Kun Gao

About me

I am a member of the GFDL FV3 team, mainly focusing on the development of the
Finite-Volume on Cubed-Sphere Dynamical Core (FV3) and
Unified System for Weather-to-Seasonal Prediction SHiELD. I also contribute to
NOAA Research Global-Nest Initiative.

My research at GFDL covers three areas:

• Developing advanced high-resolution numerical models to improve the prediction of intensity, track, and rainfall of hurricanes on the medium-range timescale.
• Understanding how storm-scale processes (e.g., convection, large eddies) affect hurricane structure and intensity changes.
• Exploring the prediction of hurricanes and other extreme weather events on subseasonal-to-seasonal timescales.

Ongoing Modeling Projects

• Developing a global nested version of SHiELD, i.e., T-SHiELD, for North Atlantic Hurricane prediction (leading role).
• Implementing a 3D-TKE based diffusion scheme into FV3 (mostly collaborating with Dr. Ping Zhu’s team at FIU).
• Developing a high-resolution regional coupled SHiELD-MOM6-WWIII system (a joint effort among GFDL W, O and Modeling System divisions).

Selected Research Work (leading or co-leading roles)

Innovations for the Next-generation Hurricane Forecasting Models

• We used a multi-level nested strategy to archive 100m scale resolution, which captured the fine-scale finger-like features at the hurricane eye/eyewall interface. See Gao et al. 2024 GRL

Improving Hurricane Track, Intensity and Structure Prediction

• Investigated how the model-resolved convection in convection-permitting models significantly affects hurricane track prediction. See Gao et al. 2023 GRL
• Built a novel framework for evaluating the wind structure of landfalling hurricanes based on sparse in-situ observations. See Chen et al. 2023 GRL
• Examined how the horizontal tracer advection algorithm alone can play a surprising role in hurricane intensity forecasts. See Gao et al. 2021 JAS
• Showcased using an 8km nest can dramatically improve the fidelity of hurricane structure representation in a GCM. See Gao et al. 2019 JAMES

MJO and Subseasonal Prediction

• Improved MJO prediction and propagation across the Maritime Continent with embedding a high-resolution nest in a GCM. See Zavadoff et al. 2023 GRL
• Explored the prediction of monthly hurricane activity over the North Atlantic. See Gao et al. 2019 GRL
• Showcased the representation of hurricane activity in the Gulf region, where most GCMs struggle, in the GFDL non-hydrostatic 25km HiRAM. See Gao et al. 2017 JGR-Atmosphere. This work is highlighted by Eos.org.

Large Eddies in the Hurricane Boundary Layer

• Conducted a series of studies examining the nature and impact of roll vortices in the hurricane boundary layer during my PhD at the University of Rhode Island, advised by Dr. Isaac Ginis, in collaboration with NRL.

  See Gao and Ginis 2014, Gao and Ginis 2016, Gao et al. 2017, Gao and Ginis 2018.