Preprints
https://doi.org/10.5194/gmd-2023-10
https://doi.org/10.5194/gmd-2023-10
Submitted as: development and technical paper
 | 
22 Feb 2023
Submitted as: development and technical paper |  | 22 Feb 2023
Status: this preprint is currently under review for the journal GMD.

An approach to refining the ground meteorological observation stations for improving PM2.5 forecasts in Beijing-Tianjin-Hebei region

Lichao Yang, Wansuo Duan, and Zifa Wang

Abstract. The paper investigates how to refine the ground meteorological observation network for greatly improving the PM2.5 concentration forecasts by identifying the sensitive areas for targeted observations associated with a total of 48 forecasts in eight heavy haze events during the years of 2016–2018 over the Beijing-Tianjin-Hebei (BTH) region. The conditional non-linear optimal perturbation (CNOP) method is adopted to determine the sensitive area of the surface meteorological fields for each forecast and a total of 48 CNOP-type errors are obtained including wind, temperature, and water vapor mixing ratio components. It is found that, although all the sensitive areas tend to locate within and/or surrounding the BTH region, their specific distributions are dependent on the events and the start times of the forecasts. Based on these sensitive areas, the current ground meteorological stations within and surrounding the BTH region are refined to form a cost-effective observation network, which makes the relevant PM2.5 forecasts starting from different initial times for varying events assimilate fewer observations but overall achieve the forecasting skill comparable to, even higher than that obtained by assimilating all ground station observations. This network sheds light on that some of the current ground stations within and surrounding the BTH region are very useless for improving the PM2.5 forecasts in the BTH region and can be greatly scattered to avoid the thankless work.

Lichao Yang et al.

Status: open (until 23 Apr 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Lichao Yang et al.

Lichao Yang et al.

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Short summary
We refine the ground meteorological stations by a nonlinear approach for improving the regional PM2.5 forecasts. The refined observation network (about 60 % of the current stations) can achieve almost the same improvements in PM2.5 forecasts as all the current station observations. The study will provide a scientific guidance to optimize the ground meteorological stations relative to PM2.5 forecasts and suggests an idea of cost-effective data assimilation for enhancing the PM2.5 forecast skills.