近50a青海西宁气温变化特征

利用西宁市1961～2010年年平均温度、平均最高最低温度、极端最高最低温度,研究西宁气温变化的气候特征。结果表明,近50 a来西宁市4季和全年的平均气温都呈上升趋势,近些年来略有回落,其中冬季增温最明显。西宁市最高最低气温变化在线性增温趋势的稳定性、倾向率和突变现象均有明显的非对称性特征:各季节的平均最高气温的线性趋势均稳定,平均最低气温在冬季和夏季线性增温趋势稳定,最高气温的倾向率在各个季节或年平均上比最低气温的倾向率大得多,冷季的线性倾向率明显大于暖季;极端最高气温线性趋势呈上升态势,极端最低则为弱的下降趋势;极端最低和年平均最低气温突变发生较早,在1963年附近,极端最高和年平均最高气温突变时间大体一致发生在1990年代。     

1954-2013年湖北省黄石市极值气温变化特征分析

利用黄石市气象台1954年1月1日至2013年12月31日共60a的地面观测资料,选取逐日的平均气温、最高气温和最低气温做为研究对象,采用气候趋势分析、相关分析、Mann-Kendall突变检验分析和小波分析等方法对黄石市极值气温变化特征进行分析,结果表明:(1)1954-2013黄石市年平均气温、平均最高气温和平均最低气温呈波动上升的趋势,其中年平均气温和平均最低气温上升趋势显著,对于近60a黄石市年平均气温的升高,年平均最低气温的贡献是主要的;(2)近60a黄石市极端最高气温和极端最低气温均呈波动上升的趋势,其中极端最低气温上升趋势显著,1984-2013年极端最低气温的升高是造成近60年极端最低气温显著升高的主要原因;(3)近60a黄石市年最大日较差呈波动下降的趋势,但不显著,平均最低气温的上升速度明显大于平均最高气温的上升速度,极端最低气温的上升速度明显大于极端最高气温的上升速度,这造成了气温日较差的不断减小;(4)近60a黄石市气温(年平均气温、年最高\最低气温、极端最高\最低气温)的显著升高,与最高气温出现在20℃以上的天数增加和出现在20℃以下的天数减少有关,与最低气温出现在10℃以上的天数增加和出现在10℃以下的天数减少有关,其中T0℃的高温日数和低温日数的显著减少以及20≤T30℃的低温日数的显著增加贡献最大。     

钦州市荔枝种植的气象条件分析

1 荔枝种植的气候环境分析 钦州市地处南亚热带季风海洋性气候区,年平均气温为22℃,极端最低气温仅1955年出现过-1.8℃,其余年份极端最低气温均在0℃以上,荔枝的安全越冬不成问题,冬季干凉少雨,夏季高温湿热,对荔枝的正常生长发育较为适宜,但在高产、稳产、优质的生产上,与邻县灵山相比,仍存在着一定的不利因素,其主要表现在:     

朔州市气温和降水变化特征分析

朔州市的年平均气温、年平均最高气温、年平均最低气温自20世纪70年代中期以来呈上升趋势，进入90年代后，这种趋势有所加快，尤其以冬季升温最为明显。年平匀气温以0．43℃／10a的速度上升；平均最低气温升温幅度明显高于平均最高气温；年平均降水量略呈下降趋势，主要是由夏季降水减少所致。     

龙胜县近50a来冬季气温变化特征分析

该文采用龙胜站1960年12月—2010年2月的逐日平均气温和最低气温资料,用一元线性回归方法对龙胜50a来年平均气温、冬季平均气温、冬季平均最低气温、冬季极端最低气温、冬季寒冷日数与冬季冷积温进行了统计分析。结果表明：50a来龙胜年平均气温、冬季平均气温、冬季平均最低气温和冬季极端最低气温都呈明显上升趋势,其中冬季极端最低气温的上升最为显著;冬季寒冷日数与冬季冷积温都呈明显下降趋势。年平均气温和冬季平均气温的年代际变化特征基本一致,20世纪90年代开始都呈明显上升趋势;冬季平均最低气温和冬季极端最低气温自20世纪60年代开始始终维持上升的年代际变化趋势;冬季寒冷日数和冬季冷积温自20世纪80年代开始始终维持下降的年代际变化趋势。特别是20世纪90年代以来,龙胜年平均气温、冬季平均气温、冬季平均最低气温和冬季极端最低气温的年代平均值都高于多年平均值,而冬季寒冷日数与冷积温的年代平均值都低于多年平均值,龙胜处于相对暖期。     

锦屏县1961—2008年气温变化分析

通过一元线性回归、滑动平均等方法,对锦屏县1961-2008年近48 a来的平均气温、平均最高气温及平均最低气温变化进行分析。结果发现,近48 a来,锦屏县的年平均气温呈上升趋势(0.132℃/10 a),特别是90年代增温明显,且冬季变暖趋势大于夏季。年平均最高气温与年平均最低气温也呈上升趋势,但最高气温的增速(0.075℃/10 a)慢于最低气温的增速(0.204℃/10 a)。     

盘县半个多世纪的气温变化特征分析

利用贵州省六盘水市盘县气象观测站1951-01—2007-02连续、可靠的地面月平均气温、月平均最高、最低气温以及日极端最高、最低气温资料,对盘县年及各季平均气温、年平均最高、最低气温的变化进行分析。结果表明:盘县半个多世纪气温总体呈上升趋势,并且具有冬暖夏热或冬冷夏凉的典型气候特征,同时极端最高气温主要发生在20世纪50年代,极端最低气温主要发生在20世纪60年代。近10 a盘县气温升高趋势更加突出,暖冬气候特征更加明显。     

河北省极值气温变化特征

利用河北省60个气象观测站资料,对全省近50年极值气温变化特征进行了分析,结果表明:极端最高气温线性变化趋势不明显,但年代际变化特征突出,而极端最低气温线性升高趋势明显。低于-30℃的极端寒冷日呈线性减少趋势,而高于40℃的极端炎热日线性变化趋势不明显,但年代际变化特征突出,20世纪90年代后期以来呈多发的特点。最低气温出现偏冷段(-10℃)的天数呈线性减少趋势,出现在偏暖段(20～30℃)的天数呈线性增加趋势,在其他界限气温的天数变化趋势不明显。最高气温出现在偏冷段(-30～0℃)的天数呈明显减少趋势,在其他界限气温的天数变化趋势不明显。河北省无霜期、无冰冻期均呈明显延长趋势,平均每10年分别延长4.5天、4.6天。年平均最高气温、最低气温和平均气温都呈显著的线性升高趋势,平均每10年分别升高0.21℃、0.45℃、0.30℃,低温升温速率明显大于高温升温速率。日较差呈逐年减小趋势,平均每10年减小0.25℃。空间上最低气温表现为全省明显升高,而最高气温升温主要集中在中北部和东部沿海地区,南部升温不明显,日较差大部分地区为逐渐减小趋势。     

包头市近50年气候变化及对策

利用包头市1961—2010年的逐日气温、降水、风等气象要素资料,分析了近50年气候变化的时空特征。结果表明:包头市气候发生了明显的变暖过程,全市年平均气温升高了1.9～2.3℃,年平均最高气温升高1.3℃,年平均最低气温升高2.2～2.7℃,特别是20世纪80年代中期以后气温持续上升,冬季变暖尤为明显。而降水量没有趋势性的年际变化,呈现出箱体内的震荡。     

山东德州市近50年极端气温时空变化特征

利用趋势系数、突变检验等方法分析山东德州市所属11个台站1966—2015年气温观测资料,结果表明:年平均、最高最低和极端最低气温都为上升趋势,年平均最低气温增温幅度是平均最高气温的3.46倍,极端最低气温增温幅度是平均最低气温的1.66倍。年极端最高气温呈下降趋势。高温日数和低温日数都为减少趋势,低温日数减少明显。在1988年出现平均最低气温突变,在1989年出现平均气温突变,在1992年出现平均最高气温突变,低温日数在1986年出现突变。各县之间最高气温无明显差异,最低气温差异明显。最低气温受城市化影响最显著,德州市区年平均最低气温在全市属最高。     

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.     

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     

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。     

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.     

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正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted