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  • CaliM&Ro project focuses on interpolation of spatial analysis of selected weather generator (WG) parameters which were abstracted from the observed time series of 125 stations of the Czech Hydrometeorological Institute. By now, we have tested GISbased methods (with the stress on kriging and cokriging), neural networks and the nearest neighbours method (Dubrovsky et al., EGU 2006; Dubrovsky et al., ECAC 2006). The aim of this paper is using the different GIS-based interpolation methods for the spatial analysis of WG parameters: kriging (kriging methods rely on the notion of autocorrelation as a function of distance), IDW (Inverse Distance Weighted -- each input point has a local influence that diminishes with distance) and spline (spline method fits a minimum-curvature surface through the input points). Due to its effect on various climatic characteristics, an altitude was found to significantly improve the quality of the interpolation. Specifically, in the GISbased interpolation, the altitude
  • CaliM&Ro project focuses on interpolation of spatial analysis of selected weather generator (WG) parameters which were abstracted from the observed time series of 125 stations of the Czech Hydrometeorological Institute. By now, we have tested GISbased methods (with the stress on kriging and cokriging), neural networks and the nearest neighbours method (Dubrovsky et al., EGU 2006; Dubrovsky et al., ECAC 2006). The aim of this paper is using the different GIS-based interpolation methods for the spatial analysis of WG parameters: kriging (kriging methods rely on the notion of autocorrelation as a function of distance), IDW (Inverse Distance Weighted -- each input point has a local influence that diminishes with distance) and spline (spline method fits a minimum-curvature surface through the input points). Due to its effect on various climatic characteristics, an altitude was found to significantly improve the quality of the interpolation. Specifically, in the GISbased interpolation, the altitude (en)
  • Cílem příspěvku bylo srovnat různé interpolační metody v prostředí GIS, Porovnány byly různé meteorologické prvky a provedena prostorová analýza pro vybrané měsíce. (cs)
Title
  • GIS-based interpolation of weather generator
  • GIS-based interpolation of weather generator (en)
  • Interpolace meteorologického generátoru založené na GIS (cs)
skos:prefLabel
  • GIS-based interpolation of weather generator
  • GIS-based interpolation of weather generator (en)
  • Interpolace meteorologického generátoru založené na GIS (cs)
skos:notation
  • RIV/62156489:43210/06:00104135!RIV07-GA0-43210___
http://linked.open.../vavai/riv/strany
  • 256;256
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA205/05/2265)
http://linked.open...iv/cisloPeriodika
  • 1
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 477101
http://linked.open...ai/riv/idVysledku
  • RIV/62156489:43210/06:00104135
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Inverse Distance Weighted; kriging; spline (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • NL - Nizozemsko
http://linked.open...ontrolniKodProRIV
  • [E39B06D444DD]
http://linked.open...i/riv/nazevZdroje
  • EMS Annual Meeting Abstracts
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 3
http://linked.open...iv/tvurceVysledku
  • Dubrovský, Martin
  • Semerádová, Daniela
  • Metelka, Ladislav
  • Halásová, Olga
issn
  • 1812-7053
number of pages
http://localhost/t...ganizacniJednotka
  • 43210
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