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 National Satellite (INSAT) 3D are used for dust storm detection in Xinjiang because of the frequent 30-min observations with six bands. An analysis of the optical properties of dust and its quantitative relationship with dust storms in Xinjiang is presented for dust events in April 2014. The Aerosol Optical Depth (AOD) derived using six predefined aerosol types shows great potential to identify dust events. Cross validation between INSAT-3D retrieved AOD and MODIS AOD shows a high coefficient of determination (R² = 0.92). Ground validation using AERONET (Aerosol Robotic Network) AOD also shows a good correlation with R² of 0.77. We combined the apparent reflectance (top-of-atmospheric reflectance) of visible and shortwave infrared bands, brightness temperature of infrared bands and retrieved AOD into a new Enhanced Dust Index (EDI). EDI reveals not only dust extent but also the intensity. EDI performed very well in measuring the intensity of dust storms between 22 and 24 April 2014. A visual comparison between EDI and Feng Yun-2E (FY-2E) Infrared Difference Dust Index (IDDI) also shows a high level of similarity. A good linear correlation (R² of 0.78) between EDI and visibility on the ground demonstrates good performance of EDI in estimating dust intensity. A simple threshold method was found to have a good performance in delineating the extent of the dust plumes but inadequate for providing information on dust plume intensity.

In order to produce long-term aerosol optical depth (AOD) dataset over land from the Advanced Very High Resolution Radiometer (AVHRR), AVHRR data quality in terms of radiometric calibration must be maintained. A vicarious calibration method have been developed by incorporating well calibrated Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) radiance data over several pseudo-invariant targets to inter-calibrate the channel 1 of AVHRR based on Bidirectional Reflectance Distribution Functions (BRDFs) and spectral band adjustment factor (SBAF) models for different targets. Comparison of our calibration coefficients with those of Pathfinder Atmospheres Extended (PATMOS-x) indicate the calibration accuracy to be within 2.5%. The operational L1B and recalibrated AVHRR radiance are applied to derive AOD maps over East America (dark surface) and West Africa (bright surface) using the land aerosol and bidirectional reflectance inversion by times series technique (LABITS) algorithm. Preliminary comparisons show that significant difference in the retrieved AOD from the two different calibration is expected, while the spatial distribut ion of AOD difference is complicated due to different surface brightness and deficiencies of numeric solutions.