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dc.contributor.author
Otero, Federico  
dc.contributor.author
Araneo, Diego Christian  
dc.date.available
2024-12-26T10:28:58Z  
dc.date.issued
2023-09  
dc.identifier.citation
Otero, Federico; Araneo, Diego Christian; Synoptic fingerprints of Zonda wind from a statistical prediction model; John Wiley & Sons Ltd; International Journal of Climatology; 43; 15; 9-2023; 6946-6962  
dc.identifier.issn
0899-8418  
dc.identifier.uri
http://hdl.handle.net/11336/251202  
dc.description.abstract
Zonda wind is a typical downslope windstorm over the eastern slopes of the Central Andes in Argentina, which produces extremely warm and dry conditions and has substantial socioeconomic impacts. In this study, we propose a new statistical model for Zonda prediction based on the “synoptic fingerprints” of atmospheric diagnostic variables from ERA5. The model combines principal component analysis (PCA) and logistic regression to establish a relationship between the observed occurrence and the PCA loading component of a predictor variable. This approach enables us to determine the probability of Zonda occurrence at selected stations and identify the synoptic structure features (fingerprints) associated with Zonda events. The obtained fields successfully discriminate between Zonda and non-Zonda events, suggesting that the available information in the reanalysis data is sufficient for predicting the presence of Zonda. The synoptic fingerprints generated by the model reveal a cross-barrier pressure gradient resulting from a negative geopotential height anomaly at low levels. The cross-barrier flow remains unimpeded by the Andes, leading to forced vertical motions on the windward side, accompanied by cooling and precipitation. On the lee side, sinking motions, warming and drying are observed, further facilitated by favourable mid- and upper-level conditions that establish the Zonda wind. The model performs comparably to previous research, with the best results achieved using low-level variables as predictors. Key performance measures, including the area under the receiver operating curve (ROC) (AUC) of 0.9468 and a Brier score lower than 0.1, demonstrate the model´s effectiveness. Using a 0.5 threshold, the accuracy, F1 score and correct alarm ratio (CAR) all exceed 88%, with a probability of detection (POD) higher than 90%. Studies on this type of downslope windstorm are scarce in South America, making this work a significant contribution to understanding synoptic-scale atmospheric structures associated with Zonda occurrences.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
John Wiley & Sons Ltd  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Zonda wind  
dc.subject
Foehn  
dc.subject
Downslope windstorm  
dc.subject
Statistical Models  
dc.subject.classification
Meteorología y Ciencias Atmosféricas  
dc.subject.classification
Ciencias de la Tierra y relacionadas con el Medio Ambiente  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Synoptic fingerprints of Zonda wind from a statistical prediction model  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-12-17T17:40:22Z  
dc.journal.volume
43  
dc.journal.number
15  
dc.journal.pagination
6946-6962  
dc.journal.pais
Reino Unido  
dc.journal.ciudad
Londres  
dc.description.fil
Fil: Otero, Federico. 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  
dc.description.fil
Fil: Araneo, Diego Christian. 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  
dc.journal.title
International Journal of Climatology  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.8244  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1002/joc.8244