You are here:
THE VALUE OF NUDGING IN THE METEOROLOGY MODEL FOR RETROSPECTIVE CMAQ SIMULATIONS
Citation:
OTTE, T. L. THE VALUE OF NUDGING IN THE METEOROLOGY MODEL FOR RETROSPECTIVE CMAQ SIMULATIONS. Presented at 5th Annual CMAS Models-3 User's Conference, Chapel Hill, NC, October 16 - 18, 2006.
Impact/Purpose:
The objectives of this task are to continue development and improvement of EPA's mesoscale (regional through urban scale) air quality modeling systems, such as the Community Multiscale Air Quality (CMAQ) model, as air quality management and NAAQS implementation tools. This task focuses on needed research and development of air quality models targeted for a major CMAQ model release in FY08. Model development for a broad scope of application is envisioned. For example, CMAQ will need to be able to simulate air quality feedbacks to meteorology and climate as well as intercontinental transport. The 2008 release of CMAQ is timed to coincide with EPA/OAR's and the states' needs for an improved model for assessments of progress (mid-course corrections) in the post-SIP submittal timeframe.
Description:
Using a nudging-based data assimilation approach throughout a meteorology simulation (i.e., as a "dynamic analysis") is considered valuable because it can provide a better overall representation of the meteorology than a pure forecast. Dynamic analysis is often used in the Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) to generate multi-day meteorology simulations that are used as background for the Community Multiscale Air Quality (CMAQ) Modeling System when CMAQ is used for retrospective research and regulatory applications. Because the influence of the input meteorology fields (e.g., from MM5) is significant, it may be considered intuitively obvious that using nudging to provide a dynamic analysis will lead to an improved air quality simulation. However, the penalty if nudging is not used in the meteorology model has not yet been quantified. This paper provides preliminary insights into the value to the chemistry model simulation of using nudging-based data assimilation for dynamic analysis in the meteorology fields that are input to CMAQ.