温度影响气温和降水的因素变化因素
点击联系发帖人
时间：2016-11-02 15:02
为什么今年秋台风来的这么频繁？今年冬季还可能偏冷？我们用数字告诉你，拉尼娜到底给我国造成了哪些影响。又到你妈喊你穿秋裤的时候，数据帝趁机祭出秋裤预警地图，替各位妈妈做个友情提醒。秋天到了，树叶开始变色，或红或黄，层林尽染。叶子为什么会变色？此时哪里最适合赏秋叶？
引起气候变化的原因
我们赖以生存的地球是一个极其复杂的系统，地球气候系统是构成这个地球系统的重要一环。在漫长的地球历史中，气候始终处在不断地变化之中。究其原因，概括起来可分成自然的气候波动与人类活动的影响两大类。前者包括太阳辐射的变化、火山爆发等。后者包括人类燃烧矿物燃料以及毁林引起的大气中温室气体浓度的增加、硫化物气溶胶浓度的变化、陆面覆盖和土地利用的变化等。
气候系统所有的能量基本上都来自太阳，因此太阳辐射的变化被认为是引起气候系统变化的一个外因。20世纪70年代末，卫星观测的应用使得人类可以在大气层以外准确地测量太阳辐射输出的变化，这才知道太阳辐射量并不是完全不变的，特别在太阳黑子异常活动的周期中存在着一定的差异。许多科学家认为太阳黑子数多时地球偏暖，低时地球偏冷。但太阳辐射的变化影响气候的机理尚不清楚，也缺乏严格的理论或者观测事实支持。不过通过研究，科学家们还是发现，太阳辐射的变化、地球轨道的变化都不是引起近代全球变暖的主要原因，同时基本排除了影响气候变化的另一个自然因素——火山爆发是引起近百年全球变暖主要原因的可能性。
科学家们认为，在气候系统的自然变化中，最重要的方面是大气与海洋环流的变化或者脉动。这种环流变化是造成区域尺度气候要素变化的主要原因大气与海洋环流的变化有时可伴随着陆面的变化。在年际时间尺度上，厄尔尼诺和南方涛动（ENSO）和NAO是大气与海洋环流变化的重要例子，它们的变化影响着大范围甚至半球或全球尺度的天气与气候变化，是目前制作季、年际气候预测的基础与依据。长期以来世界上许多气象学家一直致力于这方面的研究，旨在提高全球与区域的气候预测水平。对于更长的十年时间尺度，太平洋十年尺度振荡（PDO）和相关的年代际太平洋振荡（IPO）可以用来解释地面气温全球平均变化的一半左右，它们与明显地与地区性的温度和降水变化有联系。
关于人类活动对气候变化的影响，有越来越多的研究表明，近百年人类活动加剧了气候系统变化的进程。最新发表的权威报告——联合国政府间气候变化专门委员会（IPCC）第四次评估报告第一工作组报告的决策者摘要指出，人类活动与近50年气候变化的关联性达到90%。
对人类活动增加大气中温室气体的浓度可能导致气候变化的研究，可以追溯到19世纪末。1896年，瑞典科学家斯万特．阿尔赫许多科学家陆续对此问题进行了一些研究。1957年，瑞威拉等在美国发表了一篇关于增加大气中温室气体浓度可能产生气候变化的论文。同年，美国夏威夷观象台开始进行浓度观测，从而正式揭开人类研究气候变化的序幕。
排放温室气体的人类活动有哪些？可产生哪些温室气体呢？这些温室气体又是怎样影响了气候变化呢？
排放温室气体的人类活动包括：所有的化石能源燃烧活动排放二氧化碳。在化石能源中，煤含碳量最高，石油次之，天然气较低；化石能源开采过程中的煤炭瓦斯、天然气泄漏排放二氧化碳和甲烷；水泥、石灰、化工等工业生产过程排放二氧化碳；水稻田、牛羊等反刍动物消化过程排放甲烷；土地利用变化减少对的吸收；废弃物排放甲烷和氧化亚氮。
上述那些人类活动所产生的温室气体主要有6种：除了二氧化碳外，目前发现的人类活动排放的温室气体还有甲烷、氧化亚氮、氢氟碳化物、全氟化碳、六氟化硫。对气候变化影响最大的是二氧化碳，二氧化碳的生命期很长，一旦排放到大气中，最长可生存200年时间，因而最受关注。
这些温室气体主要是通过温室效应来影响气候变化的。何为温室效应？大气中的二氧化碳等气体，可以透过太阳短波辐射（指吸收少），使地球表面升温；但阻挡地球表面向宇宙空间发射长波辐射（指吸收多），从而使大气增温。由于二氧化碳等气体的这一作用与“温室”的作用类似，故称之为“温室效应”。
工业化革命以前，大气中的二氧化碳等气体造成的“温室效应”使得地球表面平均温度由-18℃上升到当今自然生态系统和人类已适应的15℃。一旦大气中的温室气体浓度继续增加，进一步阻挡了地球向宇宙空间发射的长波辐射，为维持辐射平衡，地面必将增温，以增大长波辐射量。地面温度增加后，水汽将增加（增加大气对地面长波辐射的吸收），冰雪将融化（减少地面对太阳短波的反射），又使地表进一步增温，即形成正反馈使全球变暖更显著。
微信关注我们，阴晴冷暖尽在掌握
转载请注明“来源：中国天气网”
Copyright& All Rights Reserved () 版权所有 复制必究 郑重声明：中国天气网版权所有，未经书面授权禁止使用年秦岭—淮河南北极端降水时空变化特征及其影响因素
李双双, 杨赛霓, 刘宪锋. .年秦岭—淮河南北极端降水时空变化特征及其影响因素[J]. 地理科学进展, ,34(3): 354-363
LI Shuangshuang, YANG Saini, LIU Xianfeng. .Spatiotemporal variability of extreme precipitation in north and south of the Qinling-Huaihe region and influencing factors during [J]. Progress In Geography,,34(3): 354-363&&
Permissions
年秦岭—淮河南北极端降水时空变化特征及其影响因素
李双双1,2,
杨赛霓1,2,
1. 北京师范大学地表过程与资源生态国家重点实验室,北京 100875
2. 北京师范大学减灾与应急管理研究院,北京 100875
3. 北京师范大学资源学院,北京 100875
通讯作者：杨赛霓(1975-),女,江苏武进人,副教授,主要研究方向为交通应急与风险管理,E-mail: 。
作者简介：李双双(1988-),男,陕西潼关人,博士生,主要研究方向为全球变化与区域灾害防治,E-mail: 。
基金: 地表过程模型与模拟创新研究群体科学基金项目(); 国家重点基础研究发展计划项目()
基于秦岭—淮河南北气象站点逐日降水数据和全国0.5°×0.5°逐月降水格网数据,选取16个极端降水指数,辅以趋势分析、Mann-Kendall检验和相关分析等气候诊断方法,分析了年秦岭—淮河南北极端降水时空变化特征,探讨了极端降水变化与ENSO事件的关系。结果表明：①年秦岭—淮河南北除长江下游降水呈增加趋势外,其他区域降水均呈下降趋势;②极端降水变化主要表现为：降水日数减少,降水强度上升,突发性强降水事件增多,连续性干旱事件增多;在空间上,秦巴山地、长江下游和黄河下游以极端降水强度上升为主,关中平原、巫山山区和四川盆地以极端干旱强度上升为主;③在影响因素方面,秦岭—淮河南北极端降水与ENSO事件关系密切。在厄尔尼诺年,秦岭—淮河南北春季极端降水偏多,夏季和全年偏少;在拉尼娜年,春季极端降水偏少,秋季和全年偏多。就各个区域而言,在厄尔尼诺年,黄河下游、关中平原、秦巴山地和四川盆地极端降水呈下降趋势,淮河平原极端降水呈上升趋势,长江下游和巫山山区响应并不明显。
秦岭—淮河南北
doi: 10.11820/dlkxjz.
Spatiotemporal variability of extreme precipitation in north and south of the Qinling-Huaihe region and influencing factors during
LI Shuangshuang1,2,
YANG Saini1,2,
LIU Xianfeng1,3
1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
2. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China
3. College of Resource Sciences and Technology, Beijing Normal University, Beijing 100875, China
Based on the monthly precipitation of a 0.5°×0.5° grid dataset and the daily precipitation observations of 135 meteorological stations released by the National Meteorological Information Center of China, this study analyzed the spatiotemporal variation of extreme precipitation in north and south of the Qinling-Huaihe region during , using the methods of trend analysis, Sen+Mann-Kendall model, and correlation analysis. More specifically, we analyzed the relationship between ENSO and the observed extreme precipitation. The results are as follows: (1) the precipitation showed an increasing trend in the lower reach of the Yangtze River and a decreasing tendency
(2) extreme precipitation analysis indicates a declining trend in rainy days and an increasing trend in precipitation intensity. The number of continuous drought events increased. Spatially, the regions with increasing intensity of extreme precipitation were mainly distributed in the Qinling-Bashan Mountains and the lower reaches of the Yangtze River and Yellow River, whereas there were more drought events in the Guanzhong Plain, Wushan Mountains, and Sichuan B (3) Extreme precipitation had a close relationship with ENSO in the study region. In El Niño years, more precipitation was found in the spring but there was less precipitation in the summer and the whole year. In La Niña years, there was less precipitation in the spring and more precipitation in the autumn and the whole year. The responses of extreme precipitation events to El Niño exhibited spatial differences. Most of the regions with decreasing extreme precipitation in El Niño years were distributed in the lower reach of the Yellow River, the Guanzhong Plain and Qinling-Bashan Mountains, as well as the Sichuan Basin, while the region with increasing extreme precipitation was the Huaihe Plain. The lower reach of the Yangtze River and the Wushan Mountains showed no clear response to ENSO.
climate change;
extreme precipitation;
spatiotemporal change;
north and south of the Qinling -Huaihe region
1 引言IPCC第五次评估报告指出, 气候系统变暖依然是毋容置疑的事实。年全球平均地表温度升温速率为0.12℃/10 a, 年为工业革命以来最暖的30年(; )。在气候变暖背景下, 全球多数区域极端降水呈现增加趋势, 但并未像极端气温具有全球一致性(), 美国、南非和加勒比等区域研究亦发现上述规律(; ; )。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)” 指出, 全球气候变化可能导致强降水等极端天气事件增加, 但是由于现阶段科学研究对此缺乏统一认识, 其结论可信度为中等()。近年来, 中国学者针对不同流域(; ; ; )、不同省域(; ; ; )以及不同自然区域(; ; )的极端降水事件进行了探索性研究, 提高了对中国极端降水变化的认识。在已有研究中, 针对秦岭— 淮河南北为整体的研究相对较少, 缺乏不同区域之间的综合对比研究, 多数研究关注点为区域内部关键流域或典型城市; 研究要素以气温、降水和径流等常规水文气象要素为主, 对极端降水事件关注相对较少(; ; ; ; ; )。秦岭— 淮河南北位于中国东部季风区, 是中国重要的地理生态分界线, 生态环境脆弱, 是气候变化的敏感区, 也是南水北调中线水源区和中国最大连片贫困区, 区域环境和发展对中国当代和未来环境和发展具有重要的意义()。在极端降水变化原因上, ENSO事件年际变化是引起中国降水异常的重要驱动因子。在厄尔尼诺发生次年夏季, 菲律宾附近对流活跃, 西北太平洋副热带高压偏北偏强, 长江流域和江南北部降水偏多, 江淮流域降水偏少(; )。但是, 东亚夏季风和ENSO之间的关系存在不稳定性, 这种不稳定性也是造成中国气候的季节— 年际预测困难的主要因素之一()。因此, 在区域尺度有针对性评估秦岭— 淮河南北极端降水事件变化趋势, 验证ENSO事件与极端降水事件的关系, 对科学适应和应对气候变化具有重要的现实意义。基于此, 本文在前期研究基础上, 利用全国0.5° × 0.5° 逐月降水格网数据和秦岭— 淮河南北135个气象站点逐日实测数据, 选取16个极端降水指数, 辅以趋势分析、Mann-Kendall检验及相关分析等气候诊断方法, 对近54年秦岭— 淮河南北极端降水变化时空变化特征进行分析, 探讨ENSO事件与极端降水变化的关系, 以期为区域重大工程建设及政府应对极端气候变化决策提供参考。2 研究区概况秦岭— 淮河南北作为中国东部南北地理生态分界线, 范围介于103.0° ~116.5° E、23.5° ~35.8° N。以秦岭— 淮河为界, 北部为暖温带, 南部为北亚热带, 位置与1月0 ℃等温线、800 mm等降水量线和2000 h日照时数等值线一致; 为了比较不同地理单元极端降水变化特征, 中国气候区划方案为依据, 将秦岭— 淮河以北地区分为两个子区域：关中平原(Ⅰ )和黄河下游(Ⅱ ); 秦岭— 淮河以南地区分为5个子区域：秦巴山地(Ⅲ )、淮河平原(Ⅳ )、四川盆地(Ⅴ )、巫山山区(Ⅵ )和长江下游(Ⅶ ), 空间分布如所示。图1Fig.1 图1 研究区气候区划及气象站点分布图Fig.1 Climate regionalization and distribution of meteorological stations in the study area3 数据来源与研究方法本文逐日降水站点数据和逐月降水格网数据均来源于中国气象科学数据共享服务网(http://www.cdc.), 以站点数据分析极端降水变化趋势特征, 以格网数据分析极端降水与ENSO事件的响应关系。其中, 中国地面降水月值0.5° × 0.5° 格点数据集(V2.0)由国家气象信息中心气象资料实验室建立, 该数据集基于中国2474个国家级地面气象站月降水量观测数据, 并利用ANUSPLIN软件的薄盘样条法和0.5° × 0.5° 的数字高程模型插值, 尽可能消除高程因素对降水空间分布的影响。厄尔尼诺指数(ONI)来源于美国国家航空航天局(http://www.swpc.noaa.gov), 并参照国家气候中心ENSO事件特征量综合表对厄尔尼诺和拉尼娜峰值年进行界定; 季节划分采用气象学标准：春季为3-5月, 夏季6-8月, 秋季9-11月, 冬季为12月-次年2月。极端降水指数定义是基于世界气象组织(WMO)气候委员会(CCI)、全球气候研究计划(WCRP)气候变化和可预测性计划(CLIVAR)气候变化检测、监测和指标专家组(ETCCDMI)确定的“ 气候变化检测和指标(Expert Team on Climate Change Detection and Indices)” , 该方法已被广泛应用于极端气候事件研究中。本文定义16个极端降水指标, 包括四大类：相对指数、绝对指数、强度指数和持续性指数()。表1Tab.1表1(Tab.1)
表1 16个极端降水指数定义
Tab.1 Definition of the 16 extreme precipitation indices指标类型极端降水指数英文缩写定义绝对指标雨日日数RD年内日降水日数/d痕雨日数Rr1年内日降水量≥ 1 mm日数/d小雨日数Rr5年内日降水量≥ 5 mm日数/d中雨日数Rr10年内日降水量≥ 10 mm日数/d大雨日数Rr25年内日降水量≥ 25 mm日数/d强度指标1日最大降水量Rx1day月内1日降水量最大值/mm5日最大降水量Rx5day月内连续5日降水量最大值/mm年降水强度SDII年内降水量与日降水量≥ 1 mm 日数之比/(mm/d)相对指标异常降水日数R95年内日降水量高于95%阈值日数之和/d极端降水日数R99年内日降水量高于99%阈值日数之和/d异常降水总量R95P年内日降水量高于95%阈值降水量之和/mm极端降水总量R99P年内日降水量高于99%阈值降水量之和/mm持续性指标连续无雨日数CDD年内日降水量连续< 1 mm日数最大值/d连续降水日数CWD年内日降水量连续≥ 1 mm日数最大值/d年降水量PRCPTOT年内日降水量≥ 1 mm降水量之和/mm生长季降水量GPRCP年内4-9月(生长季)降水量之和/mm
表1 16个极端降水指数定义
Tab.1 Definition of the 16 extreme precipitation indices由于线性回归要求时间序列符合正态分布, 且易受异常值干扰, Sen趋势度逐渐被引入气候趋势变化分析()。Sen+Mann-Kendall趋势度通过计算气候要素序列中值进行趋势分析, 并结合Mann-Kendall方法对趋势变化进行显著性检验, 可以在一定程度上提高气候变化趋势判断的准确性。Sen趋势度计算公式为： β=meanxj-xij-i, ?j> i式中：
β为极端降水序列的Sen趋势度, xi, xj为极端降水序列, i、j分别为极端降水序列年份。若
β值为正, 表示极端降水指数呈增加趋势;
β值为负, 则表示极端降水指数呈下降趋势。4 结果分析4.1 秦岭— 淮河南北降水变化背景年, 秦岭— 淮河南北降水空间格局呈现出“ 南多北少、东多西少” 特征, 秦岭— 淮河以南年降水量分别为：秦巴山地(819.1 mm)< 淮河平原(934.0 mm)< 四川盆地(1068.0 mm)< 长江下游(1237.5 mm)< 巫山山区(1319.6 mm); 秦岭— 淮河以北年降水量分别为：关中平原(602.1 mm)< 黄河下游(693.7 mm); 在长期变化趋势上, 长江下游地区降水呈增加的趋势, 上升速率为15.7 mm/10 a, 秦巴山地(-5.8 mm/10 a)、淮河平原(-8.0 mm/10 a)、关中平原(-16.0 mm/10 a)、黄河下游(-6.1 mm/10 a)、巫山山区(-28.1 mm/10 a)、四川盆地(-15.3 mm/10 a)降水均呈下降趋势()。从降水年代变化特征看, 20世纪70年代末, 由于东亚夏季风偏弱, 中国东部雨型由“ 北涝南旱” 转为“ 南涝北旱” , 黄河下游持续干旱和长江下游频发洪水均与此气候变化背景有关; 2000年后东部雨带有北移趋势, 黄河下游和淮河平原降水相对于前期呈增加趋势, 长江下游降水则持续偏低()。图2Fig.2 图2 年秦岭— 淮河南北降水变化特征 (图中蓝色阴影为降水偏多期, 红色阴影为降水偏少期, 降水距平时段为年)Fig.2 Variation of precipitation in north and south of the Qinling-Huaihe region,
(The blue shaded area shows positive p the red shaded area shows negative p the baseline period of precipitation is )4.2 秦岭— 淮河南北极端降水时空变化特征(1) 持续性指标。年, 秦岭— 淮河南北53.0%站点连续无雨日数(CDD)呈上升趋势, 整体上升速率为0.5 d/10 a, 远高于黄淮海流域变化速率0.05 d/10 a ()。在空间上, 秦巴山地所有站点均呈上升趋势, 黄河下游和四川盆地呈上升趋势站点比例分别为66.7%和50.0%, 长江下游(85.7%)、关中平原(66.7%)和巫山山区(60.0%)CDD呈下降趋势站点比重均超过50.0%; 81.0%站点连续降水日数(CWD)呈下降趋势, 整体下降速率为0.2 d/10 a, 高于黄淮海流域0.1 d/10 a(), 但低于中国南方地区0.5 d/10 a的下降速率()。空间上, 除长江下游、黄河下游和淮河平原部分站点呈上升趋势外, 其他各区均呈下降趋势; 59.0%站点生长季降水(GPRCP)呈下降趋势(-7.8 mm/10 a), 其中巫山山区所有站点均呈下降趋势, 长江下游(75.0%)和秦巴山地(53.8%)GPRCP呈现上升趋势。可以看出, 秦岭— 淮河南北持续性降水日数在下降, 持续性干旱日数在增加, 生长季降水以下降趋势为主, 区域面临干旱风险逐渐增大(, )。(2) 强度指数。在1日最大降水量(Rx1day)变化趋势上, 秦岭— 淮河南北有67.0%站点呈上升趋势, 整体上升速率为0.6 mm/10 a, 与黄淮海流域-0.6 mm/10 a下降趋势形成鲜明对比(), 而且上升区集中于长江下游、秦巴山地和四川盆地; 连续5日最大降水量(Rx5day)有54.0%站点呈上升趋势, 整体上升速率为0.2 mm/10 a, 低于南方地区1.7 mm/10 a上升速率(), 高于黄淮海流域1.9 mm/10 a的下降趋势()。就降水强度(SDII)而言, 秦岭— 淮河南北有74.0%站点呈上升趋势, 长江下游和秦巴山地降水强度增加趋势尤为明显, 上升趋势站点比重分别为92.9%和92.3%(, )。(3) 绝对指数。年, 秦岭— 淮河南北除大雨日数(Rr25)无明显变化趋势外, 绝对指数整体呈下降趋势, 下降速率分别为：Rr10(-0.3 d/10 a)< Rr5(-0.7 d/10 a)< Rr1(-1.4 d/10 a)< RD(-8.0 d/10 a), 雨日(RD)、痕雨日数(Rr1)和小雨日数(Rr5)变化趋势通过0.05显著水平检验。在空间上, 相对于东部平原区降水日数呈零散上升趋势, 西部山地区则整体呈现下降趋势, 其中关中平原、巫山山区和四川盆地所有站点均呈下降趋势(, )。(4) 相对指数。在异常降水日数(R95)变化趋势上, 秦岭— 淮河南北有59.0%站点呈下降趋势, 下降速率为0.3 d/10 极端降水日数(R99)则有63.0%站点呈上升趋势, 但其变化趋势并不显著; 异常降水总量(R95P)有45.0%的站点呈下降趋势, 下降速率为-4.3 mm/10 a, 极端降水总量(R99P)有72.0%站点呈上升趋势, 上升速率为2.2 mm/10 a。在空间上, 极端降水上升区主要集中于长江下游和秦巴山地, 极端降水下降区主要集中于关中平原和巫山山区(, )。图3Fig.3 图3 秦岭— 淮河南北极端降水变化时空分布特征 (为了统一图中颜色指示意义, 将连续无雨日数(CDD)变化趋势取反向, 图中红色渲染表示极端降水指标呈下降趋势, 区域趋于干旱; 绿色渲染表示极端指标呈上升趋势, 区域趋于湿润)Fig.3 Spatiotemporal variation of extreme precipitation in north and south of the Qinling-Huaihe region (In order to use a consistent color scheme, the trend of CDD was multiplied by -1; red color indicates a decreeing trend of extreme precip green color indicates a increasing trend of extreme precipitation index values)表2Tab.2表2(Tab.2)
表2 年秦岭— 淮河南北极端降水变化趋势及其站点比重
Tab.2 Trend of extreme precipitation and proportion of stations that showed the same trend in north and south of the Qingling-Huaihe region, 极端降水指标变化趋势站点比重/%极端降水指标变化趋势站点比重/%相对指标R99P2.2 mm/10 a72.0↑ 强度指标SDII0.1 mm/d74.0↑ R95P-4.3 mm/10 a45.0↓ Rx5day0.2 mm/10 a54.0↑ R990.0 d/10 a63.0↑ Rx1day0.6 mm/10 a67.0↑ R95-0.3 d/10 a59.0↓ 绝对指标Rr250.0 d/10 a57.0↑ 持续性指标PRCPTOT-7.7 mm/10 a64.0↓ Rr10-0.3 d/10 a70.0↓ GPRCP-7.8 d/10 a59.0↓ Rr5-0.7 d/10 a* 80.0↓ CWD-0.2 d/10 a* 81.0↓ Rr1-1.4 d/10 a* * 88.0↓ CDD0.5 d/10 a53.0↑ RD-8.0 d/10 a* * 100.0↓ 注：* 、* * 分别为通过0.10、0.05的显著性水平检验, 下同; ↑ 表示增加, ↓ 表示降低。
表2 年秦岭— 淮河南北极端降水变化趋势及其站点比重
Tab.2 Trend of extreme precipitation and proportion of stations that showed the same trend in north and south of the Qingling-Huaihe region, 4.3 ENSO事件对秦岭— 淮河南北极端降水变化的影响为年秦岭— 淮河南北各区极端降水指标与ENSO相关性分析。从表中可以看出, ①秦岭— 淮河南北7个分区140个极端指标中, 有100个指标与厄尔尼诺指数(ONI)呈负相关, 40个指标呈正相关, 极端降水指标以负相关为主。当发生厄尔尼诺事件时, 秦岭— 淮河南北降水普遍偏少, 降水强度和持续时间呈下降趋势, 拉尼娜事件与之相反; ②不同区域极端降水指标对ENSO事件响应具有差异, 关中平原和秦巴山区相关性显著性高于其他区域。③不同极端降水指标对ENSO的响应存在一致性, 除绝对指标正负相关区大致相当外, 相对指标、强度指标、持续性指标和季节指标均以负相关为主; ④结合显著性检验结果, 就各个区域而言, 当发生厄尔尼诺时, 黄河下游、关中平原、秦巴山地和四川盆地分别有17、19、19、18项极端降水指标呈下降趋势, 淮河平原有16项极端降水指标呈上升趋势, 而长江下游和巫山山区极端降水响应并无明显差异。表3Tab.3表3(Tab.3)
表3 年秦岭— 淮河南北极端降水与ENSO相关性分析
Tab.3 Correlation coefficients between extreme precipitation indices and ENSO in north and south of the Qingling-Huaihe region, 类别指标黄河下游淮河平原长江下游关中平原秦巴山地巫山山区四川盆地正相关区负相关区绝对指标RD-0.020.060.09-0.10-0.150.11-0.0834Rr1-0.060.020.06-0.29* * -0.27* * -0.01-0.27* * 25Rr5-0.090.000.08-0.25* -0.180.01-0.24* 34Rr10-0.160.020.09-0.31* * -0.210.05-0.1334Rr25-0.200.06-0.06-0.36* * -0.28* * -0.06-0.1516强度指标Rx1day-0.31* * 0.14-0.12-0.08-0.070.05-0.0625Rx5day-0.30* * 0.16-0.04-0.23* -0.200.03-0.1025SDII-0.26* 0.09-0.05-0.18-0.18-0.020.0016相对指标R75-0.140.00-0.02-0.35* * -0.20-0.04-0.1907R95-0.200.13-0.16-0.27* * -0.28* * -0.03-0.1416R95P-0.220.06-0.06-0.37* * -0.23* -0.03-0.1916R99P-0.28* * 0.14-0.17-0.24* -0.23* 0.02-0.1225持续指标CDD0.02-0.030.07-0.06-0.06-0.100.0934CWD0.03-0.030.13-0.21-0.30* * -0.09-0.29* * 25年降水-0.220.03-0.07-0.26* -0.200.00-0.24* 16GPRCP-0.220.06-0.02-0.34* * -0.24* 0.01-0.2125季节指标春季0.140.170.170.05-0.120.050.0161夏季-0.190.110.00-0.12-0.04-0.04-0.1716秋季-0.13-0.23* -0.16-0.31* * -0.23* -0.22-0.1707冬季-0.140.010.03-0.27* * 0.150.12-0.0943正相关指标数3168119240-负相关指标数1741219191118-100
表3 年秦岭— 淮河南北极端降水与ENSO相关性分析
Tab.3 Correlation coefficients between extreme precipitation indices and ENSO in north and south of the Qingling-Huaihe region, 相关分析主要表达ENSO与降水线性关系, 往往会低估其非线性信息, 利用合成分析进一步揭示秦岭— 淮河南北降水对ENSO变化的响应特征。由于极端降水指标相对较多, 受文章篇幅限制, 无法逐一展示各个极端指标与ENSO年代变化。通过构建极端指数相关矩阵, 发现年降水量具有很好的代表性, 除连续无雨日数(CDD)、秋季、冬季降水相关性较低外, 年降水变化与其他极端降水指标均高度相关(P< 0.001), 年降水量可作为典型指标, 较好地反映多数极端降水指标变化特征。依据国家气候中心ENSO事件特征量综合表, 年厄尔尼诺峰值年有：、、、、、和2009; 拉尼娜峰值年有：、、、、、和2011年。以年降水量作为气候平均态, 分别统计厄尔尼诺和拉尼娜峰值年四季和年降水正距平栅格数()。可以看出, 在厄尔尼诺峰值年, 秦岭— 淮河南北春季降水偏多, 夏季降水明显偏少, 秋季降水偏少, 冬季降水微弱增加, 全年以降水偏少为主; 在拉尼娜峰值年, 秦岭— 淮河南北春季降水偏少, 夏季降水微弱增加, 秋季偏多, 冬季降水偏少, 全年以降水偏多为主。表4Tab.4表4(Tab.4)
表4 秦岭— 淮河南北厄尔尼诺和拉尼娜峰值年降水异常偏多面积对比/%
Tab.4 Comparison of the spatial coverage of positive precipitation anomaly between El Niñ o and La Niñ o years in north and south of the Qingling-Huaihe region/%降水偏多栅格比重春季夏季秋季冬季全年厄尔尼诺年66.328.338.254.336.7拉尼娜年16.657.887.636.064.0厄尔尼诺年— 拉尼娜年82.636.285.955.833.7
表4 秦岭— 淮河南北厄尔尼诺和拉尼娜峰值年降水异常偏多面积对比/%
Tab.4 Comparison of the spatial coverage of positive precipitation anomaly between El Niñ o and La Niñ o years in north and south of the Qingling-Huaihe region/%为了更清楚展示ENSO事件对秦岭— 淮河南北降水影响的空间特征, 以厄尔尼诺峰值年降水减去拉尼娜年, 绘制中国厄尔尼诺峰值年降水异常分布图()。从可更清楚看出：在厄尔尼诺峰值年, 秦岭— 淮河南北春季降水偏多, 夏季、秋季, 冬季降水微弱偏多。其中, 全年和夏季降水偏多的区域主要分布四川盆地东部和长江下游。图4Fig.4 图4 年中国厄尔尼诺年四季和全年降水异常空间分布图Fig.4 Spatial pattern of seasonal and annual precipitation anomalies in El Niñ o years in China, 5 结论基于秦岭— 淮河南北逐日站点降水数据以及全国0.5° × 0.5° 逐月降水格网数据, 选取16项极端降水指标, 本文分析了年秦岭— 淮河南北极端降水变化时空变化特征, 探讨了ENSO事件与极端降水变化的关系, 得到初步结论如下：(1) 在降水时空变化特征上, 年秦岭— 淮河南北降水空间格局呈现出“ 南多北少、东多西少” 特征, 在长期变化趋势上, 黄河下游和长江下游降水呈增加趋势, 秦巴山地、淮河平原、关中平原、巫山山区和四川盆地呈下降趋势。20世纪70年代末, 由于东亚夏季风偏弱, 黄河下游和淮河平原持续干旱、长江下游降水增多; 2000年后中国东部雨带有北移趋势, 黄河下游、秦巴山地和淮河平原降水相对于前期呈增加趋势, 长江下游降水则持续偏低。(2) 在极端降水变化特征上, 年秦岭— 淮河南北绝对指标整体均呈下降趋势, 降水等级越降低, 下降趋势越显著; 强度指标以上升趋势为主, 东部平原区极端降水强度高于西部山地区; 在持续性指标中, 持续性降水(CWD)以下降趋势为主, 连续无雨日数(CDD)呈上升趋势; 亦即秦岭— 淮河南北降水变化更加极端, 弱降水日数下降, 强降水日数上升, 突发性强降水事件增多, 连续性干旱事件亦在增多; 在空间上, 秦巴山地、长江下游和黄河下游为极端降水强度上升, 关中平原、巫山山区和四川盆地为极端干旱强度上升。(3) 在极端降水影响因素上, 秦岭— 淮河南北极端降水与ENSO关系密切。当发生厄尔尼诺事件时, 秦岭— 淮河南北降水普遍偏少, 降水强度和持续性均呈现下降趋势, 拉尼娜事件与之相反。就不同季节而言, 在厄尔尼诺峰值年, 秦岭— 淮河南北春季降水偏多, 夏季和秋季降水异常偏少, 冬季降水小幅增加; 在拉尼娜峰值年, 秦岭— 淮河南北春季降水异常偏少, 秋季降水异常偏多, 夏季小幅增加, 冬季降水偏少。就不同区域而言, 在厄尔尼诺年, 黄河下游、关中平原、秦巴山地和四川盆地极端降水呈下降趋势, 淮河平原极端降水呈上升趋势, 长江下游和巫山山区响应并不明显。
The authors have declared that no competing interests exist.
白红英, 马新萍, 高翔, 等. 2012.
基于DEM的秦岭山地1月气温及0 ℃等温线变化[J]. [Bai H Y, Ma X P, Gao X, et al. 2012.
Variations in January temperature and
0℃ isothermal curve in Qinling Mountains based on DEM[J].
[本文引用:1]
陈丽娟, 袁媛, 杨明珠, 等. 2013.
海温异常对东亚夏季风影响机理的研究进展[J]. 应用气象学报, 24(5): 521-532. [Chen L J, Yuan Y, Yang M Z, et al. 2013.
A review of physical mechanisms of the global SSTA impact on EASM[J]. Journal of Applied Meteorological Science, 24(5): 521-532. ]
[本文引用:1]
[CJCR: 1.379]
慈晖, 张强, 张江辉, 等. 2014.
年新疆极端降水过程时空特征[J]. 地理研究, 33(10): 1881-1891. [Ci H, Zhang Q, Zhang J H, et al. 2014.
Spatiotemporal variations of extreme precipitation events within Xinjiang during [J]. Geographical Research, 33(10): 1881-1891. ]
[本文引用:1]
丁一汇, 王绍武, 郑景云, 等. 2013. 中国气候[M]. 北京: 科学出版社. [Ding Y H, Wang S W, Zheng J Y, et al. 2013. Climate in China[M]. Beijing, China: Science Press. ]
[本文引用:1]
董旭光, 顾伟宗, 孟祥新, 等. 2014.
山东省近50年来降水事件变化特征[J]. 地理学报, 69(5): 661-671. [Dong X G, Gu W Z, Meng X X, et al. 2014.
Change features of precipitation events in Shand ong Province from 1961 to 2010[J]. Atca Geographica Sinica, 69(5): 661-671. ]
[本文引用:1]
金祖辉, 陶诗言. 1999.
ENSO循环与中国东部地区夏季和冬季降水关系的研究[J]. [Jin Z H, Tao S Y. 1999.
A study on the relationships between ENSO cycle and
rainfalls during summer and
winter in eastern China[J].
[本文引用:1]
[CJCR: 1.948]
蒋冲, 朱枫, 杨陈, 等. 2013.
秦岭南北地区光合有效辐射时空变化及突变特征[J]. [Jiang C, Zhu F, Yang C, et al.
Distribution and
change of photosynthetically active radiation (PAR) in the northern and
southern regions of Qinling Mountains, China[J].
[本文引用:1]
[CJCR: 1.959]
李斌, 李丽娟, 李海滨, 等. 2011.
年澜沧江流域极端降水变化特征[J]. [Li B, Li L J, Li H B, et al. 2011.
Changes in precipitation extremes in Lancang River Basin during [J].
[本文引用:1]
[CJCR: 1.959]
李双双, 延军平, 万佳. 2012.
全球气候变化下秦岭南北气温变化特征[J]. [Li S S, Yan J P, Wan J. 2012.
The characteristics of temperature change in Qinling Mountains[J].
[本文引用:1]
马建华, 千怀遂, 管华, 等. 2004.
秦岭—黄淮平原交界带自然地理若干特征分析[J]. [Ma J H, Qian H S, Guan H, et al. 2004.
Some features of physical geography in transitional region between Qinling Mountains and
Huanghuai Plain[J].
[本文引用:1]
秦大河. 2014.
气候变化科学与人类可持续发展[J]. [Qin D H. 2014.
Climate change science and
sustainable development[J].
[本文引用:1]
[CJCR: 1.959]
任正果, 张明军, 王圣杰, 等. 2014.
年中国南方地区极端降水事件变化[J]. 地理学报, 69(5): 640-649. [Ren Z G, Zhang M J, Wang S J, et al. 2014.
Changes in precipitation extremes in south China during [J]. Atca Geographica Sinica, 69(5): 640-649. ]
[本文引用:1]
苏坤慧, 延军平, 白晶, 等. 2012.
河南省境内淮河南北气候变化的小麦适应性比较[J]. [Su K H, Yan J P, Bai J, et al. 2012.
Comparative studies on degree of adaption of wheat under climate change between areas south and
north of Huaihe River in Henan Province[J].
[本文引用:1]
[CJCR: 1.959]
王会军, 范可. 2013.
东亚季风近几十年来的主要变化特征[J]. [Wang H J, Fan K. 2013.
Recent changes in the East Asian monsoon.
[本文引用:1]
[CJCR: 1.948]
王艳姣, 闫峰. 2014.
年中国降水区域分异及年代际变化特征[J]. [Wang Y J, Yan F. 2014.
Regional differentiation and
decadal change of precipitation in China in [J].
[本文引用:1]
[CJCR: 1.959]
延军平, 郑宇. 2001.
秦岭南北地区环境变化响应比较研究[J]. [Yan J P, Zheng Y. 2001.
A comparative study on environmental change response over the northern and
the southern regions of the Qinling Mountains[J].
[本文引用:1]
周旗, 卞娟娟, 郑景云. 2011.
秦岭南北年的气温与热量资源变化[J]. 地理学报, 66(9): 1211-1218. [Zhou Q, Bian J J, Zheng J Y. 2011.
Variation of air temperature and
thermal resources in the northern and
southern regions of the Qinling Mountains from 1951 to 2009[J]. Atca Geographica Sinica, 66(9): 1211-1218. ]
[本文引用:1]
Cao L G, Pan S M. 2014.
Changes in precipitation extremes over the “Three-River Headwaters” region, hinterland
of the Tibetan Plateau, during [J].
[本文引用:1]
[JCR: 1.962]
Donat M G. Alexand er L V, Yang H. 2013.
Global land -based datasets for monitoring climatic extremes[J].
[本文引用:1]
[JCR: 6.591]
Du H, Xia J, Zeng S D. 2014.
Regional frequency analysis of extreme precipitation and
its spatial-temporal characteristics in the Huai River Basin, China[J].
[本文引用:1]
[JCR: 1.639]
Huang J, Sun S L, Xue Y, et al. 2014.
Spatial and
temporal variability of precipitation indices during
in Hunan Province, central south China[J].
[本文引用:1]
Managing the risks of extreme events and
disasters to advance climate change adaptation (SREX)[R]. Cambridge, UK: Cambridge University Press.
[本文引用:1]
Climate change 2013: the physical science basis: the summary for policymakers of the working group I contribution to the fifth assessment report[R]. Cambridge, UK: Cambridge University Press.
[本文引用:1]
Li Y G, He D M, Hu J M, et al. 2014.
Variability of extreme precipitation over Yunnan Province, China [J]. International Journal of Climatology, doi:
[本文引用:1]
Liu M X, Xu X L, Sun A Y, et al. 2014.
Is Southwestern China experiencing more frequent precipitation extremes[J]. Environmental Research Letters, 9(6): 1-14.
[本文引用:1]
[JCR: 3.582]
Monier E, Gao X. 2014.
Climate change impacts on extreme events in the United States: an uncertainty analysis[J]. Climatic Change, doi: .
[本文引用:1]
[JCR: 3.634]
Sen R S, Rouault M. 2013.
Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa[J].
[本文引用:1]
Sen P K. 1968.
Estimates of the regression coefficient based on Kendall's tau[J].
[本文引用:1]
[JCR: 1.834]
Stephenson T S, Vincent L A, Allen T, et al. 2014.
Changes in extreme temperature and
precipitation in the Caribbean region, [J]. International Journal of Climatology, 34(9): 2957-2971.
[本文引用:1]
[JCR: 2.886]
Zhang D D, Yan D H, Wang Y C, et al. 2014.
Changes in extreme precipitation in the Huang-Huai-Hai River Basin of China during [J]. Theoretical and
Applied Climatology , doi: .
[本文引用:5]
Zhao Y F, Zou X Q, Cao L G, et al. 2014.
Changes in precipitation extremes over the Pearl River Basin, Southern China during [J].
[本文引用:1]
[JCR: 1.962]
白红英, 马新萍, 高翔, 等. 2012.
基于DEM的秦岭山地1月气温及0 ℃等温线变化[J]. [Bai H Y, Ma X P, Gao X, et al. 2012.
Variations in January temperature and
0℃ isothermal curve in Qinling Mountains based on DEM[J].
Based on the records of January average temperature during 1959 to 2009 from 39 meteorological sites in the Qinling Mountains, we built the spatial database of January temperature by using space interpolation method based on DEM with the consideration of the influence of terrain factors on the temperature field. Also we extracted the 0℃ isothermal curve and examined the changes in the January average temperature and the 0℃ isothermal curve in the Qinling Mountains during the last 50 years. The January average temperature showed a rising trend at a rate of about 0.2℃/10a, and the 0℃ isothermal curve rose by 143.7 m averagely in the Qinling Mountains during the last 50 years. On longitude, the largest variation in the 0℃ isothermal curve was found in the region of 107&-109&E, where the height increased by 166.2 m during the last 50 years. This value is significantly higher than that in both eastern and western sections of Qinling M the temporal mutations point for the largest increase in the January temperature was found in 1993. The 0℃ isothermal curve after the mutations point was raised higher by 113.82 m averagely than before.
1. College of Urban and Environmental Science, Northwest University, Xi'an 710127, C 2. Public Meteorological Service Center of China Meteorological Administration, Beijing 100081, China
以秦岭南北39 个气象站点 年1 月平均气温为基础, 考虑地形因素对温度场的影响, 采取基于DEM的空间插值方法, 获取秦岭山地复杂地形下的1 月气温空间插值数据集, 并在此基础上提取1 月0℃等温线, 研究了50 年来秦岭山地1 月平均气温和1 月0℃等温线的变化情况。结果表明:秦岭南北1 月月均气温均表现为上升趋势, 温度变化倾向率约为0.2℃/10a;50 年来秦岭1 月0℃等温线发生了明显上升, 平均上升高度为143.7 m。从经度上看, 107&E~109&E 范围内1 月0℃等温线所处海拔高度的变化最为强烈, 50 年来上升高度达166.2 m, 明显高于东西两段;1993 年是秦岭地区气温明显上升的突变点, 气温突变后1 月0℃等温线比突变前平均上升了113.82 m。
金祖辉, 陶诗言. 1999.
ENSO循环与中国东部地区夏季和冬季降水关系的研究[J]. [Jin Z H, Tao S Y. 1999.
A study on the relationships between ENSO cycle and
rainfalls during summer and
winter in eastern China[J].
用中国160个站月平均降水量和赤道东太平洋Ni?o 3区海温资料研究了ENSO循环过程的不同位相与中国降水的关系。结果显示ENSO循环对中国冬、夏季降水丰或欠及时空分布有密切关系，ENSO发展年的夏季我国东部地区以雨量偏少为主，一些地区可偏少3～5成，多雨带位于江淮之间；ENSO恢复年的夏季长江及江南地区雨量偏多，其南北两边偏少；反ENSO年的夏季长江—黄河之间及东南部雨量偏少，其北边和西南正常偏多；在ENSO的准常态年夏季，长江以北为正偏差，江南除少部分地区外降水分布接近正常。还发现ENSO暖位相与中国冬季降水也有很好关系。由于本文用准常态年降水平均值代替通常的气候平均值，因而有利于更好地揭示ENSO与中国气候变化的关系。
蒋冲, 朱枫, 杨陈, 等. 2013.
秦岭南北地区光合有效辐射时空变化及突变特征[J]. [Jiang C, Zhu F, Yang C, et al.
Distribution and
change of photosynthetically active radiation (PAR) in the northern and
southern regions of Qinling Mountains, China[J].
Based on 52-year () daily data from 47 meteorological stations in the northern and southern regions of Qinling Mountains, the annual and seasonal Photosynthetically Active Radiations (PAR) were calculated with equations of Angstrom and FAO Penman-Monteith. The spatial distribution, change trends and their causes were analyzed and detected with spatial analysis method of spline interpolation, Pettitt abrupt change point detection method and correlation analysis between PAR and relative factors. The results were as followed: (1) the PAR became weaker from north part to south part, i.e. from northern region of Qinling Mountains (NQ), to southern region of Qinling Mountains (SQ), to Han River Basin (HB) and to Valleys of Ba and Wu Mountain Areas (VBW). PAR in summer was the highest, followed by spring, autumn and winter. The distribution of PAR in spring, autumn and winter showed the same spatial pattern as annual PAR , but in summer, PAR in NQ is also the highest, then HB and VBW, and SQ being the lowest one. (2) PAR declined significantly in past 52a, the declining rates became smaller from south and east part to north and west part of this region. Except for an insignificant increase in spring, PAR decreased in other seasons, and the rate in summer was fastest, followed by that in winter and autumn. The maximum and minimum PAR appeared in s and 2000s respectively in spring, summer and autumn. There were almost half of stations showing an increase of PAR mainly in west and central parts, and the other half stations showing decrease in spring. PAR of 79% of stations decreased in autumn, and the increasing stations were also located in west and central parts. PAR in summer and winter declined in most stations, and the decreasing rate was bigger in south part of Qingling Mountains than in north part. (3) 89% of stations had abrupt change points of yearly and summer PAR , and about 85% and 90% of them happened between 1979 and 1983, respectively. There were no obvious abrupt change points in spring or autumn. (4) Climate change (wind speed declining), fast urbanization and more aerosol emission from industrial production were the main reasons for the continuous decline of PAR , and the aerosol emitted from volcanoes was the main reason for fluctuation of PAR .
1. College of Resources and Environment, Northwest A & F University, Yangling 712100, C 2. Institute of Soil andWater Conservation, CAS and Ministry ofWater Resources, Yangling 712100, C 3. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
基于秦岭南北地区47个气象站年的逐日气象数据,通过Angstrom方程和Penman-Monteith公式计算了各站点的光合有效辐射( PAR ),并借助Spline空间插值、Pettitt突变点检验和相关分析等手段对 PAR 的空间分布、时空演变、突变特征及其可能成因进行了分析。结果表明:① 秦岭南北地区 PAR 的时间和空间分布特征明显,在空间上呈北高南低的分布格局;在季节分布上,夏季、春季、秋季、冬季依次减小。② 52年间,该地区年 PAR 整体呈显著下降趋势,下降速率由南向北,由东向西递减;时间变化方面,春季 PAR 呈现不显著的上升趋势,其余季节均呈下降趋势,夏季减小最快,其次为冬季,秋季最小。③ 该地区89%的站点年 PAR 存在突变,突变站点中的85%发生于年间;夏季89%的站点发生突变,突变站点中的90%发生于年间;冬季68%的站点发生突变,但突变时间同步性和一致性较差;春季和秋季突变现象不甚明显。④ 气候变化(风速下降)、城市化进程加快以及工业生产导致的气溶胶增多是导致 PAR 显著下降的主要原因,而火山爆发引发的气溶胶增加则是 PAR 波动的主要原因。
李斌, 李丽娟, 李海滨, 等. 2011.
年澜沧江流域极端降水变化特征[J]. [Li B, Li L J, Li H B, et al. 2011.
Changes in precipitation extremes in Lancang River Basin during [J].
Extreme precipitation is an important aspect of climate change. According to the estimation using the latest climate models, the extreme precipitation events will become frequent in a warming world. Significant increases of the very heavy precipitation and decreases of light and moderate precipitations have indeed been observed over most land areas of the globe in the last few decades. The Lancang River, with a relative altitude difference of about 5000 m, flows through 13 latitudes and 6 climatic zones. It is rarely seen in the world and has important scientific values for climatology, hydrology, geography and ecology. Since 1960, the basin has experienced a significant increase in temperature like most parts of the world. Studying the changes of extreme precipitation events in the basin in the context of global warming is of great importance. Based on a daily precipitation dataset of 35 meteorological observation stations distributed in and around the Lancang River basin, trends of precipitation amounts, precipitation days and daily precipitation intensity during a 45-year period () of 4 different classes ranging from less than 5, 5-10, 10-50 and larger than 50 mm were analyzed, and the precipitation frequency and the proportion of precipitation amount of each precipitation class were calculated. The result showed that all the indexes varied spatially, and for the basin as a whole, the frequency of the extreme events increased obviously. Analysis of a typical station indicated that the increase of extreme precipitation and the randomness of the climatic system might be closely related with each other.
1. Institute of Geographic Sciences and Natural Resources, CAS, Beijing 100101, C 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, C 3. Princeton University, USA
极端降水事件是气候变化的一个重要方面。澜沧江流域纵贯13 个纬度，最大相对高差近5000 m，跨6 种气候带，是全球少见的南北向大江，它在气候、水文、地理、生态学等多方面都具有重要的科学研究价值。自1960 年以来，流域经历了显著的气温上升。探讨在气候变暖背景下这一复杂流域的极端降水变化具有重要意义。本文利用澜沧江流域及其周边35 个气象站 年的日降水资料，分析了小于5 mm、5～10 mm、10～50 mm以及大于50 mm 4 个不同量级降水的降水量、降水日数和日平均降水强度的变化趋势。并计算了每种量级降水占总降水量的百分比及降水频率。结果表明，各量级各项指标均存在明显的区域变化特征，流域总体上极端降水频率的增加态势明显。对典型地区站点分析表明，极端降水的增加可能与气候系统随机性变强有关。
李双双, 延军平, 万佳. 2012.
全球气候变化下秦岭南北气温变化特征[J]. [Li S S, Yan J P, Wan J. 2012.
The characteristics of temperature change in Qinling Mountains[J].
Qinling range has been recognized as the geo-ecological boundary between subtropical and warm-temperate zones in the eastern China, which is the advantage of regional area to study global change. This article, based on the meteorological data of the 61 meteorological stations in the northern and southern regions of the Qinling Mountains (), selecting the contour 1 000 m in southern piedmont as the ecological boundary line, analyzed the fundamental characteristics, spatio-temporal distribution and reasons of temperature change using methods of linear regression, Mann-Kendall mutation test, analysis of wavelets, Kriging interpolation and other Climate diagnosis method. The results show that the average temperature, extreme high and low temperature in the south and north Qinling Mountains were in increase trend, but there was a certain difference in the sharp change time and range. The tilt rate of annual average temperature in the south of Qinling Mountains is the lowest (0.121℃/10 a),then is in the north of Qinling Mountains (0.203℃/10 a),and they all lower than the other regions of China (0.26±0.032℃/10 a). The temperature mutation of the north of Qinling Mountains (1995) occurred earlier than that of the sorth (1998), which was later than the other regions of China (1993). Based the climate characteristics, it was found that the influence of climate change mainly reflects nature and human activities.
College of Tourism and Environment, Shaanxi Normal University, Xi'an, Shaanxi 710062,China
选取秦岭南麓1000m划分方案,运用气候倾向率、线性拟合方程、Mann-Kendall非参数检验、小波分析等气候数理统计方法,分析秦岭南北气温变化特征。结果表明：近50a秦岭南北气候变化具有同步性,增温趋势明显；在气温突变方面,关中地区气温突变(1995年)早于陕南(1998年)。通过近10a秦岭南北气温时空格局演变分析,认为秦岭地区气温变化符合全球变化规律,其变化是自然因素和人类活动共同作用的结果,在小尺度上人类活动干扰尤为明显(特别体现在快速城市化影响气温上升)。
马建华, 千怀遂, 管华, 等. 2004.
秦岭—黄淮平原交界带自然地理若干特征分析[J]. [Ma J H, Qian H S, Guan H, et al. 2004.
Some features of physical geography in transitional region between Qinling Mountains and
Huanghuai Plain[J].
The boundary of the transitional region between Qinling Mountains and Huanghuai Plain was divided first in this paper, then some features of physical geography in the transitional region were discussed. (1) The east boundary of the transitional region is at the contour about 100 m, and the west boundary is at the contour about 500 m. The area of the transitional region is about 26 000 km 2 ,which makes up 15.9% of total area in Henan Province.(2) The natural features in the transitional region possess transitional characters evidently in two directions, one is from the western mountain to the eastern plain and the other is from southern subtropical zone to northern temperate zone. (3) Torrential rain especially for strong torrential rain is frequent in the transition region, and there are many torrential rain centers, such as Lushan torrential rain center, Biyang torrential rain center, and so on. A majority of torrential rain is distributed among 100-200 m above sea level. (4) The winter temperature at 100-400 m above sea level in the transitional region is not only higher than in Huanghuai Plain where its altitude is lower than the transition region's, but also higher than in Qinling Mountains where its altitude is higher than the transitional region's. The highest temperature in January appears at 350-400 m above sea level in the transitional region. The warmer belt in the transitional region is called warm slope belt, of which thickness varies from 100 m to 250 m above sea level. (5) Torrential rain and warm slope belt in the transitional region were formed by atmospheric circulation and local terrain. Frequent torrential rain and warm slope belt had tremendous influence on soil properties, plant distribution and local climate in the transitional region.
College of Environment and Planning, Henan University, Kaifeng, Henan 475001
文章探讨了秦岭-黄淮平原交界带划分的依据和方法,然后就其自然地理过渡性、暴雨频繁发生和坡地暖带及其自然地理效应进行讨论。研究表明:交界带自然地理要素不仅具有西部山地和东部平原之间的过渡性,而且北亚热带和暖温带地理成分在这里彼此交汇。交界带暴雨频繁,且以大暴雨为主,集中分布在海拔100~200 m之间。交界带冬季气温高于平原0.5~0.8℃,1月最高气温出现在海拔350~400 m之间,形成特有的坡地暖带,暖带厚度100~250 m。交界带暴雨频繁和暖坡效应是大气环流和交界带地貌格局共同作用的结果,且对本区土壤发育和植物分布等具有重大影响。
秦大河. 2014.
气候变化科学与人类可持续发展[J]. [Qin D H. 2014.
Climate change science and
sustainable development[J].
Since the Fourth Assessment Report (AR4) was released by the Intergovernmental Panel on Climate Change (IPCC) in 2007, new observations have further proved that the warming of the global climate system is unequivocal. Each of the last three successive decades before 2012 has been successively warmer at global mean surface temperature than any preceding decade since -2012 was likely the warmest 30-year period of the last 1400 years. From 1998 to 2012, the rate of warming of the global land surface slowed down, but it did not reflect the long-term trends in climate change. The ocean has warmed, and the upper 75 m of the ocean warmed by more than 0.11℃ per decade since 1970. Over the period of 1971 to 2010, 93% of the net energy increase in the Earth's climate system was stored in the oceans. The rate of global mean sea level rise has accelerated, which was up to 3.2 mm yr-1 between 1993 and 2010. Anthropogenic global ocean carbon stocks were likely to have increased and caused acidification of the ocean surface water. Since 1971, the glaciers and the Greenland and Antarctic ice sheets have been losing mass. Since 1979, the Arctic sea ice extent deceased at 3.5% to 4.1% per decade, and the Antarctic sea ice extent in the same period increased by 1.2% to 1.8% per decade. The extent of the Northern Hemisphere snow cover has decreased. Since the early 1980s, the permafrost temperatures have increased in most regions. Human influence has been detected in the warming of the atmosphere and the ocean, changes in the water cycle, reductions in snow and ice, global mean sea level rise, and changes in climate extremes. The largest contribution to the increase in the anthropogenic radiative forcing was by the increase in the atmospheric concentration of CO 2 since 1750. It led to more than half of global warming since the 1950s (with 95 % confidence). It is predicted using Coupled Model Intercomparison Project Phase 5 (CMIP5) and Representative Concentration Pathways (RCPs) that the global mean surface temperature will continue to rise for the end of this century, the frequency of extreme events such as heat waves and heavy precipitation will increase, and precipitation will present a trend of "the dry becomes drier, the wet becomes wetter". The temperature of the upper ocean will increase by 0.6 to 2.0℃ compared to the period of 1986 to 2005, heat will penetrate from the surface to the deep ocean which will affect ocean circulation, and sea level will rise by 0.26 to 0.82 m in 2100. Cryosphere will continue to warm. To control global warming, humans need to reduce the greenhouse gas emissions. If the increase in temperature is higher than 2℃ than before industrialization, the mean annual economic losses worldwide will reach 0.2% to 2.0% of income, and cause large-scale irreversible effects, including death, disease, food insecurity, inland flooding and water logging, and rural drinking water and irrigation difficulties that affect human security. If taking prompt actions, however, it is still possible to limit the increase in temperature within 2℃. To curb the gradually out-of-control global warming and achieve the goal of sustainable development of the human society, global efforts to reduce emissions are needed.
1. State Key Laboratory of Cryosphere Science, Chinese Academy of Sciences, Lanzhou 730000, C 2. China Meteorological Administration, Beijing 100081, China
政府间气候变化专门委员会（IPCC）自2007 年发布第四次评估报告（AR4）以来，新的观测证据进一步证明，全球气候系统变暖是毋庸置疑的事实。2012 年之前的3 个连续10 年的全球地表平均气温，都比1850 年以来任何一个10 年更高，且可能是过去1400 年来最热的30 年。虽然 年全球地表增温速率趋缓，但还不能反映出气候变化的长期趋势。1970 年以来海洋在变暖，海洋上层75 m以上的海水温度每10 年升温幅度超过0.11℃； 年地球气候系统增加的净能量中，93%被海洋吸收。全球平均海平面上升速率加快， 年间高达3.2 mm/年。全球海洋的人为碳库很可能已增加，导致海洋表层水酸化。1971 年以来，全球几乎所有冰川、格陵兰冰盖和南极冰盖的冰量都在损失。其中1979 年以来北极海冰范围以每10 年3.5%~4.1%的速率缩小，同期南极海冰范围以每10 年1.2%~1.8%的速率增大。北半球积雪范围在缩小。20 世纪80 年代初以来，大多数地区的多年冻土温度升高。已在大气和海洋变暖、水循环变化、冰冻圈退缩、海平面上升和极端气候事件的变化中检测到人类活动影响的信号。1750 年以来大气CO 2 浓度的增加是人为辐射强迫增加的主因，导致20 世纪50 年代以来50%以上的全球气候变暖，其信度超过95%。采用CMIP5 模式和典型浓度路径（RCPs），预估本世纪末全球地表平均气温将继续升高，热浪、强降水等极端事件的发生频率将增加，降水将呈现“干者愈干、湿者愈湿”趋势。海洋上层的温度比 年间升高0.6~2.0℃，热量将从海表传向深海，并影响大洋环流，2100 年海平面将上升0.26~0.82m。冰冻圈将继续变暖。为控制气候变暖，人类需要减少温室气体排放。如果较工业化之前的温升达到2℃，全球年均经济损失将达到收入的0.2%~2.0%，并造成大范围不可逆的影响，导致死亡、疾病、食品安全、内陆洪涝、农村饮水和灌溉困难等问题，影响人类安全。但如果采取积极行动，2℃的温升目标仍可望达到。为遏制逐渐失控的全球变暖，需全球共同努力减排，以实现人类可持续发展的理想。
苏坤慧, 延军平, 白晶, 等. 2012.
河南省境内淮河南北气候变化的小麦适应性比较[J]. [Su K H, Yan J P, Bai J, et al. 2012.
Comparative studies on degree of adaption of wheat under climate change between areas south and
north of Huaihe River in Henan Province[J].
Degree of adaption is one of the key components of adaptability processes under climate change. In this paper, we established the concepts and methods of degree of adaption (DA) in order to comparably analyze the DA of wheat in area south and north of the Huaihe River in Henan Province. Results demonstrate that the climate dividing line is not the mainstream areas of Huaihe River, but the largest tributary of the area is located in were the further north, about 300 km away from the original zone. And the spatial variation of DA of winter wheat is approximately distributed around this area. The DA of the area, which is to the south of the dividing line of the Huaihe River, is 62.57%, which is higher than 56.81% in the northern area. Therefore there is still a large space which requires the human regulation and control to adapt the wheat to the climate change. And the pressure on human control in the northern area is greater than in the southern. As regards to the annual change, accompanied by the abrupt climate change in the 1980s, the temperature DA surged but the moisture DA plunged. In the following periods when the climate became stable, DA kept an increasing tendency. However the increasing speed of DA declined in the early 21st century when a plunge trend appeared, indicating that the negative impact on wheat from global warming has become increasingly prominent.
1. College of Tourism and Environment, Shaanxi Normal University, Xi'an 710062, C 2. Center of Climate in Henan Province, Zhengzhou 450003, C 3. The First Senior High School of Qinyang in Henan province, Qinyang 454550, China
适应度是气候变化下适应性研究的关键环节,本文提出气候变化适应度的概念及其定量评价方法,并对淮河南北的小麦适应度进行比较分析。结果表明,目前河南省境内的南北气候分界线并非淮河干流区,而是由原位置北移约300 km处的最大支流地带,冬小麦的适应度空间变化大致围绕该分界线呈经向分布。淮河分界线以南地域适应度为62.57%,高于以北地域的56.81%,研究结果表明,欲达到河南农业可持续发展,距离完全适应仍有较大空间需要人为调控,且北部相比较南部其调控压力更大。在年际变化上,随着20 世纪80 年代气候的突变,各地小麦温度适应度骤增,水分适应度骤减,之后随着气候的日趋稳定,各气候要素的适应度不断上升,但在21 世纪初上升速度下降,甚至有降低趋势,表明气候变暖的环境对小麦的负面影响日渐突出。
王会军, 范可. 2013.
东亚季风近几十年来的主要变化特征[J]. [Wang H J, Fan K. 2013.
Recent changes in the East Asian monsoon.
Studies on the recent changes of the summer and winter monsoons, with priority on decadal-interdecadal scales, are reviewed briefly in this paper. The major changes in the East Asian summer monsoon (EASM) include a weakening of the EASM and a shift in precipitation patterns at the end of 1970s; an increase in South China precipitation after ; a decrease in precipitation in the middle-and-lower reaches of the Yangtze River and an increase in precipitation in the Huaihe River valley after 1999; and instability in the relationship between the EASM and El Niño-Southern Oscillation (ENSO). The changes in the East Asian winter monsoon (EAWM) include a weakening of the EAWM and its interannual variability after the mid-1980s, an increase in winter snowfall in Northeast China after the mid-1980s, and a weakening of the EAWM-ENSO relationship after the mid-1970s. In addition, the impact of the autumn Arctic sea ice decline on the winter snow cover in the Northern Hemisphere is discussed. These changes in EASM and EAWM indicate that the extreme climate and phenology have been significantly altered.
本文简要综述了关于东亚夏季风和冬季风近几十年来的主要变化特征的若干研究结果,特别是关于其年代际变化方面。夏季风及夏季气候的主要变化特征有：1970年代末之后东亚夏季风的年代际时间尺度的减弱以及相应的我国夏季降水江淮流域增多而华北减少、1992年之后我国华南夏季降水增多、1999年之后我国长江中下游夏季降水减少而淮河流域夏季降水增多、东亚夏季风和ENSO之间的年际变化相关性存在不稳定性。而关于东亚冬季风与冬季气候的主要变化特征有：1980年代中期之后东亚冬季风及其年际变率减弱、1970年代中期之后冬季风和ENSO的年际变化相关性较弱、近年来的北极秋季海冰减少对北半球冬季积雪增多有显著贡献、东北冬季积雪在1980年代中期以后增多。与上述变化有关的极端气候和物候都发生了多方面的变化。
王艳姣, 闫峰. 2014.
年中国降水区域分异及年代际变化特征[J]. [Wang Y J, Yan F. 2014.
Regional differentiation and
decadal change of precipitation in China in [J].
Based on precipitation data from 1840 meteorological stations in China in , this study examines the regional differentiation of precipitation and characteristics of its change in the recent 50 years. Using the empirical orthogonal function (EOF) and rotated EOF (REOF) methods, precipitation in China is divided into 11 regions, which are grouped into four areas according to their geographic locations: East China area (North China, Huanghuai and Jianghuai, the middle and lower reaches of the Yangtze River, and Jiangnan and South China regions), Northwest China area (Midwest Inner Mongolia, western part of the Northwest China, and eastern part of the Northwest China regions), Southwest China area (southeastern part of the Southwest China, western part of the Southwest China, and northeastern part of the Southwest China regions), and Northeast China. Compared with the results of previous studies, precipitation regions derived with the REOF method in combination with detailed long time series precipitation data are consistent with the regional differentiation of actual precipitation and the climate division of China. The analysis shows that precipitation in the East China area changed in the late 1970s, from the late 1980s to the early 1990s, and in the beginning of the 21st century respectively, featuring recurrent south-north shifts of the rain belt in both directions, which were mainly influenced by the interdecadal variability of the East Asian summer monsoon and atmospheric circulation. Precipitation in the Northwest China area experienced a major change in the mid-1980s. The western part of the Northwest China area became wet compared to the dry period in the previous years, whereas the eastern part of the area became dry compared to the previous wet years. The decreasing precipitation in the eastern Northwest China area was related to the continually weakening of the East Asia summer monsoon, while the increasing precipitation in the western Northwest China area were mainly due to the anomalous high moisture transport from the Arabia Sea and the Caspian Sea. Precipitation in the Northeast China area underwent similar abrupt changes in the early 1980s and the late 1990s respectively-it changed from the previous near normal level to high in the early 1980s, and from high to low in the late 1990s. The changes were influenced by the East Asian summer monsoon on the one hand, and related to the anomalous moisture transport form the Northwest Pacific Ocean on the other. Evident changes in precipitation have been detected over each region in the Southwest China area-precipitation changes over the western and northeastern parts of this region were in opposite directions before 2000. Precipitation in the Southwest China area is not only influenced by the terrain of the Tibetan Plateau, but also affected by the East Asian monsoon and the subtropical high, which cause complicated changes in precipitation of the area.
1. National Climate Center, China Meteorological Administration, Beijing 100081, C 2. Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China
利用 年中国1840 个台站年降水量数据,采用经验正交函数(EOF)和旋转经验正交函数分解方法(REOF)对降水进行分区,并对各区降水的变化特征进行了研究。结果表明:基于多站点资料结合REOF方法实现的降水分区与中国降水实际区域分异特征比较符合,并与中国气候区划相一致。中国各区降水变化特征分析表明,东部各区降水在20 世纪70 年代末、80 年代末-90 年代初和21 世纪初发生雨带的南北移动过程,其中夏季雨带的移动主要受东亚夏季风和大气环流年代际变化的影响。西北地区降水以 年为突变年,西北西部地区降水由前期偏少转为偏多,主要与来自阿拉伯海和里海异常偏多的水汽输送有关;西北东部地区降水由前期偏多转为偏少,主要与季风的年代际减弱有关。东北地区降水在80 年代初由前期接近正常转为偏多,90 年代末降水由前期偏多转为偏少,主要与季风和西北太平洋水汽输送的年代际变化相关。西南部各区降水阶段性变化明显,2000 年以前西南东北部地区降水与西部地区基本呈反向变化,主要受青藏高原地形、东亚季风和副热带高压等因素的影响,降水阶段性变化明显、成因复杂。
延军平, 郑宇. 2001.
秦岭南北地区环境变化响应比较研究[J]. [Yan J P, Zheng Y. 2001.
A comparative study on environmental change response over the northern and
the southern regions of the Qinling Mountains[J].
Based on the data up to 1999 from the hydro-climatological departments, this paper analyzes the climatic dividing implications of Qinling Mountains in regional response to the process of global warming, due to which the Grades of Dryness/wetness (GDW) in 100-year scale show that the northern region has entered an arid period, and the southern, a humid period. At decade scale, the D-value of annual average air temperature over Southern Shaanxi (Hanjiang Valley) and Central Shaanxi Plain (Guanzhong Plain) has narrowed, i.e. the former with slight change and the latter with rapid increase in temperature. Both regions are arid with decease in precipitation D-value, namely, the plain becomes warmer while the south drier. Qinling Mountains play a predominant role in the climatic dividing. The runoff coefficient (RC) of Weihe River decreases synchronously with that of Hanjiang River due to climate warming . The RC of Weihe dropped from 0.2 in the 1950s to less then 0.1 in the 1990s.Weihe valley (Guanzhong Plain) is practically an arid area as a result of the shortage of water .The successive 0.5 and 1.0℃ temperature anomaly over China marks, perhaps, the important transition period in which the environment becomes more vulnerable than before .The study shows the obvious trend of environmental aridity, which is of help to the understanding of regional response to the global climate change.
1. College of Tourism and Environment, Shaanxi Normal University, Xi'an 710062, C 2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
利用气象水文部门截止1999年的气象水文实测数据,计算分析在气候变暖过程中中国秦岭具有的区域响应分界意义。由于气候变暖,在百年时间尺度上,通过旱涝指数分析证明秦岭以北进入干旱期,秦岭以南为湿润期;在10年时间尺度上,陕南气温变化较小,而关中气温增高较快,陕南与关中年均气温差值变小;关中和陕南降水量差值变小,二者同时干旱或陕南更干旱,反映出秦岭在气候变化中显著的分界作用。气候变暖,渭河与汉江年径流系数同步减小,其中渭河径流系数由50年代的02下降为90年代的01以下,渭河流域已变为少水带,即相当于气候上的干旱区。秦岭以北地区较其以南地区环境干暖化的趋势更明显,这对于认识全球变化的区域响应差异有参考意义。
... 董旭光等, 2014)以及不同自然区域(Cao et al, 2014 ...
Donat M G. Alexand er L V, Yang H. 2013.
Global land -based datasets for monitoring climatic extremes[J].
Donat, M. G. 1,2 ;Alexander, L. V. 1,2 ;Yang, H. 1,2 ;Durre, I. 3 ;Vose, R. 3 ;Caesar, J. 4 ;
... Du et al, 2014 ...
... Zhao et al, 2014)、不同省域(Huang et al, 2014 ...
... Li et al, 2014 ...
... Liu et al, 2014 ...
... Monier et al, 2014 ...
Sen R S, Rouault M. 2013.
Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa[J].
Hourly precipitation data from 1998 to 2007 spread across 102 stations in South Africa were analyzed for trends in extreme hourly precipitation events. The analyses were conducted at the seasonal scale for summer and winter for nine different variables. The results of our analysis showed predominantly positive trends during summer, with the strongest trends concentrated in the coastal areas in the southeast. The spatial variations in the trends were reversed during the winter season, with negative trends observed in the coastal areas and positive trends occurring in the interior. The summer patterns also overlap with areas experiencing overall increasing trends in annual extreme precipitation as well as a stronger diurnal cycle identified in recently published literature. (C) 2012 Elsevier Ltd. All rights reserved.
Sen Roy, Shouraseni 1 ;Rouault, Mathieu 2,3 ;
... 在气候变暖背景下,全球多数区域极端降水呈现增加趋势,但并未像极端气温具有全球一致性(Donat et al, 2013),美国、南非和加勒比等区域研究亦发现上述规律(Sen et al, 2013 ...
... 由于线性回归要求时间序列符合正态分布,且易受异常值干扰,Sen趋势度逐渐被引入气候趋势变化分析(Sen, 1968) ...
... Stephenson et al, 2014) ...
... Zhang et al, 2014 ...
... 05 d/10 a (Zhang et al, 2014) ...
... 1 d/10 a(Zhang et al, 2014),但低于中国南方地区0 ...
... 6 mm/10 a下降趋势形成鲜明对比(Zhang et al, 2014),而且上升区集中于长江下游、秦巴山地和四川盆地 ...
... 9 mm/10 a的下降趋势(Zhang et al, 2014) ...
... Zhao et al, 2014)、不同省域(Huang et al, 2014 ...
年秦岭—淮河南北极端降水时空变化特征及其影响因素
[李双双1,2, 杨赛霓1,2, 刘宪锋1,3]}
引起气候变化的原因
我们赖以生存的地球是一个极其复杂的系统，地球气候系统是构成这个地球系统的重要一环。在漫长的地球历史中，气候始终处在不断地变化之中。究其原因，概括起来可分成自然的气候波动与人类活动的影响两大类。前者包括太阳辐射的变化、火山爆发等。后者包括人类燃烧矿物燃料以及毁林引起的大气中温室气体浓度的增加、硫化物气溶胶浓度的变化、陆面覆盖和土地利用的变化等。
气候系统所有的能量基本上都来自太阳，因此太阳辐射的变化被认为是引起气候系统变化的一个外因。20世纪70年代末，卫星观测的应用使得人类可以在大气层以外准确地测量太阳辐射输出的变化，这才知道太阳辐射量并不是完全不变的，特别在太阳黑子异常活动的周期中存在着一定的差异。许多科学家认为太阳黑子数多时地球偏暖，低时地球偏冷。但太阳辐射的变化影响气候的机理尚不清楚，也缺乏严格的理论或者观测事实支持。不过通过研究，科学家们还是发现，太阳辐射的变化、地球轨道的变化都不是引起近代全球变暖的主要原因，同时基本排除了影响气候变化的另一个自然因素——火山爆发是引起近百年全球变暖主要原因的可能性。
科学家们认为，在气候系统的自然变化中，最重要的方面是大气与海洋环流的变化或者脉动。这种环流变化是造成区域尺度气候要素变化的主要原因大气与海洋环流的变化有时可伴随着陆面的变化。在年际时间尺度上，厄尔尼诺和南方涛动（ENSO）和NAO是大气与海洋环流变化的重要例子，它们的变化影响着大范围甚至半球或全球尺度的天气与气候变化，是目前制作季、年际气候预测的基础与依据。长期以来世界上许多气象学家一直致力于这方面的研究，旨在提高全球与区域的气候预测水平。对于更长的十年时间尺度，太平洋十年尺度振荡（PDO）和相关的年代际太平洋振荡（IPO）可以用来解释地面气温全球平均变化的一半左右，它们与明显地与地区性的温度和降水变化有联系。
关于人类活动对气候变化的影响，有越来越多的研究表明，近百年人类活动加剧了气候系统变化的进程。最新发表的权威报告——联合国政府间气候变化专门委员会（IPCC）第四次评估报告第一工作组报告的决策者摘要指出，人类活动与近50年气候变化的关联性达到90%。
对人类活动增加大气中温室气体的浓度可能导致气候变化的研究，可以追溯到19世纪末。1896年，瑞典科学家斯万特．阿尔赫许多科学家陆续对此问题进行了一些研究。1957年，瑞威拉等在美国发表了一篇关于增加大气中温室气体浓度可能产生气候变化的论文。同年，美国夏威夷观象台开始进行浓度观测，从而正式揭开人类研究气候变化的序幕。
排放温室气体的人类活动有哪些？可产生哪些温室气体呢？这些温室气体又是怎样影响了气候变化呢？
排放温室气体的人类活动包括：所有的化石能源燃烧活动排放二氧化碳。在化石能源中，煤含碳量最高，石油次之，天然气较低；化石能源开采过程中的煤炭瓦斯、天然气泄漏排放二氧化碳和甲烷；水泥、石灰、化工等工业生产过程排放二氧化碳；水稻田、牛羊等反刍动物消化过程排放甲烷；土地利用变化减少对的吸收；废弃物排放甲烷和氧化亚氮。
上述那些人类活动所产生的温室气体主要有6种：除了二氧化碳外，目前发现的人类活动排放的温室气体还有甲烷、氧化亚氮、氢氟碳化物、全氟化碳、六氟化硫。对气候变化影响最大的是二氧化碳，二氧化碳的生命期很长，一旦排放到大气中，最长可生存200年时间，因而最受关注。
这些温室气体主要是通过温室效应来影响气候变化的。何为温室效应？大气中的二氧化碳等气体，可以透过太阳短波辐射（指吸收少），使地球表面升温；但阻挡地球表面向宇宙空间发射长波辐射（指吸收多），从而使大气增温。由于二氧化碳等气体的这一作用与“温室”的作用类似，故称之为“温室效应”。
工业化革命以前，大气中的二氧化碳等气体造成的“温室效应”使得地球表面平均温度由-18℃上升到当今自然生态系统和人类已适应的15℃。一旦大气中的温室气体浓度继续增加，进一步阻挡了地球向宇宙空间发射的长波辐射，为维持辐射平衡，地面必将增温，以增大长波辐射量。地面温度增加后，水汽将增加（增加大气对地面长波辐射的吸收），冰雪将融化（减少地面对太阳短波的反射），又使地表进一步增温，即形成正反馈使全球变暖更显著。
微信关注我们，阴晴冷暖尽在掌握
转载请注明“来源：中国天气网”
Copyright& All Rights Reserved () 版权所有 复制必究 郑重声明：中国天气网版权所有，未经书面授权禁止使用年秦岭—淮河南北极端降水时空变化特征及其影响因素
李双双, 杨赛霓, 刘宪锋. .年秦岭—淮河南北极端降水时空变化特征及其影响因素[J]. 地理科学进展, ,34(3): 354-363
LI Shuangshuang, YANG Saini, LIU Xianfeng. .Spatiotemporal variability of extreme precipitation in north and south of the Qinling-Huaihe region and influencing factors during [J]. Progress In Geography,,34(3): 354-363&&
Permissions
年秦岭—淮河南北极端降水时空变化特征及其影响因素
李双双1,2,
杨赛霓1,2,
1. 北京师范大学地表过程与资源生态国家重点实验室,北京 100875
2. 北京师范大学减灾与应急管理研究院,北京 100875
3. 北京师范大学资源学院,北京 100875
通讯作者：杨赛霓(1975-),女,江苏武进人,副教授,主要研究方向为交通应急与风险管理,E-mail: 。
作者简介：李双双(1988-),男,陕西潼关人,博士生,主要研究方向为全球变化与区域灾害防治,E-mail: 。
基金: 地表过程模型与模拟创新研究群体科学基金项目(); 国家重点基础研究发展计划项目()
基于秦岭—淮河南北气象站点逐日降水数据和全国0.5°×0.5°逐月降水格网数据,选取16个极端降水指数,辅以趋势分析、Mann-Kendall检验和相关分析等气候诊断方法,分析了年秦岭—淮河南北极端降水时空变化特征,探讨了极端降水变化与ENSO事件的关系。结果表明：①年秦岭—淮河南北除长江下游降水呈增加趋势外,其他区域降水均呈下降趋势;②极端降水变化主要表现为：降水日数减少,降水强度上升,突发性强降水事件增多,连续性干旱事件增多;在空间上,秦巴山地、长江下游和黄河下游以极端降水强度上升为主,关中平原、巫山山区和四川盆地以极端干旱强度上升为主;③在影响因素方面,秦岭—淮河南北极端降水与ENSO事件关系密切。在厄尔尼诺年,秦岭—淮河南北春季极端降水偏多,夏季和全年偏少;在拉尼娜年,春季极端降水偏少,秋季和全年偏多。就各个区域而言,在厄尔尼诺年,黄河下游、关中平原、秦巴山地和四川盆地极端降水呈下降趋势,淮河平原极端降水呈上升趋势,长江下游和巫山山区响应并不明显。
秦岭—淮河南北
doi: 10.11820/dlkxjz.
Spatiotemporal variability of extreme precipitation in north and south of the Qinling-Huaihe region and influencing factors during
LI Shuangshuang1,2,
YANG Saini1,2,
LIU Xianfeng1,3
1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
2. Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China
3. College of Resource Sciences and Technology, Beijing Normal University, Beijing 100875, China
Based on the monthly precipitation of a 0.5°×0.5° grid dataset and the daily precipitation observations of 135 meteorological stations released by the National Meteorological Information Center of China, this study analyzed the spatiotemporal variation of extreme precipitation in north and south of the Qinling-Huaihe region during , using the methods of trend analysis, Sen+Mann-Kendall model, and correlation analysis. More specifically, we analyzed the relationship between ENSO and the observed extreme precipitation. The results are as follows: (1) the precipitation showed an increasing trend in the lower reach of the Yangtze River and a decreasing tendency
(2) extreme precipitation analysis indicates a declining trend in rainy days and an increasing trend in precipitation intensity. The number of continuous drought events increased. Spatially, the regions with increasing intensity of extreme precipitation were mainly distributed in the Qinling-Bashan Mountains and the lower reaches of the Yangtze River and Yellow River, whereas there were more drought events in the Guanzhong Plain, Wushan Mountains, and Sichuan B (3) Extreme precipitation had a close relationship with ENSO in the study region. In El Niño years, more precipitation was found in the spring but there was less precipitation in the summer and the whole year. In La Niña years, there was less precipitation in the spring and more precipitation in the autumn and the whole year. The responses of extreme precipitation events to El Niño exhibited spatial differences. Most of the regions with decreasing extreme precipitation in El Niño years were distributed in the lower reach of the Yellow River, the Guanzhong Plain and Qinling-Bashan Mountains, as well as the Sichuan Basin, while the region with increasing extreme precipitation was the Huaihe Plain. The lower reach of the Yangtze River and the Wushan Mountains showed no clear response to ENSO.
climate change;
extreme precipitation;
spatiotemporal change;
north and south of the Qinling -Huaihe region
1 引言IPCC第五次评估报告指出, 气候系统变暖依然是毋容置疑的事实。年全球平均地表温度升温速率为0.12℃/10 a, 年为工业革命以来最暖的30年(; )。在气候变暖背景下, 全球多数区域极端降水呈现增加趋势, 但并未像极端气温具有全球一致性(), 美国、南非和加勒比等区域研究亦发现上述规律(; ; )。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)” 指出, 全球气候变化可能导致强降水等极端天气事件增加, 但是由于现阶段科学研究对此缺乏统一认识, 其结论可信度为中等()。近年来, 中国学者针对不同流域(; ; ; )、不同省域(; ; ; )以及不同自然区域(; ; )的极端降水事件进行了探索性研究, 提高了对中国极端降水变化的认识。在已有研究中, 针对秦岭— 淮河南北为整体的研究相对较少, 缺乏不同区域之间的综合对比研究, 多数研究关注点为区域内部关键流域或典型城市; 研究要素以气温、降水和径流等常规水文气象要素为主, 对极端降水事件关注相对较少(; ; ; ; ; )。秦岭— 淮河南北位于中国东部季风区, 是中国重要的地理生态分界线, 生态环境脆弱, 是气候变化的敏感区, 也是南水北调中线水源区和中国最大连片贫困区, 区域环境和发展对中国当代和未来环境和发展具有重要的意义()。在极端降水变化原因上, ENSO事件年际变化是引起中国降水异常的重要驱动因子。在厄尔尼诺发生次年夏季, 菲律宾附近对流活跃, 西北太平洋副热带高压偏北偏强, 长江流域和江南北部降水偏多, 江淮流域降水偏少(; )。但是, 东亚夏季风和ENSO之间的关系存在不稳定性, 这种不稳定性也是造成中国气候的季节— 年际预测困难的主要因素之一()。因此, 在区域尺度有针对性评估秦岭— 淮河南北极端降水事件变化趋势, 验证ENSO事件与极端降水事件的关系, 对科学适应和应对气候变化具有重要的现实意义。基于此, 本文在前期研究基础上, 利用全国0.5° × 0.5° 逐月降水格网数据和秦岭— 淮河南北135个气象站点逐日实测数据, 选取16个极端降水指数, 辅以趋势分析、Mann-Kendall检验及相关分析等气候诊断方法, 对近54年秦岭— 淮河南北极端降水变化时空变化特征进行分析, 探讨ENSO事件与极端降水变化的关系, 以期为区域重大工程建设及政府应对极端气候变化决策提供参考。2 研究区概况秦岭— 淮河南北作为中国东部南北地理生态分界线, 范围介于103.0° ~116.5° E、23.5° ~35.8° N。以秦岭— 淮河为界, 北部为暖温带, 南部为北亚热带, 位置与1月0 ℃等温线、800 mm等降水量线和2000 h日照时数等值线一致; 为了比较不同地理单元极端降水变化特征, 中国气候区划方案为依据, 将秦岭— 淮河以北地区分为两个子区域：关中平原(Ⅰ )和黄河下游(Ⅱ ); 秦岭— 淮河以南地区分为5个子区域：秦巴山地(Ⅲ )、淮河平原(Ⅳ )、四川盆地(Ⅴ )、巫山山区(Ⅵ )和长江下游(Ⅶ ), 空间分布如所示。图1Fig.1 图1 研究区气候区划及气象站点分布图Fig.1 Climate regionalization and distribution of meteorological stations in the study area3 数据来源与研究方法本文逐日降水站点数据和逐月降水格网数据均来源于中国气象科学数据共享服务网(http://www.cdc.), 以站点数据分析极端降水变化趋势特征, 以格网数据分析极端降水与ENSO事件的响应关系。其中, 中国地面降水月值0.5° × 0.5° 格点数据集(V2.0)由国家气象信息中心气象资料实验室建立, 该数据集基于中国2474个国家级地面气象站月降水量观测数据, 并利用ANUSPLIN软件的薄盘样条法和0.5° × 0.5° 的数字高程模型插值, 尽可能消除高程因素对降水空间分布的影响。厄尔尼诺指数(ONI)来源于美国国家航空航天局(http://www.swpc.noaa.gov), 并参照国家气候中心ENSO事件特征量综合表对厄尔尼诺和拉尼娜峰值年进行界定; 季节划分采用气象学标准：春季为3-5月, 夏季6-8月, 秋季9-11月, 冬季为12月-次年2月。极端降水指数定义是基于世界气象组织(WMO)气候委员会(CCI)、全球气候研究计划(WCRP)气候变化和可预测性计划(CLIVAR)气候变化检测、监测和指标专家组(ETCCDMI)确定的“ 气候变化检测和指标(Expert Team on Climate Change Detection and Indices)” , 该方法已被广泛应用于极端气候事件研究中。本文定义16个极端降水指标, 包括四大类：相对指数、绝对指数、强度指数和持续性指数()。表1Tab.1表1(Tab.1)
表1 16个极端降水指数定义
Tab.1 Definition of the 16 extreme precipitation indices指标类型极端降水指数英文缩写定义绝对指标雨日日数RD年内日降水日数/d痕雨日数Rr1年内日降水量≥ 1 mm日数/d小雨日数Rr5年内日降水量≥ 5 mm日数/d中雨日数Rr10年内日降水量≥ 10 mm日数/d大雨日数Rr25年内日降水量≥ 25 mm日数/d强度指标1日最大降水量Rx1day月内1日降水量最大值/mm5日最大降水量Rx5day月内连续5日降水量最大值/mm年降水强度SDII年内降水量与日降水量≥ 1 mm 日数之比/(mm/d)相对指标异常降水日数R95年内日降水量高于95%阈值日数之和/d极端降水日数R99年内日降水量高于99%阈值日数之和/d异常降水总量R95P年内日降水量高于95%阈值降水量之和/mm极端降水总量R99P年内日降水量高于99%阈值降水量之和/mm持续性指标连续无雨日数CDD年内日降水量连续< 1 mm日数最大值/d连续降水日数CWD年内日降水量连续≥ 1 mm日数最大值/d年降水量PRCPTOT年内日降水量≥ 1 mm降水量之和/mm生长季降水量GPRCP年内4-9月(生长季)降水量之和/mm
表1 16个极端降水指数定义
Tab.1 Definition of the 16 extreme precipitation indices由于线性回归要求时间序列符合正态分布, 且易受异常值干扰, Sen趋势度逐渐被引入气候趋势变化分析()。Sen+Mann-Kendall趋势度通过计算气候要素序列中值进行趋势分析, 并结合Mann-Kendall方法对趋势变化进行显著性检验, 可以在一定程度上提高气候变化趋势判断的准确性。Sen趋势度计算公式为： β=meanxj-xij-i, ?j> i式中：
β为极端降水序列的Sen趋势度, xi, xj为极端降水序列, i、j分别为极端降水序列年份。若
β值为正, 表示极端降水指数呈增加趋势;
β值为负, 则表示极端降水指数呈下降趋势。4 结果分析4.1 秦岭— 淮河南北降水变化背景年, 秦岭— 淮河南北降水空间格局呈现出“ 南多北少、东多西少” 特征, 秦岭— 淮河以南年降水量分别为：秦巴山地(819.1 mm)< 淮河平原(934.0 mm)< 四川盆地(1068.0 mm)< 长江下游(1237.5 mm)< 巫山山区(1319.6 mm); 秦岭— 淮河以北年降水量分别为：关中平原(602.1 mm)< 黄河下游(693.7 mm); 在长期变化趋势上, 长江下游地区降水呈增加的趋势, 上升速率为15.7 mm/10 a, 秦巴山地(-5.8 mm/10 a)、淮河平原(-8.0 mm/10 a)、关中平原(-16.0 mm/10 a)、黄河下游(-6.1 mm/10 a)、巫山山区(-28.1 mm/10 a)、四川盆地(-15.3 mm/10 a)降水均呈下降趋势()。从降水年代变化特征看, 20世纪70年代末, 由于东亚夏季风偏弱, 中国东部雨型由“ 北涝南旱” 转为“ 南涝北旱” , 黄河下游持续干旱和长江下游频发洪水均与此气候变化背景有关; 2000年后东部雨带有北移趋势, 黄河下游和淮河平原降水相对于前期呈增加趋势, 长江下游降水则持续偏低()。图2Fig.2 图2 年秦岭— 淮河南北降水变化特征 (图中蓝色阴影为降水偏多期, 红色阴影为降水偏少期, 降水距平时段为年)Fig.2 Variation of precipitation in north and south of the Qinling-Huaihe region,
(The blue shaded area shows positive p the red shaded area shows negative p the baseline period of precipitation is )4.2 秦岭— 淮河南北极端降水时空变化特征(1) 持续性指标。年, 秦岭— 淮河南北53.0%站点连续无雨日数(CDD)呈上升趋势, 整体上升速率为0.5 d/10 a, 远高于黄淮海流域变化速率0.05 d/10 a ()。在空间上, 秦巴山地所有站点均呈上升趋势, 黄河下游和四川盆地呈上升趋势站点比例分别为66.7%和50.0%, 长江下游(85.7%)、关中平原(66.7%)和巫山山区(60.0%)CDD呈下降趋势站点比重均超过50.0%; 81.0%站点连续降水日数(CWD)呈下降趋势, 整体下降速率为0.2 d/10 a, 高于黄淮海流域0.1 d/10 a(), 但低于中国南方地区0.5 d/10 a的下降速率()。空间上, 除长江下游、黄河下游和淮河平原部分站点呈上升趋势外, 其他各区均呈下降趋势; 59.0%站点生长季降水(GPRCP)呈下降趋势(-7.8 mm/10 a), 其中巫山山区所有站点均呈下降趋势, 长江下游(75.0%)和秦巴山地(53.8%)GPRCP呈现上升趋势。可以看出, 秦岭— 淮河南北持续性降水日数在下降, 持续性干旱日数在增加, 生长季降水以下降趋势为主, 区域面临干旱风险逐渐增大(, )。(2) 强度指数。在1日最大降水量(Rx1day)变化趋势上, 秦岭— 淮河南北有67.0%站点呈上升趋势, 整体上升速率为0.6 mm/10 a, 与黄淮海流域-0.6 mm/10 a下降趋势形成鲜明对比(), 而且上升区集中于长江下游、秦巴山地和四川盆地; 连续5日最大降水量(Rx5day)有54.0%站点呈上升趋势, 整体上升速率为0.2 mm/10 a, 低于南方地区1.7 mm/10 a上升速率(), 高于黄淮海流域1.9 mm/10 a的下降趋势()。就降水强度(SDII)而言, 秦岭— 淮河南北有74.0%站点呈上升趋势, 长江下游和秦巴山地降水强度增加趋势尤为明显, 上升趋势站点比重分别为92.9%和92.3%(, )。(3) 绝对指数。年, 秦岭— 淮河南北除大雨日数(Rr25)无明显变化趋势外, 绝对指数整体呈下降趋势, 下降速率分别为：Rr10(-0.3 d/10 a)< Rr5(-0.7 d/10 a)< Rr1(-1.4 d/10 a)< RD(-8.0 d/10 a), 雨日(RD)、痕雨日数(Rr1)和小雨日数(Rr5)变化趋势通过0.05显著水平检验。在空间上, 相对于东部平原区降水日数呈零散上升趋势, 西部山地区则整体呈现下降趋势, 其中关中平原、巫山山区和四川盆地所有站点均呈下降趋势(, )。(4) 相对指数。在异常降水日数(R95)变化趋势上, 秦岭— 淮河南北有59.0%站点呈下降趋势, 下降速率为0.3 d/10 极端降水日数(R99)则有63.0%站点呈上升趋势, 但其变化趋势并不显著; 异常降水总量(R95P)有45.0%的站点呈下降趋势, 下降速率为-4.3 mm/10 a, 极端降水总量(R99P)有72.0%站点呈上升趋势, 上升速率为2.2 mm/10 a。在空间上, 极端降水上升区主要集中于长江下游和秦巴山地, 极端降水下降区主要集中于关中平原和巫山山区(, )。图3Fig.3 图3 秦岭— 淮河南北极端降水变化时空分布特征 (为了统一图中颜色指示意义, 将连续无雨日数(CDD)变化趋势取反向, 图中红色渲染表示极端降水指标呈下降趋势, 区域趋于干旱; 绿色渲染表示极端指标呈上升趋势, 区域趋于湿润)Fig.3 Spatiotemporal variation of extreme precipitation in north and south of the Qinling-Huaihe region (In order to use a consistent color scheme, the trend of CDD was multiplied by -1; red color indicates a decreeing trend of extreme precip green color indicates a increasing trend of extreme precipitation index values)表2Tab.2表2(Tab.2)
表2 年秦岭— 淮河南北极端降水变化趋势及其站点比重
Tab.2 Trend of extreme precipitation and proportion of stations that showed the same trend in north and south of the Qingling-Huaihe region, 极端降水指标变化趋势站点比重/%极端降水指标变化趋势站点比重/%相对指标R99P2.2 mm/10 a72.0↑ 强度指标SDII0.1 mm/d74.0↑ R95P-4.3 mm/10 a45.0↓ Rx5day0.2 mm/10 a54.0↑ R990.0 d/10 a63.0↑ Rx1day0.6 mm/10 a67.0↑ R95-0.3 d/10 a59.0↓ 绝对指标Rr250.0 d/10 a57.0↑ 持续性指标PRCPTOT-7.7 mm/10 a64.0↓ Rr10-0.3 d/10 a70.0↓ GPRCP-7.8 d/10 a59.0↓ Rr5-0.7 d/10 a* 80.0↓ CWD-0.2 d/10 a* 81.0↓ Rr1-1.4 d/10 a* * 88.0↓ CDD0.5 d/10 a53.0↑ RD-8.0 d/10 a* * 100.0↓ 注：* 、* * 分别为通过0.10、0.05的显著性水平检验, 下同; ↑ 表示增加, ↓ 表示降低。
表2 年秦岭— 淮河南北极端降水变化趋势及其站点比重
Tab.2 Trend of extreme precipitation and proportion of stations that showed the same trend in north and south of the Qingling-Huaihe region, 4.3 ENSO事件对秦岭— 淮河南北极端降水变化的影响为年秦岭— 淮河南北各区极端降水指标与ENSO相关性分析。从表中可以看出, ①秦岭— 淮河南北7个分区140个极端指标中, 有100个指标与厄尔尼诺指数(ONI)呈负相关, 40个指标呈正相关, 极端降水指标以负相关为主。当发生厄尔尼诺事件时, 秦岭— 淮河南北降水普遍偏少, 降水强度和持续时间呈下降趋势, 拉尼娜事件与之相反; ②不同区域极端降水指标对ENSO事件响应具有差异, 关中平原和秦巴山区相关性显著性高于其他区域。③不同极端降水指标对ENSO的响应存在一致性, 除绝对指标正负相关区大致相当外, 相对指标、强度指标、持续性指标和季节指标均以负相关为主; ④结合显著性检验结果, 就各个区域而言, 当发生厄尔尼诺时, 黄河下游、关中平原、秦巴山地和四川盆地分别有17、19、19、18项极端降水指标呈下降趋势, 淮河平原有16项极端降水指标呈上升趋势, 而长江下游和巫山山区极端降水响应并无明显差异。表3Tab.3表3(Tab.3)
表3 年秦岭— 淮河南北极端降水与ENSO相关性分析
Tab.3 Correlation coefficients between extreme precipitation indices and ENSO in north and south of the Qingling-Huaihe region, 类别指标黄河下游淮河平原长江下游关中平原秦巴山地巫山山区四川盆地正相关区负相关区绝对指标RD-0.020.060.09-0.10-0.150.11-0.0834Rr1-0.060.020.06-0.29* * -0.27* * -0.01-0.27* * 25Rr5-0.090.000.08-0.25* -0.180.01-0.24* 34Rr10-0.160.020.09-0.31* * -0.210.05-0.1334Rr25-0.200.06-0.06-0.36* * -0.28* * -0.06-0.1516强度指标Rx1day-0.31* * 0.14-0.12-0.08-0.070.05-0.0625Rx5day-0.30* * 0.16-0.04-0.23* -0.200.03-0.1025SDII-0.26* 0.09-0.05-0.18-0.18-0.020.0016相对指标R75-0.140.00-0.02-0.35* * -0.20-0.04-0.1907R95-0.200.13-0.16-0.27* * -0.28* * -0.03-0.1416R95P-0.220.06-0.06-0.37* * -0.23* -0.03-0.1916R99P-0.28* * 0.14-0.17-0.24* -0.23* 0.02-0.1225持续指标CDD0.02-0.030.07-0.06-0.06-0.100.0934CWD0.03-0.030.13-0.21-0.30* * -0.09-0.29* * 25年降水-0.220.03-0.07-0.26* -0.200.00-0.24* 16GPRCP-0.220.06-0.02-0.34* * -0.24* 0.01-0.2125季节指标春季0.140.170.170.05-0.120.050.0161夏季-0.190.110.00-0.12-0.04-0.04-0.1716秋季-0.13-0.23* -0.16-0.31* * -0.23* -0.22-0.1707冬季-0.140.010.03-0.27* * 0.150.12-0.0943正相关指标数3168119240-负相关指标数1741219191118-100
表3 年秦岭— 淮河南北极端降水与ENSO相关性分析
Tab.3 Correlation coefficients between extreme precipitation indices and ENSO in north and south of the Qingling-Huaihe region, 相关分析主要表达ENSO与降水线性关系, 往往会低估其非线性信息, 利用合成分析进一步揭示秦岭— 淮河南北降水对ENSO变化的响应特征。由于极端降水指标相对较多, 受文章篇幅限制, 无法逐一展示各个极端指标与ENSO年代变化。通过构建极端指数相关矩阵, 发现年降水量具有很好的代表性, 除连续无雨日数(CDD)、秋季、冬季降水相关性较低外, 年降水变化与其他极端降水指标均高度相关(P< 0.001), 年降水量可作为典型指标, 较好地反映多数极端降水指标变化特征。依据国家气候中心ENSO事件特征量综合表, 年厄尔尼诺峰值年有：、、、、、和2009; 拉尼娜峰值年有：、、、、、和2011年。以年降水量作为气候平均态, 分别统计厄尔尼诺和拉尼娜峰值年四季和年降水正距平栅格数()。可以看出, 在厄尔尼诺峰值年, 秦岭— 淮河南北春季降水偏多, 夏季降水明显偏少, 秋季降水偏少, 冬季降水微弱增加, 全年以降水偏少为主; 在拉尼娜峰值年, 秦岭— 淮河南北春季降水偏少, 夏季降水微弱增加, 秋季偏多, 冬季降水偏少, 全年以降水偏多为主。表4Tab.4表4(Tab.4)
表4 秦岭— 淮河南北厄尔尼诺和拉尼娜峰值年降水异常偏多面积对比/%
Tab.4 Comparison of the spatial coverage of positive precipitation anomaly between El Niñ o and La Niñ o years in north and south of the Qingling-Huaihe region/%降水偏多栅格比重春季夏季秋季冬季全年厄尔尼诺年66.328.338.254.336.7拉尼娜年16.657.887.636.064.0厄尔尼诺年— 拉尼娜年82.636.285.955.833.7
表4 秦岭— 淮河南北厄尔尼诺和拉尼娜峰值年降水异常偏多面积对比/%
Tab.4 Comparison of the spatial coverage of positive precipitation anomaly between El Niñ o and La Niñ o years in north and south of the Qingling-Huaihe region/%为了更清楚展示ENSO事件对秦岭— 淮河南北降水影响的空间特征, 以厄尔尼诺峰值年降水减去拉尼娜年, 绘制中国厄尔尼诺峰值年降水异常分布图()。从可更清楚看出：在厄尔尼诺峰值年, 秦岭— 淮河南北春季降水偏多, 夏季、秋季, 冬季降水微弱偏多。其中, 全年和夏季降水偏多的区域主要分布四川盆地东部和长江下游。图4Fig.4 图4 年中国厄尔尼诺年四季和全年降水异常空间分布图Fig.4 Spatial pattern of seasonal and annual precipitation anomalies in El Niñ o years in China, 5 结论基于秦岭— 淮河南北逐日站点降水数据以及全国0.5° × 0.5° 逐月降水格网数据, 选取16项极端降水指标, 本文分析了年秦岭— 淮河南北极端降水变化时空变化特征, 探讨了ENSO事件与极端降水变化的关系, 得到初步结论如下：(1) 在降水时空变化特征上, 年秦岭— 淮河南北降水空间格局呈现出“ 南多北少、东多西少” 特征, 在长期变化趋势上, 黄河下游和长江下游降水呈增加趋势, 秦巴山地、淮河平原、关中平原、巫山山区和四川盆地呈下降趋势。20世纪70年代末, 由于东亚夏季风偏弱, 黄河下游和淮河平原持续干旱、长江下游降水增多; 2000年后中国东部雨带有北移趋势, 黄河下游、秦巴山地和淮河平原降水相对于前期呈增加趋势, 长江下游降水则持续偏低。(2) 在极端降水变化特征上, 年秦岭— 淮河南北绝对指标整体均呈下降趋势, 降水等级越降低, 下降趋势越显著; 强度指标以上升趋势为主, 东部平原区极端降水强度高于西部山地区; 在持续性指标中, 持续性降水(CWD)以下降趋势为主, 连续无雨日数(CDD)呈上升趋势; 亦即秦岭— 淮河南北降水变化更加极端, 弱降水日数下降, 强降水日数上升, 突发性强降水事件增多, 连续性干旱事件亦在增多; 在空间上, 秦巴山地、长江下游和黄河下游为极端降水强度上升, 关中平原、巫山山区和四川盆地为极端干旱强度上升。(3) 在极端降水影响因素上, 秦岭— 淮河南北极端降水与ENSO关系密切。当发生厄尔尼诺事件时, 秦岭— 淮河南北降水普遍偏少, 降水强度和持续性均呈现下降趋势, 拉尼娜事件与之相反。就不同季节而言, 在厄尔尼诺峰值年, 秦岭— 淮河南北春季降水偏多, 夏季和秋季降水异常偏少, 冬季降水小幅增加; 在拉尼娜峰值年, 秦岭— 淮河南北春季降水异常偏少, 秋季降水异常偏多, 夏季小幅增加, 冬季降水偏少。就不同区域而言, 在厄尔尼诺年, 黄河下游、关中平原、秦巴山地和四川盆地极端降水呈下降趋势, 淮河平原极端降水呈上升趋势, 长江下游和巫山山区响应并不明显。
The authors have declared that no competing interests exist.
白红英, 马新萍, 高翔, 等. 2012.
基于DEM的秦岭山地1月气温及0 ℃等温线变化[J]. [Bai H Y, Ma X P, Gao X, et al. 2012.
Variations in January temperature and
0℃ isothermal curve in Qinling Mountains based on DEM[J].
[本文引用:1]
陈丽娟, 袁媛, 杨明珠, 等. 2013.
海温异常对东亚夏季风影响机理的研究进展[J]. 应用气象学报, 24(5): 521-532. [Chen L J, Yuan Y, Yang M Z, et al. 2013.
A review of physical mechanisms of the global SSTA impact on EASM[J]. Journal of Applied Meteorological Science, 24(5): 521-532. ]
[本文引用:1]
[CJCR: 1.379]
慈晖, 张强, 张江辉, 等. 2014.
年新疆极端降水过程时空特征[J]. 地理研究, 33(10): 1881-1891. [Ci H, Zhang Q, Zhang J H, et al. 2014.
Spatiotemporal variations of extreme precipitation events within Xinjiang during [J]. Geographical Research, 33(10): 1881-1891. ]
[本文引用:1]
丁一汇, 王绍武, 郑景云, 等. 2013. 中国气候[M]. 北京: 科学出版社. [Ding Y H, Wang S W, Zheng J Y, et al. 2013. Climate in China[M]. Beijing, China: Science Press. ]
[本文引用:1]
董旭光, 顾伟宗, 孟祥新, 等. 2014.
山东省近50年来降水事件变化特征[J]. 地理学报, 69(5): 661-671. [Dong X G, Gu W Z, Meng X X, et al. 2014.
Change features of precipitation events in Shand ong Province from 1961 to 2010[J]. Atca Geographica Sinica, 69(5): 661-671. ]
[本文引用:1]
金祖辉, 陶诗言. 1999.
ENSO循环与中国东部地区夏季和冬季降水关系的研究[J]. [Jin Z H, Tao S Y. 1999.
A study on the relationships between ENSO cycle and
rainfalls during summer and
winter in eastern China[J].
[本文引用:1]
[CJCR: 1.948]
蒋冲, 朱枫, 杨陈, 等. 2013.
秦岭南北地区光合有效辐射时空变化及突变特征[J]. [Jiang C, Zhu F, Yang C, et al.
Distribution and
change of photosynthetically active radiation (PAR) in the northern and
southern regions of Qinling Mountains, China[J].
[本文引用:1]
[CJCR: 1.959]
李斌, 李丽娟, 李海滨, 等. 2011.
年澜沧江流域极端降水变化特征[J]. [Li B, Li L J, Li H B, et al. 2011.
Changes in precipitation extremes in Lancang River Basin during [J].
[本文引用:1]
[CJCR: 1.959]
李双双, 延军平, 万佳. 2012.
全球气候变化下秦岭南北气温变化特征[J]. [Li S S, Yan J P, Wan J. 2012.
The characteristics of temperature change in Qinling Mountains[J].
[本文引用:1]
马建华, 千怀遂, 管华, 等. 2004.
秦岭—黄淮平原交界带自然地理若干特征分析[J]. [Ma J H, Qian H S, Guan H, et al. 2004.
Some features of physical geography in transitional region between Qinling Mountains and
Huanghuai Plain[J].
[本文引用:1]
秦大河. 2014.
气候变化科学与人类可持续发展[J]. [Qin D H. 2014.
Climate change science and
sustainable development[J].
[本文引用:1]
[CJCR: 1.959]
任正果, 张明军, 王圣杰, 等. 2014.
年中国南方地区极端降水事件变化[J]. 地理学报, 69(5): 640-649. [Ren Z G, Zhang M J, Wang S J, et al. 2014.
Changes in precipitation extremes in south China during [J]. Atca Geographica Sinica, 69(5): 640-649. ]
[本文引用:1]
苏坤慧, 延军平, 白晶, 等. 2012.
河南省境内淮河南北气候变化的小麦适应性比较[J]. [Su K H, Yan J P, Bai J, et al. 2012.
Comparative studies on degree of adaption of wheat under climate change between areas south and
north of Huaihe River in Henan Province[J].
[本文引用:1]
[CJCR: 1.959]
王会军, 范可. 2013.
东亚季风近几十年来的主要变化特征[J]. [Wang H J, Fan K. 2013.
Recent changes in the East Asian monsoon.
[本文引用:1]
[CJCR: 1.948]
王艳姣, 闫峰. 2014.
年中国降水区域分异及年代际变化特征[J]. [Wang Y J, Yan F. 2014.
Regional differentiation and
decadal change of precipitation in China in [J].
[本文引用:1]
[CJCR: 1.959]
延军平, 郑宇. 2001.
秦岭南北地区环境变化响应比较研究[J]. [Yan J P, Zheng Y. 2001.
A comparative study on environmental change response over the northern and
the southern regions of the Qinling Mountains[J].
[本文引用:1]
周旗, 卞娟娟, 郑景云. 2011.
秦岭南北年的气温与热量资源变化[J]. 地理学报, 66(9): 1211-1218. [Zhou Q, Bian J J, Zheng J Y. 2011.
Variation of air temperature and
thermal resources in the northern and
southern regions of the Qinling Mountains from 1951 to 2009[J]. Atca Geographica Sinica, 66(9): 1211-1218. ]
[本文引用:1]
Cao L G, Pan S M. 2014.
Changes in precipitation extremes over the “Three-River Headwaters” region, hinterland
of the Tibetan Plateau, during [J].
[本文引用:1]
[JCR: 1.962]
Donat M G. Alexand er L V, Yang H. 2013.
Global land -based datasets for monitoring climatic extremes[J].
[本文引用:1]
[JCR: 6.591]
Du H, Xia J, Zeng S D. 2014.
Regional frequency analysis of extreme precipitation and
its spatial-temporal characteristics in the Huai River Basin, China[J].
[本文引用:1]
[JCR: 1.639]
Huang J, Sun S L, Xue Y, et al. 2014.
Spatial and
temporal variability of precipitation indices during
in Hunan Province, central south China[J].
[本文引用:1]
Managing the risks of extreme events and
disasters to advance climate change adaptation (SREX)[R]. Cambridge, UK: Cambridge University Press.
[本文引用:1]
Climate change 2013: the physical science basis: the summary for policymakers of the working group I contribution to the fifth assessment report[R]. Cambridge, UK: Cambridge University Press.
[本文引用:1]
Li Y G, He D M, Hu J M, et al. 2014.
Variability of extreme precipitation over Yunnan Province, China [J]. International Journal of Climatology, doi:
[本文引用:1]
Liu M X, Xu X L, Sun A Y, et al. 2014.
Is Southwestern China experiencing more frequent precipitation extremes[J]. Environmental Research Letters, 9(6): 1-14.
[本文引用:1]
[JCR: 3.582]
Monier E, Gao X. 2014.
Climate change impacts on extreme events in the United States: an uncertainty analysis[J]. Climatic Change, doi: .
[本文引用:1]
[JCR: 3.634]
Sen R S, Rouault M. 2013.
Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa[J].
[本文引用:1]
Sen P K. 1968.
Estimates of the regression coefficient based on Kendall's tau[J].
[本文引用:1]
[JCR: 1.834]
Stephenson T S, Vincent L A, Allen T, et al. 2014.
Changes in extreme temperature and
precipitation in the Caribbean region, [J]. International Journal of Climatology, 34(9): 2957-2971.
[本文引用:1]
[JCR: 2.886]
Zhang D D, Yan D H, Wang Y C, et al. 2014.
Changes in extreme precipitation in the Huang-Huai-Hai River Basin of China during [J]. Theoretical and
Applied Climatology , doi: .
[本文引用:5]
Zhao Y F, Zou X Q, Cao L G, et al. 2014.
Changes in precipitation extremes over the Pearl River Basin, Southern China during [J].
[本文引用:1]
[JCR: 1.962]
白红英, 马新萍, 高翔, 等. 2012.
基于DEM的秦岭山地1月气温及0 ℃等温线变化[J]. [Bai H Y, Ma X P, Gao X, et al. 2012.
Variations in January temperature and
0℃ isothermal curve in Qinling Mountains based on DEM[J].
Based on the records of January average temperature during 1959 to 2009 from 39 meteorological sites in the Qinling Mountains, we built the spatial database of January temperature by using space interpolation method based on DEM with the consideration of the influence of terrain factors on the temperature field. Also we extracted the 0℃ isothermal curve and examined the changes in the January average temperature and the 0℃ isothermal curve in the Qinling Mountains during the last 50 years. The January average temperature showed a rising trend at a rate of about 0.2℃/10a, and the 0℃ isothermal curve rose by 143.7 m averagely in the Qinling Mountains during the last 50 years. On longitude, the largest variation in the 0℃ isothermal curve was found in the region of 107&-109&E, where the height increased by 166.2 m during the last 50 years. This value is significantly higher than that in both eastern and western sections of Qinling M the temporal mutations point for the largest increase in the January temperature was found in 1993. The 0℃ isothermal curve after the mutations point was raised higher by 113.82 m averagely than before.
1. College of Urban and Environmental Science, Northwest University, Xi'an 710127, C 2. Public Meteorological Service Center of China Meteorological Administration, Beijing 100081, China
以秦岭南北39 个气象站点 年1 月平均气温为基础, 考虑地形因素对温度场的影响, 采取基于DEM的空间插值方法, 获取秦岭山地复杂地形下的1 月气温空间插值数据集, 并在此基础上提取1 月0℃等温线, 研究了50 年来秦岭山地1 月平均气温和1 月0℃等温线的变化情况。结果表明:秦岭南北1 月月均气温均表现为上升趋势, 温度变化倾向率约为0.2℃/10a;50 年来秦岭1 月0℃等温线发生了明显上升, 平均上升高度为143.7 m。从经度上看, 107&E~109&E 范围内1 月0℃等温线所处海拔高度的变化最为强烈, 50 年来上升高度达166.2 m, 明显高于东西两段;1993 年是秦岭地区气温明显上升的突变点, 气温突变后1 月0℃等温线比突变前平均上升了113.82 m。
金祖辉, 陶诗言. 1999.
ENSO循环与中国东部地区夏季和冬季降水关系的研究[J]. [Jin Z H, Tao S Y. 1999.
A study on the relationships between ENSO cycle and
rainfalls during summer and
winter in eastern China[J].
用中国160个站月平均降水量和赤道东太平洋Ni?o 3区海温资料研究了ENSO循环过程的不同位相与中国降水的关系。结果显示ENSO循环对中国冬、夏季降水丰或欠及时空分布有密切关系，ENSO发展年的夏季我国东部地区以雨量偏少为主，一些地区可偏少3～5成，多雨带位于江淮之间；ENSO恢复年的夏季长江及江南地区雨量偏多，其南北两边偏少；反ENSO年的夏季长江—黄河之间及东南部雨量偏少，其北边和西南正常偏多；在ENSO的准常态年夏季，长江以北为正偏差，江南除少部分地区外降水分布接近正常。还发现ENSO暖位相与中国冬季降水也有很好关系。由于本文用准常态年降水平均值代替通常的气候平均值，因而有利于更好地揭示ENSO与中国气候变化的关系。
蒋冲, 朱枫, 杨陈, 等. 2013.
秦岭南北地区光合有效辐射时空变化及突变特征[J]. [Jiang C, Zhu F, Yang C, et al.
Distribution and
change of photosynthetically active radiation (PAR) in the northern and
southern regions of Qinling Mountains, China[J].
Based on 52-year () daily data from 47 meteorological stations in the northern and southern regions of Qinling Mountains, the annual and seasonal Photosynthetically Active Radiations (PAR) were calculated with equations of Angstrom and FAO Penman-Monteith. The spatial distribution, change trends and their causes were analyzed and detected with spatial analysis method of spline interpolation, Pettitt abrupt change point detection method and correlation analysis between PAR and relative factors. The results were as followed: (1) the PAR became weaker from north part to south part, i.e. from northern region of Qinling Mountains (NQ), to southern region of Qinling Mountains (SQ), to Han River Basin (HB) and to Valleys of Ba and Wu Mountain Areas (VBW). PAR in summer was the highest, followed by spring, autumn and winter. The distribution of PAR in spring, autumn and winter showed the same spatial pattern as annual PAR , but in summer, PAR in NQ is also the highest, then HB and VBW, and SQ being the lowest one. (2) PAR declined significantly in past 52a, the declining rates became smaller from south and east part to north and west part of this region. Except for an insignificant increase in spring, PAR decreased in other seasons, and the rate in summer was fastest, followed by that in winter and autumn. The maximum and minimum PAR appeared in s and 2000s respectively in spring, summer and autumn. There were almost half of stations showing an increase of PAR mainly in west and central parts, and the other half stations showing decrease in spring. PAR of 79% of stations decreased in autumn, and the increasing stations were also located in west and central parts. PAR in summer and winter declined in most stations, and the decreasing rate was bigger in south part of Qingling Mountains than in north part. (3) 89% of stations had abrupt change points of yearly and summer PAR , and about 85% and 90% of them happened between 1979 and 1983, respectively. There were no obvious abrupt change points in spring or autumn. (4) Climate change (wind speed declining), fast urbanization and more aerosol emission from industrial production were the main reasons for the continuous decline of PAR , and the aerosol emitted from volcanoes was the main reason for fluctuation of PAR .
1. College of Resources and Environment, Northwest A & F University, Yangling 712100, C 2. Institute of Soil andWater Conservation, CAS and Ministry ofWater Resources, Yangling 712100, C 3. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
基于秦岭南北地区47个气象站年的逐日气象数据,通过Angstrom方程和Penman-Monteith公式计算了各站点的光合有效辐射( PAR ),并借助Spline空间插值、Pettitt突变点检验和相关分析等手段对 PAR 的空间分布、时空演变、突变特征及其可能成因进行了分析。结果表明:① 秦岭南北地区 PAR 的时间和空间分布特征明显,在空间上呈北高南低的分布格局;在季节分布上,夏季、春季、秋季、冬季依次减小。② 52年间,该地区年 PAR 整体呈显著下降趋势,下降速率由南向北,由东向西递减;时间变化方面,春季 PAR 呈现不显著的上升趋势,其余季节均呈下降趋势,夏季减小最快,其次为冬季,秋季最小。③ 该地区89%的站点年 PAR 存在突变,突变站点中的85%发生于年间;夏季89%的站点发生突变,突变站点中的90%发生于年间;冬季68%的站点发生突变,但突变时间同步性和一致性较差;春季和秋季突变现象不甚明显。④ 气候变化(风速下降)、城市化进程加快以及工业生产导致的气溶胶增多是导致 PAR 显著下降的主要原因,而火山爆发引发的气溶胶增加则是 PAR 波动的主要原因。
李斌, 李丽娟, 李海滨, 等. 2011.
年澜沧江流域极端降水变化特征[J]. [Li B, Li L J, Li H B, et al. 2011.
Changes in precipitation extremes in Lancang River Basin during [J].
Extreme precipitation is an important aspect of climate change. According to the estimation using the latest climate models, the extreme precipitation events will become frequent in a warming world. Significant increases of the very heavy precipitation and decreases of light and moderate precipitations have indeed been observed over most land areas of the globe in the last few decades. The Lancang River, with a relative altitude difference of about 5000 m, flows through 13 latitudes and 6 climatic zones. It is rarely seen in the world and has important scientific values for climatology, hydrology, geography and ecology. Since 1960, the basin has experienced a significant increase in temperature like most parts of the world. Studying the changes of extreme precipitation events in the basin in the context of global warming is of great importance. Based on a daily precipitation dataset of 35 meteorological observation stations distributed in and around the Lancang River basin, trends of precipitation amounts, precipitation days and daily precipitation intensity during a 45-year period () of 4 different classes ranging from less than 5, 5-10, 10-50 and larger than 50 mm were analyzed, and the precipitation frequency and the proportion of precipitation amount of each precipitation class were calculated. The result showed that all the indexes varied spatially, and for the basin as a whole, the frequency of the extreme events increased obviously. Analysis of a typical station indicated that the increase of extreme precipitation and the randomness of the climatic system might be closely related with each other.
1. Institute of Geographic Sciences and Natural Resources, CAS, Beijing 100101, C 2. Graduate University of Chinese Academy of Sciences, Beijing 100049, C 3. Princeton University, USA
极端降水事件是气候变化的一个重要方面。澜沧江流域纵贯13 个纬度，最大相对高差近5000 m，跨6 种气候带，是全球少见的南北向大江，它在气候、水文、地理、生态学等多方面都具有重要的科学研究价值。自1960 年以来，流域经历了显著的气温上升。探讨在气候变暖背景下这一复杂流域的极端降水变化具有重要意义。本文利用澜沧江流域及其周边35 个气象站 年的日降水资料，分析了小于5 mm、5～10 mm、10～50 mm以及大于50 mm 4 个不同量级降水的降水量、降水日数和日平均降水强度的变化趋势。并计算了每种量级降水占总降水量的百分比及降水频率。结果表明，各量级各项指标均存在明显的区域变化特征，流域总体上极端降水频率的增加态势明显。对典型地区站点分析表明，极端降水的增加可能与气候系统随机性变强有关。
李双双, 延军平, 万佳. 2012.
全球气候变化下秦岭南北气温变化特征[J]. [Li S S, Yan J P, Wan J. 2012.
The characteristics of temperature change in Qinling Mountains[J].
Qinling range has been recognized as the geo-ecological boundary between subtropical and warm-temperate zones in the eastern China, which is the advantage of regional area to study global change. This article, based on the meteorological data of the 61 meteorological stations in the northern and southern regions of the Qinling Mountains (), selecting the contour 1 000 m in southern piedmont as the ecological boundary line, analyzed the fundamental characteristics, spatio-temporal distribution and reasons of temperature change using methods of linear regression, Mann-Kendall mutation test, analysis of wavelets, Kriging interpolation and other Climate diagnosis method. The results show that the average temperature, extreme high and low temperature in the south and north Qinling Mountains were in increase trend, but there was a certain difference in the sharp change time and range. The tilt rate of annual average temperature in the south of Qinling Mountains is the lowest (0.121℃/10 a),then is in the north of Qinling Mountains (0.203℃/10 a),and they all lower than the other regions of China (0.26±0.032℃/10 a). The temperature mutation of the north of Qinling Mountains (1995) occurred earlier than that of the sorth (1998), which was later than the other regions of China (1993). Based the climate characteristics, it was found that the influence of climate change mainly reflects nature and human activities.
College of Tourism and Environment, Shaanxi Normal University, Xi'an, Shaanxi 710062,China
选取秦岭南麓1000m划分方案,运用气候倾向率、线性拟合方程、Mann-Kendall非参数检验、小波分析等气候数理统计方法,分析秦岭南北气温变化特征。结果表明：近50a秦岭南北气候变化具有同步性,增温趋势明显；在气温突变方面,关中地区气温突变(1995年)早于陕南(1998年)。通过近10a秦岭南北气温时空格局演变分析,认为秦岭地区气温变化符合全球变化规律,其变化是自然因素和人类活动共同作用的结果,在小尺度上人类活动干扰尤为明显(特别体现在快速城市化影响气温上升)。
马建华, 千怀遂, 管华, 等. 2004.
秦岭—黄淮平原交界带自然地理若干特征分析[J]. [Ma J H, Qian H S, Guan H, et al. 2004.
Some features of physical geography in transitional region between Qinling Mountains and
Huanghuai Plain[J].
The boundary of the transitional region between Qinling Mountains and Huanghuai Plain was divided first in this paper, then some features of physical geography in the transitional region were discussed. (1) The east boundary of the transitional region is at the contour about 100 m, and the west boundary is at the contour about 500 m. The area of the transitional region is about 26 000 km 2 ,which makes up 15.9% of total area in Henan Province.(2) The natural features in the transitional region possess transitional characters evidently in two directions, one is from the western mountain to the eastern plain and the other is from southern subtropical zone to northern temperate zone. (3) Torrential rain especially for strong torrential rain is frequent in the transition region, and there are many torrential rain centers, such as Lushan torrential rain center, Biyang torrential rain center, and so on. A majority of torrential rain is distributed among 100-200 m above sea level. (4) The winter temperature at 100-400 m above sea level in the transitional region is not only higher than in Huanghuai Plain where its altitude is lower than the transition region's, but also higher than in Qinling Mountains where its altitude is higher than the transitional region's. The highest temperature in January appears at 350-400 m above sea level in the transitional region. The warmer belt in the transitional region is called warm slope belt, of which thickness varies from 100 m to 250 m above sea level. (5) Torrential rain and warm slope belt in the transitional region were formed by atmospheric circulation and local terrain. Frequent torrential rain and warm slope belt had tremendous influence on soil properties, plant distribution and local climate in the transitional region.
College of Environment and Planning, Henan University, Kaifeng, Henan 475001
文章探讨了秦岭-黄淮平原交界带划分的依据和方法,然后就其自然地理过渡性、暴雨频繁发生和坡地暖带及其自然地理效应进行讨论。研究表明:交界带自然地理要素不仅具有西部山地和东部平原之间的过渡性,而且北亚热带和暖温带地理成分在这里彼此交汇。交界带暴雨频繁,且以大暴雨为主,集中分布在海拔100~200 m之间。交界带冬季气温高于平原0.5~0.8℃,1月最高气温出现在海拔350~400 m之间,形成特有的坡地暖带,暖带厚度100~250 m。交界带暴雨频繁和暖坡效应是大气环流和交界带地貌格局共同作用的结果,且对本区土壤发育和植物分布等具有重大影响。
秦大河. 2014.
气候变化科学与人类可持续发展[J]. [Qin D H. 2014.
Climate change science and
sustainable development[J].
Since the Fourth Assessment Report (AR4) was released by the Intergovernmental Panel on Climate Change (IPCC) in 2007, new observations have further proved that the warming of the global climate system is unequivocal. Each of the last three successive decades before 2012 has been successively warmer at global mean surface temperature than any preceding decade since -2012 was likely the warmest 30-year period of the last 1400 years. From 1998 to 2012, the rate of warming of the global land surface slowed down, but it did not reflect the long-term trends in climate change. The ocean has warmed, and the upper 75 m of the ocean warmed by more than 0.11℃ per decade since 1970. Over the period of 1971 to 2010, 93% of the net energy increase in the Earth's climate system was stored in the oceans. The rate of global mean sea level rise has accelerated, which was up to 3.2 mm yr-1 between 1993 and 2010. Anthropogenic global ocean carbon stocks were likely to have increased and caused acidification of the ocean surface water. Since 1971, the glaciers and the Greenland and Antarctic ice sheets have been losing mass. Since 1979, the Arctic sea ice extent deceased at 3.5% to 4.1% per decade, and the Antarctic sea ice extent in the same period increased by 1.2% to 1.8% per decade. The extent of the Northern Hemisphere snow cover has decreased. Since the early 1980s, the permafrost temperatures have increased in most regions. Human influence has been detected in the warming of the atmosphere and the ocean, changes in the water cycle, reductions in snow and ice, global mean sea level rise, and changes in climate extremes. The largest contribution to the increase in the anthropogenic radiative forcing was by the increase in the atmospheric concentration of CO 2 since 1750. It led to more than half of global warming since the 1950s (with 95 % confidence). It is predicted using Coupled Model Intercomparison Project Phase 5 (CMIP5) and Representative Concentration Pathways (RCPs) that the global mean surface temperature will continue to rise for the end of this century, the frequency of extreme events such as heat waves and heavy precipitation will increase, and precipitation will present a trend of "the dry becomes drier, the wet becomes wetter". The temperature of the upper ocean will increase by 0.6 to 2.0℃ compared to the period of 1986 to 2005, heat will penetrate from the surface to the deep ocean which will affect ocean circulation, and sea level will rise by 0.26 to 0.82 m in 2100. Cryosphere will continue to warm. To control global warming, humans need to reduce the greenhouse gas emissions. If the increase in temperature is higher than 2℃ than before industrialization, the mean annual economic losses worldwide will reach 0.2% to 2.0% of income, and cause large-scale irreversible effects, including death, disease, food insecurity, inland flooding and water logging, and rural drinking water and irrigation difficulties that affect human security. If taking prompt actions, however, it is still possible to limit the increase in temperature within 2℃. To curb the gradually out-of-control global warming and achieve the goal of sustainable development of the human society, global efforts to reduce emissions are needed.
1. State Key Laboratory of Cryosphere Science, Chinese Academy of Sciences, Lanzhou 730000, C 2. China Meteorological Administration, Beijing 100081, China
政府间气候变化专门委员会（IPCC）自2007 年发布第四次评估报告（AR4）以来，新的观测证据进一步证明，全球气候系统变暖是毋庸置疑的事实。2012 年之前的3 个连续10 年的全球地表平均气温，都比1850 年以来任何一个10 年更高，且可能是过去1400 年来最热的30 年。虽然 年全球地表增温速率趋缓，但还不能反映出气候变化的长期趋势。1970 年以来海洋在变暖，海洋上层75 m以上的海水温度每10 年升温幅度超过0.11℃； 年地球气候系统增加的净能量中，93%被海洋吸收。全球平均海平面上升速率加快， 年间高达3.2 mm/年。全球海洋的人为碳库很可能已增加，导致海洋表层水酸化。1971 年以来，全球几乎所有冰川、格陵兰冰盖和南极冰盖的冰量都在损失。其中1979 年以来北极海冰范围以每10 年3.5%~4.1%的速率缩小，同期南极海冰范围以每10 年1.2%~1.8%的速率增大。北半球积雪范围在缩小。20 世纪80 年代初以来，大多数地区的多年冻土温度升高。已在大气和海洋变暖、水循环变化、冰冻圈退缩、海平面上升和极端气候事件的变化中检测到人类活动影响的信号。1750 年以来大气CO 2 浓度的增加是人为辐射强迫增加的主因，导致20 世纪50 年代以来50%以上的全球气候变暖，其信度超过95%。采用CMIP5 模式和典型浓度路径（RCPs），预估本世纪末全球地表平均气温将继续升高，热浪、强降水等极端事件的发生频率将增加，降水将呈现“干者愈干、湿者愈湿”趋势。海洋上层的温度比 年间升高0.6~2.0℃，热量将从海表传向深海，并影响大洋环流，2100 年海平面将上升0.26~0.82m。冰冻圈将继续变暖。为控制气候变暖，人类需要减少温室气体排放。如果较工业化之前的温升达到2℃，全球年均经济损失将达到收入的0.2%~2.0%，并造成大范围不可逆的影响，导致死亡、疾病、食品安全、内陆洪涝、农村饮水和灌溉困难等问题，影响人类安全。但如果采取积极行动，2℃的温升目标仍可望达到。为遏制逐渐失控的全球变暖，需全球共同努力减排，以实现人类可持续发展的理想。
苏坤慧, 延军平, 白晶, 等. 2012.
河南省境内淮河南北气候变化的小麦适应性比较[J]. [Su K H, Yan J P, Bai J, et al. 2012.
Comparative studies on degree of adaption of wheat under climate change between areas south and
north of Huaihe River in Henan Province[J].
Degree of adaption is one of the key components of adaptability processes under climate change. In this paper, we established the concepts and methods of degree of adaption (DA) in order to comparably analyze the DA of wheat in area south and north of the Huaihe River in Henan Province. Results demonstrate that the climate dividing line is not the mainstream areas of Huaihe River, but the largest tributary of the area is located in were the further north, about 300 km away from the original zone. And the spatial variation of DA of winter wheat is approximately distributed around this area. The DA of the area, which is to the south of the dividing line of the Huaihe River, is 62.57%, which is higher than 56.81% in the northern area. Therefore there is still a large space which requires the human regulation and control to adapt the wheat to the climate change. And the pressure on human control in the northern area is greater than in the southern. As regards to the annual change, accompanied by the abrupt climate change in the 1980s, the temperature DA surged but the moisture DA plunged. In the following periods when the climate became stable, DA kept an increasing tendency. However the increasing speed of DA declined in the early 21st century when a plunge trend appeared, indicating that the negative impact on wheat from global warming has become increasingly prominent.
1. College of Tourism and Environment, Shaanxi Normal University, Xi'an 710062, C 2. Center of Climate in Henan Province, Zhengzhou 450003, C 3. The First Senior High School of Qinyang in Henan province, Qinyang 454550, China
适应度是气候变化下适应性研究的关键环节,本文提出气候变化适应度的概念及其定量评价方法,并对淮河南北的小麦适应度进行比较分析。结果表明,目前河南省境内的南北气候分界线并非淮河干流区,而是由原位置北移约300 km处的最大支流地带,冬小麦的适应度空间变化大致围绕该分界线呈经向分布。淮河分界线以南地域适应度为62.57%,高于以北地域的56.81%,研究结果表明,欲达到河南农业可持续发展,距离完全适应仍有较大空间需要人为调控,且北部相比较南部其调控压力更大。在年际变化上,随着20 世纪80 年代气候的突变,各地小麦温度适应度骤增,水分适应度骤减,之后随着气候的日趋稳定,各气候要素的适应度不断上升,但在21 世纪初上升速度下降,甚至有降低趋势,表明气候变暖的环境对小麦的负面影响日渐突出。
王会军, 范可. 2013.
东亚季风近几十年来的主要变化特征[J]. [Wang H J, Fan K. 2013.
Recent changes in the East Asian monsoon.
Studies on the recent changes of the summer and winter monsoons, with priority on decadal-interdecadal scales, are reviewed briefly in this paper. The major changes in the East Asian summer monsoon (EASM) include a weakening of the EASM and a shift in precipitation patterns at the end of 1970s; an increase in South China precipitation after ; a decrease in precipitation in the middle-and-lower reaches of the Yangtze River and an increase in precipitation in the Huaihe River valley after 1999; and instability in the relationship between the EASM and El Niño-Southern Oscillation (ENSO). The changes in the East Asian winter monsoon (EAWM) include a weakening of the EAWM and its interannual variability after the mid-1980s, an increase in winter snowfall in Northeast China after the mid-1980s, and a weakening of the EAWM-ENSO relationship after the mid-1970s. In addition, the impact of the autumn Arctic sea ice decline on the winter snow cover in the Northern Hemisphere is discussed. These changes in EASM and EAWM indicate that the extreme climate and phenology have been significantly altered.
本文简要综述了关于东亚夏季风和冬季风近几十年来的主要变化特征的若干研究结果,特别是关于其年代际变化方面。夏季风及夏季气候的主要变化特征有：1970年代末之后东亚夏季风的年代际时间尺度的减弱以及相应的我国夏季降水江淮流域增多而华北减少、1992年之后我国华南夏季降水增多、1999年之后我国长江中下游夏季降水减少而淮河流域夏季降水增多、东亚夏季风和ENSO之间的年际变化相关性存在不稳定性。而关于东亚冬季风与冬季气候的主要变化特征有：1980年代中期之后东亚冬季风及其年际变率减弱、1970年代中期之后冬季风和ENSO的年际变化相关性较弱、近年来的北极秋季海冰减少对北半球冬季积雪增多有显著贡献、东北冬季积雪在1980年代中期以后增多。与上述变化有关的极端气候和物候都发生了多方面的变化。
王艳姣, 闫峰. 2014.
年中国降水区域分异及年代际变化特征[J]. [Wang Y J, Yan F. 2014.
Regional differentiation and
decadal change of precipitation in China in [J].
Based on precipitation data from 1840 meteorological stations in China in , this study examines the regional differentiation of precipitation and characteristics of its change in the recent 50 years. Using the empirical orthogonal function (EOF) and rotated EOF (REOF) methods, precipitation in China is divided into 11 regions, which are grouped into four areas according to their geographic locations: East China area (North China, Huanghuai and Jianghuai, the middle and lower reaches of the Yangtze River, and Jiangnan and South China regions), Northwest China area (Midwest Inner Mongolia, western part of the Northwest China, and eastern part of the Northwest China regions), Southwest China area (southeastern part of the Southwest China, western part of the Southwest China, and northeastern part of the Southwest China regions), and Northeast China. Compared with the results of previous studies, precipitation regions derived with the REOF method in combination with detailed long time series precipitation data are consistent with the regional differentiation of actual precipitation and the climate division of China. The analysis shows that precipitation in the East China area changed in the late 1970s, from the late 1980s to the early 1990s, and in the beginning of the 21st century respectively, featuring recurrent south-north shifts of the rain belt in both directions, which were mainly influenced by the interdecadal variability of the East Asian summer monsoon and atmospheric circulation. Precipitation in the Northwest China area experienced a major change in the mid-1980s. The western part of the Northwest China area became wet compared to the dry period in the previous years, whereas the eastern part of the area became dry compared to the previous wet years. The decreasing precipitation in the eastern Northwest China area was related to the continually weakening of the East Asia summer monsoon, while the increasing precipitation in the western Northwest China area were mainly due to the anomalous high moisture transport from the Arabia Sea and the Caspian Sea. Precipitation in the Northeast China area underwent similar abrupt changes in the early 1980s and the late 1990s respectively-it changed from the previous near normal level to high in the early 1980s, and from high to low in the late 1990s. The changes were influenced by the East Asian summer monsoon on the one hand, and related to the anomalous moisture transport form the Northwest Pacific Ocean on the other. Evident changes in precipitation have been detected over each region in the Southwest China area-precipitation changes over the western and northeastern parts of this region were in opposite directions before 2000. Precipitation in the Southwest China area is not only influenced by the terrain of the Tibetan Plateau, but also affected by the East Asian monsoon and the subtropical high, which cause complicated changes in precipitation of the area.
1. National Climate Center, China Meteorological Administration, Beijing 100081, C 2. Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China
利用 年中国1840 个台站年降水量数据,采用经验正交函数(EOF)和旋转经验正交函数分解方法(REOF)对降水进行分区,并对各区降水的变化特征进行了研究。结果表明:基于多站点资料结合REOF方法实现的降水分区与中国降水实际区域分异特征比较符合,并与中国气候区划相一致。中国各区降水变化特征分析表明,东部各区降水在20 世纪70 年代末、80 年代末-90 年代初和21 世纪初发生雨带的南北移动过程,其中夏季雨带的移动主要受东亚夏季风和大气环流年代际变化的影响。西北地区降水以 年为突变年,西北西部地区降水由前期偏少转为偏多,主要与来自阿拉伯海和里海异常偏多的水汽输送有关;西北东部地区降水由前期偏多转为偏少,主要与季风的年代际减弱有关。东北地区降水在80 年代初由前期接近正常转为偏多,90 年代末降水由前期偏多转为偏少,主要与季风和西北太平洋水汽输送的年代际变化相关。西南部各区降水阶段性变化明显,2000 年以前西南东北部地区降水与西部地区基本呈反向变化,主要受青藏高原地形、东亚季风和副热带高压等因素的影响,降水阶段性变化明显、成因复杂。
延军平, 郑宇. 2001.
秦岭南北地区环境变化响应比较研究[J]. [Yan J P, Zheng Y. 2001.
A comparative study on environmental change response over the northern and
the southern regions of the Qinling Mountains[J].
Based on the data up to 1999 from the hydro-climatological departments, this paper analyzes the climatic dividing implications of Qinling Mountains in regional response to the process of global warming, due to which the Grades of Dryness/wetness (GDW) in 100-year scale show that the northern region has entered an arid period, and the southern, a humid period. At decade scale, the D-value of annual average air temperature over Southern Shaanxi (Hanjiang Valley) and Central Shaanxi Plain (Guanzhong Plain) has narrowed, i.e. the former with slight change and the latter with rapid increase in temperature. Both regions are arid with decease in precipitation D-value, namely, the plain becomes warmer while the south drier. Qinling Mountains play a predominant role in the climatic dividing. The runoff coefficient (RC) of Weihe River decreases synchronously with that of Hanjiang River due to climate warming . The RC of Weihe dropped from 0.2 in the 1950s to less then 0.1 in the 1990s.Weihe valley (Guanzhong Plain) is practically an arid area as a result of the shortage of water .The successive 0.5 and 1.0℃ temperature anomaly over China marks, perhaps, the important transition period in which the environment becomes more vulnerable than before .The study shows the obvious trend of environmental aridity, which is of help to the understanding of regional response to the global climate change.
1. College of Tourism and Environment, Shaanxi Normal University, Xi'an 710062, C 2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
利用气象水文部门截止1999年的气象水文实测数据,计算分析在气候变暖过程中中国秦岭具有的区域响应分界意义。由于气候变暖,在百年时间尺度上,通过旱涝指数分析证明秦岭以北进入干旱期,秦岭以南为湿润期;在10年时间尺度上,陕南气温变化较小,而关中气温增高较快,陕南与关中年均气温差值变小;关中和陕南降水量差值变小,二者同时干旱或陕南更干旱,反映出秦岭在气候变化中显著的分界作用。气候变暖,渭河与汉江年径流系数同步减小,其中渭河径流系数由50年代的02下降为90年代的01以下,渭河流域已变为少水带,即相当于气候上的干旱区。秦岭以北地区较其以南地区环境干暖化的趋势更明显,这对于认识全球变化的区域响应差异有参考意义。
... 董旭光等, 2014)以及不同自然区域(Cao et al, 2014 ...
Donat M G. Alexand er L V, Yang H. 2013.
Global land -based datasets for monitoring climatic extremes[J].
Donat, M. G. 1,2 ;Alexander, L. V. 1,2 ;Yang, H. 1,2 ;Durre, I. 3 ;Vose, R. 3 ;Caesar, J. 4 ;
... Du et al, 2014 ...
... Zhao et al, 2014)、不同省域(Huang et al, 2014 ...
... Li et al, 2014 ...
... Liu et al, 2014 ...
... Monier et al, 2014 ...
Sen R S, Rouault M. 2013.
Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa[J].
Hourly precipitation data from 1998 to 2007 spread across 102 stations in South Africa were analyzed for trends in extreme hourly precipitation events. The analyses were conducted at the seasonal scale for summer and winter for nine different variables. The results of our analysis showed predominantly positive trends during summer, with the strongest trends concentrated in the coastal areas in the southeast. The spatial variations in the trends were reversed during the winter season, with negative trends observed in the coastal areas and positive trends occurring in the interior. The summer patterns also overlap with areas experiencing overall increasing trends in annual extreme precipitation as well as a stronger diurnal cycle identified in recently published literature. (C) 2012 Elsevier Ltd. All rights reserved.
Sen Roy, Shouraseni 1 ;Rouault, Mathieu 2,3 ;
... 在气候变暖背景下,全球多数区域极端降水呈现增加趋势,但并未像极端气温具有全球一致性(Donat et al, 2013),美国、南非和加勒比等区域研究亦发现上述规律(Sen et al, 2013 ...
... 由于线性回归要求时间序列符合正态分布,且易受异常值干扰,Sen趋势度逐渐被引入气候趋势变化分析(Sen, 1968) ...
... Stephenson et al, 2014) ...
... Zhang et al, 2014 ...
... 05 d/10 a (Zhang et al, 2014) ...
... 1 d/10 a(Zhang et al, 2014),但低于中国南方地区0 ...
... 6 mm/10 a下降趋势形成鲜明对比(Zhang et al, 2014),而且上升区集中于长江下游、秦巴山地和四川盆地 ...
... 9 mm/10 a的下降趋势(Zhang et al, 2014) ...
... Zhao et al, 2014)、不同省域(Huang et al, 2014 ...
年秦岭—淮河南北极端降水时空变化特征及其影响因素
[李双双1,2, 杨赛霓1,2, 刘宪锋1,3]}
我要回帖
更多推荐
- ·17hfcn汉风西游官网 妖魔加点两速两血吗？哪个是速哪个是血？
- ·天天真人免费的斗地主主百度下载如何下载
- ·死亡空间重制版pcsteam游戏进不去怎么办办-steam进不去游戏解决方法
- ·迷你pc可以连电视吗？或者游戏本有必要外接显示器吗手柄，还是只能鼠标（我看ROG新出的那个，好像说可以连手柄...）
- ·求一款日本rpg十大良心回合制手游游戏
- ·辅警面试怎样回答问题不回答我的问题。？？？？？？？？？？？'
- ·形容幸福美满的成语人幸福的成语有哪些
- ·东莞铣床工资多少2016是做什么的
- ·行行重行行中有歧义句子的句子
- ·梦见大山倒塌了,钟自己响是什么成语
- ·大疆和法国派诺特无人机机可以飞多快，飞多远，飞多久
- ·读了天才之源这个阅读你在中国最大的收获获是什么
- ·不用在等我来爱你怎么我爱你用韩语怎么写写
- ·心落落,意茫茫,往事何堪哀拚却暗思量。意思
- ·go可属于前鼻音韵母有哪些音
- ·运动会开场表演词想要一个原创
- ·河南本科广播电视编导论文选题专业
- ·一块儿周长是6400米的正方形的面积换算公顷是几公顷。
- ·温度影响气温和降水的因素变化因素
- ·汽车技术专业专升本要读多少年有没有必要，下车间干多少年能成为主任
- ·基因工程靶向细胞疗法基因疗法
- ·唐正群这三个字网名是多少笔画
- ·珠海市第二人民医院普外科医生那个医生善长疝气手术
- ·make the case forconcrete的意思
- ·冬季是一年中昼短夜长的季节,英语翻译用非限定性定语从句句
- ·数字电子的一位有a,b两个输入怎么可理解输入?
- ·按课时收费的培训学校上课外辅导班收费标准有看护责任吗
- ·恒成立和有解问题存在
- ·市场经济剥削遵循平等交易,为什么还存在剥削
- ·大连市第七大连十四中学八七届毕业生同学录
- ·用两种方法求解置信度与置信区间间的通式
- ·农业汉唐慈善基金会骗局局
- ·66岁，男，mds病史 英文六年一直服用十一酮、环孢素。三天前突然咳血，ct检查:肺部有炎症、支气管扩张
- ·煤有6200吨30元一吨煤能发多少度电共要多少钱
