WRF-Hydro® Community Spotlight | Haiqing Soong
This Community Spotlight focuses on Haiqing Soong, a Meteorological Ph.D. student and engineer at the Ecological and Agricultural Meteorology Center of Inner Mongolia(Hohhot)/ Chinese Meteorological Administration.
Haiqing Soong established a real time land data assimilation system for the Inner Mongolia Meteorological Administration (Short for IMLDAS-2.0), the core of which is WRF-Hydro®(v5).
“The WRF-Hydro model helped us achieve a leap from site weather monitoring services to grid weather monitoring services.”
In 2018 and 2019 it was used to accurately monitor floods, drought, and snow depth and is currently running in real time on an High Performance Computing system in the Inner Mongolia Meteorological Administration of the China Meteorological Administration (CMA).
On 25 October 2019 a thundersnow event struck the eastern region of Inner Mongolia in China. The deepest snow piled up to 30cm. Haiqing states that WRF-Hydro® simulated accurate snow depth and helped them to successfully predict, mitigate, and monitor the snow disaster.
Below is a Q&A with Haiqing about his background, current research, and experience with using WRF-Hydro®.
Q. What initially excited you about modeling as your chosen area of study?
A. My undergraduate major is math. And mathematics is the foundation of the numerical model, and I would like to thank my graduate supervisor Professor Tian Xiangjun, who led me into the numerical model world.Some of the first questions that came to mind were:how soil moisture interacts with precipitation and how the model describes these processes.
Q. How did you first come to find out about the WRF-Hydro modeling system?
A. I started following the development of WRF-Hydro in 2014. At that time I browsed the RAL/NCAR website and found this model which was exactly what I was looking for. In 2015, I wanted to establish a real time land data assimilation system over Inner Mongolia to help us achieve a weather monitoring services leap from in-situ station observation to gridded data weather monitoring services.WRF-Hydro just met my needs.
Q. What is your current research project focusing on?
A. My current research project focuses on monitoring and predicting soil moisture using a high-resolution WRF-Hydro setup for North of China. And also using WRF-Hydro to monitor snow depth because snow is an important source of soil moisture. At the same time, snow is also an important predictable factor for sub-seasonal and seasonal forecasts.
Q. What aspects of the WRF-Hydro modeling system made it most suitable for your research/ project needs?
A. WRF-Hydro provides a fully-coupled hydrological processes of the water cycle.
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