Submitted as: development and technical paper
16 May 2023
Submitted as: development and technical paper |  | 16 May 2023
Status: a revised version of this preprint is currently under review for the journal GMD.

Spherical Air Mass Factors in One and Two Dimensions with SASKTRAN 1.6.0

Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa

Abstract. Air quality measurements from geostationary orbit by the upcoming instrument TEMPO (Tropospheric Emissions: Monitoring of Pollution) will offer an unprecedented view of atmospheric composition over North America. Measurements over Canadian latitudes, however, offer unique challenges: TEMPO's lines of sight are shallower, the sun is lower, and snow cover is more common. All of these factors increase the impact of the sphericity and the horizontal inhomogeneity of the atmosphere on the accuracy of the air quality measurements. Air mass factors encapsulate the complex paths of the measured sunlight, but traditionally they ignore horizontal variability. For the high spatial resolution of modern instruments such as TEMPO, the error due to neglecting horizontal variability is magnified and needs to be characterized. Here we present developments to SASKTRAN, the radiative transfer framework developed at the University of Saskatchewan, to calculate air mass factors in a spherical atmosphere, with and without consideration of horizontal inhomogeneity. Recent upgrades to SASKTRAN include first order spherical corrections for the discrete ordinates method and the capacity to compute air mass factors with the Monte Carlo method. Together with finite difference air mass factors via the successive orders method, this creates a robust framework for computing air mass factors. One dimensional air mass factors from all three methods are compared in detail and are found to be in good agreement. Two-dimensional air mass factors are computed with the deterministic successive orders method, demonstrating an alternative for a calculation which would typically be done only with a non-deterministic Monte Carlo method. The two-dimensional air mass factors are used to analyze a simulated scene with TEMPO over the Canadian oil sands. The effect of a sharp horizontal feature in surface albedo and surface NO2 was quantified while varying the distance of the feature from the intended measurement location. Such a feature in the surface albedo or surface NO2 could induce errors on the order of 5 to 10 % at a distance of 50 km, and their combination could induce errors on the order of 10 % as far as 100 km away.

Lukas Fehr et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2023-75', Anonymous Referee #1, 16 Jun 2023
    • AC1: 'Reply on RC1', Lukas Fehr, 23 Aug 2023
  • RC2: 'Comment on gmd-2023-75', Anonymous Referee #2, 20 Jun 2023
    • AC2: 'Reply on RC2', Lukas Fehr, 23 Aug 2023

Lukas Fehr et al.

Model code and software

SASKTRAN Atmospheric Research Group, University of Saskatchewan

Lukas Fehr et al.


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Short summary
This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multi-dimensional capabilities which found that ignoring horizontal variation in the atmosphere, which is a common practice in the field, can introduce non-negligible errors where there is snow or high pollution.