Roh et al. (2025) Vertical motions in clouds from EarthCare satellite and a global storm-resolving modeling

Identification

• Journal: Scientific Reports
• Year: 2025
• Date: 2025-12-15
• Authors: Woosub Roh, Masaki Satoh, Shuhei Matsugishi, Shunsuke Aoki, Takuji Kubota, Hajime Okamoto
• DOI: 10.1038/s41598-025-32256-8

Research Groups

• Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Chiba, Japan
• Typhoon Science and Technology Research Center, Yokohama National University, Yokohama, Kanagawa, Japan
• Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Ibaraki, Japan
• Research Institute for Applied Mechanics, Kyushu University, Kasuga, Fukuoka, Japan

Short Summary

This study provides an initial assessment of the newly launched EarthCARE satellite's Doppler radar observations by comparing them with high-resolution global simulations using NICAM. The findings demonstrate EarthCARE's capability to provide physically consistent information on hydrometeor vertical motions and its potential to constrain and refine cloud microphysics and dynamics in global weather and climate models.

Objective

• To provide an initial assessment of EarthCARE's Doppler radar observations by comparing them with high-resolution global simulations using NICAM and a satellite simulator.
• To examine how vertical motions influence the relationship between radar reflectivity and the fall speed of ice hydrometeors, and to identify potential discrepancies between observations and simulations in frontal and convective precipitation cases.

Study Configuration

• Spatial Scale: Global simulations with NICAM at approximately 870 m horizontal resolution. Analysis focused on two representative cases: a cold front system (extratropical cyclone) in the Southern Hemisphere and a tropical convective system near the Caribbean Sea.
• Temporal Scale: EarthCARE's initial observational period (June 17–18, 2024). Specific analysis periods: 1:08–1:20 UTC on June 18, 2024 (cold front) and 07:30–07:42 UTC on June 18, 2024 (tropical convection).

Methodology and Data

• Models used:
  • Nonhydrostatic Icosahedral Atmospheric Model (NICAM) with NICAM Single-Moment Water 6 cloud microphysics scheme, Smagorinsky type subgrid turbulence scheme, MSTRNX radiative transfer, MATSIRO land surface model, and slab-ocean model.
  • Joint Simulator for Satellite Sensors (J-Sim) for generating EarthCARE-like radar signals from NICAM data.
• Data sources:
  • EarthCARE Cloud Profiling Radar (CPR) Level 1b product (version vCa) for radar reflectivity and Doppler velocity.
  • Global Satellite Mapping of Precipitation (GSMaP) for large-scale precipitation distribution.
  • ERA5 reanalysis for initial atmospheric and oceanic conditions for NICAM simulations.

Main Results

• NICAM simulations generally reproduce the overall vertical structures observed by EarthCARE for both frontal and convective precipitation cases, including the melting layer and Doppler velocity distributions.
• Systematic differences in Doppler velocity were observed, particularly in convective regions, indicating biases in simulations (e.g., overestimation of hydrometeor fall speeds for small ice particles) and uncertainties in observations.
• For ice clouds above the melting layer, power-law relationships between radar reflectivity and Doppler velocity were derived:
  • Case 1 (cold front): EarthCARE (a = -0.812, b = 0.089); NICAM (a = -1.093, b = 0.030). NICAM underestimated 'a' and 'b', suggesting misrepresentation of small ice particle terminal velocity and the steepness of the size-velocity relationship.
  • Case 2 (tropical convection): EarthCARE (a = -0.853, b = 0.182); NICAM (a = -1.387, b = 0.062). Similar discrepancies were found.
• Retrieved vertical air velocities from EarthCARE/CPR data showed consistent upward motion near the cold front (at 52°S) and in tropical convection (near 13°N and 20°N), validating the retrieval method.
• Comparisons of retrieved and simulated vertical air velocity profiles showed agreement between 2 km and 9 km in the cold front case, but EarthCARE indicated stronger peak motion near 4 km and greater variance. In the tropical convection case, values aligned but diverged above 14 km, with increasing discrepancies below 8 km due to fast-falling hydrometeors.

Contributions

• Provides the first initial assessment of EarthCARE's spaceborne Doppler radar observations by comparing them with high-resolution global storm-resolving model simulations (NICAM).
• Demonstrates EarthCARE's capability to provide physically consistent information on hydrometeor vertical motions, offering a new observational constraint for refining cloud microphysics and dynamics in global weather and climate models.
• Proposes and validates a simpler, intuitive method for estimating vertical air velocity from spaceborne Doppler radar data based on a power-law relationship between terminal velocity and radar reflectivity.
• Identifies specific systematic biases in NICAM's microphysics scheme, particularly regarding the relationship between snow particle size and terminal velocity, suggesting areas for model improvement.
• Emphasizes the critical synergy between satellite observations and high-resolution numerical simulations for advancing the understanding of cloud systems and improving atmospheric modeling and prediction.

Funding

• Japan Aerospace Exploration Agency (EORA3) for the EarthCARE mission (25RT000098)
• JSPS KAKENHI (grant 24K00703)
• JSPS Core-to-Core Program (grant JPJSCCA20220001)
• JSPS KAKENHI (grant JP24H00275)
• Collaborative Research Program of the Research Institute for Applied Mechanics, Kyushu University
• JSPS KAKENHI (grant JP24K22898)
• Supercomputer Fugaku (Project ID: hp240106)
• National Institute for Environmental Studies (partial computational resources)

Citation

@article{Roh2025Vertical,
  author = {Roh, Woosub and Satoh, Masaki and Matsugishi, Shuhei and Aoki, Shunsuke and Kubota, Takuji and Okamoto, Hajime},
  title = {Vertical motions in clouds from EarthCare satellite and a global storm-resolving modeling},
  journal = {Scientific Reports},
  year = {2025},
  doi = {10.1038/s41598-025-32256-8},
  url = {https://doi.org/10.1038/s41598-025-32256-8}
}