Study Compares Two Weather Prediction Microphysics Schemes in Regional Simulations
Researchers from the University of Hawaiʻi and NCAR evaluated two microphysics parameterization schemes—NSSL and TEMPO—within the MPAS-A weather model across subtropical and tropical regions at up to 1-km resolution. Both schemes captured the general timing and location of convection but differed notably in storm structure, rainfall distribution, and hydrometeor composition. The findings highlight persistent model biases in convective organization and stratiform precipitation that limit forecast skill, particularly in weakly-forced weather regimes.
A new preprint study by Roseman et al. (2026) systematically compared two operational microphysics schemes—NSSL and Thompson-Eidhammer (TEMPO)—using hindcast simulations with the Model for Prediction Across Scales - Atmosphere (MPAS-A) on a variable-resolution mesh refined to 1-km. The experiments spanned three subtropical and tropical regions during boreal summer under both strongly- and weakly-forced convective regimes. TEMPO generated more numerous but weaker convective cores with earlier, more spatially widespread precipitation and cooler surface temperatures, whereas NSSL produced fewer, more intense cores with greater cloud water, ice, and graupel but less snow, and more spatially concentrated rainfall. Critically, both schemes diverged more from observations than from each other, producing scattered convective cells with insufficient mesoscale organization and underrepresented stratiform precipitation. The models also exhibited regime-dependent biases: rainfall was underestimated in strongly-forced regimes and overestimated in weakly-forced ones, with forecast skill notably lower in the latter. The authors conclude that process-level improvements targeting localized precipitation and convective organization across diverse regimes and regions are needed to advance numerical weather prediction in tropical and subtropical environments.
What's missing
The study is a preprint and has not yet undergone peer review, which limits confidence in its conclusions. The paper does not specify which observational datasets were used as ground truth for validation, making it difficult to assess the robustness of the bias characterizations. Additionally, the study is limited to boreal summer conditions and three subtropical/tropical regions, so generalizability to other seasons, regions, or model configurations remains an open question.
What different sources said
- arXiv physicsCenter
Comparison of Two Operational Microphysics Schemes Across Various Regional-MPAS Simulations
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