自动与人工观测气温差异偏大的原因及影响分析——以143个国家基准站为例

利用143个国家基准站2002—2010年自动与人工逐日平行观测资料进行对比分析,评估自动观测与人工观测气温的差异,着重分析两者存在的较大差异及其发生原因,并利用惩罚最大t检验（PMT）方法结合台站元数据中自动观测仪器变化信息,客观评价自动观测对气温序列均一性的影响。结果表明：(1) 51.29%、54.14%、67.18%的自动观测日平均、日最高、日最低气温大于人工观测值,差值在±0.2℃之间的百分率分别为78.8%、63.1%、60.9%,平均对比差值分别为0.05、0.09、0.15℃,标准差为0.14、0.22和0.15℃,各气温要素的差值、绝对差值和标准差随自动观测时间的增长并无明显的增大或减小的趋势,且空间分布各有不同;(2)通过对对比差值、绝对差值、标准差的分类比较、逐步筛选发现,少数台站自动与人工观测值差异较大,对于采集自同一传感器的不同气温要素,平均、最高、最低气温的差值表现也不尽一致。经PMT检验,在平均气温、最高气温和最低气温的绝对差值最大的20个站中分别有35%的台站的月平均气温序列、35%的台站的月平均最高气温序列和25%的台站的月平均最低气温序列由于自动观测仪器变化引起序列的非均一;(3) 分析认为：温度传感器检定更换而导致的仪器示值误差变化会造成自动与人工观测对比差值跳变,而温度传感器或数据采集器等电子元器件的零点漂移会导致自动观测气温严重偏离人工观测值,这两种因素会导致自动与人工观测气温差异偏大,也是自动观测仪器变化导致气温序列产生非均一断点的可能原因。建议加强自动观测数据的监测与质量控制,增加观测仪器检定示值误差订正,并采取硬件、软件补偿等方法,实现温度零点补偿,尽可能地减小或消除仪器误差,提高自动观测资料的准确性。     

不同时间分辨率对气象要素月平均值统计的影响

通过我国12个国家基准气候站建站至2000年的气压、气温、相对湿度、风速每日4次与24次定时观测资料月平均值的差值、差值平均值、标准差的对比分析,研究不同时间分辨率统计的资料序列的均一性;在此基础上,对全国所有基准站建站至2000年气温历年月平均值进行统计,绘制了全国基准站建站至2000年气温4次与24次定时累年月平均值差值的平均值分布图,并做了初步分析.结果表明,采用两种不同时间分辨率统计气象要素月平均值会出现统计误差,气压、相对湿度、风速4次与24次定时观测资料月平均值偏差在观测精度之内,气温的差值超过了观测精度.我国绝大部分地区的气温4次定时观测资料要比24次观测资料统计的月平均值偏小0.1～0.3 ℃.在气候分析和气候变化研究中,必须考虑因不同时间分辨率统计气温月平均值引起的统计误差,排除非气候原因造成的影响.     

甘肃省新旧气象站址观测资料对比及均一性分析

天气预报及气候预测需要准确、连续的气象观测资料,气候变化研究需要均一化的长序列数据,为了让气象科研业务人员对新旧站址气象观测资料的连续性状况以及站址变化对长时间序列中的影响进行了解,本文对甘肃15个发生迁移的台站的1年对比观测记录进行差值和差值标准差比较分析,研究台站迁移对气象要素的影响;通过SNHT方法对迁移距离最大的张掖站和海拔高差最大的宁县站进行均一化检验,研究台站迁移对长序列数据的影响。结果显示：从差值和差值标准差情况看,新站址气温偏低,风速偏高,相对湿度大部分新站偏大,台站迁移对平均气温和最低气温的影响大于对最高气温的影响,平均气温、最低气温单站差值大的站迁移的距离和高差相对也大;从差值绝对值和标准差与台站迁移距离及海拔高差的相关性看,海拔高差对最高气温和平均风速影响较大,而迁移距离对平均气温、最低气温、相对湿度影响较大;从选择的代表台站序列均一性检验结果看,显示迁移直线距离大或者海拔高差大会对气温序列造成非均一性影响,但是否在某阈值范围会有影响以及对其他要素的影响还需要深入研究。希望科研业务人员在使用气温资料的时候要注意到台站迁移可能带来的影响。     

西安观测站长序列气温资料缺测记录插补和非均一性检验

以西安观测站1971—2013年日平均气温、最高气温和最低气温序列为研究对象,利用标准序列法和多元线性回归法进行插补实验,计算插补值与实测值的平均误差、平均绝对误差、均方根误差和插补值与实测值误差在0.5℃以内的样本比例,对比分析两种插值方法的相对优劣。结果表明：多元线性回归法插补得到的气温序列效果好于标准序列法,并且气候趋势特征与实际观测值序列更具一致性。采用t检验法、惩罚最大T检验（PMTT）、惩罚最大F检验（PMFT）对西安站1951—2020年平均气温序列的均一性进行检验。依据台站历史沿革数据进行的t检验,在6次台站历史沿革变化中,只有2次造成了年平均气温和年平均最高气温序列间断,分别由观测时次增加和仪器换型导致;年平均最低气温有4次出现间断,分别由台站站址迁移、观测时次增加、仪器换型、缺测值插补造成。PMTT和PMFT检测中发现的4次间断点因无元数据支持,认为属于合理间断点,这2种方法均未检测出因缺测值插补引起的间断点,一定程度上说明采用多元线性回归法对缺测值插补得到的西安站1951—2020年气温序列相对合理,气温序列的均一性较好。     

萧山站迁站观测资料对比评估

利用2016年(站址迁移对比期)萧山国家一般气象站新、旧址的气温、降水、相对湿度、风向、风速等气象要素逐日观测值,采用差值标准差、降水量累计相对差值、风向相符率、显著性检验等统计方法,对以上气象要素进行对比分析,结果表明:1)新址的平均气温、最高气温、最低气温的年平均值均低于旧址,差值分别为-0.4℃、-0.7℃、-0.2℃,新、旧址的最高气温差异最大;新、旧址的平均气温、最高气温、最低气温在春、夏季节比较接近,而在秋、冬季节相差较大。2)新址相对湿度大于旧址,差值年平均为3%,新、旧址相对湿度的变化趋势基本一致,其中9—12月新旧址的相对湿度差值较大。3)新址的年降水量比旧址偏多110.3 mm,雨日比旧址偏少22 d,年降水量累计相对差值为7%,4—6月和9—11月期间新旧址的降水量观测数据差异较大。4)新址平均风速、最大风速、极大风速均比旧址偏大,差值年平均分别为2.0 m/s、3.6 m/s、3.5 m/s,新、旧址在春、夏季的风速相差较小,秋、冬季相差大,新、旧址在大风日数和静风出现次数上一致性较差;全年风向相符率为42.5%,两站址风向一致性较差。5)平均气温、降水量和平均相对湿度月(年)平均值与旧址近20 a的观测数据差异不显著,平均风速差异显著。分析认为,测站环境、海拔的不同以及小气候的影响,是造成以上要素差异的主要原因。     

自动气象观测与人工观测气温差异分析

利用陕西省96个气象站2004--2007年自动与人工平行观测的气温资料,分析陕西全省和不同自然区人工与自动观测气温的差异及引起差异的原因。结果表明：自动观测比人工观测的日平均气温平均偏高0．03℃,标准差为0．26℃。78．6％的样本月平均气温对比差值在0．2℃之内,在不同自然区自动与人工观测气温对比差值在0．2。c之间的百分率基本相同。气温对比差值的日、月变化规律明显,自动与人工观测时间不同步对定时值有一定影响。但对气候分析没有影响,自动观测仪器性能不稳定会造成较大的数据偏差。     

新疆阿勒泰气温人工、自动观测差异的研究

分析了新疆阿勒泰气象站2004年1月至2011年12月,CAWS600SE-H型自动与人工气象站平行观测气温资料的差值。结果表明：两者差值较大,有日、季节变化,最低、最高气温系统性误差,人工观测低于自动观测0.05～0.20 ℃;误差具有正态分布特征。气温整点观测,人工比自动观测提前,造成系统性误差,气温急剧升降时误差更大,通过时差订正,绝对误差一般收窄0.1～0.2℃,均方差减少0.142。1和10月,4、24次日平均模式,差值变化幅度≥1℃的频率达15%。平均差值,除7月外, 4次平均值低于24次平均0.1℃,10月低于0.5℃以上。平均模式对日值的影响最大,变化幅度3.7℃;对季的影响较小,变化幅度只有0.4℃。自动观测仪器的系统性偏差、测量元件的精度及对气象要素变化响应的灵敏度、观测时间的差异和人为因素的影响是造成观测误差的原因。     

甘肃临夏人工与自动气象站气温观测差异对比及均一性研究

自动气象站因其监控、观测、采集、存储资料方面的诸多优势,已成为今后我国地面气象观测的发展主流,并将逐步取代人工观测。人工观测和自动站之间不可避免地存在着观测差异,这种差异对历史气象资料的延续性提出了挑战,并将深刻影响大气科学研究和业务应用。因此,对比分析2个观测系统之间的观测差异及均一性是非常必要的。结果表明,临夏气象站2种观测数据序列中,平均气温的平均差异为-0．35℃,差值变幅为0．22～-1．56℃;最高气温的差异变幅为0．01～0．31℃;最低气温的差异大,变幅不稳定,其中1～3月差异变幅为-2．12～-3．05℃,其余月份差异变幅为0．05～-0．57℃。自动站日平均气温和最低气温系统性偏低于人工观测值,最高气温反之。在分析2个数据序列差异的基础上,建立了各季的气温订正方程。订正后2个序列的差值减小,尤其最大偏差显著减小,效果良好。     

近30年甘肃省气温时空变异分析

基于ArcGIS Analyst平台,采用协同克里格(CoKriging)插值方法,对1979—2008年甘肃省旬平均气温进行了空间插值,得到1km×1km各旬的平均气温表面数据。第36旬气温插值结果的平均误差、均方根误差、平均标准差、标准化平均误差和均方根标准差的平均分别为-0.00046,1.998,1.809,0.0035和1.087℃。利用插值计算结果和气象站观测数据,分析了旬、月和年平均气温的时空变异特征。结果表明,空间上东南部地区的气温变异较小,其他地区的变异较大;时间上第23-24旬、第24-26旬、第25-27旬、第33-35旬和第34-36旬的平均气温呈平稳下降趋势,第4-6旬、第5-7旬、第6-8旬、第7-9旬和第8-10旬的平均气温呈平稳上升趋势,7月气温呈不显著下降趋势,3,5和10月的平均气温略呈上升趋势。1979—2008年甘肃省的年平均气温为8.05℃,3年滑动平均最低气温(1983—1985年)为7.13℃,最高气温(2005—2007年)为8.82℃,气温上升趋势较为明显。     

不同方法计算的气温平均值差异分析

利用1961～2002年699个国家基本（基准）站的时值气温观测资料，分析了我国不同方法计算的气温平均值的差异。结果表明:平均气温计算值由于受4次观测、3次观测不同的计算方法的影响，造成4次、3次观测记录平均值产生一定差异。其差异在空间分布中具有明显的特征，西部、北部地区3次平均值偏高；东南部地区3次平均值偏低。中西部地区4次、3次气温平均值的差异具有扩大的趋势，是由于最低气温的升高引起的。因此，在使用气温平均值时，要充分重视平均气温值的计算方法，避免误差。     

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.     

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.     

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.     

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     

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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.     

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.     

INFORMATION FOR AUTHORS

正Aims Scope Advances in Atmospheric Sciences(AAS)is an international journal on the dynamics,physics,and chemistry of the atmosphere and ocean with papers across the full range of the atmospheric sciences,co-published bimonthly by Science Press and Springer.The journal includes Articles,Note and Correspondence,and Letters.Contributions from all over the world are welcome.     

Editorial

As we will soon celebrate the 90th anniversary of the founding of the Chinese Meteorological Society （CMS）,Acta Meteorologica Sinica （AMS）,which was originally named as Bulletin of the Chinese Meteorological Society,has gone through 89 years of development and excitement since her first issue in July 1925.According to archived documents （CMS Editorial Committee,1925）,AMS was founded to report the research findings of Chinese meteorologists,record their recommendations for improving meteorological services,and share their common meteorological interests in order to promote the growth of AMS such that more members could be inspired to conduct atmospheric research and meteorological knowledge would be better disseminated to and benefit the general public.By upholding and carrying forward this purpose,AMS has published many highly valuable scientific papers.Some could be treated as classical articles,which have produced important influences on both domestic and international meteorological communities and the related fields.