武汉市电力负荷特征及其与气象因子的关系

利用武汉市2013—2018年逐15 min精细化电力负荷数据及武汉市日降水、气温等气象资料,统计分析电力负荷特征指标,探寻电力负荷的构成、变化规律及其与气象因子的关系。研究结果表明:(1)近年来武汉市电力负荷和日负荷峰谷差屡破新高,夏季高温持续时间和强度大小对空调负荷影响最为显著。电力负荷随季节变化呈现出明显的“双峰双谷”特征。(2)夏季电力负荷远高于其它三季,冬季次之。四季日变化特征总体呈现“昼高夜低”的分布。(3)工作日和双休日负荷明显高于节假日,工作日负荷略高于双休日,其中工作日的早高峰负荷最大,而双休日和节假日的晚高峰负荷最大。(4)气象因子对全社会用电量影响尤为重要。夏季气象敏感负荷与日平均气温的关系最密切,当平均气温高于初始敏感值和强敏感值时,电力负荷随气温上升增幅更加明显。(5)无论是否出现降水,夏季气象敏感负荷与日平均气温的关系都很密切。无降水天气,负荷与日平均气温相关性最高;有降水发生时,气象敏感负荷与日平均气温的相关性呈下降趋势,总体反映出降水影响气温、气温影响电力负荷的物理过程和机制。     

南京禄口机场低能见度天气统计分析及判断模型

基于2014—2019年基于南京禄口机场能见度观测资料,统计分析了机场低能见度天气,发现低能见度天气大多发生在11月至次年1月04—07时(北京时)。通过分析雨强—能见度数据发现降水强度和能见度呈幂函数关系,建立了降水时段基于降水强度的能见度拟合模型。通过K-means聚类中心分析,发现无降水时能见度和风速以及温度的关系为正相关,和相对湿度以及修正海压的关系为负相关。最后使用随机森林算法建立低能见度天气等级判断模型,对比发现随机森林在准确度和计算效率方面较其他模型均有一定优势。     

民航广汉机场气象能见度的周期性变化特征的初步分析

基于民航广汉机场1986~1995年每日逐时气象能见度的观测资料,利用相关性分析,功率谱分析、带通滤波,以及小波分析等方法,分析和研究了广汉机场气象能见度的周期性变化特征。研究结果表明,机场能见度的变化与机场相对湿度和低云量呈显著负相关,与机场地面温度和地面风速呈正相关特征。广汉机场气象能见度的变化明显具有10~20d的准双周振荡特征和30~50d准周期性季节内振荡特征。      

桂林城区大气能见度与颗粒物浓度和气象因子关系研究

利用2015年1月至2017年6月桂林国家基本气象站能见度、相对湿度、气温、气压、降水等气象要素和PM₁₀、PM_2.5、PM_1.0颗粒物质量浓度资料,分析桂林城区大气能见度与颗粒物浓度和气象因子之间关系。结果表明：桂林城区大气能见度和PM₁₀、PM_2.5、PM_1.0呈对数关系,相关系数分别为-0.341、-0.461、-0.509,颗粒物对大气能见度影响在相对湿度为60%—70%时最为显著。在各气象因子中,大气能见度与风速的相关性最好,其次为相对湿度,与风速呈二次函数关系,与相对湿度呈幂指数关系,与温度相关性较小,与气压在秋冬季节呈正相关,相关系数冬季可达0.301,但在春、夏季节相关性不显著;利用颗粒物浓度和气象要素建立8种大气能见度非线性统计回归模型,比较后发现利用PM_1.0、风速、相对湿度、气温等因子建立的不同季节大气能见度拟合公式在实际检验中效果最优,能较好地模拟桂林地区大气能见度的变化。     

基于能见度及AOD数据的北京市PM2.5浓度的反演

选择北京市为研究地区,对2014～2017年AERONET（Aerosol Robotic Network）提供的CE-318太阳光度计440 nm波段反演的气溶胶光学厚度（AOD）进行风速订正,对订正后 AOD 日均数据与同期地面监测站PM2.5日均浓度数据做季节相关性分析并建立回归模型。又引入能见度因子并利用广义差分法构建2015～2017年北京市AOD与PM2.5浓度、能见度的三元回归模型,最后将2014年数据分为污染日和非污染日分别进行模型检验。结果表明:AOD与PM2.5浓度存在显著的线性正相关性,且存在季节性差异,夏季相关性最强、秋季次之、春季和冬季最低。引入能见度因子并消除自相关后,四季的模型相对误差均显著减小,模型拟合优度显著提高。检验结果为四季整体的平均相对误差在21%～31%范围内,与前人的结果相比拟合曲线的准确性得到了明显地提高。且模型对低PM2.5浓度日的模拟效果较好,对于高PM2.5浓度日的模拟效果较差。本研究对构建北京地区PM2.5浓度长期的历史数据具有重要的科学意义。     

南宁市大气能见度变化特征及影响因子分析

对2000至2006年的南宁市能见度资料进行统计分析。分析表明,南宁市近7a能见度年均值在13~17km之间,总体呈下降趋势。一年之中,能见度最小值主要出现在1至3月,最大值出现在6至7月,汛期能见度明显好于非汛期。一日之中,能见度的日变化为:08时<02时<20时<14时。能见度与气象因子的相关分析表明,能见度与温度、风速成正比,与压强、降水、湿度成反比。与污染物的相关分析表明,能见度与PM10浓度的相关性较强,达到-0.58。     

降水对雾中能见度参数化的影响

雾的能见度是雾滴数浓度和含水量的函数,可以利用雾滴数浓度和含水量进行参数化得到能见度拟合值。但是当雾中有降水存在时,降水会影响雾滴数浓度和含水量,进而影响能见度参数化。2009年1月19日至3月5日在湖北恩施雷达站进行了包括雾微物理特征、雨滴谱及雨滴末速度、能见度以及基本气象要素的观测。利用不同的能见度参数化公式得到能见度拟合值,并与实测值进行对比分析,考虑雾中降水影响时的能见度拟合值要比不考虑降水时的能见度偏差大,因此在有降水伴随雾产生时,降水的效应可忽略不计。同时,利用40％的雾滴谱观测数据建立了良好的模型用于拟合当地的能见度,并利用Gultepe公式得到相应的参数,对当地的能见度进行了计算和预报。     

天津港秋冬季低能见度数值释用预报研究

本文利用近5年(2009—2013年)天津港资料,分析了该地区大气能见度的分级特征。采用7年秋、冬季NCEP(2006—2012年)和地面资料,通过相关分析给出了对港口低能见度天气有高影响的高、低空物理量因子;排除沙尘和降水天气,针对不同区间的能见度样本,利用BP神经网络方法分类训练了3个统计模型;并与WRF天气模式产品对接,采用分步筛选法,研发了天津港秋、冬季72 h时效的逐时能见度BP释用预报产品。经过3年业务运行,检验结果表明:对逐时能见度而言,BP释用预报对10 km以下低能见度比WRF模式的预报技巧显著提高,达到10.5%~35.4%;其中对0.5 km大雾的预报技巧总体相当,但当WRF预报有降水时,WRF模式预报结果略优;对0.5~1 km的大雾预报,WRF模式的预报技巧1%,BP释用预报提高到了14%~21%。日最低能见度的检验表明:对小于1 km的大雾过程,BP释用预报的TS评分平均达到75%,比WRF预报技巧提高了24%;对1~10 km的低能见度过程,比WRF的预报技巧平均提高了60%。     

公路交通事故与气象条件关系及其气象预警模型

以西安地区为例, 分析该地区2002年1月—2004年12月连续3年逐日公路交通事故资料1096个样本, 以及该地区、对应的逐日13个气象要素资料, 并将样本数据划分为春夏和秋冬两个半年, 来考虑气象要素在不同时段的不同影响, 建立合理有效的公路气象预警模型。通过2005年3月—2006年4月交通事故发生起数共365个测试样本的检验, 发现这个模型具有较高的预测准确性, 运用该地区气象要素建立公路交通事故的预警模型是可行而有效的。研究表明:西安地区气象要素中包含着影响和可以预测当地公路交通的信息, 按照在logistic方程中的显著性大小和因子负载的大小, 在春夏半年 (4—9月), 影响西安地区公路交通事故相关因素依次为:能见度因子、相对湿度因子和降水因子; 而在秋冬半年 (10月—次年3月), 依次为温度因子、能见度因子、降水因子。     

南宁市大气能见度变化特征及影响因子分析

对2000至2006年的南宁市能见度资料进行统计分析。分析表明,南宁市近7a能见度年均值在13～17km之间,总体呈下降趋势。一年之中,能见度最小值主要出现在1至3月,最大值出现在6至7月,汛期能见度明显好于非汛期。一日之中,能见度的日变化为：08时〈02时〈20时〈14时。能见度与气象因子的相关分析表明,能见度与温度、风速成正比,与压强、降水、湿度成反比。与污染物的相关分析表明,能见度与PM10浓度的相关性较强,达到-0.58。     

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