太阳活动对夏季大气环流异常及云南降水的影响

利用1948～2005年太阳10．7cm射电流量资料,采用小波分析、相关合成分析方法对太阳活动与夏季大气环流异常的联系进行了初步的研究,分析了太阳活动对云南夏季降水的影响。研究表明：太阳活动有明显的年际和年代际变化特征,太阳流量特征时间尺度分别约为11年、22年;太阳活动与夏季中高层大气环流异常有十分明显的联系;太阳活动强弱年的大气环流存在显著差异：太阳活动峰值年,南亚高压异常强大,高压脊线偏南,副高表现出明显的偏强偏西;而太阳活动谷值年,南亚高压较弱,高压脊线偏北,副高表现出明显的偏弱偏东。进一步对太阳活动与异常风场的联系进行了分析,得出显著相关区主要位于中高纬,索马里附近为一显著正相关区。太阳活动峰值年,东亚地区西风急流异常偏南偏强,热带季风环流加强,梅雨锋区环流偏弱（夏季风环流加强）;太阳活动谷值年,东亚地区西风急流异常偏北偏弱,热带季风环流偏弱,梅雨锋区环流加强（夏季风环流偏弱）。云南夏季降水与太阳10．7cm流量在年代际尺度上有很好的对应关系,初夏、汛期降水分别有与太阳活动相关的11、20-24年明显周期。滇南、滇西北初夏5月的降水与太阳活动有一定的正相关关系,太阳活动强时,5月降水越多,太阳活动弱时,5月降水越少。     

青藏高原冬春积雪异常和中国东部夏季降水关系的诊断与模拟北大核心CSCD

使用1980 2010年水平分辨率为25 km的遥感积雪深度资料和0.5°×0.5°降水观测资料分析了青藏高原(下称高原)冬春(12月至翌年5月)积雪异常和中国东部夏季(6 8月)降水的关系,然后通过区域气候模式Reg CM4.1在高原冬春季、春季积雪异常强迫下的试验结果进行对比,进一步验证了高原积雪异常影响中国东部夏季降水的机理。遥感积雪深度和格点降水资料诊断分析表明高原冬春少雪,中国东部夏季降水从北向南呈"-+-+"分布;冬春多雪,降水从北向南呈"+-+-"分布。数值模拟试验结果表明,高原冬春积雪异常影响中国东部夏季降水异常,高原冬春少雪,中国东部夏季降水从北向南呈"+-"分布,高原春季少雪,中国东部夏季降水从北向南呈"+-+"分布;高原冬春季以及春季多雪情形下,中国东部夏季降水异常呈相反的空间分布。同时,数值模拟结果表明高原冬春或春季少(多)雪,东亚夏季风偏强(弱),中国东部夏季降水异常。     

青藏高原冬春积雪异常和中国东部夏季降水关系的诊断与模拟

使用1980 2010年水平分辨率为25 km的遥感积雪深度资料和0.5°×0.5°降水观测资料分析了青藏高原(下称高原)冬春(12月至翌年5月)积雪异常和中国东部夏季(6 8月)降水的关系,然后通过区域气候模式Reg CM4.1在高原冬春季、春季积雪异常强迫下的试验结果进行对比,进一步验证了高原积雪异常影响中国东部夏季降水的机理。遥感积雪深度和格点降水资料诊断分析表明高原冬春少雪,中国东部夏季降水从北向南呈"-+-+"分布;冬春多雪,降水从北向南呈"+-+-"分布。数值模拟试验结果表明,高原冬春积雪异常影响中国东部夏季降水异常,高原冬春少雪,中国东部夏季降水从北向南呈"+-"分布,高原春季少雪,中国东部夏季降水从北向南呈"+-+"分布;高原冬春季以及春季多雪情形下,中国东部夏季降水异常呈相反的空间分布。同时,数值模拟结果表明高原冬春或春季少(多)雪,东亚夏季风偏强(弱),中国东部夏季降水异常。     

南亚和东亚热带夏季风强弱不同配置及其对中国夏季降水的影响北大核心

利用NOAA向外长波辐射(OLR)、NCEP/NCAR再分析资料和CN05.1降水资料,研究了南亚和东亚热带夏季风强度年际变化关系,及其强弱不同配置对中国夏季降水的影响。结果表明:南亚和东亚热带夏季风强度变化之间存在同相和反相两种配置,定义的强度同相和反相变化指数可以很好地表征该关系。同相变化模态可能与海温异常时的强El Nino(La Nina)影响有关,其反相变化模态受El Nino(La Nina)以及印度洋海盆一致模的影响,同时西太平洋副热带高压和伊朗高压位置东西偏移和强度变化也影响着不同配置的出现。两者不同配置时,对中国夏季降水的影响不同。当变化呈同相偏强时,夏季中国东部地区降水为“中间少南北多”的雨型。当变化呈反相,东亚热带夏季风偏强南亚夏季风偏弱时,夏季中国东部地区降水为“一致偏少”雨型。     

青藏高原和热带印度洋5月热力异常与新疆夏季降水的关系

基于1979-2017年美国国家海洋和大气管理局(NOAA)提供的海表温度资料和美国国家环境预测中心(NCEP)/美国国家大气研究中心(NCAR)提供的大气环流再分析资料以及青藏高原地区149个站点观测资料计算的地表感热通量和新疆气象信息中心提供的全疆81站逐月降水资料等,研究了5月青藏高原和热带印度洋加热对新疆夏季降水的单独影响和共同影响。结果表明:5月高原感热和印度洋海表温度的异常呈较好的持续性,异常可持续至夏季。奇异值分解(SVD)分析发现5月高原东部(90°E为界)感热与新疆北部及塔里木盆地西南部夏季降水呈显著负相关,热带印度洋海温与塔里木盆地西部夏季降水呈显著正相关。当仅考虑高原感热影响时,高原东部感热偏强(弱)时,对应北疆夏季降水将偏少(多);当仅考虑热带印度洋海温影响时,海温偏暖(冷)时,塔里木盆地西部地区夏季降水偏多(少)。当高原感热和热带印度洋海温均偏强(弱)时,北疆夏季降水将偏少(多),南疆夏季降水将偏多(少)。当高原感热偏强(弱),热带印度洋海温偏弱(强)时,中亚副热带西风急流位置偏北(偏南),中亚和贝加尔湖地区上空分别为异常反气旋(异常气旋)和异常气旋(异常反气旋)控制,新疆上空盛行偏北(南)风,同时热带印度洋水汽不能(能)输送至新疆上空导致新疆夏季降水偏少(多)。     

青藏高原东部和西太平洋暖池区大气热源与中国夏季降水的关系

利用1951～2000年NCEP/NCAR逐日再分析资料计算了大气热源,并对夏季青藏高原东部大气热源异常和西太平洋暖池区大气热源异常对中国夏季降水的影响作了对比分析研究.结果表明,如果高原东部夏季大气热源显著偏强(偏弱),则长江流域地区的夏季降水显著偏多(偏少),而华南东部地区夏季降水偏少(偏多).菲律宾南部附近的热带西太平洋暖池区上空夏季大气热源显著偏强(偏弱)时,同期长江中下游地区偏涝(偏旱),而华南地区、江苏北部-山东南部则偏旱(偏涝).夏季青藏高原东部大气热源异常和热带西太平洋暖池区大气热源异常对中国夏季降水的影响是有差别的,中国的夏季降水受高原东部大气热源影响的显著范围要比受西太平洋暖池区大气热源影响的显著范围要大.无论是高原热源异常还是西太平洋暖池热源异常,东亚地区的大气环流都存在类似EAP型的遥相关波列.大气热源的异常是通过直接影响垂直运动场的异常,进而影响到我国的夏季降水的异常.夏季高原热源或西太平洋暖池热源偏强(偏弱)时,西太平洋副高的脊线比常年位置偏南(偏北).     

山西省夏季年际气候异常研究2．北少（多）南多（少）雨型

采用EOF分解和合成分析方法研究了1960-2003年山西夏季降水异常之北少(多)南多(少)型(第二类雨型)和山西省气温的变化异常.结果表明,两者具有较好的对应关系.分析了第二类异常雨型的时空分布,并给出相应的典型年份.EOF时间系数变化特征揭示了山西夏季降水第二类雨型有显著的年际振荡.利用合成分析,从500hPa位势高度场、纬向风、850hPa风场、700hPa水汽场和水汽输送场等物理量场研究了山西夏季第二类雨型的环流异常特征.结果表明,第二类雨型与弱的东亚夏季风相关联,北多南少和北少南多是弱夏季风的不同表现.山西省夏季降水北多南少年副高呈带状分布,位置偏北,强度较强;中高纬度地区异常波列呈大圆路径分布,在高纬度地区存在纬向排列的- -波列,同时在东亚大陆沿岸存在经向排列的- -波列.并且华北北部有西风异常,北支锋区偏北,由西南向东北水汽输送较强.北少南多年与之相反.海温场分析表明,第二类雨型与中北太平洋海温异常紧密相关.     

江苏近40a夏季降水异常及其成因分析

利用1961-2000年江苏省60个台站的月降水量资料，研究了江苏夏季(6、7、8月)降水量的异常空间分布特征和时间演变规律，分析了与江苏夏季降水有关的大气环流异常的基本特征及引起江苏降水异常的原因。结果表明：(1)江苏夏季降水异常主要表现出两种最为典型的空间分布。其中，第一类雨型反映了全省降水的一致性变化，表现出整体偏多或偏少的情形；而第二类雨型则反映了降水异常的南北反相分布，对应的降水分布为南多北少或南少北多的形势；(2)两类雨型均存在明显的年际变化，两类雨型均与西太平洋副热带高压的南北异常有密切关系，但二者的大气环流背景场又存在显著的不同；(3)不同区域、不同季节的SSTA与两类降水异常存在一定的相关关系，是造成江苏降水年际异常的可能原因之一。前冬北太平洋SSTA偏暖(冷)通常与江苏夏季降水的整体偏多(少)有关；而前期冬季南印度洋、春季热带印度洋、南海及我国东部沿海地区出现的SSTA大范围的冷(暖)异常，通常对应江苏夏季降水南少(多)北多(少)。     

ENSO对次年夏季西北太平洋降水的非对称影响

通过对1979—2018年Ni?o3.4指数和第二年夏季西北太平洋（Northwest Pacific, WNP）降水异常的分析发现,厄尔尼诺强度与第二年夏季WNP降水异常存在显著的负相关关系,而与拉尼娜并没有显著的相关关系。将厄尔尼诺和拉尼娜分为东部型和中部型以后发现,东部型厄尔尼诺和拉尼娜对次年夏季WNP降水的影响不对称,东部型厄尔尼诺强度与次年夏季WNP降水异常为负相关关系,而东部型拉尼娜与次年夏季WNP降水异常关系并不显著。相反,中部型厄尔尼诺和拉尼娜对WNP次年夏季降水的影响较为对称。不管是厄尔尼诺还是拉尼娜,其强度与次年夏季WNP降水异常相关性均非常显著。分析速度势和流函数场以及它们所对应的海表面温度场发现,强东部型厄尔尼诺、强中部型厄尔尼诺、强/弱东部型拉尼娜和强中部型拉尼娜事件中WNP降水主要受风场的辐合辐散控制,其降水异常区与辐合辐散中心对应得很好。而弱东部型厄尔尼诺和弱中部型厄尔尼诺事件中的WNP降水主要与中太平洋海温Gill型对称加热有关,在辐合中心西边产生一对气旋,导致了西北太平洋降水的正异常。而对于弱中部型拉尼娜,由于副热带中太平洋加热的作用,在西北太平洋区东...     

孟加拉湾热源对亚洲夏季风环流系统的影响

利用 1951—2000年NCEP/NCAR再分析逐日及月平均资料和我国 160个测站 1951—2000年月降水量资料,计算了夏季大气热源气候分布,分析了夏季孟加拉湾地区热源年际异常及亚洲季风环流系统的响应,以及夏季孟加拉湾地区热源与中国夏季降水的年际关系。结果表明:夏季亚洲季风区最强的热源中心位于孟加拉湾东北部一带。当孟加拉湾热源异常强 (弱 )时,南亚高压偏西 (东 ),西太平洋副热带高压位置偏东(西);印度夏季风偏强 (弱),东亚热带季风偏弱 (强 )。孟加拉湾热源异常对南亚高压、南亚季风、副热带高压的影响显著,对东亚热带季风的影响不显著。夏季孟加拉湾热源与同期长江以南、华南东部部分地区降水呈明显负相关,而与西南到华南西部地区降水呈明显正相关。     

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.     

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     

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.     

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;