Revisiting the Recent Dust Trends and Climate Drivers Using Horizontal Visibility and Present Weather Observations

被引:17
|
作者
Xi, Xin [1 ]
机构
[1] Michigan Technol Univ, Dept Geol & Min Engn & Sci, Houghton, MI 49931 USA
关键词
dust trend; dust variability; mineral dust; present weather; synoptic observations; visibility; NORTH-ATLANTIC OSCILLATION; AEROSOL OPTICAL DEPTH; MINERAL DUST; SURFACE WIND; AFRICAN DUST; ASIAN DUST; DROUGHT; STORMS; CHINA; VARIABILITY;
D O I
10.1029/2021JD034687
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This study revisits the use of surface weather observations from the NOAA Integrated Surface Database to examine the most recent dust trends and climate drivers in the context of multidecadal dust variability, following a critical assessment of the data completeness, temporal continuity, and cross-variable consistency of horizontal visibility and present weather reports. The global mean dust event frequency has increased at 0.02% yr(-1) from 1986 to 2019, driven by recent intensified activity resulting in a reversal of the previously reported declining dust trend over 1984-2012. Correlation analysis suggests that soil moisture has a lagged effect on the global dustiness with a maximum r = -0.3 when soil moisture leads by 14 months. North Africa experienced increased dust activity in the last decade (2010-2019), due to reduced soil moisture and enhanced wind speed following the transition of the North Atlantic Oscillation from strong negative to recurring positive phases in 2011. The Middle East had a significant decline of dust production since 2015 following the amelioration of a decade-long drought in the Tigris-Euphrates basin, as the climate shifts to more El Nino-like conditions as well as positive and weak negative Pacific Decadal Oscillation phases. East Asian dust variability is primarily driven by wind, which explains the negative trend from 1986 to 1997 and the absence of significant trends during the past two decades. This study constitutes an initial effort in creating a homogenized weather station-based data set for characterizing dust-climate connections on local and global scales.
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页数:23
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