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[期刊论文]

Effects of Spring Dust Aerosols on Direct Radiative Forcing in China from 2000 to 2020

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author:

Wang, Feng (Wang, Feng.) [1] | Qi, Minghui (Qi, Minghui.) [2] | Ren, Shuxin (Ren, Shuxin.) [3] | Unfold

Indexed by:

EI Scopus SCIE

Abstract:

In order to understand the mechanism of dust aerosol influence on regional climate change, it is crucial to quantify the radiative forcing effect of dust aerosols. However, studies on the direct radiative forcing of dust aerosols over long time series in China are still lacking. The direct radiative forcing effect of dust aerosols in China over the past 20 years was simulated and evaluated based on the WRF-Chem (Weather Research and Forecasting model coupled to Chemistry) model in conjunction with remote sensing satellites and ground-based observations. The results showed that dust aerosols exhibited an obvious inter-annual positive radiative forcing effect (about 0.38 W m(-2)) on net radiation at the top of the atmosphere, mainly in northwest China and the North China Plain, while at the atmosphere dust aerosols presented negative radiative forcing effects on shortwave radiation and positive effects on longwave radiation, with a value of 1.54 W m(-2) of net radiative forcing, showing a warming effect. Dust aerosols have a net radiative forcing value of -1.16 W m(-2) at the surface, indicating a cooling effect, with a positive forcing effect on longwave radiation and a negative forcing effect on shortwave radiation, both of which coincide with the geographical distribution of dust aerosol concentrations. In terms of inter-monthly variations, at both the atmosphere and top of the atmosphere, the dust aerosols net radiative forcing values showed an increasing trend, with March (-0.20 W m(-2) and 0.68 W m(-2)) < April (0.48 W m(-2) and 1.44 W m(-2)) < May (0.94 W m(-2) and 2.42 W m(-2)). Meanwhile, at the surface, the dust aerosols net radiative forcing values displayed a decreasing trend, with March (-0.88 W m(-2)) > April (-0.96 W m(-2)) > May (-1.48 W m(-2)).

Keyword:

China dust aerosol radiative forcing temporal and spatial distribution WRF-chem model

Community:

  • [ 1 ] [Wang, Feng]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 2 ] [Qi, Minghui]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 3 ] [Ren, Shuxin]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 4 ] [Zhu, Mengjie]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 5 ] [Xing, Qianlong]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 6 ] [Wang, Mengqiang]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 7 ] [Song, Hongquan]Henan Univ, Key Lab Geospatial Technol Middle & Lower Yellow R, Minist Educ, Kaifeng 475004, Peoples R China
  • [ 8 ] [Wang, Feng]Henan Univ, Key Res Inst Yellow River Civilizat & Sustainable, Kaifeng 475004, Peoples R China
  • [ 9 ] [Liu, Pengfei]Henan Univ, Key Res Inst Yellow River Civilizat & Sustainable, Kaifeng 475004, Peoples R China
  • [ 10 ] [Wang, Feng]Henan Univ, Collaborat Innovat Ctr Yellow River Civilizat Hena, Kaifeng 475004, Peoples R China
  • [ 11 ] [Liu, Pengfei]Henan Univ, Collaborat Innovat Ctr Yellow River Civilizat Hena, Kaifeng 475004, Peoples R China
  • [ 12 ] [Wang, Feng]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 13 ] [Qi, Minghui]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 14 ] [Ren, Shuxin]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 15 ] [Zhu, Mengjie]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 16 ] [Xing, Qianlong]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 17 ] [Wang, Mengqiang]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 18 ] [Song, Hongquan]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 19 ] [Liu, Pengfei]Henan Univ, Inst Urban Big Data, Coll Geog & Environm Sci, Kaifeng 475004, Peoples R China
  • [ 20 ] [Song, Hongquan]Henan Univ, Henan Key Lab Integrated Air Pollut Control & Ecol, Kaifeng 475004, Peoples R China
  • [ 21 ] [Wang, Qianfeng]Fuzhou Univ, Coll Environm & Safety Engn, Fuzhou 350116, Peoples R China

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Source :

REMOTE SENSING

ISSN: 2072-4292

Year: 2023

Issue: 18

Volume: 15

4 . 2

JCR@2023

4 . 2 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

30 Days PV: 0

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