| Abstract: | In the South China Sea, sea fog brings severe disasters every year, but forecasters have yet to implement an effective sea-fog forecast. To address this issue, we test a liquid-water-content-only (LWC-only) operational sea-fog prediction method based on a regional mesoscale numerical model with a horizontal resolution of about 3 km, the Global and Regional Assimilation and Prediction System (GRAPES), hereafter GRAPES-3km. GRAPES-3km models the LWC over the sea, from which we infer the visibility that is then used to identify fog. We test the GRAPES-3km here against measurements in 2016 and 2017 from coastal-station observations, as well as from buoy data, data from the Integrated Observation Platform for Marine Meteorology, and retrieved fog and cloud patterns from Himawari-8 satellite data. For two cases that we examine in detail, the forecast region of sea fog overlaps well with the multi-observational data within 72 h. Considering forecasting for 0-24 h, GRAPES-3km has a 2-year-average equitable threat score (ETS) of 0.20 and a Heidke skill score (HSS) of 0.335, which is about 5.6% (ETS) and 6.4% (HSS) better than our previous method (GRAPES-MOS). Moreover, the stations near the particularly foggy region around the Leizhou Peninsula have relatively high forecast scores compared to other sea areas. Overall, the results show that GRAPES-3km can roughly predict the formation, evolution, and dissipation of sea fog on the southern China coast. |
