新会年和月最大日降水量多年一遇的极值计算

利用新会降水资料,用皮尔逊一Ⅲ型分布分别对新会年最大日降水量和1～12月的月最大日降水量进行拟合,进而计算了它们在不同重现期下的极值。结果表明:新会50a一遇的估算年最大日降水量是308mm,100a一遇是335mm。新会4～9月5a一遇的最大日降水量接近或超过100mm,说明汛期各月比较容易出现大暴雨。除7月外,4～9月新会50年一遇的日降水量均超过200mm。经检验,除了2月和12月外,年和各月最大日降水量通过0.05显著水平检验,拟合效果良好,对其不同重现期下的极值估计结果可信。     

基于两种分布的勉县年最大日降水量重现期估算

2021年8月22日勉县遭遇极端降水事件,日降水量高达2379 mm,灾害十分严重。统计分析1959—2021年勉县历史逐年最大日降水量特点,采用皮尔逊Ⅲ型（简称P-Ⅲ型）曲线分布和耿贝尔极值分布方法推算重现期及降水量,并将两者进行比较,对2021年8月22日极端大暴雨进行重现期估算。结果表明：勉县年最大日降水年际变化明显,2008年以来变率增大且有更极端的趋势;基于P-Ⅲ型曲线分布和耿贝尔极值分布的1959—2020年最大日降水积累概率拟合效果均较好,但耿贝尔极值分布对年最大日降水量的拟合优于P-Ⅲ型分布;应用耿贝尔极值分布推算勉县极值降水,100 a一遇的日降水量为1547 mm,2021年8月22日降水量2379 mm的重现期为4 88133 a。增加2021年最大日降水量进入样本序列重新构建耿贝尔极值分布函数,推算日降水量2379 mm的重现期为70735 a,100 a一遇的估算降水量为1834 mm,重现期及降水量估算变化均较大,说明超极端降水和样本长度对重现期的推算影响较大。     

韶关市年和月最大日降水量多年一遇的极值计算

用皮尔逊-III型分布分别对韶关市年和月最大日降水量两种变量进行拟合,进而计算了它们在不同重现期下的极值。结果表明:韶关市50年一遇的估算年最大日降水量是220.5 mm,100年一遇是244.1 mm。实况表明,韶关在1956~2006年间出现的最大日降水量是234.8 mm,与韶关50年一遇估算的日降水量相吻合;韶关平均2.2年出现一次100 mm以上的日降水量,而该降水量的估算重现期是2年,亦十分接近;总体上拟合良好,对其不同重现期下的极值估计结果可信。对月最大日降水量的拟合以3月的拟合误差最小,5~7月10年一遇以上的日降水量均超过100 mm,说明这3个月较其他月份容易出现大暴雨,尤其6月份所有重现期的最大日降水量均为其它月份之最,5月和7月次之。     

吐鲁番一日最大降水量年极值频率分布

利用三参数Weibull分布函数对吐鲁番平原、山区一日最大降水量年极值频率分布进行了拟合,分析了平原、山区一日最大降水量的频率分布特征,同时应用甘倍尔分布和对数正态分布也进行了拟合。结果表明：对吐鲁番平原、山区一日最大降水量极值频率分布用三参数Weibull分布拟合比甘倍尔分布、对数正态分布精度要高。利用上述3种方法对吐鲁番平原40多年、山区30多年一日最大降水量重现期进行了估计。     

吐鲁番一日最大降水量年级值频率分布

利用三参数Ｗｅｉｂｕｌｌ分布函数对吐鲁番平原,山区一日最大降水量年级值频率分布进行了拟合,分析了平原,山区一日最大降水量的频率分布特征,同时应用甘倍尔分布和对数正态分布也进行了拟合。结果表明：对吐鲁番平原,山区一日最大降水量极值频率分布用三参数Ｗｅｉｂｕｌｌ分布拟合比甘倍尔分布,对数正态分布精度要高。利用上述３种方法对吐鲁番平原４０多年,山区３０多年一日最大降水量重现进行了估计。     

贵州年降水量和年最大月降水量多年一遇的极值计算

根据贵州省84个气象站1961-2007年的月降水资料,用耿贝尔极值I型分布分别对贵州省年降水量和年最大月降水量2种变量进行拟合,进而计算它们在不同重现期下的极值.结果表明:贵州省的降水量集中分布在东南部地区,其中贵州的安顺及黔东南地区降水量较为突出,晴隆15、30、50a一遇的年最大月、年降水量分别为559.8mm、617.1mm、658.9mm和2 019.6mm、2 177.9mm、2 293.2mm,都匀15、30、50a一遇的年最大月、年降水量分别为557mm、626.6mm、677.3mm和1 892.8mm、2 044.9mm、2 155.8mm,对拟合结果的评判采用相对均方根误差进行检验,其年降水量平均相对均方根误差为6%,年最大月降水量平均相对均方根误差为9%,可见拟合良好,对其不同重现期下的极值估计结果可信.     

珠海市年雨量和年最大日雨量多年一遇的极值计算

用皮尔逊-III型分布分别对珠海市年雨量和年最大日雨量两种变量进行拟合,进而计算了它们在不同重现期下的极值。结果表明:珠海市50年一遇的估算年雨量和年最大日雨量分别是2 908 mm和565 mm,100年一遇的分别是3 042 mm和648 mm。用澳门和珠海的雨量历史资料验证发现:澳门在104年间出现的最大年雨量是3 041.4 mm,与珠海百年一遇估算雨量吻合;珠海平均7.2年出现一次2 500 mm以上年雨量,而该雨量的估算重现期是7.5年,亦十分接近;年最大日雨量的估算重现期则比实际重现期小些。可见拟合良好,对其不同重现期下的极值估计结果可信。     

浑太流域降水极值的统计分布特征

基于浑太流域1966-2006年73个雨量站的日降水资料,建立了逐站年最大日降水量(AnnualMaximum,AM)序列和汛期4-9月日降水量<1.27mm.d-1的最长持续干旱天数(Munger Index,MI)序列,并对其时空分布规律进行了分析。采用广义极值(General Extreme Value,GEV)分布、广义帕雷托(General Pareto,GP)分布、韦布尔(Weibull,WB)分布、约翰逊SB(Jonhson SB,J-SB)分布、Burr分布和对数逻辑(Log-Logistic,L-LG)分布等6种极值分布函数对AM和MI序列进行了逐站分布拟合,结果表明,广泛应用的GEV分布整体拟合程度最好,有50个测站的KS检验统计量Dn<0.09,而未曾推广使用的Burr分布的拟合效果也非常好,有36个测站Dn<0.09。用GEV分布对50年一遇的AM和MI进行了估算,发现流域中心地区极端强降水和极端干旱的程度较高,分别为>208mm.d-1和>47d。     

鹤壁市单日降水量极值估算

利用耿贝尔(Gumber)极值分布原理,对鹤壁市1965-2004年最大日降水量进行降水分布拟合,估算预报时段内可能出现的最大日降水量,得出50 a、80 a鹤壁市可能出现的最大日降水量分别为278.7 mm和301.9 mm;利用二次指数平滑法,得到鹤壁市最大日降水量年际变化总体上呈线性减少趋势.统计结果显示:鹤壁市最大日降水量有峰值增大、谷值减小的趋势,说明在未来一定时期,极端最大日降水量发生的可能性不断增加;最大日降水量集中出现在7-8月份,有明显的季节特征.     

气象要素重现期的计算方法与比较

文章以呼伦贝尔市的海拉尔区、满洲里市、图里河镇、扎兰屯市气象台站1960—2012年日最高、日最低气温、日降水量及1971—2012年日最大风速观测数据为基础。分别使用气象上常用的重现期计算方法(皮尔逊Ⅲ分布、耿贝尔分布和对数正态分布)计算各气象要素重现期。分析表明:三种分布方式在最高、最低气温的分析中表现均较好,在最大风速的分析中表现较差,对数正态分布在重现期计算中数值偏低(最低气温偏高),根据不同气象要素重现期的卡方检验结果选择合适方法进行分析,符合实际出现情况。     

CHARACTERISTICS AND TRENDS OF CLIMATIC EXTREMES IN CHINA DURING 1959–2014

The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics.     

ANALYSIS OF “BIMODAL PATTERN” STORM ACTIVITY CHARACTERISTICS OF THE BAY OF BENGAL

Storms that occur at the Bay of Bengal (BoB) are of a bimodal pattern, which is different from that of the other sea areas. By using the NCEP, SST and JTWC data, the causes of the bimodal pattern storm activity of the BoB are diagnosed and analyzed in this paper. The result shows that the seasonal variation of general atmosphere circulation in East Asia has a regulating and controlling impact on the BoB storm activity, and the “bimodal period” of the storm activity corresponds exactly to the seasonal conversion period of atmospheric circulation. The minor wind speed of shear spring and autumn contributed to the storm, which was a crucial factor for the generation and occurrence of the “bimodal pattern” storm activity in the BoB. The analysis on sea surface temperature (SST) shows that the SSTs of all the year around in the BoB area meet the conditions required for the generation of tropical cyclones (TCs). However, the SSTs in the central area of the bay are higher than that of the surrounding areas in spring and autumn, which facilitates the occurrence of a “two-peak” storm activity pattern. The genesis potential index (GPI) quantifies and reflects the environmental conditions for the generation of the BoB storms. For GPI, the intense low-level vortex disturbance in the troposphere and high-humidity atmosphere are the sufficient conditions for storms, while large maximum wind velocity of the ground vortex radius and small vertical wind shear are the necessary conditions of storms.     

LOW-FREQUENCY CIRCULATION AND EXTENDED-RANGE FORECAST IN CONNECTION WITH AUTUMN EXTREME HEAVY RAINFALL PROCESS IN HAINAN

Observed daily precipitation data from the National Meteorological Observatory in Hainan province and daily data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-2 dataset from 1981 to 2014 are used to analyze the relationship between Hainan extreme heavy rainfall processes in autumn (referred to as EHRPs) and 10–30 d low-frequency circulation. Based on the key low-frequency signals and the NCEP Climate Forecast System Version 2 (CFSv2) model forecasting products, a dynamical-statistical method is established for the extended-range forecast of EHRPs. The results suggest that EHRPs have a close relationship with the 10–30 d low-frequency oscillation of 850 hPa zonal wind over Hainan Island and to its north, and that they basically occur during the trough phase of the low-frequency oscillation of zonal wind. The latitudinal propagation of the low-frequency wave train in the middle-high latitudes and the meridional propagation of the low-frequency wave train along the coast of East Asia contribute to the ‘north high (cold), south low (warm)’ pattern near Hainan Island, which results in the zonal wind over Hainan Island and to its north reaching its trough, consequently leading to EHRPs. Considering the link between low-frequency circulation and EHRPs, a low-frequency wave train index (LWTI) is defined and adopted to forecast EHRPs by using NCEP CFSv2 forecasting products. EHRPs are predicted to occur during peak phases of LWTI with value larger than 1 for three or more consecutive forecast days. Hindcast experiments for EHRPs in 2015–2016 indicate that EHRPs can be predicted 8–24 d in advance, with an average period of validity of 16.7 d.     

AN ATTRIBUTION ANALYSIS OF CHANGES IN POTENTIAL EVAPOTRANSPIRATION IN THE BEIJING–TIANJIN–HEBEI REGION UNDER CLIMATE CHANGE

Based on the measurements obtained at 64 national meteorological stations in the Beijing–Tianjin–Hebei (BTH) region between 1970 and 2013, the potential evapotranspiration (ET0) in this region was estimated using the Penman–Monteith equation and its sensitivity to maximum temperature (Tmax), minimum temperature (Tmin), wind speed (Vw), net radiation (Rn) and water vapor pressure (Pwv) was analyzed, respectively. The results are shown as follows. (1) The climatic elements in the BTH region underwent significant changes in the study period. Vw and Rn decreased significantly, whereas Tmin, Tmax and Pwv increased considerably. (2) In the BTH region, ET0 also exhibited a significant decreasing trend, and the sensitivity of ET0 to the climatic elements exhibited seasonal characteristics. Of all the climatic elements, ET0 was most sensitive to Pwv in the fall and winter and Rn in the spring and summer. On the annual scale, ET0 was most sensitive to Pwv, followed by Rn, Vw, Tmax and Tmin. In addition, the sensitivity coefficient of ET0 with respect to Pwv had a negative value for all the areas, indicating that increases in Pwv can prevent ET0 from increasing. (3) The sensitivity of ET0 to Tmin and Tmax was significantly lower than its sensitivity to other climatic elements. However, increases in temperature can lead to changes in Pwv and Rn. The temperature should be considered the key intrinsic climatic element that has caused the "evaporation paradox" phenomenon in the BTH region.     

Could the Recent Taal Volcano Eruption Trigger an El Ni?o and Lead to Eurasian Warming?

正The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth's climate and environment.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

Revisiting the Concentration Observations and Source Apportionment of Atmospheric Ammonia

正While China’s Air Pollution Prevention and Control Action Plan on particulate matter since 2013 has reduced sulfate significantly, aerosol ammonium nitrate remains high in East China. As the high nitrate abundances are strongly linked with ammonia, reducing ammonia emissions is becoming increasingly important to improve the air quality of China. Although satellite data provide evidence of substantial increases in atmospheric ammonia concentrations over major agricultural regions, long-term surface observation of ammonia concentrations are sparse. In addition, there is still no consensus on     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR–SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.     

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正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted