Articles | Volume 14, issue 9
https://doi.org/10.5194/amt-14-5977-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-5977-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Sep 2021
Research article |
| 03 Sep 2021
| 03 Sep 2021
Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data
Hui Li
State Key Laboratory of Information Engineering in Surveying,
Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China
Shandong Provincial Engineering and Technical Center of Light
Manipulations & Shandong Provincial Key Laboratory of Optics and Photonic
Device, School of Physics and Electronics, Shandong Normal University, Jinan
250014, China
Boming Liu
CORRESPONDING AUTHOR
State Key Laboratory of Information Engineering in Surveying,
Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China
Xin Ma
CORRESPONDING AUTHOR
State Key Laboratory of Information Engineering in Surveying,
Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China
Shikuan Jin
State Key Laboratory of Information Engineering in Surveying,
Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China
Yingying Ma
State Key Laboratory of Information Engineering in Surveying,
Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan, China
Yuefeng Zhao
Shandong Provincial Engineering and Technical Center of Light
Manipulations & Shandong Provincial Key Laboratory of Optics and Photonic
Device, School of Physics and Electronics, Shandong Normal University, Jinan
250014, China
Wei Gong
School of Electronic Information, Wuhan University, Wuhan, China
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-473, https://doi.org/10.5194/essd-2025-473, 2025
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Yinbao Jin, Yiming Liu, Xiao Lu, Xiaoyang Chen, Ao Shen, Haofan Wang, Yinping Cui, Yifei Xu, Siting Li, Jian Liu, Ming Zhang, Yingying Ma, and Qi Fan
Atmos. Chem. Phys., 24, 367–395, https://doi.org/10.5194/acp-24-367-2024, https://doi.org/10.5194/acp-24-367-2024, 2024
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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
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Atmos. Chem. Phys., 23, 3181–3193, https://doi.org/10.5194/acp-23-3181-2023, https://doi.org/10.5194/acp-23-3181-2023, 2023
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Tianqi Shi, Zeyu Han, Ge Han, Xin Ma, Huilin Chen, Truls Andersen, Huiqin Mao, Cuihong Chen, Haowei Zhang, and Wei Gong
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Atmos. Meas. Tech., 15, 4323–4337, https://doi.org/10.5194/amt-15-4323-2022, https://doi.org/10.5194/amt-15-4323-2022, 2022
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Haowei Zhang, Boming Liu, Xin Ma, Ge Han, Qinglin Yang, Yichi Zhang, Tianqi Shi, Jianye Yuan, Wanqi Zhong, Yanran Peng, Jingjing Xu, and Wei Gong
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-215, https://doi.org/10.5194/essd-2022-215, 2022
Preprint withdrawn
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X. Xia, Z. Zhu, T. Zhang, G. Wei, and Y. Ji
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 545–550, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-545-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-545-2022, 2022
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Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
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Publication in AMT not foreseen
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Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is the comparison of wind speed on a large scale between the Aeolus, ERA5 and RS , shedding important light on the data application of Aeolus wind products.
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The vertical distribution of the aerosol extinction coefficient (EC) measured by lidar systems has been used to retrieve the profile of particle matter with a diameter of less than 2.5 μm (PM2.5). However, the traditional linear model cannot consider the influence of multiple meteorological variables sufficiently, which then causes low inversion accuracy. In this study, the machine learning algorithms which can input multiple features are used to solve this constraint.
Xin Lu, Feiyue Mao, Daniel Rosenfeld, Yannian Zhu, Zengxin Pan, and Wei Gong
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Jianping Guo, Boming Liu, Wei Gong, Lijuan Shi, Yong Zhang, Yingying Ma, Jian Zhang, Tianmeng Chen, Kaixu Bai, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys., 21, 2945–2958, https://doi.org/10.5194/acp-21-2945-2021, https://doi.org/10.5194/acp-21-2945-2021, 2021
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China have thus far not been evaluated by in situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future research and applications.
Boming Liu, Jianping Guo, Wei Gong, Yong Zhang, Lijuan Shi, Yingying Ma, Jian Li, Xiaoran Guo, Ad Stoffelen, Gerrit de Leeuw, and Xiaofeng Xu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-41, https://doi.org/10.5194/acp-2021-41, 2021
Revised manuscript not accepted
Short summary
Short summary
Vertical wind profiles are crucial to a wide range of atmospheric disciplines. Aeolus is the first satellite mission to directly observe wind profile information on a global scale. However, Aeolus wind products over China were thus far not evaluated by in-situ comparison. This work is expected to let the public and science community better know the Aeolus wind products and to encourage use of these valuable data in future researches and applications.
Lianfa Lei, Zhenhui Wang, Jiang Qin, Lei Zhu, Rui Chen, Jianping Lu, and Yingying Ma
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2020-283, https://doi.org/10.5194/amt-2020-283, 2020
Revised manuscript not accepted
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This paper proposes a new method of Multichannel Microwave Radiometer 3-D antenna pattern measurement by observing the sun. The antenna pattern derived from the solar observation was compared with the result of the far-field measurement with a point source in the microwave anechoic chamber at 30 GHz, the maximum error of the beamwidth is less than 0.1°, which showed that this pattern matched well to the pattern measurement using a point source in the microwave anechoic chamber.
Boming Liu, Jianping Guo, Wei Gong, Lijuan Shi, Yong Zhang, and Yingying Ma
Atmos. Meas. Tech., 13, 4589–4600, https://doi.org/10.5194/amt-13-4589-2020, https://doi.org/10.5194/amt-13-4589-2020, 2020
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Vertical wind profiles are crucial to a wide range of atmospheric disciplines. However, the wind profile across China remains poorly understood. Here we reveal the salient features of winds from the radar wind profile of China, including the main instruments, spatial coverage and sampling frequency. This work is expected to allow the public and scientific community to be more familiar with the nationwide network and encourage the use of these valuable data in future research and applications.
B. Chen, S. Shi, W. Gong, J. Sun, B. Chen, K. Guo, L. Du, J. Yang, Q. Xu, and S. Song
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 501–505, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-501-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-501-2020, 2020
B. Wang, S. Song, W. Gong, S. Shi, B. Chen, J. Yang, L. Du, and J. Sun
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 547–551, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-547-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-547-2020, 2020
S. Jin, Y. Ma, W. Gong, and M. Zhang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 807–812, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-807-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-807-2020, 2020
Cited articles
Aryee, J., Amekudzi, L., Preko, K., Atiah, W., and Danuor, S.: Estimation of planetary boundary layer height from radiosonde profiles over West Africa during the AMMA field campaign: Intercomparison of different methods, Scientific African, 7, 00228, https://doi.org/10.1016/j.sciaf.2019.e00228, 2020.
Bradley, R. S., Keimig, F. T., and Diaz, H. F.: Recent changes in the North American Arctic boundary layer in winter, J. Geophys. Res.-Atmos., 98, 8851–8858, https://doi.org/10.1029/93jd00311, 1993.
Emeis, S., Münkel, C., Vogt, S., Müller, W. J., and Schäfer, K.: Atmospheric boundary-layer structure from simultaneous sodar, rass, and ceilometer measurements, Atmos. Environ., 38, 273–286, https://doi.org/10.1016/j.atmosenv.2003.09.054, 2004.
Eresmaa, N., Karppinen, A., Joffre, S. M., Räsänen, J., and Talvitie, H.: Mixing height determination by ceilometer, Atmos. Chem. Phys., 6, 1485–1493, https://doi.org/10.5194/acp-6-1485-2006, 2006.
Garratt, J. R.: Review: the atmospheric boundary layer, Earth-Sci. Rev., 37, 89–134, https://doi.org/10.1016/0012-8252(94)90026-4, 1994.
Garratt, J. R., Wyngaard, J. C., and Francey, R. J.: Winds in the atmospheric boundary layer-prediction and observation, J. Atmos. Sci., 39, 1307–1316, https://doi.org/10.1175/1520-0469(1982)039<1307:WITABL>2.0.CO;2, 1982.
Guo, J., Zhang, X., Che, H., Gong, S., An, X., Cao, C., Guang, J., Zhang, H., Wang, Y., and Zhang, X.: Correlation between PM concentrations and aerosol optical depth in eastern China, Atmos. Environ., 43, 5876–5886, https://doi.org/10.1016/j.atmosenv.2009.08.026, 2009.
Guo, J., Miao, Y., Zhang, Y., Liu, H., Li, Z., Zhang, W., He, J., Lou, M., Yan, Y., Bian, L., and Zhai, P.: The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data, Atmos. Chem. Phys., 16, 13309–13319, https://doi.org/10.5194/acp-16-13309-2016, 2016.
Guo, J., Li, Y., Cohen, J. B., Li, J., Chen, D., Xu, H., Liu, L., Yin, J., Hu, K., and Zhai, P.: Shift in the Temporal Trend of Boundary Layer Height in China Using Long-Term (1979–2016) Radiosonde Data, Geophys. Res. Lett., 46, 6080–6089, https://doi.org/10.1029/2019gl082666, 2019.
Guo, J., Liu, B., Gong, W., Shi, L., Zhang, Y., Ma, Y., Zhang, J., Chen, T., Bai, K., Stoffelen, A., de Leeuw, G., and Xu, X.: Technical note: First comparison of wind observations from ESA's satellite mission Aeolus and ground-based radar wind profiler network of China, Atmos. Chem. Phys., 21, 2945–2958, https://doi.org/10.5194/acp-21-2945-2021, 2021.
Holzworth, G. C.: Estimates of mean maximum mixing depths in the contiguous United States, Mon. Weather Rev., 92, 235–242, https://doi.org/10.1175/1520-0493(1964)092<0235:eommmd>2.3.co;2, 1964.
Haeffelin, M., Angelini, F., Morille, Y., Martucci, G., Frey, S., Gobbi, G. P., Lolli, S., O'Dowd, C. D., Sauvage, L., Xueref-Rémy, I., Wastine, B., and Feist, D. G.: Evaluation of Mixing-Height Retrievals from Automatic Profiling Lidars and Ceilometers in View of Future Integrated Networks in Europe, Bound.-Lay. Meteorol., 143, 49–75, https://doi.org/10.1007/s10546-011-9643-z, 2012.
Jiang, Y., Xin, J., Zhao, D., Jia, D., and Dai, L. Analysis of differences between thermodynamic and material boundary layer structure: comparison of detection by ceilometer and microwave radiometer, Atmos. Res., 248, 105179, https://doi.org/10.1016/j.atmosres.2020.105179, 2020.
Krishnamurthy, R., Newsom, R. K., Berg, L. K., Xiao, H., Ma, P.-L., and Turner, D. D.: On the estimation of boundary layer heights: a machine learning approach, Atmos. Meas. Tech., 14, 4403–4424, https://doi.org/10.5194/amt-14-4403-2021, 2021.
Kursinski, E. R., Hajj, G. A., Schofield, J. T., Linfield, R. P., and Hardy, K. R.: Observing Earth's atmosphere with radio occultation measurements using the Global Positioning System, J. Geophys. Res.-Atmos., 102, 23429–23465, https://doi.org/10.1029/97jd01569, 1997.
Liu, B., Ma, Y., Gong, W., Zhang, M., and Yang, J.: Study of continuous air pollution in winter over Wuhan based on ground-based and satellite observations, Atmos. Pollut. Res., 9, 156–165, https://doi.org/10.1016/j.apr.2017.08.004, 2018a.
Liu, B., Ma, Y., Liu, J., Gong, W., Wang, W., and Zhang, M.: Graphics algorithm for deriving atmospheric boundary layer heights from CALIPSO data, Atmos. Meas. Tech., 11, 5075–5085, https://doi.org/10.5194/amt-11-5075-2018, 2018b.
Liu, B., Ma, Y., Gong, W., Zhang, M., and Shi, Y.: The relationship between black carbon and atmospheric boundary layer height, Atmos. Pollut. Res., 10, https://doi.org/10.1016/j.apr.2018.06.007, 2019.
Liu, B., Ma, Y., Shi, Y., Jin, S., Jin, Y., and Gong, W.: The characteristics and sources of the aerosols within the nocturnal residual layer over Wuhan, China, Atmos. Res., 241, 104959, https://doi.org/10.1016/j.atmosres.2020.104959, 2020a.
Liu, B., Guo, J., Gong, W., Shi, Y., and Jin, S.: Boundary layer height as estimated from Radar wind profilers in four cities in China: Relative contributions from Aerosols and surface features, Remote Sens., 12, 1657, https://doi.org/10.3390/rs12101657, 2020b.
Liu, S. and Liang. X. Z.: Observed diurnal cycle climatology of planetary boundary layer height, J. Climate, 23, 5790–5809, https://doi.org/10.1175/2010jcli3552.1, 2010.
Lou, M., Guo, J., Wang, L., Xu, H., Chen, D., Miao, Y., Lv, Y., Li, Y., Guo, X., and Ma, S.: On the relationship between aerosol and boundary layer height in summer in China under different thermodynamic conditions, Earth and Space Science, 6, 887–901, https://doi.org/10.1029/2019ea000620, 2019.
Mcgrath-Spangler, E. L. and Denning, A. S.: Estimates of North American summertime planetary boundary layer depths derived from space-borne lidar, J. Geophys. Res., 117, D15101, https://doi.org/10.1029/2012jd017615, 2012.
Medeiros, B., Hall, A., and Stevens, B.: What Controls the Mean Depth of the PBL?, J. Climate, 18, 3157–3172, https://doi.org/10.1175/jcli3417.1, 2005.
Nieuwstadt, F. T. M.: The turbulent structure of the stable, nocturnal boundary layer, J. Atmos. Sci., 41, 2202–2216, https://doi.org/10.1175/1520-0469(1984)041<2202:TTSOTS>2.0.CO;2, 1984.
Oke, T. R.: The heat island of the urban boundary layer: characteristics, causes and effects, Wind Climate in Cities, 81–107, https://doi.org/10.1007/978-94-017-3686-2_5, 1995.
Poulos, G. S., Blumen, W., Fritts, D. C., Lundquist, J. K., Sun, J., Burns, S. P., Nappo, C., Banta, R., Newsom, R., Cuxart, J., Terradellas, E., Balsley, B., and Jensen, M.: CASES-99: A Comprehensive Investigation of the Stable Nocturnal Boundary Layer, B. Am. Meteorol. Soc., 83, 555–581, 2002.
Rieutord, T., Aubert, S., and Machado, T.: Deriving boundary layer height from aerosol lidar using machine learning: KABL and ADABL algorithms, Atmos. Meas. Tech., 14, 4335–4353, https://doi.org/10.5194/amt-14-4335-2021, 2021.
Schween, J. H., Hirsikko, A., Löhnert, U., and Crewell, S.: Mixing-layer height retrieval with ceilometer and Doppler lidar: from case studies to long-term assessment, Atmos. Meas. Tech., 7, 3685–3704, https://doi.org/10.5194/amt-7-3685-2014, 2014.
Seibert, P., Beyrich, F., Gryning, S., Joffre, S., Rasmussen, A., and Tercier, P.: Review and intercomparison of operational methods for the determination of the mixing height, Atmos. Environ., 34, 1001–1027, https://doi.org/10.1016/S1352-2310(99)00349-0, 2000.
Seidel, D. J., Ao, C. O., and Li, K.: Estimating climatological planetary boundary layer heights from radiosonde observations: Comparison of methods and uncertainty analysis, J. Geophys. Res., 115, D16113, https://doi.org/10.1029/2009jd013680, 2010.
Seidel, D. J., Zhang, Y., Beljaars, A., Golaz, J., Jacobson, A. R., and Medeiros, B.: Climatology of the planetary boundary layer over the continental United States and Europe, J. Geophys. Res., 117, D17106, https://doi.org/10.1029/2012jd018143, 2012.
Shi, Y., Liu, B., Chen, S., Gong, W., Ma Y., Zhang, M., Jin, S., and Jin Y.: Characteristics of aerosol within the nocturnal residual layer and its effects on surface PM2.5 over China, Atmos. Environ., 241, 117841, https://doi.org/10.1016/j.atmosenv.2020.117841, 2020.
Solanki, R., Guo, J., Li, J., Singh, N., Guo, X., Han, Y., Lv, Y., Zhang, J., and Liu, B.: Atmospheric-Boundary-Layer-Height Variation over Mountainous and Urban Sites in Beijing as Derived from Radar Wind-Profiler Measurements, Bound.-Lay. Meteorol., 181, 125–144, https://doi.org/10.1007/s10546-021-00639-9, 2021.
Stull, R. B.: An introduction to boundary layer meteorology, Kluwer Academic Publishers, the Netherlands, 1988.
Su, T., Li, Z., Zheng, Y., Luan, Q., and Guo, J.: Abnormally Shallow Boundary Layer Associated With Severe Air Pollution During the COVID-19 Lockdown in China, Geophys. Res. Lett., 47, e2020GL090041, https://doi.org/10.1029/2020gl090041, 2020.
Vogelezang, D., Holtslag, A. A.: Evaluation and model impacts of alternative boundary-layer height formulations, Bound.-Lay. Meteorol., 81, 245–269, https://doi.org/10.1007/bf02430331, 1996.
Wang, W., He, J., Miao, Z., and Du, L.: Space–Time Linear Mixed-Effects (STLME) model for mapping hourly fine particulate loadings in the Beijing–Tianjin–Hebei region, China, J. Clean. Prod., 292, 125993, https://doi.org/10.1016/j.jclepro.2021.125993, 2021.
Wang, X. Y. and Wang, K. C.: Estimation of atmospheric mixing layer height from radiosonde data, Atmos. Meas. Tech., 7, 1701–1709, https://doi.org/10.5194/amt-7-1701-2014, 2014.
Yang, Y., Fan, S., Wang, L., Gao, Z., Zhang, Y., Zou, H., Miao, S., Li, Y., Huang, M., and Yim, S. H. L.: Diurnal evolution of the wintertime boundary layer in urban Beijing, China: Insights from Doppler Lidar and a 325-m meteorological tower, Remote Sens.-Basel, 12, 3935, https://doi.org/10.3390/rs12233935, 2020.
Yu, L., Zhang, M., Wang, L., Lu, Y., and Li, J.: Effects of aerosols and water vapour on spatial-temporal variations of the clear-sky surface solar radiation in China, Atmos. Res., 248, 105162, https://doi.org/10.1016/j.atmosres.2020.105162, 2021.
Zhang, M., Jin, S., Ma, Y., Fan, R., Wang, L., Gong, W., and Liu, B.: Haze events at different levels in winters: A comprehensive study of meteorological factors, Aerosol characteristics and direct radiative forcing in megacities of north and central China, Atmos. Environ., 245, 118056, https://doi.org/10.1016/j.atmosenv.2020.118056, 2021.
Zhang, W., Guo, J., Miao, Y., Liu, H., Zhang, Y., Li, Z., and Zhai, P.: Planetary boundary layer height from CALIOP compared to radiosonde over China, Atmos. Chem. Phys., 16, 9951–9963, https://doi.org/10.5194/acp-16-9951-2016, 2016.
Zhang, W., Guo, J., Miao, Y., Liu, H., Song, Y., Fang, Z., He, J., Lou, M., Yan, Y., Li, Y., and Zhai, P.: On the Summertime Planetary Boundary Layer with Different Thermodynamic Stability in China: A Radiosonde Perspective, J. Climate, 31, 1451–1465, https://doi.org/10.1175/jcli-d-17-0231.1, 2018.
Zhang, Y., Sun, K., Gao, Z., Pan, Z., Shook, M. A., and Li, D.: Diurnal Climatology of Planetary Boundary Layer Height Over the Contiguous United States Derived From AMDAR and Reanalysis Data, J. Geophys. Res.-Atmos., 125, e2020JD032803, https://doi.org/10.1029/2020JD032803, 2020.
Short summary
Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer (PBL), and numerous methods have been proposed for retrieving PBL height (PBLH) from RS data. However, an algorithm that is suitable under all atmospheric conditions does not exist. This study evaluates the performance of four common PBLH algorithms under different thermodynamic stability conditions based on RS data.
Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer...
