Towards an online GIS platform to enhance data and research sharing among meteorologists, natural hazard experts, governments, and the public
- 1Physical Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
- 2Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands
The “open era” of climate science is marked by an abundance of datasets across various environmental variables. While there are many evaluation studies, researchers and practitioners often still struggle to select the most suitable dataset or product for their study. The year 2023 marked the hottest year on record, resulting in a series of destructive hazard events, including heatwaves, wildfires, and floods. These conditions underscore the urgent need for enhanced preparedness in disaster risk reduction (DRR). In the field of natural hazards, environmental data are crucial for building more accurate models. We will take 'P' (precipitation) as an example in the presentation, as it's a major trigger for multiple hazards such as floods and landslides. There are dozens of publicly freely available global gridded P products available (including satellite, (re)analysis, gauge, and combinations thereof), but estimates from different products at the same time and location can differ significantly. Currently, there is no effective platform that facilitates the sharing of quantitative information on the relative strengths and weaknesses of these P products between meteorologists and other stakeholders. To address this challenge, we propose the development of a web-based GIS platform which allows users to interactively explore the globe, click on different locations, and access various statistics and databases. Multiple P products and evaluation statistics can be accessed via the platform. We hope this platform will host multiple hazards-related datasets, fostering better collaboration between scientists in the fields of DRR and meteorology. Initially focusing on P data based on our expertise in precipitation and landslide hazard modeling, we aim to expand this resource by involving more scientists from related fields. Additionally, we plan to integrate a ChatGPT-based extension to streamline data access and enhance efficiency for researchers, practitioners, and laypeople. We want to contribute to the collective effort in creating a dynamic, accessible repository of resources and initiatives for the wider geoscience community.
How to cite: Wang, X., Beck, H., and Lombardo, L.: Towards an online GIS platform to enhance data and research sharing among meteorologists, natural hazard experts, governments, and the public, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19782, https://doi.org/10.5194/egusphere-egu24-19782, 2024.