AUTHOR=Akçay Fatma , Bingölbali Bilal , Akpınar Adem , Kankal Murat 

TITLE=Trend detection by innovative polygon trend analysis for winds and waves

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2022.930911

DOI=10.3389/fmars.2022.930911

ISSN=2296-7745

ABSTRACT=This study focuses on trend detection for monthly mean and maximum wind speed (WS) and significant wave height (SWH) at locations selected on coastal areas of the Black Sea. Wind and wave parameters were obtained from 42-year long-term SWAN simulations forced by the Climate Forecast System Reanalysis (CFSR) at 33 Black Sea coastal locations. Monthly mean and maximum WS and SWH were calculated as climatological variables at all locations. The Mann-Kendall as a traditional test and the Innovative Polygon Trend Analysis (IPTA) as an innovative test were used to examine long-term monthly trends. The IPTA approach symbolizes the one-year behavior of the time series and gives information about the transitions between the months. The Mann-Kendall test showed no trends in mean SWH, maximum SWH, mean WS, and maximum WS for more than 70% of the months studied. The IPTA, on the other hand, detected more trends in the analyzed months. Decreasing trends in 34% and increasing trends in 35% were detected of the months analyzed for mean SWH and maximum SWH, respectively according to IPTA.The lowest (highest) values were seen in summer (winter), according to a one-year cycle on the IPTA template for all variables. The decreasing trends in May, July, and November-December periods draw attention in most locations considering the IPTA in analyzing mean SWH. The polygon graphs of the maximum SWH were obtained in a more complex structure and generally with more than two cycles. According to both trend methods, most of the months showed a decreasing trend at locations (28, 30, and 31) located on the inner continental shelf of the southwestern part of the Black Sea and locations (4 and 7) in the southeastern region for mean WS. The polygon graphs of the maximum WS were found to be narrower than the other variables. This indicates that the values of the months are close to each other, so the months show similar behavior.