Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
Volume 9, issue 6
Geosci. Model Dev., 9, 2153-2165, 2016
https://doi.org/10.5194/gmd-9-2153-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Haze-fog forecasts and near real time (NRT) data application...

Geosci. Model Dev., 9, 2153-2165, 2016
https://doi.org/10.5194/gmd-9-2153-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Development and technical paper 14 Jun 2016

Development and technical paper | 14 Jun 2016

Development of an adjoint model of GRAPES–CUACE and its application in tracking influential haze source areas in north China

Xing Qin An1, Shi Xian Zhai1,2, Min Jin3, Sunling Gong1, and Yu Wang1 Xing Qin An et al.
  • 1State Key Laboratory of Severe Weather, Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
  • 2Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • 3Wuhan Meteorological Observatory, Wuhan 430040, China

Abstract. The aerosol adjoint module of the atmospheric chemical modeling system GRAPES–CUACE (Global–Regional Assimilation and Prediction System coupled with the CMA Unified Atmospheric Chemistry Environment) is constructed based on the adjoint theory. This includes the development and validation of the tangent linear and the adjoint models of the three parts involved in the GRAPES–CUACE aerosol module: CAM (Canadian Aerosol Module), interface programs that connect GRAPES and CUACE, and the aerosol transport processes that are embedded in GRAPES. Meanwhile, strict mathematical validation schemes for the tangent linear and the adjoint models are implemented for all input variables. After each part of the module and the assembled tangent linear and adjoint models is verified, the adjoint model of the GRAPES–CUACE aerosol is developed and used in a black carbon (BC) receptor–source sensitivity analysis to track influential haze source areas in north China.

The sensitivity of the average BC concentration over Beijing at the highest concentration time point (referred to as the Objective Function) is calculated with respect to the BC amount emitted over the Beijing–Tianjin–Hebei region. Four types of regions are selected based on the administrative division or the sensitivity coefficient distribution. The adjoint sensitivity results are then used to quantify the effect of reducing the emission sources at different time intervals over different regions. It is indicated that the more influential regions (with relatively larger sensitivity coefficients) do not necessarily correspond to the administrative regions. Instead, the influence per unit area of the sensitivity selected regions is greater. Therefore, controlling the most influential regions during critical time intervals based on the results of the adjoint sensitivity analysis is much more efficient than controlling administrative regions during an experimental time period.

Publications Copernicus
Special issue
Download
Short summary
The aerosol adjoint module of the atmospheric chemical modeling system GRAPES–CUACE was developed, tested for its correctness, and used in a receptor–source sensitivity test. The results showed that controlling critical emission sources during critical time intervals on the basis of adjoint sensitivity analysis is much more efficient than controlling administrative specified regions during an experiential time period.
The aerosol adjoint module of the atmospheric chemical modeling system GRAPES–CUACE was...
Citation
Share