Abstract
This study focuses on analyzing the changes to aerosol properties caused by the dust storm called “China’s Great Wall of Dust” that originated from the Taklimakan Desert in April 2014. IDDI (Infrared Difference Dust Index) images from FY-2E and true color composite images from FY-3C MERSI (Medium Resolution Spectral Imager) show the breakout and transport path of the dust storm. Three-hourly ground-based measurements from MICAPS (Meteorological Information Comprehensive Analysis and Process System) suggest that anticyclonic circulation occupying the Southern Xinjiang basin and cyclonic circulation in Mongolia form a dipole pressure system that leads to strong northwesterly winds (13.7–20 m/s), which favored the breakout of the dust storm. IDDI results indicate that the dust storm breakout occurred at ~2:00 UTC on 23 April in the Taklimakan Desert. Four-day forward air mass trajectories with the HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model gives the simulation results of the dust transport paths and dust vertical distributions, which are consistent with the corresponding aerosol vertical distributions derived from CALIPSO. The Aerosol Index (AI) data of TOU (Total Ozone Unit) aboard FY-3B are first used to study the areas affected by the dust storm. From the AI results, the dust-affected areas agree well with the synoptic meteorological condition analysis, which supports that the synoptic meteorological conditions are the main reason for the breakout and transport of the dust storm. Anomalies of the average MODIS (Moderate Resolution Imaging Spectroradiometer) AOD (Aerosol Optical Depth) distributions over northeast Asia during the dust storm to the average of the values in April between 2010 and 2014 are calculated as a percent. The results indicate high aerosol loading with a spatially-averaged anomaly of 121% for dusty days between 23 April and 25 April. Aerosol Robotic Network (AERONET) retrievals of VSD (Volume Size Distribution) and SSA (Single Scattering Albedo) show that while the aerosol properties in Dalanzadgad, which is closer to the dust source, were influenced primarily by coarse dust particles, the aerosol properties in Beijing were mostly contributed by fine dust particles that transported over longer distances and at high atmospheric levels.
Highlights
Dust storms in northeast Asia usually occur during spring, especially during the months of March and April [1,2,3]
Network (AERONET) retrievals of Volume Size Distributions (VSD) (Volume Size Distribution) and SSA (Single Scattering Albedo) show that while the aerosol properties in Dalanzadgad, which is closer to the dust source, were influenced primarily by coarse dust particles, the aerosol properties in Beijing were mostly contributed by fine dust particles that transported over longer distances and at high atmospheric levels
The present study examined the transport of the dust storm termed “China’s Great Wall of Dust”
Summary
Dust storms in northeast Asia usually occur during spring, especially during the months of March and April [1,2,3]. Anomalous changes in large-scale atmospheric circulation, such as the Antarctic Oscillation (AAO) [5], the Arctic Oscillation (AO) [6] and the Pacific/North American (PNA) pattern [7], are reported to be closely related to the Dust Storm Frequency (DSF) in northern China These large-scale anomalous atmospheric circulation patterns can alter local climate factors, including temperature, precipitation, wind and moisture, which strongly influence dust storm activity in northeast Asia [8,9,10,11,12]. Because satellites cover large areas with high spatial and temporal resolution, they provide a unique approach to monitor and characterize changes to aerosol properties during the transport of dust storms. This paper is organized as follows: Section 2 describes the data and models used for the study; Section 3 provides the results from the forward trajectory model, observational datasets depicting the meteorological conditions and the changes to the aerosol properties caused by the dust storm; Section 4 summarizes and concludes this study
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