Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers
Abstract Atmospheric aerosol over the North Atlantic Ocean impacts regional clouds and climate. In this work, we use a set of sun photometer observations of aerosol optical depth (AOD) located on the Graciosa and Cape Verde islands, along with the GEOS‐Chem chemical transport model to investigate th...
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ftdoajarticles:oai:doaj.org/article:ffea7ef77e814d81bd8b833857be77f9 2023-05-15T17:28:42+02:00 Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers Sam J. Silva David A. Ridley Colette L. Heald 2020-11-01T00:00:00Z https://doi.org/10.1029/2020EA001392 https://doaj.org/article/ffea7ef77e814d81bd8b833857be77f9 EN eng American Geophysical Union (AGU) https://doi.org/10.1029/2020EA001392 https://doaj.org/toc/2333-5084 2333-5084 doi:10.1029/2020EA001392 https://doaj.org/article/ffea7ef77e814d81bd8b833857be77f9 Earth and Space Science, Vol 7, Iss 11, Pp n/a-n/a (2020) Astronomy QB1-991 Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.1029/2020EA001392 2022-12-31T09:51:50Z Abstract Atmospheric aerosol over the North Atlantic Ocean impacts regional clouds and climate. In this work, we use a set of sun photometer observations of aerosol optical depth (AOD) located on the Graciosa and Cape Verde islands, along with the GEOS‐Chem chemical transport model to investigate the sources of these aerosol and their transport over the North Atlantic Ocean. At both locations, the largest simulated contributor to aerosol extinction is the local source of sea‐salt aerosol. In addition to this large source, we find that signatures consistent with long‐range transport of anthropogenic, biomass burning, and dust emissions are apparent throughout the year at both locations. Model simulations suggest that this signal of long‐range transport in AOD is more apparent at higher elevation locations; the influence of anthropogenic and biomass burning aerosol extinction is particularly pronounced at the height of Pico Mountain, near the Graciosa Island site. Using a machine learning approach, we further show that simulated observations at these three sites (near Graciosa, Pico Mountain, and Cape Verde) can be used to predict the simulated background aerosol imported into cities on the European mainland, particularly during the local winter months, highlighting the utility of background AOD monitoring for understanding downwind air quality. Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Earth and Space Science 7 11 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Astronomy QB1-991 Geology QE1-996.5 |
spellingShingle |
Astronomy QB1-991 Geology QE1-996.5 Sam J. Silva David A. Ridley Colette L. Heald Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers |
topic_facet |
Astronomy QB1-991 Geology QE1-996.5 |
description |
Abstract Atmospheric aerosol over the North Atlantic Ocean impacts regional clouds and climate. In this work, we use a set of sun photometer observations of aerosol optical depth (AOD) located on the Graciosa and Cape Verde islands, along with the GEOS‐Chem chemical transport model to investigate the sources of these aerosol and their transport over the North Atlantic Ocean. At both locations, the largest simulated contributor to aerosol extinction is the local source of sea‐salt aerosol. In addition to this large source, we find that signatures consistent with long‐range transport of anthropogenic, biomass burning, and dust emissions are apparent throughout the year at both locations. Model simulations suggest that this signal of long‐range transport in AOD is more apparent at higher elevation locations; the influence of anthropogenic and biomass burning aerosol extinction is particularly pronounced at the height of Pico Mountain, near the Graciosa Island site. Using a machine learning approach, we further show that simulated observations at these three sites (near Graciosa, Pico Mountain, and Cape Verde) can be used to predict the simulated background aerosol imported into cities on the European mainland, particularly during the local winter months, highlighting the utility of background AOD monitoring for understanding downwind air quality. |
format |
Article in Journal/Newspaper |
author |
Sam J. Silva David A. Ridley Colette L. Heald |
author_facet |
Sam J. Silva David A. Ridley Colette L. Heald |
author_sort |
Sam J. Silva |
title |
Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers |
title_short |
Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers |
title_full |
Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers |
title_fullStr |
Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers |
title_full_unstemmed |
Exploring the Constraints on Simulated Aerosol Sources and Transport Across the North Atlantic With Island‐Based Sun Photometers |
title_sort |
exploring the constraints on simulated aerosol sources and transport across the north atlantic with island‐based sun photometers |
publisher |
American Geophysical Union (AGU) |
publishDate |
2020 |
url |
https://doi.org/10.1029/2020EA001392 https://doaj.org/article/ffea7ef77e814d81bd8b833857be77f9 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Earth and Space Science, Vol 7, Iss 11, Pp n/a-n/a (2020) |
op_relation |
https://doi.org/10.1029/2020EA001392 https://doaj.org/toc/2333-5084 2333-5084 doi:10.1029/2020EA001392 https://doaj.org/article/ffea7ef77e814d81bd8b833857be77f9 |
op_doi |
https://doi.org/10.1029/2020EA001392 |
container_title |
Earth and Space Science |
container_volume |
7 |
container_issue |
11 |
_version_ |
1766121553122033664 |