ERA5 ve ERA-INTERİM RÜZGARLARI İLE ÇALIŞTIRILAN SWAN MODEL SONUÇLARININ PERFORMANS ANALİZİ

Yıl 2020, Cilt: 25 Sayı: 1, 65 - 80, 30.04.2020

Emre Çalışır , Adem Akpınar

https://doi.org/10.17482/uumfd.688805

Cited By: 1

Öz

Bu çalışmada, Avrupa Orta Vadeli Hava Tahmin Merkezi (ECMWF)’nin yeni yeniden değerlendirme (reanaliz) veri setinin Karadeniz bölgesi dalga tahminine katkı yapıp yapmadığı araştırılmıştır. Bu maksatla, ECMWF’in veri tabanından hem ERA5 hem de mukayese yapmak maksadıyla ERA-Interim veri setlerinin rüzgar verileri indirilmiştir. Performans değerlendirilmesi için dalga tahminlerini gerçekleştirmek maksadı ile bu rüzgar verisini kullanan üçüncü nesil dalga tahmin modeli olan SWAN varsayılan ayarlamalı olarak çalıştırılmıştır. Varsayılan ayarlamalı SWAN simülasyonu sonucunda belirgin dalga yüksekliği (Hm0), ortalama dalga periyodu (Tm02) ve ortalama dalga yönü gibi dalga parametreleri elde edilmiştir. Bu tahminler 1996 yılında NATO TU-WAVES projesi kapsamında Karadeniz’e kurulan şamandıra ölçüm istasyonlarından üçünün (Gelendzhik, Hopa, Sinop) dalga ölçümleri ile kıyaslanarak performansları irdelenmiştir. Performans değerlendirmesi sırasında hata istatistiği parametreleri, zaman serisi grafikleri, saçılım diyagramları, kuantil grafikleri ve dalga gülleri incelenmiştir. Hata istatistiği parametrelerinde örneğin Hopa şamandıra ölçüm verisi ile model veri setleri kıyaslandığında, belirgin dalga yüksekliğinde gözlenen ortalamaların farkı (bias) ERA-Interim veri setinde 0,317 m iken ERA5 veri setinde 0,261 m değerini almıştır. Tüm bu değerlendirme süreci sonucunda ise, Karadeniz özelinde ECMWF tarafından son yıllarda üretilmiş ERA5 model rüzgarlarının dalga modellerine girdi olarak tanımlandığında ERA-Interim rüzgarlarına kıyasla daha doğru dalga tahmini sağladığı sonucuna varılmıştır.

Anahtar Kelimeler

ERA5, ERA-Interim, SWAN model, Karadeniz

Teşekkür

Çalışma kapsamında kullanılan dalga tahmin modeli için Delft Üniversitesi SWAN araştırma grubuna, çalışmada kullanılan rüzgar verileri olan ERA5 ve ERA-Interim için ECMWF’ye, Karadeniz’in batimetrisini temin ettiğimiz GEBCO’ya, gerekli olan şamandıra ölçüm verilerinin paylaşımından dolayı NATO TU-WAVES Projesinin yürütücüsü Prof. Dr. Erdal Özhan’a ve bu projeye desteklerinden ötürü NATO İstikrar İçin Bilim Programına teşekkür ederiz.

Performance analysis of the SWAN model results forced with the ERA5 and ERA-Interim winds

Öz

This study investigated whether a new re-analysis of ECMWF contributes to wave hindcast performance in the Black Sea. For this purpose, ERA5 and ERA-Interim winds presented by ECMWF were downloaded in order to have an inter-comparison of ECMWF datasets. For performance evaluation of wave hindcasts, third generation wave hindcast model SWAN was run with a default setting. Wave hindcast outputs such as significant wave height (Hm0), mean wave period (Tm02) and mean wave direction were obtained as a result of default setting SWAN run. These hindcasts were compared with wave measurements at three buoys (Gelendzhik, Hopa, Sinop) installed in the Black Sea in 1996 as part of NATO TU-WAVES project. During performance evaluation, error statistics, time series, scatter plots, quantile graphics and wave roses were examined. In error statistics, for example bias observed for Hm0 compared to measurement and model data at Hopa was 0.317 m for ERA-Interim forcing and 0.261 m for ERA5 forcing. As a result of this all evaluation process, it was revealed that in the Black Sea ERA5 produced in the recent years by ECMWF presents a more advanced wind data set in comparison to the ERA-Interim winds because default setting SWAN model performs better in the case of ERA5 winds.

Anahtar Kelimeler

ERA5, ERA-Interim, SWAN model, Black Sea

Kaynakça

• 1. Appendini CM, Torres-Freyermuth A, Oropeza F, Salles P, Lopez J, Mendoza ET. (2012) Wave modelling performance in the Gulf of Mexico and Western Caribbean: wind reanalysis assessment. Applied Ocean Research, 39, 20–30. doi:10.1016/j.apor.2012.09.004
• 2. Ardhuin F, Bertotti L, Bidlot J-R, Cavaleri L, Filipetto V, Lefevre J-M, Wittman P. (2007) Comparison of wind and wave measurements and models in the Western Mediterranean Sea. Ocean Engineering, 34, 526–541. doi:10.1016/j.oceaneng.2006.02.008
• 3. Battjes, J.A, Janssen, J.P.F.M. (1978) Energy loss and set-up due to breaking of random waves. Proceedings of the Sixth Conference on Coastal Engineering, ASCE, 569-587. doi:10.1061/9780872621909.034
• 4. Bolanos-Sanchez R, Sanchez-Arcilla A, Cateura J. (2007) Evaluation of two atmospheric models for wind-wave modelling in the NW Mediterranean, Journal of Marine Systems, 65, 336–353. doi:10.1016/j.jmarsys.2005.09.014
• 5. Booij N, Holthuijsen LH, Ris RC. (1999) A third-generation wave model for coastal regions. Model description and validation, Journal of Geophysical Research, 104(C4), 7649–7666. doi:10.1029/98JC02622
• 6. Caires S, Sterl A, Bidlot JR, Graham N, Swail V. (2004) Intercomparison of different wind–wave reanalysis. Journal of Climate, 17(10), 1893–1913. doi:10.1175/1520-0442(2004)017<1893:IODWR>2.0.CO;2
• 7. Cavaleri, L. ve Sclavo, M. (2006) The calibration of wind and wave model data in the Mediterranean Sea, Coastal Engineering, 53, 613-627. doi:10.1016/j.coastaleng.2005.12.006
• 8. Chelton DB, Freilich MH. (2005) Scatterometer-based assessment of 10-m wind analyses from the operational ECMWF and NCEP numerical weather prediction models, Monthly Weather Review, 133, 409–429. doi:10.1175/MWR-2861.1
• 9. Durrant TH, Greenslade DJM, Simmonds I. (2013) The effect of statistical wind corrections on global wave forecasting, Ocean Modelling, 70, 116–131. doi:10.1016/j.ocemod.2012.10.006
• 10. Feng H, Vandemark D, Quilfen Y, Chapron B, Beckley B. (2006) Assessment of wind- forcing impact on a global wind wave model using the TOPEX altimeter, Ocean Engineering, 33, 1431–1461. doi:10.1016/j.oceaneng.2005.10.015
• 11. GEBCO, 2014. GEBCO Overview. General Bathymetric Chart of the Oceans (GEBCO), http://www.gebco.net/data_and_products/gridded_bathymetry_data, Erişim Tarihi: 14.12.2014, Konu: Batimetri verisi.
• 12. Hasselmann, S., Hasselmann, K., Allender, J. H., Barnett, T. P. (1985) Computations and parameterizations of the nonlinear energy transfer in a gravity-wave specturm. Part II: Parameterizations of the nonlinear energy transfer for application in wave models, Journal of Physical Oceanography, 15(11), 1378-1391. doi:10.1175/1520- 0485(1985)015<1378:CAPOTN>2.0.CO;2
• 13. Hersbach, H, Bell, W, Berrisford, P, Horányi, A, J., M-S, Nicolas, J, Radu, R, Schepers, D, Simmons, A, Soci, C, Dee, D. (2019) Global reanalysis: goodbye ERA-Interim, hello ERA5, ECMWF Newsletter, 159, 17-24. doi:10.21957/vf291hehd7
• 14. Hersbach, H, de Rosnay, P, Bell, B, Schepers, D, Simmons, A, Soci, C, Abdalla, S, Alonso-Balmaseda, M, Balsamo, G, Bechtold, P, Berrisford, P, Bidlot, J-R, de Boisséson, E, Bonavita, M, Browne, P, Buizza, R, Dahlgren, P, Dee, D, Dragani, R, Diamantakis, M, Flemming, J, Forbes, R, Geer, AJ, Haiden, T, Hólm, E, Haimberger, L, Hogan, R, Horányi, A, Janiskova, M, Laloyaux, P, Lopez, P, Munoz-Sabater, J, Peubey, C, Radu, R, Richardson, D, Thépaut, J-N, Vitart, F, Yang, X, Zsótér, E, Zuo, H. (2018) Operational global reanalysis: progress, future directions and synergies with NWP, ECMWF ERA Report Series 27. doi:10.21957/tkic6g3wm
• 15. Holthuijsen LH, Booij N, Ris RC. (1993) A spectral wave model for the coastal zone. Proceedings of the 2nd international symposium on ocean wave measurement and analysis. New Orleans, Louisiana, United States, 630–641.
• 16. Komen, G. J., Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., Janssen, P. A. E. M. (1994) Dynamics and Modeling of Ocean Waves. Cambridge University Press, No: 9780521577816, USA, 532 doi:10.1017/CBO9780511628955
• 17. Özhan E, Abdalla S, Sezis-Papila S, Turhan M. (1995) Measurements and modelling of wind–waves along the Turkish Mediterranean Coasts and the Black Sea. Proceedings of the second international conference on the Mediterranean coastal environment, MEDCOAST’95, Tarragona, Spain
• 18. Ponce de León S, Guedes Soares C. (2008) Sensitivity of wave model predictions to wind fields in the Western Mediterranean Sea, Coastal Engineering, 55(11), 920–929. doi:10.1016/j.coastaleng.2008.02.023
• 19. Ponce de León S, Orfila A, Gomez-Pujol L, Renault L, Vizoso G, Tintore J. (2012) Assessment of wind models around the Baleric Islands for operational wave forecast. Applied Ocean Research, 34, 1–9. doi:10.1016/j.apor.2011.09.001
• 20. Ris RC, Holthuijsen LH, Booij N. (1999) A third-generation wave model for coastal regions: 2, verification, Journal of Geophysical Research, 104(C4), 7667–7681. doi:10.1029/1998JC900123
• 21. Rogers, W.E., Hwang P.A., Wang D.W. (2003) Investigation of Wave Growth and Decay in The SWAN Model: Three Regional-Scale Applications. Journal of Physical Oceanography, 33(2), 366-389. doi:10.1175/1520-0485(2003)033<0366:IOWGAD>2.0.CO;2
• 22. Signell RP, Carniel S, Cavaleri L, Chiggiato J, Doyle JD, Pullen J, Sclavo M. (2005) Assessment of wind quality for oceanographic modelling in semi-enclosed basins, Journal of Marine Systems, 53, 217–233. doi:10.1016/j.jmarsys.2004.03.006
• 23. Tucker, M.J. ve Pitt, E.G. (2001) Waves in Ocean Engineering, Elsevier Science, Amsterdam.
• 24. Van Vledder, G.P., Akpınar, A. (2015) Wave model predictions in the Black Sea: Sensitivity to wind field, Applied Ocean Research, 53, 161-178. doi:10.1016/j.apor.2015.08.006
• 25. Wilk, M.B.; Gnanadesikan, R. (1968), Probability plotting methods for the analysis of data, Biometrika, Biometrika Trust, 55 (1), 1–17. doi:10.2307/2334448
• 26. Yılmaz N. (2007) Spectral characteristics of wind waves in the Eastern Black Sea, Doktora Tezi, The Graduate School of Natural and Applied Sciences of Middle East Technical University, Ankara, Turkey.
• 27. Zijlema M, Van der Westhuysen AJ. (2005) On convergence behaviour and numerical accuracy in stationary SWAN simulations of nearshore wind wave spectra. Coastal Engineering, 52(3), 237–256. doi:j.coastaleng.2004.12.006
• 28. Zijlema, M., Van Vledder, G.P., Holthuijsen, L.H. (2012) Bottom Friction and Wind Drag for Wave Models. Coastal Engineering, (65), 19-26. doi: 10.1016/j.coastaleng.2012.03.002