Evaluation and analysis of long-term MODIS MAIAC aerosol products in China
- Ge Huang 1, Xin Su 2, Lunche Wang 3, Yi Wang 1, Mengdan Cao 1, Lin Wang 4, Xiaoyu Ma 5, Yueji Zhao 6, Leiku Yang 7
- Ge Huang 1, Xin Su 2, Lunche Wang 3
- 1Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China.
- 2School of Future Technology (SFT), China University of Geosciences, Wuhan 430074, China.
- 3Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China; School of Future Technology (SFT), China University of Geosciences, Wuhan 430074, China; Hubei Luojia Laboratory, Wuhan 430079, China.
- 4Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
- 5Department of Materials and Food, University of Electronic Science and Technology of China Zhongshan Institute, Zhongshan 528402, China.
- 6Hulun Buir Meteorological Bureau, Hulun Buir, Inner Mongolia 021008, China.
- 7School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China.
- 0Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430078, China.
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View abstract on PubMed
Summary
This summary is machine-generated.NASA
Area Of Science
- Atmospheric Science
- Remote Sensing
- Environmental Monitoring
Background
- NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) provides aerosol optical depth (AOD) data.
- The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm processes MODIS data.
- New versions, Collection 6 (C6) and Collection 6.1 (C6.1), offer AOD at 1 km resolution.
Purpose Of The Study
- Validate and compare MAIAC C6 and C6.1 AOD products against AERONET observations.
- Assess accuracy and stability of the updated products.
- Analyze spatiotemporal AOD characteristics in China.
Main Methods
- Validation using AERONET ground-based AOD measurements.
- Comparison of C6 and C6.1 MAIAC AOD products.
- Statistical analysis of accuracy (R, BIAS, EE) and stability metrics.
- Spatio-temporal analysis across different regions in China.
Main Results
- Overall MAIAC AOD accuracy is good (R > 0.9, BIAS < 0.015, EE > 68%).
- Collection 6.1 (C6.1) shows decreased accuracy compared to C6, particularly in South China.
- C6.1 improves retrieval frequency and AOD discontinuity but introduces artifacts in the Tibetan Plateau.
- Product stability did not significantly improve and does not meet GCOS goals in China.
Conclusions
- While C6.1 offers some improvements, its overall accuracy decrease necessitates algorithm refinement.
- Regional variations in accuracy highlight the need for tailored validation.
- Further work is needed to enhance MAIAC product stability for long-term climate monitoring.
- The study provides insights for future MAIAC algorithm development and stable aerosol record creation.
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