Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark

Bibliographic Details
Main Author: Ribeiro, Sara
Publication Date: 2017
Other Authors: Caineta, J., Costa, Ana Cristina
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/130707
Summary: Ribeiro, S., Caineta, J., & Costa, A. C. (2017). Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark. In J. J. Gómez-Hernández, J. Rodrigo-Ilarri, E. Cassiraga, M. E. Rodrigo-Clavero, & J. A. Vargas-Guzmán (Eds.), Geostatistics Valencia 2016 (pp. 909-918). (Quantitative Geology and Geostatistics; Vol. 16). Springer. DOI: 10.1007/978-3-319-46819-8_63 ----------------------------- The authors gratefully acknowledge the financial support of Fundação para a Ciência e Tecnologia (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 (“GSIMCLI – Geostatistical simulation with local distributions for the homogenization and interpolation of climate data”).
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spelling Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME BenchmarkPerformance MetricsHomogenisation MethodCandidate StationCorrection ParameterProbability density functionRibeiro, S., Caineta, J., & Costa, A. C. (2017). Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark. In J. J. Gómez-Hernández, J. Rodrigo-Ilarri, E. Cassiraga, M. E. Rodrigo-Clavero, & J. A. Vargas-Guzmán (Eds.), Geostatistics Valencia 2016 (pp. 909-918). (Quantitative Geology and Geostatistics; Vol. 16). Springer. DOI: 10.1007/978-3-319-46819-8_63 ----------------------------- The authors gratefully acknowledge the financial support of Fundação para a Ciência e Tecnologia (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 (“GSIMCLI – Geostatistical simulation with local distributions for the homogenization and interpolation of climate data”).Nowadays, climate data series are used in so many different studies that their importance implies the essential need of good data quality. For this reason, the process of homogenisation became a hot topic in the last decades, and many researchers have focused on developing efficient methods for the detection and correction of inhomogeneities in climate data series. This study evaluates the efficiency of the gsimcli homogenisation method, which is based on a geostatistical simulation approach. For each instant in time, gsimcli uses the direct sequential simulation algorithm to generate several equally probable realisations of the climate variable at the candidate station’s location, disregarding its values. The probability density function estimated at the candidate station’s location (local probability density functions (PDF)), for each instant in time, is then used to verify the existence of inhomogeneities in the candidate time series. When an inhomogeneity is detected, that value is replaced by a statistical value (correction parameter) derived from the estimated local PDF. In order to assess the gsimcli efficiency with different implementation strategies, we homogenised monthly precipitation data from an Austrian network of the COST-HOME benchmark data set (COST Action ES0601, Advances in homogenization methods of climate series: an integrated approach – HOME). The following parameters were tested: grid cell size, candidate order in the homogenisation process, local radius parameter, detection parameter and correction parameter. Performance metrics were computed to assess the efficiency of gsimcli. The results show the high influence of the grid cell size and of the correction parameter in the method’s performance.SpringerNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNRibeiro, SaraCaineta, J.Costa, Ana Cristina2022-01-12T23:10:20Z20172017-01-01T00:00:00Zbook partinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10362/130707eng978-3-319-46818-1PURE: 3627440https://doi.org/10.1007/978-3-319-46819-8_63info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:58:04Zoai:run.unl.pt:10362/130707Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:29:17.952674Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
title Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
spellingShingle Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
Ribeiro, Sara
Performance Metrics
Homogenisation Method
Candidate Station
Correction Parameter
Probability density function
title_short Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
title_full Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
title_fullStr Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
title_full_unstemmed Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
title_sort Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark
author Ribeiro, Sara
author_facet Ribeiro, Sara
Caineta, J.
Costa, Ana Cristina
author_role author
author2 Caineta, J.
Costa, Ana Cristina
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Ribeiro, Sara
Caineta, J.
Costa, Ana Cristina
dc.subject.por.fl_str_mv Performance Metrics
Homogenisation Method
Candidate Station
Correction Parameter
Probability density function
topic Performance Metrics
Homogenisation Method
Candidate Station
Correction Parameter
Probability density function
description Ribeiro, S., Caineta, J., & Costa, A. C. (2017). Assessing the Performance of the Gsimcli Homogenisation Method with Precipitation Monthly Data from the COST-HOME Benchmark. In J. J. Gómez-Hernández, J. Rodrigo-Ilarri, E. Cassiraga, M. E. Rodrigo-Clavero, & J. A. Vargas-Guzmán (Eds.), Geostatistics Valencia 2016 (pp. 909-918). (Quantitative Geology and Geostatistics; Vol. 16). Springer. DOI: 10.1007/978-3-319-46819-8_63 ----------------------------- The authors gratefully acknowledge the financial support of Fundação para a Ciência e Tecnologia (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 (“GSIMCLI – Geostatistical simulation with local distributions for the homogenization and interpolation of climate data”).
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01T00:00:00Z
2022-01-12T23:10:20Z
dc.type.driver.fl_str_mv book part
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/130707
url http://hdl.handle.net/10362/130707
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-3-319-46818-1
PURE: 3627440
https://doi.org/10.1007/978-3-319-46819-8_63
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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