Variation of strong dust storm events in Northern China during 1978–2007

Wang, Ruxing; Liu, Bo; Li, Huiru; Zou, Xueyong; Wang, Jingpu; Liu, Wei; Cao, Hong; Kang, Liqiang; Zhang, Chunlai

doi:10.1016/j.atmosres.2016.09.002

Cited by 67 publications

(30 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, it is worth noting here that this trend is not obvious, since there were only a few areas in which dust AOD trends passed the significance test at the 95% confidence level (Figure a). This result is in general agreement with several previous studies (e.g., Chin et al, ; Kurosaki et al, ; Wang et al, ). For example, dust loadings over Mongolia, Inner Mongolia, and Northeast China were found to be enhanced by up to 5% between 1990–1999 and 2000–2009.…”

Section: The Dominant Mode and Shift In Springtime Dust Trends Over Esupporting

confidence: 94%

“…Consistent with our results, Chin et al () showed similar increasing trends in dust related AOD over EA during 2000–2009 by combining model‐simulated dust AOD and dust observations from multiple satellite sensors and ground‐based networks. Similarly, Wang et al () demonstrated that the frequency of large‐scale and longer‐lived dust storms over northern China increased from 1997 to 2007. More importantly, the EOF1 pattern shown in Figure a agrees well with the spatial distribution in springtime dust AOD trends by Wang et al ().…”

Section: The Dominant Mode and Shift In Springtime Dust Trends Over Ementioning

confidence: 90%

See 1 more Smart Citation

The Trend Reversal of Dust Aerosol Over East Asia and the North Pacific Ocean Attributed to Large‐Scale Meteorology, Deposition, and Soil Moisture

Guo

Liu

et al. 2019

JGR Atmospheres

View full text Add to dashboard Cite

The long‐term trend in dust loading over East Asia remains under debate and is dependent on the study period chosen. In this study, the long‐term trends in springtime dust over East Asia and the North Pacific Ocean (NPO) during 1980–2017 were examined based on the Modern‐Era Retrospective Analysis for Research and Applications version 2 reanalysis. Results showed that there was a spatial gradient in dust aerosol loadings, with decreases from western China eastward toward the NPO. This pattern was corroborated by Cloud‐Aerosol Lidar with Orthogonal Polarization observations. Furthermore, the empirical orthogonal function method was used to reveal the leading modes of springtime dust aerosol optical depth (AOD) over East Asia and the NPO. An abrupt shift occurred in the dust AOD trend in 2010 for the empirical orthogonal function 1 mode. The dust AOD increased at a rate of approximately 2 × 10‐4/year during 1999–2009 and then decreased more sharply (around 5 × 10‐4/year) afterward. This trend reversal of dust AOD was closely associated with a decrease in 10‐m wind velocity, which induces reduced dust emission. Compared with 10‐m wind, the soil moisture is less correlated with the trend reversal in dust AOD. Additionally, the trends of dry (wet) deposition were closely associated with the trends of the dust AOD, especially for the period 2010–2016. Overall, our findings add new insights to the long‐term nonlinear variability of dust.

show abstract

Section: The Dominant Mode and Shift In Springtime Dust Trends Over Esupporting

confidence: 94%

Section: The Dominant Mode and Shift In Springtime Dust Trends Over Ementioning

confidence: 90%

The Trend Reversal of Dust Aerosol Over East Asia and the North Pacific Ocean Attributed to Large‐Scale Meteorology, Deposition, and Soil Moisture

Guo

Liu

et al. 2019

JGR Atmospheres

View full text Add to dashboard Cite

show abstract

“…Therefore, SDSI is more sensitive than SDS frequency at reflecting the temporal variation in SDS events. Further case studies and field validations are required to test the performance of SDSI in reflecting SDS intensity, but SDSI appears to be suitable for accurately characterizing sand and dust storms by combining SDS frequency, SDS visibility, SDS duration, and SDS wind speed [38,39,50]. Instead of SDS frequency, SDSI can be applied to studies that are relevant to SDS intensity.…”

Section: Comparison Of Sdsi and Sds Frequencymentioning

confidence: 99%

“…Sand and dust storms caused by cold airflows from northern Asia (usually Siberian and Mongolian cyclones) [47,51] always sweep over Mongolia and inner Mongolia, and further extend toward the southeast and northeast provinces, such as Ningxia, Further case studies and field validations are required to test the performance of SDSI in reflecting SDS intensity, but SDSI appears to be suitable for accurately characterizing sand and dust storms by combining SDS frequency, SDS visibility, SDS duration, and SDS wind speed [38,39,50]. Instead of SDS frequency, SDSI can be applied to studies that are relevant to SDS intensity.…”

Section: Major Transportation Routes Of Sand and Dust Storms In The Tmentioning

confidence: 99%

Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data

Cao

Zhang

et al. 2018

Sustainability

View full text Add to dashboard Cite

Sand and dust storms (SDS) are global phenomena that significantly impact the socio-economy, human health, and the environment. The characterization of SDS intensity is a fundamental aspect of SDS issues and studies. In this study, a sand and dust storms index (SDSI) is developed to characterize SDS intensity by addressing the potential impacts of sand and dust storms on sensitive elements. Compared with other indices, SDSI includes four SDS-related components: SDS frequency, SDS visibility, SDS duration, and SDS wind speed. Using SDSI, this study characterizes the SDS intensity in the Three-North Forest Shelterbelt Program (TNFSP) region of China. The SDSI results show that high values of SDSI are mostly concentrated in southern Xinjiang, western and central Inner Mongolia, western and central Gansu, and northern Ningxia. By analyzing the SDSI components, over half of the stations experienced sand and dust storms no more than once per year on average. Most of the SDS events reduced horizontal visibility to less than 500 m, one-third of SDS events last more than two hours, and the wind speed of over half of the SDS events varied between 10-17 m/s. In comparison with SDS frequency, SDSI performs better in reflecting the spatial and temporal variation of SDS events. Therefore, instead of SDS frequency, SDSI can be applied to studies relevant to SDS intensity. Finally, five major SDS transportation routes were identified based on the surface prevailing wind direction, SDSI, and the existing literature. The SDS routes, combined with SDSI, could help governments and policy-makers cooperate on a regional level to combat SDS events more effectively.Keywords: sand and dust storms (SDS); sand and dust storms (SDS) index; sand and dust storms (SDS) intensity; sand and dust storms (SDS) routes

show abstract

“…The AOD variation obviously presents significant inter-annual cycle characteristics over the Beijing region and a unimodal or a bimodal distribution over the course of a year, among which peak values are primarily found in MAM and JJA, and the valley values are found in SON and DJF. In analyzing AOD variations (Wang et al, 2017). In the entire variation (blue line in Fig.…”

Section: Model Application--long-term Variation Of Aod At 500 Nm Overmentioning

confidence: 99%

Optimized Broadband Extinction Method for Retrieving 500 nm AOD with Long-Term Direct Solar Radiation: Model Test and Application

Xin

Liu

et al. 2017

Aerosol Air Qual. Res.

View full text Add to dashboard Cite

A traditional broadband extinction method is improved by introducing the cloud-screening module and aerosol modal adjustment module, and the new approach is known as optimized broadband extinction method (OBEM). Based on OBEM, it could retrieve 500 nm aerosol optical depth (AOD) database with the use of direct solar radiation. Comparison of the monthly average AOD from OBEM and Chinese Sun Hazemeter Network (CSHNET) for 2006-2010 over Beijing site shows that the retrievals and observations display a high degree of consistency. The correlation equation is Y = 1.00X -0.01 with a correlation coefficient R 2 of 0.83 and root-mean-square error (RMSE) of 0.08. The largest relative error for the yearly average value is only 3.85%. So it is clear that the OBEM could serve as an effective tool to retrieve highly accurate historical 500 nm AOD data and implement homogenization with the current observational 500 nm AOD monitored by satellites and sun-photometers. The yearly average AOD of Beijing in 1993-2010 is 0.58 ± 0.03, and the seasonal AODs in MAM (March-April-May) and JJA (June-July-August) are obviously higher than SON (SeptemberOctober-November) and DJF (December-January-February), with values of 0.70 ± 0.14 and 0.64 ± 0.16, respectively. The long-term 500 nm AOD reveal significant periodic inter-annual characteristics with a slight downward trend, and the irradiance also decreased due to the extinction of increasing total-cloud amount.

show abstract

Variation of strong dust storm events in Northern China during 1978–2007

Cited by 67 publications

References 42 publications

The Trend Reversal of Dust Aerosol Over East Asia and the North Pacific Ocean Attributed to Large‐Scale Meteorology, Deposition, and Soil Moisture

The Trend Reversal of Dust Aerosol Over East Asia and the North Pacific Ocean Attributed to Large‐Scale Meteorology, Deposition, and Soil Moisture

Characterizing Sand and Dust Storms (SDS) Intensity in China Based on Meteorological Data

Optimized Broadband Extinction Method for Retrieving 500 nm AOD with Long-Term Direct Solar Radiation: Model Test and Application

Contact Info

Product

Resources

About