On-Orbit Response Characteristics of Fengyun-4A Lightning Mapping Imager (LMI) and Their Impacts on LMI Detection

Abstract

Abstract The effects of the response characteristics of the Fengyun-4A Lightning Mapping Imager (LMI) on its detection capability were studied using the raw event data of LMI in 2020. The simultaneous observation data of the Lightning Imaging Sensor (LIS) on the International Space Station (ISS) were used to evaluate the LMI detection capability. The results reveal that the minimum detectable radiance of lightning events in the 16 subregions of LMI has shown regional differences, with the southern subregions lower than the northern subregions, indicating that the southern ones are more conducive to the identification of events. The diurnal variation of the detectable event radiance in all subregions presents the main peak around noon, which comes from the influence of the bright background and varies largely in different subregions depending on the subregions’ response capability. The overall high values and regional differences of flash properties observed by LMI also show strong correlation with the variation of the minimum detectable radiance of events. Moreover, it is found that the southwest subregions have the highest coincidence ratio (CR) with ISS LIS, followed by the southeast subregions and the northeast subregions, and the northwest subregions have the lowest CR, which is closely related to the response of each subregion. The LIS flashes that can be detected by LMI are brighter, larger, and last longer compared to the total LIS flashes. The findings in this study will help explain the inconsistency of the LMI detection capability and promote the LMI data processing associated with pixel energy distribution. Significance Statement The Fengyun-4A (FY-4A) Lightning Mapping Imager (LMI) is the first geostationary satellite-borne lightning imager developed in China, which has the ability to continuously observe lightning within a large field of view. However, in the application of the data, it was found that the detection capability of the LMI differed significantly in different regions and exhibited diurnal variations, which may be related to the response characteristics of the LMI detector. This study reveals the effect of the response characteristics of the LMI detector on its detection results. The findings will help improve the usability of LMI data and improve the processing of these data to adjust the observation inconsistency.