Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
    6.201
  • CiteScore value: 6.13 CiteScore
    6.13
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Discussion papers
https://doi.org/10.5194/acp-2019-969
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-969
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 23 Jan 2020

Submitted as: research article | 23 Jan 2020

Review status
This preprint is currently under review for the journal ACP.

Development and application of the WRFDA-Chem 3DVAR system: aiming to improve air quality forecast and diagnose model deficiencies

Wei Sun1,2, Zhiquan Liu1, Dan Chen3, Pusheng Zhao3, and Min Chen3 Wei Sun et al.
  • 1National Center for Atmospheric Research, Boulder, CO, 80301, USA
  • 2National Space Science Center, Chinese Academy of Sciences, Beijing, 100190, China
  • 3Institute of Urban Meteorology, China Meteorology Administration, Beijing, 100089, China

Abstract. To improve the operational air quality forecasting over China, a new aerosol/gas phase pollutants assimilation capability is developed within the WRFDA system using 3DVAR algorithm. In this first application, the interface for MOSAIC aerosol scheme is built with flexible extending potentials. Based on the new WRFDA-Chem system, five experiments assimilating different surface observations, including PM2.5, PM10, SO2, NO2, O3, and CO are conducted for January 2017 along with a control experiment without DA. Results exhibit that the WRFDA-Chem system evidently improves the air quality forecasting. On the analysis aspect, the assimilation of surface observations reduces the bias and RMSE in the initial condition (IC) remarkably; on the forecast aspect, better forecast performances are acquired up to 24-h, in which the experiment assimilating the six pollutants simultaneously displays the best forecast skill overall. With respect to the impact of DA cycling frequency, the responses toward IC updating are found out to be different among the pollutants. For PM2.5, PM10, SO2 and CO, the forecast skills increase with the DA frequency; for O3, although improvements are acquired at the 6-h cycling frequency, the advantage of more frequent DA could be consumed by the disadvantage of unbalanced photochemistry (due to inaccurate precursor NOx/VOC ratios) from assimilating the existing observations (only O3 and NO2, but no VOC). Considering after one aspect (IC) in the model is corrected by DA, the deficiencies from other aspects (e.g., chemical reactions) could be more evident, this study further explores the model deficiencies by investigating the effects of assimilating gaseous precursors on the forecast of related aerosols. Results exhibit that the parameterization (uptake coefficients) in the newly added Sulfate-Nitrate-Ammonium (SNA) relevant heterogeneous reactions in the model are not fully appropriate although it best simulates observed SNA aerosols without DA; since the uptake coefficients were originally tuned under the inaccurate gaseous precursor scenarios without DA, the biases from the two aspects (SNA reactions and IC DA) were just compensated. In the future chemistry development, parameterizations (such as uptake coefficients) for different gaseous precursor scenarios should be adjusted and verified with the help of DA technique. According to these results, DA ameliorates certain aspects by using observation as constraints, and thus provides an opportunity to identify and diagnose the model deficiencies; it is useful especially when the uncertainties of various aspects are mixed up and the reaction paths are not clearly revealed. In the future, besides being used to improve the forecast through updating IC, DA could be treated as another approach to explore necessary developments in the model.

Wei Sun et al.

Interactive discussion

Status: open (until 19 Mar 2020)
Status: open (until 19 Mar 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Wei Sun et al.

Viewed

Total article views: 161 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
137 22 2 161 13 2 1
  • HTML: 137
  • PDF: 22
  • XML: 2
  • Total: 161
  • Supplement: 13
  • BibTeX: 2
  • EndNote: 1
Views and downloads (calculated since 23 Jan 2020)
Cumulative views and downloads (calculated since 23 Jan 2020)

Viewed (geographical distribution)

Total article views: 122 (including HTML, PDF, and XML) Thereof 121 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 25 Feb 2020
Publications Copernicus
Download
Short summary
A new aerosol/gas phase pollutants assimilation capability is developed within the WRFDA system with 3DVAR algorithm and MOSAIC aerosol scheme. By assimilating surface PM2.5, PM10, SO2, NO2, O3, and CO, the new WRFDA-Chem system evidently improves the air quality forecasting up to 24-h. Based on the WRFDA-Chem system, the model deficiencies are further explored. In the future, parameterization in the newly added SNA reactions in the model should be adjusted and verified with the help of DA.
A new aerosol/gas phase pollutants assimilation capability is developed within the WRFDA system...
Citation