Characteristics of the Wind Distribution Using Automatic Weather System Observation Data over the Doyo-deung Barrier Islands off the Coast of the Nakdong River Estuary, Busan, South Korea

Abstract

This study was conducted to the Nakdong marine environmental information system (N-MEIS) using automatic weather station (AWS) observation data to elucidate the characteristics of the wind distribution, focusing on and land and sea breezes, over the Doyo-deung barrier islands in the brackish water zone off the coast of the Nakdong River Estuary, Busan, South Korea. From May 2015 to the present, the N-MEIS was run in real-time using 4th Generation (4G) long term evolution (LTE) communication, with a coverage rate of approximately 98% from AWS, along with periodic marine observations recorded one to four times per year. From April 2016 to August 2020, the average monthly wind speed over the Doyo-deung barrier islands was 3.82 m/s (range, 2.10–5.10 m/s) and the maximum wind speed, recorded in February 2019, was 46.80 m/s. These values are generally influenced by low-pressure cyclones or gusty winds. However, the maximum monthly mean velocity may be influenced by typhoons occurring in early autumn, from August to September. Based on the percentage of each wind direction, the prevailing winds are from the N, NNE, SSW, and NNW. The distribution of wind directions in summer was similar to that in spring, while that in autumn tended to be similar to that in winter. However, considering only wind speeds of 5.00 m/s or more, which can cause the movement of sand particles, N, SSW, and NNW winds are overwhelmingly dominant, at 38.7%. Research into the dynamic wind distribution is essential to effectively managing erosion and sedimentation around barrier islands, beach pollution from floating materials transported overland, coastal sand dune activity, changes in migratory bird habitats, and impacts on ecosystem health. The evolution and development of the N-MEIS will facilitate this process. Future studies should integrate real-time data with periodic marine observations and predictions and environmental sensitivity index maps.