Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors
"> Figure 1
<p>Examples of exponentially decreasing aerosol profiles for different scale heights, varying from 1.0 to 3.0 km with an interval of 0.5 km. Only profiles below 5 km are shown in this figure.</p> "> Figure 2
<p>Spectral dependence of single scattering albedo (<b>a</b>) and asymmetry factor (<b>b</b>) for three aerosol models embedded in the 6SV radiative transfer model.</p> "> Figure 3
<p>(<b>a</b>) The relative errors of AOD (Aerosol Optical Depth) 550nm with the errors of scale height for three different aerosol models. (<b>b</b>) The change in AOD relative error with AOD value. The true scale height is assumed to be 2 km.</p> "> Figure 4
<p>The relative errors of AOD 550 nm with the errors of scale height under four surface albedos (0.02, 0.05, 0.1, 0.2). The fine absorbing aerosol model is used in this experiment.</p> "> Figure 5
<p>Example of observed aerosol extinction profiles by MPL(micro-pulse lidar) at Beijing-PKU site. Only profiles below 5 km are shown in this figure.</p> "> Figure 6
<p>Two types of aerosol vertical distributions: exponential decreasing profile starting from the surface (blue line), and with a 1-km boundary layer near the surface (red line).</p> "> Figure 7
<p>(<b>a</b>) The relative errors of AOD 550 nm by ignoring the boundary layer structure, under four surface albedos (0.02, 0.05, 0.1, 0.2). (<b>b</b>) The change in AOD relative errors with the AOD value. The fine absorbing aerosol model is used in this experiment. (<b>c</b>) The expanded part of (<b>b</b>).</p> "> Figure 8
<p>Examples of aerosol layering from CALIPSO aerosol subtype products. (ND: not defined; CM: clean marine; D: dust; PC: polluted continental; CC: clean continental; PD: polluted dust; S: smoke; O: other). The red boxes indicate smoke above pollution aerosols.</p> "> Figure 9
<p>Assumed aerosol profile structures for the layered structure experiment, with two different aerosol types (sulfate and soot) located at different altitudes.</p> "> Figure 10
<p>Spectral dependence of single scattering albedo (<b>a</b>) and asymmetry factor (<b>b</b>) for soot and sulfate (50% humidity) obtained from the OPAC database.</p> "> Figure 11
<p>Relative errors of AOD 550 nm by ignoring the different vertical distribution of absorbing and scattering aerosols. (Case 1: soot lying between 0–1.0 km, sulfate lying between 3.0–4.0 km; Case 2: the reversed structure with case; Case 3: a mixed exponential profile).</p> "> Figure 12
<p>Spectral dependence of single scattering albedo (<b>a</b>) and asymmetry factor (<b>b</b>) for reconstructed seasonal aerosol models at the Beijing-PKU site.</p> "> Figure 13
<p>Scatterplots of AOD retrieved using the default profile (exponential decaying with scale height = 2 km) and the MPL-retrieved aerosol extinction profile.</p> "> Figure 14
<p>Comparison of the mean bias (upper panel), RMSE (middle panel) and the correlation (bottom panel) between the retrieval using the exponential profile (blue) and the MPL-retrieved aerosol profile (orange) for the four seasons.</p> "> Figure 15
<p>Histograms of the SSA(single scattering albedo) values at the Beijing-PKU site during 2016–2019.</p> "> Figure 16
<p>Scatterplots of AOD retrieved using the default profile (exponential decaying with scale height = 2 km) and the CALIPSO aerosol extinction profile.</p> "> Figure 17
<p>Comparison of the mean bias (upper panel), RMSE (middle panel) and the correlation (bottom panel) between the retrieval using the exponential profile (blue) and the CALIPSO aerosol profile (orange) for the four seasons.</p> "> Figure 18
<p>Geographical boundaries of the seven regions defined for the aerosol parameter analysis. AERONET sites are indicated by the red dots.</p> "> Figure 19
<p>Probability density function of AERONET AOD for the four seasons over the seven regions.</p> "> Figure 20
<p>Probability density function of AERONET SSA values for the four seasons over the seven regions.</p> ">
Abstract
:1. Introduction
2. Description of Radiative Transfer Models
2.1. 6SV Radiative Transfer Model
2.2. MODTRAN Radiative Transfer Model
3. Datasets Used for the Retrieval Experiment Using Observed Profiles
3.1. VIIRS Level 1B Data
3.2. Micro-Pulse Lidar Aerosol Extinction Profiles
3.3. CALIPSO Data
3.4. AERONET Data
4. Experiments and Results
4.1. Impact of Aerosol Scale Height Assuming Exponential Profile
4.2. Impact of the Planetary Boundary Layer
4.3. Impact of Layered Aerosol Vertical Structure
4.4. AOD Retrieval Using Observed Aerosol Vertical Profiles
5. Discussion
6. Conclusions
- The retrieved AOD is the most sensitive to aerosol vertical distribution for fine absorbing aerosols. The relative errors can exceed 30% for a −1-km scale height uncertainty when AOD = 0.2.
- The surface albedo has a large impact on the ΔAOD–Δscale height relationship. At a lower surface albedo, the AOD error varies positively with scale height error, but it shifts to negative relationships when surface albedo increases to 0.1. The AOD error becomes less sensitive to scale height error when surface albedo further increases.
- Neglecting the boundary layer will lead to an AOD error up to ~10% for absorbing aerosols at AOD = 0.2.
- For layered aerosol structure, failing to consider different aerosol types at different altitudes will lead to considerably large AOD errors. At 0.5 AOD, sulfate (scattering) lying below soot (absorbing) can produce positive errors as large as 28%, and the reverse case produces negative errors of ~18%.
- Replacing the exponential profile with the MPL derived aerosol extinction profiles can largely improve the accuracy of satellite retrieved AOD, especially during the winter season when aerosol absorption is strong. The overall bias can be reduced from 0.15 to 0.03 and the correlation is increased from 0.63 to 0.83. Replacing with spatial-average CALIPSO profiles also improves the AOD retrievals significantly in the winter season.
- Based on the distribution of aerosol optical properties, satellite AOD retrieval accuracy is more prone to errors in aerosol vertical assumption for Asia in winter, and South Africa and South America in the fall.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Real Profiles | Assumed Profiles | |
---|---|---|
Mean Bias | 0.03 | 0.15 |
RMSE | 0.002 | 0.015 |
Correlation | 0.83 | 0.63 |
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Li, C.; Li, J.; Dubovik, O.; Zeng, Z.-C.; Yung, Y.L. Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors. Remote Sens. 2020, 12, 1524. https://doi.org/10.3390/rs12091524
Li C, Li J, Dubovik O, Zeng Z-C, Yung YL. Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors. Remote Sensing. 2020; 12(9):1524. https://doi.org/10.3390/rs12091524
Chicago/Turabian StyleLi, Chong, Jing Li, Oleg Dubovik, Zhao-Cheng Zeng, and Yuk L. Yung. 2020. "Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors" Remote Sensing 12, no. 9: 1524. https://doi.org/10.3390/rs12091524