Spatio-Seasonal Variations in Long-Term Trends of Offshore Wind Speeds Over the Black Sea; an Inter-Comparison of Two Reanalysis Data
Spatio-seasonal variability of long-term trends in mean and 95th percentile wind speeds for the term between 1979 and 2016, over the Black Sea is presented. Our aim is to contribute the existing literature by presenting the inhomogeneous spatial distribution of the long-term trends in both moderate...
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description | Spatio-seasonal variability of long-term trends in mean and 95th percentile wind speeds for the term between 1979 and 2016, over the Black Sea is presented. Our aim is to contribute the existing literature by presenting the inhomogeneous spatial distribution of the long-term trends in both moderate and severe wind speeds on a monthly basis. The analysis is conducted by using two different data; European Centre for Medium-Range Weather Forecasts-ERA-Interim and U.S. National Centers for Environmental Prediction-Climate Forecast System Reanalysis (CFSR) to perform a comparative analysis. The non-parametric Mann–Kendall and Sen’s Slope methods are used to determine the trends and their significance over the Black Sea. CFSR winds presented higher interannual variability than the ERA-Interim. ERA-Interim indicates that annual mean and 95th percentile wind speeds have decreasing trends down to − 0.17%/year and − 0.20%/year in the Sea of Azov, while they have an increasing trend up to 0.35%/year and 0.38%/year in the eastern part, respectively. Results indicate that wind speeds are increasing over 28% ~ 36% of the Black Sea surface area while the wind speeds are decreasing over 2% ~ 4% of the surface area. Pacific North American Oscillation presented an influence almost all over the Black Sea with statistically significant correlation coefficients over 0.5. North Atlantic Oscillation dominates over the southwestern, western and northern Black Sea with inverse correlation coefficients over 0.6. ERA-Interim and CFSR data illustrated a similar distribution pattern over the Black Sea in means of the relation of variations in wind speeds to the teleconnection indices. |
doi_str_mv | 10.1007/s00024-019-02361-7 |
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Our aim is to contribute the existing literature by presenting the inhomogeneous spatial distribution of the long-term trends in both moderate and severe wind speeds on a monthly basis. The analysis is conducted by using two different data; European Centre for Medium-Range Weather Forecasts-ERA-Interim and U.S. National Centers for Environmental Prediction-Climate Forecast System Reanalysis (CFSR) to perform a comparative analysis. The non-parametric Mann–Kendall and Sen’s Slope methods are used to determine the trends and their significance over the Black Sea. CFSR winds presented higher interannual variability than the ERA-Interim. ERA-Interim indicates that annual mean and 95th percentile wind speeds have decreasing trends down to − 0.17%/year and − 0.20%/year in the Sea of Azov, while they have an increasing trend up to 0.35%/year and 0.38%/year in the eastern part, respectively. Results indicate that wind speeds are increasing over 28% ~ 36% of the Black Sea surface area while the wind speeds are decreasing over 2% ~ 4% of the surface area. Pacific North American Oscillation presented an influence almost all over the Black Sea with statistically significant correlation coefficients over 0.5. North Atlantic Oscillation dominates over the southwestern, western and northern Black Sea with inverse correlation coefficients over 0.6. ERA-Interim and CFSR data illustrated a similar distribution pattern over the Black Sea in means of the relation of variations in wind speeds to the teleconnection indices.</description><identifier>ISSN: 0033-4553</identifier><identifier>EISSN: 1420-9136</identifier><identifier>DOI: 10.1007/s00024-019-02361-7</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Annual variations ; Atmospheric forcing ; Climate prediction ; Climate system ; Coefficients ; Comparative analysis ; Correlation coefficient ; Correlation coefficients ; Distribution ; Distribution patterns ; Earth and Environmental Science ; Earth Sciences ; Geophysics/Geodesy ; Interannual variability ; North Atlantic Oscillation ; Ocean-atmosphere system ; Offshore ; Regular Issue ; Sea surface ; Seasonal variability ; Seasonal variation ; Seasonal variations ; Spatial distribution ; Statistical analysis ; Surface area ; Trends ; Weather forecasting ; Wind ; Wind speed ; Winds</subject><ispartof>Pure and applied geophysics, 2020-06, Vol.177 (6), p.3013-3037</ispartof><rights>Springer Nature Switzerland AG 2019</rights><rights>Springer Nature Switzerland AG 2019.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a342t-545afb56d3107a00c43c0a1bb57b3ad1c4488725a281edbbf9ccef55d98d8b193</citedby><cites>FETCH-LOGICAL-a342t-545afb56d3107a00c43c0a1bb57b3ad1c4488725a281edbbf9ccef55d98d8b193</cites><orcidid>0000-0002-2227-4905 ; 0000-0002-8460-2839 ; 0000-0002-0394-6657</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00024-019-02361-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00024-019-02361-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,41486,42555,51317</link.rule.ids></links><search><creatorcontrib>Çarpar, Tunay</creatorcontrib><creatorcontrib>Ayat, Berna</creatorcontrib><creatorcontrib>Aydoğan, Burak</creatorcontrib><title>Spatio-Seasonal Variations in Long-Term Trends of Offshore Wind Speeds Over the Black Sea; an Inter-Comparison of Two Reanalysis Data</title><title>Pure and applied geophysics</title><addtitle>Pure Appl. Geophys</addtitle><description>Spatio-seasonal variability of long-term trends in mean and 95th percentile wind speeds for the term between 1979 and 2016, over the Black Sea is presented. Our aim is to contribute the existing literature by presenting the inhomogeneous spatial distribution of the long-term trends in both moderate and severe wind speeds on a monthly basis. The analysis is conducted by using two different data; European Centre for Medium-Range Weather Forecasts-ERA-Interim and U.S. National Centers for Environmental Prediction-Climate Forecast System Reanalysis (CFSR) to perform a comparative analysis. The non-parametric Mann–Kendall and Sen’s Slope methods are used to determine the trends and their significance over the Black Sea. CFSR winds presented higher interannual variability than the ERA-Interim. ERA-Interim indicates that annual mean and 95th percentile wind speeds have decreasing trends down to − 0.17%/year and − 0.20%/year in the Sea of Azov, while they have an increasing trend up to 0.35%/year and 0.38%/year in the eastern part, respectively. Results indicate that wind speeds are increasing over 28% ~ 36% of the Black Sea surface area while the wind speeds are decreasing over 2% ~ 4% of the surface area. Pacific North American Oscillation presented an influence almost all over the Black Sea with statistically significant correlation coefficients over 0.5. North Atlantic Oscillation dominates over the southwestern, western and northern Black Sea with inverse correlation coefficients over 0.6. ERA-Interim and CFSR data illustrated a similar distribution pattern over the Black Sea in means of the relation of variations in wind speeds to the teleconnection indices.</description><subject>Annual variations</subject><subject>Atmospheric forcing</subject><subject>Climate prediction</subject><subject>Climate system</subject><subject>Coefficients</subject><subject>Comparative analysis</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Distribution</subject><subject>Distribution patterns</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Geophysics/Geodesy</subject><subject>Interannual variability</subject><subject>North Atlantic Oscillation</subject><subject>Ocean-atmosphere system</subject><subject>Offshore</subject><subject>Regular Issue</subject><subject>Sea surface</subject><subject>Seasonal variability</subject><subject>Seasonal variation</subject><subject>Seasonal variations</subject><subject>Spatial distribution</subject><subject>Statistical analysis</subject><subject>Surface area</subject><subject>Trends</subject><subject>Weather forecasting</subject><subject>Wind</subject><subject>Wind speed</subject><subject>Winds</subject><issn>0033-4553</issn><issn>1420-9136</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kMtKAzEUhoMoWC8v4CrgOnpy68zgSusVCgVbdRnOzGTa0TYZk1HxAXxvUyu4c3Xg578cPkKOOJxwgOw0AoBQDHjBQMghZ9kWGXAlgBVcDrfJAEBKprSWu2QvxmcAnmW6GJCvaYd969nUYvQOl_QRQ7tWXKSto2Pv5mxmw4rOgnV1pL6hk6aJCx8sfWpdTaedtUmfvNtA-4WlF0usXmiqO6Po6J3rbWAjv-pSbRpY52cfnt5bTGOfsY30Ens8IDsNLqM9_L375OH6aja6ZePJzd3ofMxQKtEzrTQ2pR7WkkOGAJWSFSAvS52VEmteKZXnmdAocm7rsmyKqrKN1nWR13nJC7lPjje9XfCvbzb25tm_hfRJNEIlIomKkMklNq4q-BiDbUwX2hWGT8PBrHGbDW6TcJsf3CZLIbkJxWR2cxv-qv9JfQMHGYMV</recordid><startdate>20200601</startdate><enddate>20200601</enddate><creator>Çarpar, Tunay</creator><creator>Ayat, Berna</creator><creator>Aydoğan, Burak</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-2227-4905</orcidid><orcidid>https://orcid.org/0000-0002-8460-2839</orcidid><orcidid>https://orcid.org/0000-0002-0394-6657</orcidid></search><sort><creationdate>20200601</creationdate><title>Spatio-Seasonal Variations in Long-Term Trends of Offshore Wind Speeds Over the Black Sea; 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an Inter-Comparison of Two Reanalysis Data</atitle><jtitle>Pure and applied geophysics</jtitle><stitle>Pure Appl. Geophys</stitle><date>2020-06-01</date><risdate>2020</risdate><volume>177</volume><issue>6</issue><spage>3013</spage><epage>3037</epage><pages>3013-3037</pages><issn>0033-4553</issn><eissn>1420-9136</eissn><abstract>Spatio-seasonal variability of long-term trends in mean and 95th percentile wind speeds for the term between 1979 and 2016, over the Black Sea is presented. Our aim is to contribute the existing literature by presenting the inhomogeneous spatial distribution of the long-term trends in both moderate and severe wind speeds on a monthly basis. The analysis is conducted by using two different data; European Centre for Medium-Range Weather Forecasts-ERA-Interim and U.S. National Centers for Environmental Prediction-Climate Forecast System Reanalysis (CFSR) to perform a comparative analysis. The non-parametric Mann–Kendall and Sen’s Slope methods are used to determine the trends and their significance over the Black Sea. CFSR winds presented higher interannual variability than the ERA-Interim. ERA-Interim indicates that annual mean and 95th percentile wind speeds have decreasing trends down to − 0.17%/year and − 0.20%/year in the Sea of Azov, while they have an increasing trend up to 0.35%/year and 0.38%/year in the eastern part, respectively. Results indicate that wind speeds are increasing over 28% ~ 36% of the Black Sea surface area while the wind speeds are decreasing over 2% ~ 4% of the surface area. Pacific North American Oscillation presented an influence almost all over the Black Sea with statistically significant correlation coefficients over 0.5. North Atlantic Oscillation dominates over the southwestern, western and northern Black Sea with inverse correlation coefficients over 0.6. ERA-Interim and CFSR data illustrated a similar distribution pattern over the Black Sea in means of the relation of variations in wind speeds to the teleconnection indices.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s00024-019-02361-7</doi><tpages>25</tpages><orcidid>https://orcid.org/0000-0002-2227-4905</orcidid><orcidid>https://orcid.org/0000-0002-8460-2839</orcidid><orcidid>https://orcid.org/0000-0002-0394-6657</orcidid></addata></record> |
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subjects | Annual variations Atmospheric forcing Climate prediction Climate system Coefficients Comparative analysis Correlation coefficient Correlation coefficients Distribution Distribution patterns Earth and Environmental Science Earth Sciences Geophysics/Geodesy Interannual variability North Atlantic Oscillation Ocean-atmosphere system Offshore Regular Issue Sea surface Seasonal variability Seasonal variation Seasonal variations Spatial distribution Statistical analysis Surface area Trends Weather forecasting Wind Wind speed Winds |
title | Spatio-Seasonal Variations in Long-Term Trends of Offshore Wind Speeds Over the Black Sea; an Inter-Comparison of Two Reanalysis Data |
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