体裂
弹道
航程(航空)
平流
数据同化
气象学
大地测量学
垂直速度
水平和垂直
气团(太阳能)
震级(天文学)
地质学
环境科学
统计
数学
地理
机械
物理
工程类
代表性启发
热力学
航空航天工程
气溶胶
天文
作者
Lin Su,Zibing Yuan,Jimmy Chi Hung Fung,Alexis K.H. Lau
标识
DOI:10.1016/j.scitotenv.2014.11.072
摘要
The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is widely used to generate backward trajectories in given starting locations. However, differences exist between trajectories generated from the model with different input datasets. In this study, backward trajectories in Hong Kong in the entire year of 2011 are derived by HYSPLIT model. Two sets of Global Data Assimilation System (GDAS) output data associated with different horizontal and vertical resolutions (GDAS1 and GDAS0P5) are used as drivers in an attempt to quantify the differences between the results and discover the underlying reasons responsible for discrepancy. The results reveal that the significant differences between back trajectories generated from the two GDAS datasets can be mainly attributed to different vertical velocity calculation methods due to the absence of vertical velocity in GDAS0P5 dataset. The HYSPLIT trajectories are also sensitive to the horizontal and vertical resolutions of the input meteorological data, but to lesser extents. Results of cluster analysis indicate that when the air mass is from the north, northeast, or west with a long-to-medium range, the HYSPLIT backward trajectories are sensitive to the vertical advection calculation method and data resolution, whereas when the air mass is from the south or southwest with a long range, the trajectories are more likely to remain unchanged with the shifting of vertical velocity or data resolution. By comparing the vertical velocities with the observations and the performance in retrieving PM contributions from different directions, we conclude that GDAS1 dataset is more plausible in backward trajectory analysis in the Pearl River Delta.
科研通智能强力驱动
Strongly Powered by AbleSci AI