences in this annual rate, with extent increasing in some regions and decreasing in others. {4.2} ? There is very high confidence that the extent of Northern Hemisphere snow cover has decreased since the mid-20th century (see Figure SPM.3). Northern Hemisphere snow cover extent decreased 1.6 [0.8 to 2.4] % per decade for March and April, and 11.7 [8.8 to 14.6] % per decade for June, over the 1967 to 2012 period. During this period, snow cover extent in the Northern Hemisphere did not show a statistically significant increase in any month. {4.5} ? There is high confidence that permafrost temperatures have increased in most regions since the early 1980s. Observed warming was up to 3°C in parts of Northern Alaska (early 1980s to mid-2000s) and up to 2°C in parts of the Russian European North (1971 to 2010). In the latter region, a considerable reduction in permafrost thickness and areal extent has been observed over the period 1975 to 2005 (medium confidence). {4.7} ? Multiple lines of evidence support very substantial Arctic warming since the mid-20th century. {Box 5.1, 10.3} 8 9 All references to ‘ice loss’ or ‘mass loss’ refer to net ice loss, i.e., accumulation minus melt and iceberg calving. For methodological reasons, this assessment of ice loss from the Antarctic and Greenland ice sheets includes change in the glaciers on the periphery. These peripheral glaciers are thus excluded from the values given for glaciers. 100 Gt yr?1 of ice loss is equivalent to about 0.28 mm yr?1 of global mean sea level rise. 10 7 决策者摘要 B.3 冰冻圈 过去20年以来,格陵兰冰盖和南极冰盖的冰量一直在损失,全球范围内的冰 川几乎都在继续退缩,北极海冰和北半球春季积雪范围在继续缩小(高信度) (见图SPM.3)。{4.2-4.7} ? 在1971-2009年间,全世界冰川的冰量损失平均速率8(不包括冰盖外围的冰川9)很可能是每年226[91至 361]Gt,在1993-2009年间很可能是每年275[140至410]Gt10。{4.3} ? 格陵兰冰盖的冰量损失平均速率很可能已从1992-2001年间的每年34[-6至74]Gt大幅度增至2002-2011年 间的每年215[157至274]Gt。{4.4} ? 南极冰盖的冰量损失平均速率可能从1992-2001年间的每年30[-37至97]Gt增至2002-2011年间的每年 147[72至221]Gt。具有很高信度的是,这些冰量损失主要发生在南极半岛北部和南极西部的阿蒙森海 区。{4.4} ? 1979-2012年间北极年均海冰范围在缩小,缩小速率 很可能 是在每十年3.5%至4.1%的范围内(每十年 0.45至0.51百万平方公里的范围),夏季最低海冰范围(多年海冰)很可能每十年缩小9.4%-13.6%(每 十年0.73至1.07百万平方公里的范围)。北极海冰每十年平均范围的平均减少速度在夏季最高(高信 度);1979年以来连续的各个十年,每个季节北极海冰的空间范围都在缩小(高信度)(图SPM.3)。

根据资料重建,具有中等信度的是,过去30年间,北极夏季海冰范围退缩史无前例,北极海表温度至少 在过去1450年来异常偏高。{4.2, 5.5} ? 在1979-2012年期间南极年均海冰范围很可能以每十年1.2%至1.8%区间(每十年0.13至0.20百万平方公 里范围)的速度增加。具有高信度的是,这一速率存在很大的区域差异,有些区域在增加,有些区域在 减小。{4.2.} ? 具有很高信度的是,自20世纪中叶以来,北半球积雪范围已缩小(见图SPM.3)。在1967-2012年时期, 北半球三月和四月份平均积雪范围每十年缩小1.6[0.8至2.4]%,六月份每十年缩小11.7[8.8到14.6]%。

在此期间,北半球积雪范围在任何月份都没有显现具有统计意义的显著增加。{4.5} ? 具有高信度的是,自20世纪80年代初以来,大多数地区多年冻土温度已升高。在阿拉斯加北部一些地 区,观测到的升温幅度达到3°C(20世纪80年代早期至21世纪00年代中期),俄罗斯的欧洲北部地区达 到2°C(1971-2010年)。在俄罗斯的欧洲北部地区,1975-2005年期间已观测到多年冻土层厚度和范围 的大幅减少(中等信度)。{4.7} ? 多重证据表明,自二十世纪中叶以来北极出现了大幅度增暖。{文框5.1,10.3} SPM 8 9 所有提到的‘冰量损失’或‘物质损失’均指净冰量损失:累积冰量减去融化冰量和冰山崩塌量。

由于方法原因,对南极冰盖和格陵兰冰盖的冰损失评估包括了冰盖外围的冰川变化。因而从冰川的给定值中剔除了这些外围冰川。

100Gt/年的冰损失大约相当于海平面每年上升0.28毫米。 10 7 Summary for Policymakers (a) 45 Northern Hemisphere spring snow cover SPM (million km2) 40 35 30 1900 1920 1940 1960 1980 2000 Year (b) Arctic summer sea ice extent 14 12 (million km2) 10 8 6 4 1900 1920 1940 1960 1980 2000 Year (c) Change in global average upper ocean heat content 20 10 (1022 J) 0 ?10 ?20 1900 1920 1940 1960 1980 2000 Year (d) Global average sea level change 200 150 (mm) 100 50 0 ?50 1900 1920 1940 1960 1980 2000 Year Figure SPM.3 | Multiple observed indicators of a changing global climate: (a) Extent of Northern Hemisphere March-April (spring) average snow cover;

(b) extent of Arctic July-August-September (summer) average sea ice;

(c) change in global mean upper ocean (0–700 m) heat content aligned to 2006?2010, and relative to the mean of all datasets for 1970;

(d) global mean sea level relative to the 1900–1905 mean of the longest running dataset, and with all datasets aligned to have the same value in 1993, the first year of satellite altimetry data. All time-series (coloured lines indicating different data sets) show annual values, and where assessed, uncertainties are indicated by coloured shading. See Technical Summary Supplementary Material for a listing of the datasets. {Figures 3.2, 3.13, 4.19, and 4.3;

FAQ 2.1, Figure 2;

Figure TS.1} 8 决策者摘要 I  С?????? SPM ??SU    ! ! ! ! !   ? J   С????????? ??SU    ! ! ! ! !   ? (c) ????????????????? 20 10 (1022 J) 0 ?10 ?20 1900 1920 1940 1960 1980 2000 L   ??????????? UU    ? ! ! ! ! !   ? 图SPM.3: 观测到的多项全球气候变化指标:(a) 北半球3-4月(春季)平均积雪范围;(b) 北极7-8-9月(夏季)平均海冰范 围;(c) 调整到2006-2010年时段相对于1970年所有资料集平均值的全球平均海洋上层(0–700m)热含量变化;(d) 相对于19001905年最长的连续资料集平均值的全球平均海平面,所有资料集均调整为1993年(即有卫星高度仪资料的第一年)的相同值。

所有时间序列(不同颜色的曲线表示不同的资料集)给出年度值,经评估后的不确定性用不同颜色的阴影区表示。关于资料集 列表,见技术摘要的补充材料{图3.2,图3.13,图4.19和图4.3;常见问题2.1,图2;图TS.1} 8 Summary for Policymakers B.4 Sea Level The rate of sea level rise since the mid-19th century has been larger than the mean rate during the previous two millennia (high confidence). Over the period 1901 to 2010, global mean sea level rose by 0.19 [0.17 to 0.21] m (see Figure SPM.3). {3.7, 5.6, 13.2} SPM ? Proxy and instrumental sea level data indicate a transition in the late 19th to the early 20th century from relatively low mean rates of rise over the previous two millennia to higher rates of rise (high confidence). It is likely that the rate of global mean sea level rise has continued to increase since the early 20th century. {3.7, 5.6, 13.2} ? It is very likely that the mean rate of global averaged sea level rise was 1.7 [1.5 to 1.9] mm yr–1 between 1901 and 2010, 2.0 [1.7 to 2.3] mm yr–1 between 1971 and 2010, and 3.2 [2.8 to 3.6] mm yr–1 between 1993 and 2010. Tide-gauge and satellite altimeter data are consistent regarding the higher rate of the latter period. It is likely that similarly high rates occurred between 1920 and 1950. {3.7} ? Since the early 1970s, glacier mass loss and ocean thermal expansion from warming together explain about 75% of the observed global mean sea level rise (high confidence). Over the period 1993 to 2010, global mean sea level rise is, with high confidence, consistent with the sum of the observed contributions from ocean thermal expansion due to warming (1.1 [0.8 to 1.4] mm yr–1), from changes in glaciers (0.76 [0.39 to 1.13] mm yr–1), Greenland ice sheet (0.33 [0.25 to 0.41] mm yr–1), Antarctic ice sheet (0.27 [0.16 to 0.38] mm yr–1), and land water storage (0.38 [0.26 to 0.49] mm yr–1). The sum of these contributions is 2.8 [2.3 to 3.4] mm yr–1. {13.3} ? There is very high confidence that maximum global mean sea level during the last interglacial period (129,000 to 116,000 years ago) was, for several thousand years, at least 5 m higher than present, and high confidence that it did not exceed 10 m above present. During the last interglacial period, the Greenland ice sheet very likely contributed between 1.4 and 4.3 m to the higher global mean sea level, implying with medium confidence an additional contribution from the Antarctic ice sheet. This change in sea level occurred in the context of different orbital forcing and with high-latitude surface temperature, averaged over several thousand years, at least 2°C warmer than present (high confidence). {5.3, 5.6} B.5 Carbon and Other Biogeochemical Cycles The atmospheric concentrations of carbon dioxide, methane, and nitrous oxide have increased to levels unprecedented in at least the last 800,000 years. Carbon dioxide concentrations have increased by 40% since pre-industrial times, primarily from fossil fuel emissions and secondarily from net land use change emissions. The ocean has absorbed about 30% of the emitted anthropogenic carbon dioxide, causing ocean acidification (see Figure SPM.4). {2.2, 3.8, 5.2, 6.2, 6.3} ? The atmospheric concentrations of the greenhouse gases carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) have all increased since 1750 due to human activity. In 2011 the concentrations of these greenhouse gases were 391 ppm11, 1803 ppb, and 324 ppb, and exceeded the pre-industrial levels by about 40%, 150%, and 20%, respectively. {2.2, 5.2, 6.1, 6.2} ? Concentrations of CO2, CH4, and N2O now substantially exceed the highest concentrations recorded in ice cores during the past 800,000 years. The mean rates of increase in atmospheric concentrations over the past century are, with very high confidence, unprecedented in the last 22,000 years. {5.2, 6.1, 6.2} 11 ppm (parts per million) or ppb (parts per billion, 1 billion = 1,000 million) is the ratio of the number of gas molecules to the total number of molecules of dry air. For example, 300 ppm means 300 molecules of a gas per million molecules of dry air. 9 决策者摘要 B.4 海平面 19世纪中叶以来的海平面上升速率比过去两千年来的平均速率高( 高信 度)。1901-2010年期间,全球平均海平面上升了0.19[0.17至0.21]米(见图 SPM.3)。{3.7, 5.6, 13.2} ? 海平面的代用数据和器测数据表明,在19世纪末至20世纪初出现了海平面从过去两千年相对较低的平均 上升速率向更高的上升速率的转变(高信度)。可能的是,20世纪初以来,全球平均海平面上升速率不 断加快。{3.7,5.6,13.2} ? 很可能 的是,全球平均海平面上升速率在1901-2010年间的平均值为每年1.7[1.5至1.9]毫米,19712010年间为每年2.0 [1.7至2.3]毫米,1993-2010年间为每年3.2 [2.8至3.6]毫米。对于后一个时期海 平面上升速率较高的问题,验潮仪和卫星高度计的资料是一致的。1920-1950年间可能也出现了类似的 高速率。{3.7} ? 二十世纪七十年代初以来,观测到的全球平均海平面上升的75%可以由冰川冰量损失和因变暖导致的海 洋热膨胀来解释(高信度)。具有高信度的是,1993-2010年间全球平均海平面上升与观测到的海洋热 膨胀(每年1.1 [0.8至1.4] 毫米)、冰川(每年0.76 [0.39至1.13] 毫米])、格陵兰冰盖(每年0.33 [0.25至0.41] 毫米)、南极冰盖(每年0.27 [0.16至0.38] 毫米)以及陆地水储量变化(每年0.38 [0.26至0.49] 毫米)的总贡献一致。这一总贡献为每年2.8[2.3至3.4]毫米。{13.3} ? 具有很高信度的是,末次间冰期(距今约12.9万年至11.6万年间)的几千年中,全球平均海平面的最 大值至少比当前高5米;具有高信度的是,那一时期的海平面没有高于当前的海平面10米。在末次间冰 期,格陵兰冰盖对海平面上升的贡献很可能在1.4到4.3米之间,这意味着南极冰盖也对全球海平面上升 做出了额外贡献(中等信度)。海平面的这种变化是在不同的轨道强迫,以及高纬度几千年平均的地表 温度比目前至少高出2°C的背景下出现的。{5.3, 5.6} SPM B.5 碳和其它生物地球化学循环 二氧化碳、甲烷和氧化亚氮的大气浓度至少已上升到过去80万年以来前所未有 的水平。自工业化以来,二氧化碳浓度已增加了40%,这首先是由于化石燃料 的排放,其次是由于土地利用变化导致的净排放。海洋已经吸收了大约30%的 人为二氧化碳排放,这导致了海洋酸化(见图SPM.4)。{2.2, 3.8, 5.2, 6.2, 6.3} ? 自1750年以来,由于人类活动,大气中二氧化碳(CO2)、甲烷(CH4)和氧化亚氮(N2O)等温室气体的 浓度均已增加。2011年,上述温室气体浓度依次为391ppm11、1803ppb和324ppb,分别约超过工业化前水 平的40%、150%和20%。{2.2, 5.2, 6.1, 6.2} ? 当前CO2、CH4和N2O的浓度大大超过了冰芯记录的过去80万年以来最高浓度。具有很高信度的是,上世纪 CO2、CH4和N2O浓度增加的平均速率是过去2.2万年来前所未有的。{5.2, 6.1, 6.2} 11 ppm(百万分之一)或ppb(十亿分之一,十亿=1000百万)是温室气体分子数与干燥空气的分子总数之比。例如,300ppm是指干燥空气中每百 万个分子中有300个某一温室气体的分子数。 9 Summary for Policymakers ? Annual CO2 emissions from fossil fuel combustion and cement ? production were 8.3 [7.6 to 9.0] GtC12 yr–1 averaged over 2002–2011 (high confidence) and were 9.5 [8.7 to 10.3] GtC yr–1 in 2011, 54% above the 1990 level. Annual net CO2 emissions from ? anthropogenic land use change were 0.9 [0.1 to 1.7] GtC yr–1 on average during 2002 to 2011 (medium confidence). {6.3} SPM ? From 1750 to 2011, CO2 emissions from fossil fuel combustion and cement production have released 375 [345 to 405] GtC to the atmosphere, while deforestation and other land use change are estimated to have released 180 [100 to 260] GtC. This results in cumulative anthropogenic emissions of 555 [470 to 640] GtC. {6.3} ? Of these cumulative anthropogenic CO2 emissions, 240 [230 to 250] GtC have accumulated in the atmosphere, 155 [125 to 185] GtC have been taken up by the ocean and 160 [70 to 250] GtC have accumulated in natural terrestrial ecosystems (i.e., the cumulative residual land sink). {Figure TS.4, 3.8, 6.3} ? Ocean acidification is quantified by decreases in pH13. The pH of ocean surface water has decreased by 0.1 since the beginning of the industrial era (high confidence), corresponding to a 26% increase in hydrogen ion concentration (see Figure SPM.4). {3.8, Box 3.2} (a) CO2 (ppm) Atmospheric CO2 400 380 360 340 320 300 1950 1960 1970 1980 1990 2000 2010 Year (b) pCO2 (μatm) Surface ocean CO2 and pH 400 380 360 340 320 8.09 8.06 1950 1960 1970 1980 1990 2000 2010 Year Figure SPM.4 | Multiple observed indicators of a changing global carbon cycle: (a) atmospheric concentrations of carbon dioxide (CO2) from Mauna Loa (19°32’N, 155°34’W – red) and South Pole (89°59’S, 24°48’W – black) since 1958;

(b) partial pressure of dissolved CO2 at the ocean surface (blue curves) and in situ pH (green curves), a measure of the acidity of ocean water. Measurements are from three stations from the Atlantic (29°10’N, 15°30’W – dark blue/dark green;

31°40’N, 64°10’W – blue/green) and the Pacific Oceans (22°45’N, 158°00’W ? light blue/light green). Full details of the datasets shown here are provided in the underlying report and the Technical Summary Supplementary Material. {Figures 2.1 and 3.18;

Figure TS.5} 12 13 1 Gigatonne of carbon = 1 GtC = 1015 grams of carbon. This corresponds to 3.667 GtCO2. pH is a measure of acidity using a logarithmic scale: a pH decrease of 1 unit corresponds to a 10-fold increase in hydrogen ion concentration, or acidity. 10 in situ pH unit 8.12 决策者摘要 ? 2002-2011年期间,因化石燃料燃烧和水泥生产造成的CO2年平均排放量为每年8.3[7.6至9.0]GtC12(高 信度),2011年是9.5[8.7至10.3] GtC,比1990年水平高出54%。在2002-2011年期间,因人为土地利用 变化产生的CO2年净排放量平均为每年0.9[0.1至0.7]GtC(中等信度)。{6.3} ? 从1750年至2011年,因化石燃料燃烧和水泥生产释放到大气中的CO2排放量为375 [345至405] GtC,因毁 林和其它土地利用变化估计已释放了180 [100至260] GtC。这使得人为CO2排放累积量为555 [470至640] GtC。{6.3} ? 在这些人为CO2排放累积量中,已有240[230至250] GtC累积在大气中,有155 [125至185] GtC被海洋吸 收,而自然陆地生态系统累积了160[70至250] GtC(参见累积残留土地汇)。{图TS.4,3.8, 6.3} ? 海洋酸化可用pH值13的下降来度量。自工业化时代初期以来,海表水的pH值已经下降了0.1(高信度), 相当于氢离子浓度增加了26%(见图SPM.4)。{3.8, 文框3.2}。 SPM (a) +7XXU ??+7        ! ! ! !  !!    ? X+7?I\U (b)       ??????+7???X0  !  ! ! ! !  !!   ? 图SPM.4:观测到的多项全球碳循环的变化指标:(a)从1958年起在莫纳罗亚(19 °32′N,155 °34′W–红色曲线)和南极 (89°59′S,24°48′W–黑色曲线)观测到的大气二氧化碳(CO2)浓度;(b)海洋表面溶解的CO2分压(蓝色曲线)和实地pH测 量值(绿色曲线,测量海水酸度)。观测值来自位于大西洋(29°10′N,15°30′W–深蓝/深绿;31°40′N,64°10′W–蓝/绿) 和太平洋(22°45′N,158°00′W–淡蓝/淡绿)的三个观测站。关于此处展示的数据集,详见基础报告和技术摘要补充材料。

{图2.1和图3.18;图TS.5} 12 13 10亿吨碳 = 1 GtC =1015克碳=1拍克碳=1 PgC。这相当于3.67GtCO2. pH值是使用对数标度来衡量酸度的指标,pH值下降1个单位对应氢离子浓度或酸度增加10倍。 10 QV[Q\]X0]VQ Summary for Policymakers C. Drivers of Climate Change Natural and anthropogenic substances and processes that alter the Earth’s energy budget are drivers of climate change. Radiative forcing14 (RF) quantifies the change in energy fluxes caused by changes in these drivers for 2011 relative to 1750, unless otherwise indicated. Positive RF leads to surface warming, negative RF leads to surface cooling. RF is estimated based on in-situ and remote observations, properties of greenhouse gases and aerosols, and calculations using numerical models representing observed processes. Some emitted compounds affect the atmospheric concentration of other substances. The RF can be reported based on the concentration changes of each substance15. Alternatively, the emission-based RF of a compound can be reported, which provides a more direct link to human activities. It includes contributions from all substances affected by that emission. The total anthropogenic RF of the two approaches are identical when considering all drivers. Though both approaches are used in this Summary for Policymakers, emission-based RFs are emphasized. SPM Total radiative forcing is positive, and has led to an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of CO2 since 1750 (see Figure SPM.5). {3.2, Box 3.1, 8.3, 8.5} ? The total anthropogenic RF for 2011 relative to 1750 is 2.29 [1.13 to 3.33] W m?2 (see Figure SPM.5), and it has increased more rapidly since 1970 than during prior decades. The total anthropogenic RF best estimate for 2011 is 43% higher than that reported in AR4 for the year 2005. This is caused by a combination of continued growth in most greenhouse gas concentrations and improved estimates of RF by aerosols indicating a weaker net cooling effect (negative RF). {8.5} ? The RF from emissions of well-mixed greenhouse gases (CO2, CH4, N2O, and Halocarbons) for 2011 relative to 1750 is 3.00 [2.22 to 3.78] W m–2 (see Figure SPM.5). The RF from changes in concentrations in these gases is 2.83 [2.26 to 3.40] W m–2. {8.5} ? Emissions of CO2 alone have caused an RF of 1.68 [1.33 to 2.03] W m–2 (see Figure SPM.5). Including emissions of other carbon-containing gases, which also contributed to the increase in CO2 concentrations, the RF of CO2 is 1.82 [1.46 to 2.18] W m–2. {8.3, 8.5} ? Emissions of CH4 alone have caused an RF of 0.97 [0.74 to 1.20] W m?2 (see Figure SPM.5). This is much larger than the concentration-based estimate of 0.48 [0.38 to 0.58] W m?2 (unchanged from AR4). This difference in estimates is caused by concentration changes in ozone and stratospheric water vapour due to CH4 emissions and other emissions indirectly affecting CH4. {8.3, 8.5} ? Emissions of stratospheric ozone-depleting halocarbons have caused a net positive RF of 0.18 [0.01 to 0.35] W m?2 (see Figure SPM.5). Their own positive RF has outweighed the negative RF from the ozone depletion that they have induced. The positive RF from all halocarbons is similar to the value in AR4, with a reduced RF from CFCs but increases from many of their substitutes. {8.3, 8.5} ? Emissions of short-lived gases contribute to the total anthropogenic RF. Emissions of carbon monoxide (CO) are virtually certain to have induced a positive RF, while emissions of nitrogen oxides (NOx) are likely to have induced a net negative RF (see Figure SPM.5). {8.3, 8.5} ? The RF of the total aerosol effect in the atmosphere, which includes cloud adjustments due to aerosols, is –0.9 [–1.9 to ?0.1] W m?2 (medium confidence), and results from a negative forcing from most aerosols and a positive contribution 14 The strength of drivers is quantified as Radiative Forcing (RF) in units watts per square metre (W m–2) as in previous IPCC assessments. RF is the change in energy flux caused by a driver, and is calculated at the tropopause or at the top of the atmosphere. In the traditional RF concept employed in previous IPCC reports all surface and tropospheric conditions are kept fixed. In calculations of RF for well-mixed greenhouse gases and aerosols in this report, physical variables, except for the ocean and sea ice, are allowed to respond to perturbations with rapid adjustments. The resulting forcing is called Effective Radiative Forcing (ERF) in the underlying report. This change reflects the scientific progress from previous assessments and results in a better indication of the eventual temperature response for these drivers. For all drivers other than well-mixed greenhouse gases and aerosols, rapid adjustments are less well characterized and assumed to be small, and thus the traditional RF is used. {8.1} This approach was used to report RF in the AR4 Summary for Policymakers. 15 11 决策者摘要 C. 气候变化的驱动因子 改变地球能量收支的自然和人为物质与过程是气候变化的驱动因子。辐射强迫14(RF)量化了与1750相比在 2011年由这些驱动因子引起的能量通量变化,除非另有说明。正辐射强迫值导致地表变暖,而负辐射强迫值 导致地表变冷。辐射强迫的估算是基于实地观测和遥感观测、温室气体和气溶胶的特性以及基于利用可代表 已观测到的各种过程的数值模式的计算结果。某些排放的化合物会影响其它物质的大气浓度。辐射强迫量可 根据每一种物质的浓度变化进行计算15。亦可以根据排放计算某一化合物的辐射强迫,这与人类活动有着更 直接的联系。它包含了受排放影响的所有物质的贡献。在考虑所有驱动因子的情况时,两种方法的人为辐射 强迫总估计值是一致的。虽然在本摘要中两种方法均有使用,但是更侧重于基于排放的辐射强迫。 SPM 总辐射强迫是正值,并导致了气候系统的能量吸收。对总辐射强迫的最大贡献来 自于1750年以来的大气CO2浓度的增加(见图SPM.5)。{3.2, 文框3.1, 8.3, 8.5} ? 相对于1750年,2011年总人为辐射强迫值为2.29[1.13至3.33]Wm-2(见图SPM.5),自1970年以来其增加 速率比之前的各个年代更快。2011年的总人为辐射强迫的最佳估计值比《IPCC第四次评估报告》给出的 2005年值高43%。这是由大多数温室气体浓度的继续增加和气溶胶强迫作用的估算值得到改善(气溶胶 强迫产生的净冷却效应(负辐射强迫)比之前的评估偏弱)共同造成的。{8.5} ? 相对于1750年,2011年由混合充分的温室气体(CO 2 、CH 4 、N 2 O和卤代烃)排放产生的辐射强迫为 3.00[2.22至3.78]Wm -2 (见图SPM.5)。由这些气体浓度变化造成的辐射强迫为2.83[2.26至3.40] Wm-2。{8.5} ? 仅CO2排放产生了1.68[1.33至2.03]Wm–2的辐射强迫(见图SPM.5)。将造成CO2浓度增加的其它含碳气体 的排放包括在内,CO2的辐射强迫值为1.82[1.46至2.18]Wm–2。{8.3, 8.5} ? 仅CH 4排放产生了0.97[0.74至1.20]Wm-2的辐射强迫(见图SPM.5)。这远大于基于浓度的估算值0.48 [0.38至0.58]Wm-2(自《IPCC第四次评估报告》以来无变化)。估算值中的差异是由于CH4排放导致的臭 氧浓度的变化和平流层水汽含量的变化以及其它间接影响CH4的排放所造成的。{8.3, 8.5} ? 平流层中耗损臭氧的卤代烃排放引起0.18[0.01至0.35]Wm-2的净正辐射强迫(见图SPM.5)。卤代烃本身 的正辐射强迫已超过了它导致的臭氧损耗所产生的负辐射强迫。所有卤代烃的正辐射强迫与第四次评估 报告的值相似,其中CFCs造成的辐射强迫降低,但其很多替代物造成的辐射强迫增加了。{8.3, 8.5} ? 短寿命周期气体的排放对总人为辐射强迫值有贡献。一氧化碳(CO)排放几乎确定已引起正辐射强迫, 氮氧化物(NOx)可能已引起净负辐射强迫(见图SPM.5)。{8.3, 8.5} ? 大气中气溶胶总效应(包括气溶胶造成的云调节)的辐射强迫为–0.9[–1.9至-0.1]Wm -2 ( 中等信 度),这是将大多数气溶胶产生的负强迫作用和黑碳吸收太阳辐射产生的正贡献合计得到。具有高信度 的是,气溶胶及其与云的相互作用已抵消了源于充分混合的温室气体引起的全球平均强迫的很大一部 分。它们仍然是总辐射强迫估算中的最大不确定性来源。{ 7.5,8.3,8.5} 14 辐射强迫(RF)用于量化驱动因子的强度,如同之前的IPCC评估报告,均以瓦/平方米(Wm-2)为单位表示。RF是由某一驱动因子造成的能量 通量变化,在对流层顶或大气层顶计算。在之前的IPCC报告采用的RF传统概念中,所有地表和对流层状况均保持不变。在本报告中,在计算 充分混合的温室气体和气溶胶的RF过程中,除海洋和海冰外,允许物理变量利用快速调节的方式响应各种扰动。这种产生的强迫在报告全文 中被称为有效辐射强迫(ERF)。这一变化体现了自之前评估报告发表以来所取得的科学进展,并更好地表示温度对这些驱动因子的最终响 应。对于除充分混合的温室气体和气溶胶外的所有其它驱动因子,描述它们快速调节的效果要差一些,而且假定这些调节作用不大,因此用 传统的RF作为强迫作用的最佳估计值。{8.1} AR4 SPM中使用此方法计算RF。 15 11 Summary for Policymakers from black carbon absorption of solar radiation. There is high confidence that ? aerosols and their interactions with clouds have offset a substantial portion of global mean forcing from well-mixed greenhouse gases. They continue to contribute the largest uncertainty to the total RF estimate. {7.5, 8.3, 8.5} ? The forcing from stratospheric volcanic aerosols can have a large impact on the climate for some years after volcanic eruptions. Several small eruptions have caused an RF of –0.11 [–0.15 to –0.08] W m–2 for the years 2008 to 2011, which is approximately twice as strong as during the years 1999 to 2002. {8.4} ? The RF due to changes in solar irradiance is estimated as 0.05 [0.00 to 0.10] W m?2 (see Figure SPM.5). Satellite observations of total solar irradiance changes from 1978 to 2011 indicate that the last solar minimum was lower than the previous two. This results in an RF of –0.04 [–0.08 to 0.00] W m–2 between the most recent minimum in 2008 and the 1986 minimum. {8.4} ? The total natural RF from solar irradiance changes and stratospheric volcanic aerosols made only a small contribution to the net radiative forcing throughout the last century, except for brief periods after large volcanic eruptions. {8.5} SPM Emitted compound Well-mixed greenhouse gases Resulting atmospheric drivers Radiative forcing by emissions and drivers Level of confidence VH H H VH M M M H L M M H H M CO2 CH4 Halocarbons N 2O CO CO2 CO2 H2Ostr O3 CH4 O3 CFCs HCFCs N 2O CO2 CO2 CH4 O3 CH4 O3 1.68 [1.33 to 2.03] 0.97 [0.74 to 1.20] 0.18 [0.01 to 0.35] 0.17 [0.13 to 0.21] 0.23 [0.16 to 0.30] 0.10 [0.05 to 0.15] -0.15 [-0.34 to 0.03] Anthropogenic Short lived gases and aerosols NMVOC NOx Aerosols and precursors Nitrate CH4 O3 Mineral dust Sulphate Nitrate Organic carbon Black carbon -0.27 [-0.77 to 0.23] (Mineral dust, SO2, NH3, Organic carbon and Black carbon) Cloud adjustments due to aerosols Albedo change due to land use Changes in solar irradiance -0.55 [-1.33 to -0.06] -0.15 [-0.25 to -0.05] 0.05 [0.00 to 0.10] 2.29 [1.13 to 3.33] Natural Total anthropogenic RF relative to 1750 ?1 2011 1980 1950 1.25 [0.64 to 1.86] 0.57 [0.29 to 0.85] 0 1 2 3 Radiative forcing relative to 1750 (W m?2) Figure SPM.5 | Radiative forcing estimates in 2011 relative to 1750 and aggregated uncertainties for the main drivers of climate change. Values are global average radiative forcing (RF14), partitioned according to the emitted compounds or processes that result in a combination of drivers. The best estimates of the net radiative forcing are shown as black diamonds with corresponding uncertainty intervals;

the numerical values are provided on the right of the figure, together with the confidence level in the net forcing (VH – very high, H – high, M – medium, L – low, VL – very low). Albedo forcing due to black carbon on snow and ice is included in the black carbon aerosol bar. Small forcings due to contrails (0.05 W m–2, including contrail induced cirrus), and HFCs, PFCs and SF6 (total 0.03 W m–2) are not shown. Concentration-based RFs for gases can be obtained by summing the like-coloured bars. Volcanic forcing is not included as its episodic nature makes is difficult to compare to other forcing mechanisms. Total anthropogenic radiative forcing is provided for three different years relative to 1750. For further technical details, including uncertainty ranges associated with individual components and processes, see the Technical Summary Supplementary Material. {8.5;

Figures 8.14–8.18;

Figures TS.6 and TS.7} 12 决策者摘要 ? 在火山爆发后的若干年内,平流层火山气溶胶的强迫作用对气候有很大影响。2008-2011年间几座小火 山的喷发已产生了–0.11[–0.15至–0.08]Wm–2的辐射强迫,其强度大约是1999-2002年火山气溶胶辐 射强迫的两倍。{8.4} ? 由于太阳辐照度变化产生的辐射强迫估计为0.05[0.00至0.10]Wm-2(见图SPM.5)。1978至2011年期间 对太阳总辐照度变化的卫星观测表明,最后一个太阳极小值低于前两个极小值。这导致最近一次极小值 (2008年)与1986年极小值之间产生了–0.04[–0.08至0.00]Wm-2的辐射强迫差值。{8.4} ? 除了几次大规模火山爆发以后的短暂时期以外,太阳辐照度和平流层火山气溶胶产生的总自然辐射强迫 在整个过去一个世纪对净辐射强迫的贡献很小。{8.5} SPM ??????? ??????????? φ????????????????????  C\WE ???? >0 0 0 >0 5 5 5 +7 ??????????? +7 +7 07[\Z 7 +0 7 +.+[ 0+.+[ 67 +7 +0 7 +7 σ? ?????? ???????? +0 0ITW KIZJWV[ 67 +7 !C\WE  C\WE C\WE C\WE ?? ????????????? 65>7+ 67` ????? ??? +0 7 +0 7 ?????? σ? C\WE C\WE C\WE 0 4 5 5 ?????? ??????σ? ???????? ??????????? C\WE ?????????????? ?? C\WE ????????? C\WE !C\WE   C\W E  C!\W E  0 0 5 ???????????????? !  !     ???????????????U??  图SPM.5: 相对于1750年,2011年的气候变化主要驱动因子的辐射强迫估计值和总的不确定性。图中给出的估计值是全球平均 辐射强迫值(RF15),这些估计值的划分是根据使驱动因子复合的排放混合物或排放过程。净辐射强迫的最佳估计值用黑色菱 形表示,并给出了相应的不确定性区间;在本图的右侧给出了各数值,包括净辐射强迫的信度水平(VH–很高,H–高,M–中 等,L–低,VL–很低)。黑碳气溶胶柱状图中包括积雪和冰上的黑碳产生的反照率强迫。图中没有给出凝结尾迹(0.05Wm-2, 其中包括凝结尾迹产生的卷云)和氢氟碳化物(HFCs)、全氟化碳(PFCs)和六氟化硫(SF6)(共计0.03Wm-2)产生的小的强 迫作用。可以通过合计同色柱状图的数值获得各种气体基于浓度的辐射强迫。图中没有包括火山强迫,因为该强迫时断时续的 特点使其很难与其它强迫机制进行比较。本图给出了相对于1750年的三个不同年份的人为辐射强迫总值。进一步的技术细节, 包括与各种成分和过程相关的不确定性范围,参见技术摘要补充材料。{8.5;图8.14-8.18;图TS.6和图TS.7} 12 Summary for Policymakers D. Understanding the Climate System and its Recent Changes Understanding recent changes in the climate system results from combining observations, studies of feedback processes, and model simulations. Evaluation of the ability of climate models to simulate recent changes requires consideration of the state of all modelled climate system components at the start of the simulation and the natural and anthropogenic forcing used to drive the models. Compared to AR4, more detailed and longer observations and improved climate models now enable the attribution of a human contribution to detected changes in more climate system components. Human influence on the climate system is clear. This is evident from the increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and understanding of the climate system. {2–14} SPM D.1 Evaluation of Climate Models Climate models have improved since the AR4. Models reproduce observed continentalscale surface temperature patterns and trends over many decades, including the more rapid warming since the mid-20th century and the cooling immediately following large volcanic eruptions (very high confidence). {9.4, 9.6, 9.8} ? The long-term climate model simulations show a trend in global-mean surface temperature from 1951 to 2012 that agrees with the observed trend (very high confidence). There are, however, differences between simulated and observed trends over periods as short as 10 to 15 years (e.g., 1998 to 2012). {9.4, Box 9.2} ? The observed reduction in surface warming trend over the period 1998 to 2012 as compared to the period 1951 to 2012, is due in roughly equal measure to a reduced trend in radiative forcing and a cooling contribution from natural internal variability, which includes a possible redistribution of heat within the ocean (medium confidence). The reduced trend in radiative forcing is primarily due to volcanic eruptions and the timing of the downward phase of the 11-year solar cycle. However, there is low confidence in quantifying the role of changes in radiative forcing in causing the reduced warming trend. There is medium confidence that natural internal decadal variability causes to a substantial degree the difference between observations and the simulations;

the latter are not expected to reproduce the timing of natural internal variability. There may also be a contribution from forcing inadequacies and, in some models, an overestimate of the response to increasing greenhouse gas and other anthropogenic forcing (dominated by the effects of aerosols). {9.4, Box 9.2, 10.3, Box 10.2, 11.3} ? On regional scales, the confidence in model capability to simulate surface temperature is less than for the larger scales. However, there is high confidence that regional-scale surface temperature is better simulated than at the time of the AR4. {9.4, 9.6} ? There has been substantial progress in the assessment of extreme weather and climate events since AR4. Simulated global-mean trends in the frequency of extreme warm and cold days and nights over the second half of the 20th century are generally consistent with observations. {9.5} ? There has been some improvement in the simulation of continental-? scale patterns of precipitation since the AR4. At regional scales, precipitation is not simulated as well, and the assessment is hampered by observational uncertainties. {9.4, 9.6} ? Some important climate phenomena are now better reproduced by models. There is high confidence that the statistics of monsoon and El Ni?o-Southern Oscillation (ENSO) based on multi-model simulations have improved since AR4. {9.5} 13 决策者摘要 D. 认识气候系统及其最近的变化 认识气候系统最近的变化是基于对观测、反馈过程的研究和模式模拟的综合。评估气候模式模拟最近变化 的能力时需考虑所有被模拟的气候系统分量的初始状态,以及用于驱动各模式的自然和人为强迫。与第四 次评估报告相比,目前的观测资料更加详尽、时间序列更长,气候模式得到进一步改进,它们能够在更多 的气候系统分量中把已检测到的变化归因于人为影响。 SPM 人类对气候系统的影响是明确的。从大气中温室气体浓度增加、正辐射强迫、 观测到的变暖以及对当前气候系统的科学认识均清楚地表明这一点。{2-14} D.1 对气候模式的评估 自《第四次评估报告》以来,气候模式已得到改进。模式能够再现观测到的 大陆尺度地表温度分布和多年代际趋势,包括自20世纪中叶以来的快速增温 和大规模火山爆发后立即出现的降温(很高信度)。{ 9.4, 9.6, 9.8} ? 长期气候模式模拟结果显示的1951-2012年的全球平均地表温度趋势与观测到的趋势相一致( 很高信 度)。然而,模拟与观测的10–15年(例如1998到2012年)的短期趋势之间存在差异。{9.4, 文框9.2} ? 与1951-2012年相比,1998-2012年间观测到的地表增温趋势减少是因为辐射强迫趋势减弱以及内部变率 (包括海洋内部可能的热量再分配)致冷效应,二者的贡献不相上下(中等信度)。辐射强迫趋势减弱 主要是因为火山爆发和为期11年的太阳周期处于下行阶段。但是,对造成变暖趋势减少的辐射强迫变化 的作用进行量化仅有低信度。具有中等信度的是,自然内部年代际变率在很大程度导致了观测和模拟之 间的差异;模式模拟不能重现内部变率的时间。还有可能是由于不足的强迫,以及某些模式高估了对增 加的温室气体和其它人为强迫(主要是气溶胶效应)的响应。{9.4, 文框9.2, 10.3, 文框10.2, 11.3} ? 模式模拟地表温度的能力在区域尺度上比更大尺度上的可信度要低。然而,具有高信度的是,对区域尺 度地表温度的模拟能力好于第四次评估报告时期。{9.4, 9.6} ? 自第四次评估报告以来,对极端天气气候事件的评估取得了重要进展。模拟的20世纪后50年极暖和极冷 昼夜频次的全球平均趋势与观测基本一致。{9.5} ? 自第四次评估报告以来,对大陆尺度降水分布的模拟得到一些改进。在区域尺度仍然不能很好地模拟降 水,而且由于观测的不确定性使得评估工作仍然很难开展。{9.4, 9.6} ? 现在模式能够更好地再现一些重要的气候现象。具有高信度的是,自第四次评估报告以来,基于多模式 模拟的季风和厄尔尼诺-南方涛动(ENSO)的结果有所改进。{9.5} ? 与第四次评估报告相比,气候模式目前包括更多的云和气溶胶过程以及它们的相互作用,但是模式中这 些过程的表征和量化仍然是低信度。{7.3, 7.6, 9.4, 9.7} ? 具有确凿证据的是,与第四次评估报告相比,更多的模式能够再现1979年以来夏季北极海冰范围的下降 趋势,大约四分之一的模式模拟的趋势与观测的趋势一样大或更大。尽管模式间结果的离散度很大,大 多数模式模拟的南极海冰范围呈小幅下降的趋势,这与观测到的小幅增加的趋势相反。{9.4} 13 Summary for Policymakers ? Climate models now include more cloud and aerosol processes, and their interactions, than at the time of the AR4, but there remains low confidence in the representation and quantification of these processes in models. {7.3, 7.6, 9.4, 9.7} ? There is robust evidence that the downward trend in Arctic summer sea ice extent since 1979 is now reproduced by more models than at the time of the AR4, with about one-quarter of the models showing a trend as large as, or larger than, the trend in the observations. Most models simulate a small downward trend in Antarctic sea ice extent, albeit with large inter-model spread, in contrast to the small upward trend in observations. {9.4} ? Many models reproduce the observed changes in upper-ocean heat content (0–700 m) from 1961 to 2005 (high confidence), with the multi-model mean time series falling within the range of the available observational estimates for most of the period. {9.4} ? Climate models that include the carbon cycle (Earth System Models) simulate the global pattern of ocean-atmosphere CO2 fluxes, with outgassing in the tropics and uptake in the mid and high latitudes. In the majority of these models the sizes of the simulated global land and ocean carbon sinks over the latter part of the 20th century are within the range of observational estimates. {9.4} SPM D.2 Quantification of Climate System Responses Observational and model studies of temperature change, climate feedbacks and changes in the Earth’s energy budget together provide confidence in the magnitude of global warming in response to past and future forcing. {Box 12.2, Box 13.1} ? The net feedback from the combined effect of changes in water vapour, and differences between atmospheric and surface warming is extremely likely positive and therefore amplifies changes in climate. The net radiative feedback due to all cloud types combined is likely positive. Uncertainty in the sign and magnitude of the cloud feedback is due primarily to continuing uncertainty in the impact of warming on low clouds. {7.2} ? The equilibrium climate sensitivity quantifies the response of the climate system to constant radiative forcing on multicentury time scales. It is defined as the change in global mean surface temperature at equilibrium that is caused by a doubling of the atmospheric CO2 concentration. Equilibrium climate sensitivity is likely in the range 1.5°C to 4.5°C (high confidence), extremely unlikely less than 1°C (high confidence), and very unlikely greater than 6°C (medium confidence)16. The lower temperature limit of the assessed likely range is thus less than the 2°C in the AR4, but the upper limit is the same. This assessment reflects improved understanding, the extended temperature record in the atmosphere and ocean, and new estimates of radiative forcing. {TS TFE.6, Figure 1;

Box 12.2} ? The rate and magnitude of global climate change is determined by radiative forcing, climate feedbacks and the storage of energy by the climate system. Estimates of these quantities for recent decades are consistent with the assessed likely range of the equilibrium climate sensitivity to within assessed uncertainties, providing strong evidence for our understanding of anthropogenic climate change. {Box 12.2, Box 13.1} ? The transient climate response quantifies the response of the climate system to an increasing radiative forcing on a decadal to century timescale. It is defined as the change in global mean surface temperature at the time when the atmospheric CO2 concentration has doubled in a scenario of concentration increasing at 1% per year. The transient climate response is likely in the range of 1.0°C to 2.5°C (high confidence) and extremely unlikely greater than 3°C. {Box 12.2} ? A related quantity is the transient climate response to cumulative carbon emissions (TCRE). It quantifies the transient response of the climate system to cumulative carbon emissions (see S ? ection E.8). TCRE is defined as the global mean 16 No best estimate for equilibrium climate sensitivity can now be given because of a lack of agreement on values across assessed lines of evidence and studies. 14 决策者摘要 ? 许多模式再现了1961年至2005年间观测到的海洋上层(0-700米)热含量的变化(高信度),在大部分 时期中,多模式平均的时间序列都在现有观测的估计值范围内。{9.4} ? 包括碳循环的气候模式(地球系统模式)能够模拟出全球海洋-大气二氧化碳通量分布,包括热带地区的 排放和中、高纬度地区的吸收。其中的大多数模式模拟的20世纪后半期的全球陆地和海洋碳汇都在观测 的估计值范围内。{9.4} SPM D.2 气候系统响应的量化 温度变化的观测和模式研究,气候反馈和地球能量收支的变化一起,为全球 变暖对过去和未来强迫的响应幅度提供了信度。{文框12.2, 文框13.1} ? 水汽变化以及大气和地表增暖之间差异的共同影响所造成的净反馈极有可能为正,因此会放大气候的变 化。包括所有云型产生的净辐射反馈可能为正。造成云反馈正负符号和大小不确定性的主要原因是变暖 对低云影响的持续不确定性。{7.2} ? 平衡气候敏感度量化了气候系统对多世纪时间尺度上恒定辐射强迫的响应。它是指大气CO2浓度加倍后 达到平衡时的全球平均地表温度的变化。平衡气候敏感度的范围可能是1.5°C至4.5°C(高信度),极不 可能低于1°C(高信度),很不可能大于6°C(中等信度)16。因此评估的平衡气候敏感度可能范围的温 度下限小于第四次评估报告中的2°C,但是上限是相同的。这一评估反映了更好的科学认识,增加的大 气和海洋资料记录,以及对辐射强迫的最新估计。{TS TFE.6, 图1;文框12.2} ? 全球气候变化的速率和幅度决定于辐射强迫,气候反馈和气候系统储存的能量。对这些量近几十年的估 计值与评估的平衡气候敏感度的可能范围相一致,为认识人为气候变化提供了有力证据。{文框12.2, 文框13.1} ? 瞬时气候响应量化了年代际到百年时间尺度上气候系统对增加的辐射强迫的响应。它是指大气CO2浓度 每年增加1%直至加倍时的全球平均地表温度的变化。瞬时气候响应的范围 可能 为1.0°C至2.5°C(高信 度),极不可能大于3°C。{文框12.2} ? 一个相关的变量是累积碳排放的瞬时气候响应(TCRE)。它量化了气候系统对累积碳排放的瞬时响应 (见E.8)。TCRE定义为向大气中每排放1000GtC时的全球平均地表温度变化。TCRE的范围可能是每1000 PgC引起0.8°C至2.5°C的温度变化,这适用在达到温度峰值之前,累积排放不超过2000GtC的情况下(见 图SPM.10)。{12.5;文框12.2} 16 现在不能给出平衡气候敏感度的最佳估算,因为在已评估的多项证据和研究中缺乏评估值的一致性。 14 Summary for Policymakers ? urface temperature change per 1000 GtC emitted to the atmosphere. TCRE is likely in the range of 0.8°C to 2.5°C per s 1000 GtC and applies for cumulative emissions up to about 2000 GtC until the time temperatures peak (see Figure SPM.10). {12.5, Box 12.2} ? Various metrics can be used to compare the contributions to climate change of emissions of different substances. The most appropriate metric and time horizon will depend on which aspects of climate change are considered most important to a particular application. No single metric can accurately compare all consequences of different emissions, and all have limitations and uncertainties. The Global Warming Potential is based on the cumulative radiative forcing over a particular time horizon, and the Global Temperature Change Potential is based on the change in global mean surface temperature at a chosen point in time. Updated values are provided in the underlying Report. {8.7} SPM D.3 Detection and Attribution of Climate Change Human influence has been detected in warming of the atmosphere and the ocean, in changes in the global water cycle, in reductions in snow and ice, in global mean sea level rise, and in changes in some climate extremes (see Figure SPM.6 and Table SPM.1). This evidence for human influence has grown since AR4. It is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century. {10.3–10.6, 10.9} ? It is extremely likely that more than half of the observed increase in global average surface temperature from 1951 to 2010 was caused by the anthropogenic increase in greenhouse gas concentrations and other anthropogenic forcings together. The best estimate of the human-induced contribution to warming is similar to the observed warming over this period. {10.3} ? Greenhouse gases contributed a global mean surface warming likely to be in the range of 0.5°C to 1.3°C over the period 1951 to 2010, with the contributions from other anthropogenic forcings, including the cooling effect of aerosols, likely to be in the range of ?0.6°C to 0.1°C. The contribution from natural forcings is likely to be in the range of ?0.1°C to 0.1°C, and from natural internal variability is likely to be in the range of ?0.1°C to 0.1°C. Together these assessed contributions are consistent with the observed warming of approximately 0.6°C to 0.7°C over this period. {10.3} ? Over every continental region except Antarctica, anthropogenic forcings have likely made a substantial contribution to surface temperature increases since the mid-20th century (see Figure SPM.6). For Antarctica, large observational uncertainties result in low confidence that anthropogenic forcings have contributed to the observed warming averaged over available stations. It is likely that there has been an anthropogenic contribution to the very substantial Arctic warming since the mid-20th century. {2.4, 10.3} ? It is very likely that anthropogenic influence, particularly greenhouse gases and stratospheric ozone depletion, has led to a detectable observed pattern of tropospheric warming and a corresponding cooling in the lower stratosphere since 1961. {2.4, 9.4, 10.3} ? It is very likely that anthropogenic forcings have made a substantial contribution to increases in global upper ocean heat content (0–700 m) observed since the 1970s (see Figure SPM.6). There is evidence for human influence in some individual ocean basins. {3.2, 10.4} ? It is likely that anthropogenic influences have affected the global water cycle since 1960. Anthropogenic influences have contributed to observed increases in atmospheric moisture content in the atmosphere (medium confidence), to globalscale changes in precipitation patterns over land (medium confidence), to intensification of heavy precipitation over land regions where data are sufficient (medium confidence), and to changes in surface and sub-surface ocean salinity (very likely). {2.5, 2.6, 3.3, 7.6, 10.3, 10.4} 15 决策者摘要 ? 许多指标可用于比较不同物质的排放对气候变化的贡献。最合适的指标和时间尺度取决于在特定的应用 中气候变化哪方面最重要。没有一种指标能精确比较不同排放的所有后果,每个都具有局限性和不确定 性。全球增温潜势是基于特定时间尺度上的累积辐射强迫,全球温度变化潜势是基于选定时间点上的全 球平均地表温度的变化。在报告全文中提供了更新后的数值。{8.7} SPM D.3 气候变化的检测与归因 已经在大气和海洋的变暖、全球水循环的变化、积雪和冰的减少、全球平均海 平面的上升以及一些极端气候事件的变化中检测到人为影响。自《第四次评估 报告》以来,有关人为影响的证据有所增加。极有可能的是,人为影响是造成 观测到的20世纪中叶以来变暖的主要原因。{10.3-10.6, 10.9} ? 极有可能的是,观测到的1951-2010年全球平均地表温度升高的一半以上是由温室气体浓度的人为增加 和其他人为强迫共同导致的。人类活动引起的变暖最佳估计值与这个时期观测到的变暖相似。{10.3} ? 1951-2010年间,温室气体造成的全球平均地表增温可能在0.5°C至1.3°C之间,包括气溶胶降温效应在 内的其它人为强迫的贡献可能在-0.6 °C至0.1 °C之间。自然强迫的贡献可能在-0.1 °C至0.1 °C之间,自 然内部变率的贡献可能在-0.1°C至0.1°C之间。综合起来,所评估的这些贡献与这个时期所观测到的约 0.6°C到0.7°C的变暖相一致。{10.3} ? 在除南极以外的每个大陆地区,人为强迫可能对20世纪中叶以来的地表温度升高作出了重要贡献(见图 SPM.6)。对南极地区,很大的观测不确定性导致人为强迫对现有台站观测到的变暖具有贡献这一结论具 有低信度。可能的是,人类活动对20世纪中叶以来北极明显的变暖具有贡献。{2.4,10.3} ? 很可能的是,人为影响特别是温室气体和平流层臭氧损耗,导致了可检测到的1961年以来对流层升温以 及平流层下部相应降温的分布。{2.4, 9.4, 10.3} ? 很可能的是,人为强迫对观测到的20世纪70年代以来全球海洋上层热含量(0-700米)增加作出了重要 贡献(见图SPM.6)。有证据表明人类活动影响了某些个别洋盆。{3.2, 10.4} ? 可能的是,人为活动影响了1960年以来的全球水循环。人为影响对观测到的大气水汽含量的增加(中 等信度),全球尺度陆地降水分布的变化(中等信度),资料充分的陆地地区强降水的加强(中等信 度),以及海洋表层和次表层盐度的变化(很可能)作出了贡献。{2.5, 2.6, 3.3, 7.6, 10.3, 10.4} 15 Summary for Policymakers SPM Global averages Land surface Land and ocean surface Ocean heat content Observations Models using only natural forcings Models using both natural and anthropogenic forcings Figure SPM.6 | Comparison of observed and simulated climate change based on three large-scale indicators in the atmosphere, the cryosphere and the ocean: change in continental land surface air temperatures (yellow panels), Arctic and Antarctic September sea ice extent (white panels), and upper ocean heat content in the major ocean basins (blue panels). Global average changes are also given. Anomalies are given relative to 1880–1919 for surface temperatures, 1960–1980 for ocean heat content and 1979–1999 for sea ice. All time-series are decadal averages, plotted at the centre of the decade. For temperature panels, observations are dashed lines if the spatial coverage of areas being examined is below 50%. For ocean heat content and sea ice panels the solid line is where the coverage of data is good and higher in quality, and the dashed line is where the data coverage is only adequate, and thus, uncertainty is larger. Model results shown are Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble ranges, with shaded bands indicating the 5 to 95% confidence intervals. For further technical details, including region definitions see the Technical Summary Supplementary Material. {Figure 10.21;

Figure TS.12} 16 决策者摘要 С? SPM С?? ?? ?? С??? С??? ?? ???? ??? ???? ??? ???? ?? ??? ??? ???? ???? ??????? ????????? ?? ?????????? ???????????????? 图SPM.6: 利用大气、冰冻圈和海洋的三个大尺度指标比较观测到的和模拟的气候变化。三个指标分别为:大陆地表气温变化 (黄色部分)、北极和南极9月海冰范围(白色部分)以及主要洋盆的海洋上层热含量(蓝色部分)。同时也给出了全球平均变 化。地表温度的距平相对于1880-1919年,海洋热含量的距平相对于1960-1980年,海冰距平相对于1979-1999年。所有时间序列 都是在十年的中心处绘制的十年平均值。在气温图中,如果研究区域的空间覆盖率低于50%,则观测值用虚线表示。在海洋热含 量和海冰图中,实线是指资料覆盖完整且质量较高的部分,虚线是指仅资料覆盖充分而不确定性较大的部分。模式结果是耦合 模式比较计划第五阶段(CMIP5)的多模式集合范围,阴影带表示5%至95%信度区间。进一步的技术细节,包括区域定义,参见 技术摘要补充材料。{图10.21;图TS.12} 16 Summary for Policymakers ? There has been further strengthening of the evidence for human influence on temperature extremes since the SREX. It is now very likely that human influence has contributed to observed global scale changes in the frequency and intensity of daily temperature extremes since the mid-20th century, and likely that human influence has more than doubled the probability of occurrence of heat waves in some locations (see Table SPM.1). {10.6} ? Anthropogenic influences have very likely contributed to Arctic sea ice loss since 1979. There is low confidence in the scientific understanding of the small observed increase in Antarctic sea ice extent due to the incomplete and competing scientific explanations for the causes of change and low confidence in estimates of natural internal variability in that region (see Figure SPM.6). {10.5} ? Anthropogenic influences likely contributed to the retreat of glaciers since the 1960s and to the increased surface mass loss of the Greenland ice sheet since 1993. Due to a low level of scientific understanding there is low confidence in attributing the causes of the observed loss of mass from the Antarctic ice sheet over the past two decades. {4.3, 10.5} ? It is likely that there has been an anthropogenic contribution to observed reductions in Northern Hemisphere spring snow cover since 1970. {10.5} ? It is very likely that there is a substantial anthropogenic contribution to the global mean sea level rise since the 1970s. This is based on the high confidence in an anthropogenic influence on the two largest contributions to sea level rise, that is thermal expansion and glacier mass loss. {10.4, 10.5, 13.3} ? There is high confidence that changes in total solar irradiance have not contributed to the increase in global mean surface temperature over the period 1986 to 2008, based on direct satellite measurements of total solar irradiance. There is medium confidence that the 11-year cycle of solar variability influences decadal climate fluctuations in some regions. No robust association between changes in cosmic rays and cloudiness has been identified. {7.4, 10.3, Box 10.2} SPM E. Future Global and Regional Climate Change Projections of changes in the climate system are made using a hierarchy of climate models ranging from simple climate models, to models of intermediate complexity, to comprehensive climate models, and Earth System Models. These models simulate changes based on a set of scenarios of anthropogenic forcings. A new set of scenarios, the Representative Concentration Pathways (RCPs), was used for the new climate model simulations carried out under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) of the World Climate Research Programme. In all RCPs, atmospheric CO2 concentrations are higher in 2100 relative to present day as a result of a further increase of cumulative emissions of CO2 to the atmosphere during the 21st century (see Box SPM.1). Projections in this Summary for Policymakers are for the end of the 21st century (2081–2100) given relative to 1986–2005, unless otherwise stated. To place such projections in historical context, it is necessary to consider observed changes between different periods. Based on the longest global surface temperature dataset available, the observed change between the average of the period 1850–1900 and of the AR5 reference period is 0.61 [0.55 to 0.67] °C. However, warming has occurred beyond the average of the AR5 reference period. Hence this is not an estimate of historical warming to present (see Chapter 2) . Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and ? sustained reductions of greenhouse gas emissions. {6, 11–14} ? Projections for the next few decades show spatial patterns of climate change similar to those projected for the later 21st century but with smaller magnitude. Natural internal variability will continue to be a major influence on climate, particularly in the near-term and at the regional scale. By the mid-21st century the magnitudes of the projected changes are substantially affected by the choice of emissions scenario (Box SPM.1). {11.3, Box 11.1, Annex I} 17 决策者摘要 ? 自SREX以来,极端温度人为影响的证据进一步增强。目前,很可能的是,人为影响对观测到的20世纪中 叶以来日极端温度的频率和强度的全球变化作出了贡献,人类影响可能使一些地区热浪发生的概率加倍 (见表SPM.1)。{10.6} ? 人为强迫很可能对1979年以来北极海冰的损耗作出了贡献。由于对南极海冰范围变化原因的科学解释不 完整且相互矛盾,而且对该地区自然内部变率的估计具有低信度,因此对观测到的南极海冰范围小幅增 加的科学认识具有低信度(见图SPM.6)。{10.5} ? 人为影响可能对20世纪60年代以来的冰川退缩和1993年以来格陵兰冰盖表面冰量损耗加剧作出了贡 献。由于科学认识的水平还较低,对观测到的过去二十年南极冰盖冰量损耗的归因具有低信度。{4.3, 10.5} ? 可能的是,观测到的1970年以来北半球春季积雪减少有人为贡献。{10.5} ? 很可能的是,人类活动对20世纪70年代以来的全球平均海平面上升作出了重要贡献。这是由于人类活 动对造成海平面上升的两大因子,即热膨胀和冰川冰量损耗产生影响的这一结论具有高信度。{10.4, 10.5, 13.3} ? 具有高信度的是,基于对太阳总辐射的直接卫星观测,1986-2008年间,太阳总辐射的变化未对此期间 的全球平均地表温度上升作出贡献。具有中等信度的是,太阳变率的11年周期影响了某些地区的年代际 气候波动。宇宙射线和云量的变化之间没有确凿的联系被发现。{7.4,10.3,文框10.2} SPM E. 未来的全球及区域气候变化 对气候系统变化的预估基于一系列气候模式得出,包括简单气候模式、中等复杂模式、综合气候模式以及 地球系统模式。这些模式基于一系列人为强迫的情景来模拟气候变化。典型浓度路径(RCPs)是世界气候 研究计划(WCRP)中耦合模式比较计划第五阶段(CMIP5)框架下的一套新情景,被用来进行新的气候模式 模拟。在所有RCP中,由于21世纪累计排放到大气中的二氧化碳进一步增加,2100年大气二氧化碳浓度比当 前要高(见文框SPM.1)。除另有说明,本决策者摘要预估的是21世纪末(2081-2100年)相对于1986-2005 年的变化。为了将这种预估结果置于历史背景下,有必要考虑观测到的不同时期之间的变化。基于可用的 最长的全球地表温度数据集,观测到的1850年至1900年间平均值与AR5参照期平均值的变化为0.61[0.55到 0.67]°C。然而,变暖已经超出了AR5参照期的平均值。因此,这不是对到现在的历史变暖的估算(参见第 2章)。 温室气体继续排放将会造成进一步增暖,并导致气候系统所有组成部分发生变 化。限制气候变化将需要大幅度和持续地减少温室气体排放。{第6章, 第11-14章} ? 未来几十年的预估显示气候变化的空间模态与21世纪后期的预估结果类似,但幅度较小。自然内部变率 仍将是影响气候的主要因素,在近期和区域尺度上尤其如此。到21世纪中叶,预估的变化幅度基本取决 于所选择的排放情景(文框SPM.1)。{11.3,文框11.1,附录1} 17 Summary for Policymakers SPM ? Projected climate change based on RCPs is similar to AR4 in both patterns and magnitude, after accounting for scenario differences. The overall spread of projections for the high RCPs is narrower than for comparable scenarios used in AR4 because in contrast to the SRES emission scenarios used in AR4, the RCPs used in AR5 are defined as concentration pathways and thus carbon cycle uncertainties affecting atmospheric CO2 concentrations are not considered in the concentration-driven CMIP5 simulations. Projections of sea level rise are larger than in the AR4, primarily because of improved modelling of land-ice contributions.{11.3, 12.3, 12.4, 13.4, 13.5} E.1 Atmosphere: Temperature Global surface temperature change for the end of the 21st century is likely to exceed 1.5°C relative to 1850 to 1900 for all RCP scenarios except RCP2.6. It is likely to exceed 2°C for RCP6.0 and RCP8.5, and more likely than not to exceed 2°C for RCP4.5. Warming will continue beyond 2100 under all RCP scenarios except RCP2.6. Warming will continue to exhibit interannual-to-decadal variability and will not be regionally uniform (see Figures SPM.7 and SPM.8). {11.3, 12.3, 12.4, 14.8} ? The global mean surface temperature change for the period 2016–2035 relative to 1986–2005 will likely be in the range of 0.3°C to 0.7°C (medium confidence). This assessment is based on multiple lines of evidence and assumes there will be no major volcanic eruptions or secular changes in total solar irradiance. Relative to natural internal variability, near-term increases in seasonal mean and annual mean temperatures are expected to be larger in the tropics and subtropics than in mid-latitudes (high confidence). {11.3} ? Increase of global mean surface temperatures for 2081–2100 relative to 1986–2005 is projected to likely be in the ranges derived from the concentration-driven CMIP5 model simulations, that is, 0.3°C to 1.7°C (RCP2.6), 1.1°C to 2.6°C (RCP4.5), 1.4°C to 3.1°C (RCP6.0), 2.6°C to 4.8°C (RCP8.5). The Arctic region will warm more rapidly than the global mean, and mean warming over land will be larger than over the ocean (very high confidence) (see Figures SPM.7 and SPM.8, and Table SPM.2). {12.4, 14.8} ? Relative to the average from year 1850 to 1900, global surface temperature change by the end of the 21st century is projected to likely exceed 1.5°C for RCP4.5, RCP6.0 and RCP8.5 (high confidence). Warming is likely to exceed 2°C for RCP6.0 and RCP8.5 (high confidence), more likely than not to exceed 2°C for RCP4.5 (high confidence), but unlikely to exceed 2°C for RCP2.6 (medium confidence). Warming is unlikely to exceed 4°C for RCP2.6, RCP4.5 and RCP6.0 (high confidence) and is about as likely as not to exceed 4°C for RCP8.5 (medium confidence). {12.4} ? It is virtually certain that there will be more frequent hot and fewer cold temperature extremes over most land areas on daily and seasonal timescales as global mean temperatures increase. It is very likely that heat waves will occur with a higher frequency and duration. Occasional cold winter extremes will continue to occur (see Table SPM.1). {12.4} E.2 Atmosphere: Water Cycle Changes in the global water cycle in response to the warming over the 21st century will not be uniform. The contrast in precipitation between wet and dry regions and between wet and dry seasons will increase, although there may be regional exceptions (see Figure SPM.8). {12.4, 14.3} ? Projected changes in the water cycle over the next few decades show similar large-scale patterns to those towards the end of the century, but with smaller magnitude. Changes in the near-term, and at the regional scale will be strongly influenced by natural internal variability and may be affected by anthropogenic aerosol emissions. {11.3} 18 决策者摘要 ? 考虑情景差异后,基于各RCPs预估的气候变化在模态和幅度方面都与第四次评估报告的预估结果相似。

与第四次评估报告中可比的SRES排放情景相比,利用高RCPs得出的预估总体离散度要窄一些,这是因为 相对于第四次评估报告中使用的SRES排放情景,第五次评估报告使用的RCPs是用浓度路径来定义,因此 影响大气CO2浓度的碳循环不确定性在以浓度驱动CMIP5模拟中未予以考虑。对于海平面上升的预估大于 AR4中的预估,这主要是因为改进了对陆地冰贡献的模拟。{11.3, 12.3, 12.4, 13.4, 13.5} SPM E.1 大气:温度 相对于1850-1900年,在所有情景下(RCP2.6情景除外),21世纪末全球表 面温度变化可能超过1.5°C。在RCP6.0和RCP8.5情景下,可能超过2°C。在 RCP4.5情景下多半可能超过2°C。在所有情景下(RCP2.6情景除外),2100 年之后仍将持续变暖。变暖将继续表现为年际到年代变率,并且不具有区域一 致性(见图SPM.7和SPM.8){11.3, 12.3, 12.4, 14.8} ? 与1986-2005年相比,2016-2035年期间全球平均表面温度变化 可能升高0.3°C到0.7°C(中等信度)。

这一评估是以多个证据链为依据,并假定没有大的火山喷发或太阳总辐照度的长期变化。与自然内部 变率相比,热带和副热带的季节平均温度和年平均温度的近期上升幅度预计会大于中纬度地区(高信 度)。{11.3} ? 与1986-2005年相比,预估2081-2100年全球平均表面温度上升可能处于由浓度驱动的CMIP5模式模拟得 出的范围,即0.3°C至1.7°C(RCP2.6),1.1°C至2.6°C(RCP4.5),1.4°C至3.1°C(RCP6.0),2.6°C 至4.8°C(RCP8.5)。北极地区变暖速度将高于全球平均,陆地平均变暖幅度将大于海洋(很高信度) (见图SPM.7和SPM.8,以及表SPM.2)。{12.4, 14.8} ? 与1850-1900年平均值相比,预估到21世纪末全球表面温度变化在RCP4.5、RCP6.0和RCP8.5情景下 可能 都超过1.5°C(高信度)。在RCP6.0和RCP8.5情景下,升温可能超过2°C(高信度),在RCP4.5情景下多 半可能超过2°C(高信度),但在RCP2.6情景下升温不可能超过2°C(中等信度)。在RCP2.6、RCP4.5和 RCP6.0情景下升温不可能超过4°C(高信度),在RCP8.5情景下或许可能超过4°C(中等信度)。{12.4} ? 几乎确定的是,随着全球平均温度上升,日和季节尺度上,大部分陆地区域的极端暖事件将增多,极端 冷事件将减少。很可能的是,热浪发生的频率更高,时间更长。偶尔仍会发生冷冬极端事件。(见表 SPM.1)。{12.4} E.2 大气:水循环 在21世纪,全球水循环对变暖的响应不均一。干湿地区之间和干湿季节之间 的降水差异将会增大,尽管有的区域例外(见图SPM.8)。{12.4, 14.3} ? 预估未来几十年水循环的变化在大尺度型态方面与到本世纪末的变化相似,但是幅度较小。近期区域尺 度的变化将受自然内部变率的强烈影响,并可能受人为气溶胶排放的影响。{11.3} 18 Summary for Policymakers (a) 6.0 4.0 Global average surface temperature change historical RCP2.6 RCP8.5 Mean over 2081–2100 39 RCP8.5 (oC) SPM 2.0 0.0 ?2.0 1950 32 RCP4.5 RCP4.5 RCP4.5 42 RCP2.6 2000 2050 2100 (b) 10.0 8.0 Northern Hemisphere September sea ice extent 39 (5) (106 km2) 6.0 4.0 2.0 0.0 1950 37 (5) 29 (3) RCP2.6 RCP6.0 RCP6.0 RCP6.0 2000 2050 2100 (c) 8.2 Global ocean surface pH 12 9 RCP2.6 (pH unit) 8.0 10 7.8 7.6 1950 2000 Year 2050 2100 Figure SPM.7 | CMIP5 multi-model simulated time series from 1950 to 2100 for (a) change in global annual mean surface temperature relative to 1986–2005, (b) Northern Hemisphere September sea ice extent (5-year running mean), and (c) global mean ocean surface pH. Time series of projections and a measure of uncertainty (shading) are shown for scenarios RCP2.6 (blue) and RCP8.5 (red). Black (grey shading) is the modelled historical evolution using historical reconstructed forcings. The mean and associated uncertainties averaged over 2081?2100 are given for all RCP scenarios as colored vertical bars. The numbers of CMIP5 models used to calculate the multi-model mean is indicated. For sea ice extent (b), the projected mean and uncertainty (minimum-maximum range) of the subset of models that most closely reproduce the climatological mean state and 1979 to 2012 trend of the Arctic sea ice is given (number of models given in brackets). For completeness, the CMIP5 multi-model mean is also indicated with dotted lines. The dashed line represents nearly ice-free conditions (i.e., when sea ice extent is less than 106 km2 for at least five consecutive years). For further technical details see the Technical Summary Supplementary Material {Figures 6.28, 12.5, and 12.28–12.31;

Figures TS.15, TS.17, and TS.20} 19 RCP8.5 RCP8.5 决策者摘要 (a) 6.0 4.0 ?? RCP2.6 RCP8.5 ??????????   ??? 39 (oC) ?2.0 1950 2000 2050 2100 (b) 10.0 8.0 С?????????? 39 (5) (106 km2) 6.0 4.0 2.0 0.0 1950 37 (5) 29 (3) RCP2.6 RCP2.6 0.0 32 RCP4.5 RCP4.5 42 RCP6.0 RCP6.0 2000 2050 2100 (c) 8.2 12 ??????X0 (pH unit) 9 RCP2.6 8.0 7.8 7.6 1950 10 RCP4.5 RCP6.0 2000 2050 2100 图SPM.7:CMIP5多模式模拟的1950至2100年时间序列:(a)相对于1986-2005年的全球年均地表温度的变化,(b)北半球9月海冰范围(5年滑动平均),以及 (c)全球平均海洋表面pH。图上是RCP2.6(蓝色)和RCP8.5(红色)情景下预估的时间序列和不确定性(阴影)。黑色(灰色阴影)是利用历史重建强迫模拟的历史演 变。垂直色块是所有RCP情景下2081-2100年期间的平均值和相关的不确定性。在此也给出了用于计算多模式平均的CMIP5模式数量。对于海冰范围(b),给出了最准确 重现北极海冰气候平均状况和1979-2012年趋势的子模式集(括号中给出模式的数量)预估的平均值和不确定性(最小值到最大值的范围)。为了完整性,也用点线给 出了CMIP5多模式平均值。虚线代表的是几乎无冰条件(即海冰范围至少连续五年小于106平方公里)。更多的技术详情参见技术摘要补充材料。{图6.28,12.5和12.28– 12.31;图TS.15,TS.17和TS.20} 19 RCP8.5 RCP8.5 RCP8.5 2.0 SPM Summary for Policymakers (a) RCP 2.6 RCP 8.5 Change in average surface temperature (1986?2005 to 2081?2100) 32 39 SPM (°C) ?2 ?1.5 ?1 ?0.5 0 0.5 1 1.5 2 3 4 5 7 9 11 (b) Change in average precipitation (1986?2005 to 2081?2100) 32 39 ?50 ?40 ?30 ?20 ?10 0 10 20 30 40 50 (%) (c) Northern Hemisphere September sea ice extent (average 2081?2100) 29 (3) CMIP5 multi-model average 1986?2005 CMIP5 multi-model average 2081?2100 CMIP5 subset average 1986?2005 CMIP5 subset average 2081?2100 37 (5) (d) Change in ocean surface pH (1986?2005 to 2081?2100) 9 10 ?0.6 ?0.55 ?0.5 ?0.45 ?0.4 ?0.35 ?0.3 ?0.25 ?0.2 ?0.15 ?0.1 ?0.05 (pH unit) Figure SPM.8 | Maps of CMIP5 multi-model mean results for the scenarios RCP2.6 and RCP8.5 in 2081–2100 of (a) annual mean surface temperature change, (b) average percent change in annual mean precipitation, (c) Northern Hemisphere September sea ice extent, and (d) change in ocean surface pH. Changes in panels (a), (b) and (d) are shown relative to 1986–2005. The number of CMIP5 models used to calculate the multi-model mean is indicated in the upper right corner of each panel. For panels (a) and (b), hatching indicates regions where the multi-model mean is small compared to natural internal variability (i.e., less than one standard deviation of natural internal variability in 20-year means). Stippling indicates regions where the multi-model mean is large compared to natural internal variability (i.e., greater than two standard deviations of natural internal variability in 20-year means) and where at least 90% of models agree on the sign of change (see Box 12.1). In panel (c), the lines are the modelled means for 1986?2005;

the filled areas are for the end of the century. The CMIP5 multi-model mean is given in white colour, the projected mean sea ice extent of a subset of models (number of models given in brackets) that most closely reproduce the climatological mean state and 1979 to 2012 trend of the Arctic sea ice extent is given in light blue colour. For further technical details see the Technical Summary Supplementary Material. {Figures 6.28, 12.11, 12.22, and 12.29;

Figures TS.15, TS.16, TS.17, and TS.20} 20 决策者摘要 (a) RCP 2.6 RCP 8.5 ?????????! ??? ??? 32 39 SPM (°C) ?2 ?1.5 ?1 ?0.5 0 0.5 1 1.5 2 3 4 5 7 9 11 (b) ???????! ??? ??? 32 39 ?50 ?40 ?30 ?20 ?10 0 10 20 30 40 50 (%) (c) С??!??????? ???? 29 (3) +518??????? ! ?? +518???????  ?? +518???? ! ?? +518????  ?? 37 (5) (d) ????X0???! ??? ??? 9 10 ?0.6 ?0.55 ?0.5 ?0.45 ?0.4 ?0.35 ?0.3 ?0.25 ?0.2 ?0.15 ?0.1 ?0.05 (pH unit) 图SPM.8:CMIP5多模式在RCP2.6和RCP8.5情景下对2081–2100年模拟的平均结果:(a)年均表面温度变化,(b)年均降水百 分率变化,(c)北半球9月海冰范围,以及(d)海洋表面pH的变化。图(a)、(b)和(d)部分的变化相对于1986-2005年。每个 部分右上角都标明了用于计算多模式平均的CMIP5模式数量。图(a)和(b)中的阴影是指多模式平均值小于内部变率的地区 (即,小于20年平均自然内部变率一个标准差)。点状部分是指多模式平均值大于自然内部变率(即,大于20年平均自然内部 变率两个标准差)且90%的模式在变化特征上吻合的地区(见文框12.1)。图(c)中,线条表示模拟的1986-2005年均值;填充 部分是本世纪末的均值。白色是CMIP5的多模式平均值,浅蓝色是最准确重现北极气候平均状况和北极海冰范围1979-2012年趋 势的模式子集(模式的数量见括号)预估的平均海冰范围。更多的技术细节参见技术摘要补充材料。{图6.28,12.11,12.22和 12.29;图TS.15,TS.16,TS.17和TS.20} 20 Summary for Policymakers ? The high latitudes and the equatorial Pacific Ocean are likely to experience an increase in annual mean precipitation by the end of this century under the RCP8.5 scenario. In many mid-latitude and subtropical dry regions, mean precipitation will likely decrease, while in many mid-latitude wet regions, mean precipitation will likely increase by the end of this century under the RCP8.5 scenario (see Figure SPM.8). {7.6, 12.4, 14.3} ? Extreme precipitation events over most of the mid-latitude land masses and over wet tropical regions will very likely become more intense and more frequent by the end of this century, as global mean surface temperature increases (see Table SPM.1). {7.6, 12.4} ? Globally, it is likely that the area encompassed by monsoon systems will increase over the 21st century. While monsoon winds are likely to weaken, monsoon precipitation is likely to intensify due to the increase in atmospheric moisture. Monsoon onset dates are likely to become earlier or not to change much. Monsoon retreat dates will likely be delayed, resulting in lengthening of the monsoon season in many regions. {14.2} ? There is high confidence that the El Ni?o-Southern Oscillation (ENSO) will remain the dominant mode of interannual variability in the tropical Pacific, with global effects in the 21st century. Due to the increase in moisture availability, ENSOrelated precipitation variability on regional scales will likely intensify. Natural variations of the amplitude and spatial pattern of ENSO are large and thus confidence in any specific projected change in ENSO and related regional phenomena for the 21st century remains low. {5.4, 14.4} Table SPM.2 | Projected change in global mean surface air temperature and global mean sea level rise for the mid- and late 21st century relative to the reference period of 1986–2005. {12.4;

Table 12.2, Table 13.5} 2046–2065 Scenario RCP2.6 2081–2100 Mean 1.0 1.8 2.2 3.7 d Mean 1.0 1.4 1.3 2.0 Likely rangec 0.4 to 1.6 0.9 to 2.0 0.8 to 1.8 1.4 to 2.6 Likely rangec 0.3 to 1.7 1.1 to 2.6 1.4 to 3.1 2.6 to 4.8 Global Mean Surface Temperature Change (°C) a RCP4.5 RCP6.0 RCP8.5 Scenario RCP2.6 Mean 0.24 0.26 0.25 0.30 Likely range 0.17 to 0.32 0.19 to 0.33 0.18 to 0.32 0.22 to 0.38 Mean 0.40 0.47 0.48 0.63 Likely ranged 0.26 to 0.55 0.32 to 0.63 0.33 to 0.63 0.45 to 0.82 Global Mean Sea Level Rise (m)b RCP4.5 RCP6.0 RCP8.5 Notes: a Based on the CMIP5 ensemble;

anomalies calculated with respect to 1986–2005. Using HadCRUT4 and its uncertainty estimate (5?95% confidence interval), the observed warming to the reference period 1986?2005 is 0.61 [0.55 to 0.67] °C from 1850?1900, and 0.11 [0.09 to 0.13] °C from 1980?1999, the reference period for projections used in AR4. Likely ranges have not been assessed here with respect to earlier reference periods because methods are not generally available in the literature for combining the uncertainties in models and observations. Adding projected and observed changes does not account for potential effects of model biases compared to observations, and for natural internal variability during the observational reference period {2.4;

11.2;

Tables 12.2 and 12.3} Based on 21 CMIP5 models;

anomalies calculated with respect to 1986–2005. Where CMIP5 results were not available for a particular AOGCM and scenario, they were estimated as explained in Chapter 13, Table 13.5. The contributions from ice sheet rapid dynamical change and anthropogenic land water storage are treated as having uniform probability distributions, and as largely independent of scenario. This treatment does not imply that the contributions concerned will not depend on the scenario followed, only that the current state of knowledge does not permit a quantitative assessment of the dependence. Based on current understanding, only the collapse of marine-based sectors of the Antarctic ice sheet, if initiated, could cause global mean sea level to rise substantially above the likely range during the 21st century. There is medium confidence that this additional contribution would not exceed several tenths of a meter of sea level rise during the 21st century. b c Calculated from projections as 5?95% model ranges. These ranges are then assessed to be likely ranges after accounting for additional uncertainties or different levels of confidence in models. For projections of global mean surface temperature change in 2046?2065 confidence is medium, because the relative importance of natural internal variability, and uncertainty in non-greenhouse gas forcing and response, are larger than for 2081?2100. The likely ranges for 2046?2065 do not take into account the possible influence of factors that lead to the assessed range for near-term (2016?2035) global mean surface temperature change that is lower than the 5?95% model range, because the influence of these factors on longer term projections has not been quantified due to insufficient scientific understanding. {11.3} Calculated from projections as 5?95% model ranges. These ranges are then assessed to be likely ranges after accounting for additional uncertainties or different levels of confidence in models. For projections of global mean sea level rise confidence is medium for both time horizons. d 21 决策者摘要 ? 在RCP8.5情景下,到本世纪末,高纬度地区和赤道太平洋年平均降水可能增加。在RCP8.5情景下,到本 世纪末,很多中纬度和副热带干旱地区平均降水将可能减少,很多中纬度湿润地区的平均降水可能增加 (见图SPM.8)。{7.6, 12.4, 14.3} ? 随着全球平均表面温度的上升,中纬度大部分陆地地区和湿润的热带地区的极端降水事件很可能强度加 大、频率增高(见表SPM.1)。{7.6, 12.4} ? 全球范围内受季风系统影响的地区在21世纪可能增加。而在季风可能减弱的同时,由于大气湿度增加, 季风降水可能增强。季风开始日期可能提前,或者变化不大。季风消退日期可能推后,导致许多地区的 季风期延长。{14.2} ? 具有高信度的是,厄尔尼诺-南方涛动(ENSO)在21世纪仍是热带太平洋地区年际变率的主导模态,并 且影响全球。由于水汽供应增加,区域尺度上ENSO相关的降水变率将可能加强。ENSO的振幅和空间分 布有显著的自然变化,因此对21世纪ENSO及相关区域现象进行的具体预估变化的信度仍然为 低。{5.4, 14.4} SPM 表SPM.2: 与1986-2005年参照期相比,21世纪中期和后期全球平均表面气温和全球平均海平面上升的预估变化。{12.4; 表12.2,表13.5} 2046-2065 情景 RCP2.6 2081-2100 平均 1.0 1.8 2.2 3.7 d 平均 1.0 1.4 1.3 2.0 可能性区间c 0.4 to 1.6 0.9 to 2.0 0.8 to 1.8 1.4 to 2.6 可能性区间c 0.3 to 1.7 1.1 to 2.6 1.4 to 3.1 2.6 to 4.8 全球平均表面温 度变化 (°C) a RCP4.5 RCP6.0 RCP8.5 情景 RCP2.6 平均 0.24 0.26 0.25 0.30 可能性区间 0.17 to 0.32 0.19 to 0.33 0.18 to 0.32 0.22 to 0.38 平均 0.40 0.47 0.48 0.63 可能性区间d 0.26 to 0.55 0.32 to 0.63 0.33 to 0.63 0.45 to 0.82 全球平均海平面 上升 (m)b RCP4.5 RCP6.0 RCP8.5 注: a 基于CMIP5集合;距平相对于1986-2005年。根据HadCRUT4及其不确定性估计(5-95%的置信区间),参照期1986-2005年比1850-1900年 偏暖0.61 [0.55至0.67] °C,比1980-1999年偏暖0.11 [0.09 至0.13] °C,1890-1999年是AR4的预估参照期。因为文献中的方法总体不能用于 结合模式和观测中的不确定性,所以此处没有评估与较早参照期相应的可能性区间。将预估和观测到的变化加入后,不能解释与观测相比的模 式偏差的潜在影响,也不能解释观测参照期的内部变率{2.4; 11.2;表 12.2 和12.3} 基于21个CMIP5模式;距平相对于1986-2005年。如果在一个特定的AOGCM和情景下CMIP5无结果时,距平是估算的,有关解释见第13章中 的表13.5。在处理冰盖的快速动态变化和人类陆地水储存的贡献时采用一致的概率分布,并且其贡献大小基本不取决于情景。这种处理方法并 不意味着相关的贡献与模式使用的情景无关,而是因为现有知识水平无法量化评估对情景的依赖性。根据目前的理解,只有当南极大冰盖的海 上部分崩塌后,才有可能使全球平均海平面在21世纪大幅上升至可能性区间以上。在21世纪这种额外的贡献不会超过海平面上升几分米,此判 断具有中等信度。 b c 由模式预估计算得到5-95%的区间。在考虑附加的不确定性或模式信度水平后,这些区间被评估为可能性区间。2046-2065年全球平均表面温 度变化预估信度为中等,是因为自然内部变率的重要性以及非温室气体强迫和响应比2081-2100年要大。2046-2065年的可能性区间没有考虑 导致近期(2016-2035)全球平均地表温度变化区间低于5-95%模式区间的因素的可能影响,这是因为科学认知的不足使这些因素对于长期预 估的影响无法量化。{11.3} 由模式预估计算得到5-95%的区间。在考虑更多不确定性或模式信度水平后,这些区间被评估为可能性区间。两个时间段的全球平均海平面上 升预估信度都为中等。 d 21 Summary for Policymakers E.3 Atmosphere: Air Quality ? The range in projections of air quality (ozone and PM2.517 in near-surface air) is driven primarily by emissions (including CH4), rather than by physical climate change (medium confidence). There is high confidence that globally, warming decreases background surface ozone. High CH4 levels (as in RCP8.5) can offset this decrease, raising background surface ozone by year 2100 on average by about 8 ppb (25% of current levels) relative to scenarios with small CH4 changes (as in RCP4.5 and RCP6.0) (high confidence). {11.3} ? Observational and modelling evidence indicates that, all else being equal, locally higher surface temperatures in polluted regions will trigger regional feedbacks in chemistry and local emissions that will increase peak levels of ozone and PM2.5 (medium confidence). For PM2.5, climate change may alter natural aerosol sources as well as removal by precipitation, but no confidence level is attached to the overall impact of climate change on PM2.5 distributions. {11.3} SPM E.4 Ocean The global ocean will continue to warm during the 21st century. Heat will penetrate from the surface to the deep ocean and affect ocean circulation. {11.3, 12.4} ? The strongest ocean warming is projected for the surface in tropical and Northern Hemisphere subtropical regions. At greater depth the warming will be most pronounced in the Southern Ocean (high confidence). Best estimates of ocean warming in the top one hundred meters are about 0.6°C (RCP2.6) to 2.0°C (RCP8.5), and about 0.3°C (RCP2.6) to 0.6°C (RCP8.5) at a depth of about 1000 m by the end of the 21st century. {12.4, 14.3} ? It is very likely that the Atlantic Meridional Overturning Circulation (AMOC) will weaken over the 21st century. Best estimates and ranges18 for the reduction are 11% (1 to 24%) in RCP2.6 and 34% (12 to 54%) in RCP8.5. It is likely that there will be some decline in the AMOC by about 2050, but there may be some decades when the AMOC increases due to large natural internal variability. {11.3, 12.4} ? It is very unlikely that the AMOC will undergo an abrupt transition or collapse in the 21st century for the scenarios considered. There is low confidence in assessing the evolution of the AMOC beyond the 21st century because of the limited number of analyses and equivocal results. However, a collapse beyond the 21st century for large sustained warming cannot be excluded. {12.5} E.5 Cryosphere It is very likely that the Arctic sea ice cover will continue to shrink and thin and that Northern Hemisphere spring snow cover will decrease during the 21st century as global mean surface temperature rises. Global glacier volume will further decrease. {12.4, 13.4} ? Year-round reductions in Arctic sea ice extent are projected by the end of the 21st century from multi-model averages. These reductions range from 43% for RCP2.6 to 94% for RCP8.5 in September and from 8% for RCP2.6 to 34% for RCP8.5 in February (medium confidence) (see Figures SPM.7 and SPM.8). {12.4} 17 18 PM2.5 refers to particulate matter with a diameter of less than 2.5 micrometres, a measure of atmospheric aerosol concentration. The ranges in this paragraph indicate a CMIP5 model spread. 22 决策者摘要 E.3 大气:空气质量 ? 空气质量(近地表空气中的臭氧和PM2.517)的预估范围主要是以排放(包括CH4)为驱动,而不是以自 然气候变化为驱动(中等信度)。具有高信度的是,在全球尺度上,变暖会降低本底地表臭氧。高CH4 水平(RCP8.5)可以抵消这种下降,相对于CH4变化小的情景(RCP4.5、RCP6.0),到2100年本底地表 臭氧平均上升约8ppb(目前水平的25%)(高信度)。{11.3} ? 观测和模拟的证据表明,当其它条件都相同时,受污染地区的局地较高地表温度将会触发区域化学和 局地排放反馈,进一步推高臭氧和PM2.5的峰值水平(中等信度)。对于PM2.5,气候变化可能会改变 自然气溶胶的源,并改变可发挥清除作用的降水,但气候变化对PM2.5分布总体影响的信度水平尚未确 定。{11.3} SPM E.4 海洋 21世纪全球海洋将持续变暖。热量将从海面输送到深海,并影响海洋环流。 {11.3, 12.4} ? 预计海洋变暖最强的区域是热带和北半球副热带地区的海表面。深海变暖以南大洋最为明显( 高信 度 ) 。

到 2 1 世 纪 末 , 上 层 1 0 0 米 内 海 洋 变 暖 幅 度 的 最 佳 估 计 值 约 为 0 . 6 °C ( R C P 2 . 6 情 景 ) 至2.0 °C(RCP8.5情景),1000米深的海洋变暖幅度大约为0.3 °C(RCP2.6情景)至0.6 °C(RCP8.5情 景)。{12.4, 14.3} ? 很可能的是,在21世纪,大西洋经向翻转环流(AMOC)将会减弱。CMIP5模拟的AMOC减弱的最佳估计值 和范围18在RCP2.6情景下为11%(1-24%),在RCP8.5情景下为34%(12-54%)。可能的是,大约到2050 年,AMOC会有一些减弱,但由于显著的内部变率,AMOC可能会在其中几十年间增强。{11.3,12.4} ? 依据现有的情景,21世纪内AMOC发生突变或者崩溃的情况是很不可能的。因为分析有限,结果不确定, 对21世纪之后AMOC演变的评估只有低信度。但是,不排除21世纪之后由于显著持续升温致使AMOC崩溃的 可能。{12.5} E.5 冰冻圈 很可能的是,在21世纪随着全球平均表面温度上升,北极海冰覆盖将继续缩 小、变薄,北半球春季积雪将减少。全球冰川体积将进一步减少。{12.4, 13.4} ? 到21世纪末,根据多模式平均值,预估北极海冰范围全年都会减少。9月份减少的范围从RCP2.6情景下 的43%到RCP8.5情景下的94%;2月份减少的范围从RCP2.6情景下的8%到RCP8.5情景下的34%(中等信度) (见图SPM.7和SPM.8)。{12.4} 17 18 PM2.5是指直径小于2.5微米的颗粒物,是大气气溶胶浓度的计量单位。

本段中的范围是指CMIP5的模式离散度。 22 Summary for Policymakers ? Based on an assessment of the subset of models that most closely reproduce the climatological mean state and 1979 to 2012 trend of the Arctic sea ice extent, a nearly ice-free Arctic Ocean19 in September before mid-century is likely for RCP8.5 (medium confidence) (see Figures SPM.7 and SPM.8). A projection of when the Arctic might become nearly icefree in September in the 21st century cannot be made with confidence for the other scenarios. {11.3, 12.4, 12.5} ? In the Antarctic, a decrease in sea ice extent and volume is projected with low confidence for the end of the 21st century as global mean surface temperature rises. {12.4} ? By the end of the 21st century, the global glacier volume, excluding glaciers on the periphery of Antarctica, is projected to decrease by 15 to 55% for RCP2.6, and by 35 to 85% for RCP8.5 (medium confidence). {13.4, 13.5} ? The area of Northern Hemisphere spring snow cover is projected to decrease by 7% for RCP2.6 and by 25% in RCP8.5 by the end of the 21st century for the model average (medium confidence). {12.4} ? It is virtually certain that near-surface permafrost extent at high northern latitudes will be reduced as global mean surface temperature increases. By the end of the 21st century, the area of permafrost near the surface (upper 3.5 m) is projected to decrease by between 37% (RCP2.6) to 81% (RCP8.5) for the model average (medium confidence). {12.4} SPM E.6 Sea Level Global mean sea level will continue to rise during the 21st century (see Figure SPM.9). Under all RCP scenarios, the rate of sea level rise will very likely exceed that observed during 1971 to 2010 due to increased ocean warming and increased loss of mass from glaciers and ice sheets. {13.3–13.5} ? Confidence in projections of global mean sea level rise has increased since the AR4 because of the improved physical understanding of the components of sea level, the improved agreement of process-based models with observations, and the inclusion of ice-sheet dynamical changes. {13.3–13.5} ? Global mean sea level rise for 2081–2100 relative to 1986–2005 will likely be in the ranges of 0.26 to 0.55 m for RCP2.6, 0.32 to 0.63 m for RCP4.5, 0.33 to 0.63 m for RCP6.0, and 0.45 to 0.82 m for RCP8.5 (medium confidence). For RCP8.5, the rise by the year 2100 is 0.52 to 0.98 m, with a rate during 2081 to 2100 of 8 to 16 mm yr–1 (medium confidence). These ranges are derived from CMIP5 climate projections in combination with process-based models and literature assessment of glacier and ice sheet contributions (see Figure SPM.9, Table SPM.2). {13.5} ? In the RCP projections, thermal expansion accounts for 30 to 55% of 21st century global mean sea level rise, and glaciers for 15 to 35%. The increase in surface melting of the Greenland ice sheet will exceed the increase in snowfall, leading to a positive contribution from changes in surface mass balance to future sea level (high confidence). While surface melting will remain small, an increase in snowfall on the Antarctic ice sheet is expected (medium confidence), resulting in a negative contribution to future sea level from changes in surface mass balance. Changes in outflow from both ice sheets combined will likely make a contribution in the range of 0.03 to 0.20 m by 2081?2100 (medium confidence). {13.3?13.5} ? Based on current understanding, only the collapse of marine-based sectors of the Antarctic ice sheet, if initiated, could cause global mean sea level to rise substantially above the likely range during the 21st century. However, there is medium confidence that this additional contribution would not exceed several tenths of a meter of sea level rise during the 21st century. {13.4, 13.5} 19 Conditions in the Arctic Ocean are referred to as nearly ice-free when the sea ice extent is less than 106 km2 for at least five consecutive years. 23 决策者摘要 ? 根据对最能重现气候平均状态和1979-2012年北极海冰范围变化趋势的各种模式子集的评估,在RCP8.5 情景下,在本世纪中叶前,9月份 可能 出现北冰洋几乎无冰 19 的情况( 中等信度 )(见图SPM.7和 SPM.8)。在其它情景下,无法对21世纪北极9月份何时会出现几乎无冰情况做出具有信度的预 估。{11.3, 12.4, 12.5} ? 随着全球地表平均温度上升,预估南极海冰范围和体积到21世纪末将减少,这具有低信度。{12.4} ? 到21世纪末,在RCP2.6情景下全球冰川体积(不包括南极周边地区的冰川)预估减少15-55%;在RCP8.5 情景下将减少35-85%(中等信度)。{13.4, 13.5} ? 到21世纪末,模式预估的北半球春季积雪范围的平均值在RCP2.6情景下将减少7%,在RCP8.5情景下将减 少25%(中等信度)。{12.4} ? 几乎确定 的是,随着全球平均表面温度的上升,北半球高纬度地区近地表多年冻土范围将减少。到 21世纪末,模式预估的近地表(上层3.5米)多年冻土范围的平均值将减少37%(RCP2.6情景)到81% (RCP8.5情景)(中等信度)。{12.4} SPM E.6 海平面 21世纪全球平均海平面将持续上升。在所有RCP情景下,由于海洋变暖以及 冰川和冰盖冰量损失的加速,海平面上升速率很可能超过1971-2010年间观测 到的速率。{13.3-13.5} ? 随着对影响海平面变化主要过程物理机制理解的深入,以及物理模式与观测数据之间一致性的提高, 同时考虑了冰盖的动力学变化,第四次评估报告以来,对全球平均海平面上升的预估信度得到了提 高。{13.3-13.5} ? 与1986-2005年相比,2081-2100年间全球平均海平面上升区间可能为:0.26-0.55米(RCP2.6情 景),0.32-0.63米(RCP4.5情景),0.33-0.63米(RCP6.0情景),0.45-0.82米(RCP8.5情景)(中 等信度)。在RCP8.5情景下,2100年底全球平均海平面将上升0.52-0.98米,2081-2100年间的上升速度 为每年8-16毫米(中等信度)。这些估计来源于CMIP5模式的气候预估以及对关于冰川和冰盖贡献的相 关文献的分析(见图SPM.9,表SPM.2)。{13.5} ? 在RCP情景预估中,热膨胀的贡献占21世纪全球平均海平面上升的30-55%,冰川融化占15-35%。格陵兰 冰盖表面的融化量将超过降雪的增加量,从而使格陵兰冰盖表面物质平衡的变化对未来海平面的贡献为 正(高信度)。南极冰盖表面融化仍将很少,且预计降雪量将增加(中等信度),这将使南极冰盖表面 物质平衡的变化对未来海平面的贡献为负。到2081-2100年,两个冰盖的总流出量变化可能会导致海平 面上升0.03至0.20米(中等信度)。{13.3-13.5} ? 根据目前的认知,只有当南极冰盖的洋基部分崩溃时,全球平均海平面才会出现高于21世纪可能变化范 围的大幅度上升。然而,具有中等信度的是,在21世纪,这一额外贡献可能造成的海平面上升将不超几 十厘米。{13.4, 13.5} 19 北冰洋海冰面积至少连续五年小于106平方公里的状况称为几乎无冰。 23 Summary for Policymakers 1.0 Global mean sea level rise Mean over 2081–2100 0.8 SPM 0.6 (m) 0.4 RCP4.5 RCP6.0 0.2 0.0 2000 2020 2040 Year 2060 2080 2100 Figure SPM.9 | Projections of global mean sea level rise over the 21st century relative to 1986–2005 from the combination of the CMIP5 ensemble with process-based models, for RCP2.6 and RCP8.5. The assessed likely range is shown as a shaded band. The assessed likely ranges for the mean over the period 2081–2100 for all RCP scenarios are given as coloured vertical bars, with the corresponding median value given as a horizontal line. For further technical details see the Technical Summary Supplementary Material {Table 13.5, Figures 13.10 and 13.11;

Figures TS.21 and TS.22} ? The basis for higher projections of global mean sea level rise in the 21st century has been considered and it has been concluded that there is currently insufficient evidence to evaluate the probability of specific levels above the assessed likely range. Many semi-empirical model projections of global mean sea level rise are higher than process-based model projections (up to about twice as large), but there is no consensus in the scientific community about their reliability and there is thus low confidence in their projections. {13.5} ? Sea level rise will not be uniform. By the end of the 21st century, it is very likely that sea level will rise in more than about 95% of the ocean area. About 70% of the coastlines worldwide are projected to experience sea level change within 20% of the global mean sea level change. {13.1, 13.6} E.7 Carbon and Other Biogeochemical Cycles Climate change will affect carbon cycle processes in a way that will exacerbate the increase of CO2 in the atmosphere (high confidence). Further uptake of carbon by the ocean will increase ocean acidification. {6.4} ? Ocean uptake of anthropogenic CO2 will continue under all four RCPs through to 2100, with higher uptake for higher concentration pathways (very high confidence). The future evolution of the land carbon uptake is less certain. A majority of models projects a continued land carbon uptake under all RCPs, but some models simulate a land carbon loss due to the combined effect of climate change and land use change. {6.4} ? Based on Earth System Models, there is high confidence that the feedback between climate and the carbon cycle is positive in the 21st century;

that is, climate change will partially offset increases in land and ocean carbon sinks caused by rising atmospheric CO2. As a result more of the emitted anthropogenic CO2 will remain in the atmosphere. A positive feedback between climate and the carbon cycle on century to millennial time scales is supported by paleoclimate observations and modelling. {6.2, 6.4} 24 RCP2.6 RCP8.5 决策者摘要 ???????????    ???  SPM  U  :+8 :+8              ? 图SPM.9:RCP2.6和RCP8.5情景下,CMIP5气候模式集合预估的相对于1986-2005年的21世纪全球平均海平面上升。阴影带 表示预估的可能区间。彩色柱表示所有RCP情景下预估的2081-2100年间平均海平面上升的可能区间,横线表示相应的中值。

更多技术细节可参见技术摘要补充材料{表13.5,图13.10和13.11;图TS.21和TS.22} ? 考虑了对21世纪全球平均海平面上升作出更高预估值的可能性,但结论是目前没有足够的证据来评估高 于上述可能区间特定水平的概率。一些半经验模式的预估值高于物理模式(最高可达两倍左右),但科 学界对其可靠性尚未达成共识,因此这些预估为低信度。{13.5} ? 海平面上升不是全球一致的。到21世纪末,很可能全球超过95%的海平面会上升。预计全球约70%的海 岸带会经历不超过全球平均海平面变化区间20%的海平面变化。{13.1, 13.6} E.7 碳和其它生物地球化学循环 气候变化将通过加剧大气中二氧化碳的增长来影响碳循环过程(高信度)。

海洋对碳的进一步吸收将加剧海洋的酸化。{6.4} ? 在所有四个RCP情景下,到2100年海洋都将继续吸收人为二氧化碳排放,越高的浓度路径下吸收量越大 (很高信度)。关于未来陆地碳吸收趋势的确定性较小。大多数的模式预估,在所有RCP情景下将有持 续的陆地碳吸收,但由气候变化和土地利用变化的综合作用,一些模式模拟出了陆地发生碳损失的情 况。{6.4} ? 根据地球系统模式的结果,具有高信度的是,21世纪气候和碳循环之间是正反馈,即气候变化将部分抵 消由于大气二氧化碳浓度上升造成的陆地和海洋碳汇的增加。因此,会有更多人为排放的二氧化碳滞留 在大气中。在世纪到千年时间尺度上,气候和碳循环之间为正反馈的结论也得到了古气候观测和模拟的 支持。{6.2, 6.4} 24 :+8 :+8  Summary for Policymakers Table SPM.3 | Cumulative CO2 emissions for the 2012 to 2100 period compatible with the RCP atmospheric concentrations simulated by the CMIP5 Earth System Models. {6.4, Table 6.12, Figure TS.19} Cumulative CO2 Emissions 2012 to 2100a Scenario Mean RCP2.6 RCP4.5 RCP6.0 RCP8.5 270 780 1060 1685 GtC Range 140 to 410 595 to 1005 840 to 1250 1415 to 1910 GtCO2 Mean 990 2860 3885 6180 Range 510 to 1505 2180 to 3690 3080 to 4585 5185 to 7005 SPM Notes: a 1 Gigatonne of carbon = 1 GtC = 1015 grams of carbon. This corresponds to 3.667 GtCO . 2 ? Earth System Models project a global increase in ocean acidification for all RCP scenarios. The corresponding decrease in surface ocean pH by the end of 21st century is in the range18 of 0.06 to 0.07 for RCP2.6, 0.14 to 0.15 for RCP4.5, 0.20 to 0.21 for RCP6.0, and 0.30 to 0.32 for RCP8.5 (see Figures SPM.7 and SPM.8). {6.4} ? Cumulative CO2 emissions20 for the 2012 to 2100 period compatible with the RCP atmospheric CO2 concentrations, as derived from 15 Earth System Models, range18 from 140 to 410 GtC for RCP2.6, 595 to 1005 GtC for RCP4.5, 840 to 1250 GtC for RCP6.0, and 1415 to 1910 GtC for RCP8.5 (see Table SPM.3). {6.4} ? By 2050, annual CO2 emissions derived from Earth System Models following RCP2.6 are smaller than 1990 emissions (by 14 to 96%). By the end of the 21st century, about half of the models infer emissions slightly above zero, while the other half infer a net removal of CO2 from the atmosphere. {6.4, Figure TS.19} ? The release of CO2 or CH4 to the atmosphere from thawing permafrost carbon stocks over the 21st century is assessed to be in the range of 50 to 250 GtC for RCP8.5 (low confidence). {6.4} E.8 Climate Stabilization, Climate Change Commitment and Irreversibility Cumulative emissions of CO2 largely determine global mean surface warming by the late 21st century and beyond (see Figure SPM.10). Most aspects of climate change will persist for many centuries even if emissions of CO2 are stopped. This represents a substantial multi-century climate change commitment created by past, present and future emissions of CO2. {12.5} ? Cumulative total emissions of CO2 and global mean surface temperature response are approximately linearly related (see Figure SPM.10). Any given level of warming is associated with a range of cumulative CO2 emissions21, and therefore, e.g., higher emissions in earlier decades imply lower emissions later. {12.5} ? Limiting the warming caused by anthropogenic CO2 emissions alone with a probability of >33%, >50%, and >66% to less than 2°C since the period 1861–188022, will require cumulative CO2 emissions from all anthropogenic sources to stay between 0 and about 1570 GtC (5760 GtCO2), 0 and about 1210 GtC (4440 GtCO2), and 0 and about 1000 GtC (3670 GtCO2) since that period, respectively23. These upper amounts are reduced to about 900 GtC (3300 GtCO2), 820 GtC (3010 GtCO2), and 790 GtC (2900 GtCO2), respectively, when accounting for non-CO2 forcings as in RCP2.6. An amount of 515 [445 to 585] GtC (1890 [1630 to 2150] GtCO2), was already emitted by 2011. {12.5} 20 21 22 23 From fossil fuel, cement, industry, and waste sectors. Quantification of this range of CO2 emissions requires taking into account non-CO2 drivers. The first 20-year period available from the models. This is based on the assessment of the transient climate response to cumulative carbon emissions (TCRE, see Section D.2). 25 决策者摘要 表SPM.3: 与CMIP5地球系统模式模拟的RCP情景下大气CO2浓度相对应的2012-2100年间的累积CO2排放量 2012-2100年间累积CO2排放量 情景 平均 RCP2.6 RCP4.5 RCP6.0 RCP8.5 270 780 1060 1685 GtC 区间 140–410 595–1005 840–1250 1415–1910 GtCO2 平均 990 2860 3885 6180 区间 510–1505 2180–3690 3080–4585 5185–7005 SPM 注:

a 1GtC=10亿吨=1015克碳,相当于3.667 GtCO 。

2 ? 地球系统模式预估,在所有RCP情景下全球海洋酸化都将加剧。到21世纪末,表层海洋的pH值相应下 降,其下降区间 18在RCP2.6情景下为0.06 - 0.07、RCP4.5情景下为0.14 - 0.15、RCP6.0情景下为0.20 0.21、RCP8.5情景下为0.30-0.32(见图SPM.7和SPM.8)。{6.4} ? 根据15个地球系统模式的结果,2012-2100年期间与RCP情景下大气CO2浓度相对应的累积CO2排放量20在 RCP2.6下为140至410GtC,在RCP4.5下为595至1005GtC,在RCP6.0下为840至1250GtC,在RCP8.5下为 1415 至1910 GtC(见表SPM.3)。{6.4} ? 根据地球系统模式,在RCP2.6情景下,到2050年前年均CO 2 排放要比1990年水平低(范围在14% 96%)。至21世纪末,大约一半的模式推算排放会略高于零,而另一半模式推算将实现大气中的CO2的净 消除。{6.4,图TS.19} ? 在RCP8.5情景下,21世纪因储存碳的多年冻土融化释放到大气中的CO2或CH4预计为50GtC到250GtC(低信 度)。{6.4} E.8 气候稳定性、气候变化的持续性和不可逆性 21世纪末期及以后的全球平均地表变暖主要取决于累积CO2排放。即使停止CO2 排放,气候变化的许多方面将持续许多世纪。这意味着过去、现在和将来的CO2 排放会产生显著的、长达多个世纪的持续气候变化。{12.5} ? 累积总CO2排放和全球平均表面温度响应为近似线性相关(见图SPM.10)。任一给定的变暖水平都对应 着一定的累积CO2排放范围21,所以,如果早期排放较多,那么后期排放就会较低。{12.5} ? 如果要在概率>33%,>50%和>66%的条件下,将人为CO 2 排放单独引起的变暖限制在2 ° C(相对于 1861至1880年 22 )以内,则需要将1861-1880年以来所有人为CO 2 累积排放量分别限制在0至约1570 GtC(5760GtCO2)、0至约1210 GtC(4440GtCO2)和0至约1000 GtC(3670GtCO2)23。如果按RCP2.6考 虑非CO2强迫,那么这些区间的上限将分别降至约900 GtC(3300GtCO2)、820 GtC(3010GtCO2)和790 GtC(2900GtCO2)。2011年以前已经排放了515[445至585] GtC(1890[1630-2150]GtCO2)。{12.5}} 20 21 22 23 来自化石燃料、水泥、工业和废物处理部门。

对该CO2排放范围的量化要求考虑非CO2驱动因子。

模式中可得到的最早的20年。

基于累积二氧化碳排放瞬变气候响应的评估(TCRE,见D.2部分) 25 Summary for Policymakers ? A lower warming target, or a higher likelihood of remaining below a specific warming target, will require lower cumulative CO2 ? emissions. Accounting for warming effects of increases in non-CO2 greenhouse gases, reductions in aerosols, or the release of greenhouse gases from permafrost will also lower the cumulative CO2 emissions for a specific warming target (see Figure SPM.10). {12.5} SPM ? A large fraction of anthropogenic climate change resulting from CO2 emissions is irreversible on a multi-century to millennial time scale, except in the case of a large net removal of CO2 from the atmosphere over a sustained period. Surface temperatures will remain approximately constant at elevated levels for many centuries after a complete cessation of net anthropogenic CO2 emissions. Due to the long time scales of heat transfer from the ocean surface to depth, ocean warming will continue for centuries. Depending on the scenario, about 15 to 40% of emitted CO2 will remain in the atmosphere longer than 1,000 years. {Box 6.1, 12.4, 12.5} ? It is virtually certain that global mean sea level rise will continue beyond 2100, with sea level rise due to thermal expansion to continue for many centuries. The few available model results that go beyond 2100 indicate global mean sea level rise above the pre-industrial level by 2300 to be less than 1 m for a radiative forcing that corresponds to CO2 concentrations that peak and decline and remain below 500 ppm, as in the scenario RCP2.6. For a radiative forcing that corresponds to a CO2 concentration that is above 700 ppm but below 1500 ppm, as in the scenario RCP8.5, the projected rise is 1 m to more than 3 m (medium confidence). {13.5} 5 Temperature anomaly relative to 1861–1880 (°C) Cumulative total anthropogenic CO2 emissions from 1870 (GtCO2) 1000 2000 3000 4000 5000 6000 7000 8000 2100 4 3 2100 2050 2100 2 2030 2050 2050 2050 2100 2030 1 1950 2010 2000 1980 0 1890 RCP2.6 RCP4.5 RCP6.0 RCP8.5 Historical RCP range 1% yr -1 CO2 1% yr -1 CO2 range 0 500 1000 1500 2000 Cumulative total anthropogenic CO2 emissions from 1870 (GtC) 2500 Figure SPM.10 | Global mean surface temperature increase as a function of cumulative total global CO2 emissions from various lines of evidence. Multimodel results from a hierarchy of climate-carbon cycle models for each RCP until 2100 are shown with coloured lines and decadal means (dots). Some decadal means are labeled for clarity (e.g., 2050 indicating the decade 2040?2049). Model results over the historical period (1860 to 2010) are indicated in black. The coloured plume illustrates the multi-model spread over the four RCP scenarios and fades with the decreasing number of available models in RCP8.5. The multi-model mean and range simulated by CMIP5 models, forced by a CO2 increase of 1% per year (1% yr–1 CO2 simulations), is given by the thin black line and grey area. For a specific amount of cumulative CO2 emissions, the 1% per year CO2 simulations exhibit lower warming than those driven by RCPs, which include additional non-CO2 forcings. Temperature values are given relative to the 1861?1880 base period, emissions relative to 1870. Decadal averages are connected by straight lines. For further technical details see the Technical Summary Supplementary Material. {Figure 12.45;

TS TFE.8, Figure 1} 26 决策者摘要 ? 较低的温升目标,或保持低于特定温升目标的较高可能性,都要求降低CO2的累积排放量。考虑到非CO2 温室气体的增加、气溶胶的减少或多年冻土层温室气体的释放均会产生温升效应,这还将降低达到特定 温升目标的CO2累积排放量(见图SPM.10)。

{12.5} ? 就多世纪至千年时间尺度而言,由CO2排放导致的大部分人为气候变化是不可逆转的,除非在持续时期 内将大气中的CO2大量净移除。在净人为CO2排放完全停止后,表面温度仍会在多个世纪基本维持在较高 水平上。由于从海洋表面到海洋深处的热转移的时间尺度较长,所以海洋变暖将持续若干世纪。在不同 的情景下,排放的CO2中有大约15%到40%将在大气中保持1000年以上。{文框6.1;12.4, 12.5} ? 几乎确定的是,全球平均海平面到2100年之后仍会持续上升,因热膨胀造成的海平面上升会持续数个世 纪。少数现有的模拟2100年后的模式结果表明,如RCP2.6情景,在CO2浓度达到峰值后下降并保持低于 500ppm对应的辐射强迫下,到2300年全球平均海平面相对于工业化前时期的上升会小于1米,但是,如 RCP8.5情景,在对应CO2浓度高于700ppm但低于1500ppm的辐射强迫情况下,预估上升幅度会在1米到3米 以上(中等信度)。{13.5} SPM           ??????+      ????? –         !   !    ! :+8 :+8 :+8 :+8  ?? :+8?? ? +7 ? +7??        ? ???????+7?????/\+?  图SPM.10:以不同证据源的全球CO2累积排放总量为函数计算得出的全球平均表面升温图。各RCP情景下一系列气候-碳循环模 式模拟的到2100年的多模式结果以彩色线条和十年均值(点)表示。为清楚起见,标出了一些十年均值(如2050表示2040-2049 年)。历史时期(1860-2010年)的模式结果以黑色表示。彩色羽状表示四个RCP情景的多模式离散,并随着RCP8.5中可用模式 的减少而渐淡。细黑线和深灰区域是用CMIP5模式模拟的、以每年1%的CO2增量(每年1%的CO2模拟)强迫的多模式平均和范围。

针对一定量的累积CO2排放,每年1%的CO2模拟显示的升温比RCP驱动的升温低,这些RCP中还包括其它非CO2驱动因子。所有给出 的数值均与1861-1880年基准期对比。十年平均值用直线连接。更多技术细节请见技术摘要补充材料。{图12.45;TSTFE.8,图 1} 26 Summary for Policymakers ? Sustained mass loss by ice sheets would cause larger sea level rise, and some part of the mass loss might be irreversible. There is high confidence that sustained warming greater than some threshold would lead to the near-complete loss of the Greenland ice sheet over a millennium or more, causing a global mean sea level rise of up to 7 m. Current estimates indicate that the threshold is greater than about 1°C (low confidence) but less than about 4°C (medium confidence) global mean warming with respect to pre-industrial. Abrupt and irreversible ice loss from a potential instability of marinebased sectors of the Antarctic ice sheet in response to climate forcing is possible, but current evidence and understanding is insufficient to make a quantitative assessment. {5.8, 13.4, 13.5} ? Methods that aim to deliberately alter the climate system to counter climate change, termed geoengineering, have been proposed. Limited evidence precludes a comprehensive quantitative assessment of both Solar Radiation Management (SRM) and Carbon D ioxide Removal (CDR) and their impact on the climate system. CDR methods have biogeochemical and technological limitations to their potential on a global scale. There is insufficient knowledge to quantify how much CO2 emissions could be partially offset by CDR on a century timescale. Modelling indicates that SRM methods, if realizable, have the potential to substantially offset a global temperature rise, but they would also modify the global water cycle, and would not reduce ocean acidification. If SRM were terminated for any reason, there is high confidence that global surface temperatures would rise very rapidly to values consistent with the greenhouse gas forcing. CDR and SRM methods carry side effects and long-term consequences on a global scale. {6.5, 7.7} SPM Box SPM.1: Representative Concentration Pathways (RCPs) Climate change projections in IPCC Working Group I require information about future emissions or concentrations of greenhouse gases, aerosols and other climate drivers. This information is often expressed as a scenario of human activities, which are not assessed in this report. Scenarios used in Working Group I have focused on anthropogenic emissions and do not include changes in natural drivers such as solar or volcanic forcing or natural emissions, for example, of CH4 and N2O. For the Fifth Assessment Report of IPCC, the scientific community has defined a set of four new scenarios, denoted Representative Concentration Pathways (RCPs, see Glossary). They are identified by their approximate total radiative forcing in year 2100 relative to 1750: 2.6 W m-2 for RCP2.6, 4.5 W m-2 for RCP4.5, 6.0 W m-2 for RCP6.0, and 8.5 W m-2 for RCP8.5. For the Coupled Model Intercomparison Project Phase 5 (CMIP5) results, these values should be understood as indicative only, as the climate forcing resulting from all drivers varies between models due to specific model characteristics and treatment of short-lived climate forcers. These four RCPs include one mitigation scenario leading to a very low forcing level (RCP2.6), two stabilization scenarios (RCP4.5 and RCP6), and one scenario with very high greenhouse gas emissions (RCP8.5). The RCPs can thus represent a range of 21st century climate policies, as compared with the no-climate policy of the Special Report on Emissions Scenarios (SRES) used in the Third Assessment Report and the Fourth Assessment Report. For RCP6.0 and RCP8.5, radiative forcing does not peak by year 2100;

for RCP2.6 it peaks and declines;

and for RCP4.5 it stabilizes by 2100. Each RCP provides spatially resolved data sets of land use change and sector-based emissions of air pollutants, and it specifies annual greenhouse gas concentrations and anthropogenic emissions up to 2100. RCPs are based on a combination of integrated assessment models, simple climate models, atmospheric chemistry and global carbon cycle models. While the RCPs span a wide range of total forcing values, they do not cover the full range of emissions in the literature, particularly for aerosols. Most of the CMIP5 and Earth System Model simulations were performed with prescribed CO2 concentrations reaching 421 ppm (RCP2.6), 538 ppm (RCP4.5), 670 ppm (RCP6.0), and 936 ppm (RCP 8.5) by the year 2100. Including also the prescribed concentrations of CH4 and N2O, the combined CO2-equivalent concentrations are 475 ppm (RCP2.6), 630 ppm (RCP4.5), 800 ppm (RCP6.0), and 1313 ppm (RCP8.5). For RCP8.5, additional CMIP5 Earth System Model simulations are performed with prescribed CO2 emissions as provided by the integrated assessment models. For all RCPs, additional calculations were made with updated atmospheric chemistry data and models (including the Atmospheric Chemistry and Climate component of CMIP5) using the RCP prescribed emissions of the chemically reactive gases (CH4, N2O, HFCs, NOx, CO, NMVOC). These simulations enable investigation of uncertainties related to carbon cycle feedbacks and atmospheric chemistry. 27 决策者摘要 ? 持续的冰盖冰量损失可造成海平面更大的升幅,有些冰量损失是不可逆的。具有高信度的是,高于某 一阈值的持续变暖会导致一千多年或更长时间后格陵兰冰盖几乎完全消失,其导致的全球平均海平面 上升幅度可高达7米。目前的估算表明,该阈值为比工业化前增温1°C以上(低信度)4°C以下(中等信 度)。不能排除气候强迫造成南极冰盖的海洋部分由于潜在的不稳定性而出现突然的、不可逆的冰量损 失的可能性,但现在的证据和认识不足以做出量化的评估。{5.8,13.4,13.5} ? 已经提出称之为地球工程的方法,旨在有意改变气候系统以抵消气候变化。有限的证据无法对太阳辐 射管理(SRM)和二氧化碳清除(CDR)以及其对气候系统的影响进行全面定量评估。CDR方法在全球应 用的潜力尚存在生物地球化学和技术方面的局限。由于知识不足,目前还无法计算出在世纪尺度上通 过CDR能够减少多少CO2排放量。模拟表明,SRM方法如果可以实现的话,有可能会显著抵消全球温度上 升,但同时也会改变全球水循环,而且无法抵消海洋酸化。不管SRM以何种原因终止,具有高信度 的 是,全球表面温度会极快地上升,升幅与温室气体强迫相一致。SRM和CDR会在全球尺度带来副作用和长 期后果。{6.5,7.7} SPM 文框SPM.1:典型浓度路径(RCPs) IPCC第一工作组(WGI)的气候变化预估需要关于未来温室气体排放或浓度、气溶胶以及其它气候 驱动因子的信息。此类信息通常表述为人类活动的一个情景,在本报告未对此加以评估。WGI使用 的情景关注的是人为排放,并未包括自然驱动因子(如太阳、火山强迫、甲烷和氧化亚氮等的自然 排放)的变化。

对于IPCC第五次评估报告,科学界已定义了一套新的四个情景,称之为典型浓度路径(RCPs,见词 汇表)。这些情景是用相对于1750年的2100年的近似总辐射强迫来表示的,在RCP 2.6情景下为2.6 Wm-2,在RCP 4.5情景下为4.5 Wm-2,在RCP 6.0情景下为6.0Wm-2,在RCP 8.5情景下的8.5 Wm-2。在 耦合模式比较计划第五阶段(CMIP5)中,由于每个模式的特点和对短寿命气候强迫因子的处理方 法不同,源自所有驱动因子的气候强迫在各模式之间是不同的,所以这些值应当被理解为仅是表征 性的。这4个情景中,一个为极低强迫水平的减缓情景(RCP2.6),两个为中等稳定化情景(RCP4.5 和RCP6.0),一个为温室气体排放非常高的情景(RCP8.5)。与第3次和第4次评估报告中所用的 排放情景特别报告(SRES)中的非气候政策相比, RCPs可以代表一系列21世纪的气候政策。对于 RCP6.0和RCP8.5情景,到2100年辐射强迫还没有达到峰值;对RCP2.6情景,辐射强迫先达到峰值, 然后下降;对RCP4.5情景,辐射强迫在2100年前达到了稳定。每个RCP都提供全面的高空间分辨率 资料集,涉及土地利用变化、基于行业的空气污染物排放量、到2100年的人为排放量和温室气体浓 度。RCPs是基于综合评估模式、简单气候模式、大气化学和全球碳循环模式的结合。虽然RCP情景 涵盖的总强迫值范围很广,但并未涵盖文献中的所有排放范围,特别是气溶胶排放。

大 多 数 C M I P 5 和 地 球 系 统 模 式 模 拟 都 按 规 定 的 C O 2浓 度 运 行 , 即 , 到 2 1 0 0 年 大 约 为 4 2 1 p p m (RCP2.6)、538ppm(RCP4.5)、670ppm(RCP6.0)和936ppm(RCP8.5)。在计入预先规定 的CH 4和N 2O浓度后,综合CO 2当量浓度为475ppm(RCP2.6)、630ppm(RCP4.5)、800ppm(RCP6.0)和 1313ppm(RCP8.5)。对RCP8.5,额外的CMIP5地球系统模式模拟按规定的CO2排放(由综合评估模式 提供)运行。在所有的RCP情景下,都使用更新的大气化学资料和模式(包括大气化学和CMIP5的气 候组分)及RCP情景规定的化学反应气体(CH4、N2O、HFCs、NOx、CO、NMVOC)的排放进行额外计算。

这些模拟可用于分析研究碳循环反馈和大气化学的不确定性。 27

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