基于支持向量机的遥感大雾判识

提出了一种基于支持向量机的卫星遥感数据大雾判识方法:首先通过对风云1D卫星大雾区域的各通道辐射值出现频次进行概率统计,利用其阈值来粗判识大雾;然后在粗判识的基础上通过支持向量机的方法进行大雾细判识;最后利用腐蚀和膨胀的图像处理技术对判识后的图像进行优化处理。在对我国2006年9-12月的65条监测到大雾的风云1D轨道的探测数据进行分析之后,发现大雾判识结果与专家标记吻合。检验结果表明,利用1、2、4、6、7、10通道组合进行粗判识的结果最好,5交叉正确率为89.9849%,TS评分为74.04%。利用上述方法对个例的分析检验表明,基于支持向量机的遥感大雾判识方法是切实可行的。     

EOS—MODIS卫星资料在北疆大雾监测中的应用分析

根据雾与云、积雪、裸地等地表物在可见光、长波红外和中红外波段的反射及辐射特性差异,利用MODIS卫星多通道多光谱探测数据,采用最佳波段组合法和量化判识指标法,对2006年3月8日到10日北疆大雾天气进行判识检验试验和动态监测分析。结果:发现较利于雾与背景(地物、云、雪)分离的最佳波段是可见光B0.65μm和近红外B0.85μm、短红外B1.64μm、中红外B3.7μm、热红外B11μm,综合判识就可以将云、雾、雪、裸地有效的区分;雾在夜间的有效温度在中红外波段比热红外波段低,可采用中红外和热红外波段的组合方法,根据两通道的亮温差进行雾的监测。     

基于多灰度共生矩阵特征值的黄渤海白天海雾识别算法

本文基于多灰度共生矩阵特征值,即相关性、对比度、同质性和能量,进行联合海雾遥感判识,提出一种高准确率黄渤海白天海雾识别算法。采用第二代静止气象卫星FY-4A可见光、近红外和红外数据,将该算法应用于黄渤海区域白天海雾判识,并利用2019—2020年沿黄渤海气象站点能见度实测数据及CALIPSO卫星数据产品对本算法识别结果进行精度验证。结果表明：海雾识别平均检测率(POD)为92%,误报率(FAR)为27%,临近成功指数(CSI)为69%,可以实现对海雾的动态监测,为海上交通等领域提供较好的数据支持。     

基于FY-4A卫星数据的强对流云团识别与监测

为解决强对流监测问题,克服地区亮温特征对卫星监测的影响,利用FY 4A卫星L1数据,结合滑动窗口方法和多通道动态阈值自动识别法,对典型强对流云团进行识别与监测。结果表明：1）多通道动态阈值自动识别方法结合滑动窗口方法,可避免人为设置阈值的主观性,整合强对流的区域识别结果,实现全国强对流云团监测。2）此方法具有良好的强对流云团识别效果,识别正确率达到89%;3）FY 4A卫星识别结果与雷达反射率高值区基本一致,能够准确监测强对流云团发生发展和移动的过程,具有较高的识别精度。     

基于FY-2C红外资料进行夜间云检测的方法研究

应用2007年4月30日20时至5月1日03时的FY-2C红外亮温资料、地面云观测资料以及地理海拔高度资料,详细分析了无云条件下红外亮温与地理海拔高度之间的关系特征。通过建立夜间无云条件下红外亮温与地理海拔高度之间对应关系的标准数据库,以此为判据实现了有云区和无云区的分离,云检测个例结果表明正确率可达88%;将无云区误判为有云区的百分比为4%,同时将有云区误判为晴空区的百分比是8%。在云区的云检测正确率为82%;在无云区的云检测正确率达到92%。在业务化应用和适用性分析中,以5月1日00时资料建立的判据,分别对5月2日至5日00时整个区域进行云检测试验,分析结果表明其总体准确率与5月1日00时的基本接近但稍高,达到92%。在云区的判识正确率提高到93%,从而导致总体准确率稍微提高;而在无云区的判识效果与5月1日00时的一致为92%。     

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。      

三种经典夜间陆地雾遥感反演方法的适用性对比分析

相较于地面站点观测,卫星可以监测更大范围的夜间雾区分布,目前虽然已存在几种经典的夜间陆地雾遥感反演算法,然而其在我国大范围陆上的适用性尚不清楚。基于葵花8号（Himawari-8）静止气象卫星数据,分别利用双通道差值法、温度差值法及归一化大雾指数法反演了我国2016年1月—2018年12月的夜间陆地雾区,并用地面观测资料以鉴定成功评分、准确率、判识率和误判率为指标参数对雾区反演结果进行验证分析,讨论了三种反演方法的适用性。结果显示:1)三种夜间陆地雾反演方法在秋季和冬季反演效果最好,其中温度差值法的鉴定成功评分高、准确率高、误判率低,反演效果最好,双通道差值法的判识率高、误判率高,反演效果次之,归一化大雾指数法效果最差。2)三种方法对夜间陆地雾的反演在秋季和冬季的最佳适用区域略有不同,但都倾向于在平原和盆地达到最佳效果,如华北平原、长江中下游平原和四川盆地。3)两次雾过程的反演结果显示,温度差值法和双通道差值法对平原地区夜间雾的识别能力均较强,在具体雾过程反演中各有优势。     

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。     

FY-4A卫星夜间大雾识别及其在高速公路服务应用中的潜力分析

利用2018年3月至2020年2月FY-4A卫星AGRI高时空分辨率多通道数据与同期湖北省夜间大雾天气个例,先确定夜间大雾在AGRI长波红外波段(10.8μm)和中波红外波段(3.72μm)的识别阈值,再使用地面气象观测站点资料对卫星识别结果进行检验;最后,结合高速公路交通管制信息,分析夜间大雾识别方法在湖北省高速公路服务应用中的潜力。结果表明:(1)基于FY-4A卫星识别的夜间大雾,与气象观测站实况大雾较为一致。(2)卫星对夜间大雾的识别命中率普遍在70%以上;不考虑地形影响,其识别命中率可提高5%～8%;不考虑云影响,识别命中率可提高3%～4%。(3)与湖北省高速公路交通管制信息对比,FY-4A卫星对收费站点大雾识别命中率均高于70%,并在部分国家气象站未观测到大雾而因雾封路的区域可实现对大雾天气的有效识别,其对夜间大雾的识别信息在高速公路交通气象服务中具有较大应用潜力。     

深度学习网络在降水相态判识和预报中的应用

利用1996—2015年中国的高空探测资料和地面观测数据,挑选发生降水的数十万个样本将其分为降雨和降雪两类事件,抽象为二分类问题,采用深度学习网络技术构建降水相态判识模型,并用2016—2017年的数据进行测试检验,针对2018年1月下旬中国一次大范围雨雪天气过程进行个例检验,在此基础上探讨了深度学习网络在降水相态判识和预报中的应用。主要结论如下:基于深度学习网络判识模型的判识准确率为98.2%,雨、雪的TS评分分别为97.4%和94.4%,相应空报率为1.7%和2.0%,漏报率为1.0%和3.7%,较传统指标阈值法的判识准确率有较大提高;个例检验显示,基于实况探空数据的模型判识结果与降水相态实况在全国基本保持一致,欧洲中期数值预报中心(ECMWF)的降水相态预报产品和模型的预报结果对全国的降水相态都表现出较好的预报能力,而对雨雪分界线的预报,模型的预报结果较ECMWF总体上更接近实况。测试结果表明,模型较好地提取了雨、雪降水相态的结构特征,深度学习网络在降水相态判识和预报中的应用具有可行性和一定的优势,可为降水相态的客观判识和预报提供重要技术支撑。     

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.     

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.     

Information for Authors

正AIMS AND SCOPE Atmospheric and Oceanic Science Letters (AOSL) publishes short research letters on all disciplines of the atmosphere sciences and physical oceanography. Contributions from all over the world are welcome.SUBMISSIONAll submitted     

Information for Authors

AIMS AND SCOPE Atmospheric and Oceanic Science Letters （AOSL） pub- lishes short research letters on all disciplines of the atmos- phere sciences and physical oceanography. Contributions from all over the world are welcome.