共查询到19条相似文献，搜索用时 109 毫秒
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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。 相似文献
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基于水汽吸收波段云的反射率主要依赖于云粒子大小的原理,利用SBDART辐射传输模式和FY-3A极轨气象卫星可见光红外扫描辐射计(VIRR)的通道3(3.7μm)、中分辨率光谱成像仪(MERSI)的通道6(1.64μm)和通道7(2.13μm)所提供的探测数据进行了水云有效粒子半径的反演和比较。发现,1.64、2.13和3.7μm三个通道均能定最反演有效粒子半径的大小,其中1.64和2.13μm通道对大粒子的敏感性较高,3.7μm通道在光学厚度较小时敏感性好。三个通道的有效粒子半径反演产品与MODIS有效粒子半径产品具有较好的相关性。 相似文献
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利用MODIS资料反演兰州地区气溶胶光学厚度 总被引：15，自引：7，他引：8
借助6S模式对MODIS的蓝光(0.46μm)、红光(0.66μm)和中红外(2.1μm)通道进行了行星反照率对地表反射率和气溶胶光学厚度的敏感性试验, 并对蓝光和红光通道的路径辐射对行星反照率的贡献做了数值试验; 计算了MODIS的蓝光、红光和中红外通道在兰州市及其周围地区的地表反射率, 检验了Kaufman给出的三个通道地表反射率之间的关系。检验结果表明, 在兰州周围地区蓝光通道与中红外通道地表反射率之间的关系与Kaufman给出的关系比较符合, 对于兰州周围大范围区域都是适用的。利用此关系通过6S模式进一步反演了兰州城市及其附近地区 1×104 km2 范围内的气溶胶光学厚度, 反演结果较为合理。 相似文献
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应用AMSU-B微波资料识别强对流云区的研究 总被引：3，自引：1，他引：2
微波遥感可以穿透云顶直接探测对流云内的冰态粒子分布,受冰晶粒子的强烈散射衰减作用,AMSU-B的3个微波水汽吸收波段亮温随冰粒子的增加而降低.由于探测权重高度不同,辐射传输过程中受冰粒子的散射影响也不尽相同,3个水汽通道之间存在亮温差异,这种差异与对流云的强弱密切相关.利用微波向量辐射传输模式(VDISORT)模拟了云雨粒子对微波水汽通道观测的影响,并利用2005年8月12日华北地区的对流天气过程,分析了AMSU-B通道亮温与对流强弱变化之间的对应关系.在此基础上,建立了一种利用NOAA卫星AMSU-B水汽通道亮温差定量判识深对流云和冲顶对流云的方法.利用该方法对典型对流降水云团进行判识,结果显示,微波识别的对流云区可以较好地表征强降水的分布,其中的冲顶对流区与可见光云系的上冲云顶结构有着很好的对应. 相似文献
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HEIFE绿洲区太阳总辐射和地表反射率的分光谱特征 总被引：3，自引：0，他引：3
太阳辐射的分光测量在许多研究和应用领域中都具有十分重要的意义．本文利用HEIFE临泽子站进行的太阳总辐射和反射辐射的分光观测资料，研究了黑河绿洲区太阳总辐射和地表反射率的光谱特征．研究结果表明：在太阳总辐射的光谱能量分布中，紫外和可见光部分的比倒偏小，近红外部分则偏太．在其从冬到夏的季节变化中紫外和可见光部分是由小到大，近红外部分剐是由大到小。在其日变化中0．5μm以下波段是中午大早晚小；0．7μm以上波段是中午小，早晚大；0．5-0．7μm波段的日变化不明显。紫外波段的相对日变化幅度最大．地表反射率的光谱特性有明显的季节变化，变化特征与地表植被状况有关．各波段地表反射率的日变化型有一定的季节差异，其中波长小于0．7μm部分较为明显，并与地表植被状况有关．在裸露地表各波段反射率与太阳高度角的关系中，近红外波段随太阳高度角增加而增大，紫外和可见光波段则随太阳高度角增大而减小．全波段反射率随太阳高度角增大而增大主要是近红外波段的贡献．这是裸露地表光谱反射率的重要特征之一。 相似文献
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应用6S辐射传输模式对MODIS可见光到中红外波段的反射率进行大气订正，订正过程分两步进行:首先设定地表为朗伯体，再应用二向反射模型BRDF进行订正，订正结果与美国MODIS研究组应用MAS实验结果进行比较表明，两者变化趋势是一致的；经过臭氧、水汽、气溶胶等散射吸收订正，对于一定范围的反射率，大气订正使植被区红光波段反射率ρ1降低、近红外波段反射率ρ2增加，蓝光波段反射率ρ3降低；大气订正后，归一化植被指数INDV较大气订正前有所增加，增加的最大值为0.104，抗土壤-大气植被指数IEV值略有减小，减小的最大值为0.005。 相似文献
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利用NOAA-16/AMSU-B微波亮温资料和GOES-9光学遥感资料对2004年6月16日一次锋面气旋云系中的强对流云团进行识别, 尝试了NOAA-16/AM SU-B微波两窗区通道亮温、3个微波水汽通道间亮温差, GOES-9红外亮温阈值、水汽和红外通道亮温差、红外和水汽通道亮温多光谱逐个修改聚类等方法, 通过比较各种方法的识别结果, 分析各种识别技术的特点, 同时采用地面常规观测资料进行叠加, 对识别方法进行了验证。结果表明:微波对强对流云团均能较好识别, 但89 GHz通道亮温受地表影响较大, 不能很好剔除过冷水体, 150 GHz通道亮温与微波水汽通道间亮温差的识别结果较一致, 3个微波水汽通道间亮温差对阈值的依赖性相对较小; GOES-9红外亮温阈值因其随时空变化对识别结果会造成较大差别, 而水汽和红外通道亮温差对强对流云团能进行较好定位, 但识别范围较小, 多光谱逐个修改聚类方法对积雨云的识别效果较好, 且和NOAA-16/AMSU-B识别结果有较好的对应关系; 地面常规观测资料的叠加结果也说明, 多波段遥感资料对强对流云团的识别结果与当时的天气现象及积雨云状均有较好的对应关系。 相似文献
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Jung-Moon Yoo Myeong-Jae Jeong Young Min Hur Dong-Bin Shin 《Asia-Pacific Journal of Atmospheric Sciences》2010,46(1):29-40
This study analyzes radiative effect of the higher clouds over the fog layer and presents the improvement of fog detection over the Korean peninsula, utilizing satellite data of the Multi-functional Transport SATellite (MTSAT)-1R and the MODerate resolution Imaging Spectroradiometer (MODIS) and the Look-Up Table (LUT) based on Radiative Transfer Model (RTM) simulations. Fog detection utilizing the satellite data from visible (0.68 µm) and infrared (3.75 µm and 10.8 µm) channels has been evaluated in comparison with ground-based observations over 52 meteorological stations in the Korean Peninsula from March 2006 to February 2007. The threshold values for fog sensing have been derived from the difference (i.e., T3.7–11) in brightness temperature between 3.75 µm (T3.7) and 10.8 µm (T11) during day and night, and also from the reflectivity at 0.68 µm (R0.68) in the daytime. In the twilight, however, the difference between the temperature values at 10.8 µm and their maximum within previous 15 days (i.e., T11max-11) are used instead, because the 3.75 µm channel is inaccurate for the fog detection at dawn/dusk. The sensitivity of the T3.7–11 values with respect to the clouds is investigated based on the cloud variables such as its height, optical thickness, and amount. The values of T3.7–11 are the most sensitive to cloud height, followed by cloud optical thickness and effective radius, while R0.68 is insensitive to cloud height. The sensitivity is examined with various conditions of cloud phases and day/night. Sixteen cases among eighteen fog occurrences, which have been unable to be sensed by using only the conventional threshold values, are successfully detected with the additional LUT corrections, indicating a significant improvement. The method of fog detection in this study can be useful to the Communication, Ocean, and Meteorological Satellite (COMS) Meteorological Data Processing System (CMDPS) by reducing the cloud effect on fog sensing. 相似文献
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Based on a current fog detection theory, a multiband threshold method for MODIS data was put forward to detect daytime fog in the South China Sea. It used Bands 1, 2, 18, 20 and 31 of MODIS data to separate fog from the cloud and the sea surface. The digital detection indexes were as follows. If RB1<20%, RB2<20% and RB1>RB2, the pixel was identified to be the sea surface. If RB1>55%, RB2>55% and TB31<273 K, the pixel was identified to be a middle- and high-level cloud. If IFC>20, the pixel was classified to be sea fog. The method was verified with sea fog data observed from the coastal region of Guangdong during January-April 2011. Out of the 13 samples of satellite detection, nine were consistent with the surface observations, three were identified to be low-level the cloud according to the satellite detection but fog according to the surface observations, and only one sample was identified to be the ocean surface by the satellite detection but fog by the surface observations. Because the MODIS data cannot penetrate the cloud or fog, the model was designed for a single field of view which had only one layer of cloud or fog. It can accurately distinguish fog which is not covered by the cloud, but it identifies fog as cloud if the former is covered by a cloud. Generally speaking, the model is effective and feasible. 相似文献
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海雾是一种常见的灾害性天气现象。以我国台湾海峡为示范研究区, 利用新一代卫星传感器MODIS的可见光和红外探测通道数据, 在分析海洋、中高云、低云和海雾等不同下垫面的MODIS光谱辐射特征基础上, 选择对海雾具有敏感反应的探测通道, 通过综合判识建立台湾海峡海雾遥感监测模型。利用该模型对2004-2007年我国台湾海峡海雾事件进行监测, 并用福建沿海5个地面气象观测站的能见度数据对监测结果进行验证分析。结果表明:基于MODIS数据的海雾遥感监测模型能够较准确地对台湾海峡海雾分布和发展过程进行监测, 从地面观测数据与卫星监测结果对比验证来看, 海雾监测的准确率可达80 %以上, 具有较高的业务化应用前景。 相似文献
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利用FY-2C卫星数据反演云辐射特性 总被引：2，自引：0，他引：2
本文利用FY-2C静止卫星提供的可见光、中红外和热红外观测数据, 开展了水云光学厚度、粒子有效半径和云顶温度的云参数遥感探测理论和反演方法研究。基于FY-2C可见光、中红外(3.75 μm)与热红外(11 μm)通道辐射率对云光学厚度、 云滴有效半径、云顶温度辐射参数的敏感性分析, 提出三通道同时反演云的光学厚度、云滴有效半径及云顶温度的迭代方案; 通过个例分析进行了云参数反演试验, 并将结果与MODIS的云反演产品进行了对比, 最后对反演误差进行了分析。主要结论如下:(1) 个例反演得到的云参数与各通道探测数据有着较好的对应关系, 迭代计算标准偏差在允许的计算精度范围内(<0.89%), 反演结果具有合理性; (2) 通过与MODIS云反演产品的对比可以看到, 两者云光学厚度、云滴有效半径的均值和直方图分布都非常一致, 而MODIS的云顶温度比FY-2C反演值要高, 考虑到FY-2C的 11 μm通道测量的辐射值与MODIS相比偏小, 因此认为我们的反演方法与MODIS方法的精度是相当的。 相似文献
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Jung-Rim Lee Chu-Yong Chung Mi-Lim Ou 《Asia-Pacific Journal of Atmospheric Sciences》2011,47(2):113-122
A fog detection algorithm that uses geostationary satellite data has been developed and tested. This algorithm focuses on continuous fog detection since temporal discontinuities, especially at dawn and dusk, are a major problem with current fog detection algorithms that use satellite imagery data. This is because the spectral radiance at 3.7 μm contains overlapping emissive and reflectance components. In order to determine the radiance at 3.7 μm under fog conditions, radiative transfer model simulations were performed. The results showed that the radiance at 3.7 μm obviously varies with the solar zenith angle, and the brightness temperature differences between 3.7 μm and 10.8 μm are completely dissimilar between day and night (positive and varying with the angle during the daytime, but negative and constant at night). In this algorithm, a dynamic threshold is used as a function of the solar zenith angle. Moreover, additional criteria such as infrared, split-window channels, and a water vapor channel are used to remove high-level clouds. Also, the visible reflectance (0.67 μm) channel is used in the daytime algorithm because visible channel images are very practical for confirming a fog area with the high reflectivity and the smooth texture. The clear-sky visible reflectance for the previous 15 days was also employed to eliminate the surface effect that appeared during dawn and dusk. As the results, fog areas were estimated continuously, allowing the lifecycle of the fog system, from its development to decline, to appear obviously in the resulting images. Moreover, the estimated fog areas matched well with surface observations, except in a high latitude region that was covered by thin cirrus clouds. 相似文献
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利用2005-2010年卫星云图FY-2E、海岸带一海区出现的28次大雾天气资料和2008-2010年海岛站资料,依据大气状态方程、热力学原理,在MICAPS3．0系统下,应用云图与同步探空、地面雾区叠加图、温度场逆温层剖面及TBB值与海面温度比较,估算雾区面积、高度及秋、冬季雾区温度垂直递减率。结果表明：在环渤海地区特定的环流背景下,红外云图和可见光云图监测到的雾区分别在大连、烟台及天津一带由轻雾转为大雾,沿海岸带向北发生发展,雾区垂直厚度为400-600m,递减率为0．02-0．04℃／100m,渤海东西向温度差值为1q℃,南北向为3-5℃;辐射雾对应弱高压均压场,平流雾对应弱低压均压场;低云覆盖雾区浓雾加重,轻雾被低云叠加使得能见度降低;平流雾被锋面抬升后混合到低空水汽输送带之中,对后期降雪（水）具有指示作用。在2009-2010年海区一海岸带大雾天气预报及预警信号升级应用中效益显著,可为海岸带大雾预报因子选取及预报监测业务流程的改进提供参考。 相似文献
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This paper presents a nighttime sea fog detection algorithm incorporating unsupervised learning technique. The algorithm is based on data sets that combine brightness temperatures from the 3.7 μm and 10.8 μm channels of the meteorological imager (MI) onboard the Communication, Ocean and Meteorological Satellite (COMS), with sea surface temperature from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA). Previous algorithms generally employed threshold values including the brightness temperature difference between the near infrared and infrared. The threshold values were previously determined from climatological analysis or model simulation. Although this method using predetermined thresholds is very simple and effective in detecting low cloud, it has difficulty in distinguishing fog from stratus because they share similar characteristics of particle size and altitude. In order to improve this, the unsupervised learning approach, which allows a more effective interpretation from the insufficient information, has been utilized. The unsupervised learning method employed in this paper is the expectation–maximization (EM) algorithm that is widely used in incomplete data problems. It identifies distinguishing features of the data by organizing and optimizing the data. This allows for the application of optimal threshold values for fog detection by considering the characteristics of a specific domain. The algorithm has been evaluated using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) vertical profile products, which showed promising results within a local domain with probability of detection (POD) of 0.753 and critical success index (CSI) of 0.477, respectively. 相似文献
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导线积冰在贵州山区是常见的气象灾害, 导线积冰增长率与气象云雾因子密切相关。研究选择贵州西部、北部、中部3个积冰区进行了专门外场观测, 观测项目有:云滴谱、含水量、气温、风向、风速、导线上积冰的长径、短径。观测分析表明:贵州云滴浓度、特征平均直径没有显著性地区差异; 云滴平均浓度140~312个/cm3, 云滴算术平均直径、均立方根直径、中值体积直径分别为7.5 μm, 11.3 μm和20 μm; 14 μm以上大云滴浓度平均占云滴总浓度的12.5%, 但对含水量的贡献高达78%, 大滴与导线碰撞效率高, 大滴是导线积冰的关键因子; 云雾含水量平均0.20 g/m3; 在0~-6 ℃之间, 含水量随温度的降低而降低; 南北向导线积冰比东西向的积冰多; 导线积冰增长率与含水量的大小成正比, 风速超过3 m/s时, 积冰增长率与风速有较明显的正比关系。 相似文献