2007年汛期淮河流域致洪暴雨的雨情和水情特征分析

利用2007年6月19日～7月23日淮河流域167个测站逐日降水观测资料,对2007年汛期淮河流域致洪暴雨的雨情和水情特征进行分析,并与2003年历史同期进行了比较。结果表明:2007年汛期淮河流域持续性强降水天气集中于6月19日~7月23日,期间共经历了10次暴雨过程, 2007年总降水量和水位都超过2003年同期,2007年淮河流域洪水期间王家坝上游的面雨量大于2003年,下游的面雨量和2003年持平。2007年汛期淮河流域雨情的重要特点是:雨带稳定,前期强降水过程的降雨中心基本上出现在淮河支流分布比较密集的淮北地区和上游地区,致使淮河流域底水明显增加,是后期强降水导致全流域性洪水的主要原因。造成淮河流域降水稳定持续的重要原因是副高稳定、位置偏南,冷空气活动频繁等。       

2011年渭河和汉江上游秋汛期环流特征及暴雨致洪成因

利用气候统计和天气分析方法,结合气象和水文资料,对2011年9月华西秋雨的时空分布特点、大尺度环流形势及相关流域的洪水与秋雨关系进行了分析。结果显示,2011年华西秋雨主雨区位于渭河、汉江上游及渠江流域,雨区集中和强降水时段集中是2011年华西秋雨的主要特点。分析大尺度环流表明,欧亚中高纬度地区位势高度距平场从西北到东南呈现"+-+"的典型波列分布,副热带高压的东西摆动和稳定维持直接影响雨带位置变化,西风槽与高原槽的叠加导致了大范围的强降水。渭河和汉江上游流域水位变化与流域强降水过程有很好的对应关系。与秋汛期历年洪涝年比较,2011年渭河和汉江上游流域秋汛期总降水量低于2003年,但暴雨过程集中、强度大导致该流域出现自1983年以来最大洪水。     

乌鲁木齐河流域两次暴雨洪水浅析

利用乌鲁木齐河流域7个站的降水资料对1994年6月15日和7月15日两次暴雨洪水成因进行了大气形势和天气热力分析，得出在南支槽发展的同时高空大气热力条件配合下在中高山带出现大降水过程，并且造成在特定的流域地理环境下出现近30年一遇的大洪水。     

地面资料在侦测暴雨天气过程中的应用

利用地面常规观测资料和自动站加密温度资料以及卫星云图资料,分析了2005年7月6—7日和7月9—10日发生在江淮流域及其附近的两次暴雨过程的地面要素分布特征,发现强降水带分布在非锋性斜压带和斜压槽附近。然后利用NCEP再分析资料,用第二类热成风螺旋度和非地转湿矢量诊断解释了非锋性斜压带和斜压槽产生强降水的动力机制,结果表明在地面非锋性斜压带和斜压槽处易发生锋生和斜压现象,从而诱发强降水。     

花林流域面雨量监测分析

以花林流域发生的2次洪水过程为例,对雨量计观测记录插值得到的降水分析场(P_s)和雷达联合雨量计估计的降水分析场(P_r)进行了对比,分析了不同来源降水场对流域面雨量计算和流域水文响应的影响。结果表明:雨量计稀疏或分布不均匀,可能会漏测强降水中心,导致不同降水场计算的面雨量存在较大偏差;不同来源降水分析场的差值场(P_r-P_s)能够直观地显示出无雨量计观测的地区是否发生了强降水,有助于判断这些地区的山洪地质灾害气象风险等级;导致一次洪峰的所有强降水风暴的发生位置、演变和移动情况,在很大程度上决定着流域的水文响应,需要重点监测强降水雨团沿流域汇流方向的移动。     

基于精细化降水分布的山洪气象条件分析

提出了天气雷达联合地面雨量计估测降水的局地分级平均校准方法.以该方法得到的精细化降水分布(0.01°×0.01°)为基础,对重庆綦江石角流域(面积707 km2)2008年5月28日、2009年8月5日和2010年6月23日的3次洪峰过程进行了山洪气象条件分析.结合由数字高程模型(Digital Elevation Model,DEM)资料计算的流域河道出口距离分布,提出了流域出口无损径流序列(假设降水全部转换为径流)的预报方法.结果表明:与局地平均校准法相比,局地分级平均校准法对强降水的估计效果更好.无损径流预报对预测山洪发生的可能性具有参考意义.     

2007年夏季江淮强降水过程中10~30d低频变化及其与对流层上层波包活动的联系

利用NCEP/NCAR再分析和全国740站逐日降水资料,运用一点滞后相关等方法,对2007年夏季江淮流域强降水期间低频振荡的波动活动特征及其与降水低频变化的联系进行了分析。结果表明,在2007年夏季降水中,降水低频分量起着重要作用。降水的低频振荡主周期为10~30d,降水距平时间序列与10~30d低频分量具有较好的对应关系。低频扰动在对流层上层和低层都呈现波列状分布,且在降水活跃位相时,低频环流在高、低层具有斜压结构。在对流层上层,低频扰动有缓慢的东移倾向,相速度为每天2~3个经度。西风带中存在多次移动性波列向下游的传播,且在120°E以西以每天14经度的群速度向下游频散能量,表明10~30d低频波动具有明显的下游发展特征。在强降水开始5d前,低频波动与能量可起源于高纬的乌拉尔山附近,沿着西北-东南向的路径向下游传播。下游发展的低频波动为江淮流域带来了能量,为强降水的发生提供了条件。这些结果加深了人们对低频波动在江淮流域强降水过程中所起作用的认识,可为寻找江淮流域强降水过程预报线索提供科学依据。     

渠江流域汛期强降水时空分布特征

本文从分析研究渠江流域汛期强降水时空分布入手,试图揭示该流域21世纪以来洪水频发的原因。经对渠江流域1970~2012年降水资料分析研究得出:(1)渠江流域汛期降水量、暴雨日数、降水变差系数呈“北大南小”的空间分布;“北区(河流汇水区,下同)”近年来汛期降水量增大、暴雨频率增加、降水趋于极端;(2)短时强降水多发生在04~08时,频发区主要位于“北区”,近年来频次呈上升趋势;(3)小时雨强极值“北区”普遍大于“南区”;近43年渠江流域汛期小时雨强极值总体呈增大趋势,“北区”尤为明显。因此,渠江流域汛期发生的强降水趋势性变化,是导致该流域洪水频发的主要原因之一。      

2007年夏季中国大陆85°E以东的异常天气与气候——中国科学院大气物理研究所2007年汛期降水预测的总结

对中国科学院大气物理研究所2007年的夏季(6~8月)降水预测进行检验,结果表明,3月底的预测与实况有一定差异,6月的预测有所改进。简要讨论了2007年夏季的主要降水过程及其成因。2007年夏季华南、长江中下游和淮河流域先后出现梅雨锋强降水,6月中旬和8月中旬出现两次Rossby波列的下游发展效应,引起陕甘宁一次强降水以及加强了圣帕台风引起的强降水。7月上中旬出现高压脊发展后,下游小低槽强烈斜压发展过程引起淮河出现致洪暴雨以及济南暴雨灾害。7月中下旬,由于阻高南侧的3次高空槽切断过程,造成重庆地区以及山西和豫西的暴雨灾害。在东亚季风区,夏季大气季节内振荡很显著,而且对降水的时空分布有重要影响。由于短期气候预测对夏季风季节内变化的预测还是一个难点,这给汛期降水的可预报性带来了限制。     

长江上游中小洪水月分布特征及天气成因

基于1981~2012年宜昌站日均流量、长江上游287个气象站逐日雨量及NCEP再分析资料,选取长江上游中小洪水过程128例,分析其洪水、致洪降雨月分布特征,并研究其天气成因。结果表明:长江上游流域中小洪水多发于7~9月,且过程持续时间6~9月呈逐渐变长趋势,其中过程洪量7月最大,洪峰流量及次洪量最大值出现在8月。6月副热带高压(以下简称副高)及南亚高压偏东偏南,贝加尔湖槽引导冷空气南下,与西南急流在重庆—宜昌、乌江汇合,造成降水各子流域分布不均,中心位置偏东,强降水日数少但强度较大;7月副高及南亚高压西伸北抬,中高纬地区多短波槽活动,西南气流强盛,辐合区范围大,造成降水范围广且分布均匀,强降水日数多;8月副高进一步西伸北抬,中高纬环流平直,辐合中心位于长江上游流域西北部,配合高热高湿的环境场,造成降水分布不均匀且局地性强,中心位于岷沱江,过程面雨量大;9月以后,副高继续西伸,南亚高压南压东移,受深厚东北槽影响,地面冷空气活跃,西南暖湿气流减弱,降水中心位于岷沱江、嘉陵江,强度减弱,过程面雨量小。     

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;