Preprints
https://doi.org/10.5194/acp-2022-655
https://doi.org/10.5194/acp-2022-655
 
01 Nov 2022
01 Nov 2022
Status: this preprint is currently under review for the journal ACP.

Comparison of dust optical depth from multi-sensor products and the MONARCH dust reanalysis over Northern Africa, the Middle East and Europe

Michail Mytilinaios1, Sara Basart2, Sergio Ciamprone1, Juan Cuesta3, Claudio Dema1, Enza Di Tomaso2, Paola Formenti4, Antonis Gkikas5, Oriol Jorba2, Ralph Kahn6, Carlos Pérez García-Pando2,7, Serena Trippetta1, and Lucia Mona1 Michail Mytilinaios et al.
  • 1Consiglio Nazionale delle Ricerche-Istituto di Metodologie per l’Analisi Ambientale (CNR-IMAA), Tito Scalo, Italy
  • 2Barcelona Supercomputing Center (BSC), Barcelona, Spain
  • 3Univ Paris Est Creteil and Université Paris Cité, CNRS, LISA, F-94010 Créteil, France
  • 4Université Paris Cité and Univ Paris Est Creteil, CNRS, LISA, F-75013 Paris, France
  • 5National Observatory of Athens-Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (NOA-IAASARS), Penteli, Greece
  • 6Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 7Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain

Abstract. Aerosol reanalysis datasets are model-based observationally constrained continuous 3D aerosol fields with relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects and impacts upon socio–economic sectors, such as health. Here we compare and assess the recently published MONARCH high resolution regional desert dust reanalysis over Northern Africa, the Middle East and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS, MISR and IASI space-borne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows for at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products, are factors that bias the reanalysis assessment. We, therefore, also used ground-based DOD observations provided by 238 stations of the AERONET network located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking into consideration these results, the MONARCH reanalysis assessment showed that total and coarse DOD simulations are consistent with satellite and ground-based data, capturing qualitatively the major dust sources in the area as well as the dust transport patterns. Moreover, the reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases were found over the Sahara Desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low as the low relative bias in the Sahara Desert (< 0.5) and over the adjacent maritime regions (< 1), certifies. Similarly, over areas with intense dust activity the linear correlation coefficient between the reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean and the Arabian Sea, and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions where large amounts of observations are available, allowing for robust model assessment.

Michail Mytilinaios et al.

Status: open (until 13 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-655', Anonymous Referee #2, 18 Nov 2022 reply

Michail Mytilinaios et al.

Michail Mytilinaios et al.

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Short summary
MONARCH dust reanalysis provides a high-resolution 3D reconstruction of past dust conditions, allowing a better quantification of dust impacts upon climate, society and economy. Here we assess the performance of the reanalysis in reproducing dust optical depth using dust products retrieved from satellite and ground-based observations. The comparison shows that the reanalysis reproduces very well the spatial distribution and the seasonal variability of atmospheric dust.
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