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A record-breaking severe ozone (O3) pollution episode occurred in the Pearl River Delta (PRD) in early autumn 2019 when the PRD was under the influence of a Pacific subtropical high followed by Typhoon Mitag. In this study, we analyzed the effects of meteorological and photochemical processes on the O3 concentration in the PRD during this episode by carrying out the Weather Research Forecast–Community Multiscale Air Quality (WRF-CMAQ) model simulations. Results showed that low relative humidity, high boundary layer height, weak northerly surface wind, and strong downdrafts were the main meteorological factors contributing to O3 pollution. Moreover, delayed sea breezes that lasted into the night would transport O3 from the sea back to the land and resulted in secondary O3 maxima at night. In addition, O3 and its precursors stored in the residual layer above the surface layer at night can be mixed down to the surface in the next morning, further enhancing the daytime ground-level O3 concentration on the following day. Photochemical production of O3 , with a daytime average production rate of about 7.2 ppbh-1 (parts per billion), is found to be the predominate positive contributor to the O3 budget of the boundary layer (0–1260 m) during the entire O3 episode, while the horizontal and vertical transport fluxes are the dominant negative contributors. This O3 episode accounted for 10 out of the yearly total of 51 d when the maximum daily 8 h average (MDA8) O3 concentration exceeded the national standard of 75 ppb in the PRD in 2019. Based on these results, we propose that the enhanced photochemical production of O3 during the episode is a major cause of the most severe O3 pollution year since the official O3 observation started in the PRD in 2006. Moreover, since this O3 episode is a synoptic-scale phenomenon covering the entire eastern China, we also suggest that the enhanced photochemical production of O3 in this O3 episode is a major cause of the extraordinarily high O3 concentrations observed in eastern China in 2019. [ABSTRACT FROM AUTHOR]

Six dust storms that originated from Mongolia and moved to northern China in Spring 2021 are investigated by the anomaly variable‐based analysis method, which is compared to the traditional total‐variable based analysis method. Strong surface wind is a force to form dust storms as commonly known in current practice. However, dust area depicted by total‐wind model product analysis and operational forecast has a large bias to observation even for leading 24 hr. The analysis method of anomaly based variables showed that the domain of an airborne dust storm observed from satellite images is usually located between two neighboring convergence lines of 850 hPa anomalous winds. This connection of dust storm associated with the anomalous wind convergence extends southwestward from an anomalous cyclone and moves from Mongolia to northern China or Northeast China. It is thermodynamically associated with an anomalous thermal contrast, which has a spatial structure of wind, temperature, and geopotential height anomalies in the troposphere. We further found that numerical weather prediction products of the ECMWF model are able to indicate the anomalous wind pattern with lead times of 4–8 days by applying the anomaly based analysis approach. Therefore, this approach can not only depict dust area better but also reveal predictors much easier compared to the traditional total‐variable or full‐field‐based analysis method. Key Points: Dust storm can be well detected by the anomaly based analysis of atmospheric variablesA dust domain is located between two neighboring convergence lines of 850 hPa anomalous windsThe ECMWF model can predict the anomalous wind pattern for leading 4–8 days [ABSTRACT FROM AUTHOR]

Previous studies showed that 4D-Var technique used for data assimilation could be modified for weather control. This study demonstrates the ability of 4D-Var to influence the future path of a tropical cyclone by calculating perturbations in WRF simulation. Given the background error covariance matrix, the initial field is improved by the vortex dynamic initialization technique. Our results show that 4D-Var can be applied to control the trajectory of simulated tropical cyclones by producing "optimal" perturbations. In the numerical simulation experiment of Typhoon Mitag in 2019, after this kind of weather control similar to data assimilation, the tropical cyclone moved obviously, and the damaging wind over the coastline weakened. The prediction results after the initial field modified by 4D-Var have a great change, and the position of the tropical cyclone moved about 0.5° southeastward after assimilation, which misses the southeast coast of China. Moreover, the damaging wind is also weakened. Since the 4D-Var is premised on the assumption that the model is perfect and does not consider the model error, then the research plan to consider model error and introduce new methods is discussed in the paper. [ABSTRACT FROM AUTHOR]

Low visibility episodes (visibility < 1000 m) were studied by applying the anomaly-based weather analysis method. A regional episode of low visibility associated with a coastal fog that occurred from 27 to 28 January 2016 over Ningbo-Zhoushan Port, Zhejiang Province, East China, was first examined. Some basic features from the anomalous weather analysis for this case were identified: (1) the process of low visibility mainly caused by coastal fog was a direct response to anomalous temperature inversion in the lower troposphere, with a warm center around the 925 hPa level, which was formed by a positive geopotential height (GPH) anomaly in the upper troposphere and a negative GPH anomaly near the surface; (2) the positive humidity anomaly was conducive to the formation of coastal fog and rain; (3) regional coastal fog formed at the moment when the southwesterly wind anomalies transferred to northeasterly wind anomalies. Other cases confirmed that the low visibility associated with coastal fog depends upon low-level inversion, a positive humidity anomaly, and a change of wind anomalies from southwesterly to northeasterly, rain and stratus cloud amount. The correlation coefficients of six-hourly inversion, 850–925-hPa-averaged temperature, GPH and humidity anomalies against visibility are −0.31, 0.40 and −0.48, respectively, reaching the 99% confidence level in the first half-years of 2015 and 2016. By applying the anomaly-based weather analysis method to medium-range model output products, such as ensemble prediction systems, the anomalous temperature-pressure pattern and humidity—wind pattern can be used to predict the process of low visibility associated with coastal fog at several days in advance. [ABSTRACT FROM AUTHOR]

Nine rainfall events affecting southern China in the 2020 summer were studied by a novel anomaly-based synoptic analysis approach, and the results were compared to those of standard synoptic analysis. These rainfall events occurred in the Dragon-boat rainy season and Meiyu rainy season from the Pearl River to the Yangtze and Huaihe rivers and did not entirely follow the climatic seasonal march of the summer monsoon. The first rainfall event occurred within the Dragon-boat rainy season and was associated with a broad rainfall area with scattered precipitation centers related to a broad convergence area of anomalous flows with scattered moist vorticity anomaly (MVA) centers located between two anomalous anticyclonic systems at 925 hPa. The other eight rainfall events appeared in the Meiyu rainy season and were generally associated with only a narrow convergence belt of anomalous flows and a positive MVA belt, sometimes with an anomalous cyclone moving eastward in the lower troposphere. The ECMWF model successfully predicted these anomalous convergence areas and MVA belts with lead times of 2–7 days. The advantages of this anomaly-based analysis approach include its ability to visually identify the location of a rainfall event, pinpoint possible meteorological causes and extend the model forecast length by the earlier detection of predictors. • Southern China summer rainfall events occurring in 2020 were studied based on the anomaly-based synoptic analysis approach. • Rain bands were associated with anomalous convergence bands and moist vorticity anomalies (MVA) in the lower troposphere. • The ECMWF model products can predict the anomalous convergence and MVA areas (or bands) with lead times of 5–7 days. [ABSTRACT FROM AUTHOR]