Assessment of metocean forecasts for Hurricane Lorenzo in the Azores Archipelago. (1st January 2022)

• Record Type: Journal Article
• Authors: Campos, R.M.; Bernardino, M.; Gonçalves, M.; Guedes Soares, C.
• Is Part Of: Ocean engineering. Volume 243(2022)
• Publication Date: 2022-01-01
• Subjects: Extreme events -- Wind forecast -- Wave forecast -- Azores archipelago -- Hurricane assessment -- Ensemble forecasts -- Satellite data; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2021.110292
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: This paper analyzes the performance of multiple wind and wave operational forecasts of Hurricane Lorenzo, the easternmost Category 5 Atlantic hurricane on record. Deterministic and ensemble forecast products from the National Centers for Environmental Prediction, Environment Canada's Meteorological Center, US Navy Fleet Numerical Meteorology and Oceanography Center, and Deutscher Wetterdienst have been selected for the assessment, which is based on in situ observations collected in the Azores Archipelago and satellite data (altimeters and scatterometers). Forecast ranges up to one week are analyzed and the error metrics are calculated as a function of the forecast lead times. The results show that the ensemble forecasts presented better performance than the deterministic forecasts, maintaining high correlation coefficients and low scatter indexes at longer ranges. However, the ensemble averages are associated with negative bias and increasing underestimation of the peak of the storm when the ensemble spread is large. Highlights: This paper analyzes the performance of multiple wind and wave operational forecasts of Hurricane Lorenzo. Forecast ranges up to one week are analyzed and the error metrics are calculated as a function of the forecast lead times. The results show that the ensemble forecasts presented better performance than the deterministic forecasts. Ensemble forecasts are associated with negative bias and increasing underestimation of the peak of the storm.