Innovative Polygonal Trend Analysis (IPTA) in detecting the seasonal trend behavior of statistically downscaled precipitation for the Eastern Black Sea Basin of Turkey

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  • SDG 6 · Temiz Su ve Sanitasyon
  • SDG 13 · İklim Eylemi

Özet

This study compares projected and past seasonal precipitation trends in the Eastern Black Sea Basin, Turkey. Historical data from twelve stations representing the basin during 1981–2010 was used, while statistically downscaled data from two representative concentration pathway scenarios (RCP4.5 and RCP8.5) outputs of the GFDL-ESM2M general circulation model were utilized for 2021–2050. To determine the seasonal trend behaviors of precipitation variables and transitions between consecutive months, the Innovative Polygon Trend Analysis (IPTA) was implemented. Furthermore, the star concept was employed to illustrate the changing sizes between consecutive periods. Both scenarios showed considerable summer and autumn declines at almost all locations, with low seasonal precipitation variability. These scenarios indicated January to be the important month for trend shift, except for Rize, Pazar, and Hopa stations. The formation of several polygons, polygons intersecting, and polygons not forming on the global regression line show that the hydro-climatic cycle might be chaotic.

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dc.contributor.authorNacar, Sinan
dc.contributor.authorŞan, Murat
dc.contributor.authorKankal, Murat
dc.contributor.authorOkkan, Umut
dc.date.accessioned2026-10-22T10:22:42.555853487Z
dc.date.available2026-10-22T10:22:42.555853487Z
dc.date.issued2024
dc.description.abstractThis study compares projected and past seasonal precipitation trends in the Eastern Black Sea Basin, Turkey. Historical data from twelve stations representing the basin during 1981–2010 was used, while statistically downscaled data from two representative concentration pathway scenarios (RCP4.5 and RCP8.5) outputs of the GFDL-ESM2M general circulation model were utilized for 2021–2050. To determine the seasonal trend behaviors of precipitation variables and transitions between consecutive months, the Innovative Polygon Trend Analysis (IPTA) was implemented. Furthermore, the star concept was employed to illustrate the changing sizes between consecutive periods. Both scenarios showed considerable summer and autumn declines at almost all locations, with low seasonal precipitation variability. These scenarios indicated January to be the important month for trend shift, except for Rize, Pazar, and Hopa stations. The formation of several polygons, polygons intersecting, and polygons not forming on the global regression line show that the hydro-climatic cycle might be chaotic.
dc.identifier.doi10.1080/1573062x.2024.2312496
dc.identifier.eissn1744-9006
dc.identifier.endpage418
dc.identifier.issn1573-062X
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85184864357
dc.identifier.startpage406
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/14440
dc.identifier.volume21
dc.identifier.wosWOS:001159886000001
dc.language.isoen
dc.publisherTaylor and Francis Ltd.
dc.relation.ispartofUrban Water Journal
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectClimate change
dc.subjectEastern Black Sea Basin
dc.subjectInnovative polygon trend method (IPTA)
dc.subjectstar concept
dc.subject.classificationWater Resources
dc.subject.otherTurkey
dc.subject.otherclimate change
dc.subject.otherdetection method
dc.subject.otherdownscaling
dc.subject.othergeneral circulation model
dc.subject.otherhydrometeorology
dc.subject.otherinnovation
dc.subject.otherpolygon
dc.subject.otherprecipitation (climatology)
dc.subject.othertrend analysis
dc.subject.otherweather forecasting
dc.titleInnovative Polygonal Trend Analysis (IPTA) in detecting the seasonal trend behavior of statistically downscaled precipitation for the Eastern Black Sea Basin of Turkey
dc.typeArticle
rdl.citation.openalex16
rdl.citation.scopus12
rdl.citation.wos12
rdl.oa.statusclosed
rdl.scopus.quartileQ2
rdl.sdgSDG13
rdl.sdgSDG06
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)