Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements
Abstract
:1. Introduction
- (1)
- Polar orbiters acquire images at a fixed time of a day (for example, the local overpass times for MODIS Aqua and Terra are 1:30 pm and 10:30 am, respectively), but atmospheric aerosol loading and its associated properties could vary substantially over a very short time scale due to various emission sources, small scale meteorology effects as well as complex aerosol compositions and atmospheric processing [15,52]. Therefore, the satellite AOD retrievals and associated products may not well represent the daily aerosol conditions in theory. To address this issue, Kaufman [53] used AERONET observations to compare the daily means and mean values averaged over the MODIS Aqua/Terra time windows (i.e., synthetic MODIS data using AERONET), and they concluded that the AOD measurements at the satellite overpass time could represent daily AOD averages within an error level of 5%. While this former effort was conducted before the launch of the two MODIS instruments when real satellite data were not available, the results were only based on simulations with AERONET data. As such, the expected errors (i.e., 5%) could be different from the real satellite observations since the uncertainties in the satellite AOD retrieval algorithms were not considered. Additionally, data gaps may also exist in the AERONET AOD measurement within a day due to unfavorable weather conditions, instrument malfunctions, and many other factors [51]. However, the associated uncertainties to the daily mean AERONET AODs were not quantified [53].
- (2)
- Optical remote sensing suffers from cloud contamination, which results in a rather limited number of available high-quality data and remarkable observation gaps in the dataset. Indeed, a global cloud cover statistic using MODIS cloud mask products revealed that the global mean cloud coverage was 67% [54] and could vary substantially over different seasons and locations, which could significantly reduce the number of valid AOD retrievals. Moreover, this problem could be further exacerbated due to the associated issues of sub-pixel clouds, thin clouds, and their adjacency effects [55] as well as biases in retrievals [50]. Additionally, high AODs (e.g., smoke plumes, dust storms, biomass burning days) scenarios are often misinterpreted as clouds, where the signals tend to be saturated, leading to upper limitation of satellite retrievals [56,57]. This kind of misclassification could not only decrease the frequency of valid instantaneous remote sensed retrievals, especially for large values, but also further underestimate long-term satellite composites. That is, often only a few days of daily satellite AOD images with relatively lower observations were used to compose monthly (or other temporal binning) products. It remains unclear whether and to what extent these composed monthly, seasonal, or annual aerosol products could represent actual global or regional levels of aerosol concentrations. Although a recent attempt by Fan et al. (2018) was performed to examine whether the AOD trends of 53 sites detected by monthly AERONET observations could be reproduced through MODIS AOD data, the fundamental question of how satellite observation gaps could impact the reliability of monthly satellite products has never been analyzed. Similarly, Yoon et al. (2011) realized the uncertainty caused by data gaps and discarded monthly AOD data when less than five observations per month were available. However, how the uncertainties could be impacted by the changing numbers of valid data within a month has never been investigated.
- (1)
- Quantify the uncertainty levels of satellite AOD products in various temporal domains based on global long-term concurrent measurements between the MODIS and AERONET observations; and
- (2)
- Understand the potential factors that could affect the temporal representativeness of the satellite AOD products, and discuss the future efforts that could be used to improve the validity of AOD temporal binning products and their derived long-term trends.
2. Materials and Methods
2.1. MODIS AOD Data
2.2. AERONET AOD Data
2.3. Determination of the Satellite and AERONET Match-Ups
2.4. Statistical Measures for the Representativeness Analysis
3. Results
3.1. Overall Global Statistics
3.2. Site-Specific Assessments
3.3. Global Distributions of the POU100
4. Discussion
4.1. Factors Influencing the Representativeness of Satellite AOD Products
4.2. Implications and Future Efforts
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Notations
AERONET | Aerosol Robotic Network |
MODIS | Moderate Resolution Imaging Spectroradiometer |
AOD | Aerosol optical depth |
PHOTONS | PHOtométrie pour le Traitement Opérationnel de Normalisation Satellitaire |
DB | Deep Blue |
DT | Dark Target |
AVHRR | Advanced Very High Resolution Radiometer |
TOMS | Total Ozone Mapping Spectrometer |
SeaWiFS | Sea-Viewing Wide Field-of-View Sensor |
MISR | Multiangle Imaging Spectroradiometer |
VIIRS | Visible Infrared Imaging Radiometer Suite |
GOCI | Geostationary Ocean Color Imager |
NASA | U.S. National Aeronautics and Space Administration |
GSFC | Goddard Space Flight Center |
NDVI | Normalized Difference Vegetation Index |
α | Angström exponent |
N_SAOD | Number of valid satellite AOD data |
RMB | relative mean bias |
EE | error envelope |
POU100 | Probabilities of satellite-derived AODs with uncertainties larger than 100% |
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Tong, Y.; Feng, L.; Sun, K.; Tang, J. Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. Remote Sens. 2020, 12, 2330. https://doi.org/10.3390/rs12142330
Tong Y, Feng L, Sun K, Tang J. Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. Remote Sensing. 2020; 12(14):2330. https://doi.org/10.3390/rs12142330
Chicago/Turabian StyleTong, Yan, Lian Feng, Kun Sun, and Jing Tang. 2020. "Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements" Remote Sensing 12, no. 14: 2330. https://doi.org/10.3390/rs12142330
APA StyleTong, Y., Feng, L., Sun, K., & Tang, J. (2020). Assessment of the Representativeness of MODIS Aerosol Optical Depth Products at Different Temporal Scales Using Global AERONET Measurements. Remote Sensing, 12(14), 2330. https://doi.org/10.3390/rs12142330