Publication: Trend detection by innovative polygon trend analysis for winds and waves
dc.contributor.buuauthor | Akcay, Fatma | |
dc.contributor.buuauthor | Bingölbali, Bilal | |
dc.contributor.buuauthor | BİNGÖLBALİ, BİLAL | |
dc.contributor.buuauthor | Akpınar, Adem | |
dc.contributor.buuauthor | AKPINAR, ADEM | |
dc.contributor.buuauthor | Kankal, Murat | |
dc.contributor.buuauthor | KANKAL, MURAT | |
dc.contributor.department | İnegöl Meslek Yüksekokulu | |
dc.contributor.department | İnşaat Mühendisliği Bölümü | |
dc.contributor.orcid | 0000-0003-4496-5974 | |
dc.contributor.orcid | 0000-0002-9042-6851 | |
dc.contributor.orcid | 0000-0003-0897-4742 | |
dc.contributor.researcherid | AAZ-6851-2020 | |
dc.contributor.researcherid | AAC-6763-2019 | |
dc.date.accessioned | 2024-10-02T06:11:49Z | |
dc.date.available | 2024-10-02T06:11:49Z | |
dc.date.issued | 2022-08-10 | |
dc.description.abstract | It is known that densely populated coastal areas may be adversely affected as a result of the climate change effects. In this respect, for coastal protection, utilization, and management it is critical to understand the changes in wind speed (WS) and significant wave height (SWH) in coastal areas. Innovative approaches, which are one of the trend analysis methods used as an effective way to examine these changes, have started to be used very frequently in many fields in recent years, although not in coastal and marine engineering. The Innovative Polygon Trend Analysis (IPTA) method provides to observe the one-year behavior of the time series by representing the changes between consecutive months as well as determining the trends in each individual month. It is not also affected by constraints such as data length, distribution type or serial correlation. Therefore, the main objective of this study is to investigate whether using innovative trend methods compared to the traditional methods makes a difference in trends of the climatological variables. For this goal, trends of mean and maximum WS and SWH series for each month at 33 coastal locations in Black Sea coasts were evaluated. Wind and wave parameters WS and SWH were obtained from 42-year long-term wave simulations using Simulating Waves Nearshore (SWAN) model forced by the Climate Forecast System Reanalysis (CFSR). Monthly mean and maximum WS and SWH were calculated at all locations and then trend analyses using both traditional and innovative methods were performed. Low occurrence of trends were detected for mean SWH, maximum SWH, mean WS, and maximum WS according to the Mann-Kendall test in the studied months. The IPTA method detected more trends, such as the decreasing trend of the mean SWH at most locations in May, July and November December. The lowest (highest) values were seen in summer (winter), according to a one-year cycle on the IPTA template for all variables. According to both methods, most of the months showed a decreasing trend for the mean WS at some locations in the inner continental shelf of the southwestern and southeastern Black Sea. The IPTA method can capture most of the trends detected by the Mann-Kendall method, and more missed by the latter method. | |
dc.identifier.doi | 10.3389/fmars.2022.930911 | |
dc.identifier.uri | https://doi.org/10.3389/fmars.2022.930911 | |
dc.identifier.uri | https://hdl.handle.net/11452/45636 | |
dc.identifier.volume | 9 | |
dc.identifier.wos | 000843931800001 | |
dc.indexed.wos | WOS.SCI | |
dc.language.iso | en | |
dc.publisher | Frontiers Media Sa | |
dc.relation.journal | Frontiers In Marine Science | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi | |
dc.relation.tubitak | 214M436 | |
dc.subject | Coastal regions | |
dc.subject | Ocean wind | |
dc.subject | Model | |
dc.subject | Swan | |
dc.subject | Variability | |
dc.subject | Identification | |
dc.subject | Simulation | |
dc.subject | Extremes | |
dc.subject | Height | |
dc.subject | Monthly trend analysis | |
dc.subject | Innovative polygon trend analysis | |
dc.subject | Mann-kendall test | |
dc.subject | Significant wave height | |
dc.subject | Wind speed | |
dc.subject | Black sea | |
dc.subject | Science & technology | |
dc.subject | Life sciences & biomedicine | |
dc.subject | Environmental sciences | |
dc.subject | Marine & freshwater biology | |
dc.title | Trend detection by innovative polygon trend analysis for winds and waves | |
dc.type | Article | |
dspace.entity.type | Publication | |
local.contributor.department | Mühendislik Fakültesi/İnşaat Mühendisliği Bölümü | |
local.contributor.department | İnegöl Meslek Yüksekokulu | |
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relation.isAuthorOfPublication | 875454d9-443c-4a31-9bce-5442b8431fdb | |
relation.isAuthorOfPublication.latestForDiscovery | eae8fad3-a39c-4f74-b0a3-dc174fdc76ad |