Advancing Hyperresolution Modeling of Land-Atmosphere Interactions to Improve Extreme Precipitation Forecasting

This presentation examines the evolution and future trajectory of hyperresolution modeling for land-atmosphere interactions. Starting with Eric Wood et al.'s 2011 landmark paper in Water Resources Research, which first underscored the potential of hyperresolution terrestrial hydrology modeling, I will trace key advancements leading to Julia Slingo et al.'s 2022 article in Nature Climate Change, which champions the shift to ultra-high-resolution, kilometer-scale Earth system models.

I will highlight recent breakthroughs, including Lingcheng Li et al.'s development of global 1-km land surface parameters and Stefan Kollet's exa-scale-ready groundwater modeling presented at the 2024 GEWEX Science Meeting. Additional focus will be given to the pioneering efforts of Andreas Prein, the EU's Digital Twin Earth initiative, and NVIDIA's innovations in GPU technology, all pushing the boundaries of mesoscale, multi-scale Earth system modeling.

The presentation will then address the significant challenges of modeling mesoscale convective systems, particularly in predicting rainfall, infiltration, soil moisture dynamics, and ecohydrology. Overcoming these challenges requires enhancing model resolution, incorporating a broader range of physical processes, and advancing ensemble forecasting methods.

I will propose the Noah-MP model as a promising pathway forward, emphasizing its multiple physics options to improve the prediction of extreme precipitation events. This strategy aims to enhance water resource planning and management under changing climate conditions.