A new global gridded lightning dataset with high spatial and temporal resolution

Lightning is a key atmospheric phenomenon that modulates atmospheric chemistry and impacts terrestrial carbon dynamics through the ignition of wildfires and direct tree mortality. Despite its importance, there is a data gap in publicly available global lightning datasets with high spatial and temporal resolution for scientific use. In this study, we present our progress towards creating a global gridded lightning dataset derived from Vaisala’s Global Lightning Detection Network (GLD360), covering the period from 2019 to 2024, with potential annual updates thereafter. This dataset is produced through a systematic gridding procedure that converts raw GLD360 lightning event data into 0.1º hourly, 0.25º daily, and 0.5º monthly gridded values. It includes key variables such as positive and negative cloud-to-ground and intra-cloud stroke count/density, stroke peak current, stroke location uncertainty, and flash count/density, making it valuable for a wide range of scientific applications. We are evaluating the gridded dataset using local lightning detection networks in Alaska (USA), Spain, South Africa, and the New South Wales and Australian Capital Territory (Australia). Meanwhile, we are comparing stroke density with the Global Lightning Climatology (WGLC) dataset derived from the World Wide Lightning Location Network (WWLLN) and flash density with the Lightning Imaging Sensor/Optical Transient Detector (LIS/OTD). The dataset could be particularly useful for advancing studies on lightning climatology, the role of lightning in wildfire ignition, thunderstorm identification, and other related topics. Its high spatial and temporal resolution also supports regional studies of lightning-related hazards and ecosystem impacts. Our goal is to make this dataset publicly available to the scientific community to facilitate new insights into the role of lightning in the Earth system.