Articles | Volume 17, issue 11
https://doi.org/10.5194/acp-17-7111-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-17-7111-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
15 Jun 2017
Research article |
| 15 Jun 2017
Impact of the choice of the satellite aerosol optical depth product in a sub-regional dust emission inversion
Jerónimo Escribano
CORRESPONDING AUTHOR
Laboratoire de Météorologie Dynamique, Université Pierre et Marie Curie/CNRS, Paris, France
Olivier Boucher
Laboratoire de Météorologie Dynamique, Université Pierre et Marie Curie/CNRS, Paris, France
Frédéric Chevallier
Laboratoire des Sciences du Climat et de l'Environnement, CEA, Saclay, France
Nicolás Huneeus
Geophysics Department, University of Chile, Santiago, Chile
Center for Climate and Resilience Research (CR2), Santiago, Chile
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Cited
19 citations as recorded by crossref.
- Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0 D. McGuffin et al. 10.5194/gmd-14-1821-2021
- Status and future of numerical atmospheric aerosol prediction with a focus on data requirements A. Benedetti et al. 10.5194/acp-18-10615-2018
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. 10.1016/j.jes.2022.04.012
- Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data X. Ceamanos et al. 10.5194/amt-16-2575-2023
- Retrieval of desert dust and carbonaceous aerosol emissions over Africa from POLDER/PARASOL products generated by the GRASP algorithm C. Chen et al. 10.5194/acp-18-12551-2018
- Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
- A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. 10.5194/gmd-15-1821-2022
- Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system A. Tsikerdekis et al. 10.5194/acp-21-2637-2021
- Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting M. Pang et al. 10.5194/gmd-17-8223-2024
- Variability in Observation-Based Onroad Emission Constraints from a Near-Road Environment H. Simon et al. 10.3390/atmos11111243
- Global transport of dust emitted from different regions of the Sahara C. Lamancusa & K. Wagstrom 10.1016/j.atmosenv.2019.05.042
- Aerosols in atmospheric chemistry and biogeochemical cycles of nutrients M. Kanakidou et al. 10.1088/1748-9326/aabcdb
- Quasi‐Global Maps of Daily Aerosol Optical Depth From a Ring of Five Geostationary Meteorological Satellites Using AERUS‐GEO X. Ceamanos et al. 10.1029/2021JD034906
- Machine Learning-Based Improvement of Aerosol Optical Depth from CHIMERE Simulations Using MODIS Satellite Observations F. Lemmouchi et al. 10.3390/rs15061510
- Merging regional and global aerosol optical depth records from major available satellite products L. Sogacheva et al. 10.5194/acp-20-2031-2020
- Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs) A. Tsikerdekis et al. 10.5194/gmd-15-3253-2022
- Assimilation of POLDER observations to estimate aerosol emissions A. Tsikerdekis et al. 10.5194/acp-23-9495-2023
- Profiling of Saharan dust from the Caribbean to western Africa – Part 2: Shipborne lidar measurements versus forecasts A. Ansmann et al. 10.5194/acp-17-14987-2017
- Constraining global aerosol emissions using POLDER/PARASOL satellite remote sensing observations C. Chen et al. 10.5194/acp-19-14585-2019
19 citations as recorded by crossref.
- Novel estimation of aerosol processes with particle size distribution measurements: a case study with the TOMAS algorithm v1.0.0 D. McGuffin et al. 10.5194/gmd-14-1821-2021
- Status and future of numerical atmospheric aerosol prediction with a focus on data requirements A. Benedetti et al. 10.5194/acp-18-10615-2018
- Vertical aerosol data assimilation technology and application based on satellite and ground lidar: A review and outlook T. Yang et al. 10.1016/j.jes.2022.04.012
- Instantaneous aerosol and surface retrieval using satellites in geostationary orbit (iAERUS-GEO) – estimation of 15 min aerosol optical depth from MSG/SEVIRI and evaluation with reference data X. Ceamanos et al. 10.5194/amt-16-2575-2023
- Retrieval of desert dust and carbonaceous aerosol emissions over Africa from POLDER/PARASOL products generated by the GRASP algorithm C. Chen et al. 10.5194/acp-18-12551-2018
- Assimilating spaceborne lidar dust extinction can improve dust forecasts J. Escribano et al. 10.5194/acp-22-535-2022
- A three-dimensional variational data assimilation system for aerosol optical properties based on WRF-Chem v4.0: design, development, and application of assimilating Himawari-8 aerosol observations D. Wang et al. 10.5194/gmd-15-1821-2022
- Assimilating aerosol optical properties related to size and absorption from POLDER/PARASOL with an ensemble data assimilation system A. Tsikerdekis et al. 10.5194/acp-21-2637-2021
- Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting M. Pang et al. 10.5194/gmd-17-8223-2024
- Variability in Observation-Based Onroad Emission Constraints from a Near-Road Environment H. Simon et al. 10.3390/atmos11111243
- Global transport of dust emitted from different regions of the Sahara C. Lamancusa & K. Wagstrom 10.1016/j.atmosenv.2019.05.042
- Aerosols in atmospheric chemistry and biogeochemical cycles of nutrients M. Kanakidou et al. 10.1088/1748-9326/aabcdb
- Quasi‐Global Maps of Daily Aerosol Optical Depth From a Ring of Five Geostationary Meteorological Satellites Using AERUS‐GEO X. Ceamanos et al. 10.1029/2021JD034906
- Machine Learning-Based Improvement of Aerosol Optical Depth from CHIMERE Simulations Using MODIS Satellite Observations F. Lemmouchi et al. 10.3390/rs15061510
- Merging regional and global aerosol optical depth records from major available satellite products L. Sogacheva et al. 10.5194/acp-20-2031-2020
- Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman smoother: observing system simulation experiments (OSSEs) A. Tsikerdekis et al. 10.5194/gmd-15-3253-2022
- Assimilation of POLDER observations to estimate aerosol emissions A. Tsikerdekis et al. 10.5194/acp-23-9495-2023
- Profiling of Saharan dust from the Caribbean to western Africa – Part 2: Shipborne lidar measurements versus forecasts A. Ansmann et al. 10.5194/acp-17-14987-2017
- Constraining global aerosol emissions using POLDER/PARASOL satellite remote sensing observations C. Chen et al. 10.5194/acp-19-14585-2019
Latest update: 30 Dec 2024
Short summary
Top-down estimates of mineral dust flux usually rely on a single observational dataset whose observational errors propagate onto the emission estimates. Aerosol optical depth from five satellites are assimilated one by one into a source inversion system over northern Africa. We find a relatively large dispersion in flux estimates among the five experiments, which can likely be attributed to differences in the assimilated observational datasets and their associated error statistics.
Top-down estimates of mineral dust flux usually rely on a single observational dataset whose...
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