Recently, model team from the Department of Earth System Science (DESS) at Tsinghua University developed a novel objective automatic tracking algorithm and used this method to generate a long term Mesoscale Convective System (MSC) dataset. This high-quality dataset can improve the reliability of the statistical analysis results of the mesoscale convective system, promote understanding of the global water cycle process, and optimize the simulation of atmospheric convection in the Earth system model. The related paper entitled “A long-term tropical mesoscale convective systems dataset based on a novel objective automatic tracking algorithm” has been published on the Journal of Climate Dynamics.

Table 1 shows the basic features of the MCSs tracked by the KF and area-overlapping methods during year 2000. These results indicate that the KF method performs better in capturing small and fast-moving MCSs, and thus a practical approach for MCS tracking.

Table 1. Features of MCSs tracked by our new method (KF) and the area-overlapping (AOL) method in 2000. Total number indicates the cumulative number of MCSs occurring over the whole year. The latter three variables indicate the mean lifetime, size and moving speed of each MCS. The size and moving speed are calculated by averaging over each time step of the lifespan of each MCS.

Associated Professor Huang Xiaomeng, PhD candidate Huang Xing and master candidate Hu Chenqi of the DESS are the joint first authors of this article, Associated Professor Lin Yanluan is the corresponding author, Professor Zhang Guangjun also contributed to this work. Journal of Climate Dynamics is the authoritative magazine in the field of the atmospheric science, the averaged impact factor for the recent five years is 4.744.

Link:https://link.springer.com/article/10.1007/s00382-018-4071-0