Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST
International audience The predictability of northern Africa dust events is assessed using daily numerical forecast simulations for the next 3 days. The dust concentration fields, modeled with the CHIMERE-DUST model, were first evaluated by comparison with both Aerosol Robotic Network (AERONET) surf...
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Online Access: | https://hal.science/hal-03197734 https://hal.science/hal-03197734/document https://hal.science/hal-03197734/file/2008JD010523.pdf https://doi.org/10.1029/2008JD010523 |
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ftuniversailles:oai:HAL:hal-03197734v1 2024-04-28T07:53:23+00:00 Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST Menut, Laurent Chiapello, Isabelle Moulin, Cyril Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) 2009 https://hal.science/hal-03197734 https://hal.science/hal-03197734/document https://hal.science/hal-03197734/file/2008JD010523.pdf https://doi.org/10.1029/2008JD010523 en eng HAL CCSD American Geophysical Union info:eu-repo/semantics/altIdentifier/doi/10.1029/2008JD010523 hal-03197734 https://hal.science/hal-03197734 https://hal.science/hal-03197734/document https://hal.science/hal-03197734/file/2008JD010523.pdf doi:10.1029/2008JD010523 info:eu-repo/semantics/OpenAccess ISSN: 0148-0227 EISSN: 2156-2202 Journal of Geophysical Research https://hal.science/hal-03197734 Journal of Geophysical Research, 2009, 114 (D7), ⟨10.1029/2008JD010523⟩ [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment info:eu-repo/semantics/article Journal articles 2009 ftuniversailles https://doi.org/10.1029/2008JD010523 2024-04-04T17:34:31Z International audience The predictability of northern Africa dust events is assessed using daily numerical forecast simulations for the next 3 days. The dust concentration fields, modeled with the CHIMERE-DUST model, were first evaluated by comparison with both Aerosol Robotic Network (AERONET) surface data and Ozone Monitoring Instrument (OMI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite measurements. The accuracy and spread between measurements and simulations are discussed for the first short observation period of the African Monsoon Multidisciplinary Analysis (AMMA) experiment in western Africa, between January and March 2006. The predictability of dust events was then estimated by comparing model results for different leads in a forecast mode. The model performance was evaluated with respect to its capability to forecast the surface wind speed, which is the key process for dust emission, and the transport of mineral dust near source regions and toward remote areas. It is shown that forecast emissions can vary up to 80% (close to the sources) but that the variability on forecasted dust concentrations and optical thicknesses do not exceed 40% and 20%. Article in Journal/Newspaper Aerosol Robotic Network Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQ Journal of Geophysical Research 114 D7 |
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Open Polar |
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Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQ |
op_collection_id |
ftuniversailles |
language |
English |
topic |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment |
spellingShingle |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment Menut, Laurent Chiapello, Isabelle Moulin, Cyril Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST |
topic_facet |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environment |
description |
International audience The predictability of northern Africa dust events is assessed using daily numerical forecast simulations for the next 3 days. The dust concentration fields, modeled with the CHIMERE-DUST model, were first evaluated by comparison with both Aerosol Robotic Network (AERONET) surface data and Ozone Monitoring Instrument (OMI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite measurements. The accuracy and spread between measurements and simulations are discussed for the first short observation period of the African Monsoon Multidisciplinary Analysis (AMMA) experiment in western Africa, between January and March 2006. The predictability of dust events was then estimated by comparing model results for different leads in a forecast mode. The model performance was evaluated with respect to its capability to forecast the surface wind speed, which is the key process for dust emission, and the transport of mineral dust near source regions and toward remote areas. It is shown that forecast emissions can vary up to 80% (close to the sources) but that the variability on forecasted dust concentrations and optical thicknesses do not exceed 40% and 20%. |
author2 |
Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) |
format |
Article in Journal/Newspaper |
author |
Menut, Laurent Chiapello, Isabelle Moulin, Cyril |
author_facet |
Menut, Laurent Chiapello, Isabelle Moulin, Cyril |
author_sort |
Menut, Laurent |
title |
Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST |
title_short |
Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST |
title_full |
Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST |
title_fullStr |
Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST |
title_full_unstemmed |
Predictability of mineral dust concentrations: The African Monsoon Multidisciplinary Analysis first short observation period forecasted with CHIMERE‐DUST |
title_sort |
predictability of mineral dust concentrations: the african monsoon multidisciplinary analysis first short observation period forecasted with chimere‐dust |
publisher |
HAL CCSD |
publishDate |
2009 |
url |
https://hal.science/hal-03197734 https://hal.science/hal-03197734/document https://hal.science/hal-03197734/file/2008JD010523.pdf https://doi.org/10.1029/2008JD010523 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
ISSN: 0148-0227 EISSN: 2156-2202 Journal of Geophysical Research https://hal.science/hal-03197734 Journal of Geophysical Research, 2009, 114 (D7), ⟨10.1029/2008JD010523⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1029/2008JD010523 hal-03197734 https://hal.science/hal-03197734 https://hal.science/hal-03197734/document https://hal.science/hal-03197734/file/2008JD010523.pdf doi:10.1029/2008JD010523 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1029/2008JD010523 |
container_title |
Journal of Geophysical Research |
container_volume |
114 |
container_issue |
D7 |
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1797568123002421248 |