Articles | Volume 22, issue 1
https://doi.org/10.5194/acp-22-535-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-22-535-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Assimilating spaceborne lidar dust extinction can improve dust forecasts
Jerónimo Escribano
CORRESPONDING AUTHOR
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Enza Di Tomaso
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Oriol Jorba
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Martina Klose
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-TRO), Department Troposphere Research, Karlsruhe, Germany
Maria Gonçalves Ageitos
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Department of Project and Construction Engineering, Universitat Politècnica de Catalunya – BarcelonaTech (UPC), Barcelona, Spain
Francesca Macchia
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Vassilis Amiridis
National Observatory of Athens (NOA), Athens, Greece
Holger Baars
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Eleni Marinou
National Observatory of Athens (NOA), Athens, Greece
Deutsches Zentrum für Luft und Raumfahrt (DLR), Institut für Physik der Atmosphäre (IPA), Oberpfaffenhofen, Germany
Emmanouil Proestakis
National Observatory of Athens (NOA), Athens, Greece
Claudia Urbanneck
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Dietrich Althausen
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Johannes Bühl
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Rodanthi-Elisavet Mamouri
Department of Civil Engineering and Geomatics, Cyprus University of Technology of Technology, Limassol, Cyprus
ERATOSTHENES Centre of Excellence, Limassol, Cyprus
Carlos Pérez García-Pando
Barcelona Supercomputing Center (BSC), Barcelona, Spain
ICREA, Catalan Institution for Research and Advanced Studies, Barcelona, Spain
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Cited
4 citations as recorded by crossref.
- Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts M. Gonçalves Ageitos et al. 10.5194/acp-23-8623-2023
- Modeling coarse and giant desert dust particles E. Drakaki et al. 10.5194/acp-22-12727-2022
- Comparison of dust optical depth from multi-sensor products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) dust reanalysis over North Africa, the Middle East, and Europe M. Mytilinaios et al. 10.5194/acp-23-5487-2023
- Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) Version 2.0 M. Klose et al. 10.5194/gmd-14-6403-2021
3 citations as recorded by crossref.
- Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts M. Gonçalves Ageitos et al. 10.5194/acp-23-8623-2023
- Modeling coarse and giant desert dust particles E. Drakaki et al. 10.5194/acp-22-12727-2022
- Comparison of dust optical depth from multi-sensor products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) dust reanalysis over North Africa, the Middle East, and Europe M. Mytilinaios et al. 10.5194/acp-23-5487-2023
1 citations as recorded by crossref.
Latest update: 21 Sep 2023
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.
We explore the benefits and consistency in adding lidar dust observations in a dust optical...
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