Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment
- Autores
- Shields, Christine A.; Payne, Ashley E.; Shearer, Eric Jay; Wehner, Michael; O'Brien, Travis Allen; Rutz, Jonathan J.; Leung, Ruby; Ralph, F. Martin; Marquardt Collow, Allison B.; Ullrich, Paul; Dong, Qizhen; Gershunov, Alexander; Griffith, Helen; Guan, Bin; Lora, Juan Manuel; Lu, Mengqian; McClenny, Elizabeth; Nardi, Kyle M.; Pan, Mengxin; Qian, Yun; Ramos, Alexandre M.; Shulgina, Tamara; Viale, Maximiliano; Sarangi, Chandan; Tomé, Ricardo; Zarzycki, Colin
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.
Fil: Shields, Christine A.. National Center for Atmospheric Research; Estados Unidos
Fil: Payne, Ashley E.. University Of Michigan; Estados Unidos
Fil: Shearer, Eric Jay. University of California at Irvine; Estados Unidos
Fil: Wehner, Michael. Lawrence Berkeley National Laboratory; Estados Unidos
Fil: O'Brien, Travis Allen. Indiana University; Estados Unidos. Lawrence Berkeley National Laboratory; Estados Unidos
Fil: Rutz, Jonathan J.. National Weather Service; Estados Unidos
Fil: Leung, Ruby. Pacific Northwest National Laboratory; Estados Unidos
Fil: Ralph, F. Martin. University of California at San Diego; Estados Unidos
Fil: Marquardt Collow, Allison B.. University of Maryland; Estados Unidos. National Aeronautics and Space Administration; Estados Unidos
Fil: Ullrich, Paul. University of California at Davis; Estados Unidos
Fil: Dong, Qizhen. University Of Science And Technology; Hong Kong
Fil: Gershunov, Alexander. University of California at San Diego; Estados Unidos
Fil: Griffith, Helen. University of Reading; Reino Unido
Fil: Guan, Bin. University of California at Los Angeles; Estados Unidos
Fil: Lora, Juan Manuel. University of Yale; Estados Unidos
Fil: Lu, Mengqian. The Hong Kong University of Science and Technology; Hong Kong
Fil: McClenny, Elizabeth. University of California at Davis; Estados Unidos
Fil: Nardi, Kyle M.. Pennsylvania State University; Estados Unidos
Fil: Pan, Mengxin. The Hong Kong University of Science and Technology; Hong Kong
Fil: Qian, Yun. Pacific Northwest National Laboratory; Estados Unidos
Fil: Ramos, Alexandre M.. Universidade de Lisboa. Faculdade de Ciências. Instituto Dom Luiz; Portugal. Karlsruher Institut für Technologie; Alemania
Fil: Shulgina, Tamara. University of California at Davis; Estados Unidos
Fil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina
Fil: Sarangi, Chandan. Indian Institute Of Technology Madras; India. Pacific Northwest National Laboratory; Estados Unidos
Fil: Tomé, Ricardo. Universidade de Lisboa. Faculdade de Ciências. Instituto Dom Luiz; Portugal
Fil: Zarzycki, Colin. State University of Pennsylvania; Estados Unidos - Materia
-
ATMOSPHERIC RIVER DETECTION TOOLS
ATMOSPHERIC RIVERS
CLIMATOLOGY
HIGH RESOLUTION CLIMATE CHANGE
PRECIPITATION AND EXTREMES
UNCERTAINTY QUANTIFICATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
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- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/233400
Ver los metadatos del registro completo
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Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming ExperimentShields, Christine A.Payne, Ashley E.Shearer, Eric JayWehner, MichaelO'Brien, Travis AllenRutz, Jonathan J.Leung, RubyRalph, F. MartinMarquardt Collow, Allison B.Ullrich, PaulDong, QizhenGershunov, AlexanderGriffith, HelenGuan, BinLora, Juan ManuelLu, MengqianMcClenny, ElizabethNardi, Kyle M.Pan, MengxinQian, YunRamos, Alexandre M.Shulgina, TamaraViale, MaximilianoSarangi, ChandanTomé, RicardoZarzycki, ColinATMOSPHERIC RIVER DETECTION TOOLSATMOSPHERIC RIVERSCLIMATOLOGYHIGH RESOLUTION CLIMATE CHANGEPRECIPITATION AND EXTREMESUNCERTAINTY QUANTIFICATIONhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.Fil: Shields, Christine A.. National Center for Atmospheric Research; Estados UnidosFil: Payne, Ashley E.. University Of Michigan; Estados UnidosFil: Shearer, Eric Jay. University of California at Irvine; Estados UnidosFil: Wehner, Michael. Lawrence Berkeley National Laboratory; Estados UnidosFil: O'Brien, Travis Allen. Indiana University; Estados Unidos. Lawrence Berkeley National Laboratory; Estados UnidosFil: Rutz, Jonathan J.. National Weather Service; Estados UnidosFil: Leung, Ruby. Pacific Northwest National Laboratory; Estados UnidosFil: Ralph, F. Martin. University of California at San Diego; Estados UnidosFil: Marquardt Collow, Allison B.. University of Maryland; Estados Unidos. National Aeronautics and Space Administration; Estados UnidosFil: Ullrich, Paul. University of California at Davis; Estados UnidosFil: Dong, Qizhen. University Of Science And Technology; Hong KongFil: Gershunov, Alexander. University of California at San Diego; Estados UnidosFil: Griffith, Helen. University of Reading; Reino UnidoFil: Guan, Bin. University of California at Los Angeles; Estados UnidosFil: Lora, Juan Manuel. University of Yale; Estados UnidosFil: Lu, Mengqian. The Hong Kong University of Science and Technology; Hong KongFil: McClenny, Elizabeth. University of California at Davis; Estados UnidosFil: Nardi, Kyle M.. Pennsylvania State University; Estados UnidosFil: Pan, Mengxin. The Hong Kong University of Science and Technology; Hong KongFil: Qian, Yun. Pacific Northwest National Laboratory; Estados UnidosFil: Ramos, Alexandre M.. Universidade de Lisboa. Faculdade de Ciências. Instituto Dom Luiz; Portugal. Karlsruher Institut für Technologie; AlemaniaFil: Shulgina, Tamara. University of California at Davis; Estados UnidosFil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Sarangi, Chandan. Indian Institute Of Technology Madras; India. Pacific Northwest National Laboratory; Estados UnidosFil: Tomé, Ricardo. Universidade de Lisboa. Faculdade de Ciências. Instituto Dom Luiz; PortugalFil: Zarzycki, Colin. State University of Pennsylvania; Estados UnidosAmerican Geophysical Union2023-03-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/233400Shields, Christine A.; Payne, Ashley E.; Shearer, Eric Jay; Wehner, Michael; O'Brien, Travis Allen; et al.; Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment; American Geophysical Union; Geophysical Research Letters; 50; 6; 14-3-2023; 1 - 90094-82761944-8007CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022GL102091info:eu-repo/semantics/altIdentifier/doi/10.1029/2022GL102091info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:11:55Zoai:ri.conicet.gov.ar:11336/233400instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:11:55.315CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| title |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| spellingShingle |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment Shields, Christine A. ATMOSPHERIC RIVER DETECTION TOOLS ATMOSPHERIC RIVERS CLIMATOLOGY HIGH RESOLUTION CLIMATE CHANGE PRECIPITATION AND EXTREMES UNCERTAINTY QUANTIFICATION |
| title_short |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| title_full |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| title_fullStr |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| title_full_unstemmed |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| title_sort |
Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment |
| dc.creator.none.fl_str_mv |
Shields, Christine A. Payne, Ashley E. Shearer, Eric Jay Wehner, Michael O'Brien, Travis Allen Rutz, Jonathan J. Leung, Ruby Ralph, F. Martin Marquardt Collow, Allison B. Ullrich, Paul Dong, Qizhen Gershunov, Alexander Griffith, Helen Guan, Bin Lora, Juan Manuel Lu, Mengqian McClenny, Elizabeth Nardi, Kyle M. Pan, Mengxin Qian, Yun Ramos, Alexandre M. Shulgina, Tamara Viale, Maximiliano Sarangi, Chandan Tomé, Ricardo Zarzycki, Colin |
| author |
Shields, Christine A. |
| author_facet |
Shields, Christine A. Payne, Ashley E. Shearer, Eric Jay Wehner, Michael O'Brien, Travis Allen Rutz, Jonathan J. Leung, Ruby Ralph, F. Martin Marquardt Collow, Allison B. Ullrich, Paul Dong, Qizhen Gershunov, Alexander Griffith, Helen Guan, Bin Lora, Juan Manuel Lu, Mengqian McClenny, Elizabeth Nardi, Kyle M. Pan, Mengxin Qian, Yun Ramos, Alexandre M. Shulgina, Tamara Viale, Maximiliano Sarangi, Chandan Tomé, Ricardo Zarzycki, Colin |
| author_role |
author |
| author2 |
Payne, Ashley E. Shearer, Eric Jay Wehner, Michael O'Brien, Travis Allen Rutz, Jonathan J. Leung, Ruby Ralph, F. Martin Marquardt Collow, Allison B. Ullrich, Paul Dong, Qizhen Gershunov, Alexander Griffith, Helen Guan, Bin Lora, Juan Manuel Lu, Mengqian McClenny, Elizabeth Nardi, Kyle M. Pan, Mengxin Qian, Yun Ramos, Alexandre M. Shulgina, Tamara Viale, Maximiliano Sarangi, Chandan Tomé, Ricardo Zarzycki, Colin |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
ATMOSPHERIC RIVER DETECTION TOOLS ATMOSPHERIC RIVERS CLIMATOLOGY HIGH RESOLUTION CLIMATE CHANGE PRECIPITATION AND EXTREMES UNCERTAINTY QUANTIFICATION |
| topic |
ATMOSPHERIC RIVER DETECTION TOOLS ATMOSPHERIC RIVERS CLIMATOLOGY HIGH RESOLUTION CLIMATE CHANGE PRECIPITATION AND EXTREMES UNCERTAINTY QUANTIFICATION |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
| dc.description.none.fl_txt_mv |
Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection. Fil: Shields, Christine A.. National Center for Atmospheric Research; Estados Unidos Fil: Payne, Ashley E.. University Of Michigan; Estados Unidos Fil: Shearer, Eric Jay. University of California at Irvine; Estados Unidos Fil: Wehner, Michael. Lawrence Berkeley National Laboratory; Estados Unidos Fil: O'Brien, Travis Allen. Indiana University; Estados Unidos. Lawrence Berkeley National Laboratory; Estados Unidos Fil: Rutz, Jonathan J.. National Weather Service; Estados Unidos Fil: Leung, Ruby. Pacific Northwest National Laboratory; Estados Unidos Fil: Ralph, F. Martin. University of California at San Diego; Estados Unidos Fil: Marquardt Collow, Allison B.. University of Maryland; Estados Unidos. National Aeronautics and Space Administration; Estados Unidos Fil: Ullrich, Paul. University of California at Davis; Estados Unidos Fil: Dong, Qizhen. University Of Science And Technology; Hong Kong Fil: Gershunov, Alexander. University of California at San Diego; Estados Unidos Fil: Griffith, Helen. University of Reading; Reino Unido Fil: Guan, Bin. University of California at Los Angeles; Estados Unidos Fil: Lora, Juan Manuel. University of Yale; Estados Unidos Fil: Lu, Mengqian. The Hong Kong University of Science and Technology; Hong Kong Fil: McClenny, Elizabeth. University of California at Davis; Estados Unidos Fil: Nardi, Kyle M.. Pennsylvania State University; Estados Unidos Fil: Pan, Mengxin. The Hong Kong University of Science and Technology; Hong Kong Fil: Qian, Yun. Pacific Northwest National Laboratory; Estados Unidos Fil: Ramos, Alexandre M.. Universidade de Lisboa. Faculdade de Ciências. Instituto Dom Luiz; Portugal. Karlsruher Institut für Technologie; Alemania Fil: Shulgina, Tamara. University of California at Davis; Estados Unidos Fil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina Fil: Sarangi, Chandan. Indian Institute Of Technology Madras; India. Pacific Northwest National Laboratory; Estados Unidos Fil: Tomé, Ricardo. Universidade de Lisboa. Faculdade de Ciências. Instituto Dom Luiz; Portugal Fil: Zarzycki, Colin. State University of Pennsylvania; Estados Unidos |
| description |
Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection. |
| publishDate |
2023 |
| dc.date.none.fl_str_mv |
2023-03-14 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/233400 Shields, Christine A.; Payne, Ashley E.; Shearer, Eric Jay; Wehner, Michael; O'Brien, Travis Allen; et al.; Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment; American Geophysical Union; Geophysical Research Letters; 50; 6; 14-3-2023; 1 - 9 0094-8276 1944-8007 CONICET Digital CONICET |
| url |
http://hdl.handle.net/11336/233400 |
| identifier_str_mv |
Shields, Christine A.; Payne, Ashley E.; Shearer, Eric Jay; Wehner, Michael; O'Brien, Travis Allen; et al.; Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier 2 High-Resolution Global Warming Experiment; American Geophysical Union; Geophysical Research Letters; 50; 6; 14-3-2023; 1 - 9 0094-8276 1944-8007 CONICET Digital CONICET |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
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info:eu-repo/semantics/altIdentifier/url/https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022GL102091 info:eu-repo/semantics/altIdentifier/doi/10.1029/2022GL102091 |
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openAccess |
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application/pdf application/pdf |
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American Geophysical Union |
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American Geophysical Union |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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