Preprints
https://doi.org/10.5194/amt-2022-336
https://doi.org/10.5194/amt-2022-336
31 Jan 2023
 | 31 Jan 2023
Status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Validation of NH3 observations from AIRS and CrIS against aircraft measurements from DISCOVER-AQ and a surface network in the Magic Valley

Karen Elena Cady-Pereira, Xuehui Guo, Rui Wang, April Leytem, Chase Calkins, Elizabeth Berry, Kang Sun, Markus Müller, Armin Wisthaler, Vivienne H. Payne, Mark W. Shephard, Mark A. Zondlo, and Valentin H. Kantchev

Abstract. Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large scale, intensive agricultural activities, which are often accompanied by greater use of fertilizers and concentrated animal feedlots. Ammonia is highly reactive, and thus highly variable and difficult to measure. Satellite based instruments, such as the Atmospheric Infrared Sounder (AIRS), and the Cross-Track Infrared Sounder (CrIS) sensors, have been shown to provide much greater temporal and spatial coverage of ammonia distribution and variability than is possible with in situ networks or aircraft campaigns, but the validation of these data is limited.

Here we evaluate ammonia retrievals from AIRS and CrIS against ammonia measurements from aircraft in the California Central Valley and in the Colorado Front Range. The satellite datasets were small and in California were obtained under difficult conditions. We show that the surface values of the retrieved profiles are biased very low in California and slightly high in Colorado, and that the bias appears to be primarily due to smoothing error. We also compare three years of CrIS ammonia against an in situ network in the Magic Valley in Idaho We show that CrIS ammonia captures both the seasonal signal and the spatial variability in the Magic Valley, though it is biased low here also. In summary, analysis adds to the validation record but also points to the need for more validation under different conditions.

Karen Elena Cady-Pereira et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-336', Anonymous Referee #1, 27 Apr 2023
    • AC1: 'Reply on RC1', Karen Cady-Pereira, 27 Apr 2023
    • AC2: 'Reply on RC1', Karen Cady-Pereira, 02 Aug 2023
  • RC2: 'Comment on amt-2022-336', Anonymous Referee #2, 26 May 2023
    • AC3: 'Reply on RC2', Karen Cady-Pereira, 02 Aug 2023

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-336', Anonymous Referee #1, 27 Apr 2023
    • AC1: 'Reply on RC1', Karen Cady-Pereira, 27 Apr 2023
    • AC2: 'Reply on RC1', Karen Cady-Pereira, 02 Aug 2023
  • RC2: 'Comment on amt-2022-336', Anonymous Referee #2, 26 May 2023
    • AC3: 'Reply on RC2', Karen Cady-Pereira, 02 Aug 2023

Karen Elena Cady-Pereira et al.

Karen Elena Cady-Pereira et al.

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Short summary
Ammonia is a significant precursor of PM2.5 particles and thus contributes to poor air quality in many regions. Furthermore, ammonia concentrations are rising due to the increase of large scale, intensive agricultural activities. Here we evaluate satellite measurements of ammonia against aircraft and surface network data, and show that there are significant differences, which can be explained mainly by different vertical and horizontal sampling scales.