Skill assessment of a high resolution (1/72 degree) Black Sea ocean model

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The skill of a high-resolution Black Sea circulation model (ROMS) is assessed using the available satellite and field data for Sea Surface Height Anomaly (SSHA), Sea Surface Temperature, and CTD profiles. The model is configured to simulate the 9-year period between 2012 and 2021. The model’s skill is assessed using standard analytical methods for error calculation such as Root Mean Square Error (RMSE) and correlation. Additionally, the model results are assessed using several more recent methods such as the relative operating characteristic (ROC). The results show that the model is capable of simulating daily mean SSHA with an RMSE value of 1.2 cm. When the mean monthly SSHA values are considered, the RMSE drops down to 0.7 cm. The biggest source of the error for SSHA is found to be related to the freshwater balance, as the Black Sea is a freshwater-dominated marine environment. The results for SST show that the model is able to capture both the daily and seasonal variation with high correlation values. The correlation coefficient for basin averaged SST over the entire simulation period compared to the satellite-based OISST data is calculated as 0.98, and the RMSE value is 1.6 °C. In addition to the surface comparisons obtained from SSHA and SST, the model results are compared to 2300 Argo Float CTD profiles. The RMSE is 1.1 °C for the temperature profiles and 0.7 PSU for the salinity over the entire water column. The methods used to assess the skill of the model show that the model is quite capable of simulation of oceanic conditions within the Black Sea. As one of the aims of this model’s development is to simulate mesoscale-to-sub-mesoscale eddies, results on the model’s capabilities show that it can simulate eddies successfully from 5 – 50 km eddies in the Black Sea.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)235-246
Sayfa sayısı12
DergiTurkish Journal of Earth Sciences
Basın numarası2
Yayın durumuYayınlandı - 2022

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This work was supported by Research Fund of the İstanbul Technical University. Project Number: 39408. Computing resources used in this work were provided by the National Center for High Performance Computing of Turkey (UHeM) under grant number 5003952016.

FinansörlerFinansör numarası
National Center for High Performance Computing of Turkey
Ulusal Yüksek Başarımlı Hesaplama Merkezi, Istanbul Teknik Üniversitesi5003952016
Istanbul Teknik Üniversitesi39408

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