Evaluating skill of BMKG wave model forecast (Wavewatch-3) with observation data in Indian Ocean (5 – 31 December 2017)

• Published in: IOP conference series. Earth and environmental science 2021-11, Vol.893 (1), p.12058
• Main Authors: Kurniawan, R, Harsa, H, Ramdhani, A, Fitria, W, Rahmawati, D, Habibie, M N, Hutapea, T D
• Format: Article
• Language: English
• Subjects: Mathematical models; Ocean waves; Performance evaluation; Root-mean-square errors; Statistical correlation; Wave height; Weather forecasting; Wind
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/893/1/012058

Providing Maritime meteorological forecasts (including ocean wave information) is one of BMKG duties. Currently, BMKG employs Wavewatch-3 (WW3) model to forecast ocean waves in Indonesia. Evaluating the wave forecasts is very important to improve the forecasts skill. This paper presents the evaluation of 7-days ahead BMKG’s wave forecast. The evaluation was performed by comparing wave data observation and BMKG wave forecast. The observation data were obtained from RV Mirai 1708 cruise on December 5th to 31st 2017 at the Indian Ocean around 04°14'S and 101°31'E. Some statistical properties and Relative Operating Characteristics (ROC) curve were utilized to assess the model performance. The evaluation processes were carried out on model’s parameters: Significant Wave Height (Hs) and Wind surface for each 7-days forecast started from 00 UTC. The comparation results show that, in average, WW3 forecasts are over-estimate the wave height than that of the observation. The forecast skills determined from the correlation and ROC curves are good for the first- and second-day forecast, while the third until seventh day decrease to fair. This phenomenon is suspected to be caused by the wind data characteristics provided by the Global Forecasts System (GFS) as the input of the model. Nevertheless, although statistical correlation is good for up to 2 days forecast, the average value of Root Mean Square Error (RMSE), absolute bias, and relative error are high. In general, this verifies the overestimate results of the model output and should be taken into consideration to improve BMKG’s wave model performance and forecast accuracy.