2016年2月大气环流和天气分析

2016年2月大气环流的主要特征是北半球极涡呈偶极型分布,中高纬环流经向度大;太平洋副热带高压接近常年同期或偏强,南支槽较常年同期偏弱,不利于水汽向我国输送。2月全国平均降水量12.3 mm,较常年同期（17.4 mm）偏少29.3%,全国平均气温-1.6℃,接近常年同期（-1.7℃）。月内,我国中东部大部地区出现一次寒潮天气过程;西北地区出现今年首次沙尘天气过程。     

2023年12月大气环流和天气分析

2023年12月大气环流的主要特征是：北半球极涡呈多极型分布,欧亚中高纬环流经向度大,东亚大槽偏强,西太平洋副热带高压异常强盛。12月,全国平均降水量为12.2mm,较常年同期（11.9mm）偏多2.5%;全国平均气温为-2.6℃,比常年同期（-3.0℃）偏高0.4℃。月内共出现6次冷空气过程、1次沙尘天气过程和1次大范围持续性雾 霾天气过程。其中13—16日,我国大部地区遭遇的强寒潮过程具有影响范围广、降温幅度大和低温极端性显著等特点。     

2016年1月大气环流和天气分析

2016年1月大气环流主要特征为：北半球共有三个极涡中心,强度较常年同期偏强,欧亚中高纬环流经向度大,东亚大槽和南支槽均偏强。1月,全国平均降水量25.7 mm,较常年同期偏多94.7%,广东、广西和湖南三省(区)平均降水量偏多3.7倍,为1951年以来同期第一多。1月,全国平均气温-5.3℃,较常年同期（-5.0℃）偏低0.3℃,冷空气和降水活动频繁,共有5次降水过程和4次寒潮过程,其中,1月21—25日,我国大部地区遭受强寒潮天气。此次过程降温幅度大,影响范围广,多地最低气温跌破历史极值。1月28—29日,南方出现历史同期罕见的强暴雨天气过程。     

2014年2月大气环流和天气分析

2014年2月大气环流的主要特征是极涡偏强且呈偶极型分布,中高纬环流呈4波型,西太平洋副热带高压偏弱,南支槽位置偏西。2月全国平均气温为-2.3℃,较常年同期偏低0.6℃;全国平均降水量17.5 mm,与常年同期（17.4 mm）持平。月内我国有一次全国性寒潮天气过程;北方有明显雨（雪）天气,冬麦区旱情缓解;南方雨雪过程较多且范围较大,多地出现阶段性低温雨雪天气和冻害;中东部出现3次大范围的雾或霾天气过程。     

2014年1月大气环流和天气分析

2014年1月大气环流主要特征如下：北半球极涡呈偶极型分布,位置较常年同期明显偏南;欧亚中高纬环流经向度较小;南支槽平均位置位于70°E附近,位置较常年同期明显偏西;同时,西太平洋副热带高压较常年同期略偏弱。1月,全国平均降水量为6.2 mm,较常年同期（13.2 mm）偏少53.0%。全国平均气温为-3.4℃,较常年同期（-5.0℃）偏高1.6℃。月内,我国出现1次主要冷空气过程和4次主要降水过程。北方冬麦区降水偏少,气象干旱持续;中东部地区出现大范围雾或霾天气;南方地区出现低温雨雪天气     

2020年2月大气环流和天气分析

2020年2月大气环流的主要特征是北半球极涡呈偶极型分布且较常年同期明显偏强,欧亚地区中高纬环流呈三波型,环流呈纬向型,经向度较小。西太平洋副热带高压较常年偏强;下旬南支槽趋于活跃。2月,我国冷空气过程较常年偏少,出现今年首个全国型寒潮过程;全国平均气温为-0.1℃,较常年同期偏高1.6℃;全国平均降水量21.1 mm,较常年同期偏多18%。此外,前半月中东部多过程性雾 霾天气;西北地区出现今年首次沙尘天气过程。     

2013年1月大气环流和天气分析

2013年1月大气环流特征为:北半球极涡呈偶极型,极涡范围及强度较常年偏弱,中高纬环流呈三波型,欧亚大陆槽位于西西伯利亚,位置偏北,引导多股冷空气影响我国北方,月内中高纬环流形势调整较大,上旬以经向型环流为主,中下旬则转为纬向型环流;西太平洋副热带高压接近常年同期,东亚大槽位于西北太平洋西岸,较常年偏强,南支槽位于90°E附近,较常年略偏弱.2013年1月,全国平均气温为-5.2℃,略低于常年同期(-5.0℃).月内气温阶段性调整明显,上旬,较同期偏低3℃,下旬,较同期偏高1.7℃.全国平均降水量为6.5 mm,较常年同期(13.2 mm)偏少50.8％.月内出现一次强冷空气过程,雾霾天气频繁,共出现3次较大范围雾霾过程.南方部分地区遭受低温雨雪冰冻灾害,北方局地遭受雪灾,云南大部、贵州西部及四川南部等地气象干旱持续.     

2017年12月大气环流和天气分析

2017年12月大气环流的主要特征如下：北半球极涡呈偶极型分布,欧亚中高纬环流呈两槽一脊型;南支槽位于70°E 附近,较常年同期偏西,副热带高压位置偏西,不利于水汽向我国中东部地区输送。12月,全国平均降水量为5.9 mm,比常年同期（10.8 mm）偏少44.8%,我国北方大部分地区降水量较常年同期偏少4~8成。全国平均气温-2.2℃,较常年同期（-3.2℃）偏高1℃;受偏强东北低涡影响,东北地区和内蒙古中东部气温较常年同期偏低1~3℃。月内,冷空气活动频繁,但强度较弱,出现5次一般强度冷空气过程。受频繁冷空气影响,雾 霾天气较常年同期偏少,仅28—30日出现一次大范围持续性雾 霾天气。     

2020年1月大气环流和天气分析

2016年1月大气环流主要特征为：北半球极涡呈偶极型分布,东亚大槽位置较常年同期偏东偏北,强度偏弱。1月,全国平均降水量为23.3 mm,较常年同期（13.2 mm）偏多77%,为1961年以来历史同期第二多。1月,全国平均气温为-3.6℃,较常年同期（-5.0℃）偏高1.4℃,月内冷空气较弱,我国中东部雾 霾天气频发,共有三次大范围持续性雾 霾过程,分别为1月3—5日、16—18日和22—28日。此外,月内共有四次降水过程。     

2011年4月大气环流和天气分析

2011年4月大气环流主要特征如下：北半球极涡呈现单极型,且偏向西半球,中高纬度地区环流呈现三波型分布,亚洲中高纬地区为一槽一脊形势。东亚大槽较常年同期偏强,西太平洋副热带高压明显偏弱,南支槽接近常年同期。2011年4月全国平均气温为11.3℃,较常年同期偏高1.0℃,西北地区大部气温明显偏高。4月全国平均降水量为21.4mm,较常年同期偏少22.4mm。月内共出现4次冷空气过程和4次沙尘天气过程,部分省（市、区）遭受强对流天气袭击。     

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