Comparisons of PBL heights derived from CALIPSO and ECMWF reanalysis data over China

Liu, Jingjing; Huang, Jianping; Chen, Bin; Zhou, Tian; Yan, Hongru; Jin, Hongchun; Huang, Zhongwei; Zhang, Beidou

doi:10.1016/j.jqsrt.2014.10.011

Cited by 66 publications

(55 citation statements)

References 27 publications

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“…In our collected PBLH datasets of the two years, the PBLH in northwest possessed a large span from 50 to 2800 m and had the largest standard deviation when compared to other regions of china, which is consistent with previous research finding that the boundary layer height varied dramatically due to high frequencies of temperature variation and surface pressure change, combined with the climatologically strong near-surface wind and intense solar radiation in northwestern China [50,51]. Assuming that aerosols are homogeneous under PBL, changes in PBLH could stretch or compress the surface aerosol layer, further influencing the density of aerosols, which led to the discrepancies of PM 2.5 with column AOD [26].…”

Section: The Recommended Vertical Correction Schemessupporting

confidence: 89%

Impact and Suggestion of Column-to-Surface Vertical Correction Scheme on the Relationship between Satellite AOD and Ground-Level PM2.5 in China

et al. 2017

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As China is suffering from severe fine particle pollution from dense industrialization and urbanization, satellite-derived aerosol optical depth (AOD) has been widely used for estimating particulate matter with an aerodynamic diameter less than 2.5 µm (PM 2.5 ). However, the correlation between satellite AOD and ground-level PM 2.5 could be influenced by aerosol vertical distribution, as satellite AOD represents the entire column, rather than just ground-level concentration. Here, a new column-to-surface vertical correction scheme is proposed to improve separation of the near-surface and elevated aerosol layers, based on the ratio of the integrated extinction coefficient within 200-500 m above ground level (AGL), using the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)) aerosol profile products. There are distinct differences in climate, meteorology, terrain, and aerosol transmission throughout China, so comparisons between vertical correction via CALIOP ratio and planetary boundary layer height (PBLH) were conducted in different regions from 2014 to 2015, combined with the original Pearson coefficient between satellite AOD and ground-level PM 2.5 for reference. Furthermore, the best vertical correction scheme was suggested for different regions to achieve optimal correlation with PM 2.5 , based on the analysis and discussion of regional and seasonal characteristics of aerosol vertical distribution. According to our results and discussions, vertical correction via PBLH is recommended in northwestern China, where the PBLH varies dramatically, stretching or compressing the surface aerosol layer; vertical correction via the CALIOP ratio is recommended in northeastern China, southwestern China, Central China (excluding summer), North China Plain (excluding Beijing), and the spring in the southeast coast, areas that are susceptible to exogenous aerosols and exhibit the elevated aerosol layer; and original AOD without vertical correction is recommended in Beijing and the southeast coast (excluding spring), where the elevated aerosol layer rarely occurs and a large proportion of aerosol is aggregated in near-surface. Moreover, validation experiments in 2016 agreed well with our discussions and conclusions drawn from the experiments of the first two years. Furthermore, suggested vertical correction scheme was applied into linear mixed effect (LME) model, and high cross validation (CV) R 2 (~85%) and relatively low root mean square errors (RMSE,~20 µg/m 3 ) were achieved, which demonstrated that the PM 2.5 estimation agreed well with the measurements. When compared to the original situation, CV R 2 values and RMSE after vertical correction both presented improvement to a certain extent, proving that the suggested vertical correction schemes could further improve the estimation accuracy of PM 2.5 based on sophisticated model in China. Estimating PM 2.5 with better accuracy could contribute to a more

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Section: The Recommended Vertical Correction Schemessupporting

confidence: 89%

Impact and Suggestion of Column-to-Surface Vertical Correction Scheme on the Relationship between Satellite AOD and Ground-Level PM2.5 in China

et al. 2017

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“…High terrain elevation corresponds to thinner air and lower value of aerosol optical thickness, less precipitable water vapor amount, and stronger solar radiation (Chen et al, 2014;Zhu et al, 2010), which enhance thermal convections and lead to high MMD. These results agree well with the study of Liu et al (2015) for Qinghai-Tibet-Yunnan Plateau. The spatial distribution of 25 transport wind speed is displayed in Fig.…”

Section: Ventilation Climatology 10supporting

confidence: 92%

Climatological study of a new air stagnation index (ASI) for China and its relationship with air pollution

Huang

Cai

Wang

et al. 2018

Preprint

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Abstract. Air stagnation index (ASI) is a vital meteorological measure of the atmosphere's ability to dilute air pollutants. The original metric adopted by US National Climatic Data Center (NCDC) is found not well suitable to China, because the decouple between upper and lower atmospheric layer results in a weak link between the near surface air pollution and upper-air wind speed. Therefore, a new threshold for ASI is proposed, consisting of daily 10 maximal ventilation in the atmospheric boundary layer, precipitation and real latent instability. In the present study, the climatological features of this newly defined ASI is investigated. It shows that the spatial distribution of the new ASI is similar to the original one; that is, annual mean stagnations occur most often in the northwest and southwest basins, i.e., Xinjiang and Sichuan basins (more than 180 days), and the least over plateaus, i.e., QinghaiTibet and Yunnan plateaus (less than 40 days). However, the seasonal cycle of the new ASI is changed. Stagnation 15 days under new metric are observed to be maximal in winter and minimal in summer, which is positively correlated with air pollution index (API) during 2000-2012. The correlation between ASI and concentration of fine particulate matter (PM2.5) during January 2013 of Beijing is also investigated. It shows that the new ASI matches the day-byday variation of PM2.5 concentration very well and is able to catch the haze episodes in that month. 20

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“…And, we found that this technique compared favorably to the ground-based lidar at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) ) with a correlation coefficient of 0.73 (Liu et al, 2015).…”

Section: Step 3: Determination Of Pbl Heightmentioning

confidence: 86%

Detection of anthropogenic dust using CALIPSO lidar measurements

et al. 2015

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Abstract. Anthropogenic dusts are those produced by human activities on disturbed soils, which are mainly cropland, pastureland, and urbanized regions, and are a subset of the total dust load which includes natural sources from desert regions. Our knowledge of anthropogenic dusts is still very limited due to a lack of data. To understand the contribution of anthropogenic dust to the total global dust load, it is important to identify it apart from total dust. In this study, a new technique for distinguishing anthropogenic dust from natural dust is proposed by using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) dust and planetary boundary layer (PBL) height retrievals along with a land use data set. Using this technique, the global distribution of dust is analyzed and the relative contribution of anthropogenic and natural dust sources to regional and global emissions are estimated. Results reveal that local anthropogenic dust aerosol due to human activity, such as agriculture, industrial activity, transportation, and overgrazing, accounts for about 25 % of the global continental dust load. Of these anthropogenic dust aerosols, more than 53 % come from semiarid and semi-wet regions. Annual mean anthropogenic dust column burden (DCB) values range from 0.42 g m −2 , with a maximum in India, to 0.12 g m −2 , with a minimum in North America. A better understanding of anthropogenic dust emission will enable us to focus on human activities in these critical regions and with such knowledge we will be more able to improve global dust models and to explore the effects of anthropogenic emission on radiative forcing, climate change, and air quality in the future.

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Comparisons of PBL heights derived from CALIPSO and ECMWF reanalysis data over China

Cited by 66 publications

References 27 publications

Impact and Suggestion of Column-to-Surface Vertical Correction Scheme on the Relationship between Satellite AOD and Ground-Level PM2.5 in China

Impact and Suggestion of Column-to-Surface Vertical Correction Scheme on the Relationship between Satellite AOD and Ground-Level PM2.5 in China

Climatological study of a new air stagnation index (ASI) for China and its relationship with air pollution

Detection of anthropogenic dust using CALIPSO lidar measurements

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