山东省汛期小时极端强降水分布和变化特征

利用山东省1961—2012年74个气象站逐时降水数据,分析研究了山东省汛期(5—9月)小时极端强降水的时空变化和日变化特征。结果表明:(1)山东省小时极端强降水量和频次呈大致的带状分布,由东南沿海向西北内陆递减。山东中西部极端小时强降水强度较大,鲁西、鲁西北、鲁西南及半岛西部一带极端强降水量占比较高。(2)山东历年各站平均小时极端降水量、频次、强度均呈不显著的增多增强趋势。鲁南、鲁西北和半岛东部、北部等地降水量增多趋势明显,鲁南、鲁东南、鲁西、半岛中东部降水强度增强趋势明显。(3)下午(15时)至傍晚(20时)是山东省小时极端强降水主要发生时段。降水量和降水频次在11—18时呈减少趋势,其他时段多为增加趋势。降水强度的变化在上午基本为减弱趋势,其他时次多为不同程度的增强趋势。(4)7月小时极端降水量和降水频次最大,一日中有两个高值中心。(5)山东夜间两个时段21时至次日02时、03—08时段平均和大部分区域极端强降水有增多趋势。     

白龙江流域甘肃段2015—2018年汛期降水特征

利用2015—2018年5—9月白龙江流域甘肃段140个气象站小时降水资料,定义流域降水过程次数等特征量,分析该流域汛期降水变化特征。结果表明：（1）白龙江流域甘肃段汛期平均降水量逐年增加,近4 a汛期平均降水量分布与逐年分布在空间上相似,均为下游的广坪河支流最多,短时强降水主要集中在白龙江主河道上。（2）流域内平均降雨日数与平均降水量的空间分布不对应,降雨日数多的年份各支流降雨日数分布较均匀,降雨日数少的年份则各支流间差异较大。（3）流域内各支流的平均降水量、降雨日数与短时强降水在空间分布上并不一致。（4）流域内白天出现降水的次数小于夜间,01时出现最多;各支流降水出现次数夜间多于白天,以22—23时、03—04时这两个时段最多;流域内短时强降水天气在21时出现最多。（5）流域内的最大降水过程的累计雨量、持续时间及小时最大降水量随着季节变化明显。5、6月累计雨量不大,持续时间较长,小时降水量较小;7、8月累计雨量大,持续时间较短,小时降水量较大;9月累计雨量较大,持续时间长,小时降水量小。     

1961—2014年广东小时强降水的变化特征

利用1961—2014年广东32个气象观测站逐小时降水资料,采用线性趋势分析、Mann Kendall检验、功率谱分析、计算趋势系数等统计诊断方法,分析了广东小时强降水在年以及前、后汛期的气候特征及变化。结果表明,广东年、前、后汛期多年平均小时强降水的次数、强度、降水量和贡献率的空间分布均呈沿海向内陆递减。近54年来,广东平均小时强降水的次数、强度、降水量和贡献率在年以及前、后汛期的时间尺度上均为显著上升的趋势,与同期广东年暴雨次数和年降水变化不明显有明显差异。广东大部分测站小时强降水量均呈增加的趋势,其中珠三角增加最为显著。近54年来广东年和前汛期小时强降水次数存在3.7年和22年、后汛期存在3年左右的显著周期震荡。广东年和后汛期小时强降水次数在1993—1994年发生增加的突变,前汛期小时强降水次数没有突变发生。     

云南小时降水的时空分布变化研究

利用2005—2018年125个国家级台站小时降水观测数据研究云南小时降水时空分布特征。结果表明:云南年总降水量、不同持续时间降水量、极端强降水量及降水日变化空间分布差异很大。年降水量自西北向南增加,雨强自北向南增强,降水时长西部大于东部、南部略大于北部,年降水量受降水时长和雨强共同影响,降水时长影响最强,雨强影响较弱,这种特征在滇西北最突出,但滇东北的降水量与雨强相关更好。云南大部夜雨量多于昼雨量,滇东北和北部边缘夜雨特征最显著;降水日变化特征在云南北部为夜间单峰,西部边缘为清晨单峰,中部为夜间与午后峰值相当的双峰,南部也为夜间和午后双峰,但南部不同区域间主峰和次峰出现时间不同。云南南部降水贡献以短、中历时降水为主,北部则以长、超长历时降水为主。云南短时强降水发生次数的空间分布表现为自西北向东南增加;年发生站次数具有增加趋势,日变化特征为显著单峰,多在傍晚至入夜出现,且极端短时强降水更易在凌晨出现。这些小时降水时空分布特征很大程度上代表了低纬高原地区的降水特征。由于低值天气系统多影响低纬高原中北部,热带天气系统多影响南部,且低纬高原地形复杂,局地热力条件差异明显,这些因素造成该区域小时降水时空分布特征差异显著。     

济南地区小时强降水变化特征

利用济南地区2008—2017年3—11月50个区域自动站逐时降水数据,研究该区域雨强超过10.0、20.0、30.0 mm·h~(-1)的降水量时空变化特征。结果表明:济南全区小时强降水受城市化、地形和盛行风的影响显著,济南城区、南部山区、长清山前地带、商河等地降水偏多,济南市区下风向近郊、章丘、济阳、平阴一带强降水偏少。7、8月济南地区小时强降水最多,雨强≥20.0 mm·h~(-1)的月平均降水量均超过40.0 mm,贡献率均超过25.0%。小时强降水日变化呈双峰双谷特征,11:00和23:00前后为强降水最少时段,04:00—05:00和14:00—21:00是强降水较多时段。大部分站点强降水峰值出现在午夜至凌晨和下午至傍晚时段。     

乌江流域极端降水时空分布特征及重现期分析

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。     

深圳市强降水的气候变化趋势及突变特征

基于深圳市1961～2008年遥测站整点自记小时雨量,对强降水变化趋势、突变和周期特征进行分析。结果表明:(1)48年来,强降水量(≥20 mm/h)主要出现在汛期,占年强降水量93.6%。月值变化呈双峰型分布,峰值为6月和8月。(2)汛期强降水量20世纪60年代先下降后上升;70、80年代持续上升,趋势不显著;90年代以来显著增长。降水时数60年代末开始出现持续上升趋势,分别在70年代和21世纪初达到α=0.05显著性水平,趋势显著。(3)汛期强降水量在1992年发生突变,而强降水时数有2个突变点为1965和1991年。降水时数的突变早于降水量的突变。(4)汛期强降水存在以6～8年和1～2年为主周期的多时间尺度的震荡;6～8年的震荡有4个明显的高值中心,分别是20世纪60年代末、80年代中期、90年代中期和21世纪初。最后未闭合的高值中心表明未来几年强降水将处于一个较丰富的阶段。     

渠江流域汛期强降水时空分布特征

本文从分析研究渠江流域汛期强降水时空分布入手,试图揭示该流域21世纪以来洪水频发的原因。经对渠江流域1970~2012年降水资料分析研究得出:(1)渠江流域汛期降水量、暴雨日数、降水变差系数呈“北大南小”的空间分布;“北区(河流汇水区,下同)”近年来汛期降水量增大、暴雨频率增加、降水趋于极端;(2)短时强降水多发生在04~08时,频发区主要位于“北区”,近年来频次呈上升趋势;(3)小时雨强极值“北区”普遍大于“南区”;近43年渠江流域汛期小时雨强极值总体呈增大趋势,“北区”尤为明显。因此,渠江流域汛期发生的强降水趋势性变化,是导致该流域洪水频发的主要原因之一。      

1967-2006年中国东南沿海盛夏降水强度变化特征分析

利用中国地面台站逐日和逐时降水资料,对中国东南沿海地区近40年(1967-2006年)盛夏(7-8月)降水强度变化特征进行了分析.逐日降水资料的分析结果表明我国东南沿海盛夏的降水量呈显著增加趋势,且主要是由日降水强度增强所致,日降水频次的贡献不显著.结合逐时降水资料的分析结果发现,东南沿海地区虽然降水日的平均降水时数显著增加,平均逐时降水强度也显著增强.通过按降水持续时数确定的降水事件分类分析发现,短持续降水(≤4h)平均小时强度显著增强,具体表现为弱小时强度降水减少和强降水增多.长持续性降水(≥15h)平均小时强度减弱,但降水频次增加.由于长持续性降水的平均小时降水强度远大于短时降水平均小时强度,对整体小时强度增强是正贡献.总之,我国东南沿海盛夏平均降水强度增强主要来自长持续性降水频次的增多、短时强降水频次的增多和短时弱降水频次的减少.     

近40年湖南省极端强降水气候变化趋势与突变特征

利用1961-2004年逐日降水资料,对湖南极端强降水事件气候变化趋势和突变特征进行分析.结果表明:近44年来,极端强降水量和日数呈增加趋势.1993年是显著增加的突变点,年平均极端强降水量与日数1994-2004年比1961-1993年分别增加126.4mm和2.05d.极端强降水年平均强度趋势不明显,无明显突变,但1993年之后一直处于上升趋势,1994-2004年比1961-1993年增加了2.25mm·d-1.间隔1～5d的极端强降水事件除湘西和永州南部外,大部分地区呈增加趋势,洞庭湖区和湘江流域增加显著.极端强降水事件发生时间主要集中在6月中下旬和5月上中旬,1990年代以来,7月中旬也是极端强降水事件频发时段.     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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.     

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