郑州市暴雨的气候特征

统计分析了郑州市7站自建站始至2005年的全部暴雨天气过程,结果显示:暴雨天气发生在夏半年(4~10月);单站暴雨年平均1.3~2.8次,区域性暴雨年平均1.5次;郑州地区暴雨出现次数南部多于北部,东部多于西部,其中登封是郑州市出现暴雨次数最多的测站;暴雨次数的年际变化呈明显波动形势;造成郑州市夏季暴雨的主要天气系统有低槽型、切变线型、副高西伸型、台风或台风倒槽型等。     

连云港市暴雨天气形势分析

用连云港市7个气象观测站的常规观测资料,对1971-2008年的38 a中29次区域性暴雨天气过程进行数理统计,对连云港市的暴雨天气变化趋势进行探讨,连云港市暴雨天气主要发生在6-9月,7-8月次数最多,占总数79％,雨量极值出现在西连岛站,暴雨日数及雨量极值趋于增大且趋势比较明显.同时,对全市区域性暴雨天气的高空影响系统进行了分类,划分为4种类型:台风减弱型、低压型、横槽类型、低槽类型,各类型几乎各占总暴雨数的1/4.     

广西前汛期暴雨天气过程的特征分析

通过对１９５９－１９９９年４～６月发生在广西的暴雨天气过程特征作一较系统的分析,得出４～６月广西出现暴雨天气过程的年平均次数分别为０．９８、２．３９、２．７８次;４～６月不出现暴雨天气过程的机率分别为０．３４、０．０７和０．０７;４～６月出现的暴雨过程的年平均日数为１．０２、２．７３和４．０５ｄ。     

20世纪90年代华北大暴雨过程特征的分析研究

首先对1960～1999年的华北夏季暴雨过程进行了统计分析,之后,又进一步对1990～1999年造成夏季特大暴雨过程的天气形势进行了分型研究.结果表明,从20世纪60年代到90年代夏季每10年发生的暴雨和大暴雨次数基本相当,40年中山西和河北的北部暴雨发生次数在20次以上,沿海地区暴雨发生次数为60～100次.1990～1999年的6～8月华北地区发生大暴雨共39天,大体可分为5型:1型为台风与低槽(低涡)远距离相互作用;2型为低涡(登陆台风)与西风槽相互作用;3型为登陆台风北上受高压阻挡停滞;4型为低涡暴雨;5型为暖切变暴雨.其中,台风和低涡是主要影响系统.最后,对北京夏季的暴雨过程也进行了统计和分型研究.40年中有7年未发生暴雨,而最多的年份发生了5次,存在很明显的年变化.研究表明,尽管北京暴雨具有华北暴雨的共同特征,但也有北京地区的特点,如以暴雨频次而言,最多的是低涡暴雨,其次是台风与低槽(低涡)相互作用型.另外,低槽冷锋暴雨也是一类值得关注的系统.     

钦州市登陆中越边境南海台风暴雨天气分析

以1958～2000年间登陆中越边境的16个台风的季节强度，移速、影响的地域、天气形势作了对比分析，结果发现：该类南海台风产生暴雨有时间性和地地域性，暴雨基本上出现在6～9月份，出现暴雨的台风概率8月最大9月次之6、7月较小；钦州、灵山、浦北三站中出现暴雨的均在钦州市沿海一带，灵山、浦北在该类台风过程中无暴雨天气。     

广西前汛期暴雨天气过程的特征分析

通过对1959-1999年4～6月发生在广西的暴雨天气过程特征作一较系统的分析,得出4～6月广西出现暴雨天气过程的年平均次数分别为0.98、2.39、2.78次;4～6月不出现暴雨天气过程的机率分别为0.34、0.07和0.07;4～6月出现的暴雨过程的年平均日数为1.02、2.73和4.05d。     

厦门连续性暴雨天气气候特征

1956～2002年厦门降水资料和相应天气图资料分析结果表明：厦门连续性暴雨天气过程主要产生在台风季和雨季；雨季间连续性暴雨环流背景是500hPa的阻塞形势，分单阻和双阻两型，850hPa形势特征则表现为低涡切变偏南和低空西南急流两型；台风连续性暴雨的台风路径主要有台湾类和南海类两类，所对应的主要登陆地段分别是厦门至福清和厦门至珠江口，500hPa环流形态有台风倒槽、台风后部、槽台迎近和北槽南台4类。     

眉山两次台风倒槽暴雨过程对比分析

利用常规探测、NCEP FNL1°×1°全球分析和自动站等资料,对影响眉山地区的两次台风倒槽暴雨过程进行诊断分析,结果表明:两次过程都是在副高588线西伸加强控制整个四川地区的环流背景下发生,第一次台风倒槽暴雨过程(2017年8月22日)由台风倒槽和地面冷空气共同影响,台风倒槽较浅薄,伸展高度不高,过程发生前大气层结热力不稳定特征明显,水汽辐合主要出现在近地面层,整层上升运动较强,对应短时强降水、阵性大风等强对流天气。第二次台风倒槽暴雨过程(2017年8月24日)由单一台风外围的台风倒槽影响造成,台风倒槽较明显,伸展高度较高,过程发生前热力不稳定特征不明显,水汽辐合时间较长,上升运动主要出现在中低层,对应降雨持续时间长,降水强度较弱。     

濮阳市台风倒槽影响下不同天气对比分析

通过对１９９４年７月１２日和８月２３日两次台风倒槽影响下不同天气的对比分析，确定了台风倒槽型暴雨预报指标。     

近60年黑龙江省台风暴雨统计及环流特征分析

使用台风最佳路径、黑龙江省83个国家基本气象站日降水量资料及NCEP NC再分析资料,对近60年黑龙江省台风活动规律、台风暴雨时空分布和环流形势及各物理量统计特征等进行分析。结果表明：2010年以后造成暴雨的台风个数增加,2015年之后台风暴雨强度持续增加,2020年达到最强。黑龙江省台风暴雨站次最多的时间是7月下旬至9月上旬。黑龙江省受台风影响出现暴雨的次数自东南向西北递减,暴雨次数多的站点一般与地形有关。将台风暴雨过程的高空环流形势分为3型8类,A型暴雨过程以台风环流降水为主,多数为稳定性降水,降水持续时间较长,B型和C型暴雨过程有较强冷空气参与,对流活跃,通常雨强较大。给黑龙江省带来大范围暴雨的环流形势有5类。以A-Ⅱ和C-Ⅰ两种环流形势出现的台风个数最多,A-Ⅱ和B-Ⅱ造成的暴雨范围最广。黑龙江省台风暴雨过程低空均有低涡活动;水汽主要来自日本海和黄渤海;低层辐合中心与暴雨区有较好的对应关系。A-Ⅱ类台风暴雨的各个物理量特征最突出（假相当位温和比湿略小于B-Ⅱ类）;B-Ⅱ类台风暴雨过程的暖湿空气最强,尽管动力条件稍差,但较好的热力和水汽条件也足以造成大范围的暴雨天气,成为平均单个过程出现暴雨以上站次最多的类型。     

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.     

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