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.
Research article
| 
14 Jan 2022
Research article |
| 14 Jan 2022
| 14 Jan 2022
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
10 citations as recorded by crossref.
- Optimizing the Numerical Simulation of the Dust Event of March 2021: Integrating Aerosol Observations through Multi-Scale 3D Variational Assimilation in the WRF-Chem Model S. Mei et al. https://doi.org/10.3390/rs16111852
- Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts M. Gonçalves Ageitos et al. https://doi.org/10.5194/acp-23-8623-2023
- The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2 M. Pang et al. https://doi.org/10.5194/gmd-18-3781-2025
- Global assimilation of NRL MODIS aerosol optical thickness and its impact on aerosol direct radiative effect over a full year M. Zhao et al. https://doi.org/10.1016/j.atmosres.2026.108819
- Modeling coarse and giant desert dust particles E. Drakaki et al. https://doi.org/10.5194/acp-22-12727-2022
- Copernicus Atmosphere Monitoring Service – Regional Air Quality Production System v1.0 A. Colette et al. https://doi.org/10.5194/gmd-18-6835-2025
- Improved hourly estimate of aerosol optical thickness over Asian land by fusing geostationary satellites Fengyun-4B and Himawari-9 Y. Cheng et al. https://doi.org/10.1016/j.scitotenv.2024.171541
- 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. https://doi.org/10.5194/acp-23-5487-2023
- Quantifying dust deposition over the Atlantic Ocean E. Proestakis et al. https://doi.org/10.5194/essd-17-4351-2025
- Impact of assimilating NOAA VIIRS aerosol optical depth (AOD) observations on global AOD analysis from the Copernicus Atmosphere Monitoring Service (CAMS) S. Garrigues et al. https://doi.org/10.5194/acp-23-10473-2023
10 citations as recorded by crossref.
- Optimizing the Numerical Simulation of the Dust Event of March 2021: Integrating Aerosol Observations through Multi-Scale 3D Variational Assimilation in the WRF-Chem Model S. Mei et al. https://doi.org/10.3390/rs16111852
- Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts M. Gonçalves Ageitos et al. https://doi.org/10.5194/acp-23-8623-2023
- The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2 M. Pang et al. https://doi.org/10.5194/gmd-18-3781-2025
- Global assimilation of NRL MODIS aerosol optical thickness and its impact on aerosol direct radiative effect over a full year M. Zhao et al. https://doi.org/10.1016/j.atmosres.2026.108819
- Modeling coarse and giant desert dust particles E. Drakaki et al. https://doi.org/10.5194/acp-22-12727-2022
- Copernicus Atmosphere Monitoring Service – Regional Air Quality Production System v1.0 A. Colette et al. https://doi.org/10.5194/gmd-18-6835-2025
- Improved hourly estimate of aerosol optical thickness over Asian land by fusing geostationary satellites Fengyun-4B and Himawari-9 Y. Cheng et al. https://doi.org/10.1016/j.scitotenv.2024.171541
- 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. https://doi.org/10.5194/acp-23-5487-2023
- Quantifying dust deposition over the Atlantic Ocean E. Proestakis et al. https://doi.org/10.5194/essd-17-4351-2025
- Impact of assimilating NOAA VIIRS aerosol optical depth (AOD) observations on global AOD analysis from the Copernicus Atmosphere Monitoring Service (CAMS) S. Garrigues et al. https://doi.org/10.5194/acp-23-10473-2023
Saved (final revised paper)
Latest update: 28 Aug 2026
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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