Articles | Volume 16, issue 3
https://doi.org/10.5194/essd-16-1185-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-1185-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
06 Mar 2024
Data description article |
| 06 Mar 2024
| 06 Mar 2024
The Tibetan Plateau space-based tropospheric aerosol climatology: 2007–2020
Honglin Pan
Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
Institute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, China
Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, China
Key Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, China
Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
Jiming Li
Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
Zhongwei Huang
Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
Minzhong Wang
Institute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, China
Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, China
Key Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, China
Ali Mamtimin
Institute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, China
Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, China
Key Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, China
Institute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, China
Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, China
Key Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, China
Fan Yang
Institute of Desert Meteorology, China Meteorological Administration, Urumqi, 830002, China
National Observation and Research Station of Desert Meteorology, Taklimakan Desert of Xinjiang, Urumqi, 830002, China
Taklimakan Desert Meteorology Field Experiment Station of China Meteorological Administration, Urumqi, 830002, China
Xinjiang Key Laboratory of Desert Meteorology and Sandstorm, Urumqi, 830002, China
Key Laboratory of Tree-ring Physical and Chemical Research, China Meteorological Administration, Urumqi, 830002, China
Tian Zhou
Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
Kanike Raghavendra Kumar
Department of Engineering Physics, College of Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur 522302, Andhra Pradesh, India
Related authors
No articles found.
Dongsheng Wu, Tian Zhou, Xingran Li, Yonghong Gu, Wenxuan Fan, Zikai Lin, Qili Gao, Keyu Zhang, and Zhongwei Huang
EGUsphere, https://doi.org/10.5194/egusphere-2026-5002, https://doi.org/10.5194/egusphere-2026-5002, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Saharan dust can be transported eastward over long distances, worsening air quality in East Asia. We found that in spring most dust moves eastward along different pathways, with differences in dust layer height, event scale, and duration. These pathways are controlled by changes in high-altitude winds and large-scale weather systems. These findings help explain long-range dust transport and can support early warning of air quality.
Yuchen Jiang, Yuan Wang, Qiudi Xu, Zhao Ji, Ping Zhang, Yang Wang, Hao Wu, Zhiliang Shu, Weiyuan Zhang, Xinyi Wang, and Jiming Li
EGUsphere, https://doi.org/10.5194/egusphere-2026-6076, https://doi.org/10.5194/egusphere-2026-6076, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
Distinguishing aerosols, droplets and ice crystals in mixed-phase clouds is challenging yet vital for cloud research. This work presents a ground-based particle classification method validated by lab and mountain field tests. Using combined parameters, it separates these particles with high accuracy and handles overlapping signals. This temperature-independent tool quantifies cloud freezing and aids cloud and climate studies.
Yifei Wang, Wen Huo, Mayibaier Maihamuti, and Yisilamu Wulayin
EGUsphere, https://doi.org/10.5194/egusphere-2026-4673, https://doi.org/10.5194/egusphere-2026-4673, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
The 1–20 m measurement combination yielded the most consistent wind estimates among those tested. Higher-level measurements generally produced larger estimates, particularly at the dune-surrounded site, where results also varied more with wind direction. Surface heating was more closely related to wind strength there than at the flatter site. These findings show that measurement height and local terrain influence how tower-based wind observations should be interpreted.
Ruixue Li, Jiming Li, Bida Jian, Lijie Zhang, and Jiayi Li
Atmos. Chem. Phys., 26, 12591–12612, https://doi.org/10.5194/acp-26-12591-2026, https://doi.org/10.5194/acp-26-12591-2026, 2026
Short summary
Short summary
Using satellite radiation observations and a surface energy framework, we show that recent cloud changes weakly affect global mean warming but strongly modulate regional warming, enhancing warming in low- and mid-latitudes while mitigating it in polar regions. This effect is driven by changes from low- and mid-level clouds to high-level thin clouds, reducing planetary albedo and weakening longwave emission, with distinct controls in the two hemispheres.
Zhongwei Huang, Wenjin Zhang, Qing Dong, Teruya Maki, Yongkai Wang, Yuanzong Ji, Fanli Xue, Xuefei Huo, Da Lu, Dongdong Wang, Jinsen Shi, Jianrong Bi, and Jianping Huang
Earth Syst. Sci. Data, 18, 6191–6206, https://doi.org/10.5194/essd-18-6191-2026, https://doi.org/10.5194/essd-18-6191-2026, 2026
Short summary
Short summary
Bioaerosols exert significant influences on climate, the environment, ecosystems, and public health. This study establishes an integrated bioaerosol dataset across East Asia using unified sampling and analytical methods. It was found that bioaerosol concentrations are negatively correlated with local Normalized Difference Vegetation Index (NDVI), and their relationship with atmospheric temperature is nonlinear. The α-diversity indices were negatively correlated with NDVI.
Zikai Lin, Tian Zhou, Zhengpeng Li, Yonghong Gu, Dongsheng Wu, Ping Zhou, Keyu Zhang, Qili Gao, Xingran Li, Zhongwei Huang, Jianrong Bi, Lili Yang, and Lina Wang
Atmos. Chem. Phys., 26, 11111–11133, https://doi.org/10.5194/acp-26-11111-2026, https://doi.org/10.5194/acp-26-11111-2026, 2026
Short summary
Short summary
This study examined high-altitude airborne particles over the Hexi Corridor using field observations. Such particles commonly accumulate 0.6–2 km aloft. Dunhuang features natural dust, while Minqin is dominated by human pollutants. Upper-level pollution is five times higher than that on the ground. These trapped particles warm the air and may accelerate glacier melting. This work suggests that high-altitude pollution should not be overlooked to better protect fragile local environments.
Yifei Wang, Wen Huo, Yongqiang Liu, Mayibaier Maihamuti, Fan Yang, Chenglong Zhou, Xinghua Yang, and Ali Mamtimin
Nat. Hazards Earth Syst. Sci., 26, 3523–3539, https://doi.org/10.5194/nhess-26-3523-2026, https://doi.org/10.5194/nhess-26-3523-2026, 2026
Short summary
Short summary
Dust storms threaten health, travel and farming, but the conditions that prepare them may change with season. We studied eight 2024 storms in the Taklimakan Desert using two towers, weather records and air-path tracking. Spring storms were mainly prepared by strong regional pressure differences, while summer storms showed stronger early ground heating, followed by rising winds just before they began. Local terrain altered these signals. The results may improve seasonal dust-storm warnings.
Chengqing Chen, Yang Wang, Jiming Li, Lu Feng, Tianrong Chai, Zhao Ji, Jian Wang, and Yuan Wang
Atmos. Chem. Phys., 26, 9017–9036, https://doi.org/10.5194/acp-26-9017-2026, https://doi.org/10.5194/acp-26-9017-2026, 2026
Short summary
Short summary
Our observations show that both local dust and dust carried over long distances can increase the number of particles that help form ice in clouds. Polluted air held fewer such particles and appears to weaken the ability of dust to initiate ice formation. In semi-arid cities, larger particles in the 1–2.5 µm range strongly indicate how many of these ice-forming particles are present. Understanding how different particles behave is essential for representing cloud glaciation and regional climate.
Jiayi Li, Yang Wang, Jiming Li, Weiyuan Zhang, Lijie Zhang, and Yuan Wang
Atmos. Chem. Phys., 25, 17455–17472, https://doi.org/10.5194/acp-25-17455-2025, https://doi.org/10.5194/acp-25-17455-2025, 2025
Short summary
Short summary
A key challenge in climate projections is the uncertainty in cloud water response to aerosols, especially from unclear diurnal microphysical-dynamical mechanisms. Geostationary satellite shows that neglecting the diurnal variations leads to an underestimation (up to 89 %) of the cooling effect induced by changes in cloud albedo due to aerosol perturbations. The results provide new insights in aerosol-cloud interactions, verifying this is a significant yet often overlooked source of uncertainty.
Hongxiang Yu, Li Guang, Benjamin Walter, Jianping Huang, Ning Huang, and Michael Lehning
The Cryosphere, 19, 5389–5402, https://doi.org/10.5194/tc-19-5389-2025, https://doi.org/10.5194/tc-19-5389-2025, 2025
Short summary
Short summary
Cornices are overhanging snow accumulations that form on mountain crests. Using wind-tunnel experiments and high-speed photography, the study tracks particle trajectories around cornices and finds distinct differences between edge and surface deposition. A static adhesion model for edge deposition was developed and validated to predict how particle size and shape affect adhesion. The work clarifies the microdynamics of early cornice growth and provides a foundation for avalanche modeling.
Ruixue Li, Bida Jian, Jiming Li, Deyu Wen, Lijie Zhang, Yang Wang, and Yuan Wang
Atmos. Chem. Phys., 24, 9777–9803, https://doi.org/10.5194/acp-24-9777-2024, https://doi.org/10.5194/acp-24-9777-2024, 2024
Short summary
Short summary
Hemispheric or interannual averages of reflected solar radiation (RSR) can mask signals from seasonally active or region-specific mechanisms. We examine RSR characteristics from latitude and month perspectives, revealing decreased trends observed by CERES in both hemispheres driven by clear-sky atmospheric and cloud components at 30–50° N and cloud components at 0–50° S. AVHRR achieves symmetry criteria within uncertainty and is suitable for the long-term analysis of hemispheric RSR symmetry.
Yuxin Zhao, Jiming Li, Deyu Wen, Yarong Li, Yuan Wang, and Jianping Huang
Atmos. Chem. Phys., 24, 9435–9457, https://doi.org/10.5194/acp-24-9435-2024, https://doi.org/10.5194/acp-24-9435-2024, 2024
Short summary
Short summary
This study identifies deep convection systems (DCSs), including deep convection cores and anvils, over the Tibetan Plateau (TP) and tropical Indian Ocean (TO). The DCSs over the TP are less frequent, showing narrower and thinner cores and anvils compared to those over the TO. TP DCSs show a stronger longwave cloud radiative effect at the surface and in the low-level atmosphere. Distinct aerosol–cloud–precipitation interaction is found in TP DCSs, probably due to the cold cloud bases.
Guangyao Dai, Songhua Wu, Wenrui Long, Jiqiao Liu, Yuan Xie, Kangwen Sun, Fanqian Meng, Xiaoquan Song, Zhongwei Huang, and Weibiao Chen
Atmos. Meas. Tech., 17, 1879–1890, https://doi.org/10.5194/amt-17-1879-2024, https://doi.org/10.5194/amt-17-1879-2024, 2024
Short summary
Short summary
An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
Qiantao Liu, Zhongwei Huang, Jiqiao Liu, Weibiao Chen, Qingqing Dong, Songhua Wu, Guangyao Dai, Meishi Li, Wuren Li, Ze Li, Xiaodong Song, and Yuan Xie
Atmos. Meas. Tech., 17, 1403–1417, https://doi.org/10.5194/amt-17-1403-2024, https://doi.org/10.5194/amt-17-1403-2024, 2024
Short summary
Short summary
The achieved results revealed that the ACDL observations were in good agreement with the ground-based lidar measurements during dust events. The heights of cloud top and bottom from these two measurements were well matched and comparable. This study proves that the ACDL provides reliable observations of aerosol and cloud in the presence of various climatic conditions, which helps to further evaluate the impacts of aerosol on climate and the environment, as well as on the ecosystem in the future.
Shikuan Jin, Yingying Ma, Zhongwei Huang, Jianping Huang, Wei Gong, Boming Liu, Weiyan Wang, Ruonan Fan, and Hui Li
Atmos. Chem. Phys., 23, 8187–8210, https://doi.org/10.5194/acp-23-8187-2023, https://doi.org/10.5194/acp-23-8187-2023, 2023
Short summary
Short summary
To better understand the Asian aerosol environment, we studied distributions and trends of aerosol with different sizes and types. Over the past 2 decades, dust, sulfate, and sea salt aerosol decreased by 5.51 %, 3.07 %, and 9.80 %, whereas organic carbon and black carbon aerosol increased by 17.09 % and 6.23 %, respectively. The increase in carbonaceous aerosols was a feature of Asia. An exception is found in East Asia, where the carbonaceous aerosols reduced, owing largely to China's efforts.
Yaozhi Jiang, Kun Yang, Youcun Qi, Xu Zhou, Jie He, Hui Lu, Xin Li, Yingying Chen, Xiaodong Li, Bingrong Zhou, Ali Mamtimin, Changkun Shao, Xiaogang Ma, Jiaxin Tian, and Jianhong Zhou
Earth Syst. Sci. Data, 15, 621–638, https://doi.org/10.5194/essd-15-621-2023, https://doi.org/10.5194/essd-15-621-2023, 2023
Short summary
Short summary
Our work produces a long-term (1979–2020) high-resolution (1/30°, daily) precipitation dataset for the Third Pole (TP) region by merging an advanced atmospheric simulation with high-density rain gauge (more than 9000) observations. Validation shows that the produced dataset performs better than the currently widely used precipitation datasets in the TP. This dataset can be used for hydrological, meteorological and ecological studies in the TP.
Yuxin Zhao, Jiming Li, Lijie Zhang, Cong Deng, Yarong Li, Bida Jian, and Jianping Huang
Atmos. Chem. Phys., 23, 743–769, https://doi.org/10.5194/acp-23-743-2023, https://doi.org/10.5194/acp-23-743-2023, 2023
Short summary
Short summary
Diurnal variations of clouds play an important role in the radiative budget and precipitation. Based on satellite observations, reanalysis, and CMIP6 outputs, the diurnal variations in total cloud cover and cloud vertical distribution over the Tibetan Plateau are explored. The diurnal cycle of cirrus is a key focus and found to have different characteristics from those found in the tropics. The relationship between the diurnal cycle of cirrus and meteorological factors is also discussed.
Chenglong Zhou, Yuzhi Liu, Qingzhe Zhu, Qing He, Tianliang Zhao, Fan Yang, Wen Huo, Xinghua Yang, and Ali Mamtimin
Atmos. Chem. Phys., 22, 5195–5207, https://doi.org/10.5194/acp-22-5195-2022, https://doi.org/10.5194/acp-22-5195-2022, 2022
Short summary
Short summary
Based on the radiosonde observations, an anomalously warm layer is measured at altitudes between 500 and 300 hPa over the Tarim Basin (TB) with an average intensity of 2.53 and 1.39 K in the spring and summer, respectively. The heat contributions of dust to this anomalously warm atmospheric layer in spring and summer were 13.77 and 10.25 %, respectively. Topographically, the TB is adjacent to the Tibetan Plateau; we propose the concept of the Tibetan heat source’s northward extension.
Jingyu Yao, Zhongming Gao, Jianping Huang, Heping Liu, and Guoyin Wang
Atmos. Chem. Phys., 21, 15589–15603, https://doi.org/10.5194/acp-21-15589-2021, https://doi.org/10.5194/acp-21-15589-2021, 2021
Short summary
Short summary
Gap-filling usually accounts for a large source of uncertainties in the annual CO2 fluxes, though gap-filling CO2 fluxes is challenging at dryland sites due to small fluxes. Using data collected from a semiarid site, four machine learning methods are evaluated with different lengths of artificial gaps. The artificial neural network and random forest methods outperform the other methods. With these methods, uncertainties in the annual CO2 flux at this site are estimated to be within 16 g C m−2.
Cited articles
Boos, W. and Kuang, Z.: Dominant control of the South Asian monsoon by orographic insulation versus plateau heating, Nature, 436, 218–222, 2010.
Bucci, S., Cagnazzo, C., Cairo, F., Di Liberto, L., and Fierli, F.: Aerosol variability and atmospheric transport in the Himalayan region from CALIOP 2007–2010 observations, Atmos. Chem. Phys., 14, 4369–4381, https://doi.org/10.5194/acp-14-4369-2014, 2014.
Buchard, V., da Silva, A. M., Colarco, P. R., Darmenov, A., Randles, C. A., Govindaraju, R., Torres, O., Campbell, J., and Spurr, R.: Using the OMI aerosol index and absorption aerosol optical depth to evaluate the NASA MERRA Aerosol Reanalysis, Atmos. Chem. Phys., 15, 5743–5760, https://doi.org/10.5194/acp-15-5743-2015, 2015.
Carrió, G. G., van Den Heever, S. C., and Cotton, W. R.: Impacts of nucleating aerosol on anvil-cirrus clouds: A modeling study, Atmos. Res., 84, 111–131, 2007.
Chen, S., Huang, J., Zhao, C., Qian, Y., Leung, L. R., and Yang, B.: Modeling the transport and radiative forcing of Taklimakan dust over the Tibetan Plateau: A case study in the summer of 2006, J. Geophys. Res.-Atmos., 118, 797–812, 2013.
Chen, S., Zhang, R., Mao, R., Zhang, Y., Chen, Y., Ji, Z., Gong, Y., and Guan, Y.: Sources, characteristics and climate impact of light-absorbing aerosols over the Tibetan Plateau, Earth-Sci. Rev., 232, 104111, https://doi.org/10.1016/j.earscirev.2022.104111, 2022.
Chen, X., Zuo, H., Zhang, Z., Cao, X., Duan, J., Zhu, C., Zhang, Z., and Wang, J.: Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China, Earth Syst. Sci. Data, 14, 5233–5252, https://doi.org/10.5194/essd-14-5233-2022, 2022.
Giles, D. M., Sinyuk, A., Sorokin, M. G., Schafer, J. S., Smirnov, A., Slutsker, I., Eck, T. F., Holben, B. N., Lewis, J. R., Campbell, J. R., Welton, E. J., Korkin, S. V., and Lyapustin, A. I.: Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements, Atmos. Meas. Tech., 12, 169–209, https://doi.org/10.5194/amt-12-169-2019, 2019.
Goldberg, D. L., Gupta, P., Wang, K., Jena, C., Zhang, Y., Lu, Z., and Streets, D. G.: Using gap-filled MAIAC AOD and WRF-Chem to estimate daily PM2.5 concentrations at 1 km resolution in the Eastern United States, Atmos. Environ., 199, 443–452, https://doi.org/10.1016/j.atmosenv.2018.11.049, 2019.
Guan, H., Chatfield, R. B., Freitas, S. R., Bergstrom, R. W., and Longo, K. M.: Modeling the effect of plume-rise on the transport of carbon monoxide over Africa with NCAR CAM, Atmos. Chem. Phys., 8, 6801–6812, https://doi.org/10.5194/acp-8-6801-2008, 2008.
Guan, H., Esswein, R., Lopez, J., Bergstrom, R., Warnock, A., Follette-Cook, M., Fromm, M., and Iraci, L. T.: A multi-decadal history of biomass burning plume heights identified using aerosol index measurements, Atmos. Chem. Phys., 10, 6461–6469, https://doi.org/10.5194/acp-10-6461-2010, 2010.
Hammer, M. S., Martin, R. V., Li, C., Torres, O., Manning, M., and Boys, B. L.: Insight into global trends in aerosol composition from 2005 to 2015 inferred from the OMI Ultraviolet Aerosol Index, Atmos. Chem. Phys., 18, 8097–8112, https://doi.org/10.5194/acp-18-8097-2018, 2018.
Hsu, N. C., Si-Chee, T., King, M. D., and Herman, J. R.: Aerosol properties over bright-reflecting source regions, IEEE T. Geosci. Remote, 42, 557–569, 2004.
Hu, Q., Wang, H., Goloub, P., Li, Z., Veselovskii, I., Podvin, T., Li, K., and Korenskiy, M.: The characterization of Taklamakan dust properties using a multiwavelength Raman polarization lidar in Kashi, China, Atmos. Chem. Phys., 20, 13817–13834, https://doi.org/10.5194/acp-20-13817-2020, 2020.
Hu, Y., Rodier, S., Xu, K., Sun, W., Huang, J., Lin, B., Zhai, P., and Josset, D.: Occurrence,liquid water content, and fraction of supercooled water clouds from combined CALIOP/IIR/MODIS measurements, J. Geophys. Res., 115, D00H34, https://doi.org/10.1029/2009JD012384, 2010.
Huang, J.: Dataset of characteristic parameters of tropospheric aerosols over the Qinghai Tibet Plateau (2007–2020), National Tibetan Plateau / Third Pole Environment Data Center [data set], https://doi.org/10.11888/Atmos.tpdc.300614, 2023.
Huang, J., Minnis, P., Chen, B., Huang, Z., Liu, Z., Zhao, Q., Yi, Y., and Ayers, J. K.: Long-range transport and vertical structure of Asian dust from CALIPSO and surface measurements during PACDEX, J. Geophys. Res.-Atmos., 113, https://doi.org/10.1029/2008JD010620, 2008.
Huang, L., Jiang, J. H., Tackett, J. L., Su, H., and Fu, R.: Seasonal and diurnal variations of aerosol extinction profile and type distribution from CALIPSO 5-year observations, J. Geophys. Res.-Atmos., 118, 4572–4596, 2013.
Immerzeel, W., Van Beek, L., and Bierkens, M.: Climate change will affect the Asian water towers, Science, 328, 1382–1385, 2010.
Iglewicz, B. and Hoaglin, D.: How to Detect and Handle Outliers, ASQC basic references in quality control, ASQC Quality Press, Milwaukee, 1993.
IPCC: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp., 2013.
IPCC: Climate Change 2021: The Physical Science Basis, Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, in press, https://doi.org/10.1017/9781009157896, 2021.
Jeong, M.-J. and Hsu, N. C.: Retrievals of aerosol single-scattering albedo and effective aerosol layer height for biomass-burning smoke: Synergy derived from “A-Train” sensors, Geophys. Res. Lett., 35, L24801, https://doi.org/10.1029/2008GL036279, 2008.
Kahn, R. A., Gaitley, B. J., Garay, M. J., Diner, D. J., Eck, T. F., Smirnov, A., and Holben, B. N.: Multiangle Imaging SpectroRadiometer global aerosol product assessment by comparison with the Aerosol Robotic Network, J. Geophys. Res.-Atmos., 115, D23209, https://doi.org/10.1029/2010jd014601, 2010.
Kim, M.-H., Omar, A. H., Tackett, J. L., Vaughan, M. A., Winker, D. M., Trepte, C. R., Hu, Y., Liu, Z., Poole, L. R., Pitts, M. C., Kar, J., and Magill, B. E.: The CALIPSO version 4 automated aerosol classification and lidar ratio selection algorithm, Atmos. Meas. Tech., 11, 6107–6135, https://doi.org/10.5194/amt-11-6107-2018, 2018.
Kojima, T., Buseck, P. R., Wilson, J. C., Reeves, J. M., and Mahoney, M. J.: Aerosol particles from tropical convective systems: Cloud tops and cirrus anvils, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2003JD004504, 2004.
Kovilakam, M., Thomason, L. W., Ernest, N., Rieger, L., Bourassa, A., and Millán, L.: The Global Space-based Stratospheric Aerosol Climatology (version 2.0): 1979–2018, Earth Syst. Sci. Data, 12, 2607–2634, https://doi.org/10.5194/essd-12-2607-2020, 2020.
Liou, K.: Influence of cirrus clouds on weather and climate processes: a global perspective, Mon. Weather Rev., 114, 1167–1199, 1986.
Liu, D., Wang, Z., Liu, Z., Winker, D., and Trepte, C.: A height resolved global view of dust aerosols from the first year CALIPSO lidar measurements, J. Geophys. Res., 113, D16214, https://doi.org/10.1029/2007JD009776, 2008.
Liu, P., Zhao, C., Liu, P., Deng, Z., Huang, M., Ma, X., and Tie, X.: Aircraft study of aerosol vertical distributions over Beijing and their optical properties, Tellus B, 61, 756–767, https://doi.org/10.1111/j.1600-0889.2009.00440.x, 2009.
Liu, Y., Hua, S., Jia, R., and Huang, J.: Effect of aerosols on the ice cloud properties over the Tibetan Plateau, J. Geophys. Res.-Atmos., 124, 9594–9608, 2019.
Liu, Y., Li, Y., Huang, J., Zhu, Q., and Wang, S.: Attribution of the Tibetan Plateau to northern drought, Nat. Sci. Rev., 7, 489–492, 2020.
Liu, Y., Huang, J., Wang, T., Li, J., Yan, H., and He, Y.: Aerosol-cloud interactions over the Tibetan Plateau: An overview, Earth-Sci. Rev., 234, 104216, https://doi.org/10.1016/j.earscirev.2022.104216, 2022.
Liu, Z., Liu, D., Huang, J., Vaughan, M., Uno, I., Sugimoto, N., Kittaka, C., Trepte, C., Wang, Z., Hostetler, C., and Winker, D.: Airborne dust distributions over the Tibetan Plateau and surrounding areas derived from the first year of CALIPSO lidar observations, Atmos. Chem. Phys., 8, 5045–5060, https://doi.org/10.5194/acp-8-5045-2008, 2008.
Liu, Z., Kar, J., Zeng, S., Tackett, J., Vaughan, M., Avery, M., Pelon, J., Getzewich, B., Lee, K.-P., Magill, B., Omar, A., Lucker, P., Trepte, C., and Winker, D.: Discriminating between clouds and aerosols in the CALIOP version 4.1 data products, Atmos. Meas. Tech., 12, 703–734, https://doi.org/10.5194/amt-12-703-2019, 2019.
Luo, H. and Yanai, M.: The large-scale circulation and heat sources over the Tibetan Plateau and surrounding areas during the early summer of 1979, Part II: Heat and moisture budgets, Mon. Weather Rev., 112, 966–989, 1984.
Matsuki, A., Iwasaka, Y., Osada, K., Matsunaga, K., Kido, M., Inomata, Y., Trochkine, D., Nishita, C., Nezuka, T., Sakai,T., Zhang,D., and Kwon, S. A.: Seasonal dependence of the long-range transport and vertical distribution of free tropospheric aerosols over east Asia: On the basis of aircraft and lidar measurements and isentropic trajectory analysis, J. Geophys. Res.-Atmos., 108, https://doi.org/10.1029/2002JD003266, 2003.
Molnar, P., Boos, W., and Battisti, D.: Orographic controls on climate and paleoclimate of Asia: thermal and mechanical roles for the Tibetan Plateau, Annu. Rev. Earth Planet. Sc., 38, 77–102, 2010.
Nakajima, T., Higurashi, A., Kawamoto, K., and Penner, J. E.: A possible correlation between satellite-derived cloud and aerosol microphysical parameters, Geophys. Res. Lett., 28, 1171–1174, https://doi.org/10.1029/2000GL012186, 2001.
Nieberding, F., Wille, C., Fratini, G., Asmussen, M. O., Wang, Y., Ma, Y., and Sachs, T.: A long-term (2005–2019) eddy covariance data set of CO2 and H2O fluxes from the Tibetan alpine steppe, Earth Syst. Sci. Data, 12, 2705–2724, https://doi.org/10.5194/essd-12-2705-2020, 2020.
Pan, H., Huo, W., Wang, M., Zhang, J., Meng, L., Kumar, K. R., and Devi, N. L.: Insight into the climatology of different sand-dust aerosol types over the Taklimakan Desert based on the observations from radiosonde and A-train satellites, Atmos. Environ., 238, 117705, https://doi.org/10.1016/j.atmosenv.2020.117705, 2020.
Qiu, J.: China: The third pole, Nature, 454, 393–396, https://doi.org/10.1038/454393a, 2008.
Rieger, L. A., Bourassa, A. E., and Degenstein, D. A.: Merging the OSIRIS and SAGE II stratospheric aerosol records, J. Geophys. Res.-Atmos., 120, 8890–8904, https://doi.org/10.1002/2015JD023133, 2015.
Rieger, L. A., Zawada, D. J., Bourassa, A. E., and Degenstein, D. A.: A Multiwavelength Retrieval Approach for Improved OSIRIS Aerosol Extinction Retrievals, J. Geophys. Res.-Atmos., 124, 7286–7307, https://doi.org/10.1029/2018JD029897, 2019.
Rossow, W. and Schiffer, R.: Advances in understanding clouds from ISCCP, B. Am. Meteorol. Soc., 80, 2261–2287, 1999.
Sasano, Y.: Tropospheric aerosol extinction coefficient profiles derived from scanning lidar measurements over Tsukuba, Japan from 1990 to 1993, Appl. Optics, 35, 4941–4952, 1996.
Seifert, P., Ansmann, A., Müller, D., Wandinger, U., Althausen, D., Heymsfield, A. J., Massie, S. T., and Schmitt, C.: Cirrus optical properties observed with lidar, radiosonde, and satellite over the tropical Indian Ocean during the aerosol-polluted northeast and clean maritime southwest monsoon, J. Geophys. Res.-Atmos., 112, https://doi.org/10.1029/2006JD008352, 2007.
Thomason, L. W. and Vernier, J.-P.: Improved SAGE II cloud/aerosol categorization and observations of the Asian tropopause aerosol layer: 1989–2005, Atmos. Chem. Phys., 13, 4605–4616, https://doi.org/10.5194/acp-13-4605-2013, 2013.
Torres, O., Bhartia, P. K., Herman, J. R., Ahmad, Z., and Gleason, J.: Derivation of aerosol properties from satellite measurements of backscattered ultraviolet radiation: Theoretical basis, J. Geophys. Res., 103, 17099–17110, https://doi.org/10.1029/98JD00900, 1998.
Torres, O., Tanskanen, A., Veihelmann, B., Ahn, C., Braak, R., Bhartia, P. K., Veefkind, P., and Levelt, P.: Aerosols and surface UV products from Ozone Monitoring Instrument observations: An overview, J. Geophys. Res., 112, D24S47, https://doi.org/10.1029/2007JD008809, 2007.
Twomey, S. A.: The influence of pollution on the shortwave albedo of clouds, J. Atmos. Sci., 34, 1149–1154, 1977.
Vernier, J. P., Fairlie, T. D., Natarajan, M., Wienhold, F. G., Bian, J., Martinsson, B. G., Crumeyrolle, S., Thomason, L. W., and Bedka, K. M.: Increase in upper tropospheric and lower stratospheric aerosol levels and its potential connection with Asian pollution, J. Geophys. Res.-Atmos., 120, 1608–1619, 2015.
Wan, B., Gao, Z., Chen, F., and Lu, C.: Impact of Tibetan Plateau surface heating on persistent extreme precipitation events in Southeastern China, Mon. Weather Rev., 145, 3485–3505, 2017.
Wei, X., Bai, K., Chang, N.-B., and Gao, W.: Multi-source hierarchical data fusion for high-resolution AOD mapping in a forest fire event, Int. J. Appl. Earth Obs., 102, 102366, https://doi.org/10.1016/j.jag.2021.102366, 2021.
Winker, D. M., Hunt, W. H., and McGill, M. J.: Initial performance assessment of CALIOP, Geophys. Res. Lett., 34, L19803, https://doi.org/10.1029/2007GL030135, 2007.
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young, S. A.: Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos. Ocean. Tech., 26, 2310–2323, 2009.
Wu, G. and Zhang, Y.: Tibetan Plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea, Mon. Weather Rev., 126, 913–927, 1998.
Wu, G., Liu, Y., Zhang, Q., Duan, A., Wang, T., Wan, R., Liu, X., Li, W., Wang, Z., and Liang, X.: The influence of mechanical and thermal forcing by the Tibetan Plateau on Asian climate, J. Hydro. Meteor. Spec. Sect., 8, 770–789, 2007.
Wu, G., Liu, Y., Dong, B., Liang, X., Duan, A., Bao, Q., and Yu, J.: Revisiting Asian monsoon formation and change associated with Tibetan Plateau forcing: I. Formation, Clim. Dynam., 39, 1169–1181, 2012.
Wu, G., Duan, A., Liu, Y., Mao, J., Ren, R., Bao, Q., He, B., Liu, B., and Hu, W.: Tibetan Plateau climate dynamics: recent research progress and outlook, Natl. Sci. Rev., 2, 100–116, 2015.
Xu, C., Ma, Y. M., You, C., and Zhu, Z. K.: The regional distribution characteristics of aerosol optical depth over the Tibetan Plateau, Atmos. Chem. Phys., 15, 12065–12078, https://doi.org/10.5194/acp-15-12065-2015, 2015.
Xu, X., Lu, C., Shi, X., and Gao, S.: World water tower: an atmospheric perspective, Geophys. Res. Lett., 35, L20815, https://doi.org/10.1029/2008gl035867, 2008.
Yanai, M., Li, C., and Song, Z.: Seasonal heating of the Tibetan Plateau and its effects on the evolution of the Asian summer monsoon, J. Meteor. Soc. Japan, 70, 319–351, 1992.
Zhang, S., Huang, Z., Li, M., Shen, X., Wang, Y., Dong, Q., Bi, J., Zhang, J., Li, W., Li, Z., and Song, X.: Vertical structure of dust aerosols observed by a ground-based raman lidar with polarization capabilities in the center of the Taklimakan desert, Remote Sens., 14, 2461, https://doi.org/10.3390/rs14102461, 2022.
Zhang, S., Huang, Z., Alam, K., Li, M., Dong, Q., Wang, Y., Shen, X., Bi, J., Zhang, J., Li, W., Li, Z., Wang, W., Cui, Z., and Song, X.: Derived Profiles of CCN and INP Number Concentrations in the Taklimakan Desert via Combined Polarization Lidar, Sun-Photometer, and Radiosonde Observations, Remote Sens., 15, 1216, https://doi.org/10.3390/rs15051216, 2023.
Zhou, J., Yu, G., Jin, C., Qi, F., Liu, D., Hu, H., Gong, Z., Shi, G., Nakajima, T., and Takamura, T.: Lidar observations of Asian dust over Hefei, China in Spring 2000, J. Geophys. Res., 107, 4252, https://doi.org/10.1029/2001JD000802, 2002.
Short summary
We applied several correction procedures and rigorously checked for data quality constraints during the long observation period spanning almost 14 years (2007–2020). Nevertheless, some uncertainties remain, mainly due to technical constraints and limited documentation of the measurements. Even though not completely accurate, this strategy is expected to at least reduce the inaccuracy of the computed characteristic value of aerosol optical parameters.
We applied several correction procedures and rigorously checked for data quality constraints...
Altmetrics
Final-revised paper
Preprint