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Professional Specialist

Cooperative Institute for Modeling the Earth System – Princeton University

Weather and Climate Dynamics Division

Curriculum vitae


Google scholar

Contact Information:


phone (609) 452-6555

Research Interests:

  • Weather and Climate Modeling
  • Dynamics and Physics Coupling
  • Cloud Microphysics Parameterization


Linjiong Zhou

I am a researcher at Princeton University, working at the Geophysical Fluid Dynamics Laboratory (GFDL). I am leading the SHiELD (System for High-resolution prediction on Earth-to-Local Domains) global prediction system development as part of the NOAA Research Global-Nest Initiative. In particular, my research focuses on building a novel integrated dynamics-physics coupling framework and developing advanced but efficient cloud microphysics parameterization to improve global weather prediction from large-scale to mesoscale. I am actively involved in the SHiELD developments that contributed to the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project and Different Models-Same Initial Conditions (DIMOSIC) project.

Integrated Dynamics-Physics Coupling Framework

Zhou and Lucas (2022) proposes an integrated dynamics-physics coupling framework for weather and climate-scale models. Each physical parameterization would be advanced on its natural time scale, revise the thermodynamics to include moist effects, and finally integrated into the relevant components of the dynamical core. This study shows results using a cloud microphysics scheme integrated within the dynamical core of the GFDL SHiELD weather model to demonstrate the promise of this concept. We call it the in-line microphysics as it is in-lined within the dynamical core. Statistics gathered from 1 year of weather forecasts show significantly better prediction skills when the model is upgraded to use the in-line microphysics. The in-line microphysics also shows larger-amplitude and higher-frequency variations in cloud structures within a tropical cyclone than the traditionally-coupled microphysics.

GFDL Cloud Microphysics Parameterization

Zhou et al. (2022) describes the third version of the GFDL cloud microphysics scheme (GFDL MP v3) implemented in SHiELD. Compared to the GFDL MP v2 (Harris et al. 2020), the GFDL MP v3 is entirely reorganized, optimized, and modularized into functions. The particle size distribution (PSD) of all hydrometeor categories is redefined to better mimic observations, and the cloud droplet number concentration (CDNC) is calculated from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2) aerosol data. In addition, the GFDL MP has been redesigned so all processes use the redefined PSD to ensure overall consistency and easily permit the introduction of new PSDs and microphysical processes. A year’s worth of global 13-km, 10-day weather forecasts were performed with the new GFDL MP. Compared to the GFDL MP v2, the GFDL MP v3 significantly improves SHiELD’s predictions of geopotential height, air temperature, and specific humidity in the Troposphere, as well as the high, middle and total cloud fractions and the liquid water path. The predictions are improved even further by the use of reanalysis aerosol data to calculate CDNC, and also by using the more realistic PSD available in GFDL MP v3.

Global 6.5-km Prediction System

We are developing a 6.5-km version of the GFDL’s SHiELD. This global model is designed to bridge the gap between global medium-range weather prediction and global storm-resolving simulation while remaining practical for real-time prediction. The 6.5-km SHiELD represents a significant advancement over GFDL’s flagship global forecast system, the 13-km SHiELD. This global model features a holistically-developed scale-aware suite of physical parameterizations, stepping into the formidable convective “gray zone” of resolutions below 10 km. Comparative analyses with the 13-km SHiELD, conducted over a three-year hindcast period, highlight noteworthy improvements across global-scale, regional-scale, tropical cyclone (TC), and continental mesoscale convection predictions. These findings affirm the superiority of the 6.5-km SHiELD compared to the current 13-km SHiELD, which will advance weather prediction by successfully addressing both synoptic weather systems and specific storm-scale phenomena in the same global model.