MODIS和HJ-1B资料在江苏大雾监测中的应用

雾是一种常见的天气现象,雾的遥感监测是近年来的热点之一。利用多种卫星资料实现雾的监测和预警工作,对于环境保护、灾害评估等具有重要的意义。根据云、雾及下垫面在可见光、中红外和热红外波段的光谱特性差异,结合EOS-MODIS数据特点和HJ-1B传感器波段设置等,利用多通道阈值法分别对2013年1月24日江苏省一次雾天过程不同生长阶段的雾进行雾区监测,并分别结合地面实测数据对两种数据源的监测结果进行精度检测。结果发现:对此次雾的两个生长阶段的雾区监测,MODIS数据监测的结果总体精度为80.28%,HJ-1B数据的监测结果总体精度为91.04%,两者监测效果均比较理想,HJ-1B数据可作为雾监测的一种可靠资料来源。     

利用MODIS资料定量判识沙尘暴方法研究

为了利用MOD IS资料对沙尘暴的范围和强度进行定量判识,应用多时次MOD IS多波段资料,在对沙尘暴、云、雪和沙漠光谱特征进行较为细致分析的基础上,寻找出能区分沙尘、云和地表的波段,构建了2个定量判别沙尘暴范围和强度的沙尘指数,并利用沙尘指数对2002~2005年多次MOD IS沙尘暴的范围和强度进行判识。研究结果表明:1)沙尘在反射光谱段的光谱特征为反射率随着波长的增加而增大,与土壤光谱特征相近;大粒径沙尘反射率增长速率大于小粒径沙尘。2)小粒径沙尘具有较典型的气溶胶特征,对0.46μm蓝光波段敏感,对1.6和2.1μm短红外波段不敏感。3)大粒径沙尘不具有气溶胶特性,对蓝光波段不敏感,对短波红外敏感。4)3.7μm和8.5μm是对沙尘敏感波段,2波段的差可以作为判别沙尘的指标,并在一定程度上反映沙尘强度。5)设计的2个沙尘指数对监测沙尘十分有效,且方法简单,适于业务应用。     

基于MODIS遥感资料监测南海白天雾

根据现有雾遥感监测理论,采用多通道阈值判识法,基于MODIS资料进行南海白天雾监测。该方法利用MODIS的1、2、18、20、31通道数据,分离云、雾、海表的相关信息。满足RB1<20%、RB2<20%、RB1>RB2的象元判识为海表;满足RB1>55%、RB2>55%、TB31<273 K的象元判识为中高云;海雾和低云的分离指标IFC>20的象元判识为海雾。利用2011年1—4月广东沿海海雾实地观测结果对该方法进行验证,在13个样本数据中,有9个样本的卫星监测结果与地面观测结果一致,有3个样本地面观测有雾但卫星监测为低云,1个样本地面观测有雾但卫星监测为晴空洋面。主要是因为MODIS资料本身对云雾不具备穿透性,算法设计时只能假设单一视场中只有一层云雾,对于无云覆盖的雾区较易识别,但对于被云覆盖的雾区则只能将其判识为云区,但总体来说,该监测模型是有效的、可行的。      

FY-4A资料在乌鲁木齐机场浓雾天气监测中的初步应用

利用FY-4A多通道扫描成像辐射计(AGRI)所生成的多通道图像及L2级卫星云产品数据,结合地面观测实况资料,对2019年1月25—26日和3月17—18日发生于乌鲁木齐国际机场的两次持续性浓雾天气进行分析,结果表明:对于浓雾的监测,白天综合使用通道3(BD_(0.83μm))、通道6(BD_(2.2μm))、通道8(BD_(3.725μm))和通道12(BD_(10.8μm))能很好地显示雾区范围、雾顶云结构、雾区温度等特征,且云图能很好地表现雾的消散。夜间可以结合BD_(10.8μm)和BD_(3.725μm)的差(以下简写为BTD_(10.8μm-3.725μm))和BD_(10.8μm)图像,用于识别夜间雾区,BTD_(10.8μm-3.725μm)通道亮温差越大说明雾的浓度越强。FY-4 A卫星云顶高度和云分类产品对雾的微物理特征结构反应更为细致,对于夜间大雾监测有较好的效果,能够弥补可见光通道1～通道3、短波红外通道(BD_(2.2μm))和中波红外通道(BD_(3.725μm))仅能在白天使用的不足。     

天山西部地区冰雹云的卫星光谱特征及监测应用

针对冰雹灾害多发的新疆天山西部地区,利用2007年和2008年5一10月14次MODIS卫星过境资料,选取共计45个云系样本数,进行冰雹云、强对流云团和薄卷云的光谱特征提取和雹暴指数计算与分析。结果表明,冰雹云的热红外亮度温度（CH31、CH32、CH35）均〈240K,中红外波段反射率（CH20）相对较低〈30％,可见光和短红外波段反射率（CH1和CH6）均〉80％,雹暴指数≥0．35,得到了有利于冰雹云的卫星遥感客观判识指标。     

地基可见光/红外全天空成像仪数据融合

采用60m基线的双站可见光成像仪和扫描式红外成像仪构建地基双波段全天空测云系统,双站可见光成像仪根据双站测距原理准确地获取云底高,通过全方位立体扫描获取全天空可见光云图,扫描式红外成像仪基于大气辐射传输原理测量云底亮温,反演云底高度,通过全方位立体扫描获取全天空红外云图。结合双站可见光成像仪测得云底高,对大气温度垂直递减率进行实时订正,提高扫描式红外成像仪反演云底高精度,达到双波段云底高数据融合目的;基于小波变换多分辨率分析的图像融合技术,对全天空可见光和红外云图进行图像融合,提高能见度低、以及雾、霾等天气条件下云量计算准确度;最终实现昼夜云高、云量同时观测。     

用极轨气象卫星资料分析飞机增雨云层条件

综合应用NOAA卫星AVHRR／3和FY-1极轨气象卫星高分辨0．58～0．68μm可见光、1．58～1．64μm近红外和10．3～11．3μm红外多通道资料,充分考虑了云的厚度、云中粒子尺度和云顶亮温的信息,给出了适宜飞机增雨作业云层的卫星遥感判据,建立了云层作业条件分析模型。实际应用表明,卫星遥感分析图可以有效地监测、判识和分析云层的增雨作业条件,应用效果好,可作为飞机增雨航线设计、作业决策的重要依据。通过增雨个例的微波图像特征分析,初步分析了AMSU—B微波图像在人工增雨作业中的作用和应用前景。     

双光谱云图的云分类探讨

依据各类云在红外和可见光波段不同的光谱特性，考察了近百个数字云图样本，在红外－可见光二维光谱特征空间上基本确定了与种类相应的集群分布范围，由此判识出积雨云、薄卷云、厚卷云、中云、低云、沈积云和多层云系等７种主要云类及晴空区。并以１９９０年３月１５日１４时云图为例进一步讨论了诸云类在光谱特征空间上高频数分布区的形状和分布特点。     

白天和夜间通用的卫星遥感沙尘判识算法构建与验证分析

Himawari-8是日本发射的新一代静止气象卫星,与前一代的MTSAT-2相比,在时间、空间分辨率上都有了很大提升,特别是红外通道数量从4个增至10个,为红外遥感沙尘提供了新的观测数据。本研究利用Himawari-8的红外观测数据,发展了仅用红外通道的沙尘全天候判识算法,可以实现对白天和夜间的连续监测。算法在前人基础上去除了可见光通道,同时引入更多红外通道来进行云检测和沙尘判识。由于一日之中,地表温度发生变化,因此针对白天和夜间设置了两套不同的判别阈值,来保证算法的全天适用性。最后通过两次沙尘事件对沙尘判别结果的分析和检验表明,遥感判识结果与地面气象站和PM_(10)观测较为一致,说明了只用红外通道全天候判识沙尘的可行性。     

MODIS监测雾的方法及分析

根据云雾及下垫面在可见光、长波红外和中红外波段的反射及辐射特性差异，结合MODIS资料，得出不同的波谱廓线并进行波谱分析。利用分析结果给出多通道综合阈值法监测大雾的流程，并用此方法进行了个例分析。结果表明：MODIS资料在雾监测方面有很好的应用潜力；中红外通道在雾监测上有独特的优势。     

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.     

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.     

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.     

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     

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.     

Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings

正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any     

Index to Vol.31

正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang;