Preprints
https://doi.org/10.5194/amt-2021-373
https://doi.org/10.5194/amt-2021-373

  15 Dec 2021

15 Dec 2021

Review status: this preprint is currently under review for the journal AMT.

Satellite data validation: a parametrization of the natural variability of atmospheric mixing ratios

Alexandra Laeng1, Thomas von Clarmann1, Quentin Errera2, Udo Grabowski1, and Shawn Honomichl3 Alexandra Laeng et al.
  • 1Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research, Karlsruhe, Germany
  • 2Royal Belgian Institute of Space Aeronomy, Brussels, Belgium
  • 3UCAR/NCAR/ACOM, Boulder, Colorado, USA

Abstract. High-resolution model data are used to estimate typical variabilities of mixing ratios of trace species as a function of spatial and temporal distance. These estimates can be used to explain that part of the differences between observations made with different observing systems that are due to less than perfect collocation of the measurements. The variability values are described by a two-parameter regression function. A reparametrization of the variabilities values as function of latitudinal graidents is proposed, and season-independence of linear approximation of such function is demonstrated.

Alexandra Laeng et al.

Status: open (until 19 Jan 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-373', Anonymous Referee #1, 12 Jan 2022 reply

Alexandra Laeng et al.

Alexandra Laeng et al.

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Short summary
In validation exercice, a universal excuse used to explain the residual discrepancy between the data is the natural atmospheric variability due to the imperfect collocations. This work is the first attempt to quantify this atmospheric variability for big sample of atmospheric constituents and provide the user with a tool to substract from the residual variability the part coming from natural atmospheric variability.