A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

Tang, Youhua; Pagowski, Mariusz; Chai, Tianfeng; Pan, Li; Lee, Pius; Baker, Barry; Kumar, Rajesh; Delle Monache, Luca; Tong, Daniel; Kim, Hyun-Cheol

doi:https://doi.org/10.5194/gmd-10-4743-2017

Articles | Volume 10, issue 12

https://doi.org/10.5194/gmd-10-4743-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-10-4743-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 12

Development and technical paper

|

22 Dec 2017

Development and technical paper |

| 22 Dec 2017

A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods

Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius Lee, Barry Baker, Rajesh Kumar, Luca Delle Monache, Daniel Tong, and Hyun-Cheol Kim

Model code and software

Meteorological code of WRF 3.4.1 National Center for Atmospheric Research (NCAR) http://www2.mmm.ucar.edu/wrf/users/download/get_source.html

CMAQ 5.1 UNC Institute for the Environment https://www.cmascenter.org/download.cfm

GSI data assimilation tool Developmental Testbed Center http://www.dtcenter.org/com-GSI/users.v3.5/downloads/index.php

Short summary

In order to evaluate the data assimilation tools for regional real-time PM_2.5 forecasts, we applied a 3D-Var assimilation tool to adjust the aerosol initial condition by assimilating satellite-retrieved aerosol optical depth and surface PM_2.5 observations for a regional air quality model, which is compared to another assimilation method, optimal interpolation. We discuss the pros and cons of these two assimilation methods based on the comparison of their 1-month four-cycles-per-day runs.