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  • Conventional interpolation methods for precipitation estimation use well-known al- gorithms such as Thiessen polygons or kriginig, which recalculate point precipitation measurement into a grid form. One of the advantages of the method is using relatively accurate precipitation data; thereafter the estimated neighbouring values of a precipi- tation measurement station represent the disadvantage. The standard method used in meteorology is optimal interpolation one, i.e. interpola- tion of new observed values into so-called ?preliminary eld? based on autocorrela- tion analysis, (mean ?information effect? analysis of new observed values according to measurement errors and according to variability of analysed eld). This method includes calculations of various factors, which inuence precipitation eld. The contribution presents basic geostatistical methods for precipitation interpolation using diverse software (GRASS GIS, ArcGIS, GSTAT, ISATIS). Investigated out- comes are compared with optimal i
  • Conventional interpolation methods for precipitation estimation use well-known al- gorithms such as Thiessen polygons or kriginig, which recalculate point precipitation measurement into a grid form. One of the advantages of the method is using relatively accurate precipitation data; thereafter the estimated neighbouring values of a precipi- tation measurement station represent the disadvantage. The standard method used in meteorology is optimal interpolation one, i.e. interpola- tion of new observed values into so-called ?preliminary eld? based on autocorrela- tion analysis, (mean ?information effect? analysis of new observed values according to measurement errors and according to variability of analysed eld). This method includes calculations of various factors, which inuence precipitation eld. The contribution presents basic geostatistical methods for precipitation interpolation using diverse software (GRASS GIS, ArcGIS, GSTAT, ISATIS). Investigated out- comes are compared with optimal i (en)
  • Tradiční interpolační metody pro odhad srážek využívají známé algoritmy (např. Thiessonovy polygony, krigování), podle kterých jsou srážkoměrná měření přepočítávána do sítě bodů v ploše. Jednou z výhod této metody je, že využívá relativně přesná srážkoměrná data, nevýhodou pak je, že se musí odhadovat hodnoty v okolí stanice. Běžnou metodou využívanou v meteorologii je optimální interpolace. Tento příspěvek ukazuje výsledky různých interpolačních metod s využitím různého programového vybavení (GRASS, ArcGIS, GSTAT, ISATIS). (cs)
Title
  • Using interpolation methods for precipitation estimation
  • Využití interpolačních metod pro odhad srážek (cs)
  • Using interpolation methods for precipitation estimation (en)
skos:prefLabel
  • Using interpolation methods for precipitation estimation
  • Využití interpolačních metod pro odhad srážek (cs)
  • Using interpolation methods for precipitation estimation (en)
skos:notation
  • RIV/61989100:27350/07:00016453!RIV09-MSM-27350___
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  • 457012
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  • RIV/61989100:27350/07:00016453
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  • interpolation; precipitation; geostatistics (en)
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  • [DF545B5A1749]
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  • San Lorenzo de El Escorial
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  • Berlin
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  • Juřikovská, Lucie
  • Šeděnková, Monika
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issn
  • 1812-7053
number of pages
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  • European Meteorological Society
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  • 27350
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