Intercomparison in spatial distributions and temporal trends derived from multi-source satellite aerosol products

Abstract

Abstract. Satellite-derived aerosol products provide long-term and large-scale observations for analysing aerosol distributions and variations, climate-scale aerosol simulations, and aerosol–climate interactions. Therefore, a better understanding of the consistencies and differences among multiple aerosol products is important. The objective of this study is to compare 11 global monthly aerosol optical depth (AOD) products, which are the European Space Agency Climate Change Initiative (ESA-CCI) Advanced Along-Track Scanning Radiometer (AATSR), Advanced Very High Resolution Radiometer (AVHRR), Multi-angle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Visible Infrared Imaging Radiometer (VIIRS), and POLarization and Directionality of the Earth's Reflectance (POLDER) products. AErosol RObotic NEtwork (AERONET) Version 3 Level 2.0 monthly measurements at 308 sites around the world are selected for comparison. Our results illustrate that the spatial distributions and temporal variations of most aerosol products are highly consistent globally but exhibit certain differences on regional and site scales. In general, the AATSR Dual View (ADV) and SeaWiFS products show the lowest spatial coverage with numerous missing values, while the MODIS products can cover most areas (average of 87 %) of the world. The best performance is observed in September–October–November (SON) and the worst is in June–July–August (JJA). All the products perform unsatisfactorily over northern Africa and Middle East, southern and eastern Asia, and their coastal areas due to the influence from surface brightness and human activities. In general, the MODIS products show the best agreement with the AERONET-based AOD values on different spatial scales among all the products. Furthermore, all aerosol products can capture the correct aerosol trends at most cases, especially in areas where aerosols change significantly. The MODIS products perform best in capturing the global temporal variations in aerosols. These results provide a reference for users to select appropriate aerosol products for their particular studies.

Synergetic Satellite Trend Analysis of Aerosol and Warm Cloud Properties ver Ocean and Its Implication for Aerosol‐Cloud Interactions

“…The opposite trends in AOD and AE lead to an insignificant AI trend over the same region (Figure 1d). The apparent positive trend in AOD over this region is also found in previous studies (Mehta et al, 2016; Pozzer et al, 2015; Wei et al, 2019). Note that in the remote ocean region, aerosols are dominated by sea salt.…”

Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees

“…Monthly PM 2.5 maps are thus synthesized and averaged from at least 20 % of available daily PM 2.5 estimates for each grid in a month, and annual PM 2.5 maps are generated from monthly PM 2.5 maps if there are more than eight available values for each grid across China (Hsu et al, 2012;Wei et al, 2019f). The spatial coverage of monthly PM 2.5 maps varies from 73 % to 92 %, with an average of 83 % across mainland China.…”

“…Nowadays, air pollution is becoming more severe due to continuously increasing anthropogenic aerosols in developing countries, especially in China (He et al, 2011;Liu et al, 2017;Zhai et al, 2019). Fine particulate matter has become the primary pollutant in urban environments, garnering much scrutiny from the public Sun et al, 2016;Wu et al, 2018). Therefore, the China Meteorological Administration established a ground PM 2.5 observation network to monitor the urban air quality in 2004 (Guo et al, 2009), followed by a denser network established by the Chinese Ministry of Environmental Protection in 2013.…”

Continuing the MODIS Dark Target Aerosol Time Series with VIIRS

“…As the comparison between the Terra and Aqua versions of the MODIS record shows [12], even identical instruments will have differences in calibration and changes in performance over time. This is also true of other aerosol products using multiple copies of the same sensor and algorithm, although the differences are smaller than the differences across less similar products [19,20]. When instruments are not identical, the difficulty in maintaining continuity increases.…”