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Thiết lập một thuật toán dự báo mù và sương mù cho khu vực Sân bay quốc tế Nội Bài

Bài báo trình bày một thuật toán dự báo mù và sương mù trước 24 giờ cho khu vực sân bay quốc tế Nội Bài bằng phương pháp hồi quy và phân lớp. Thuật toán dự báo phụ thuộc các chỉ số FSI (Fog Stability Index), Fog Threat (Fog Potential), Fog Point (Fog formation temperature) và lớp nghịch nhiệt ở độ cao 1000 - 800mb tương ứng cao độ từ sát bề mặt đến độ cao khoảng 1500m. | Transport and Communications Science Journal Vol 72 Issue 3 04 2021 342-355 Transport and Communications Science Journal AN ALGORITHM FOR MIST AND FOG FORECASTING FOR NOIBAI INTERNATIONAL AIRPORT HANOI VIETNAM Le Thi Viet Ha Hoang Nam Binh Tran Thu Phuong University of Transport and Communications No 3 Cau Giay Street Hanoi Vietnam ARTICLE INFO TYPE Research Article Received 25 01 2021 Revised 18 03 2021 Accepted 29 03 2021 Published online 15 04 2021 https doi.org 10.47869 tcsj.72.3.9 Corresponding author Email binhhn@utc.edu.vn Abstract. Mist or fog is a product of water vapor condensation in the air at or near Earth s surface limiting visibility reducing visibility to less than 4 000 meters mist or 1 000 meters fog . They are severe weather phenomenon and work in small or medium areas. Mist and fog conditions have potential negative impact on several economic activities such as agriculture marine etc. and especially aviation operations. They are the limiting factor in aviation and can delay a flight or to cause the flight to divert to the planned destination airport. Therefore the visibility forecasting is very important in aviation to ensure flight safety. This article presents an algorithm for fog and mist forecasting in a 24 hours period at Noibai International Airport Hanoi Vietnam by regression and classification method. Forecasting algorithm depends on the indexes FSI Fog Stability Index Fog Threat Fog Potential Fog Point Fog formation temperature and the thermal inversions layer at 1000 - 800 milibar level sea level to near 1 500 meters . The forecasting model includes 2 regression equations combining other conditions. The results show that the forecasting model has good quality for the mist but not good for the fog phenomenon. Keywords Fog forecating Fog Index Regression Classification Noibai international airport 2021 University of Transport and Communications 342 Tạp chí Khoa học Giao thông vận tải Tập 72 Số 3 04 2021 342-355 Tạp chí Khoa học Giao .