五道梁地区总辐射的年际变化

利用实测的太阳总辐射通量密度及地气温差资料，建立了月平均地气温差与月平均太阳总辐射通量密度的回归方程，并用该回归方程计算了五道梁地区1980-1993年共14年的月平均总辐射通量密度，分析了该地区总辐射通量密度的年际变化，发现该地区总辐射通量密度具有较明显的6～7年的振荡周期。20世纪后10年年平均总辐射通量密度有增大的趋势。     

由GMS资料估算我国东部地区夏季地表净辐射

利用1994年6月、7月上海和北京地区08—17时地面观测资料及同期GMS卫星红外、可见光数字云图资料，用统计的方法讨论了地表净辐射与卫星测值之间的关系，建立了用卫星资料计算08—17时各时刻地表净辐射和08—17时总地表净辐射的估算模式，并分别以1994年7月1日14时的云图和济南地区为例作了检验。结果表明用卫星数字云图资料估算地面08—17时各时刻地表净辐射和08—17时总地表净辐射是可行的。     

青藏高原地区大气顶净辐射与地表净辐射的关系

地表净辐射为地气系统净辐射与大气层净辐射之差。对大气层净辐射作不同的假定，可将地表净辐射与大气顶辐射收支之间的关系表示成不同的形式。本文利用１９８２年８月—１９８３年７月青藏高原地区地面辐射收支观测资料及同期ＮＯＡＡ－７辐射收支资料，用统计方法讨论了大气顶净辐射与地表净辐射之间的相关性，建立了两者之间的回归方程，并在此基础上分析了青藏高原地区月平均地表净辐射的时空分布特征。     

青藏高原太阳总辐射的计算方法的讨论

本文利用1982年8月—1983年7与1978—1980年青藏高原地区总辐射的观测资料与二流近似的模式计算讨论了高原地区总辐射的气候学计算方法,计算了纬度24°—46°不同海拔高度,不同地表反射率条件下的晴天地面总辐射的月平均值,并绘制了青藏高原地区1月与7月晴天地面总辐射的分布图。     

昌吉市太阳总辐射的气候学计算及其变化特征分析

利用昌吉市1961—1997年的逐日气候资料,对昌吉市1961—1997年多年平均逐日太阳总辐射进行了气候学计算,并分析了其变化特征和变化趋势,结果表明:昌吉市太阳总辐射多年平均年日总量为22.82MJ.m-2.d-1,太阳总辐射在8～9月份最高,12月份最低,昌吉市的太阳总辐射呈逐年下降趋势。     

半干旱草原下垫面能量平衡特征及土壤热通量对能量闭合率的影响

土壤热通量在半干旱草原下垫面能量平衡研究中极为重要,土壤热通量估计不够准确是导致地表能量不平衡的一个重要原因。利用2008年6—9月锡林郭勒草原主生长期地表辐射、通量和土壤温度梯度观测资料,研究中纬度半干旱草原下垫面地表能量平衡特征。首先,在分析能量平衡各分量月平均日变化特征的基础上,通过对土壤热流量板观测的5 cm深度土壤热通量(G)的相位前移,研究了土壤热通量相位滞后对地表能量平衡产生的影响;其次,利用谐波分析方法,通过计算地表土壤热通量(Gs),分析了地表到热流量板之间的土壤热量储存对地表能量平衡的影响。结果表明:(1)将土壤热通量相位前移30 min,湍流通量与可利用能量(Rn-G)线性回归的斜率从0.835增加到0.842,地表能量闭合率提高了0.7%,但仍有15.8%的能量不闭合;(2)考虑了地表到热流量板之间的土壤热量储存之后,湍流通量与可利用能量之间的回归斜率达到0.979,能量不闭合程度仅为2.1%。     

中国不同时间尺度地表太阳总辐射估算研究

利用全国95个气象站点逐日地表太阳总辐射和日照时数资料,通过最小二乘法拟合回归建立地表太阳总辐射气候学计算模型。通过对比分析以日值和月值为起点的地表太阳总辐射计算模型的精度,确定了全国不同省份和区域的不同时间尺度（月、季节、生长季和年）地表太阳总辐射计算模型,并探讨了经验系数a、b值的分布及变化特征。结果表明,以日值和月值为起点建立的月、四季、生长季和年地表太阳总辐射计算模型精度无显著性差异,相对误差均低于8.5%,但以日值为起点的计算模型a、b值变异性更小。在以日值为起点建立计算模型的前提下,全国各地a、b值自西北部向南部减小,且从四季到生长季再到年尺度,随着时间尺度增大,a、b值振幅减小。根据不同省份年地表太阳总辐射计算模型经验系数a、b值,全国可划分为新甘蒙地区、青藏高原地区和中东部地区3个区域,分别确定了每个区域四季、生长季和年尺度下地表太阳总辐射计算模型。各区域不同时间尺度地表太阳总辐射计算模型均通过了显著性检验（p<0.01）,其中青藏高原地区和新甘蒙地区模型相对误差低于8.0%,模拟精度较高。     

珠峰北坡地区地表辐射和能量季节变化的初步分析

对青藏高原地区地表能量的研究是一个十分重要的问题.利用中国科学院珠穆朗玛峰大气与环境综合观测研究站2006年5月至2007年4月一年的观测资料,分析了青藏高原珠峰地区的地表能量,即净辐射通量、感热通量、潜热通量和土壤热通量,得到了一些有关珠峰地区地表能量的结果,即太阳总辐射、大气长波辐射、地面长波辐射和净辐射呈现出明显的年变化特征,净辐射、感热通量、潜热通量和土壤热通量得到的日变化是很明显的.并且讨论了计算地表能量通量的方法及其优缺点.     

唐古拉地区超声雪深传感器SR-50监测研究

利用2004年5月以来超声雪深传感器SR-50在青藏高原唐古拉综合监测场获取的实时积雪资料和相关气象数据,评估了SR-50在青藏高原积雪监测中的性能和作用,并对青藏高原腹地多年冻土区积雪变化特征进行初步分析。结果表明:超声雪深传感器SR-50对不同时间尺度的地表积雪过程均有较好的监测能力。监测数据清晰地显示唐古拉地区地表积雪深度在夜间相对稳定、在日间迅速降低的特点。唐古拉地区平均年积雪日数为82 d,各月均有地表积雪出现,但夏季的地表积雪较少且持续时间很短。该地区地表积雪总体上呈厚度较薄、消融较快、持续时间较短的特点。2005—2008年该地区瞬时最大积雪深度为22 cm,日平均积雪深度小于5 cm日数占总积雪日数的71.58%。     

高寒地区日光温室地温变化及预报

利用2012年4月至2013年3月青海大通县日光温室内外地温、气温资料和大通县气象站人工观测资料,分析了高寒冷凉地区不同天气类型下日光温室地温变化规律。结果表明;研究区日光温室内日地温呈正弦曲线变化,晴天变化幅度最明显,阴天最小,地温变幅为地表〉5 cm〉10 cm〉15cm〉20 cm;室内地表、10 cm和20 cm平均地温月变化呈波形变化,最大值出现在7月,最小值在12月;随着深度增加,平均地温年较差逐渐减小;晴天、多云天、阴天不同深度地温平均日较差分别为9.6、8.3、6.1℃;地温日垂直变化仅在14时随着深度增加逐渐下降;除晴天室内最高温度外,其余温度要素与地温之间存在极显著正相关关系;建立的日光温室内10 cm最低温度预报方程和地表最低温度预报模型,可以在业务服务中应用。     

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。     

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 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;