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The Mainz Profile Algorithm (MAPA)

MPS-Authors
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Beirle,  Steffen
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Dörner,  Steffen
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons145432

Donner,  Sebastian
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons101213

Remmers,  Julia
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Wang,  Yang
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

/persons/resource/persons101349

Wagner,  Thomas
Satellite Remote Sensing, Max Planck Institute for Chemistry, Max Planck Society;

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Citation

Beirle, S., Dörner, S., Donner, S., Remmers, J., Wang, Y., & Wagner, T. (2019). The Mainz Profile Algorithm (MAPA). Atmospheric Measurement Techniques, 12(3), 1785-1806. doi:10.5194/amt-12-1785-2019.


Cite as: https://hdl.handle.net/21.11116/0000-0003-F368-6
Abstract
The Mainz profile algorithm MAPA derives vertical profiles of aerosol extinction and trace gas concentrations from MAX-DOAS measurements of slant column densities under multiple elevation angles. This manuscript presents (a) a detailed description of the MAPA algorithm v0.98, including the flagging scheme for the identification of questionable or dubious results, (b) results for the CINDI-2 campaign, and (c) sensitivity studies on the impact of a-priori assumptions such as flag thresholds.

MAPA is based on a profile parameterization combining box profiles, which also might be lifted, and exponential profiles. The profile parameters yielding best match to the MAX-DOAS observations are derived by a Monte Carlo approach, making MAPA much faster than previous parameter-based inversion schemes, and directly providing distributions of profile parameters. The AODs derived with MAPA for the CINDI-2 campaign show good agreement to AERONET if a scaling factor of 0.8 is applied for O4, and the respective NO2 and HCHO surface mixing ratios match those derived from coincident long-path DOAS measurements. MAPA results are robust to modifications of the a-priori MAPA settings within plausible limits.