Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile

This work proposes a linear algorithm which relates precipitable water (PW) with altitude and distance from the coast, on a regional scale. For precipitable water, the ERA-Interim (ECMWF) database for the period 1989-2010 was used, while a digital elevation model was used for the geographical variab...

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Autores principales: Morales-Salinas,L, Parra-Aravena,J.C, Lang-Tasso,F, Abarca-Del Río,R, Jorquera-Fontena,E
Lenguaje:English
Publicado: Chilean Society of Soil Science / Sociedad Chilena de la Ciencia del Suelo 2012
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Acceso en línea:http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162012000200009
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spelling oai:scielo:S0718-951620120002000092012-09-10Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, ChileMorales-Salinas,LParra-Aravena,J.CLang-Tasso,FAbarca-Del Río,RJorquera-Fontena,E linear algorithm precipitable water digital elevation model This work proposes a linear algorithm which relates precipitable water (PW) with altitude and distance from the coast, on a regional scale. For precipitable water, the ERA-Interim (ECMWF) database for the period 1989-2010 was used, while a digital elevation model was used for the geographical variables. The results obtained indicate statistical significance between the two variables (p< 0.01), with a confidence level of 99%. The model makes it possible to describe the mean monthly space-time variability of precipitable water, stratifying the study area into clearly differentiated zones.info:eu-repo/semantics/openAccessChilean Society of Soil Science / Sociedad Chilena de la Ciencia del SueloJournal of soil science and plant nutrition v.12 n.2 20122012-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162012000200009en10.4067/S0718-95162012000200009
institution Scielo Chile
collection Scielo Chile
language English
topic linear algorithm
precipitable water
digital elevation model
spellingShingle linear algorithm
precipitable water
digital elevation model
Morales-Salinas,L
Parra-Aravena,J.C
Lang-Tasso,F
Abarca-Del Río,R
Jorquera-Fontena,E
Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile
description This work proposes a linear algorithm which relates precipitable water (PW) with altitude and distance from the coast, on a regional scale. For precipitable water, the ERA-Interim (ECMWF) database for the period 1989-2010 was used, while a digital elevation model was used for the geographical variables. The results obtained indicate statistical significance between the two variables (p< 0.01), with a confidence level of 99%. The model makes it possible to describe the mean monthly space-time variability of precipitable water, stratifying the study area into clearly differentiated zones.
author Morales-Salinas,L
Parra-Aravena,J.C
Lang-Tasso,F
Abarca-Del Río,R
Jorquera-Fontena,E
author_facet Morales-Salinas,L
Parra-Aravena,J.C
Lang-Tasso,F
Abarca-Del Río,R
Jorquera-Fontena,E
author_sort Morales-Salinas,L
title Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile
title_short Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile
title_full Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile
title_fullStr Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile
title_full_unstemmed Simple linear algorithm to estimate the space-time variability of precipitable water in the Araucanía Region, Chile
title_sort simple linear algorithm to estimate the space-time variability of precipitable water in the araucanía region, chile
publisher Chilean Society of Soil Science / Sociedad Chilena de la Ciencia del Suelo
publishDate 2012
url http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162012000200009
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