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Lightning Assimilation in WRF4.0.2: Impact of Parameter Options and Introduction of New Lightning Data
Citation:
Kang, D., R. Gilliam, Jerold Herwehe, AND J. Pleim. Lightning Assimilation in WRF4.0.2: Impact of Parameter Options and Introduction of New Lightning Data. 2019 Community Modeling and Analysis System (CMAS) Conference, Chapel Hill, NC, October 21 - 23, 2019.
Impact/Purpose:
To develop efficient emission control strategies in State Implementation Plans that seek to attain National Ambient Air Quality Standards (NAAQS) for ozone and fine particulate matter (PM2.5) under the Clean Air Act, it is critical to have a modeling system to accurately predict the changes and trends of various constituents. As an integral part of air quality modeling system, meteorological models provide the meteorological fields to drive air quality model to simulate air pollutants. This presentation reports on a model excise to evaluate how the meteorological model (WRF) reacts to the different combinations of parameter options.
Description:
Lightning assimilation has been proven to be effective in improving atmospheric convection simulations in the Weather Research and Forecasting (WRF) model. A few parameter options are associated with the Kain-Fritch (KF) convective scheme in the WRF model: kfeta_trigger -controls how convections are trigged with values of 0 (default) and 1 (moisture-advection modulated trigger function) and cudt - minutes between cumulus physics calls (for example, cudt = 10, 10 minutes, and cudt = 0, call every time step). Different combinations of these parameter options are recommended with/without lightning assimilation for WRF simulations. In this model exercise, the possible combinations of these parameter options are applied to the WRFv4.0.2 simulations with/without lightning assimilation and the impact on 2-m temperature, water vapor mixing ratio, wind speed, and wind direction is evaluated against ground observations. Precipitation is assessed against the PRISM (Parameter elevation Regression on Independent Slopes Model) product that is ingested from in-situ point measurement. In addition to using lightning flash data from the National Lightning Detection Network (NLDN), the lightning data from the World Wide Lightning Location Network (WWLLN) is introduced for the first time to perform lightning assimilation in the WRF model. The preliminary assessment of using the new data source for lightning assimilation will be presented.