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Featured researches published by Ke Gui.


Science of The Total Environment | 2018

Temporal and spatial variations in sand and dust storm events in East Asia from 2007 to 2016: Relationships with surface conditions and climate change

Linchang An; Huizheng Che; Min Xue; Tianhang Zhang; Hong Wang; Yaqiang Wang; Chunhong Zhou; Hujia Zhao; Ke Gui; Yu Zheng; T. R. Sun; Yuanxin Liang; Enwei Sun; Hengde Zhang; Xiaoye Zhang

We analyzed the frequency and intensity of sand and dust storms (SDSs) in East Asia from 2007 to 2016 using observational data from ground stations, numerical modeling, and vegetation indices obtained from both satellite and reanalysis data. The relationships of SDSs with surface conditions and the synoptic circulation pattern were also analyzed. The statistical analyses demonstrated that the number and intensity of SDS events recorded in spring during 2007 to 2016 showed a decreasing trend. The total number of spring SDSs decreased from at least ten events per year before 2011 to less than ten events per year after 2011. The overall average annual variation of the surface dust concentration in the main dust source regions decreased 33.24μg/m3 (-1.75%) annually. The variation in the temperatures near and below the ground surface and the amount of precipitation and soil moisture all favored an improvement in vegetation coverage, which reduced the intensity and frequency of SDSs. The strong winds accompanying the influx of cold air from high latitudes showed a decreasing trend, leading to a decrease in the number of SDSs and playing a key role in the decadal decrease of SDSs. The decrease in the intensity of the polar vortex during study period was closely related to the decrease in the intensity and frequency of SDSs.


Advances in Meteorology | 2017

Characteristics of Water Vapor in the UTLS over the Tibetan Plateau Based on AURA/MLS Observations

Yi Sun; Quanliang Chen; Ke Gui; Fangyou Dong; Xiao Feng; Qichao Long

Water vapor (WV) has a vital effect on global climate change. Using satellite data observed by AURA/MLS and ERA-Interim reanalysis datasets, the spatial distributions and temporal variations of WV were analyzed. It was found that high WV content in the UTLS over the southern Tibetan Plateau is more apparent in summer, due to monsoon-induced strong upward motions. The WV content showed the opposite distribution at 100u2009hPa, though, during spring and winter. And a different distribution at 121u2009hPa indicated that the difference in WV content between the northern and southern plateau occurs between 121 and 100u2009hPa in spring and between 147 and 121u2009hPa in winter. In the UTLS, it diminishes rapidly with increase in altitude in these two seasons, and it shows a “V” structure in winter. There has been a weak increasing trend in WV at 100u2009hPa, but a downtrend at 147 and 215u2009hPa, during the past 12 years. At the latter two heights, the WV content in summer has been much higher than in other seasons. Furthermore, WV variation showed a rough wave structure in spring and autumn at 215u2009hPa. The variation of WV over the Tibetan Plateau is helpful in understanding the stratosphere-troposphere exchange (STE) and climate change.


Journal of meteorological research | 2017

Optical and Radiative Properties of Aerosols during a Severe Haze Episode over the North China Plain in December 2016

Yu Zheng; Huizheng Che; Leiku Yang; Jing Chen; Yaqiang Wang; Xiangao Xia; Hujia Zhao; Hong Wang; Deying Wang; Ke Gui; Linchang An; T. R. Sun; Jie Yu; Xiang Kuang; Xin Li; Enwei Sun; Dapeng Zhao; Dongsen Yang; Zengyuan Guo; Tianliang Zhao; Xiaoye Zhang

The optical and radiative properties of aerosols during a severe haze episode from 15 to 22 December 2016 over Beijing, Shijiazhuang, and Jiaozuo in the North China Plain were analyzed based on the ground-based and satellite data, meteorological observations, and atmospheric environmental monitoring data. The aerosol optical depth at 500 nm was < 0.30 and increased to > 1.4 as the haze pollution developed. The Ångström exponent was > 0.80 for most of the study period. The daily single-scattering albedo was > 0.85 over all of the North China Plain on the most polluted days and was > 0.97 on some particular days. The volumes of fine and coarse mode particles during the haze event were approximately 0.05–0.21 and 0.01–0.43 μm3, respectively—that is, larger than those in the time without haze. The daily absorption aerosol optical depth was about 0.01–0.11 in Beijing, 0.01–0.13 in Shijiazhuang, and 0.01–0.04 in Jiaozuo, and the average absorption Ångström exponent varied between 0.6 and 2.0. The aerosol radiative forcing at the bottom of the atmosphere varied from –23 to –227,–34 to –199, and –29 to –191 W m–2 for the whole haze period, while the aerosol radiative forcing at the top of the atmosphere varied from –4 to –98, –10 to –51, and –21 to –143 W m–2 in Beijing, Shijiazhuang, and Jiaozuo, respectively. Satellite observations showed that smoke, polluted dust, and polluted continental components of aerosols may aggravate air pollution during haze episodes. The analysis of the potential source contribution function and concentration-weighted trajectory showed that the contribution from local emissions and pollutants transport from upstream areas were 190–450 and 100–410 μg m–3, respectively.


Aerosol Science and Engineering | 2017

Comparison of Aerosol Optical Properties Between Two Nearby Urban Sites in Beijing, China

Jie Yu; Huizheng Che; Quanliang Chen; Hongbin Chen; Philippe Goloub; Ke Gui; Yu Zheng; Hong Wang; Yaqiang Wang; Linchang An; T. R. Sun; Xiaoye Zhang; Renjian Zhang; Mingkai Dai

This study compares the aerosol optical properties measured by CE318 sunphotometers at the Institute of Atmospheric Physics and the Chinese Academy of Meteorological Sciences in Beijing between January 2013 and July 2015 to provide the framework to quantify the spatial and temporal variability of aerosol properties. Aerosol optical parameters included extinction (scattering plus absorption) aerosol optical depth (EAOD), extinction Ångström exponent (EAE), columnar water vapor (CWV), absorption aerosol optical depth (AAOD), absorption Ångström exponent (AAE), extinction aerosol optical depth of fine particles (EAODf), extinction aerosol optical depth of coarse particles (EAODc), real parts of the refractive index (REFR), imaginary parts of the refractive index (REFI), single scattering albedo (SSA), asymmetry factor (ASYM), size distribution, and sphericity fraction. Comparison of aerosol optical properties using the simultaneous observations between two sites showed that correlation coefficients were larger than or equal to 0.98 for EAOD, EAE, and CWV, but smaller than or equal to 0.90 for AAOD, REFR, REFI, and SSA; the percentage differences for most of the parameters were less than 2%, but for EAODf were relatively large, ranging from 4.35 to 6.45%; the mean size distributions simultaneously showed bi-modal patterns, with two peak volumes at the radii of 0.15 and 2.94 μm; two kinds of tri-peak model were apparent during the study period; a case of EAODs at 440xa0nm differing by more than 0.2 between the two sites reflected the effect of local aerosol pollution. Comparison of aerosol characterization inferred by absorption properties using all the inversion data showed that classification using EAE, AAE, and sphericity fraction indicated the main aerosol type was “U/I&BB” (urban/industrial and biomass-burning), accounting for 59.87 and 57.43%, respectively; the volume size distribution retrievals binned by AAE exhibited coarse mode particles became dominant as AAE increased to 2.0; the SSA retrievals binned by AAE demonstrated SSA transitioned from spectra representing dust to U/I&BB pollution; averaged SSA for all the retrievals and SSA data partitioned by the EAE and η675xa0nm suggested there were more absorbing aerosols at IAP. The results of the study will be beneficial in validating satellite observations and model simulation results, providing more accurate input parameters for model simulations.


Atmosphere | 2016

Aerosol Optical Properties over Beijing during the World Athletics Championships and Victory Day Military Parade in August and September 2015

Yu Zheng; Huizheng Che; Tianliang Zhao; Xiangao Xia; Ke Gui; Linchang An; Bing Qi; Hong Wang; Yaqiang Wang; Jie Yu; Xiaoye Zhang


Atmosphere | 2016

Aerosol Optical Properties Based on Ground and Satellite Retrievals during a Serious Haze Episode in December 2015 over Beijing

Ke Gui; Huizheng Che; Quanliang Chen; Linchang An; Zhaoliang Zeng; Zengyuan Guo; Yu Zheng; Hong Wang; Yaqiang Wang; Jie Yu; Xiaoye Zhang


Atmospheric Chemistry and Physics | 2018

Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China

Huizheng Che; Bing Qi; Hujia Zhao; Xiangao Xia; Thomas F. Eck; Philippe Goloub; Oleg Dubovik; V. Estellés; Emilio Cuevas-Agulló; L. Blarel; Yunfei Wu; Jun Zhu; Rongguang Du; Yaqiang Wang; Hong Wang; Ke Gui; Jie Yu; Yu Zheng; T. R. Sun; Quanliang Chen; Guangyu Shi; Xiaoye Zhang


Atmosphere | 2016

Analysis of the Error in Retrievals of Aerosol Optical Properties from Sunphotometer Measurements of CARSNET Due to a Variety of Objective Factors

Ke Gui; Huizheng Che; Quanliang Chen; Jie Yu; Yu Zheng; Sai Lu; Hong Wang; Yaqiang Wang; Xiaoye Zhang; Guangyu Shi


Atmospheric Environment | 2017

Water vapor variation and the effect of aerosols in China

Ke Gui; Huizheng Che; Quanliang Chen; Zhaoliang Zeng; Yu Zheng; Qichao Long; T. R. Sun; Xinyu Liu; Yaqiang Wang; Tingting Liao; Jie Yu; Hong Wang; Xiaoye Zhang


Atmospheric Chemistry and Physics | 2017

Aerosol optical characteristics and their vertical distributions under enhanced haze pollution events: effect of the regional transport of different aerosol types over eastern China

T. R. Sun; Huizheng Che; Bing Qi; Yaqiang Wang; Yunsheng Dong; Xiangao Xia; Hong Wang; Ke Gui; Yu Zheng; Huijia Zhao; Qianli Ma; Rongguang Du; Xiaoye Zhang

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Huizheng Che

China Meteorological Administration

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Xiaoye Zhang

China Meteorological Administration

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Yaqiang Wang

China Meteorological Administration

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Hong Wang

China Meteorological Administration

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Yu Zheng

Nanjing University of Information Science and Technology

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T. R. Sun

Chinese Academy of Sciences

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Quanliang Chen

Chengdu University of Information Technology

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Hujia Zhao

China Meteorological Administration

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Xiangao Xia

Chinese Academy of Sciences

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Linchang An

Chinese Academy of Sciences

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