1961—2014年中国东部地区夏季极端降水事件时空变化特征

基于我国东部地区438站1961—2014年逐日降水资料,选取世界气象组织定义的最大1日降水量RX1day、最大5日降水量RX5day、持续降水日数CWD和日降水强度SDII 4个极端降水指标,采用面积加权法对中国东部地区的极端降水事件进行了季节尺度的时空变化特征的研究。结果表明：夏季极端降水指数的长期变化趋势显示,除CWD整体呈减少趋势外,RX1day,RX5day和SDII在我国黄河以南均呈现增加的趋势,而在北部以减少趋势为主。夏季极端降水指数随时间的变化表明,RX1day,RX5day和SDII整体呈现出增长的趋势,CWD则表现为减小的趋势。     

1971~2020年藏东南极端降水指数的时空变化特征

基于1971~2020年藏东南4个气象站逐日降水量资料,选取最大1日降水量（RX1day）、最大5日降水量（RX5day）、降水强度（SDII）、中雨日数（R10mm）、大雨日数（R20mm）、连续干燥日数（CDD）、连续湿润日数（CWD）、强降水量（R95pTOT）、极强降水量（R99pTOT）和年总降水量（PRCPTOT）共10个极端降水指数,采用线性趋势、Mann-Kendall非参数检验、R/S趋势分析、Morlet小波等方法,分析了藏东南极端降水指数的时空变化特征及其与大气环流指数、太阳黑子、海温指数之间的关系。结果表明:1971~2020年藏东南各极端降水指数变化幅度不大;RX1day、R20mm、CWD、R95pTOP、PRCPTOP呈下降趋势,尤其是近30 a（1991~2020年）PRCPTOP减幅显著,达?38.43 mm·10a?1;其他指数趋于增加,以CDD增幅最大（1.31 d·10a?1）。年代际变化尺度上,极端降水指数在20世纪90年代为正距平,21世纪前10年为负距平。极端降水指数的Hurst指数大多表现为较强或强持续性,未来将保持近50 a以来的变化趋势,仅CDD在2002年发生了气候突变。极端降水指数大多存在显著的3~4 a振荡周期。除CDD、CWD外,其他极端降水指数之间具有显著的正相关关系;而各极端降水指数均与年降水量、汛期降水量存在显著的相关性。多个极端降水指数与大气环流指数的相关性不显著,只有RX1day、RX5day、R95pTOT与亚洲极涡面积指数有显著的负相关,RX5day还与西太平洋副高强度指数有显著的正相关。绝大多数极端降水指数与太阳黑子的相关性不显著,仅有CWD与之有显著的正相关。RX5day、PRCPTOT和CDD与赤道太平洋次表层海温指数存在显著的相关关系。RX5day与印度洋暖池面积和强度指数存在显著的正相关,CWD与西太平洋暖池面积指数为显著的负相关。      

基于气象台站的澜沧江上游极端气温与极端降水变化特性研究

基于流域内的3个气象站点1960-2020年逐日最高气温、最低气温和降水量等基础资料,采用线性倾向回归分析法、Mann-Kendall突变检验法和小波分析等方法进行研究,分析和揭示了澜沧江上游流域在时间尺度上的变化。研究结果表明：(1)在1960-2020年,澜沧江上游流域的极端气温暖昼日数(TX90P)和暖夜日数(TN90P)呈显著上升趋势,速率分别为1.6d/10a和2.7d/10a;冷昼日数(TX10P)和冷夜日数(TN10P)呈显著下降趋势,速率分别为1.2d/10a和2.7d/10a,而极端降水变化只有持续湿润指数(CWD)的变化趋势不显著,其余三个降水指标降水总量(PRCPTOT)、1日最大降水量(RX1day)、5日最大降水量(RX5day)都呈显著上升趋势,速率分别为18.8mm/10a、0.5mm/10a和0.8mm/10a。(2)澜沧江上游流域极端气温指数冷昼日数(TX10P)在1992年出现突变点,冷夜日数(TN10P)在1978-1993年间出先了连续突变现象,极端气温指数降水总量(PRCPTOT)在2000年以后发生突变,这也说明了在时间尺度上的变化明显。(3)在1960-2020年,澜沧江上游流域的极端气温和极端降水周期特征变化显著,均存在多时间尺度的特征,第一主周期主要在10-15a、15-20a和25-30a三个时间尺度范围内。     

欧亚大陆极端降水事件的区域变化特征

近年来,在全球变暖的背景下,极端气候事件特别是极端降水事件,发生频率愈发上升。本文使用美国气候预测中心提供的逐日降水资料,统计分析了1979—2018年期间欧亚大陆各个子区域极端降水事件的时空变化特征。结果表明:1)从气候态的空间分布特征来看,南欧、南亚、东南亚、东亚地区为欧亚大陆全年总降水量高值区,同时也是极端强降水频发地区;而东亚地区青藏高原、中国中西部至蒙古一带,南亚地区印度次大陆以及中亚、西亚等地的部分地区则是连续性干旱事件的高频区,极端强降水事件发生频次较少;2)在21世纪初之后,东南亚、南亚、东亚、北亚、西亚和南欧这6个地区的全年总降水量发生年代际增加,且在研究时段呈显著增加趋势。在过去近40 a,南亚、东亚和中亚的RX1day(日最大降水量)、RX5day(连续5 d最大降水量)、中雨日数(R10mm)、大雨日数(R20mm)自20世纪90年代中期年代际增加,且呈长期增加趋势。南亚、北亚、东亚、中亚这4个地区的最大连续干旱日数在20世纪80年代初显著增加,但长期趋势并不显著。需要指出的是,自2014年起极端强降水事件在东南亚、南亚和东亚地区持续增多,而连续性干旱事件在北欧地区持续增多。     

基于国家气象观测站逐日降水格点数据的交叉检验误差分析

利用2006-2008年2 403个国家气象观测站地面雨量计的逐日降水量资料,采用与网格点最近的观测站有、无降水确定该网格点有、无降水和Barnes插值方案确定网格点降水大小的混合插值方案,得到全国空间分辨率为0.1°×0.1°（约10km×10km）的逐日降水量格点数据,在此基础上通过交叉检验方法统计格点数据的误差,...     

RCPs情景下汉江流域未来极端降水的模拟与预估

采用应用于跨行业影响模式比较计划(ISIMIP)的5个CMIP5全球气候模式模拟的历史和未来RCP排放情景下的逐日降水数据,在评估模式对汉江流域1961—2005年极端降水变化特征模拟能力的基础上,进一步计算了RCP2.6、RCP4.5和RCP8.5排放情景下汉江流域未来2016—2060年极端降水总量(R95p)、极端降水贡献率(PEP)、连续5 d最大降水(RX5d)和降水强度(SDII),结果表明:RCP4.5情景下的极端降水指数上升最明显,R95p和RX5d分别较基准期增加12.5%和8.2%,PEP增加3.2个百分点,SDII微弱上升。在不同排放情景下,PEP均有一定的增幅,以流域西北和东南部增幅较大;R95p在流域绝大部分区域表现出一定的增加,且流域东南部和北部是增幅高值区;RX5d在RCP2.6和RCP4.5情景下整体表现为增加的特征,但在RCP8.5情景下整体表现为减少的特征。对极端降水预估的不确定性中,SDII的不确定性最小,RX5d的不确定性最大;不确定性大值区主要位于流域东部、东南部和西北部部分区域。     

祁连山南麓汛期降水时空分布特征研究

利用1961—2019年祁连山南麓12个国家气象站汛期(5—9月)逐日降水资料,采用线性趋势、相关分析、ArcGIS空间分析和Morlet小波分析对祁连山南麓汛期降水时空分布特征进行分析研究.结果表明:(1)祁连山南麓汛期降水量呈显著增加趋势,降水日数呈减少趋势,7月降水量最多,8月降水强度最大.(2)汛期降水量、降水...     

应用CGDPA评估中国大陆地区IMERG的降水估计精度

应用国家气象信息中心基于地面雨量计的逐日降水分析产品CGDPA (China Gauge-Based Daily Precipitation Analysis)为基准数据,采用定量和分类评分指标分析了2014年9月—2015年8月中国大陆地区全球降水观测GPM (Global Precipitation M easurement)多星集成降水产品IM ERG (Integrated M ulti-satellite Retrievals for GPM)的精度。结果表明:1) IMERG日平均降水量能够较好地反映我国降水量的空间分布特点(局部地区偏低),季节平均降水强度的空间分布与CGDPA具有较好的一致性(尤其中东部和南部)。2) IMERG与CGDPA日平均降水量的相关系数在大部分地区介于0. 2～0. 5,只有少数地区超过0. 6,局部地区甚至出现负相关。3) IM ERG在中国大陆东部的降水估计精度明显优于西部,但东部绝大部分地区IMERG日降水量比CGDPA偏低10%～30%,甚至更低。4) IMERG与CGDPA降水概率密度相差最大的是微量降雨,其次是中雨,其他降水强度则相差很小。5)各季节IMERG探测降水的准确率POD都比较低,空报率FAR则比较高,临界成功指数CSI也比较低。     

近42年辽宁极端降水事件分析

利用辽宁 51个台站的逐日降水资料 ,分别计算出 1961～2002年 51个台站的年降水量、年降水日数、年平均降水强度、年暴雨日数、年大暴雨日数、年最大连续降水量、年最长连续降水日数、年最长连续无降水日数的 8个时间序列 ,用极值法对上述时间序列极端偏多 (大)和极端偏少 (小) 2种极端情况的年际变化进行分析。结果表明 :辽宁年降水量极端偏小、降水日数极端偏少和连续无降水日数极端偏多均有增加的年际变化趋势。     

中国降水极值变化趋势检测

利用中国２９６个分布均匀的测站的逐日降水资料,研究了中国过去４５ａ中降水量、降水频率、降水强度等方面的极值变化趋势。结果表明,总体上讲,中国年降水量、１日和３日最大降水量以及不同级别的强降水总量没有发现明显的极端化倾向,但伴随着降水日数极端偏多的区域范围越来越小的变化趋势,平均降水强度极端偏高的区域范围表现为扩大的趋势。中国降水极值变化还反映出明显的区域性特点。在中国东部,平均降水强度极值出现的范围趋于扩大。如华北地区在年降水量明显趋于减少的同时,年降水量极端偏多的范围减少,１日和３日最大降水量、日降水≥５０ｍｍ和１００ｍｍ的暴雨日数极端偏多的情况也趋于减少,而平均降水强度极值显著增加。在年降水明显趋于增多的西北西部地区,降水日数的极值变化趋势不明显,但年降水量、１日和３日最大降水量以及日降水≥１０ｍｍ的降水总量极端偏多的区域范围均反映出趋于增加的变化趋势。     

CMIP6全球气候模式对中亚极端降水模拟能力的评估

本文基于NOAA再分析逐日降水数据和22个CMIP6模式的降水模拟数据,选取了6个极端降水指数,从气候态和相对变率两个角度对CMIP6模式在中亚地区极端降水方面的模拟能力开展了评估。结果表明,在气候态方面,中亚地区降水的空间分布表现为由西南向东北递增,其东南部山地迎风侧降水偏多;多模式集合对SDII(简单降水强度)和CDD(最大无雨期)模拟的平均误差分别为-5.43%和0.45%,对PRCPTOT(年总降水量)、R1mm(有雨日数)、Rx5day(最大连续五日降水)和CWD(最大雨期)的模拟结果存在明显高估,且在中亚东南部高海拔地区误差偏高。在相对变率方面,多模式集合模拟的中亚极端降水的相对变率偏小,其中对CWD的模拟效果相对较好,平均误差为-4.78%;对R1mm的模拟效果最差,平均误差为-36.16%。模式间进行比较,TaiESM1、EC-Earth3-Veg-LR和GFDL-ESM为22个CMIP6模式中模拟能力最好的前3个模式。     

7个IPCC AR4模式对中国地区极端降水指数模拟能力的评估及其未来情景预估

利用中国区域550个站点1961～2000年日降水量资料, 考察参与政府间气候变化委员会(IPCC)第四次评估报告的7个新一代全球模式及多模式集合对现代气候情景下(20C3M)5个极端降水指数的模拟能力, 同时进行中国区域未来不同排放情形下极端降水事件变化的预估, 结果表明: 最新全球模式能较好地模拟出极端降水指数气候场的空间分布及其中国区域的线性趋势, 且模式集合模拟能力优于大部分单个模式, 但在青藏高原东侧、 高原南部存在虚假的极端降水高值区, 模拟的东部季风区的极端降水强度系统性偏低, 区域平均序列年际变率的模拟能力也较低。中国地区21世纪与降水有关的事件都有趋于极端化的趋势, 极端降水强度可能增强, 干旱也将加重, 且变化幅度与排放强度成正比。     

Change in Extreme Climate Events over China Based on CMIP5

The changes in a selection of extreme climate indices(maximum of daily maximum temperature(TXx),minimum of daily minimum temperature(TNn),annual total precipitation when the daily precipitation exceeds the 95th percentile of wet-day precipitation(very wet days,R95p),and the maximum number of consecutive days with less than 1 mm of precipitation(consecutive dry days,CDD))were projected using multi-model results from phase 5 of the Coupled Model Intercomparison Project in the early,middle,and latter parts of the 21st century under different Representative Concentration Pathway(RCP)emissions scenarios.The results suggest that TXx and TNn will increase in the future and,moreover,the increases of TNn under all RCPs are larger than those of TXx.R95p is projected to increase and CDD to decrease significantly.The changes in TXx,TNn,R95p,and CDD in eight sub-regions of China are different in the three periods of the 21st century,and the ranges of change for the four indices under the higher emissions scenario are projected to be larger than those under the lower emissions scenario.The multi-model simulations show remarkable consistency in their projection of the extreme temperature indices,but poor consistency with respect to the extreme precipitation indices.More substantial inconsistency is found in those regions where high and low temperatures are likely to happen for TXx and TNn,respectively.For extreme precipitation events(R95p),greater uncertainty appears in most of the southern regions,while for drought events(CDD)it appears in the basins of Xinjiang.The uncertainty in the future changes of the extreme climate indices increases with the increasing severity of the emissions scenario.     

An intercomparison of model-simulated in extreme rainfall and temperature events during the last half of the twentieth century. Part 1: mean values and variability

In this study we examine the performance of eight of the IPCC AR4 global coupled climate models used in the WCRP CMIP3 Multimodel Dataset, as well as their ensemble mean, in simulating annual indices of extreme temperature and precipitation climate events in South America. In this first part we focus on comparing observed and modeled mean values and interannual variability. Two extreme temperature indices based on minimum temperature (warm nights and frost days) and three indices of extreme precipitation (R95t, R10 and consecutive dry days), obtained both from meteorological stations during 1961–2000 and model outputs, were compared. The number of warm nights are better represented by models than the FD. The interannual variability pattern is also in good agreement with the observed values. For precipitation, the index that is best represented by the models is the R95t, which relates the extreme precipitation to local climate. The maximum of dryness observed over the central Argentinian Andes or the extensive dry season of the Amazon region could not be represented by any model.     

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during1961–2005, the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5), are assessed in terms of spatial distribution and interannual variability. The CMIP6 multi-model ensemble mean(CMIP6-MME) can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature, and minimum daily minimum temperature. However, CMIP6-MME has difficulties in reproducing cold nights and warm days, and has large cold biases over the Tibetan Plateau. Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices. Compared to CMIP5, CMIP6 models show improvements in the simulation of climate indices over China. This is particularly true for precipitation indices for both the climatological pattern and the interannual variation, except for the consecutive dry days. The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME) to 79%(CMIP6-MME). The most striking feature is that the dry biases in southern China, very persistent and general in CMIP5-MME, are largely reduced in CMIP6-MME. Stronger ascent together with more abundant moisture can explain this reduction in dry biases. Wet biases for total precipitation, heavy precipitation, and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME, but smaller, compared to CMIP5-MME.     

Extreme climate events in China: IPCC-AR4 model evaluation and projection

Observations from 550 surface stations in China during 1961–2000 are used to evaluate the skill of seven global coupled climate models in simulating extreme temperature and precipitation indices. It is found that the models have certain abilities to simulate both the spatial distributions of extreme climate indices and their trends in the observed period. The models’ abilities are higher overall for extreme temperature indices than for extreme precipitation indices. The well-simulated temperature indices are frost days (Fd), heat wave duration index (HWDI) and annual extreme temperature range (ETR). The well-simulated precipitation indices are the fraction of annual precipitation total due to events exceeding the 95th percentile (R95T) and simple daily intensity index (SDII). In a general manner, the multi-model ensemble has the best skill. For the projections of the extreme temperature indices, trends over the twenty-first century and changes at the end of the twenty-first century go into the same direction. Both frost days and annual extreme temperature range show decreasing trends, while growing season length, heat wave duration and warm nights show increasing trends. The increases are especially manifested in the Tibetan Plateau and in Southwest China. For extreme precipitation indices, the end of the twenty-first century is expected to have more frequent and more intense extreme precipitation. This is particularly visible in the middle and lower reaches of the Yangtze River, in the Southeast coastal region, in the west part of Northwest China, and in the Tibetan Plateau. In the meanwhile, accompanying the decrease in the maximum number of consecutive dry days in Northeast and Northwest, drought situation will reduce in these regions.     

1980~2019年夏季青藏高原中东部极端日降水分布特征

基于中国气象局国家基准气象观测站逐日观测资料,采用百分位法对1980~2019年夏季青藏高原中东部地区极端日降水进行定义,分析了不同分位极端日降水的气候分布特征。结果表明:（1）青藏高原中东部夏季降水呈东多西少、中间多南北少的反位相分布特征,且存在显著的年际和年代际变化。（2）99%分位降水阈值普遍在24 mm/d以上,95%分位和90%分位降水阈值维持在12~20 mm/d,75%分位降水阈值则进一步下降至7~9 mm/d。（3）从长期变化趋势看,青藏高原中东部99%分位的极端日降水出现频次呈显著的上升趋势,其余几个分位则以下降趋势为主。（4）相较于99%和90%分位而言,95%分位在青藏高原中东部夏季降水中具有更为突出的贡献,且近40 a来99%分位的贡献在不断增加。（5）青藏高原中东部日降水量介于0.1~10.5 mm,但日降水量的频次波峰和总降水量的波峰位置存在差异,2.4~5.1 mm日降水量在青藏高原中东部降水中具有重要作用。      

Variability and trends in daily precipitation extremes on the northern and southern slopes of the central Himalaya

This study focuses on the precipitation extremes recorded on the northern and southern slopes of the central Himalaya, especially those documented at higher altitudes. Daily precipitation data recorded over a 35-year period at nine meteorological stations in the region were studied. We used the precipitation extreme indices delineated by the Expert Team on Climate Change Detection and Indices (ETCCDI). The spatial and temporal variations in these precipitation extremes were calculated. When regional patterns were investigated to detect any anomalies, only 1 of the 10 precipitation extreme indices from the southern slopes of the central Himalaya showed a statistically significant trend; none from the northern slopes of the central Himalaya highlighted a statistically significant trend. On the southern slopes, all indices increased, apart from the maximum 1-day precipitation (RX1) and simple daily precipitation intensity (SDII) indices. Indices such as the consecutive dry days (CDDs) and RX1 indices exhibited similar increases on both the northern and southern slopes of the central Himalaya. These results suggest that increases in precipitation have been accompanied by an increasing frequency of extremes over the southern central Himalaya. Nonetheless, no relation could be established between the precipitation extreme indices and circulation indices for higher altitudes.