Characteristic Analysis of Sandstorms in Taklamakan Desert

Abstract

Firstly, the annual variation of sandstorm and strong sandstorm weather process in China from 2000 to 2012 is analyzed according to the"Sand-Dust Weather Yearbook" (2012). Secondly, based on the ERA-Interim Reanalysis from ECMWF and MISR data from the Terra satellite, we investigate the correlation between different dust weather process and land meteorological elements. Finally, the temporal and spatial distribution features of the aerosol optical depth (AOD) in the Taklamakan Desert is studied. And we compare the Taklamakan Desert AOD with nationwide AOD. The results show that: (1) the frequency of sandstorm and strong sandstorm has shown a downward trend and the occurrence of sandstorm decreases more in recent years. (2) In the Taklamakan Desert, the number of sandstorm is positively correlated with the surface temperature, meanwhile, negatively related to the surface relative humidity. (3) In all seasons, the average of AOD in Taklamakan Desert is higher than that of the whole country, and there are obvious differences among the four seasons.

Evaluation of Five Reanalysis Products With Radiosonde Observations Over the Central Taklimakan Desert During Summer

“…As shown in Figure 1, TD is covered by moving sand that can spread hundreds of kilometers, causing inconvenient transportation (Sun et al., 2001). Besides, due to the dry climate, the frequency of sand storms have been increased in this region in the last decades (Guo et al., 2017; Huang et al., 2015; Wang et al., 2013; Yang et al., 2007), it brings danger to the habitants (Luo et al., 2017). More than this, as the main dust source in East Asia (Sun et al., 2001; Zhang et al., 2003), TD has a great influence on global weather and climate.…”

“…At present, as shown in Figure 1, there is only one conventional surface station available (shown as a black dot) in the Central Taklimakan Desert (CTD) due to the harsh natural conditions (e.g., moving‐sand, sandstorm), which is far below the requirement to understand the characteristics of weather and climate over this region. Consequently, atmospheric reanalysis data has been widely used for weather, climate, and environmental studies in this area as the substitute for observational data (e.g., Ge et al., 2016; Luo et al., 2017; Saeedi et al., 2019). However, there exist many uncertainties of the reanalysis data because only a few observational data in this region are assimilated into the reanalysis products (Whitaker et al., 2004).…”