Vine copula models for predicting water flow discharge at King George Island, Antarctica

In order to understand the future behavior of the glaciers, their mass balance should be studied. The loss of water produced by melting, known as glacier discharge, is one of the components of this mass balance. In this paper, a vine copula structure is proposed to model the multivariate and nonline...

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Bibliographic Details
Main Authors: Gómez Díaz, Mario, Ausín Olivera, María Concepción, Domínguez, M. Carmen
Other Authors: Universidad Carlos III de Madrid. Departamento de Estadística
Format: Report
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10016/23812
Description
Summary:In order to understand the future behavior of the glaciers, their mass balance should be studied. The loss of water produced by melting, known as glacier discharge, is one of the components of this mass balance. In this paper, a vine copula structure is proposed to model the multivariate and nonlinear dependence among the glacier discharge and other related meteorological variables such as temperature, humidity, solar radiation and precipitation. The multivariate distribution of these variables is divided in four cases according to the presence or not of positive discharge and/or positive precipitation. Then, each different case is modelled with a vine copula. The conditional probability of zero discharge for given meteorological conditions is obtained from the proposed joint distribution. Moreover, the structure of the vine copula allows us to derive the conditional distribution for the glacier discharge for the given meteorological conditions. Three different prediction methods for the future values of the discharge are used and compared. The proposed methodology is applied to a large database collected since 2002 by the GLACKMA association from a measurement station located in the King George Island in the Antarctica. Seasonal effects are included by using different parameters for each season. We have found that the proposed vine copula model outperforms a previous work where we only used the temperature to predict the glacier discharge using a time- varying bivariate copula.