近44a济南市四季变化气候分析

利用济南市所属6个国家级地面气象观测站的1971—2014年44a的逐日气温资料,从气象角度分析了济南市近44a四季开始时间和持续期的变化特征。结果显示：近44a来,济南春季、夏季和秋季开始时间呈现出提前的趋势,春季开始时间变化在四季中变化最为明显,秋季开始时间变化在四季中变化最为缓慢;冬季开始时间呈现出推迟的趋势。济南春季、夏季和秋季持续时间呈现出增长的趋势,夏季持续时间变化在四季中变化最为缓慢;冬季持续时间呈现出缩短的趋势,冬季持续时间变化在四季中最为明显。     

通辽市可吸入颗粒物质量浓度变化监测分析

文章基于通辽市2011年6月至2013年5月可吸入颗粒物质量浓度(PM10)资料数据,统计结果表明:(1)PM10年均质量浓度为85.92μg·m-3,未达到国家环境空气质量二级标准;(2)PM10季均质量浓度特征是春季冬季秋季夏季,PM10月平均质量浓度与季节分布基本一致;(3)PM10质量浓度在一周中呈现出单峰变化的特点,不同季节PM10质量浓度周变化不同;(4)PM10质量浓度日变化呈现双峰型分布。PM10浓度峰值从夏季到冬季逐渐推迟,这主要与日出日落时间和其他气象条件,以及上下班交通高峰相关;春季峰值还与沙尘天气发生时间有关。     

近56 a湖北荆州四季初日与季节长度变化特征

利用1960—2015年湖北省荆州市6个国家地面气象观测站的逐日平均气温资料,采用候气温分析荆州春、夏、秋、冬四季初日与长度变化特征,结果表明:荆州近56 a四季初日表现为春季和夏季提前,秋季和冬季推迟;春、夏和秋季初日随年代变化显著,而冬季初日随年代变化不显著。季节平均长度夏季和冬季为120 d左右,春季和秋季为60 d左右,夏季日数冬季日数春季日数秋季日数。从年际变化来看,夏季变长,冬季缩短,春秋季变化不明显;从年代际变化来看,夏季明显变长,秋季和冬季缩短较明显,而春季变化不明显。     

北京中央商务区(CBD)城市热岛效应的研究

利用2012~2013年北京中央商务区（Central Business District,CBD）加密观测资料,分析CBD区域城市热岛（Urban Heat Island,UHI）强度日变化和空间变化特征及其影响因子。研究发现,CBD区域气温高于周边自动站气温,平均偏高0.64℃;CBD区域城市热岛强度呈现夜间强、白天弱的现象,中午甚至存在“城市冷岛”现象。季节平均UHI日变化表现为:在夜间,秋季最强,冬季次之,春季和夏季较弱;在白天,夏季最强,冬季次之,春季和秋季较弱。相对于晴朗无风天气,雾、雨、大风等天气对城市热岛有抑制作用,并结合小波分析结果发现,秋季城市热岛强度强于冬季是由于冬季雾、雨、大风等天气过程发生比例较高的缘故。CBD区域城市热岛空间变化特征研究发现,花园、学校等绿地有助于缓解城市热岛效应。雾日、雨日和大风日的CBD区域城市热岛强度空间变化标准差比晴朗无风日小。     

城市雷暴日特征及防雷减灾应对措施

利用驻马店市气象观测站提供的相关气象数据2000—2013年驻马店市逐月观测雷暴日资料,进行了统计、分析得出驻马店地区雷暴日活动时间、变化规律和分布特征,结果表明:驻马店地区年平均雷暴日数为27.6d,雷暴日数呈现出缓慢减少的总趋势,属于中雷区;除了12月和1月份外,一年中驻马店地区都有雷暴天气出现,尤其是3—7月份为雷暴多发月份,占总雷暴日数的89%;夏季出现雷暴天气的概率较大,其次是春季和秋季,冬季很少出现雷暴天气。     

近60a来南京季节变化特征分析

利用1951年1月-2010年12月南京市逐日气温观测资料,依据张宝堃应用候平均气温稳定通过某一临界值划分四季的标准,建立了近60 a南京的季节平均气温的时间序列,分析了近60a南京春、夏、秋、冬四季开始、结束及持续时间的变化特征,给出了季节气温的变化趋势以及候平均与入季时间、季节持续时间的相关分析.结果表明:近60a,南京入冬时间推迟,入夏时间提前.冬季变短,缩短的平均速率为2.9 d/10a;夏季变长,增加的平均速率为4.1d/10a;秋季变短,缩短的平均速率为1.5d/10a;春季略有些变长.南京冬、春季平均气温升高,且冬季气温升高更为显著,而夏、秋季平均气温下降,秋季气温下降略明显于夏季.冬季最低气温有升高的趋势,夏季最高气温与年较差有下降的趋势.春季入季时间与春季的平均气温成正相关,而秋季的入季时间与秋季平均气温成负相关;夏季的平均最低气温和平均气温与夏季的长度成负相关,冬季的平均最高气温和冬季的长度成正相关.     

青岛大气气溶胶的浓度分布和干沉降的观测研究

根据青岛沙尘天气历史资料和近年来的青岛地面气溶胶观测资料,分析了青岛沙尘日数的长期变化趋势、季节变化特征以及气溶胶质量浓度、谱分布和干沉降的季节变化.分析结果表明,1961～1988年青岛沙尘日数呈波动变化,且幅度较大.1999年以来沙尘日数明显增加,且以浮尘天气为主.青岛在1961～2001年扬沙日数年平均值为1.83天,是北京同期的13%;年浮尘日数为2.93天,是北京同期的75%.青岛沙尘发生日数主要集中在冬春季,春季最高,冬季次高;夏季没有沙尘天气,秋季很低.青岛气溶胶质量浓度有明显的季节变化,春季最高,冬季次之,秋季又次之,夏季最低.大流量观测的总悬浮颗粒物(TSP)年平均浓度为177μgm-3,安德森分级采样器观测的气溶胶质量浓度为123μg m-3,两者的差别与不同的观测时间和观测仪器有关.在3月和4月,粗细粒子的浓度相差很大,粗粒子分别占总浓度的80%和62%.青岛气溶胶沉降通量在0.06～0.2 g m-2d-1之间,平均值为0.13 g m-2d-1,是北京沉降通量的30%.     

塔中比湿变化特征

本文计算出塔中气象站2007年的比湿,结合其他气象要素分析了塔中比湿的变化特征。结果显示：本地区比湿的月平均日总量7月最大（155.5 g?kg-1）,1月最小（21.8 g?kg-1）,年平均值为72.4 g?kg-1。年振幅为86.3 g?kg-1,相对年振幅为66%。夏季约为冬季的5倍。日最大值和日最小值夏季大于冬季,其中7月最大,分别为263.4 g?kg-1和93.4 g?kg-1。夏季最高,冬季最低,秋季高于春季。四季的平均日变化7月最大,1月最小,4月与10月相差不大。4月与10月的日峰值相差0.1 g?kg-1,7月和1月的日峰值相差6.2 g?kg-1。各季晴天日变化较小。日总量最大值与最小值在夏季相差最大,冬季相差最小。逐日比湿上下变动的离散度在冬季最小,其次是春季和秋季,夏季最大,这与地方气候特征有关。降水天比湿增加,沙尘天比湿减小。各季比湿与气温、相对湿度的相关性较高,水汽压和露点温度也与比湿有很大的正相关性。     

1961—2008年银川市灰霾天气的气候特征

对1961—2008年银川市灰霾天气日数资料进行分析。结果表明：银川市灰霾天气呈逐渐增加的趋势2,0世纪80年代前为缓慢增加阶段,20世纪后灰霾天气显著增加2,000年后灰霾天气急剧增加。银川市灰霾日数最多为12月,其次为11月,最少为5月,呈现出冬季大于秋季大于春季大于夏季的季节特征。一般情况下,银川市灰霾日数持续1—3d,持续2d及以上的灰霾天气占17%,持续5d及以上的灰霾天气占1%。持续时间较长的灰霾天气集中出现在冬季11月至翌年2月。灰霾天气持续时间与年代际变化有关,2000年前,银川未出现持续5d以上的灰霾天气过程;2000年后,随着灰霾天气日数增多,灰霾持续时间延长。     

中国中东部地区硫酸盐气溶胶直接辐射强迫及气候效应的数值模拟

分析了MODIS卫星资料反演的2001年我国中东部地区气溶胶光学厚度的时空分布特征，并利用中尺度数值模式MM5对该地区硫酸盐气溶胶的直接辐射强迫及其气候效应进行了模拟。结果表明:2001年四川盆地、长江中下游地区、黄淮一带及两广等地区气溶胶光学厚度较大。各季光学厚度变化不同，全年以春季最大。地面温度响应呈现出明显的区域季节变化特征，主要表现为冬、春、秋季南方降温幅度明显，夏季北方降温幅度明显。就区域平均而言，2001年中东部地区晴空时气溶胶辐射强迫以春季最大，达-34.53 W/m2；夏季次之，达-22.76 W/m2；冬季再次，达-22.57 W/m2；秋季最小，达-20 W/m2。地面降温则以冬季最大，达-0.65℃；秋季次之，达-0.37 ℃；春季再次，达-0.34 ℃；夏季最小，达-0.09 ℃。     

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.     

VARIABILITY OF INTER-ANNUAL RELATIONSHIP BETWEEN INDIAN OCEAN DIPOLE AND HUAXI REGION’S AUTUMN PRECIPITATION

The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region.     

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     

全球贸易隐含碳变化及其影响分析

基于最新的GTAP8 (Global Trade Analysis Project）数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。     

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.     

Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery

Hourly outgoing longwave radiation(OLR) from the geostationary satellite Communication Oceanography Meteorological Satellite(COMS) has been retrieved since June 2010. The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels. This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm(OLR12.0using the 12.0 μm channel) and three multiple-channel algorithms(OLR10.8+12.0using the 10.8 and 12.0 μm channels; OLR6.7+10.8using the 6.7 and 10.8 μm channels; and OLR All using the 6.7, 10.8, and 12.0 μm channels). The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth's Radiant Energy System(CERES) over the full COMS field of view [roughly(50°S–50°N, 70°–170°E)] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5–7 W m-2, which indicates good agreement with CERES OLR over the vast domain. OLR6.7+10.8and OLR All have much smaller errors(～ 6 W m-2) than OLR12.0and OLR10.8+12.0(～ 8 W m-2). Moreover, the small errors of OLR6.7+10.8and OLR All are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration. These results indicate a noteworthy role of the6.7 μm water vapor absorption channel in improving the accuracy of the OLRs. The dependence of the accuracy of COMS OLRs on various surface, atmospheric, and observational conditions is also discussed.