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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Estonian Academy Publishers
2011-08-01
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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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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 AT jaakjaagus interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics AT agritabriede interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics AT egidijusrimkus interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics AT tiiukelviste interpolativemappingofmeanprecipitationinthebalticcountriesbyusinglandscapecharacteristics |
_version_ |
1716801780012023808 |