An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region
Precipitation decreased in the last century in the southern Argentinian Andes mountains, especially in winter, and this trend is expected to continue in the future, generating a significant negative impact on the local and national economy. This fact is relevant since the Comahue river basin, compre...
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Format: | Book Part |
Language: | English |
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Springer
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Online Access: | http://hdl.handle.net/11336/229769 |
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author | Vita Sanchez, Maximiliano Sergio González, Marcela Hebe Rolla, Alfredo Luis |
author_facet | Vita Sanchez, Maximiliano Sergio González, Marcela Hebe Rolla, Alfredo Luis |
author_sort | Vita Sanchez, Maximiliano Sergio |
collection | CONICET Digital (Consejo Nacional de Investigaciones Científicas y Técnicas) |
description | Precipitation decreased in the last century in the southern Argentinian Andes mountains, especially in winter, and this trend is expected to continue in the future, generating a significant negative impact on the local and national economy. This fact is relevant since the Comahue river basin, compressed by the sub-basins of the Negro, Neuquén and Limay rivers, is characterized by fruit-horticultural production and by the presence of hydroelectric dams. As the river flows are largely influenced by the interannual variability of autumn and winter rainfall, the availability of a good seasonal forecast provides an efficient tool to minimize risks. The study addresses the analysis of the main climatic forcing of precipitation to design some statistical models to forecast autumn rainfall. Using monthly precipitation data for the period 1981–2017 from several national institutions and data of atmospheric variables from the NCEP/NCAR reanalysis, correlation maps have been used to define the best set of predictors. The multiple linear regression methodology was used to build predictive models. The main conclusion is that the South Atlantic Ocean High, the sea surface temperature of the Pacific and Indian Oceans and the polar jet are the most relevant predictors and the designed models have good skill. Fil: Vita Sanchez, Maximiliano Sergio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: González, Marcela Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Rolla, Alfredo Luis. Consejo Nacional de Investigaciones Científicas y ... |
format | Book Part |
genre | South Atlantic Ocean |
genre_facet | South Atlantic Ocean |
geographic | Argentina Indian Pacific |
geographic_facet | Argentina Indian Pacific |
id | ftconicet:oai:ri.conicet.gov.ar:11336/229769 |
institution | Open Polar |
language | English |
op_collection_id | ftconicet |
op_relation | info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/chapter/10.1007/978-3-031-04532-5_5#editor-information http://hdl.handle.net/11336/229769 CONICET Digital CONICET |
op_rights | info:eu-repo/semantics/restrictedAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
publisher | Springer |
record_format | openpolar |
spelling | ftconicet:oai:ri.conicet.gov.ar:11336/229769 2025-01-17T00:50:12+00:00 An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region Vita Sanchez, Maximiliano Sergio González, Marcela Hebe Rolla, Alfredo Luis application/pdf http://hdl.handle.net/11336/229769 eng eng Springer info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/chapter/10.1007/978-3-031-04532-5_5#editor-information http://hdl.handle.net/11336/229769 CONICET Digital CONICET info:eu-repo/semantics/restrictedAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Seasonal forecast Precipitation Statistical models https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/bookPart info:ar-repo/semantics/parte de libro ftconicet 2024-10-04T09:34:18Z Precipitation decreased in the last century in the southern Argentinian Andes mountains, especially in winter, and this trend is expected to continue in the future, generating a significant negative impact on the local and national economy. This fact is relevant since the Comahue river basin, compressed by the sub-basins of the Negro, Neuquén and Limay rivers, is characterized by fruit-horticultural production and by the presence of hydroelectric dams. As the river flows are largely influenced by the interannual variability of autumn and winter rainfall, the availability of a good seasonal forecast provides an efficient tool to minimize risks. The study addresses the analysis of the main climatic forcing of precipitation to design some statistical models to forecast autumn rainfall. Using monthly precipitation data for the period 1981–2017 from several national institutions and data of atmospheric variables from the NCEP/NCAR reanalysis, correlation maps have been used to define the best set of predictors. The multiple linear regression methodology was used to build predictive models. The main conclusion is that the South Atlantic Ocean High, the sea surface temperature of the Pacific and Indian Oceans and the polar jet are the most relevant predictors and the designed models have good skill. Fil: Vita Sanchez, Maximiliano Sergio. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: González, Marcela Hebe. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina Fil: Rolla, Alfredo Luis. Consejo Nacional de Investigaciones Científicas y ... Book Part South Atlantic Ocean CONICET Digital (Consejo Nacional de Investigaciones Científicas y Técnicas) Argentina Indian Pacific |
spellingShingle | Seasonal forecast Precipitation Statistical models https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 Vita Sanchez, Maximiliano Sergio González, Marcela Hebe Rolla, Alfredo Luis An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region |
title | An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region |
title_full | An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region |
title_fullStr | An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region |
title_full_unstemmed | An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region |
title_short | An Attempt to Forecast Seasonal Precipitation in the Comahue River Basins (Argentina) to Increase Productivity Performance in the Region |
title_sort | attempt to forecast seasonal precipitation in the comahue river basins (argentina) to increase productivity performance in the region |
topic | Seasonal forecast Precipitation Statistical models https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
topic_facet | Seasonal forecast Precipitation Statistical models https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
url | http://hdl.handle.net/11336/229769 |