青藏高原积雪对广西气候影响的过程和物理机制分析

利用1967～1997年500hPa高度场及同期副热带高压资料，分别将年、春、夏、秋、冬季的青藏高原积雪与这两者之间的联系进行分析，并“借用”他人通过数值模拟所得结果来印证由统计分析而得到的相关关系，从而揭示青藏高原积雪对广西气候影响的过程和物理机制。结果表明：青藏高原积雪多、少雪年时，在高原主体所处的范围以及我国以北以贝加尔湖为中心的区域范围内，500hPa高度场的距平符号呈反向变化形式，高原多雪时，高原主体上层500hPa高度场为负距平，高原少雪时，则为正距平。而青藏高原多雪时，太平洋副热带高压脊线要比少雪年位置偏南。     

1961—2004年青海积雪及雪灾变化

利用1961—2004年青海省海西东部和环青海湖地区地面气象观测资料和北半球500 hPa高度场网格点资料, 整理了地表积雪序列和雪灾年表, 并对积雪的年代际变化特征和雪灾发生的机理及其成因进行了研究。结果表明:海西东部和环青海湖地区出现区域性雪灾的几率为15.9% (7/44), 而出现局部雪灾的几率仅为9.1% (4/44)。海西东部和环青海湖地区近44年来冬季累计积雪量的缓慢增加易形成雪灾和低温冻害。造成该区域主要降水的影响系统是高原槽、蒙古槽和高原低涡, 若后冬至春季北半球500 hPa极涡中心偏向西 (东) 半球, 青藏高原与我国东部沿海地区高度距平场形成“西低东高 (西高东低)”的距平分布型时, 海西东部和环青海湖地区容易出现多 (少) 雪年。     

青藏高原积雪异常与广西气候的关系

利用青藏高原55个地面观测站的积雪日数、积雪深度资料,按年、春、夏、秋、冬不同时段分别进行时段距平计算,选取积雪日数、积雪深度均为正、负距平的年份,划分为高原积雪偏多、偏少年,在此基础上选取距平绝对值相对较大的年份为显著多雪年、显著少雪年。然后分析青藏高原积雪异常与广西异常气候事件的关系特征以及青藏高原积雪显著多、少雪年与广西不同时段的降水、气温的关系特征。结果发现:青藏高原积雪偏多、少与广西异常气候事件的关系不十分明显,好的对应概率也只有60%～75%左右,而青藏高原积雪显著多、少雪年对广西某些时段的降水、气温存在全区性的影响。     

青藏高原积雪异常与广西气候的关系

利用青藏高原55个地面观测站的积雪日数、积雪深度资料。按年、春、夏、秋、冬不同时段分别进行时段距平计算，选取积雪日数、积雪深度均为正、负距平的年份，划分为高原积雪偏多、偏少年。在此基础上选取距平绝对值相对较大的年份为显着多雪年、显着少雪年。然后分析青藏高原积雪异常与广西异常气候事件的关系特征以及青藏高原积雪显着多、少雪年与广西不同时段的降水、气温的关系特征。结果发现：青藏高原积雪偏多、少与广西异常气候事件的关系不十分明显。好的对应概率也只有60％-75％左右。而青藏高原积雪显着多、少雪年对广西某些时段的降水、气温存在全区性的影响。     

国家气候中心海气耦合模式汛期降水预报的一种订正方案及其试验

用奇异值分解(SVD)方法,分析了1983～2003年夏季国家气候中心海气耦合模式500hPa高度预报场与中国特别是华中区域降水场、1971～2000年夏季NCEP/NCAR 500hPa高度场与中国特别是华中区域降水场的关系.结果表明:夏季NCEP/NCAR 500hPa高度场与中国特别是华中区域降水场关系明显较模式500hPa高度场密切,若夏季NCEP/NCAR 500hPa高度场南、北半球副热带高压较强(弱),北半球副热带高压主体偏南(北),则长江流域、东北地区中部及青藏高原东侧将降水偏多(偏少).对比分析结果,发现国家气候中心海气耦合模式存在一定程度的预报误差,如长江流域误差就较为明显.作者提出一种订正方案,利用SVD从模式500hPa高度预报场中提取大尺度信号,借助最优化技术,合理订正误差,改进降水场的预报.经试验表明:订正后降水场预报的距平同号率有可能接近NCEP/NCAR 500 hPa高度场相当的技巧水平.     

青藏高原积雪异常与大气环流异常间关系分析

在参考前人对青藏高原积雪异常年的划分成果的基础上,初步确定出1957—2003年的典型积雪异常年。采用NCEP提供的全球144×73个格点1957—2003年前一年12月至当年5月100 hPa和500 hPa的月平均高度场资料,分析了青藏高原积雪异常与大气环流异常的相互关系,提出了大气环流异常影响青藏高原积雪异常可能的天气气候成因机制;应用三因子最优子集二级判别,建立了判别青藏高原积雪多雪年/少雪年的判别方程,作为客观、定量判断高原积雪异常的指标;结合初步确定的典型青藏高原积雪异常年,用得到的最优判别方程进行划分,并经反复论证后,确定出1957—2003年青藏高原积雪正常略多年和正常略少年。     

北半球大气环流异常与广西夏季高温天气

利用1951~2003年北半球500 hPa月平均高度场资料,对广西多高温年份和少高温年份的大尺度环流场进行对比分析,发现多高温年和少高温年500 hPa位势高度距平场差异明显,主要表现在:北太平洋阿留申群岛到副热带地区在冬春季和前汛期都呈现相反的南北距平分布结构;盛夏,多高温年在乌拉尔山至贝加尔湖地区及孟加拉湾至我国西南地区是正距平区,而少高温年在上述地区为负距平中心。典型相关分析表明,7~8月500 hPa高度场与前期1月、4~6月的高度场有密切的联系,高空槽脊的强弱分布及西太平洋副高等大尺度天气系统的变化本身具有一定的内相关,从而揭示了高温天气形成的大尺度环流变化的一些事实。     

青海南部地区初冬雪灾变化及环流特征

利用青海南部地区1961~2004年气温、降水、积雪等资料,分析了初冬雪灾变化及环流特征。结果表明:青海南部地区初冬降雪量呈缓慢减少的变化趋势,平均积雪量变化与年及其它季相比,呈微弱的减少趋势,平均积雪量与气温呈反相关,而与降雪量呈正相关;影响青海南部地区初冬降雪的主要天气系统是西风带南北槽结合类、移动性高原槽类、高原低涡类、高原切变类、孟加拉湾风暴类;典型多雪(少雪)年高原及南亚与中亚地区850 hPa温度距平场配置为“南正北负”(“南负北正”)型5、00 hPa高原与东部沿海地区距平分布为“西低东高”(“西高东低”)型。     

青藏高原春季积雪多、少年中低层环流对比分析

利用青藏高原(下称高原)68个气象测站1961-2007年逐日积雪观测资料,分析了高原春季积雪日数变化及其异常偏多、偏少年的环流特征,还深入分析了春季积雪的多少对北半球夏季环流的影响。结果表明,在高原春季积雪日数偏多、少年,在500 hPa高度场上欧亚(东半球)地区中高纬度虽然均表现为两槽一脊的环流形势,但积雪日数偏多、少年槽脊的位置和强弱明显不同。同期春季,当高原春季积雪日数偏多(少)时,500 hPa环流场上冰岛低压偏强(弱)、蒙古高压偏强(弱)、印度低压偏弱(强)。高原春季积雪与夏季北半球的主要大气活动中心和影响中国夏季气候的主要大气环流系统之间存在紧密联系,当高原春季积雪日数偏多(少)时,夏季500 hPa环流场上东亚地区易(不易)形成阻塞高压,同时西太平洋副热带高压易(不易)偏南。这种关系说明高原春季积雪有一定前兆意义,对中国短期气候预测有重要的指示意义。     

青藏高原地面感热对北半球大气环流和中国气候异常的影响

在青藏高原地面感热通量的基本气候特征以及异常变化的空间结构和时间演变趋势研究的基础上,进一步就高原地面感热异常对北半球大气环流和中国气候异常的影响进行诊断研究,并利用IAP2-LAGCM对青藏高原地面感热异常的影响进行了数值试验.结果表明:冬季地面感热在青藏高原西部、藏南谷地、横断山地区异常偏强,中、东部异常偏弱时,可使北半球500 hPa高度场表现出较明显的EU型和PNA型;高原西部、青海中北部异常偏弱,高原中部及东南部异常偏强时,使北半球100 hPa高度场的年际差异加强;西部、南部为正,柴达木及青海东部地区为负时,则新疆南部、西北东部及江南地区少雨,全国大部地区气温偏高.夏季高原地面感热通量距平特征为西南、藏南谷地、横断山区偏强,高原大部(中心在青海南部)异常偏弱时,则500"a高度场上青藏高原南部(孟加拉湾)高度偏高,高原北部高度偏低,负值区在帕米尔;当感热通量距平特征为高原西南、藏南谷地、横断山区偏弱,高原大部异常偏强时,有利于南亚高压的建立与维持;当地面感热通量呈南正北负距平差异时,长江上游、黄河源头及西北地区东部和东北部分地区降水量比常年偏多,气温偏低,中国东部、南部降水偏少,气温偏高.通过数值模式进行的敏感性试验证实了大气环流及区域气候变化对青藏高原地面感热总体异常的响应.       

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.     

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.     

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.     

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