Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics

Maps of the long-term mean precipitation involving local landscape variables were generated for the Baltic countries, and the effectiveness of seven modelling methods was compared. The precipitation data were recorded in 245 meteorological stations in 1966–2005, and 51 location-related explanatory v...

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Main Authors: Kalle Remm, Jaak Jaagus, Agrita Briede, Egidijus Rimkus, Tiiu Kelviste
Format: Article
Language:English
Published: Estonian Academy Publishers 2011-08-01
Series:Estonian Journal of Earth Sciences
Subjects:
Online Access:http://www.kirj.ee/public/Estonian_Journal_of_Earth_Sciences/2011/issue_3/earth-2011-3-172-190.pdf
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spelling doaj-502ed107d8724156bf9881449919c1dc2020-11-24T20:51:33ZengEstonian Academy PublishersEstonian Journal of Earth Sciences1736-47282011-08-0160317219010.3176/earth.2011.3.05Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristicsKalle RemmJaak JaagusAgrita BriedeEgidijus RimkusTiiu KelvisteMaps of the long-term mean precipitation involving local landscape variables were generated for the Baltic countries, and the effectiveness of seven modelling methods was compared. The precipitation data were recorded in 245 meteorological stations in 1966–2005, and 51 location-related explanatory variables were used. The similarity-based reasoning in the Constud software system outperformed other methods according to the validation fit, except for spring. The multivariate adaptive regression splines (MARS) was another effective method on average. The inclusion of landscape variables, compared to reverse distance-weighted interpolation, highlights the effect of uplands, larger water bodies and forested areas. The long-term mean amount of precipitation, calculated as the station average, probably underestimates the real value for Estonia and overestimates it for Lithuania due to the uneven distribution of observation stations.http://www.kirj.ee/public/Estonian_Journal_of_Earth_Sciences/2011/issue_3/earth-2011-3-172-190.pdfprecipitationlandscape variablesdata miningBaltic countries.
collection DOAJ
language English
format Article
sources DOAJ
author Kalle Remm
Jaak Jaagus
Agrita Briede
Egidijus Rimkus
Tiiu Kelviste
spellingShingle Kalle Remm
Jaak Jaagus
Agrita Briede
Egidijus Rimkus
Tiiu Kelviste
Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
Estonian Journal of Earth Sciences
precipitation
landscape variables
data mining
Baltic countries.
author_facet Kalle Remm
Jaak Jaagus
Agrita Briede
Egidijus Rimkus
Tiiu Kelviste
author_sort Kalle Remm
title Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
title_short Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
title_full Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
title_fullStr Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
title_full_unstemmed Interpolative mapping of mean precipitation in the Baltic countries by using landscape characteristics
title_sort interpolative mapping of mean precipitation in the baltic countries by using landscape characteristics
publisher Estonian Academy Publishers
series Estonian Journal of Earth Sciences
issn 1736-4728
publishDate 2011-08-01
description Maps of the long-term mean precipitation involving local landscape variables were generated for the Baltic countries, and the effectiveness of seven modelling methods was compared. The precipitation data were recorded in 245 meteorological stations in 1966–2005, and 51 location-related explanatory variables were used. The similarity-based reasoning in the Constud software system outperformed other methods according to the validation fit, except for spring. The multivariate adaptive regression splines (MARS) was another effective method on average. The inclusion of landscape variables, compared to reverse distance-weighted interpolation, highlights the effect of uplands, larger water bodies and forested areas. The long-term mean amount of precipitation, calculated as the station average, probably underestimates the real value for Estonia and overestimates it for Lithuania due to the uneven distribution of observation stations.
topic precipitation
landscape variables
data mining
Baltic countries.
url http://www.kirj.ee/public/Estonian_Journal_of_Earth_Sciences/2011/issue_3/earth-2011-3-172-190.pdf
work_keys_str_mv AT kalleremm interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics
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AT agritabriede interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics
AT egidijusrimkus interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics
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