未来气候情景下中国东部极端降水和气温的危险性特征

基于BCC-CSM11模式降尺度预估结果,通过构建极端天气气候事件的危险性指数,考察和分析了中国东部极端降水和气温未来气候情景下可能的变化趋势和危险性分布格局。结果表明: 1）在中等排放情景（RCP4.5）下,近期（2021—2050年）极端降水和极端高温危险性呈现增强趋势,危险性指数增幅分别约为2%和10%,而极端低温危险性则呈减弱趋势,危险性指数降幅约为4%。21世纪末期（2070—2099年）,极端降水和气温危险性均基本保持现有水平,未有明显趋势。在高等排放情景（RCP8.5）下,极端降水和极端高温危险性将持续增强,至21世纪末危险性指数增幅分别约为5%和60%;极端低温危险性持续减弱,危险性指数降幅约为5%。2）在未来气候情景下,中国东部极端高温的危险性以全域持续增强为主要特征,特别是西南地区、长江以南地区和东南沿海危险性增强最为显著。至21世纪末,在高排放情景下的危险性指数增幅为30%—60%。极端降水危险性在黄河上游、长江上游和下游以及东北地区中南部等地区呈增强趋势,危险性指数增幅为3%—5%。极端低温危险性全域呈减弱趋势,至21世纪末期高等排放情景下的危险性指数最高降幅为7%—9%。     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

应用NASA MERRA再分析资料对一次高原切变线的诊断分析

高原切变线是影响青藏高原及其下游地区重要的降水天气系统,也是高原气象学研究的重点和热点。本文回顾了近10 a高原切变线的研究进展,包括高原切变线的时空分布及其与暴雨的关系、高原切变线的结构特征及演变机制、高原切变线与高原低涡的相互作用等。在此基础上,对未来高原切变线研究的主要方面进行了展望,以期加深对高原切变线的认识,为青藏高原及其下游地区灾害性天气研究和预报预警提供参考依据。

     

Recent trends in observed temperature and precipitation extremes in the Yangtze River basin,China

Summary The present study is an analysis of the observed extreme temperature and precipitation trends over Yangtze from 1960 to 2002 on the basis of the daily data from 108 meteorological stations. The intention is to identify whether or not the frequency or intensity of extreme events has increased with climate warming over Yangtze River basin in the last 40 years. Both the Mann-Kendall (MK) trend test and simple linear regression were utilized to detect monotonic trends in annual and seasonal extremes. Trend tests reveal that the annual and seasonal mean maximum and minimum temperature trend is characterized by a positive trend and that the strongest trend is found in the winter mean minimum in the Yangtze. However, the observed significant trend on the upper Yangtze reaches is less than that found on the middle and lower Yangtze reaches and for the mean maximum is much less than that of the mean minimum. From the basin-wide point of view, significant increasing trends are observed in 1-day extreme temperature in summer and winter minimum, but there is no significant trend for 1-day maximum temperature. Moreover, the number of cold days ≤0 °C and ≤10 °C shows significant decrease, while the number of hot days (daily value ≥35 °C) shows only a minor decrease. The upward trends found in the winter minimum temperature in both the mean and the extreme value provide evidence of the warming-up of winter and of the weakening of temperature extremes in the Yangtze in last few decades. The monsoon climate implies that precipitation amount peaks in summer as does the occurrence of heavy rainfall events. While the trend test has revealed a significant trend in summer rainfall, no statistically significant change was observed in heavy rain intensity. The 1-day, 3-day and 7-day extremes show only a minor increase from a basin-wide point of view. However, a significant positive trend was found for the number of rainstorm days (daily rainfall ≥50 mm). The increase of rainstorm frequency, rather than intensity, on the middle and lower reaches contributes most to the positive trend in summer precipitation in the Yangtze.     

北京地区夏季极端降水变化特征及城市化影响

利用1981-2016年京津冀地区174个国家站逐日降水资料,采用百分位方法和线性倾向估计方法对京津冀地区极端降水的时空分布特征及演变趋势进行了分析。结果表明：（1）对于京津冀地区极端降水空间分布,不同百分位降水阈值表现为一致的分布特征,年平均极端降水量、平均极端降水强度与百分位极端降水阈值分布大体一致,而年平均极端降水日数的分布则与其相反。（2）年平均极端降水量在103.6~259.1 mm之间,年平均极端降水日数在3.0~4.0 d之间,平均极端降水强度在大雨到暴雨之间,极端降水量对总降水量贡献达28%以上。（3）极端降水总站次和极端降水日数年变化趋势一致,7月、8月和10月是极端降水较活跃月份。（4）在36 a期间,年平均极端降水量、年平均极端降水日数、平均极端降水强度以及极端降水量对总降水量贡献的变化趋势分布情况基本一致,呈减少趋势的站点均相对较多,年平均极端降水量增减幅度较大,年平均极端降水日数变化在1 d·（10 a）^-1以内,平均极端降水强度和极端降水量对总降水量贡献减少趋势相对明显。

     

近20年中国气象灾害损失的初步分析

采用全国气象部门收集的县（区）域行政单元灾情普查资料,结合全国气象站点降水观测资料,分析了1984—2008年中国暴雨及其引发的洪涝灾害的时空演变特点及灾害损失情况,揭示了气候变化及人类活动双重作用下中国暴雨洪涝灾害变化趋势和演变特点,以及暴雨洪涝灾害影响的时空差异性。结果表明：近25 a来中国暴雨日数总体上稍有增加,暴雨强度和暴雨天数的空间分布均表现为南方高于北方,东部高于西部的特点,20世纪90年代中后期为中国暴雨高发期。研究时段内,中国暴雨洪涝灾害造成的直接经济损失呈增加趋势,但直接经济损失占当年GDP的比例则呈下降趋势,平均每年经济损失约为573亿元人民币,损失较高的地区主要集中在中国南方地区,县域年平均损失超过2 000万元的县约占15%,其中有34个县超过亿元。受灾人口呈增加趋势,但因灾死亡人口呈下降趋势;暴雨洪涝灾害对农作物受灾面积和绝收面积的影响均呈微弱上升趋势,年平均作物受灾面积近9.00×10⁶ hm²,作物绝收面积为1.27×10⁶ hm²。

     

Compound summer temperature and precipitation extremes over central Europe

Theoretical and Applied Climatology - Reliable knowledge of the near-future climate change signal of extremes is important for adaptation and mitigation strategies. Especially compound extremes,...     

1951-1990年中国极端气温变化分析

利用1975-2014年安徽省77个观测站的日最高温度、最低温度和平均气温资料,对近40 a极端温度事件的时空分布特征进行分析。结果表明：安徽省冬季极端低温事件的发生频次分布,总体呈北多南少,地区差异较大,极端低温事件发生次数最多的是宿州萧县。近40 a间冬季的极端低温事件发生减少趋势显著,与冬季平均温度的显著上升相对应。年极端最低温度年际变化趋势不明显,且极端低温的发生频次与强度并不对应。夏季极端高温事件发生频次较多区域为江南。1975-2014年,夏季极端高温事件发生呈整体增多趋势,但趋势不显著。年极端最高温度的时间序列,与极端高温事件发生频次的时间序列是相对应的,呈现明显的正相关。从MK突变上看,年极端低温和高温事件发生均存在突变。分析合成环流场发现,冬季极端冷事件发生时,亚洲中高纬度环流的经向度明显增强;夏季极端暖事件的发生与副高的明显西伸增强维持有关。

     

长江流域极端降水过程事件的年内分布特征

基于1960-2016年乌江流域41个气象站的逐日降水观测资料,利用线性倾向估计、滑动平均、累积距平等方法计算趋势系数和气候趋势,分析了研究时段内乌江流域年暴雨等级面雨量、年平均最大日降水量、年平均极端持续强降水次数和对应降水量的时空分布特征,分析表明：（1）乌江流域年暴雨等级面雨量和日数呈显著增加趋势（均通过α=0.05显著性水平检验）,而暴雨强度呈不显著性增加趋势;5-10月各旬暴雨等级面雨量及日数变化基本一致,5月中旬至8月上旬呈单峰型分布,暴雨强度呈波动增减分布。（2）近57 a乌江流域年平均最大日降水量年代际变化比较明显。（3）乌江流域发生极端持续强降水年平均次数呈不显著的减少趋势,但极端持续强降水量呈不显著的增加趋势。采用耿贝尔极值Ⅰ型分布法计算了乌江流域5个代表站不同重现期日最大降水量值,发现不同站点日极端最大降水量重现期水平差异明显,重现期时间尺度存在临界点,约为50 a。

     

中国近50 a极端降水事件变化特征的季节性差异

强降水极易造成暴雨灾害,尤其是突发性强的短时强降水,动态监测、影响评估和风险预估是灾害防御的重要手段。但目前气象服务业务中,强降水的定量评估和风险预估还是以天为单位,现代气象服务精细化的需求迫切要将时间分辨率提升至小时尺度。本文利用1951-2018年国家气象观测站小时降水观测资料,从小时尺度界定站点、大区域、小区域降水过程的辨识方法。基于改进的降水过程综合强度评估方法,在概率密度分布的基础上,重新划分了极端、特强、强、较强、中等五个等级的降水过程综合强度指数。检验论证显示,基于小时分辨率降水过程的自动提取和评估方法合理,具有可操作性,能够对过程性降水、短时降水过程动态评估和预评估,可实时支撑气象服务业务,提升气象防灾减灾能力,也为后续开展短时强降水影响评估和风险预估建立基础。

     

西南地区未来极端降水增加将导致其人口暴露风险加剧

基于CN05.1观测数据和一套经过降尺度偏差校正处理的模式(NEX-GDDP-CMIP6)数据,结合泰勒图、GEV极值拟合等方法,综合评估了模式对西南地区极端降水变化的模拟性能,并系统分析了未来西南地区不同重现期的极端降水演变趋势及其人口暴露度变化。结果表明,NEX-GDDP-CMIP6模式及其集合(N-CMIP6-MME)能够较好地再现观测极端降水的时空变化特征,且多模式集合结果优于大多数单个模式。未来西南地区绝大多数区域的降水和极端降水将持续增加,十年一遇、二十年一遇极端降水事件也呈增加趋势,使得未来西南地区人口暴露于不同重现期极端降水的风险进一步增加。相比十年一遇,重现期为20 a的极端降水事件增加速度更快,增加范围更广,模式一致性也更高,对应的人口暴露度增加幅度更大。到2050年左右,在SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5情景下二十年一遇的RX1day(RX5day)分别增加了175.2%(148.9%)、216.0%(162.4%)、210.9%(156.8%)和274.3%(207.1%),对应人口暴露度分别增加了129.1%(118.8%...     

Modelling daily temperature extremes: recent climate and future changes over Europe

Probability distributions of daily maximum and minimum temperatures in a suite of ten RCMs are investigated for (1) biases compared to observations in the present day climate and (2) climate change signals compared to the simulated present day climate. The simulated inter-model differences and climate changes are also compared to the observed natural variability as reflected in some very long instrumental records. All models have been forced with driving conditions from the same global model and run for both a control period and a future scenario period following the A2 emission scenario from IPCC. We find that the bias in the fifth percentile of daily minimum temperatures in winter and at the 95th percentile of daily maximum temperature during summer is smaller than 3 (±5°C) when averaged over most (all) European sub-regions. The simulated changes in extreme temperatures both in summer and winter are larger than changes in the median for large areas. Differences between models are larger for the extremes than for mean temperatures. A comparison with historical data shows that the spread in model predicted changes in extreme temperatures is larger than the natural variability during the last centuries.     

Risk assessment of precipitation extremes in northern Xinjiang,China

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity–humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity–humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites’ 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.     

Detection of trends in precipitation extremes in Zhejiang, east China

Extreme weather exerts a huge impact on human beings and it is of vital importance to study the regular pattern of meteorological and hydrological factors. In this paper, a selection of seven extreme indices is used to analyze the trend of precipitation extremes of 18 meteorological stations located in Zhejiang Province, east China using the Mann–Kendall test. Then the precipitation trends in the plum season (from May to July) and typhoon season (from August to October) are studied separately. The results show that the precipitation trend varies from east to west. There is a positive trend in the east and a negative one in the west. The largest part of Zhejiang Province shows a positive trend in heavy precipitation and the most significant upward trend is detected in Dinghai with 3.4?mm/year for precipitation on very wet days. Although the upward trend of extreme precipitation is not prevailing, the range of increase in specific areas is apparent, like Dinghai with 1.3?mm/year. Precipitation intensity exhibits an upward trend in most areas and a typical upward trend can be found in Dachendao, Tianmushan, and Yuhuan with 0.04, 0.02, and 0.05?mm/year respectively. Precipitation intensity in both plum and typhoon seasons has increased too, especially for the coastal stations.     

Changes in precipitation extremes over arid to semiarid and subhumid Punjab,Pakistan

Asymmetrical monsoons during the recent past have resulted into spatially variable and devastating floods in South Asia. Analysis of historic precipitation extremes record may help in formulating mitigation strategies at local level. Eleven indices of precipitation extremes were evaluated using RClimDex and daily time series data for analysis period of 1981–2010 from five representative cities across Punjab province of Pakistan. The indices include consecutive dry days, consecutive wet days, number of days above daily average precipitation, number of days with precipitation ≥10 mm, number of days with precipitation ≥20 mm, very wet days, extremely wet days, simple daily intensity index, maximum 1-day precipitation quantity, maximum 5 consecutive day precipitation quantity, and annual total wet-day precipitation. Mann-Kendall test and Sen’s slope extremes were used to detect trends in indices. Droughts and excessive precipitation were dictated by elevation from mean sea level with prolonged dry spells in southern Punjab and vice versa confirming spatial trends for precipitation extremes. However, no temporal trend was observed for any of the indices. Summer in the region is the wettest season depicting contribution of monsoons during June through August toward devastating floods in the region.