Articles | Volume 18, issue 5
https://doi.org/10.5194/tc-18-2257-2024
https://doi.org/10.5194/tc-18-2257-2024
Research article
 | 
07 May 2024
Research article |  | 07 May 2024

Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign

Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist

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Cited articles

Abrams, M.: The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA's Terra platform, Int. J. Remote Sens., 21, 847–859, https://doi.org/10.1080/014311600210326, 2000. 
Balick, L. K., Jerrell, R. B., Smith, J. A., and Goltz, S. M.: Directional satellite thermal IR measurements and modeling of a forest in winter and their relationship to air temperature, in: Remote Sensing for Agriculture, Ecosystems, and Hydrology III, Proc. SPIE 4542, Remote Sensing for Agriculture, Ecosystems, and Hydrology III, https://doi.org/10.1117/12.454212, 162–169, https://doi.org/10.1117/12.454212, 2002. 
Berk, A., Conforti, P., Kennett, R., Perkins, T., Hawes, F., and van den Bosch, J.: MODTRAN6: a major upgrade of the MODTRAN radiative transfer code, in: Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, edited by: Velez-Reyes, M. and Kruse, F. A., Proc. SPIE, 9088, 1–4, 90880H-90880H-7, 2014. 
Bréon, F.-M., Maignan, F., Leroy, M., and Grant, I.: Analysis of hot spot directional signatures measured from space, J. Geophys. Res.-Atmos., 107, AAC 1-1–AAC 1-15, https://doi.org/10.1029/2001JD001094, 2002. 
Colbeck, S. C.: Air Movement in Snow Due to Windpumping, J. Glaciol., 35, 209–213, https://doi.org/10.3189/S0022143000004524, 1989. 
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Short summary
We compared infrared images taken by GOES-R satellites of an area with snow and forests against surface temperature measurements taken on the ground, from an aircraft, and by another satellite. We found that GOES-R measured warmer temperatures than the other measurements, especially in areas with more forest and when the Sun was behind the satellite. From this work, we learned that the position of the Sun and surface features such as trees that can cast shadows impact GOES-R infrared images.
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