Articles | Volume 13, issue 14
https://doi.org/10.5194/acp-13-6777-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/acp-13-6777-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
22 Jul 2013
Research article |
| 22 Jul 2013
Coherent uncertainty analysis of aerosol measurements from multiple satellite sensors
M. Petrenko
Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
C. Ichoku
NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
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- Gaussian Conditional Random Fields for Aggregation of Operational Aerosol Retrievals N. Djuric et al. https://doi.org/10.1109/LGRS.2014.2361154
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27 citations as recorded by crossref.
- Regional modeling of dust mass balance and radiative forcing over East Asia using WRF-Chem S. Chen et al. https://doi.org/10.1016/j.aeolia.2014.02.001
- Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product M. Garay et al. https://doi.org/10.5194/amt-13-593-2020
- Evaluation of the MODIS Collection 6.1 3 km aerosol optical depth product over China M. Zhang et al. https://doi.org/10.1016/j.atmosenv.2022.118970
- Impact of environmental attributes on the uncertainty in MAIAC/MODIS AOD retrievals: A comparative analysis S. Falah et al. https://doi.org/10.1016/j.atmosenv.2021.118659
- Aerosol retrieval algorithm based on adaptive land–atmospheric decoupling for polarized remote sensing over land surfaces H. Wang et al. https://doi.org/10.1016/j.jqsrt.2018.08.011
- Improving WRF-Chem aerosol optical depth prediction over India using artificial neural network A. Khan et al. https://doi.org/10.1007/s44292-025-00067-1
- Use of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter A. van Donkelaar et al. https://doi.org/10.1289/ehp.1408646
- Satellite remote sensing of aerosol optical depth: advances, challenges, and perspectives X. Wei et al. https://doi.org/10.1080/10643389.2019.1665944
- A global land aerosol fine-mode fraction dataset (2001–2020) retrieved from MODIS using hybrid physical and deep learning approaches X. Yan et al. https://doi.org/10.5194/essd-14-1193-2022
- Harnessing remote sensing to address critical science questions on ocean-atmosphere interactions G. Neukermans et al. https://doi.org/10.1525/elementa.331
- Fifteen-Year Global Time Series of Satellite-Derived Fine Particulate Matter B. Boys et al. https://doi.org/10.1021/es502113p
- Satellite‐retrieved direct radiative forcing of aerosols over North‐East India and adjoining areas: climatology and impact assessment J. Biswas et al. https://doi.org/10.1002/joc.5004
- Global evaluation of Fengyun-3 MERSI dark target aerosol retrievals over land L. Yang et al. https://doi.org/10.1080/17538947.2024.2344580
- Daily seamless reconstruction of aerosol optical depth product from a single satellite data source using the novel stream method X. Zhang et al. https://doi.org/10.1080/10095020.2025.2603729
- Multi-Time Scale Analysis of Regional Aerosol Optical Depth Changes in National-Level Urban Agglomerations in China Using Modis Collection 6.1 Datasets from 2001 to 2017 L. Zhang et al. https://doi.org/10.3390/rs11020201
- Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors A. van Donkelaar et al. https://doi.org/10.1021/acs.est.5b05833
- An AeroCom–AeroSat study: intercomparison of satellite AOD datasets for aerosol model evaluation N. Schutgens et al. https://doi.org/10.5194/acp-20-12431-2020
- Intercomparison and assessment of long-term (2004–2013) multiple satellite aerosol products over two contrasting sites in South Africa A. Adesina et al. https://doi.org/10.1016/j.jastp.2016.09.001
- Using Multi-Platform Satellite Observations to Study the Atmospheric Evolution of Brown Carbon in Siberian Biomass Burning Plumes I. Konovalov et al. https://doi.org/10.3390/rs14112625
- Satellite-based aerosol optical depth estimates over the continental U.S. during the 2020 wildfire season: Roles of smoke and land cover J. Daniels et al. https://doi.org/10.1016/j.scitotenv.2024.171122
- Gaussian Conditional Random Fields for Aggregation of Operational Aerosol Retrievals N. Djuric et al. https://doi.org/10.1109/LGRS.2014.2361154
- Calibration of the span of Himawari-8 AOD products in eastern China X. He et al. https://doi.org/10.1080/2150704X.2021.1937371
- Uncertainties Assessment of Regional Aerosol Classification Schemes in South America A. Scagliotti et al. https://doi.org/10.1007/s41748-024-00423-y
- Decadal-scale relationship between measurements of aerosols, land-use change, and fire over Southeast Asia J. Cohen et al. https://doi.org/10.5194/acp-17-721-2017
- Intercomparison of Multiple Satellite Aerosol Products against AERONET over the North China Plain X. Fan et al. https://doi.org/10.3390/atmos10090480
- SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe N. Ajtai et al. https://doi.org/10.3390/rs13050844
- Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution D. Goto et al. https://doi.org/10.5194/gmd-17-651-2024
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