Toward targeted observations of the meteorological initial state for improving the PM_2.5 forecast of a heavy haze event that occurred in the Beijing–Tianjin–Hebei region

Abstract. An advanced approach of conditional non-linear optimal perturbation (CNOP) was adopted to identify the sensitive area for targeted 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; specifically, 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 provides, beyond all doubt, theoretical guidance for practical field observations of meteorological fields associated with PM2.5 forecasts.