Natural events have had a significant impact on overall flight activity,and the aviation industry plays a vital role in helping society cope with the impact of these events.As one of the most impactful weather typhoon...Natural events have had a significant impact on overall flight activity,and the aviation industry plays a vital role in helping society cope with the impact of these events.As one of the most impactful weather typhoon seasons appears and continues,airlines operating in threatened areas and passengers having travel plans during this time period will pay close attention to the development of tropical storms.This paper proposes a deep multimodal fusion and multitasking trajectory prediction model that can improve the reliability of typhoon trajectory prediction and reduce the quantity of flight scheduling cancellation.The deep multimodal fusion module is formed by deep fusion of the feature output by multiple submodal fusion modules,and the multitask generation module uses longitude and latitude as two related tasks for simultaneous prediction.With more dependable data accuracy,problems can be analysed rapidly and more efficiently,enabling better decision-making with a proactive versus reactive posture.When multiple modalities coexist,features can be extracted from them simultaneously to supplement each other’s information.An actual case study,the typhoon Lichma that swept China in 2019,has demonstrated that the algorithm can effectively reduce the number of unnecessary flight cancellations compared to existing flight scheduling and assist the new generation of flight scheduling systems under extreme weather.展开更多
Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some p...Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some physical quantities and time variables which can effectively identify severe convective weather types were preliminarily obtained.The results show that CAPE was sensitive to different types of weather,but the uncertainty was relatively large.Convective temperature T_(CON),temperature difference between 500 and 850 hPa,and vertical wind shear can distinguish thunderstorm gale,thunderstorm and heavy precipitation weather obviously.Besides,K index,Showalter index,θ_(se) difference between 500 and 850 hPa were also important basis to distinguish thunderstorm and heavy precipitation weather.Thunderstorm gale can be distinguished by the 24-hour variations of K index,and the difference of dew point between 500 and 850 hPa.The 24-hour variations of(T-T_(d))_(500) and vertical wind shear can be used to distinguish between heavy precipitation and thunderstorm weather;the 24-hour variation of stratification stability Δθ_(se) can distinguish the three kinds of weather well.For the wind field,the existence of vertical wind shear was required for strong convective weather,and the 24-hour increment of thunderstorm gale and thunderstorm was larger than that of heavy precipitation.展开更多
基金supported by the National Natural Science Foundation of China(62073330)。
文摘Natural events have had a significant impact on overall flight activity,and the aviation industry plays a vital role in helping society cope with the impact of these events.As one of the most impactful weather typhoon seasons appears and continues,airlines operating in threatened areas and passengers having travel plans during this time period will pay close attention to the development of tropical storms.This paper proposes a deep multimodal fusion and multitasking trajectory prediction model that can improve the reliability of typhoon trajectory prediction and reduce the quantity of flight scheduling cancellation.The deep multimodal fusion module is formed by deep fusion of the feature output by multiple submodal fusion modules,and the multitask generation module uses longitude and latitude as two related tasks for simultaneous prediction.With more dependable data accuracy,problems can be analysed rapidly and more efficiently,enabling better decision-making with a proactive versus reactive posture.When multiple modalities coexist,features can be extracted from them simultaneously to supplement each other’s information.An actual case study,the typhoon Lichma that swept China in 2019,has demonstrated that the algorithm can effectively reduce the number of unnecessary flight cancellations compared to existing flight scheduling and assist the new generation of flight scheduling systems under extreme weather.
文摘Continuous thunderstorm occurring at Qingdao Airport in China from August 7 to 13,2022 was analyzed based on sounding data.The weather was divided into thunderstorm gale,thunderstorm and heavy precipitation,and some physical quantities and time variables which can effectively identify severe convective weather types were preliminarily obtained.The results show that CAPE was sensitive to different types of weather,but the uncertainty was relatively large.Convective temperature T_(CON),temperature difference between 500 and 850 hPa,and vertical wind shear can distinguish thunderstorm gale,thunderstorm and heavy precipitation weather obviously.Besides,K index,Showalter index,θ_(se) difference between 500 and 850 hPa were also important basis to distinguish thunderstorm and heavy precipitation weather.Thunderstorm gale can be distinguished by the 24-hour variations of K index,and the difference of dew point between 500 and 850 hPa.The 24-hour variations of(T-T_(d))_(500) and vertical wind shear can be used to distinguish between heavy precipitation and thunderstorm weather;the 24-hour variation of stratification stability Δθ_(se) can distinguish the three kinds of weather well.For the wind field,the existence of vertical wind shear was required for strong convective weather,and the 24-hour increment of thunderstorm gale and thunderstorm was larger than that of heavy precipitation.
