Articles | Volume 22, issue 1
https://doi.org/10.5194/acp-22-535-2022
https://doi.org/10.5194/acp-22-535-2022
Research article
 | 
14 Jan 2022
Research article |  | 14 Jan 2022

Assimilating spaceborne lidar dust extinction can improve dust forecasts

Jerónimo Escribano, Enza Di Tomaso, Oriol Jorba, Martina Klose, Maria Gonçalves Ageitos, Francesca Macchia, Vassilis Amiridis, Holger Baars, Eleni Marinou, Emmanouil Proestakis, Claudia Urbanneck, Dietrich Althausen, Johannes Bühl, Rodanthi-Elisavet Mamouri, and Carlos Pérez García-Pando

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Cited articles

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Amiridis, V., Wandinger, U., Marinou, E., Giannakaki, E., Tsekeri, A., Basart, S., Kazadzis, S., Gkikas, A., Taylor, M., Baldasano, J., and Ansmann, A.: Optimizing CALIPSO Saharan dust retrievals, Atmos. Chem. Phys., 13, 12089–12106, https://doi.org/10.5194/acp-13-12089-2013, 2013. a, b, c
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Badia, A., Jorba, O., Voulgarakis, A., Dabdub, D., Pérez García-Pando, C., Hilboll, A., Gonçalves, M., and Janjic, Z.: Description and evaluation of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH) version 1.0: gas-phase chemistry at global scale, Geosci. Model Dev., 10, 609–638, https://doi.org/10.5194/gmd-10-609-2017, 2017. a
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Short summary
We explore the benefits and consistency in adding lidar dust observations in a dust optical depth assimilation. We show that adding lidar data to a dust optical depth assimilation has valuable benefits and the dust analysis improves. We discuss the impact of the narrow satellite footprint of the lidar dust observations on the assimilation.
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