Applying the anomaly-based weather analysis on Beijing severe haze episodes

Area of Science:

• Atmospheric Science
• Environmental Science
• Meteorology

Background:

• Weather extremes, such as severe haze events, share similarities with other meteorological phenomena like storms.
• Anomaly-based meteorological variable analysis is an emerging method for studying and forecasting weather extremes.

Purpose of the Study:

• To analyze severe haze episodes in Beijing and North China using anomaly-based meteorological variable analysis.
• To identify key meteorological factors contributing to the intensification of PM2.5 pollution.

Main Methods:

• Applied anomaly-based meteorological variable analysis to ten severe haze episodes (PM2.5 > 300 μg/m³ for >24h) in Beijing/North China (2015-2016).
• Examined anomalous spatial features of tropospheric meteorological variables and their correlation with PM2.5 concentrations.

Main Results:

• Haze intensity correlates with five key factors: lower troposphere temperature inversion, surface negative geopotential anomaly, upper troposphere positive geopotential anomaly, southwesterly wind anomaly, and lower troposphere positive specific humidity anomaly.
• A significant correlation (0.56, 95% confidence) was found between upper troposphere geopotential anomaly and Beijing's PM2.5 concentration in December 2016.

Conclusions:

• The identified meteorological anomalies provide insights into the mechanisms driving severe haze formation.
• The European Centre for Medium-Range Weather Forecasts (ECMWF) model shows capability in predicting haze-related atmospheric structures and PM2.5 intensities up to a week in advance.