Executive Summary- Project 10-029
Wind Modeling Improvements with the Ensemble Kalman Filter
Meteorological models provide essential inputs to photochemical models that are used to simulate and study the formation and transport of air pollutants such as ozone. The appropriate treatment of vertical mixing in the lower atmosphere is a crucial component of meteorological and air quality models. Models use various schemes to simulate the vertical changes in heat, momentum, and other constituents within the lower portion of the atmosphere. Errors and uncertainties associated with these schemes remain one of the primary sources of inaccuracies in model predictions.
The purpose of this project is to improve meteorological analyses and forecasts, particularly of low-level winds and vertical diffusion, using a technique known as the Ensemble Kalman Filter (EnKF) data assimilation system. EnKF provides a methodology, using a combination of independent sources of observed and model-predicted information, to reduce errors in the model state resulting in an improved meteorological simulation. Previous work with a single case study demonstrated improvements in both analyses and forecasts using an initial version of EnKF. This project will obtain firmer conclusions regarding improved model performance by testing the procedure on other ozone episodes, increasing the number of considered model variables, and expanding the study to include a larger variety of meteorological conditions.
This meteorological research is directed toward the modeling priority area of the AQRP Strategic Plan. It specifically addresses the need for better use of data assimilation for more accurate modeling of individual ozone episodes and improvements in the physical representation of processes within the models. It also indirectly addresses all other modeling aspects of the AQRP Strategic Plan, because improved representation of winds and transport will allow more accurate conclusions to be drawn in all modeling studies involving meteorology, including but not limited to TCEQ attainment demonstrations.
This project utilizes the WRF (Weather Research and Forecast) mesoscale meteorological model and the Asymmetrical Convection Model, version 2 (ACM2) vertical mixing scheme. The final results will include software modifications for use in WRF along with the appropriate documentation. TCEQ can use the results of this project to potentially improve the meteorological model performance in their own models, and to continue to refine or improve the EnKF technique. Any improvements in meteorological model performance may lead to improved photochemical model performance and improved development of ozone control strategies and forecasts.