基于GPS资料分析西藏中东部夏季可降水量日变化特征

利用中日JICA项目2010-2013年地基GPS探测的逐时大气可降水量PWV资料以及西藏自治区气象局信息中心提供的2011年自动气象站逐时降水资料,分析了西藏中东部地区4个测站(丁青、那曲、隆子和林芝)夏季PWV日变化特征及有、无降水日的差别,并初步讨论了其与累积降水的关系。结果表明:(1)西藏中东部各站PWV存在明显的日变化特征,通常于02:00(世界时,下同)左右达到最低值,此后迅速上升,高值普遍从08:00持续到19:00。各站PWV日变化幅度普遍随测站的海拔升高而减小;(2)各站PWV日平均值随海拔降低而增加,在有降水日PWV要比无降水日高出10.2%~31.3%,且有、无降水日PWV差值随海拔升高而增大;(3)谐波分析表明,各站PWV日变化主要以日循环为主,同时各站PWV日变化也表现出不同程度的半日循环,这种双峰型变化特征在海拔较高的测站较为明显。与有降水日相比,无降水日PWV半日循环信号普遍有所增强;(4)各站累积降水量和累积降水频次的日变化具有较明显的日循环特征,降水主要出现在当地傍晚以后;(5)各站PWV开始上升的时间普遍超前于降水,并在降水结束后出现明显回落,降水量通常在PWV还处于较高值时达到最大。     

2017-2019年南疆西部和昆仑山北坡大气可降水量变化特征

基于2017-2019年南疆地基GPS大气可降水量（下文简称“GPS-PWV”）、常规探空水汽廓线计算的大气可降水量（下文简称“RS-PWV”）和逐时降水资料，统计分析南疆西部和昆仑山北坡GPS-PWV时空变化特征、夏季不同海拔高度不同降水量级下GPS-PWV变化与实际降水的对应关系。结果表明：（1）南疆西部和昆仑山北坡GPS-PWV与RS-PWV，二者具有符合预期的很高的相关性。（2）不同海拔高度站点GPS-PWV空间分布差异明显，大部分站点GPS-PWV随海拔高度的增加而降低。（3）各站点GPS-PWV逐月变化均呈单峰型，冬季12月或1月最小，夏季7、8月最大；春、夏季各站GPS-PWV距平日变化为单峰型，秋、冬季GPS-PWV距平日变化除秋季乌恰站、若羌站为单峰型外，其它均为三峰或四峰型。（4）各站有、无降水时PWV平均值差异明显，昆仑山北坡差异更大；降水发生前GPS-PWV已开始上升，南疆西部PWV峰值主要出现在降水前0～1 h，昆仑山北坡PWV峰值主要出现在降水前0～3 h和7～9 h。     

地基GPS遥感西藏改则站大气可降水量变化特征及其与夏季降水的关系

利用中日JICA项目2010-2011年期间的地基GPS探测逐时大气可降水量（PWV）资料,分析了西藏西部改则站PWV的季节变化和日变化特征及其与夏季降水的关系。结果表明：（1）该站PWV存在明显的季节变化特征,其高（低）值出现在6-9（12-3）月,呈现出明显的单峰型变化特征,同时表现出春季持续上升和秋季快速下降的特点。（2）谐波分析表明,改则站各季PWV日变化均以日循环为主,只是夏季也表现出一定的半日循环特征。（3）改则站PWV存在明显的日变化特征,低值一般出现在当地时间的凌晨至次日上午,各季谷值普遍出现在当地时间10：00前后;高值通常出现在当地的午后至午夜,但各季最大值出现时间不固定;（4）改则站降水通常都发生在PWV高值期,降水发生前后PWV有明显的逐渐积累与迅速下降的变化特征,PWV达到峰值的时间提前于降水。PWV对累积降水频次的影响要比累积降水量更显著。     

地基遥感西藏改则站大气可降水量变化特征及其与夏季降水的关系

利用中日JICA项目2010—2011年期间的地基GPS探测逐时大气可降水量(PWV)资料,分析了西藏西部改则站PWV的季节变化和日变化特征及其与夏季降水的关系。结果表明:(1)该站PWV存在明显的季节变化特征,其高(低)值出现在6—9(12—3)月,呈现出明显的单峰型变化特征,同时表现出春季持续上升和秋季快速下降的特点。(2)谐波分析表明,改则站各季PWV日变化均以日循环为主,只是夏季也表现出一定的半日循环特征。(3)改则站PWV存在明显的日变化特征,低值一般出现在当地时间的凌晨至次日上午,各季谷值普遍出现在当地时间10∶00前后;高值通常出现在当地的午后至午夜,但各季最大值出现时间不固定;(4)改则站降水通常都发生在PWV高值期,降水发生前后PWV有明显的逐渐积累与迅速下降的变化特征,PWV达到峰值的时间提前于降水。PWV对累积降水频次的影响要比累积降水量更显著。     

近50 a南京夏季降水的气候特征

利用南京6站近50 a(1960—2009年)的夏季逐日降水资料,应用累积距平、趋势系数、小波分析等方法,分析了南京地区夏季降水和旱、涝年的时空特征。结果表明,南京地区夏季降水量、雨日、暴雨日和暴雨日降水强度均有明显的年代际变化特征,其中降水量和暴雨日数的年代际变化基本一致;各站夏季降水量、雨日和暴雨日均呈增加趋势,总降水量的增加趋势主要是大雨及以上量级降水的贡献;夏季降水量存在2～8 a的周期变化;南京地区旱、涝年的夏季降水量与长江中下游地区有较好的一致性,与华南地区呈相反关系。     

近48年西南地区降水量和雨日的气候变化特征

利用1960-2007年西南地区97个观测站点的日降水量资料,研究分析了西南地区年、季节的降水量和雨日的气候变化特征。结果表明,西南地区降水量分布整体呈"东多西少"的分布形态,高值区位于四川盆地的雅安地区和滇西南区,且这两个地区也是四季中降水最多的。年雨日、春季雨日和秋季雨日呈东北—西南向的"偏少—偏多—偏少"型分布,夏季雨日呈"西多东少"型分布,冬季与夏季分布相反。近48年西南地区年降水量总体上呈弱的减少趋势,春、冬季的降水量呈增多趋势,而夏、秋季的降水量呈减少趋势,且夏季降水量存在着明显的准16年周期变化。雨日的季节变化趋势与降水量类似,夏季雨日呈明显的准17年周期变化。另外,中雨日和小雨日呈明显减少趋势,但暴雨日、大雨日均呈增加趋势,极端降水天气日益突出。     

川北绵阳地区降水量的时空分布特征及变化趋势

选用四川省绵阳地区8个台站1959~2005年日降水资料,采用经验正交函数分解法和连续功率谱分析等方法分析了绵阳地区年降水量的时空分布特征及变化趋势,结果表明,绵阳地区年降水量的空间分布不均匀,局地差异大,主要表现为3种分布型:①区域一致型;②东南—西北型;③中部型。绵阳地区的年降水量呈整体下降趋势,但降水剧烈程度加大,同时东南—西北分布型在加剧;功率谱分析发现,绵阳年降水量的变化具有2.9年和6.7年的显著变化周期;绵阳地区各站的年降水和不同等级降水的降水量和降水日数大致呈不同程度的下降趋势和减少趋势,但不同站点暴雨以上量级的降水量和降水日数变化特征又有所不同;绵阳地区区域平均年降水量呈减少趋势主要是由于雨季降水量和降水日数均出现减少趋势造成的。      

新疆天山山区夏季极端降水的日变化特征

基于天山山区11个国家气象站2012—2018年夏季（6—8月）逐小时降水资料，使用百分位法计算极端降水阈值，分析极端降水特征量（包括极端降水量、极端降水频次、极端降水强度、极端降水贡献和极端降水量最大值）的日变化特征，揭示极端降水与海拔高度的关系。结果表明：87°E以东地区，极端降水量最大值出现的时间大致都存在自西向东顺时针变化的特点。极端降水主要以短持续性为主，极端降水贡献和极端降水量最大值的谷值都出现在白天。极端降水与海拔密切相关，总极端降水频次更多发生在高海拔地区，在海拔2 000 m左右存在一个极端降水最大值带。     

峨眉山及其周边地区降水气候特征研究

基于1959-2016年峨眉山、峨眉市、乐山市及夹江县气象站逐日降水数据和1964-2016年6-9月逐时降水数据,应用统计诊断分析方法,研究了峨眉山及其周边地区降水量、雨日和降水频次的多时间尺度变化特征。结果表明,峨眉山及其周边地区年代降水变化趋势基本一致,但随海拔具有一定差异性,高海拔峨眉山趋势更明显。峨眉山与其周边地区年降水量和年雨日均在20世纪90年代后显著减少,且峨眉山年雨日比其周边地区减少更快。汛期峨眉山及其周边地区降水量、雨日变化均强于其年代和年降水量、雨日变化,较其他时段更突出;高海拔峨眉山冬季、秋季和夏季降水量减少趋势显著,而周边地区夏季和秋季降水量减少趋势明显;峨眉山及其周边地区四季雨日都呈减少趋势,但峨眉山减少程度大于其周边地区。峨眉山及其周边地区月降水量和雨日都呈减少趋势,但峨眉山更明显。峨眉山降水量日变化呈单峰单谷结构,而峨眉市则在清晨出现次峰值,两地夜雨特征突出,夜间降水量远大于白天,且两地降水量峰值出现时间都存在提前的变化特征;峨眉山小时降水频次最大值出现时间存在提前的变化特征,但峨眉市相反,具有延后的变化特征。在全球气候变暖下,峨眉山及其周边地区气候响应主要为降水减少,高海拔地区降水减少的趋势大于低海拔地区。峨眉山及其周边地区这种区域气候响应的一致性与差异性,可能与区域温度响应与水汽状况差异有关。     

四川盆地边缘山地强降水与海拔的关系

利用四川盆地1666个站点2011—2015年4—10月的逐小时降水资料及高精度格点海拔高度资料,对降水特征与海拔高度的变化关系进行详细分析,研究发现:(1)汛期总降水量、总雨日、小雨日、中雨日随海拔高度升高而增加,但降水量与雨日随海拔的增长方式并不相同,降水量显著增长区主要集中在200～1200 m,当海拔超过1200 m时降水量迅速减少;大雨日及暴雨日在海拔超过1200 m后也迅速减少。(2)盆地西北部、西南部沿山一带的暴雨日主要由强小时雨强贡献,而盆地东北部的暴雨日主要受持续性降水影响。(3)四川盆地复杂地形对降水的日变化有较为显著的影响,小时雨量及短时强降水频次峰值出现时间均随着海拔高度升高而提前,而短时强降水首次出现时间则随海拔高度升高而推迟。     

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.