新疆探空8站仪器换型前后资料对比分析

本文选取阿勒泰、阿克苏、和田等8个台站L波段和59-701系统对比观测逐日07时和19时850hPa-100hPa十个位势等压面上的高度、气温、露点温度数据,进行差值、离散程度分析,对数据进行t检验,并给出订正方程。研究发现：（1）温度差值07时阿勒泰、库尔勒、民丰等五站为正,哈密、若羌、阿克苏三站为负,正值表明L波段雷达探测的温度值大于59型的温度值,大部分台站19时的差值比07时稳定。（2）高度差值07时和19时4站为正,250hPa以下差值在0~ -10之间,250hPa以上差值迅速增大,除个别台站外差值最大值均在100hPa处。（3）07、19时露点温度差值除个别等压面外均为负值,且07时的差值大于19时。（4）大部分台站的高度、温度能过信度α=0.05的检验,说明L波段与59-701雷达探空高度和气温观测资料无显著性差异。露点温度均未能通过T检验,通过计算给出订正方程。     

L波段与59—701系统高空对比观测资料特征分析

选择喀什探空观测站10个位势等压面上的高度、气温、露点L波段雷达探空系统与59—701雷达探空系统对比观测资料进行分析,结果表明,两种仪器的露点差异最大,而且随高度增加而增加。对各时段高度、气温、露点观测资料进行“检验也表明,L波段与59—701雷达探空高度和气温观测资料无显著性差异,属于同一气候序列;而部分露点值没有通过检验。另外,气温观测值的离散性相对较大,各位势层高度、气温、露点观测值的离散性19时比07时大,低空比高空大。两种仪器在各等压面上的气温值有一定差异,这种差异在大气对流活跃时尤为突出。     

高空气象探测系统换型记录对比分析

利用青海省西宁市气象站L波段雷达探空系统和701雷达探空系统定时探测资料,应用统计学方法,分别对各标准等压面层的高度、温度、湿度、风进行差值对比分析,同时对500hPa高度、温度及其差值的分布特征进行研究。结果表明:L波段雷达探测系统感应灵敏,滞后误差小,所获资料离散性小,更加稳定可靠;L波段雷达系统高度、温度的测值比701雷达系统的测值偏高,湿度测值却偏低,07时偏高或偏低比19时明显,500hPa及其以下两者测值接近,差值较小,温度差值分布较高度差值分布集中;两种探空仪灵敏度的高低在对流层顶附近表现得更为突出,其差异更加明显;各层之间比较:高度平均绝对差值随着探测高度的升高而增大;温度平均绝对差值随高度的变化不尽相同,在温度突变的对流层顶附近差值幅度较大,同样当湿度变化剧烈时,其差值幅度也相应增大;风的变化随机性较大,总体上风向在对流层底部尤其在摩擦层内偏差相对较大,但随高度变化呈减小趋势,相反,风速平均绝对差值表现出随高度变化逐渐增大的趋势。     

L波段与59 701探空系统观测资料差异评估

利用四川在59-701探空系统向L波段雷达GTS1型电子探空仪系统转变时,就4个高空台站开展了两套系统对比观测的资料进行了差异评估。结果表明:太原厂59型探空仪所测的温度、位势高度比上海厂59型探空仪所测偏高。100 hPa高度以下温度、位势高度观测数据没有明显的跳变,但以上高度换型带来的变化较明显;两套系统所测湿度差异较大,近地面差值最小,差值随高度升高而增大;L波段系统所测湿度基本是低于59-701系统所测湿度。两套系统所测平均风向、平均风速差异较小。直接差异各要素差异的峰值均较大。各要素差值的离散情况随高度的变化各异,总体离散程度最大的是位势高度,其次依次是风向、湿度、露点、风速、温度。两套系统所测要素的差值变化趋势虽然普遍没有太大差异,但湿度、风向和风速的差值变化还是表现出与地理位置、季节和施放时间有关。两套系统在观测所使用设备、原理、精度、订正、观测方法、对比时的放球时间等的不同,都会引起测量值出现差异。     

59型探空仪与L波段探空仪数据对比分析

利用西安泾河站2004、2007年共1460多个时次的高空资料,对100hPa及以下等压面的位势高度、温度、露点温度和相对湿度进行全面统计、对比、分析,结果表明：59型探空仪与L波段探空仪所测位势高度和温度差异较小,但59型探空仪前后时次探测值波动较大,而L波段探空仪探测值波动小,前后时次连续性好;59型探空仪与L波段探空仪所测露点温度和湿度差异较大,59型探空仪湿度变化比较平稳,曲线较均匀,符合大气层结规律,而L波段电子探空仪湿度变化较大,曲线呈锯齿状,不符合大气层结规律,L波段电子探空仪湿度感应元件的质量和性能还须进一步提高。     

杭州L波段和59-701高空探测系统资料对比分析

为比较L波段高空探测系统和59-701高空探测系统的资料异同,采用平均差、均方差比较的方法分析了杭州站平行观测一个月资料的温压湿资料,比较其异同及产生原因,为更好利用高空探测资料、改进L波段高空探测系统提供参考。通过比较发现:L波段高空探测系统比59-701高空探测系统所测的温度、高度资料更稳定、离散率更小,对提高预报准确率有利。两套系统的温度差值在70 hPa层出现明显拐点,其原因有待进一步研究。     

L波段与59-701探空系统相对湿度对比分析

通过统计全国探空系统早期换型时获取的59个高空站L波段雷达-GTS1型电子探空仪系统相对于59-701探空系统在1000 hPa到200 hPa之间各规定等压面相对湿度的差值,分析探空系统换型对于相对湿度一致性的影响。结果表明:GTS1型探空仪测得的相对湿度明显比59型探空仪低,且差值随高度增加而增大,近地层二者相对湿度差值低于5%,200 hPa高度二者差值达到20%以上;冬季两套探空系统相对湿度的差值明显大于夏季,且差值随高度分布情况不尽相同。分析表明:相对湿度差值的变化除了与探空仪施放过程中外界温度变化相关,还与湿度变化趋势和变化幅度密切相关,湿度传感器存在湿滞回线和滞后现象。分析还发现,太原无线电一厂与上海长望气象科技有限公司制造的59型探空仪的性能差异不明显,且GTS1型探空仪与59型探空仪的两种湿度传感器在白天受太阳辐射的残余影响差异也不明显。     

L波段与701 400M探空系统观测资料比较评估

利用四川达州站在701-400M探空系统向L波段雷达GTS1-2型电子探空仪系统转变时的对比观测资料进行了评估分析。结果表明:温度平均差值为-0.28℃,200hPa以下平均差值为-0.05℃,200hPa以上平均差值为-0.52℃,换型带来的温度变化还是明显的;直接差异的80.1%在-1.0~1.0℃间。位势高度平均差值为-7.63gpm,100hPa以下高度平均偏低-1.13gpm,100hPa以上高度平均偏低-19.57gpm,换型带来的位势高度变化还是明显的;直接差异的89.0%在-50~10gpm间。湿度平均差值为-2%,直接差异的87.2%在-20%~10%间。风向平均差值为1.0°,直接差异的80.1%在-10°~10°间。风速平均差值为0.3m/s,直接差异的95.0%在-5~5m/s间。就平均差值来看,温度、位势高度、湿度是L波段系统所测值低于701-400 M系统所测值,而风向、风速则反之。换型造成各要素差异的峰值还是较大。由于两套系统所使用的设备、探空仪的制造、测量精度、施放、接收等方面的不同,都会引起测量值出现差异,但对各要素的影响确有所不同。     

GTS1型数字探空仪和59型探空仪对比观测记录的差异统计分析

利用贵阳高空气象探测站L波段雷达探空系统和701雷达探空系统定时对比探测资料,对各标准等压的高度、温度、露点进行对比分析,分析记录差异特征和原因,并作统计学检验,为高空探测员和气候工作者提供有益参考。     

59型与L波段探空仪温度和位势高度记录对比

利用全国探空系统换型时获取的70个高空台站的对比观测数据,计算了59型探空仪和L波段探空仪温度和位势高度的差异,分析了探空仪换型对于探空数据一致性的影响。结果表明:就全国平均而言,在100 hPa特别是在400 hPa以下高度,两套系统提供的温度和位势高度观测值没有明显的系统差异;但在70 hPa以上高空,59型探空仪测定的规定等压面温度比L波段探空仪低0.1～0.7℃,导致位势高度在20 hPa高度时偏低达30 m左右,换型前后变化明显。系统差异的产生与59型探空仪的生产厂家、施放地区和季节关系较大,进一步分析表明:太原厂生产的探空仪测得的温度在对流层偏高,在平流层偏低,位势高度在对流层偏高,在平流层逐步转为偏低;上海厂生产的探空仪测得的温度全程偏低,引起位势高度也全程偏低,因此两个厂家的59型探空仪相对于L波段的温度和位势高度系统差也有明显不同。用户在使用局部地区高空站59型探空仪的观测数据时需了解该59型探空仪的生产厂家。     

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.