济南市一次大雾天气过程的诊断分析

利用济南地区地面气象观测资料和探空观测资料以及NCEP1°×1°再分析资料，对2007年1月2-4日济南地区大雾形成及持续原因进行了初步分析，发现：稳定的经向大气环流、较弱的地面气压场是大雾形成的主要天气形势，较弱而持续的偏北风、源源不断的水汽补充及明显的逆温层是这次大雾形成并维持的必要条件。在实际气象预报工作中，不仅要注意天气形势、水汽等条件的分析，在冬季更要注重逆温层对大雾形成的分析。     

柳州市一次连续性大雾过程分析

利用常规观测资料,NCEP/NCAR的1°×1°格点的再分析资料对柳州市2012年3月14日-19日的一次连续性大雾过程进行分析,结果表明:槽前较弱的西南气流、地面处于均压场,是大雾形成的一个有利的环流形式;中低层充足的水汽、适宜的风速及较强的逆温层为大雾维持提供了有利条件.     

雾的特征分析、预报方法及预报模型建立

本文利用1980~2010年巴中地区历史观测资料,研究出巴中大雾年际变化及月变化特征,综合利用地面资料以及NECP 1°×1°再分析资料,对发生在巴中地区的大雾典型个例进行诊断分析,探讨巴中地区大雾天气的成因,根据巴中地区自身的地理特点,通过分析比较筛选出对预报有意义的气象要素,建立一套适用于本地区的预报方法,利用VB软件开发预报雾的应用平台,经检验表明该模式能很好的预报出我市大雾天气,有很好的参考价值。      

一次大雾天气过程的数值模拟研究

利用非静力平衡中尺度模式WRFV3.2、NCEP 1°×1°再分析资料和常规观测资料,对2002年12月12-13日西安地区一次持续大雾天气进行阶段性数值模拟研究.结果表明:利用WRFV3.2模式能较好地模拟出雾的范围、强度和生消过程,但模拟白天雾的强度较弱.这次大雾是平流辐射雾过程,其生成的主要因素是:在夜间辐射降温...     

喀什市沙尘天气的变化趋势及其成因

1 资料和方法 本文选用1971-2010年喀什国家基准气候站(39°28′N,75°59′E,海拔高度为1289.4 m)的沙尘暴、扬沙、浮尘日数以及大风、土壤表面冻结终日、年降水量等地面观测资料,形成1-12月、春季、夏季、秋季、冬季、全年等气候序列(季节划分:冬季为12月—次年2月,春季为3-5月,夏季为6-8月,秋季为9-11月). 采用线性变化趋势方法,分析了喀什市沙尘与大风天气时空变化特征,得到喀什市沙尘与大风天气出现时间和季节分布特点和年代际变化、年际变化、季节、月变化特征,为今后的防灾、减灾工作提供参考依据.     

河北平原一次持续大雾天气分析

利用气象观测资料和NCEP 1°×1°资料,从天气背景、温湿特征、层结条件、动力热力学特征等方面分析了2007年11月7～13日河北平原1次持续大雾的成因.结果表明:这次大雾是在较为稳定的大气环流背景下产生的,中高层以纬向环流为主,冷空气以扩散形势影响华北地区;地面夜间风速在0～2 m/s,充足的水汽及地面辐射冷却作用有利于大雾的形成和维持;大气层结是对流稳定的,同时近地面层为逆温结构;近地面层的弱辐合及持续微弱的暖平流十分有利于逆温层的维持,对于大雾长时间维持具有重要作用.大雾多发生在地面辐合线偏向冷空气一侧.本次大雾性质复杂,持续大雾由平流辐射雾-辐射雾-平流雾3个阶段构成,不同阶段大雾逆温强度及湿层厚度有所不同.     

近10 a黔北地区雾的时空分布及能见度与AQI的关系浅析

选取2006—2015年近10 a遵义市14个国家气象站观测资料,分析统计了大雾天气的时空分布,雾日的季节和月频率分布以及区域性大雾年际变化;并通过2015—2017年遵义市市区空气质量指数资料和能见度等地面气象资料,浅析其时间变化特征。结果表明:遵义大雾区主要有西部河谷大雾区、中部偏南大雾区、东部大雾区、北部雾区等4个。遵义市12月—次年1月出现的雾日最多,6—8月出现最少。近10 a区域性大雾天气次数随着年代的增加,总体呈现逐年减少的趋势。遵义秋冬季节空气质量状况不佳,空气中污染颗粒物较多,此时较高的相对湿度有助于形成能见度较差的天气。     

冀中南连续12天大雾天气的形成及维持机制

利用NCEP 1°×1°再分析资料、常规观测资料和加密观测资料,对2007年12月17-28日冀中南地区连续性大雾过程的天气背景和雾长时间维持的原因及热力、动力结构特征进行了分析。结果表明,大雾期间我国中高纬地区冷空气活动偏弱,500hPa受稳定的暖性宽广高压脊控制,为维持数日不散的大雾天气提供了有利的环流背景;850hPa及以下多以偏东风和偏南风为主,偏东风不仅使雾区近地层温度降低,而且还将海域水汽送至雾区;同时偏南风也为雾区源源不断地输送水汽,特别是东北风的维持有利于强浓雾的形成,这是大雾持久不消散的主要原因;低层弱辐合、正涡度区、弱水汽辐合和900hPa以上的暖脊有利于雾的稳定维持和发展;由于强冷空气的到来导致大雾消散,破坏了稳定的逆温层结。     

2020年12月一次北部湾海雾过程的生消特征分析

2020年12月26-28日,北部湾出现了持续性大雾,其中炮台角站连续35h出现大雾.利用北部湾沿岸海岛站、浮标站等观测资料和ERA5再分析资料,对此次典型海雾过程的生消特征进行分析.结果表明,此次海雾过程主要受人海高压后部偏东暖湿气流影响.海雾期间,北部湾上空有逆温层,大气层结稳定,湿层深厚且维持时间长,近地层有0～...     

一次持续性大雾边界层结构特征及诊断分析

2010年11月30日至12月2日,冀中南部及天津地区出现了一次大范围的大雾天气,持续时间长达3 d,其中石家庄浓雾持续时间长达34 h,强浓雾持续时间7 h。利用加密自动站、天津市250 m气象铁塔梯度观测资料,结合常规气象资料和NCEP/NCAR再分析资料,对连续性大雾边界层结构特征以及大雾的形成、发展维持和消散进行了诊断分析。研究得到:大雾形成前期地面持续东风,有利水汽的聚积;当地面风向转为偏北风时促进水汽凝结,致使大雾形成,大雾形成后再次转为长时间偏东风有利大雾的维持和加强;850 hPa以下西南暖湿气流和近地面层逆温的长时间维持,是平流大雾持续的主要原因;低层3支水汽的输送及850 hPa的西南急流重建直接导致了强浓雾形成。大雾维持加强期间,边界层风速为1~2 m·s~(-1),尤其是强浓雾期间,风速仅为1 m·s~(-1);当边界层4 m·s~(-1)以上西北风速从250 m逐渐下传至地面时,逆温层破坏,大雾天气结束。     

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.