Articles | Volume 14, issue 6
https://doi.org/10.5194/amt-14-4639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-4639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Jun 2021
Research article |
| 23 Jun 2021
| 23 Jun 2021
Assessing sub-grid variability within satellite pixels over urban regions using airborne mapping spectrometer measurements
Advanced Study Program, National Center for Atmospheric Research, Boulder, CO 80301, USA
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
David P. Edwards
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Louisa K. Emmons
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Helen M. Worden
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Laura M. Judd
NASA Langley Research Center, Hampton, VA 23681, USA
Lok N. Lamsal
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Universities Space Research Association, Columbia, MD 21046, USA
Jassim A. Al-Saadi
NASA Langley Research Center, Hampton, VA 23681, USA
Scott J. Janz
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
James H. Crawford
NASA Langley Research Center, Hampton, VA 23681, USA
Merritt N. Deeter
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Gabriele Pfister
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Rebecca R. Buchholz
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Benjamin Gaubert
Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO 80301, USA
Caroline R. Nowlan
Harvard–Smithsonian Center for Astrophysics, Cambridge, MA 02138, USA
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Cited
7 citations as recorded by crossref.
- Quantifying the diurnal variation in atmospheric NO2 from Geostationary Environment Monitoring Spectrometer (GEMS) observations D. Edwards et al. 10.5194/acp-24-8943-2024
- Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation A. Mynard et al. 10.5194/amt-16-4229-2023
- Dealing with spatial heterogeneity in pointwise-to-gridded- data comparisons A. Souri et al. 10.5194/amt-15-41-2022
- Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources J. Park et al. 10.5194/amt-17-197-2024
- Facing & mitigating common challenges when working with real-world data: The Data Learning Paradigm J. Lever et al. 10.1016/j.jocs.2024.102523
- Characterization of errors in satellite-based HCHO ∕ NO2 tropospheric column ratios with respect to chemistry, column-to-PBL translation, spatial representation, and retrieval uncertainties A. Souri et al. 10.5194/acp-23-1963-2023
- Capturing High‐Resolution Air Pollution Features Using the Multi‐Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) Global Modeling System W. Tang et al. 10.1029/2022JD038345
7 citations as recorded by crossref.
- Quantifying the diurnal variation in atmospheric NO2 from Geostationary Environment Monitoring Spectrometer (GEMS) observations D. Edwards et al. 10.5194/acp-24-8943-2024
- Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation A. Mynard et al. 10.5194/amt-16-4229-2023
- Dealing with spatial heterogeneity in pointwise-to-gridded- data comparisons A. Souri et al. 10.5194/amt-15-41-2022
- Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources J. Park et al. 10.5194/amt-17-197-2024
- Facing & mitigating common challenges when working with real-world data: The Data Learning Paradigm J. Lever et al. 10.1016/j.jocs.2024.102523
- Characterization of errors in satellite-based HCHO ∕ NO2 tropospheric column ratios with respect to chemistry, column-to-PBL translation, spatial representation, and retrieval uncertainties A. Souri et al. 10.5194/acp-23-1963-2023
- Capturing High‐Resolution Air Pollution Features Using the Multi‐Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) Global Modeling System W. Tang et al. 10.1029/2022JD038345
Latest update: 23 Apr 2025
Short summary
We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability within satellite pixels over urban regions. The sub-grid variability within satellite pixels increases with increasing satellite pixel sizes. Temporal variability within satellite pixels decreases with increasing satellite pixel sizes. This work is particularly relevant and useful for future satellite design, satellite data interpretation, and point-grid data comparisons.
We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability...
