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Abstract:

This paper investigates the detection of particular conditions in which the surface air temperature shows evidence an increased predictability for periods greater than five days. Analysis was performed on the maximum and minimum pentad temperature anomalies at San Miguel de Tucumán (1891-2007). To investigate the conditions, conditional-entropy and mutual-information metrics coupled with a cluster-analysis algorithm are proposed. Using these methodologies, it is possible to detect defined trajectories where the entropy of certain transitions decreases significantly. These decreases imply an increase in the predictability under these defined trajectories. Few weather patterns associated with enhanced predictability exist. It is mostly the warm and humid events that have these characteristics. Additionally, particular periods during which physical processes tend to vary more slowly and produce greater predictability structures can be found through local analysis of mutual information. For these periods, the predictability can be two times greater than the average. Additionally, these events tend to show a seasonal behavior, appearing mainly during the winter and spring. © 2012 Nova Science Publishers, Inc. All Rights Reserved.

Registro:

Documento: Parte de libro
Título:Detection of five-day to one-month surface air temperature predictability using information theory
Autor:Naumann, G.; Vargas, W.M.
Filiación:National Scientific and Technological Research Council (CONICET), Department of Atmospheric and Oceanic Sciences, University of Buenos Aires, Intendente Güiraldes 2160 - Pab II, 20 floor, Buenos Aires C1428EGA, Argentina
Año:2012
Página de inicio:93
Página de fin:106
Título revista:Climatology: New Developments
Título revista abreviado:Clim.: New Dev.
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816210_v_n_p93_Naumann

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Citas:

---------- APA ----------
Naumann, G. & Vargas, W.M. (2012) . Detection of five-day to one-month surface air temperature predictability using information theory. Climatology: New Developments, 93-106.
Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816210_v_n_p93_Naumann [ ]
---------- CHICAGO ----------
Naumann, G., Vargas, W.M. "Detection of five-day to one-month surface air temperature predictability using information theory" . Climatology: New Developments (2012) : 93-106.
Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816210_v_n_p93_Naumann [ ]
---------- MLA ----------
Naumann, G., Vargas, W.M. "Detection of five-day to one-month surface air temperature predictability using information theory" . Climatology: New Developments, 2012, pp. 93-106.
Recuperado de https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816210_v_n_p93_Naumann [ ]
---------- VANCOUVER ----------
Naumann, G., Vargas, W.M. Detection of five-day to one-month surface air temperature predictability using information theory. Clim.: New Dev. 2012:93-106.
Available from: https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_97816210_v_n_p93_Naumann [ ]