Improved long-term mean annual rainfall fields for Colombia

Authors

  • Oscar David Álvarez-Villa,

    1. School of Geosciences and Environment, Universidad Nacional de Colombia, Medellín, Antioquia, Colombia
    Current affiliation:
    1. Grupo de Hidrogeología, Universidad Politécnica de Valencia, Valencia, España.
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  • Jaime Ignacio Vélez,

    1. School of Geosciences and Environment, Universidad Nacional de Colombia, Medellín, Antioquia, Colombia
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  • Germán Poveda

    Corresponding author
    1. School of Geosciences and Environment, Universidad Nacional de Colombia, Medellín, Antioquia, Colombia
    • School of Geosciences and Environment, Universidad Nacional de Colombia, Medellín, Colombia.
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Abstract

With the aim of improving the long-term mean annual surface water balance of Colombia, four new annual average precipitation fields are estimated at 4 km spatial resolution. To put in context, a concise literature review of rainfall in Colombia is presented. For estimation purposes, diverse multivariate geostatistical methods are implemented by combining information from 1180 raingauges covering the period 1950-2005, and satellite data from the tropical rainfall measuring mission (TRMM) for the period 1999-2005, used as a drift for the following geostatistical methods: (1) kriging with an external drift (KED), (2) standardized cokriging (SCK), (3) colocated cokriging (CCK), and (4) Markov regionalization CCK (CCKM). To ensure the reliability of the estimated precipitation fields, a detailed cross-validation procedure is performed, including univariate and bivariate analyses of residuals, which allows us to conclude that the best estimated rainfall field is obtained with KED, and the worst with SCK. Visual analyses are also performed in the search for consistency of the resulting precipitation fields. Furthermore, local (at-a-pixel) uncertainty modelling analysis is performed using the indicator approach. Conditional cumulative distribution functions (CCDF) are estimated using indicator CCK with Bayes-Markov hypothesis. Statistical descriptors for the pixel's CCDFs are estimated based on the resulting precipitation fields, including long-term mean, conditional variance and the coefficient of variation. These improved precipitation fields along with their estimated uncertainties are available (http://cancerbero.unalmed.edu.co/∼hidrosig/index.php) for the scientific community and constitute useful basic information for diverse applications in water resources, agriculture, hydropower generation, human health, risks and disaster prevention, and many other applied sectors in Colombia. Copyright © 2010 Royal Meteorological Society

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