EOF在广西春季降水分析中的应用

利用EOF方法对广西1961~2003年春季(2~4月)降水进行分析,得出广西降水一致性即旱或涝为春季主要降水类型与桂北-桂南和桂东南-桂西北反位相型。依此广西春季降水可分为桂东北、桂东南和桂西三个区。利用第一时间系数、67个站平均降水距平值和正负距平站数三种方法统计出广西春季历年的旱涝年,1961~2003年期间存在11a涝和14a旱。在降水异常年里桂东南降水变化最大,其次为桂东北,变化最小为桂西。     

Morlet小波分析在广西春季降水分析中的应用

利用广西67个气象观测站1961—2003年的降水资料,采用Morlet小波分析了桂东北、桂东南和桂西地区春季(2—4月)降水年际变化,结果表明普遍存在着2 a、4 a和8 a周期振荡信号,各信号频率分布的时间域及其强度也存在着差异,短周期强于长周期。广西春季降水长期变化总体呈下降的趋势。     

广西暴雨非均匀性分布特征研究

利用广西1979—2008 年83 个气象观测站的逐日降水和NCEP/NCAR 再分析资料,采用蒙特卡罗检验等方法,计算和分析广西暴雨非均匀性分布及其变化特征。结果表明,广西暴雨主要发生在汛期(4—9 月),暴雨总站次约占全年总数的9 成;年暴雨量占全年总降水量的比例随年际变化有增加的趋势,即以后发生极端强降水的可能性增大。广西暴雨集中度分布为桂东大于桂西,桂西北和沿海地区的暴雨集中度变化趋势大部分为正趋势,桂东南大部分为负趋势。桂东北和西南地区暴雨集中期最晚,百色北部山区和桂东南地区最早,暴雨集中期气候趋势是桂东大部分地区和沿海地区有偏晚趋势,桂中和桂西大部分地区有偏早趋势。冬春季青藏高原南部和西太平洋高度场负距平,夏秋季副热带高压偏强、面积偏大、脊线偏西,这种稳定的东高西低形势有利于广西暴雨集中度偏大。冬季青藏高原南部和西太平洋地区的高度场均为正距平,春夏秋季青藏高原南部及西太平洋高度场的周期性变化特征使广西暴雨集中度偏小。夏季风强(弱)的年份孟加拉湾向广西输送的水汽通量少(大),低空风速小(大),造成广西除了北部山区和北海以外大部分地区暴雨集中度偏小(大)。      

基于Z指数的江西省旱涝指标与时空分布特征

利用1961—2020年江西省逐日降水资料,基于Z指数分析确定了适用于江西省的旱涝指标。运用M-K检验、小波分析和EOF等方法分析了江西省旱涝时空分布特征。结果表明,1961—2020年江西省降水量年际变化大,20世纪90年代出现突变,但未出现显著的持续增加或减少。江西省干旱、雨涝事件存在准20 a主周期,从90年代开始偏涝年份明显增多,且雨涝呈增强的趋势。江西省旱涝主要存在4种空间分布型,分别为全区型、北涝（旱）南旱（涝）型、西涝（旱）东旱（涝）型、中心涝（旱）南北旱（涝）型,累计贡献率为83.61％。Z指数作为表征江西省旱涝指标的方法具有一定的适用性。     

广西春夏季旱涝的等级划分及时空分布特征分析

利用广西80多个站点1961～2006年的逐月降水资料,采用Z指数定义方法,对广西春夏季的旱涝进行等级划分.利用经验正交函数(EOF)分析方法对春夏季旱涝等级的时空分布进行研究,给出了四个旱涝典型场的分布特征.分析结果表明:全区性偏涝或偏旱是春夏季早涝分布的最主要型态;春季和夏季的前4种分布形态都通过了显著性检验,两个季度的第一、第二分布形态都是全区一致型和南北反向型;春季近5年时间系数多为正值,说明近年来全区春季表现为偏旱;1990年以后,夏季第一特征向量时间系数只有3年为正值,其余均为负值,说明近16年广西夏季降水较多,以偏涝为主,年代际变化也较明显.     

近50年长江中下游春季和梅雨期降水变化特征

利用1961—2009年长江中下游地区52个气象站逐日降水资料,研究了该地区春季降水与梅雨期降水的连续变化特征,划分了连续旱、连续涝、先旱后涝和先涝后旱4类连续性事件,并探讨其成因。结果表明:长江中下游地区春季降水量年际和年代际变化较为显著,其中连续旱和连续涝事件发生较多。前冬Ni?o3区的海温与春季和梅雨期降水量相关性超过0.05显著性水平,前冬青藏高原积雪深度与6月西太平洋季风指数与梅雨期降水量相关性均达到0.05显著性水平。当春季水汽丰富,同时春季与6月副热带高压中心位置持续偏西可能导致春季和梅雨期降水持续偏多;春季水汽丰富,但春季至6月副热带高压中心位置由偏西向偏东转变,可能造成先涝后旱;春季水汽偏少,且春季与6月副热带高压中心位置持续异常偏东,易造成持续干旱。2011年水汽突变可能是导致旱涝急转的直接原因,前冬的La Ni?a事件不利于春季降水而6月副热带高压位置异常西伸, 则容易引发旱涝急转。     

贵州夏季降水异常的区域特征

利用贵州省19个测站1951～2000年夏季逐月降水资料,计算了降水量的月平均（区域平均）标准化距平。并进行模糊聚类分析、经验正交函数分解（EOF）和小波分析,研究了贵州夏季降水异常的区域特征。结果表明,贵州夏季降水在近50 a中存在5个明显的气候段：20世纪50年代前期为多雨期;50年代中期到60年代前期为少雨期;60年代中后期为多雨期;70～80年代为少雨期;90年代以后进入多雨期;降水呈增多的趋势。全省一致性是贵州夏季降水的最主要特征,同时还存在区域差异。贵州夏季降水异常有5种空间分布型,即：全省旱（涝）型、东旱（涝）西涝（旱）型、南旱（涝）北涝（旱）型、中东旱（涝）西南涝（旱）型和西南旱（涝）其余涝（旱）型。各型降水具有多时间尺度振荡的特点,存在10～12 a、4～5 a、2～3 a的周期。     

珠江流域4～9月降水空间分布特征和类型

采用珠江流域1954～2003年51站的月降水资料,利用主分量分析方法,研究珠江流域4～9月降水的空间分布特征。分析结果表明：珠江流域4～9月平均降水量在600～1900mm之间,最大中心在广东阳江附近,自东南向西北逐渐减小;其标准差分布基本上是从东向西减小,最大变率中心仍然在广东阳江附近。珠江流域4～9月降水存在5种主要分布型态：全区涝（旱）型、南涝（旱）北旱（涝）型、东涝（旱）西旱（涝）型、东西涝（旱）中部旱（涝）型、南和北旱（涝）中部涝（旱）。珠江流域出现全区性涝（旱）和南旱（涝）北涝（旱）的分布型态较多,占总年数的64％。珠江流域夏半年降水场在1983～1992年呈较显著的全区偏旱分布;在1967～1971年前后东涝西旱的分布较显著;在1979年前后中部涝东西旱分布较明显。在1985～1986年前后有南北部涝中部旱分布特征。南涝北旱和南旱北涝分布交错出现,没有明显的集中分布期。     

NCEP/NCAR再分析资料中南北半球大气质量交换的特征研究

采用珠江流域1954～2003年51站的月降水资料,利用主分量分析方法,研究珠江流域4～9月降水的空间分布特征.分析结果表明:珠江流域4～9月平均降水量在600～1 900 mm之间,最大中心在广东阳江附近,自东南向西北逐渐减小;其标准差分布基本上是从东向西减小,最大变率中心仍然在广东阳江附近.珠江流域4～9月降水存在5种主要分布型态:全区涝(旱)型、南涝(旱)北旱(涝)型、东涝(旱)西旱(涝)型、东西涝(旱)中部旱(涝)型、南和北旱(涝)中部涝(旱).珠江流域出现全区性涝(旱)和南旱(涝)北涝(旱)的分布型态较多,占总年数的64%.珠江流域夏半年降水场在1983～1992年呈较显著的全区偏旱分布;在1967～1971年前后东涝西旱的分布较显著;在1979年前后中部涝东西旱分布较明显.在1985～1986年前后有南北部涝中部旱分布特征.南涝北旱和南旱北涝分布交错出现,没有明显的集中分布期.     

长江中下游沿江地区夏季旱涝分型及预测

对1961-2000年长江中下游沿江地区8个站夏季（6-8月）累积降水距平进行EOF分析，根据有三个特和下向量将长江中下游沿江地区旱涝趋势异常分成4种主要空间型：旱型、涝型、东旱西涝型、东涝西旱型。并在此基础上，分析了它们与500hPa高度场异常的同时，时滞关系，得到一些对长江中下游沿江地区汛期旱涝异常预测有意义的结果。     

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.     

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.     

Information for Authors

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     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.