Evaluating the impact of spatial resolution on tropospheric NO 2 column comparisons within urban areas using high-resolution airborne data.

Autor: Judd LM; NASA Langley Research Center, Hampton, VA, 23681, United States.; NASA Postdoctoral Program, Hampton, VA, 23681, United States., Al-Saadi JA; NASA Langley Research Center, Hampton, VA, 23681, United States., Janz SJ; NASA Goddard Space Flight Center, Greenbelt, MD, 20771, United States., Kowalewski MG; NASA Goddard Space Flight Center, Greenbelt, MD, 20771, United States.; Universities Space Research Association, Columbia, MD, 21046, United States., Pierce RB; University of Wisconsin-Madison Space Science and Engineering Center, Madison, WI, 53706, United States., Szykman JJ; United States Environmental Protection Agency Office of Research and Development, Triangle Research Park, NC, 27709, United States., Valin LC; United States Environmental Protection Agency Office of Research and Development, Triangle Research Park, NC, 27709, United States., Swap R; NASA Goddard Space Flight Center, Greenbelt, MD, 20771, United States., Cede A; LuftBlick, Kreith, Austria., Mueller M; LuftBlick, Kreith, Austria.; Department of Atmospheric and Cryospheric Science, University of Innsbruck, Innsbruck, Austria., Tiefengraber M; LuftBlick, Kreith, Austria.; Department of Atmospheric and Cryospheric Science, University of Innsbruck, Innsbruck, Austria., Abuhassan N; NASA Goddard Space Flight Center, Greenbelt, MD, 20771, United States.; Joint Center for Earth Systems Technology, University of Maryland-Baltimore County, Baltimore, MD, 21228, United States., Williams D; United States Environmental Protection Agency Office of Research and Development, Triangle Research Park, NC, 27709, United States.
Jazyk: angličtina
Zdroj: Atmospheric measurement techniques [Atmos Meas Tech] 2019 Nov; Vol. 12 (11), pp. 6091-6111. Date of Electronic Publication: 2019 Nov 22.
DOI: 10.5194/amt-12-6091-2019
Abstrakt: NASA deployed the GeoTASO airborne UV-Visible spectrometer in May-June 2017 to produce high resolution (approximately 250 × 250 m) gapless NO 2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO 2 observations (r 2 =0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO, TROPOMI, and OMI, the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale=0.88; TROPOMI scale=0.77; OMI scale=0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×10 15 molecules cm -2 . Two publicly available OMI tropospheric NO 2 retrievals are both found to be biased low with respect to these Pandora observations. However, the agreement improves when higher resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 Standard Product slope = 0.18 and Berkeley High Resolution Product slope=0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high spatial resolution NO 2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high temporal resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.
Databáze: MEDLINE
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