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Combined dust detection algorithm by using MODIS infrared channels over East Asia

机译:利用东亚地区的MODIS红外通道进行组合式粉尘检测算法

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摘要

A new dust detection algorithm is developed by combining the results of multiple dust detectionmethods using IR channels onboard the MODerate resolution Imaging Spectroradiometer (MODIS). Brightness Temperature Difference (BTD) between two wavelength channels has been used widely in previous dust detection methods. However, BTDmethods have limitations in identifying the offset values of the BTDto discriminate clear-sky areas. The current algorithm overcomes the disadvantages of previous dust detection methods by considering the Brightness Temperature Ratio (BTR) values of the dual wavelength channels with 30-day composite, the optical properties of the dust particles, the variability of surface properties, and the cloud contamination. Therefore, the current algorithm shows improvements in detecting the dust loaded region over land during daytime. Finally, the confidence index of the current dust algorithm is shown in 10 × 10 pixels of the MODIS observations. From January to June, 2006, the results of the current algorithm are within 64 to 81% of those found using the fine mode fraction (FMF) and aerosol index (AI) from the MODIS and Ozone Monitoring Instrument (OMI). The agreement between the results of the current algorithm and the OMI AI over the non-polluted land also ranges from 60 to 67% to avoid errors due to the anthropogenic aerosol. In addition, the developed algorithm shows statistically significant results at four AErosol RObotic NETwork (AERONET) sites in East Asia.
机译:通过使用MODerate分辨率成像光谱仪(MODIS)上的IR通道结合多种灰尘检测方法的结果,开发了一种新的灰尘检测算法。在先前的灰尘检测方法中,两个波长通道之间的亮度温差(BTD)已被广泛使用。但是,BTD方法在识别BTD的偏移值以区分晴朗天空区域方面存在局限性。当前的算法通过考虑具有30天复合材料的双波长通道的亮度温度比(BTR)值,灰尘颗粒的光学特性,表面特性的可变性以及云污染,克服了以前的灰尘检测方法的缺点。 。因此,当前算法显示出在白天白天检测陆地上的粉尘负荷区域方面的改进。最后,当前尘埃算法的置信指数显示在MODIS观测值的10×10像素中。从2006年1月到6月,当前算法的结果是使用MODIS和臭氧监测仪(OMI)的精细模式分数(FMF)和气溶胶指数(AI)得出的结果的64%至81%之内。当前算法的结果与无污染土地上的OMI AI的一致性也介于60%到67%之间,以避免人为气溶胶引起的误差。此外,开发的算法在东亚的四个AErosol机器人网络(AERONET)站点上显示出统计上显着的结果。

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