Abstract

In this study, Terra-MODIS (Moderate Resolution Imaging Spectroradiometer) Collections 6 and 6.1 (C6 & C6.1) aerosol optical depth (AOD) retrievals with the recommended high-quality flag (QF = 3) were retrieved from Dark-Target (DT), Deep-Blue (DB) and merged DT and DB (DTB) level–2 AOD products for verification against Aerosol Robotic Network (AERONET) Version 3 Level 2.0 AOD data obtained from 2004–2014 for three sites located in the Beijing-Tianjin-Hebei (BTH) region. These are: Beijing, located over mixed bright urban surfaces, XiangHe located over suburban surfaces, and Xinglong located over hilly and vegetated surfaces. The AOD retrievals were also validated over different land-cover types defined by static monthly NDVI (Normalized Difference Vegetation Index) values obtained from the Terra-MODIS level-3 product (MOD13A3). These include non-vegetated surfaces (NVS, NDVI < 0.2), partially vegetated surfaces (PVS, 0.2 ≤ NDVI ≤ 0.3), moderately vegetated surfaces (MVS, 0.3 < NDVI < 0.5) and densely vegetated surfaces (DVS, NDVI ≥ 0.5). Results show that the DT, DB, and DTB-collocated retrievals achieve a high correlation coefficient of ~ 0.90–0.97, 0.89–0.95, and 0.86–0.95, respectively, with AERONET AOD. The DT C6 and C6.1 collocated retrievals were comparable at XiangHe and Xinglong, whereas at Beijing, the percentage of collocated retrievals within the expected error (↔EE) increased from 21.4% to 35.5%, the root mean square error (RMSE) decreased from 0.37 to 0.24, and the relative percent mean error (RPME) decreased from 49% to 27%. These results suggest significant relative improvement in the DT C6.1 product. The percentage of DB-collocated AOD retrievals ↔EE was greater than 70% at Beijing and Xinglong, whereas less than 66% was observed at XiangHe. Similar to DT AOD, DTB AOD retrievals performed well at XiangHe and Xinglong compared with Beijing. Regionally, DB C6 and C6.1-collocated retrievals performed better than DT and DTB in terms of good quality retrievals and relatively small errors. For diverse vegetated surfaces, DT-collocated retrievals reported small errors and good quality retrievals only for NVS and DVS, whereas larger errors were reported for PVS. MVS. DB contains good quality AOD retrievals over PVS, MVS, and DVS compared with NVS. DTB C6.1 collocated retrievals were better than C6 over NVS, PVS, and DVS. C6.1 is substantially improved overall, compared with C6 at local and regional scales, and over diverse vegetated surfaces.

Highlights

  • Aerosol optical depth (AOD) is used for understanding the impact of aerosol on the Earth’s climate system [1], human health [2,3,4], atmospheric visibility [5], and air quality [6,7,8,9,10]

  • The performance of the Terra–MODIS DT, DB and DTB C6 and C6.1 AOD retrievals at km spatial resolution is evaluated on a local scale against three Aerosol Robotic Network (AERONET) stations located at urban (Beijing), suburban (XiangHe), and hilly and vegetated surfaces (Xinglong) for a period of years (2004–2014)

  • DT C6 AOD retrievals performed better over Xinglong and XiangHe, as 78.3% and 67R.e7m%oteoSfetnhs.e20re19tr, i1e1v, xalFsOwRePrEeEwR RitEhVinIE(W↔) the expected error (EE) compared with Beijing (↔EE = 21.4%), respectively.6 of 17

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Summary

Introduction

Aerosol optical depth (AOD) is used for understanding the impact of aerosol on the Earth’s climate system [1], human health [2,3,4], atmospheric visibility [5], and air quality [6,7,8,9,10]. To expand upon this framework, global AOD observations are required for better understanding of aerosol distributions and their impacts on regional and larger scales. The spatial distribution of AOD can be examined from passive radiometric satellite sensors, but the accuracy of AOD retrievals depends on instrument calibration, cloud screening fidelities, estimates of background surface reflectance, and available spectral aerosol models to support requisite radiance inversions [13]. AOD over land can be obtained from space-borne sensors such as the AVHRR (Advanced Very High Resolution Radiometer) [14,15], SeaWiFS (Sea-viewing Wide Field of view Sensor) [16], MISR (Multiangle Imaging Spectroradiometer) [17,18], TOMS (Total Ozone Mapping Spectroradiometer) [19], OMI (Ozone Monitoring Instrument) [20], the MERIS (Medium Resolution Imaging Spectroradiometer) [21], the VIIRS (Visible Infrared Imaging Radiometer Suite) [22,23], and the MODIS (MODerate resolution Imaging Spectroradiometer) [24,25]. Improvements to over-land retrieval algorithms as a whole, are important to increase data availability globally

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