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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Mar 2019

Research article | 05 Mar 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm: version 4.1 description and validation

Sieglinde Callewaert1, Sophie Vandenbussche1, Nicolas Kumps1, Arve Kylling2, Xiaoxia Shang3, Mika Komppula3, Philippe Goloub4, and Martine De Mazière1 Sieglinde Callewaert et al.
  • 1Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Avenue Circulaire 3, 1180 Brussels, Belgium
  • 2Norwegian Institute for Air Research (NILU), P. O. Box 100, 2027 Kjeller, Norway
  • 3Finnish Meteorological Institute (FMI), P.O. Box 1627, 70211, Kuopio, Finland
  • 4Laboratoire d’Optique Amosphérique (LOA), Université des Sciences et Technologies de Lille, Villeneuve d’Ascq, France

Abstract. The Mineral Aerosol Profiling from Infrared Radiances (MAPIR) algorithm retrieves vertical dust concentration profiles from cloud-free IASI thermal infrared (TIR) radiances using the Rodgers Optimal Estimation Method (OEM). We describe the new version 4.1 and validation results. Main differences with respect to previous versions are the Levenberg-Marquardt modification of the OEM, the use of the logarithm of the concentration in the retrieval and the use of RTTOV for in-line radiative transfer calculations. The dust aerosol concentrations are retrieved in seven 1 km thick layers centered at 0.5 to 6.5 km. A global data set of the daily dust distribution was generated with MAPIR v4.1 covering September 2007 to June 2018, with further extensions planned every six months. The post-retrieval quality filters reject about 16 % of the retrievals, a huge improvement with respect to the previous versions where up to 40 % of the retrievals were of bad quality. The median difference between the observed and fitted spectra of the good quality retrievals is 0.32 K, with lower values over oceans. The information content of the retrieved profiles shows dependency on the total aerosol load due to the assumption of a log-normal state vector. The median degrees of freedom in dusty scenes (min 10 µm AOD of 0.5) is 1.4. A validation of the aerosol optical depth (AOD) obtained from the integrated MAPIR v4.1 profiles was performed against 72 AERONET stations. The MAPIR AOD correlates well with the ground-based data with a mean correlation coefficient of 0.66 and values as high as 0.88. Overall, there is a mean AOD (500 nm) negative bias of only 0.04 with respect to AERONET, which is an extremely good result. The previous versions of MAPIR were known to largely overestimate AOD (about 0.28 for v3). A second validation exercise was performed comparing the mean aerosol layer altitude from MAPIR with the mean dust altitude from CALIOP. A small underestimation was found, with a mean difference of about 350 m (standard deviation of about 1 km) with respect to the CALIOP cumulative extinction altitude, which is again considered very good as the vertical resolution of MAPIR is 1 km. In the comparisons against AERONET and CALIOP, a dependency of MAPIR on the quality of the temperature profiles used in the retrieval is observed. Finally, a qualitative comparison of dust aerosol concentration profiles was done against lidar measurements from two ground-based stations (M'Bour and Al Dhaid) and from the CATS instrument onboard the ISS. MAPIR v4.1 showed the ability to detect dust plumes at the same time and with a similar extent as the lidar instruments. This new MAPIR version shows a great improvement of the accuracy of the aerosol profile retrievals with respect to previous versions, especially so for the integrated AOD. It now offers a unique 3-D dust data set, which can be used to gain more insight in the transport and emission processes of mineral dust aerosols.

Sieglinde Callewaert et al.
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Sieglinde Callewaert et al.
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Publications Copernicus
Short summary
This article presents the updated MAPIR algorithm, which uses infrared satellite data to obtain the global 3-D distribution of mineral aerosols. A description of the method together with its technical improvements is given. Additionally, a 10-year data set was generated and used to validate this new algorithm against AERONET, CALIOP, CATS and two ground-based lidar stations. We have shown that the new MAPIR algorithm provides reliable aerosol optical depth, dust layer mean altitude and profiles.
This article presents the updated MAPIR algorithm, which uses infrared satellite data to obtain...