Chung-Yi Lin

TL;DR: In this article, the authors compared the performance of the momentum control variables ψ and χ (ψχ) for high-resolution data assimilation and forecast experiments for seven convective events in a domain that encompasses the Rocky Mountain Front Range using the 3DVar system of the Weather Research and Forecasting (WRF) Model.

TL;DR: In this article, Radar and surface rainfall observations are two sources of operational data crucial for heavy rainfall prediction, and their individual values on improving convective forecasting through data a a...

TL;DR: In this article , the authors investigated the co-evolution issues in coupled natural human systems via two-way coupling RiverWare (RW; a river-reservoir routing model) with agent-based models (ABMs, human decision models) in the Yakima River Basin in Washington, US.

TL;DR: An uncertainty analysis of coupled hydrological and human decision models to better evaluate CNHS modeling properties is explored and the inclusion of a learning mechanism in the human system can potentially offset the impact of the natural system on uncertainty through coupling natural and human systems.

TL;DR: The HydroCNHS as mentioned in this paper is an open-source Python package supporting four application programming interfaces (APIs) that enable users to integrate their human decision models, which can be programmed with the agent-based modeling concept, into Hydro-CNHS.