广西盛夏高温天气特点与环流特征

对广西1959－2000年盛夏极端最高气温≥35℃及≥37℃总日数与平均气温≥30℃总日数进行气候分析，发现：各级别最高气温总日数7月份90年代比60－80各年代均明显偏少，而8月份90年代比60－80各年均明显偏多；7月份极端最高气温总日数具有减少趋势，而8月份各级别最高气温总日数具有增多趋势。7月与8月极端最高气温≥35℃与日平均气温≥30℃总日数，分别由1990年以前的多日数期向少日数期转变和由1989年以前的少日数期转多日数期。广西盛夏高温总日数偏多年龄与偏少年份500hPa环流场存在明显的差异，500hPa高度场有较明显的10a尺度变化，而这种10a尺度的环流异常变化是造成90年代广西盛夏8月份高温总日数偏多的重要原因。     

湖北省1994年夏季(6～8月)天气气候概况及其影响

湖北省1994年夏季天气比较炎热,出现四次最高气温≥35℃以上的酷热期,其日数比常年同期偏多,居建国以后第五位,平均气温比常年同期高,梅雨不明显,时间短,整个夏季降雨以过程性和阵性为主,干旱呈阶段性发展,局部地方有洪涝,总雨量大部地区偏少,部分县市出现大风灾害,天气气候对工农业生产比较有利。 1 四次高温酷热期,气温比常年同期高 由于今年夏季西太平洋副热带高压持续偏强,先后共出现四次最高气温在35℃以上的酷热天气。其时间分别是6月28日～7月11日,7月20日～23日,8月 1～6日,8月9～23日。极端最高气温鄂西南长江河谷地区在8月3～4日达到42℃,其他地区在7月3日出现39～40℃。≥35℃的高温日数鄂西南40天左右,武汉市、鄂东北、鄂东南在35天左     

思南2001年气候影响评价

1　全年温度变化趋势全年平均温度 1 7 7℃ ,比历年偏高0 4℃ ,极端最高温度是 7月 7日的 37 9℃ ,极端最低温度是 1 2月 2 3日的 - 0 3℃ ,3月1日气温稳定通过 1 0℃以上 ,比历年提前1 7ｄ ,结束时间为 1 2月 3日 ,比历年推迟 8ｄ ,总积温 582 0 2℃ ,比历年偏多 335 1℃ ,持续2 78,比历年偏多 2 5ｄ ,有利于农业生产。春季倒春寒不明显 ,有利于夏粮作物的生长 ,是大季作物育苗好时机。夏季日平均气温≥ 30℃的有 5ｄ ,日最高值是 8月 7日的 31 5℃ ,极端最高温度≥35℃ ,出现 1 7ｄ ,连续极端最高温度达≥ 35℃以上时段 ,7月出现 4ｄ …     

韶关市近50年强降水频数统计及周期分析

利用韶关市近50年降水资料,对逐日降水量R24（20～20时）≥50．0mm的强降水次数进行统计分析,结果表明韶关暴雨及以上强降水主要集中在多水期的3～7月,其中5、6月份为最多,这与韶关的自然季节降水特点是相吻合的;从50年代至90年代,各年代大暴雨和暴雨分别呈现出偏少．正常-正常-偏少-偏多和偏多～正常-偏少～偏少～偏多的演变趋势;R24≥50．0mm的强降水总次数及历年5、6月份R24≥50．0mm的强降水次数存在周期变化。     

盛夏高温多雨 局地洪灾严重

初夏（6月份）,北疆气温接近常年,南疆气温比常年偏高。盛夏（7－8月）全疆气温比常年仍偏高;7月全疆降水较常年偏少,8月全疆降水较常年异常偏多,但降水时空分布不均,降水主要集中在天山两侧。另外盛夏7月中旬至8月上旬初,我区出现了一场历史上罕见的高空高温天气,造成高山区积雪大面积融化,同时有大降水天气过程出现,造成了我区历史上罕见的高空升温融雪与暴雨相结合的特大洪水灾害。1月平均气温和月总降水量1．1月平均气温7月份,北疆8站平均气温是24．8℃,较常年偏高1．ot;其中北疆北部较常年偏高1．l－2．gCC,偏高幅度最…     

1951—2015年通辽市科尔沁区日气温特征分析

文章利用通辽国家基本气象站1951—2015年逐日最高气温、最低温度和日平均气温,计算了3个要素序列的算数平均值、中位数、众数及样本标准差等基本统计量,分析了每个气温等级出现的频次和不同气温段的气温日较差出现日数、日最高气温〉30℃日数和日最低气温≤-20℃日数等。结果表明：（1）该地极端最高气温达39.4℃,极端最低气温为-33.9℃,最高气温出现在7月12日,最低气温出现在1月17日。（2）全年26.1~28.0℃的最高气温出现频次和16.1~18.0℃的日最低气温出现频次最高。（3）一年中,日最高气温在0℃以上的天数占全年总日数的75%;日最低气温在0℃以下的日数占全年总日数的46%;日较差〉10℃的日数占全年总日数的69%。（4）1981—2015年平均气温比1951—1981年明显升高,表现为低温日数明显减少,而近10a不仅冬季低温日数减少而且夏季高温日数明显增多。     

湖北省1994年夏季（6～8月）天气气候概况及影响

胡北省1994年夏季天气比较炎热，出现四次最高气温≥35℃以上的酷热期．其日数比常年同期偏多，居建国以后第五位，平均气温比常年同期高，梅雨不明显，时间短，整个夏季降雨以过程性和阵性为主，干旱呈阶段性发展，局部地方有洪涝，总雨量大部地区偏少，部分县市出现大风灾害．天气气候对工表业生产比较有利。     

滕州“数九寒天”气候变化特征分析

使用滕州1960-2010年数九期间的逐日气温资料,计算各九及数九的平均气温、最高气温、最低气温及各级日最高最低气温日数,将资料分为近20a （1991-2010年）及前30a（1961-1990年）,用Kruskal-Wallis检验分析两组样本是否有显著差异,结果表明1990年代以来,数九期间平均气温比前30a增高了2.1℃,平均最高气温升高了1.3℃,平均最低气温升高了2.7℃,这些增温是显著的。极端最低气温也显著升高,而极端最高气温变化并不显著。近20a 数九平均气温、平均最低气温冷在四九,极端最低气温冷在一九。数九期间日最高气温＜5℃日数显著减少,而≥10℃日数显著增加,日最低气温≤-10℃及介于-10～-5℃日数均极显著减少,而＞-5℃日数极显著增加。     

万荣县1999年农业气候评价

1气候概况1．1气温年平均气温13．0℃,比常年偏高1．3℃,与去年持平。年极端最高气温37.2℃（7月31日）,年极端最低气温-17．5℃（12月20日）,日最高气温≥35℃日数达8天,稳定通过0℃积温日数278天,积温4821．0℃。终霜出现在3月30日,初霜日出现10月17日,无霜期200天。冬季（199年12月-1999年2月）气温持续偏高又是一个典型暖冬年份。冬季平均气温0．8℃比历年偏高3．1℃,特别是12月下旬平均气温比历年偏高5．2℃。春季（199年3月-5月）气温比历年偏高1．5℃。气温先降后扬,自3月19日以后,气温明显下降,下旬平均气温比历年偏低0…     

揭阳市高温天气的气候背景特征及其成因

对1966～2006年揭阳市日极端最高气温大于等于35℃的高温天气进行统计分析,得出了高温灾害天气的气候特征,并概括出造成揭阳市高温灾害天气的成因以及环流形势.结果表明:揭阳市高温天气具有明显的时间变化,20世纪90年代以前是偏少期,1990～1997年为平均线附近平稳变化期,1998以来为明显偏多期,而且强度也是呈明显上升的趋势,这与全球气候变暖和城市热岛效应的大背景有密切的关系.同时也与区域大气环流异常有关,造成揭阳市高温天气的主要天气系统是西太平洋副热带高压和热带气旋西北气流的增温作用,前者容易造成持续性的高温天气,后者则容易造成极端最高气温.     

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.     

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.     

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.     

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。     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.     

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;