Aerosol Optical Depth investigated with satellite remote sensing observations in China
نویسندگان
چکیده
In this study, Aerosol Optical Depth (AOD) at 550nm from the MODIS sensor on board the Terra/Aqua satellites were compared with sun photometer (CE-318) measurements from 11 AERONET stations in China. The average correlation coefficient (R) value from the AOD product, using the Aqua-MODIS Deep Blue algorithm, in the Hexi Corridor was 0.67. The MODIS Dark Target algorithm AOD product is superior to Deep Blue algorithm AOD products in SACOL of the Semi-arid regions of the Loess Plateau. These two kinds of algorithm are not applicable to sites in Lanzhou city. The average R value of Dark Target algorithm AOD MODIS products is 0.91 for Terra and 0.88 for Aqua in the eastern part of China. According to the analysis of spatial and temporal characteristics of the two MODIS AOD products in China, high value areas are mainly distributed in the southern part of Xinjiang (0.5~0.8), Sichuan Basin (0.8~0.9), North China (0.6~0.8) and the middle and lower reaches of the Changjiang River (0.8~1.0). The Deep Blue algorithm for Aqua-MODIS is a good supplement for the retrieval of AOD above bright surfaces of deserts in Northwest China.
منابع مشابه
Validation of MODIS Aerosol Optical Depth Retrieval over Mountains in Central China Based on a Sun-Sky Radiometer Site of SONET
The 3 km Dark Target (DT) aerosol optical depth (AOD) products, 10 km DT and Deep Blue (DB) AOD products from the Collection 6 (C6) product data of Moderate Resolution Imaging Spectroradiometer (MODIS) are compared with Sun-sky Radiometer Network (SONET) measurements at Song Mountain in central China, where ground-based remote sensing measurements of aerosol properties are still very limited. T...
متن کاملبهره گیری از سری زمانی داده های ماهواره ای به منظور اعتبارسنجی کانون های شناسایی شده تولید گرد و غبار استان البرز
Dust is one of the common processes of arid and semiarid regions that its occurrence frequencies has increased in recent years in Iran. The proper identification of sand and dust storms (SDS) is particular importance due to its impact on the environment and human health. So far, several methods for identifying these sources have been proposed such as methods based on field studies and geomorpho...
متن کاملQuantitative retrieval of aerosol optical thickness from FY-2 VISSR data
Atmospheric aerosol, as particulate matter suspended in the air, exists in a variety of forms such as dust, fume and mist. It deeply affects climate and land surface environment in both regional and global scales, and furthermore, lead to be hugely much influence on human health. For the sake of effectively monitoring it, many atmospheric aerosol observation networks are set up and provide asso...
متن کاملDust Aerosol Optical Depth Retrieval and Dust Storm Detection for Xinjiang Region Using Indian National Satellite Observations
The Xinjiang Uyghur Autonomous Region (Xinjiang) is located near the western border of China. Xinjiang has a high frequency of dust storms, especially in late winter and early spring. Geostationary satellite remote sensing offers an ideal way to monitor the regional distribution and intensity of dust storms, which can impact the regional climate. In this study observations from the Indian Natio...
متن کاملMerging aerosol optical depth data from multiple satellite missions
This discussion paper is/has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP if available. Abstract Agricultural biomass burning (ABB) in Central and East China occurs every year from occurred mainly in An-hui, Henan, Jiangsu and Shandong provinces. A comprehensive set of aerosol optical 5 depth (AOD) data, produced...
متن کامل