Preprints
https://doi.org/10.5194/acp-2022-77
https://doi.org/10.5194/acp-2022-77
 
17 Mar 2022
17 Mar 2022
Status: this preprint is currently under review for the journal ACP.

Toward target observations of the meteorological initial state for improving the PM2.5 forecast of a heavy haze event that occurred in the Beijing-Tianjin-Hebei region

Lichao Yang1, Wansuo Duan1,2, Zifa Wang2,3, and Wenyi Yang3 Lichao Yang et al.
  • 1LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
  • 2University of Chinese Academy of Sciences, Beijing, 100049, China
  • 3LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

Abstract. An advanced approach of Conditional Nonlinear Optimal Perturbation (CNOP) was adopted to identify the sensitive area for targeting observations of meteorological fields associated with PM2.5 concentration forecasts of a heavy haze event that occurred in the Beijing-Tianjin-Hebei (BTH) region, China, from 30 November to 4 December 2017. The results show that a few specific regions in the southern and northwestern directions close to the BTH region represent the sensitive areas. Numerically, when predetermined artificial observing arrays (i.e., possible “targeted observations”) in the sensitive areas were assimilated, the forecast errors of PM2.5 during the accumulation and dissipation processes were aggressively reduced; in particular, these assimilations, compared with those in other areas that have been thought of as being important for the PM2.5 forecasts in the BTH region in previous studies, exhibited a more obvious decrease in the forecast errors of PM2.5. Physically, the reason why these possible “targeted observations” can significantly improve the forecasting skill of PM2.5 was interpreted by comparing relevant meteorological fields before and after assimilation. Therefore, we conclude that preferentially deploying additional observations in the sensitive areas identified by the CNOP approach can greatly improve the forecasting skill of PM2.5, which, beyond all doubt, provides theoretical guidance for practical field observations of meteorological fields associated with PM2.5 forecasts.

Lichao Yang et al.

Status: open (until 01 Jun 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on acp-2022-77', Youmin Tang, 02 May 2022 reply
  • RC1: 'Comment on acp-2022-77', Anonymous Referee #1, 09 May 2022 reply
  • RC2: 'Comment on acp-2022-77', Anonymous Referee #2, 09 May 2022 reply

Lichao Yang et al.

Lichao Yang et al.

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Short summary
The meteorological initial state has a great impact on the PM2.5 forecasts. To improve the accuracy of the meteorological initial state, assimilating additional observations is an effective way. Here we used an advanced optimization approach to identify where we should preferentially place the meteorological observations associated with the PM2.5 forecasts in the BTH region of China. We provide evidences the target observation strategy is effective for improving the PM2.5 forecast.
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