Abstract
NASA deployed the GeoTASO airborne UV-Visible spectrometer in May-June 2017 to produce high resolution (approximately 250 × 250 m) gapless NO2 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 NO2 observations (r2=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 30×1015 molecules cm-2. Two publicly available OMI tropospheric NO2 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 NO2 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.
Highlights
Nitrogen oxides (NOx: NO + NO2) are primarily emitted via fossil fuel combustion, soil microbial processes, biomass burning, and lightning
Coincidences are identified as the median of all cloud-free GeoTASO tropospheric vertical columns (TropVCs) having pixel centers within a 750 m radius of a Pandora spectrometer site for each overpass and the Pandora column observed closest in time to the GeoTASO overpass
A Pandora TropVC is derived by subtracting the stratospheric vertical column calculated with the PRATMO climatology from the Pandora total column, following the same approach used with GeoTASO TropVCs
Summary
Nitrogen oxides (NOx: NO + NO2) are primarily emitted via fossil fuel combustion, soil microbial processes, biomass burning, and lightning. These geostationary measurements over industrialized regions of the Northern Hemisphere along with ongoing global daily sun-synchronous measurements will be important contributors to the goal of creating an atmospheric composition global observing network (IGACO, 2004; CEOS, 2011) To prepare for these planned geostationary air quality missions, NASA supported the development of airborne ultraviolet–visible (UV–VIS) mapping instruments (Geostationary Trace Gas and Aerosol Sensor Optimization: GeoTASO, and GEO-CAPE Airborne Simulator: GCAS) to help determine the satellite instrument requirements for measurements relevant to air quality and to facilitate retrieval algorithm development at fine spatial resolutions at all times of day (Leitch et al, 2014; Kowalewski and Janz, 2014; Nowlan et al, 2016, 2018; Lamsal et al, 2017). This work shows the sensitivity of satellite product validation strategies to spatial resolution and begins to demonstrate how the high-spatialresolution NO2 data retrieved from airborne mapping observations can be used with planned high-temporal-resolution ground-based column observations to evaluate the influence of spatiotemporal heterogeneity on satellite-based trace gas product validation
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