NEX-GDDP降尺度数据对中国极端降水指数模拟能力的评估

利用1986—2005年中国地面气象台站观测的格点化逐日降水数据(CN05.1)评估了NASA高分辨率降尺度逐日数据集NEX-GDDP中21个全球气候模式在0.25?(约25 km×25 km)分辨率下对中国极端降水的模拟能力.选取年最大日降水量(RX1D)、年最大5 d降水量(RX5D)、湿日总降水量(PRCPTOT...     

1960-2005年长江中下游极端降水指数变化特征分析

本文利用长江中下游流域内的81个气象站,对长江中下游极端降水指数的时空变化特征进行分析.结果发现,在时间尺度上,长江中下游地区近46 a来极端降水指数呈上升趋势,其中降水强度上升趋势最明显,各个极端降水指数在年代际尺度上具有相同的变化特征,均存在着12 a左右的周期振荡,在年际尺度上,各极端降水指数变化周期并不一致.大雨日数与其他指数相比突变时间比较早,发生在1979年,其他几个指数突变时间比较接近,出现在1990年前后.在空间变化上,除极端湿天降水量在全区均为上升趋势外,其他几种极端降水指数在江苏东部地区、湖北西北部都存在着极端降水指数的负变化趋势,高值区主要分布在江西大部、湖北东南部、湖南东北部地区.     

Simulation of extreme precipitation over the Yangtze River Basin using Wakeby distribution

Based on the daily observational precipitation data at 147 stations in the Yangtze River Basin during 1960–2005 and projected daily data of 79 grid cells from the ECHAM5/ MPI-OM model in the 20th and 21st century, time series of precipitation extremes which contain AM (Annual Maximum) and MI (Munger Index) are constructed. The distribution feature of precipitation extremes is analyzed based on the two index series. Three principal results were obtained, as stated in the sequel. (i) In the past half century, the intensity of extreme heavy precipitation and drought events was higher in the mid-lower Yangtze than in the upper Yangtze reaches. Although the ECHAM5 model still can’t capture the precipitation extremes over the Yangtze River Basin satisfactorily, spatial pattern of the observed and the simulated precipitation extremes are much similar to each other. (ii) For quantifying the characteristics of extremely high and extremely low precipitation over the Yangtze River Basin, four probability distributions are used, namely: General Extreme Value (GEV), General Pareto (GPA), General Logistic (GLO), and Wakeby (WAK). It was found that WAK can adequately describe the probability distribution of precipitation extremes calculated from both observational and projected data. (iii) Return period of precipitation extremes show spatially different changes under three greenhouse gas emission scenarios. The 50-year heavy precipitation and drought events from simulated data during 1951–2000 will become more frequent, with return period below 25 years, for the most mid-lower Yangtze region in 2001–2050. The changing character of return periods of precipitation extremes should be taken into account for the hydrological design and future water resources management.     

2018年北京\

利用2010—2019年自动气象观测站逐小时降水资料,分析了近10 a浙江省极端短时强降水（1 h雨量≥50 mm或3 h雨量≥100 mm的降水）的时空分布特征,结果表明：（1）浙江省每年约有极端短时强降水169.8 h,主要分布在暖季（5—10月）及午后（14—21时）,东部沿海（包括东南沿海和杭州湾）是高发带。（2）极端短时强降水主要始于5月,由浙南逐渐向浙北伸展,7—9月对应站点基本覆盖全境,而8月影响范围最大,对应有站点逐月年均频数峰值1.3 h·a^-1,位于东南沿海,月平均强度峰值99.1 mm·h^-1,位于杭州湾,10月及以后降水向东部沿海收缩,过程趋于结束。（3）极端短时强降水午后高发且强度增大,影响范围最广,并在17时有年均频数日变化曲线峰值,达17.4 h·a^-1,同时午后东南沿海高频站点密集,占全省高频站数的83.2%,杭州湾降水强度增加,50%以上的站点超过57.6 mm·h^-1。（4）地形地貌与极端短时强降水的空间分布关系密切,东南沿海处的海陆交界下垫面及喇叭口地形有助于极端短时强降水的发生,而杭州湾洋面向内陆伸展的喇叭口地貌对降水效率的提高有促进作用。

     

中国南方降水及其极端事件的动力-统计相结合延伸期预报

延伸期预报是无缝隙预测系统中的薄弱环节,如何提高灾害天气过程的延伸期预报技巧是国际热点及前沿问题。本研究基于2005年12月—2014年8月的观测/再分析资料,通过奇异值分解方法,揭示了与中国南方低频降水变化高度耦合的热带对流和中纬度波列信号。利用中国气象局参加国际次季节至季节预报计划模式（BCC-CPS-S2Sv2模式,简称BCC S2S模式）的回报数据,对中国南方低频降水异常场进行统计降尺度,构建了一套动力-统计相结合的延伸期降水预测模型。独立预测时段（2014年12月—2019年8月）的结果表明,BCC S2S模式可以提前10—15 d预报中国南方大部分区域的异常降水;提前15—20 d以上预报时,动力-统计结合预报模型对冬季（夏季）华南沿海地区（长江以北地区）的降水时间演变、降水空间分布及极端强降水事件的预报技巧均优于BCC S2S模式。文中提出的思路和方法可广泛应用于其他区域气象要素和极端天气事件的延伸期预报。     

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。

     

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。

     

Predictability of a large-scale flow conducive to extreme precipitation over the western Alps

Summary The quality of numerical weather prediction has improved considerably since its beginning. Over the last decade, in the North Hemisphere and more specifically over Europe, the accuracy of global numerical weather predictions of 500 hPa height has increased by one day. However this remarkable achievement has to be considered true for average conditions since it is computed over many days/seasons with very different flow patterns and atmospheric states. It is known that atmospheric predictability and model errors are highly flow-dependent therefore an increase in skill for average conditions may not imply the same improvements in specific conditions. Moreover the potential value of numerical weather prediction is perceived to be higher in some specific conditions, like high-impact weather events. There is therefore a growing need to know the forecasting accuracy of significant weather events, something that cannot be easily inferred through average scores, not least because of the rarity of these events. For these reasons, a study has been carried out to examine the skill of the European Centre for Medium-Range Weather Forecast (ECMWF) global forecasting system in predicting a specific flow configuration that is believed to be associated with extreme precipitation events over the Alpine region. Despite quantitative predictions of extreme precipitations is still challenging, it was found that the large-scale flow conducive to major rain events has better predictive skill than average conditions. This is perhaps surprising since it is a common perception to associate severe weather with low predictability.     

Simulation of extreme precipitation indices in the Yangtze River basin by using statistical downscaling method (SDSM)

In this study, the applicability of the statistical downscaling model (SDSM) in modeling five extreme precipitation indices including R10 (no. of days with precipitation ≥10?mm?day^?1), SDI (simple daily intensity), CDD (maximum number of consecutive dry days), R1d (maximum 1-day precipitation total) and R5d (maximum 5-day precipitation total) in the Yangtze River basin, China was investigated. The investigation mainly includes the calibration and validation of SDSM model on downscaling daily precipitation, the validation of modeling extreme precipitation indices using independent period of the NCEP reanalysis data, and the projection of future regional scenarios of extreme precipitation indices. The results showed that: (1) there existed good relationship between the observed and simulated extreme precipitation indices during validation period of 1991–2000, the amount and the change pattern of extreme precipitation indices could be reasonably simulated by SDSM. (2) Under both scenarios A2 and B2, during the projection period of 2010–2099, the changes of annual mean extreme precipitation indices in the Yangtze River basin would be not obvious in 2020s; while slightly increase in the 2050s; and significant increase in the 2080s as compared to the mean values of the base period. The summer might be the more distinct season with more projected increase of each extreme precipitation indices than in other seasons. And (3) there would be distinctive spatial distribution differences for the change of annual mean extreme precipitation indices in the river basin, but the most of Yangtze River basin would be dominated by the increasing trend.     

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。     

基于ETCCDI指数2017年中国极端温度和降水特征分析

利用中国1961—2017年2419站均一化逐日气候数据,计算了气候变化检测和指数联合专家组定义的26个极端气候指数,分析2017年中国极端温度和降水特征。结果表明：2017年中国区域平均的所有极端高温指数均高于1961—1990年30年平均,所有极端低温指数均低于1961—1990年30年平均。中国区域平均的多个极端温度指数达到或者接近历史极值,其中年最小日最高气温(TXn)和年最小日最低气温(TNn)均达到历史最高值,冷夜(TN10p)、冷昼(TX10p)和持续冷日日数(CSDI)达到历史最低值。年最大日最高气温(TXx)、年最大日最低气温(TNx)、暖夜(TN90p)、霜冻(FD)、冰冻(ID)、热夜(TR)、生长期长度(GSL)排在1961年以来的第2或第3位,其余极端温度指数全部排在了1961年以来前10位。2017年中国区域平均的10个极端降水指数中,有7个指数值处于1961—2017年1个标准差范围内,指示2017年的极端降水接近正常年。     

中国未来极端气温变化的概率预估及其不确定性

本文基于第五次耦合模式比较计划的23个全球气候模式所提供的最高气温与最低气温在RCP4.5情景下的逐日格点资料,根据模式对5个极端气温指数的模拟能力,使用秩加权方法研究了中国未来极端气温变化的概率预估及其不确定性。结果表明,21世纪中期（2046—2065年）中国区域平均最高气温和平均最低气温的增加幅度相对于历史时期（1986—2005年）可能超过2.0℃（概率>66%),增加的大值区主要位于青藏高原南部。暖夜指数在中国大部分地区增加超过15%,西南和东南部沿海是增加的大值区,增幅超过20%。霜冻日数在全国范围内减少,减少的大值区位于青藏高原周围,减少日数超过了20 d。热浪指数在整个中国区域可能增加10 d以上,大值区位于西藏西南部,可达30 d。不确定性的结果表明,除热浪指数的可信度较低外,其余指数都有较高的可信度。到21世纪末期（2081—2100年),中国区域极端气温增加幅度超过前期,平均最高气温和平均最低气温很可能增加超过2.0℃（概率>90%),大值区除中国西部地区外,还扩展到了东北和青藏高原西南地区。中国大部分地区的暖夜指数增加超过15%,西南和南部沿海可能超过25%。大部分地区的霜冻日数减少20 d,青藏高原周围减少超过40 d。热浪指数在中国范围内增加20 d,青藏高原西南部增加40 d以上。除霜冻指数的信噪比略比21世纪中期大外,其余指数的信噪比与中期基本一致。     

Variability and probability of annual and extreme precipitation over Serbia and Montenegro

Summary Annual precipitation over Serbia and Montenegro is studied in terms of its variability. The dependence of three selected absolute measures of variability (standard deviation, absolute mean deviation and mean absolute interannual variability) from the mean annual precipitation are examined for the area of interest. Two cases of extreme precipitation in Serbia were analysed using the gamma probability density function and some transformations.     

Diurnal cycles of precipitation over subtropical China in IPCC AR5 AMIP simulations

Atmospheric Intercomparison Project simulations of the summertime diurnal cycle of precipitation and low-level winds over subtropical China by Intergovernmental Panel on Climate Change Fifth Assessment Report models were evaluated. By analyzing the diurnal variation of convective and stratiform components, results confirmed that major biases in rainfall diurnal cycles over subtropical China are due to convection parameterization and further pointed to the diurnal variation of convective rainfall being closely related to the closure of the convective scheme. All models captured the early-morning peak of total rainfall over the East China Sea, but most models had problems in simulating diurnal rainfall variations over land areas of subtropical China. When total rainfall was divided into stratiform and convective rainfall, all models successfully simulated the diurnal variation of stratiform rainfall with a maximum in the early morning. The models, overestimating noon-time （nocturnal） total rainfall over land, generally simulated too much convective rainfall, which peaked close to noon （midnight）, sharing some similarities in the closures of their deep convection schemes. The better performance of the Meteorological Research Institute atmospherer. ocean coupled global climate model version 3 （MRI-CGCM3） is attributed to the well captured ratio of the two kinds of rainfall, but not diurnal variations of the two components. Therefore, a proper ratio of convective and stratiform rainfall to total rainfall is also important to improve simulated diurnal rainfall variation.     

Trends in thermal discomfort indices over western coastal cities of India

Theoretical and Applied Climatology - The present research aimed at analyzing temporal trends in thermal discomfort indices for a period of 46 years from 1969 to 2014 over western coastal...     

1971—2020年金华地区极端降水变化特征

利用浙江省7个国家气象站逐日降水数据和8个极端降水气候指数,应用线性拟合、Mann Kendall检验、小波分析和反距离权重插值等方法,分析1971—2020年金华地区极端降水指数时空分布特征。结果表明：金华地区除了持续干期（CDD）呈下降趋势外,年降水量（PRCPTOT）、平均日降水强度（ISDII）、强降水量（R95p）、极强降水量（R99p）、最大1 d降水量（Rx1day）、暴雨日数（R50）和持续湿期（CWD）均呈逐渐增大趋势。金华地区极端降水指数具有一定的周期性和突变特征,PRCPTOT、ISDII、R50、Rx1day、R95p和R99p第一主周期为23—25 a;CDD和CWD周期较短,第一主周期分别为2 a和4 a。PRCPTOT、ISDII、R95p和R50突变主要出现在21世纪初,Rx1day和R99p主要出现在20世纪80年代和21世纪初,均是由相对偏少期突变为相对偏多期。ISDII和CDD空间分布表现为东北部大于西南部外,除此之外的6个指数总体表现为西部大于东部。     

Trends in evaporation of a large subtropical lake

In order to further investigate the capability of the Standardized Precipitation Index (SPI) to identify flood/drought events, monthly precipitation data from 26 precipitation stations and monthly discharge data from four hydrological stations from 1960 to 2006 in the Minjiang River basin were used to analyze the correlations between multiple time scales of the SPI and river discharge. The SPI series that had a maximum correlation with discharge was chosen to detect flood/drought events in the basin, and the results were compared to historical flood/drought events. The results indicated the following. (1) High Pearson correlations between the SPI and discharge were identified at shorter time scales (1 to 3 months), and the maximum correlation was found on the time scale of 2 months. (2) Five floods among the six largest historical flood events in the Minjiang River basin were identified with the 2-month SPI, but the SPI does have shortcomings in identifying more general floods. The SPI also identified major drought events that were consistent with historical data. This demonstrates that the 2-month SPI is an effective indicator for the identification of major flood/drought events in the Minjiang River basin.