Evaluation of Terra Modis C6 and C6.1 Aerosol Products Against Beijing, Xianghe, and Xinglong Aeronet Sites in China During 2004 2014

Abstract

In this study, Terra-MODIS (Moderate Resolution Imaging Spectroradiometer) Collections 6 and 6.1 (C6 and 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.

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Document Details

Document Type
Technical Report
Publication Date
Feb 27, 2019
Accession Number
AD1096679

Entities

People

  • 10) Lollo (9 Simone
  • 3) Nazeer (2 Majid
  • James R Campbell (8)
  • Janet Nichol (4)
  • Lunche Wang (5)
  • Max P Bleiweiss (6)
  • Muhammad Bilal (1)
  • Xiaojing Shen (7)
  • Zhongfeng Qiu (1)

Organizations

  • United States Naval Research Laboratory

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  • Autonomy
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Air Pollution
  • Atmospheric Sciences
  • Central Europe
  • Cirrus Clouds
  • Climate Change
  • Control Systems
  • Data Sets
  • Dust Storms
  • Earth Sciences
  • Geography
  • High Resolution
  • Information Science
  • Measurement
  • Remote Sensing
  • Test And Evaluation
  • Urban Areas

Fields of Study

  • Environmental science

Readers

  • Aerospace Engineering
  • Atmospheric Remote Sensing.

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  • AI & ML
  • AI & ML - Bayesian Inference
  • Autonomy