自动站与人工观测气温的对比分析

根据2000年自动站和人工观测气温资料, 对两种气温序列进行了对比分析, 以了解仪器改变对观测数据产生的影响以及为换型后数据的连续使用提供科学依据。结果表明:除个别地区以外, 自动站与人工观测气温偏差都在允许范围之内或略超出允许范围, 季节性和地域性差异不大; 由于自动站温度传感器灵敏度高, 所以在日出日落、日气温最高和最低时与人工观测偏差较大; 自动站观测气温与历史序列无显著性差异。自动站可以用于业务, 但需进行一定时间的平行观测, 尤其在西北及高山站更为必要。     

Milos500型自动站与人工观测气温记录的对比分析

通过对青海省2002年Milos500型自动站与人工观测站两种定时气温记录和最高、最低气温记录的对比分析，结果表明：自动站与人工站气温记录值的差异，主要与仪器的观测原理不同和观测时间不一致有关；气温变化较剧烈时两之间的差异较大；气温差异存在季节性变化，但无明显的地域性；高原地区气温变化剧烈，两偏差较大，自动站与人工观测站进行一定时间的平行观测十分重要。     

自动站与人工站常规气象要素的对比分析

对比分析陕西省6个基准站2003—2005年自动站和人工观测的气压、气温和相对湿度,并对自动站观测的资料进行显著性检验。结果表明:自动站的气压和相对湿度观测值普遍低于人工观测值,偏差大都超出允许范围;气温月际变化不一,偏差基本在允许范围内,多数自动站观测值高于人工观测值,且夏季比冬季明显;自动站观测的气压、气温、相对湿度的月平均值与历史序列中的气压、气温、相对湿度无显著性差异。     

海南省自动站气温观测资料评估及气候订正研究

通过海南省16个气象台站2004～2005年自动站与人工并行观测气温资料的对比分析,根据相关标准对海南省自动站气温资料进行了评估.分析表明:海南省自动站与人工观测气温的偏差有日变化和季节差异.产生偏差原因有观测仪器的系统性偏差、观测仪器对气温变化响应的灵敏度、观测时间的差异、太阳辐射对观测仪器的影响等.建立了海口自动站与人工观测气温值之间的经验换算关系,为气候资料的前后连续性使用提供了订正的思路和方法.     

自动站与人工观测常规气象要素差异对比分析

利用青海省海西州所属气象站人工与自动平行观测资料,统计分析气温、气压、相对湿度、风要素观测差异,探讨差异产生的原因。结果表明:自动站与人工观测常规气象要素均存在一定的差异,自动站气温、风普遍高于人工站观测值,气压、相对湿度自动站观测大多低于人工观测值,没有一个站各要素偏差都在评估允许范围内的;观测仪器结构与观测原理的不同、观测时空差异、观测方式的不同是造成偏差的主要原因。     

青海省自动站与人工观测气温的对比分析

根据青海省4个代表站2006-2008年人工和自动站观测的气温资料,对气温资料进行了对比分析并探讨了两者差值形成的原因,以了解仪器改变对观测数据产生的影响以及为换型后数据的连续使用提供科学依据。结果表明：两种观测方式观测的气温虽然有一定的差异,但自动站与人工观测气温偏差都在允许范围之内或略超出允许范围。由于自动站温度传感器灵敏度较高,日出后到日落前气温变化剧烈时偏差较大。     

内蒙古自动站与人工观测数据差异对比分析

利用2006年内蒙古自治区共36个自动站和人工站平行观测资料,对观测得到的气象要素进行了统计和评估。通过分析气温、气压、相对湿度、风等要素的对比差值及其标准差、对比差值的频次分布和空间分布等,探讨自动站与人工观测数据差异的可能原因。结果表明：内蒙古自动观测与人工观测各气象要素均存在一定的差异,对所有台站平均而言,其差异均在自动站差值允许范围之内。产生差异的原因：观测仪器结构与观测原理差异、观测时空差异、观测方式差异等,在将人工观测数据与自动观测数据连续使用时,需要根据当地情况进行适当订正,以确保资料的连续性。     

自动观测与人工观测差异的初步分析

利用2001—2005年我国700个地面自动气象站与人工平行观测期间的数据, 对自动与人工观测的气温、气压、相对湿度、地表温度、风速风向、降水量进行了差异分析, 统计了两种观测之间的对比差值、百分误差和风向相符率。 对各要素观测差异在全国的分布特点进行了分析, 并检验了气温自动观测对气温资料连续性的可能影响。 结果表明:自动观测与人工观测各气象要素均存在一定的差异, 但大部分地区各要素的差异都在自动站误差允许范围之内; 造成差异的原因是多方面的, 包括仪器本身存在缺陷及观测方法不一致等。各要素自动观测与人工观测差异在全国的分布特点各不相同, 同一要素在不同的气候背景条件下差异大小不一致; 如果要将人工观测数据与自动观测数据连续使用, 还要检验自动观测与人工观测序列是否有显著性差异, 并进行均一性订正。 自动站的使用对年气温序列有一定影响, 总体差异不显著, 但当自动观测与人工观测气温合并使用时, 应进行均一性检验。     

自动观测替代人工观测对气象要素资料均一性的影响分析及订正

利用t检验法对青海省海西所属7个站气温、气压、相对湿度、平均风速、0~320cm地温年平均值序列进行显著性检验;在人工与自动观测资料对比差值分析的基础上,建立人工与自动观测要素间的回归方程,对年序列差异显著的要素进行回归订正和效果对比分析。结果表明,自动替换人工观测对海西7个站各气象要素年平均值序列均一性产生了不同程度的影响,多个站多个要素不连续;统计人工与自动观测要素资料月平均对比差值,用一元线性回归法进行订正,订正后的序列基本消除了自动观测替换人工观测的差异,实现了观测资料的均一性和延续性。      

自动站与人工站气温观测资料分析

通过对河南省65个自动站在2年平行观测期间人工站与自动站气温（平均、最高、最低）观测资料的差值平均值、差值标准差进行综合分析,得出以下结论：自动站观测值比人工站观测值整体偏低,但差值集中在-0．4～0．4之间。所以自动观测代替人工观测后,对河南省气温长期观测资料的序列没有太大的影响。排除引起数据变化异常的主、客观原因后,自动站与人工站气温观测资料一致性良好。     

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.     

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.     

IMPACT OF ATMOSPHERIC LOW-FREQUENCY OSCILLATION ON THE IMMIGRATION OF NILAPARVATA LUGENS(STL) IN HUNAN AND JIANGXI PROVINCES

Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration.     

A COMPARATIVE ANALYSIS OF ATMOSPHERIC AND OCEANIC CONDITIONS BEFORE THE OCCURRENCE OF TWO TYPES OF EL NIO EVENTS

The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o.     

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