Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast
International audience Aerosol optical thickness (AOT) was provided by SeaWiFS over oceans from October 1997 to December 2010. Weekly, monthly, and annually maps might help scientifics to better understand climate change and its impacts. Making average of several images to get these maps is not suit...
Main Authors: | , , , , , |
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Other Authors: | , , , , , , , , , , , |
Format: | Book Part |
Language: | English |
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HAL CCSD
2016
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Online Access: | https://hal.archives-ouvertes.fr/hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520/document https://hal.archives-ouvertes.fr/hal-01507520/file/52970.pdf https://doi.org/10.5772/65874 |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
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ftccsdartic |
language |
English |
topic |
West African coast absorbing aerosols neural networks [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
spellingShingle |
West African coast absorbing aerosols neural networks [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere Diouf, Daouda Niang, Awa Brajard, Julien Sawadogo, Salam Crépon, Michel Thiria, Sylvie Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast |
topic_facet |
West African coast absorbing aerosols neural networks [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
description |
International audience Aerosol optical thickness (AOT) was provided by SeaWiFS over oceans from October 1997 to December 2010. Weekly, monthly, and annually maps might help scientifics to better understand climate change and its impacts. Making average of several images to get these maps is not suitable on West African coast. A particularity of this area is that it is constantly traversed by desert dust. The algorithm used by SeaWiFS inverts the reflectance measurements to retrieve the aerosol optical thickness at 865 nm. For the poorly absorbing aerosol optical thickness less than 0.35, the standard algorithm works very well. On the west African coast that is often crossed by desert aerosol plumes characterized by high optical thicknesses. In this paper we study the spatial and temporal variability of aerosols on the West African coast during the period from December 1997 to November 2009 by using neural network inversion. The neural network method we used is mixed method of neuro-variational inversion called SOM-NV. It is an evolution of NeuroVaria that is a combination of a variational inversion and multilayer perceptrons, multilayer perceptrons (MLPs). This work also enables validation of the optical thickness retrieved by SOM-NV with AOT in situ measurements collected at AErosol RObotic NETwork (AERONET) stations. |
author2 |
École Supérieure Polytechnique de Dakar (ESP) Université Cheikh Anta Diop Dakar, Sénégal (UCAD) Coupling environmental data and simulation models for software integration (CLIME) Inria de Paris Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) Processus de la variabilité climatique tropicale et impacts (PARVATI) Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN) Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)) École normale supérieure - Paris (ENS Paris) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) |
format |
Book Part |
author |
Diouf, Daouda Niang, Awa Brajard, Julien Sawadogo, Salam Crépon, Michel Thiria, Sylvie |
author_facet |
Diouf, Daouda Niang, Awa Brajard, Julien Sawadogo, Salam Crépon, Michel Thiria, Sylvie |
author_sort |
Diouf, Daouda |
title |
Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast |
title_short |
Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast |
title_full |
Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast |
title_fullStr |
Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast |
title_full_unstemmed |
Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast |
title_sort |
spatial distribution of aerosol optical thickness retrieved from seawifs images by a neural network inversion over the west african coast |
publisher |
HAL CCSD |
publishDate |
2016 |
url |
https://hal.archives-ouvertes.fr/hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520/document https://hal.archives-ouvertes.fr/hal-01507520/file/52970.pdf https://doi.org/10.5772/65874 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Aerosols-Science and Case Studies https://hal.archives-ouvertes.fr/hal-01507520 Aerosols-Science and Case Studies, InTech, 2016, 978-953-51-2843-4. ⟨10.5772/65874⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5772/65874 ISBN: 978-953-51-2843-4 hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520/document https://hal.archives-ouvertes.fr/hal-01507520/file/52970.pdf doi:10.5772/65874 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5772/65874 |
_version_ |
1765999440075685888 |
spelling |
ftccsdartic:oai:HAL:hal-01507520v1 2023-05-15T13:06:17+02:00 Spatial Distribution of Aerosol Optical Thickness Retrieved from SeaWiFS Images by a Neural Network Inversion over the West African Coast Diouf, Daouda Niang, Awa Brajard, Julien Sawadogo, Salam Crépon, Michel Thiria, Sylvie École Supérieure Polytechnique de Dakar (ESP) Université Cheikh Anta Diop Dakar, Sénégal (UCAD) Coupling environmental data and simulation models for software integration (CLIME) Inria de Paris Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria) Processus de la variabilité climatique tropicale et impacts (PARVATI) Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN) Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)) École normale supérieure - Paris (ENS Paris) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)) Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales Toulouse (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) 2016 https://hal.archives-ouvertes.fr/hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520/document https://hal.archives-ouvertes.fr/hal-01507520/file/52970.pdf https://doi.org/10.5772/65874 en eng HAL CCSD InTech info:eu-repo/semantics/altIdentifier/doi/10.5772/65874 ISBN: 978-953-51-2843-4 hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520 https://hal.archives-ouvertes.fr/hal-01507520/document https://hal.archives-ouvertes.fr/hal-01507520/file/52970.pdf doi:10.5772/65874 info:eu-repo/semantics/OpenAccess Aerosols-Science and Case Studies https://hal.archives-ouvertes.fr/hal-01507520 Aerosols-Science and Case Studies, InTech, 2016, 978-953-51-2843-4. ⟨10.5772/65874⟩ West African coast absorbing aerosols neural networks [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/bookPart Book sections 2016 ftccsdartic https://doi.org/10.5772/65874 2021-12-05T02:51:43Z International audience Aerosol optical thickness (AOT) was provided by SeaWiFS over oceans from October 1997 to December 2010. Weekly, monthly, and annually maps might help scientifics to better understand climate change and its impacts. Making average of several images to get these maps is not suitable on West African coast. A particularity of this area is that it is constantly traversed by desert dust. The algorithm used by SeaWiFS inverts the reflectance measurements to retrieve the aerosol optical thickness at 865 nm. For the poorly absorbing aerosol optical thickness less than 0.35, the standard algorithm works very well. On the west African coast that is often crossed by desert aerosol plumes characterized by high optical thicknesses. In this paper we study the spatial and temporal variability of aerosols on the West African coast during the period from December 1997 to November 2009 by using neural network inversion. The neural network method we used is mixed method of neuro-variational inversion called SOM-NV. It is an evolution of NeuroVaria that is a combination of a variational inversion and multilayer perceptrons, multilayer perceptrons (MLPs). This work also enables validation of the optical thickness retrieved by SOM-NV with AOT in situ measurements collected at AErosol RObotic NETwork (AERONET) stations. Book Part Aerosol Robotic Network Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |