柳州市区短历时强降雨时空分布

利用柳州市2010-2015年24个自动站观测资料,对柳州市区短历时强降雨的时间、空间分布特征以及与年降水量的关系进行分析,结果表明:(1)2010-2015年,柳州市区短历时强降雨的次数呈递增趋势,年际间变化较大;(2)从时空分布看,短历时强降雨最易发生在6月,时段集中在02-06时,发生最大概率的地区在柳州的西南部(柳南区);(3)从短历时降雨和年降水量的关系看,短历时强降雨对年总降雨量有贡献,短历时强降雨次数多,年总降雨量也高。     

汕尾市短历时强降雨的时空分布特征

利用汕尾市2013—2018年间115个自动气象站逐小时降雨量资料,对汕尾地区短历时强降水时空分布特征以及与年总降水量的关系进行研究。分析表明:(1)2013—2018年汕尾市短历时强降雨的次数大体呈递增趋势,各年发生的次数差异较大;(2)短历时强降雨具有明显的季节变化和日变化特征,最易发生在6月,时段集中在下午至傍晚;(3)短历时强降水主要集中在莲花山脉东南侧的海丰县大部及陆丰市东北部,包括莲花山、公平、梅陇、海城、八万等地区;(4)短历时强降雨发生次数多的年份降水量也大,两者具有很强的相关性。     

北京市强降雨分区及重现期研究

利用北京观象台1841—2008年年降水量资料及近50年北京市20个气象站和82个雨量站资料分析了北京地区降水量的时间和空间变化规律,对北京地区的降雨进行分区研究,并结合观象台站逐分钟降雨资料应用广义偏态分布（GPD）方法分析了北京地区不同历时降雨量重现期。结果表明：近168年来,北京地区有两个多雨时段和两个少雨时段,目前北京处于20世纪90年代至今的少雨时段内。70至80年代,北京地区强降雨主要为全市区域性降雨,90年代之后北京的短历时强降雨呈现出局地性的特征,降水分布不均,强降水中心大致成东北一西南向带状分布。根据北京市降雨EOF分析,将北京市划分为4个降雨分区,分别是山后区、城市中心区、东北部山区和东南部平原区。其中城区代表站观象台站多个历时不同重现期降雨量分析结果经过与现行排水规范对比表明,重现期模拟结果可靠。     

衢州市突发灾害性天气—短历时强降雨时空分布特征

为掌握衢州境内突发灾害性天气短历时强降雨的时空分布特征,依据浙江省县级气象台突发灾害性天气的有关规定,应用2007—2013年全市区域自动观测站小时降水资料,对突发灾害性天气短历时强降雨发生时间及其落区进行统计分析。结果表明,2010年短历时强降雨发生次数最多,占总次数的21.2%;6月短时强降雨发生频次最多,占年发生次数24.4%;18—19时发生频次最多,占总次数的14%。短时强降雨空间分布为西多东少,全市发生短时强降雨出现次数最多的为开化苏庄镇;强度最强的为开化常山交界的林山、芙蓉等地。     

重庆地区短历时强降水气候特征

利用重庆地区34个气象站1981—2016年逐分钟降水资料,对10、60、360和1440 min短历时强降水量空间分布规律和分区进行了分析。结果表明:重庆地区短历时强降水量空间分布差异较大,全市有3个高值区,中心分别位于西部沙坪坝站、东北部开州站、东南部秀山站。短历时强降水趋势变化空间差异较大,东南部、东北偏北地区以增多趋势为主,其余地区以减少为主。360 min最大降水量最不稳定,随着降水历时的缩短,最大降水量的稳定性逐步增大;各历时最大降水量均为正偏态分布。根据重庆地区短历时强降水的空间分布及其EOF分析结果,并考虑到重庆地区复杂地形、城市雨水排除规划和应用上的方便,将重庆地区短历时强降水分为3个区,分别是西部区、东南部区和东北部区。     

四川秋季连阴雨的变化特征和时空分布

利用1961-2007年四川省38个站9-11月的日降水资料,从发生次数、降水量和持续天数三方面资料,应用现代气候统计诊断方法,对四川秋季连阴雨的变化特征和时空分布进行了分析.结果表明:四川秋雨量约占四川全年降水量的四分之一,其中秋季连阴雨量约占全年降永的五分之一、约占秋雨量的80％;四川秋季连阴雨的发生次数、降水量和持续天数总体上均呈减少趋势,这种减少是一种突变现象,发生在1980s中后期;从地域上来看,四川秋季连阴雨总体上呈西部增多、东部减少的趋势;EOF分析结果表明四川秋季连阴雨最主要的特征为东西反相型分布.     

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。     

山东省汛期小时降水过程时空分布特征

利用山东省74个气象站1961-2012年逐时降水观测数据,分析了山东省汛期(5-9月)短历时和持续性降水过程的时空分布特征。结果表明:(1)过程降水量和过程历时显著增大使得山东省汛期总降水量略有增加,持续性降水过程次数、过程降水量、过程历时的增加对总降水量增加的贡献最大。(2)短历时总降水量以鲁中山区、鲁东南地区最多,鲁东南沿海、半岛东部持续性总降水量最多;短历时过程降水量、平均雨强以鲁东南向西北方向经鲁中山区至德州一带最大,持续性过程降水量、平均雨强在半岛东部和鲁东南部分地区最大。(3)短历时峰值雨强以鲁中山区周边地区较大,持续性峰值雨强以鲁南、鲁东南、半岛东部较大。(4)鲁中山区、鲁南及半岛个别地区短历时降水一般开始于午后(13-18时),鲁中山区周边及半岛沿海一带多以夜雨为主,持续性降水过程开始时间多出现在夜间。     

黑龙江省短历时降水时空分布特征研究

以百分位法和空间系统聚类法为理论基础，利用GIS空间插值技术，分析近30 a(1991—2020年)黑龙江省短历时（1 h、3 h、6 h、12 h）降水时空分布特征。结果表明：黑龙江省短历时降水分布趋势与夏季降水量分布趋势差异较大；短历时降水极值分布较为分散，基本上在西部松嫩平原地区最高，北部大、小兴安岭地区和东南山区最低；短历时降水99%、95%和90%分位，在西部松嫩平原地区最高，向东南和东部两个方向逐渐降低，大、小兴安岭最低；短历时降水从极值到99%、95%、90%分位降水量迅速下降，短历时降水高值在总降水样本中出现比例较小；黑龙江省各短历时降水的极值和均值年际变化趋势基本一致，各短历时的极值均呈明显增加趋势，历时越短增加趋势越明显。     

山西不同历时强降水的统计特征及趋势变化

利用山西省109站1981-2018年的短历时强降水资料,采用趋势系数、归一化、中尺度天气分析等方法,对1 h、3 h、6 h、12 h短历时强降水的极值、频次、日、月以及年代际等趋势变化和主要影响系统进行统计分析。结果表明:(1)极值空间分布具有山区大于盆地、南部大于北部,时效越短,极值分布的局地性越强等特点。(2)12 h内不同历时强降水出现频次具有"南高北低、山区高于盆地、东部山区高于西部山区、东南明显集中"的空间分布特点。(3)不同历时强降水集中出现在每年的7-8月,其中,1 h≥20 mm的短历时强降水出现频次最高。(4)1 h雨量≥20 mm、3 h雨量≥30 mm以及12 h雨量≥50mm强降水发生频次日内分布均为单峰型,6 h雨量≥50 mm强降水发生频次日内分布为双峰型。(5)1 h、3 h和6 h短历时强降水年发生次数的变化趋势为山西省东南部的增长速率最大;12 h短历时强降水年发生次数的变化趋势为山西省的东部和西部山区最大。(6)6 h和12 h与1 h和3 h短历时强降水的主要影响系统有明显差异,61%的6 h和12 h短历时强降水个例为系统性降水与多个中尺度强降水的组合造成。     

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.     

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.     

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.     

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