Improving lightning representation in global model through convective cloud based Price and Rind 1992 scheme

Area of Science:

• Atmospheric Science
• Meteorology
• Weather Forecasting

Background:

• Accurate lightning activity representation in medium-range weather forecasting models is challenging due to fine-scale electrification processes.
• The National Centre for Medium-Range Weather Forecasting Global Unified Model (NCUM-G) uses the Price and Rind (1992) (PR92) formulation, which currently relies on a cloud-thickness threshold for storm detection, leading to excessive false alarms over India.

Purpose of the Study:

• To enhance the accuracy of lightning parameterization in the NCUM-G, specifically over the Indian subcontinent.
• To evaluate and improve storm detection criteria and flash count estimation within the existing lightning parameterization framework.

Main Methods:

• Investigated three approaches to improve storm detection: modifying cloud depth definitions, redefining cloud-depth limits, and incorporating dynamical parameters alongside cloud depth.
• Evaluated the combination of column-maximum vertical velocity and cold cloud depth for storm identification.
• Utilized convective cloud-top height within the PR92 flash-count formulation.

Main Results:

• The modified scheme, using column-maximum vertical velocity, cold cloud depth, and convective cloud-top height, showed the most promising results.
• Fractional Skill Score (FSS) analysis confirmed enhanced skill in representing observed lightning flash counts at medium-range time scales.
• Categorical verification metrics (CSI, ETS) indicated a more balanced performance, reducing bias and false alarms while improving detection skill.

Conclusions:

• The refined lightning parameterization scheme in NCUM-G demonstrates a more realistic representation of lightning-producing convection over India.
• Despite improvements, persistent regional discrepancies are linked to systematic model biases in simulating convective processes.
• The study highlights the importance of refined storm identification criteria for accurate medium-range lightning forecasting.