南宁市大雾气候特征分析

利用南宁市所管辖8个站1965-2002年的观测资料，分析了南宁市大雾天气的分布情况和气候变化特征。结果表明：南宁市大雾的平均季节分布为冬季最多，夏季最少。各月大雾总日数出现频率呈双峰型，多项式回归分析结果表明大雾日数的年际变化呈逐渐减少趋势。     

江苏省高影响性大雾天气演变特征及综合影响评估

利用江苏省分布较为均匀的59个台站1961—2006年的大雾日数资料,分析了大雾日数的年际变化特征;利用1961—2006年南京、淮安、徐州、赣榆、射阳、东台、吕泗、溧阳8站的资料重点研究了大雾的生成、消散及大雾持续时间变化特征。结果表明,年雾日数呈先升后降的分布形势,80年代前中期为大雾的鼎盛期,之后呈较快的下降趋势。大雾持续时间呈显著增长趋势,主要表现为雾消时间的推迟。考虑大雾日数和大雾持续时间2个因子的综合作用,设计了大雾综合影响指数,该指数的年际变化表征了江苏区域大雾天气的高影响性趋强。     

我国大雾的气候特征及变化初步解释

为了分析全国范围内大雾的气候特征及变化，利用1950年以来我国气象系统地面观测网679个国家基本（基准）站的大雾天气现象观测资料，分析了我国大雾空间、时间分布的基本气候特征。从整体来看，我国大雾分布呈现东南部多西北部少的特点。在月大雾的日数、月最多大雾日数、大雾季节分布中都显示出北南、西东的地区差异及局地明显的特征。分析表明，我国大部分地区大雾日数呈减少趋势。而浓雾出现的年日数变化不明显；文章对大雾日数的变化原因进行了初步解释。     

鞍山地区大雾天气气候特征及成因探讨

利用1951—2014年鞍山地区大雾天气观测资料,采用线性趋势法和多项式趋势法分析了鞍山地区大雾天气的空间及时间变化特征。结果表明:1951—2014年鞍山地区年和季大雾日数呈东南部地区多、西北部和中部地区少的空间分布特征,同时各区域大雾日数的季节变化差异显著,东南部山区夏季和秋季(6—10月)为大雾多发季,其他地区深秋和冬季(11月至翌年1月)为大雾多发季;鞍山市各区域大雾日数趋势变化的差异较大,中部地区大雾日数呈减少的趋势,西部地区大雾日数呈弱增加的趋势,东南部地区大雾日数呈增加的趋势。近64 a鞍山地区区域性大雾过程最长持续时间为7 d,全区性大雾过程较少,一致性大雾过程仅出现8次;鞍山地区大雾天气受地形影响较大,具有明显的区域特征,平原地区大雾天气少、山区大雾天气多,且山区连续性大雾过程持续时间较长。鞍山地区大雾过程持续时间多集中在1—2 h,大雾天气出现时间主要集中在05—06时、08时和20时前后,大雾过程日最长持续时间为20—21 h。在1961—2010年鞍山地区大雾日数的年代际变化中,东南部山区大雾日数呈增加的趋势,中部地区大雾日数呈减少的趋势;特别是20世纪90年代以后,中部地区大雾日数减少明显,东南部地区大雾日数增加显著,区域性差异较大。同时,人类活动对气候环境的反馈影响可能也是鞍山地区大雾天气变化的一个原因。     

1961~2005年中国大雾天气气候特征

利用1961～2005年中国541个地面台站观测的能见度和相对湿度资料,分析了中国大雾时空分布特征和趋势变化特征.结果表明:中国大部分地区冬半年大雾日数明显偏多.夏半年明显偏少.其中11月最多,6月最少.在空间分布上,中国东部降水量较多的平原和丘陵年均大雾日数较多,而内蒙古大部和中国西部大部分地区年均大雾日数较少,多在1天以下.长江中下游和黄淮地区一些省市,是大雾天气多发的地区,并且具有明显正变化趋势,年大雾天气日数呈波动增多的趋势,波动的周期大约为1.5年.1982、1987、1989～2000年和2002年是大雾日数较多的年份,而1967年则是大雾日数明显偏少的年份.     

河南省大雾的时空分布特征及500hPa环流特点分析

对河南省45年的大雾日数进行分析研究,结果表明：河南省年平均大雾日数秋冬季多,春夏季少,雾日主要集中在11月到翌年1月;大雾区域分布极不均匀,总体来说是东多西少,平原和盆地多山区明显少,全省有5个多雾中心。选择40个代表站进行经验正交函数（EOF）展开分析,前三个模态的积累方差贡献率为76．5％,通过相关系数和第一模态的时间系数分析,全省大部分地区大雾日数呈增加的趋势,与温度变化趋势相同。小波分析存在2～4年、8～10年和19～22年的周期变化。进一步对历史上典型多雾年和少雾年500hPa高度距平场分析,发现多雾年与少雾年欧亚中高纬度地区高度距平趋势恰好相反,多雾年呈＋-＋分布,而少雾年呈-＋-分布。     

福建近44年雾日趋势变化特征及可能影响因素

应用1961—2004年福建省50个气象站逐月大雾及浓雾日数资料, 分析了全省大雾日数及浓雾日数的年、季分布特点、长期变化趋势、年代际变化特征以及可能的影响因素。结果表明:全省年、季雾日数分布均表现为中部及三明西部的多雾区, 沿海及南部地区的少雾区, 而多雾区中浓雾所占的比率达30%以上; 全省年、季大雾日数大部分地区表现为明显的减少趋势, 仅在龙岩西部呈增加趋势, 而浓雾的减少趋势不如大雾; 年、季雾日数具有明显的年代际变化特征, 年、季雾日数在20世纪80年代中期左右转为明显偏少期, 之前则为明显的偏多期。文中还重点分析了6个代表站大雾与浓雾的趋势与月际分布特征。进一步研究指出, 年雾日数与年平均气温有较好的负相关关系, 而与年平均相对湿度有很好的正相关关系, 同时与森林覆盖率的变化有一定关系。     

近48a六盘水市大雾天气气候特征分析

该文利用1961—2008年六盘水市3个测站的逐日大雾天气现象观测资料,采用线性倾向估计、Mann-Kendall突变检验等方法,对六盘水地区大雾天气的分布情况、年际变化等进行分析,结果表明:六盘水大雾天气差异显著。出现大雾日数最多的是水城,最少的是盘县。各月均有大雾发生,大雾主要出现在11—次年2月,5-7月相对最少。近48a六盘水大雾日数呈下降趋势,大雾日数以每10a减少0.5d。20世纪60年代和80年代大雾日数较多,70年代和90年代相对偏少,2001年以来大雾天气明显减少。六盘水年大雾日数在1972年发生突变,表明1972之前大雾日数较多转为减少的趋势。     

招远地区大雾气候特征分析

该文采用1961—2010年招远气象站大监站地面气象观测资料,对所选大雾的气候资料进行整理归纳,利用统计方法统计出历年各月、季、年际和年代大雾的平均日数等特征量,并进行大雾的变化特征分析。结果表明,招远地区大雾年际间差异很大,20世纪70—80年代为大雾多发年代,90年代开始呈缓慢增加趋势,年日数呈振荡增加趋势,季节分布特别明显,以冬季最多,春季最少,出现最多月份为12月和1月,生成主要是在夜间至清晨,消散多在上午到中午。     

黔东南大雾气候特征

利用1961~2007年黔东南州16个地面气象观测站逐日大雾日数资料,对黔东南州大雾日数的日、年、季分布特点、长期变化趋势、年代际的变化特征等进行分析。结果表明:20世纪60年代平均雾日最多,80年代最少,进入21世纪后具有逐渐增多的趋势;以秋季雾日最多,冬季次之,春季最少;以11月为最多,2月为最少。并且大雾日数有准40年的周期,在大雾多发期存在着准5年的周期性。大雾主要分布在黔东南州的中部,东南部和西北部相对较少。     

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.     

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.     

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.     

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。     

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;     

Information for Contributors

正Journal of Meteorological Research is an international academic journal in atmospheric sciences edited and published by Acta Meteorologica Sinica Press,sponsored by the Chinese Meteorological Society.It has been acting as a bridge of academic exchange between Chinese and foreign meteorologists and aiming at introduction of the current advancements in atmospheric sciences in China.The journal columns include Articles.Note and Correspondence,and research letters.Contributions from all over the world are welcome.