Abstract
The Chinese Academy of Meteorological Sciences Lightning Nowcasting and Warning System (CAMS_LNWS) was designed to predict lightning within the upcoming 0-1 h and provide lightning activity potential and warning products. Multiple remote sensing data and numerical simulation of an electrification and discharge model were integrated in the system. Two core algorithms were implemented: (1) an area identification, tracking, and extrapolating algorithm and (2) a decision tree algorithm. The system was designed using a framework and modular structure, and integrated warning methods were applied in the warning program. Two new algorithms related to the early warning of the first lightning and thunderstorm dissipation were also introduced into the system during the upgrade process. Thunderstorms occurring in Beijing, Tianjin, and Hebei during 2016-2017 were used to evaluate the CAMS_LNWS by the low-frequency cloud to ground lightning detection data, and the results showed that the system has good forecasting and warning ability for local lightning activities. The TS score in 0-1 h ranged from 0.11 to 0.32, with a mean of 0.20. Operational experiments and promotional work for the CAMS_LNWS are now in progress.
Highlights
Lightning is a natural phenomenon with the potential to destroy buildings, power supply systems, and communication equipment
Two new algorithms related to the early warning of the first lightning and thunderstorm dissipation were introduced into the system during the upgrade process. understorms occurring in Beijing, Tianjin, and Hebei during 2016-2017 were used to evaluate the CAMS_LNWS by the low-frequency cloud to ground lightning detection data, and the results showed that the system has good forecasting and warning ability for local lightning activities. e TS score in 0-1 h ranged from 0.11 to 0.32, with a mean of 0.20
At 08 : 00, the maximum convective available potential energy (CAPE) was 2900 J/kg, the free convection level was lower than 925 hPa, which was conducive to the development of deep convection. e maximum temperature di erence between high (500 hPa) and low (850 hPa) air reaches 24°C, and the strati cation was very unstable
Summary
Lightning is a natural phenomenon with the potential to destroy buildings, power supply systems, and communication equipment. Satellite, lightning locator, atmospheric electric field meter, and conventional meteorological observation data are used to continuously monitor and track areas of potential lightning activity, identify the intensity change and moving path of lightning activity, and use extrapolation algorithms to predict lightning activity areas and the probability of occurrence, development, evolution, and extinction in the 0-1 h. The GANDOLF system synthesizes a targetoriented method and a conceptual model of the convective cell life cycle and uses multibeam radar reflectivity data, infrared and visible satellite cloud images, and prediction results of the mesoscale numerical model to establish a 0–3 h convective precipitation movement and development prediction. There have been many studies of lightning nowcasting [3,4,5,6], these studies have been largely based on single observation data and were academic rather than functional attempts to develop early warning systems to predict lightning activity. The discussion and conclusion of this study are given
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