Simulating lightning NO production in CMAQv5.2: evolution of scientific updates

Area of Science:

• Atmospheric Chemistry
• Air Quality Modeling
• Environmental Science

Background:

• Lightning is a significant natural source of nitric oxide (NO).
• Accurate modeling of lightning nitric oxide (LNO) is crucial for air quality assessments.
• Existing LNO production schemes in air quality models require refinement.

Purpose of the Study:

• To document and update lightning nitric oxide (LNO) production schemes within the Community Multiscale Air Quality (CMAQ) model.
• To compare LNO production estimates using different lightning data sources.
• To develop a new LNO scheme for scenarios lacking observational lightning data.

Main Methods:

• Documented existing LNO production schemes and vertical distribution algorithms in CMAQ.
• Updated LNO scheme using hourly National Lightning Detection Network (hNLDN) data.
• Developed a new LNO scheme (pNLDN) using historical NLDN data and meteorological simulations for data-scarce applications.

Main Results:

• The monthly NLDN (mNLDN) scheme overestimated LNO by over 40% compared to the hNLDN scheme.
• The hNLDN scheme provides a more faithful representation of observed lightning activity in time and space.
• The pNLDN scheme produced LNO columns comparable to hNLDN and generally outperformed mNLDN, especially when observed data are unavailable.

Conclusions:

• Updating LNO schemes with higher temporal resolution lightning data (hNLDN) significantly improves model accuracy.
• The developed pNLDN scheme offers a reliable alternative for estimating LNO emissions in air quality forecasts and climate studies.
• Accurate LNO emission estimates are vital for understanding and regulating air quality impacts from natural NO sources.