2012年10月大气环流和天气分析

2012年10月环流特征如下:北半球高纬度地区为单一极涡,强度较常年同期偏弱,中高纬环流呈现4波型,欧亚地区中高纬环流经向度较常年偏大,南支槽偏强,西太平洋副热带高压强度偏弱.10月,全国平均降水量为29.1 mm,比常年同期(36.9 mm)偏少18.9％,全国平均气温为10.3℃,与常年同期(10.3℃)持平.月内,冷空气活动频繁,先后有4次冷空气过程影响我国;受台风山神影响,我国华南地区出现一次强降水过程;西南地区阴雨寡照天气及华南秋旱天气持续,在中下旬均有所好转;我国中东部大部地区出现雾霾天气;个别地区出现低温冰冻、局地洪涝及风雹灾害.     

2016年10月大气环流和天气分析

2016年10月北半球极地地区极涡呈偶极性分布,极涡强度较常年同期偏强。中高纬环流为４波型,西太平洋副热带高压位置明显偏西、偏北,强度偏强。10月全国平均降水量55.4 mm,较常年同期（35.8 mm）偏多55%,为1951年来同期最多;全国平均气温10.9℃,较常年同期（10.3℃）偏高0.6℃。月内我国主要出现了6次区域性暴雨天气过程,其中2次是台风莎莉嘉和海马导致,2次是受低涡、切变线影响。冷空气活动频繁,出现5次过程,较常年偏多。京津冀地区出现4次雾 霾天气过程。今年第21号台风莎莉嘉于10月18日在海南省万宁市以强台风级别登陆,今年第22号台风海马于10月21日在广东省汕尾市登陆,均造成重大影响。     

2022年10月大气环流和天气分析北大核心CSCD

2022年10月大气环流的主要特征是北半球极涡呈单极型分布且较常年同期强度偏强,欧亚地区中高纬环流呈“两槽一脊”型,西太平洋副热带高压较常年位置偏西、偏北,强度偏强。10月,全国平均气温为10.8℃,较常年同期(10.6℃)偏高0.2℃;全国平均降水量为34.4 mm,比常年同期(35.6 mm)偏少3.4%。月内我国有2次暴雨天气过程,一次受高空槽、低空急流和副热带高压影响,另一次受台风尼格和高空槽影响。10月共有5个热带气旋在南海和西北太平洋活动,生成个数较常年偏多1.2个,无登陆台风(较常年偏少),其中台风桑卡、纳沙和尼格影响南海、海南岛和华南地区。长江以北气象干旱缓和,长江以南气象干旱持续。     

2019年10月大气环流和天气分析

2019年10月大气环流主要特征如下：北半球极涡呈偶极型,中高纬地区西风带为4波型分布,西太平洋副热带高压呈东西向带状分布,较常年位置偏西偏强。全国平均降水量为36.6 mm,接近常年同期（35.8 mm）。全国平均气温为11.1℃,较常年同期（10.3℃）偏高0.8℃。10月我国有两次暴雨天气过程,一次是受台风米娜影响,一次是高空槽及低空切变线导致。10月共有4次冷空气活动,分别为2次寒潮天气过程和2次强冷空气过程。我国北部地区出现1次扬沙天气过程。2019年第19号台风米娜于10月1日20:30在浙江舟山普陀沿海登陆。     

2013年10月大气环流和天气分析

2013年10月环流特征如下:北半球高纬度地区为单一极涡,强度较常年同期偏强,中高纬环流呈现4波型,北美地区中高纬环流经向度较常年偏大,南支槽偏强,西太平洋副热带高压强度偏强。10月,全国平均降水量为30.8 mm,比常年同期(35.8 mm)偏少14.0%,全国平均气温为11.1℃,比常年同期(10.3℃)偏高0.8℃。月内,冷空气活动频繁,先后有4次冷空气过程影响我国,但只有22—26日的冷空气达到全国较强冷空气标准,其他3次都是影响北方的中等强度冷空气;受台风菲特影响,我国华东地区南部和华南地区北部出现一次强降水过程;江南中部及河南等地气象干旱持续或发展;我国中东部大部地区出现雾霾天气。     

2016年7月大气环流和天气分析

2016年7月大气环流特征为,极涡呈偏心型分布,主体强度较常年偏强;中高纬环流呈4波型分布,北半球副热带高压强度偏强,西太平洋副热带高压整体位置偏南,脊线南北振荡。7月我国平均气温为22.6℃,较常年同期（21.9℃）偏高0.7℃。全国平均降水量131.8 mm,较常年同期（120.6 mm）偏多9.3%,华北、江淮和江南等地偏多显著。强降水天气主要出现在华北地区和南方,7月我国出现8次区域性暴雨天气过程,7月18—22日降水过程多方面突破历史极值。7月西北太平洋地区有4个台风生成,3个台风活跃,2个台风登陆我国,数量较历史同期明显偏少。第一号台风是1949年以来生成时间第二晚的首个台风。内蒙古东北部出现气象干旱。中东部地区和新疆持续高温天气,最长持续天数为11 d,最大影响1075个站点;高温极值为46.8℃,发生在吐鲁番站。     

2023年8月大气环流和天气分析

2023年8月大气环流的主要特征是:北半球极涡强度略偏强,500 hPa上亚洲中高纬地区环流形势为“两槽一脊”,影响我国东北、华北地区的高空槽偏强,西太平洋副热带高压西段脊线的平均位置较历史同期偏南。8月,全国平均气温为21.9℃,较常年同期(21.1℃)偏高0.8℃,全国平均降水量为110.9 mm,较常年同期(107.1 mm)偏多3.5%。月内,高温日数较常年同期偏多,区域高温过程持续影响我国,西北、东北等地气象干旱持续发展;我国出现6次暴雨过程。8月共有6个台风在南海和西北太平洋活动,生成个数较常年偏多,登陆个数较常年偏少。强对流天气多发,局地受灾严重,江苏盐城大丰区出现龙卷风。     

2018年7月大气环流和天气分析

2018年7月大气环流的主要特征是极涡偏强且呈单极型分布,中高纬环流呈4波型,西太平洋副热带高压强度较常年明显偏强,位置较常年明显偏北。7月全国平均气温22.9℃,较常年同期偏高1.1℃,为1961年以来历史同期第三高;全国平均降水量133.8 mm,比常年同期（120.6 mm）偏多11%,与历史同期相比呈现北多南少的分布特征。月内我国有7次区域性暴雨天气过程,多站出现极端日降水量。7月共有5个热带气旋在西北太平洋和南海活动,并有“玛莉亚”、“山神”、“安比”3个台风登陆,生成和登陆个数均较常年偏多。我国中东部出现持续性高温天气,同时强对流天气频发,影响范围较广。     

2021年4月大气环流和天气分析

2021年4月中高纬大气环流为三波型,极涡呈单极偏心型分布,强度偏强,西太平洋副热带高压强度较常年偏弱,南支槽较常年偏强。4月主要天气气候特点是全国平均气温为11.1℃,较常年同期偏高0.1℃;全国平均降水量为42.5 mm,较常年同期(45.1 mm)偏少5.8%,其中青海平均月降水量为历史同期第一多。月内,我国遭受四次冷空气过程影响;西南和华南东部气象干旱持续或发展;北方地区出现两次沙尘天气过程;多地遭受风雹袭击,部分地区受灾较重。     

2017年7月大气环流和天气分析

2017年7月大气环流特征为,极涡呈偶极型分布,主体强度较常年偏强;中高纬环流呈5波型分布,北半球副热带高压强度偏强,西太平洋副热带高压整体位置偏北,脊线持续北抬。7月我国平均气温为23.2℃,较常年同期（21.9℃）偏高1.3℃。全国平均降水量112.5 mm,较常年同期（120.6 mm）偏少6.7%,东北地区西部、江南地区东北部、江淮地区西南部和新疆北部等地降水偏少显著。强降水天气主要出现在东北地区和南方,7月我国出现9次区域性暴雨天气过程,7月13—14日降水过程多方面突破历史极值。7月西北太平洋地区有8个台风生成,其中7个台风活跃,3个台风登陆我国,数量较历史同期明显偏多;台风生成个数与1994、1967和1971年并列为历史同期最多。内蒙古东部出现气象干旱,江淮江汉伏旱发展。中东部地区和新疆持续高温天气,最长持续天数为20 d,1884站出现35℃以上高温天气;高温极值为49℃,发生在吐鲁番站。     

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.     

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.     

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     

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.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;