Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data
Descripción del Articulo
The aerosol and precipitable water vapor (PW) distribution over the tropical Andes region is characterized using Aerosol Robotic Network (AERONET) observations at stations in Medellin (Colombia), Quito (Ecuador), Huancayo (Peru), and La Paz (Bolivia). AERONET aerosol optical depth (AOD) is interpret...
Autores: | , , , , , , |
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Formato: | artículo |
Fecha de Publicación: | 2024 |
Institución: | Instituto Geofísico del Perú |
Repositorio: | IGP-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.igp.gob.pe:20.500.12816/5641 |
Enlace del recurso: | http://hdl.handle.net/20.500.12816/5641 https://doi.org/10.1038/s41598-024-51247-9 |
Nivel de acceso: | acceso abierto |
Materia: | Aerosols Aerosols optical depth Tropical Andes Aeronet Sounding https://purl.org/pe-repo/ocde/ford#1.05.09 |
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dc.title.none.fl_str_mv |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
title |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
spellingShingle |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data Cazorla, María Aerosols Aerosols optical depth Tropical Andes Aeronet Sounding https://purl.org/pe-repo/ocde/ford#1.05.09 |
title_short |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
title_full |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
title_fullStr |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
title_full_unstemmed |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
title_sort |
Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 data |
author |
Cazorla, María |
author_facet |
Cazorla, María Giles, David M. Herrera, Edgar Suárez Salas, Luis Estevan, Rene Andrade, Marcos Bastidas, Álvaro |
author_role |
author |
author2 |
Giles, David M. Herrera, Edgar Suárez Salas, Luis Estevan, Rene Andrade, Marcos Bastidas, Álvaro |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Cazorla, María Giles, David M. Herrera, Edgar Suárez Salas, Luis Estevan, Rene Andrade, Marcos Bastidas, Álvaro |
dc.subject.none.fl_str_mv |
Aerosols Aerosols optical depth Tropical Andes Aeronet Sounding |
topic |
Aerosols Aerosols optical depth Tropical Andes Aeronet Sounding https://purl.org/pe-repo/ocde/ford#1.05.09 |
dc.subject.ocde.none.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#1.05.09 |
description |
The aerosol and precipitable water vapor (PW) distribution over the tropical Andes region is characterized using Aerosol Robotic Network (AERONET) observations at stations in Medellin (Colombia), Quito (Ecuador), Huancayo (Peru), and La Paz (Bolivia). AERONET aerosol optical depth (AOD) is interpreted using PM₂.₅ data when available. Columnar water vapor derived from ozone soundings at Quito is used to compare against AERONET PW. MERRA-2 data are used to complement analyses. Urban pollution and biomass burning smoke (BBS) dominate the regional aerosol composition. AOD and PM₂.₅ yearly cycles for coincident measurements correlate linearly at Medellin and Quito. The Andes cordillera’s orientation and elevation funnel or block BBS transport into valleys or highlands during the two fire seasons that systematically impact South America. The February–March season north of Colombia and the Colombian-Venezuelan border directly impacts Medellin. Possibly, the March aerosol signal over Quito has a long-range transport component. At Huancayo and La Paz, AOD increases in September due to the influence of BBS in the Amazon. AERONET PW and sounding data correlate linearly but a dry bias with respect to soundings was identified in AERONET. PW and rainfall progressively decrease from north to south due to increasing altitude. This regional diagnosis is an underlying basis to evaluate future changes in aerosol and PW given prevailing conditions of rapidly changing atmospheric composition. |
publishDate |
2024 |
dc.date.accessioned.none.fl_str_mv |
2024-12-02T16:13:57Z |
dc.date.available.none.fl_str_mv |
2024-12-02T16:13:57Z |
dc.date.issued.fl_str_mv |
2024-01-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
dc.identifier.citation.none.fl_str_mv |
Cazorla, M., Giles, D. M., Herrera, E., Suárez, L., Estevan, R., Andrade, M., & Bastidas, Á. (2024). Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA-2 data.==$Scientific Reports, 14$==(1). https://doi.org/10.1038/s41598-024-51247-9 |
dc.identifier.govdoc.none.fl_str_mv |
index-oti2018 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12816/5641 |
dc.identifier.journal.none.fl_str_mv |
Scientifc Reports |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1038/s41598-024-51247-9 |
identifier_str_mv |
Cazorla, M., Giles, D. M., Herrera, E., Suárez, L., Estevan, R., Andrade, M., & Bastidas, Á. (2024). Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA-2 data.==$Scientific Reports, 14$==(1). https://doi.org/10.1038/s41598-024-51247-9 index-oti2018 Scientifc Reports |
url |
http://hdl.handle.net/20.500.12816/5641 https://doi.org/10.1038/s41598-024-51247-9 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.none.fl_str_mv |
urn:issn:2045-2322 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.uri.none.fl_str_mv |
https://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
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https://creativecommons.org/licenses/by/4.0/ |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Nature Research |
publisher.none.fl_str_mv |
Nature Research |
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Cazorla, MaríaGiles, David M.Herrera, EdgarSuárez Salas, LuisEstevan, ReneAndrade, MarcosBastidas, Álvaro2024-12-02T16:13:57Z2024-12-02T16:13:57Z2024-01-09Cazorla, M., Giles, D. M., Herrera, E., Suárez, L., Estevan, R., Andrade, M., & Bastidas, Á. (2024). Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA-2 data.==$Scientific Reports, 14$==(1). https://doi.org/10.1038/s41598-024-51247-9index-oti2018http://hdl.handle.net/20.500.12816/5641Scientifc Reportshttps://doi.org/10.1038/s41598-024-51247-9The aerosol and precipitable water vapor (PW) distribution over the tropical Andes region is characterized using Aerosol Robotic Network (AERONET) observations at stations in Medellin (Colombia), Quito (Ecuador), Huancayo (Peru), and La Paz (Bolivia). AERONET aerosol optical depth (AOD) is interpreted using PM₂.₅ data when available. Columnar water vapor derived from ozone soundings at Quito is used to compare against AERONET PW. MERRA-2 data are used to complement analyses. Urban pollution and biomass burning smoke (BBS) dominate the regional aerosol composition. AOD and PM₂.₅ yearly cycles for coincident measurements correlate linearly at Medellin and Quito. The Andes cordillera’s orientation and elevation funnel or block BBS transport into valleys or highlands during the two fire seasons that systematically impact South America. The February–March season north of Colombia and the Colombian-Venezuelan border directly impacts Medellin. Possibly, the March aerosol signal over Quito has a long-range transport component. At Huancayo and La Paz, AOD increases in September due to the influence of BBS in the Amazon. AERONET PW and sounding data correlate linearly but a dry bias with respect to soundings was identified in AERONET. PW and rainfall progressively decrease from north to south due to increasing altitude. This regional diagnosis is an underlying basis to evaluate future changes in aerosol and PW given prevailing conditions of rapidly changing atmospheric composition.Por paresapplication/pdfengNature Researchurn:issn:2045-2322info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/AerosolsAerosols optical depthTropical AndesAeronetSoundinghttps://purl.org/pe-repo/ocde/ford#1.05.09Latitudinal and temporal distribution of aerosols and precipitable water vapor in the tropical Andes from AERONET, sounding, and MERRA‑2 datainfo:eu-repo/semantics/articlereponame:IGP-Institucionalinstname:Instituto Geofísico del Perúinstacron:IGPLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.igp.gob.pe/bitstreams/120280d3-50c8-4141-8791-5a19afc10793/downloadbb9bdc0b3349e4284e09149f943790b4MD51ORIGINALCarzola_et_al_2024_Nature_Research.pdfCarzola_et_al_2024_Nature_Research.pdfapplication/pdf5071082https://repositorio.igp.gob.pe/bitstreams/f68dffe7-ae5e-4f11-b2bd-044e79f47a76/downloadf860e9f5964c15892d6f7bfe8936abfeMD52TEXTCarzola_et_al_2024_Nature_Research.pdf.txtCarzola_et_al_2024_Nature_Research.pdf.txtExtracted texttext/plain88645https://repositorio.igp.gob.pe/bitstreams/67fbb473-4a48-43a9-81f3-a74578dd9af3/download2503e5d67df1b954f4555a719cdb2ff4MD53THUMBNAILCarzola_et_al_2024_Nature_Research.pdf.jpgCarzola_et_al_2024_Nature_Research.pdf.jpgGenerated Thumbnailimage/jpeg43704https://repositorio.igp.gob.pe/bitstreams/3c601327-027a-497e-9677-af5471af08fe/download0c3a65b73467fc4f01f8a536e620e454MD5420.500.12816/5641oai:repositorio.igp.gob.pe:20.500.12816/56412024-12-10 14:19:57.051https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessopen.accesshttps://repositorio.igp.gob.peRepositorio Geofísico Nacionalbiblio@igp.gob.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 |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).