Skip to main content

Advertisement

SpringerLink
Log in

Assessing the Surface-Layer Stability over China Using Long-Term Wind-Tower Network Observations

  • Research Article
  • Published:
Boundary-Layer Meteorology Aims and scope Submit manuscript

Abstract

Surface-layer stability is important in many processes, such as in the surface energy budget, atmospheric pollution, and boundary-layer parametrizations. Most previous studies on stability, however, conducted either theoretical or observational investigations at specific sites, thus leaving a gap with regard to the large-scale pattern. Here, wind-speed and temperature observations at multiple heights from the wind-tower network of China are used to estimate low-level stability during the 2009–2016 period. A series of data-quality-control procedures are conducted and data from 170 wind towers with more than 2 years of valid observations are selected. The degree of stability is classified by the Obukhov length, which is derived from the wind speed and temperature at 10 m and 70 m above ground level, combined with information regarding the roughness length. Overall, the occurrence frequency of surface-layer instability exhibits significant temporal and spatial variability, being particularly larger in spring and summer than in autumn and winter. The maximum frequency of summertime instability occurs in the time period 1000–1200 local solar time, approximately 2 h earlier than in autumn. Geographically, the peak instability frequency occurs much earlier in the day in north-west China than in other regions, likely owing to the arid and semi-arid land cover. Also noteworthy is the steady increase in instability frequency observed during the period analyzed here, likely resulting from the reduction in the vertical gradient of wind speed. Our findings call for explicit consideration of stability variability in the wind-energy industry and in fundamental boundary-layer investigations in China.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Bartholy J, Radics K (2005) Wind profile analyses and atmospheric stability over a complex terrain in southwestern part of Hungary. Phys Chem Earth Parts A/B/C 30(1–3):195–200

    Google Scholar 

  • Basu S (2018) A simple recipe for estimating atmospheric stability solely based on surface-layer wind speed profile. Wind Energy 21(10):937–941

    Google Scholar 

  • Bauer BO, Sherman DJ, Wolcott JF (1992) Sources of uncertainty in shear stress and roughness length estimates derived from velocity profiles. Prof Geogr 44(4):453–464

    Google Scholar 

  • Brock BW, Willis IC, Sharp MJ (2006) Measurement and parameterization of aerodynamic roughness length variations at Haut Glacier d’Arolla, Switzerland. J Glaciol 52(177):281–297

    Google Scholar 

  • Businger JA, Wyngaard JC, Izumi Y, Bradley EF (1971) Flux-profile relationships in the atmospheric surface layer. J Atmos Sci 28(2):181–189

    Google Scholar 

  • Chambers SD, Wang F, Williams AG, Deng X, Zhang H, Lonati G, Crawford J, Griffiths A, Ianniello A, Allegrini I (2015) Quantifying the influences of atmospheric stability on air pollution in Lanzhou, China, using a radon-based stability monitor. Atmos Environ 107:233–243

    Google Scholar 

  • Coelingh J, Van Wijk AJM, Holtslag AAM (1996) Analysis of wind speed observations over the North Sea. J Wind Eng Ind Aerod 61(1):51–69

    Google Scholar 

  • Drach P, Krüger EL, Emmanuel R (2018) Effects of atmospheric stability and urban morphology on daytime intra-urban temperature variability for Glasgow, UK. Sci Total Environ 627:782–791

    Google Scholar 

  • Golder D (1972) Relations among stability parameters in the surface layer. Boundary-Layer Meteorol 3(1):47–58

    Google Scholar 

  • Gong X, Zhu R, Fan G, Li Z, Ma W, Zhou R (2014) Observational study of the vertical wind profile in the Inner Mongolia grassland near surface. Acta Meteorol Sin 72(4):711–722 (in Chinese)

    Google Scholar 

  • Gong X, Zhu R, Chen L (2019) Characteristics of near surface winds over different underlying surfaces in China: implications for wind power development. J Meteorol Res 33(2):349–362

    Google Scholar 

  • Guo H, Xu M, Hu Q (2011) Changes in near-surfac wind speed in China: 1969–2005. Int J Climatol 31(3):349–358

    Google Scholar 

  • Guo J, Miao Y, Zhang Y, Liu H, Li Z, Zhang W, He J, Lou M, Yan Y, Bian L (2016) The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data. Atmos Chem Phys 16(20):13309–13319

    Google Scholar 

  • Guo J, Li Y, Cohen JB, Li J, Chen D, Xu H, Liu L, Yin J, Hu K, Zhai P (2019) Shift in the temporal trend of boundary layer height in China using long-term (1979–2016) radiosonde data. Geophys Res Lett 46(11):6080–6089

    Google Scholar 

  • He Y, Wang K (2020) Contrast patterns and trends of lapse rates calculated from near-surface air and land surface temperatures in mainland China from 1961 to 2014. Sci Bull 65:1217–1224

    Google Scholar 

  • Högström U (1988) Non-dimensional wind and temperature profiles in the atmospheric surface layer: a re-evaluation, Topics in Micrometeorology. A Festschrift for Arch Dyer. Springer, Berlin

    Google Scholar 

  • Holtslag AAM, Boville BA (1993) Local versus nonlocal boundary-layer diffusion in a global climate model. J Clim 6(10):1825–1842

    Google Scholar 

  • Hu XM, Nielsengammon JW, Zhang F (2010) Evaluation of three planetary boundary layer schemes in the WRF model. J Appl Meteorol Climatol 49(9):1831–1844

    Google Scholar 

  • Huang T, Yim SHL, Yang Y, Lee OSM, Lam DHY, Cheng JCH, Guo J (2020) Observation of turbulent mixing characteristics in the typical daytime cloud-topped boundary layer over Hong Kong in 2019. Remote Sens 12(9):1533

    Google Scholar 

  • Jiang Y, Luo Y, Zhao Z, Tao S (2009) Changes in wind speed over China during 1956–2004. Theor Appl Climatol 99(3):421–430

    Google Scholar 

  • Joffre SM, Kangas M, Heikinheimo M, Kitaigorodskii SA (2001) Variability of the stable and unstable atmospheric boundary-layer height and its scales over a boreal forest. Boundary-Layer Meteorol 99(3):429–450

    Google Scholar 

  • Kendall MG (1975) Rank correlation methods. Griffin, London

    Google Scholar 

  • Li QS, Zhi L, Hu F (2010) Boundary layer wind structure from observations on a 325 m tower. J Wind Eng Ind Aerodyn 98(12):818–832

    Google Scholar 

  • Liu Y, Mamtimin A, Huo W, Yang X, Liu X, Yang F, He Q (2016) Nondimensional wind and temperature profiles in the atmospheric surface layer over the hinterland of the Taklimakan Desert in China. Adv Meteor. https://doi.org/10.1155/2016/9325953

    Article  Google Scholar 

  • Liu J, Gao CY, Ren J, Gao Z, Liang H, Wang L (2018) Wind resource potential assessment using a long term tower measurement approach: a case study of Beijing in China. J Clean Prod 174:917–926

    Google Scholar 

  • Liu F, Sun F, Liu W, Wang T, Wang H, Wang X, Lim WH (2019) On wind speed pattern and energy potential in China. Appl Energy 236:867–876

    Google Scholar 

  • Lolli S, Khor WY, Matjafri MZ, Lim HS (2019) Monsoon season quantitative assessment of biomass burning clear-sky aerosol radiative effect at surface by ground-based lidar observations in Pulau Pinang, Malaysia in 2014. Remote Sens 11(22):2660

    Google Scholar 

  • Machefaux E, Larsen GC, Koblitz T, Troldborg N, Kelly MC, Chougule A, Hansen KS (2016) An experimental and numerical study of the atmospheric stability impact on wind turbine wakes. Wind Energy 19(10):1785–1805

    Google Scholar 

  • Mahrt L, Ek M (1984) The influence of atmospheric stability on potential evaporation. J Appl Meteorol 23(2):222–234

    Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245–259

    Google Scholar 

  • Martano P (2000) Estimation of surface roughness length and displacement height from single-level sonic anemometer data. J Appl Meteorol 39(5):708–715

    Google Scholar 

  • Martinez-Agirre A, Álvarez-Mozos J, Giménez R (2016) Evaluation of surface roughness parameters in agricultural soils with different tillage conditions using a laser profile meter. Soil Till Res 161:19–30

    Google Scholar 

  • Melgarejo JW, Deardorff JW (1975) Revision to ‘stability functions for the boundary-layer resistance laws based upon observed boundary-layer heights.’ J Atmos Sci 31(5):1324–1333

    Google Scholar 

  • Miao Y, Liu S (2019) Linkages between aerosol pollution and planetary boundary layer structure in China. Sci Total Environ 650:288–296

    Google Scholar 

  • Milroy C, Martucci G, Lolli S, Loaec S, Sauvage L, Xueref-Remy I, Lavrič JV, Ciais P, Feist DG, Biavati G, O’Dowd CD (2012) An assessment of pseudo-operational ground-based light detection and ranging sensors to determine the boundary-layer structure in the coastal atmosphere. Adv Meterorol 2012:929080

    Google Scholar 

  • Mohan M, Siddiqui TA (1998) Analysis of various schemes for the estimation of atmospheric stability classification. Atmos Environ 32(21):3775–3781

    Google Scholar 

  • Monin A, Obukhov A (1954) Basic laws of turbulent mixing in the atmosphere near the ground. Tr Akad Nauk SSSR Geofiz Inst 24(151):163–187

    Google Scholar 

  • Papaioannou G, Jacovides C, Kerkides P (1989) Atmospheric stability effects on eddy transfer coefficients and on Penman’s evaporation estimates. Water Resour Manag 3(4):315–322

    Google Scholar 

  • Pasquill F (1961) The estimation of the dispersion of windborne material. Aust Meteorol Mag 90:33–49

    Google Scholar 

  • Peña A, Hahmann AN (2012) Atmospheric stability and turbulence fluxes at Horns Rev—an intercomparison of sonic bulk and WRF model data. Wind Energy 15(5):717–731

    Google Scholar 

  • Peña A, Gryning SE, Hasager CB (2008) Measurements and modelling of the wind speed profile in the marine atmospheric boundary layer. Boundary-Layer Meteorol 129(3):479–495

    Google Scholar 

  • Peng X, Hu Y, Xiang W, Xu C, Xue F (2016) Atmospheric stability affects wind turbine power in large offshore wind farms. In: International conference on energy and environmental protection 2016, Atlantis Press

  • Perrino C, Catrambone M, Pietrodangelo A (2008) Influence of atmospheric stability on the mass concentration and chemical composition of atmospheric particles: a case study in Rome, Italy. Environ Int 34(5):621–628

    Google Scholar 

  • Pimenta FM, Silva AR, Assireu AT, Saavedra OR (2019) Brazil offshore wind resources and atmospheric surface layer stability. Energies 12(21):4195

    Google Scholar 

  • Pirazzoli PA, Tomasin A (2003) Recent near-surface wind changes in the central Mediterranean and Adriatic areas. Int J Climatol 23(8):963–973

    Google Scholar 

  • Pryor SC, Barthelmie RJ, Young DT, Takle ES, Arritt RW, Flory D, Gutowski WJ, Nunes A, Roads J (2009) Wind speed trends over the contiguous United States. J Geophys Res Atmos 114:D14

    Google Scholar 

  • Qin Y, Ren G, Zhai T, Zhang P, Wen K (2018) A new methodology for estimating the surface temperature lapse rate based on grid data and its application in China. Remote Sens 10(10):1617–1634

    Google Scholar 

  • Reid JS, Lagrosas ND, Jonsson HH, Reid EA, Atwood SA, Boyd TJ, Boyd TJ, Ghate VP, Xian P, Posselt DJ, Simpas JB, Uy SN, Zaiger K, Blake DR, Bucholtz A, Campbell JR, Chew BN, Cliff SS, Holben BN, Holz RE, Hyer EJ, Kreidenweis SM, Kuciauskas AP, Lolli S, Oo M, Perry KD, Salinas SV, Sessions WR, Smirnov A, Walker AL, Wang Q, Yu L, Zhang J, Zhao Y (2016) Aerosol meteorology of maritime continent for the 2012 7seas southwest monsoon intensive study–part 2: Philippine receptor observations of fine-scale aerosol behavior. Atmos Chem Phys 16(22):14057–14078

    Google Scholar 

  • Richardson H, Basu S, Holtslag AAM (2013) Improving stable boundary-layer height estimation using a stability-dependent critical bulk richardson number. Boundary-Layer Meteorol 148(1):93–109

    Google Scholar 

  • Rotach MW (1994) Determination of the zero plane displacement in an urban environment. Boundary-Layer Meteorol 67(1–2):187–193

    Google Scholar 

  • Sathe A, Gryning SE, Peña A (2011) Comparison of the atmospheric stability and wind profiles at two wind farm sites over a long marine fetch in the North Sea. Wind Energy 14(6):767–780

    Google Scholar 

  • Seibert P, Beyrich F, Gryning SE, Joffre S, Rasmussen A, Tercier P (2000) Review and intercomparison of operational methods for the determination of the mixing height. Atmos Environ 34(7):1001–1027

    Google Scholar 

  • Shen YJ, Shen Y, Goetz J, Brenning A (2016) Spatial-temporal variations of near-surface temperature lapse rates over the Tianshan Mountains, central Asia. J Geophys Res Atmos 121(23):14006–14017

    Google Scholar 

  • Silva J, Ribeiro C, Guedes R (2007) Roughness length classification of Corine Land Cover classes. In: Proceedings of the European wind energy conference, Milan, Italy 2007, vol 710, p. 110

  • Stull RB (1988) An introduction to boundary layer meteorology. Springer, Berlin

    Google Scholar 

  • Sumner J, Masson C (2006) Influence of atmospheric stability on wind turbine power performance curves. J Sol Energy Eng 128(4):531–538

    Google Scholar 

  • Takagi K, Miyata A, Harazono Y, Ota N, Komine M, Yoshimoto M (2003) An alternative approach to determining zero-plane displacement, and its application to a lotus paddy field. Agric For Meteorol 115(3–4):173–181

    Google Scholar 

  • Tong CHM, Yim SHL, Rothenberg D, Wang C, Lin CY, Chen YD, Lau NC (2018) Assessing the impacts of seasonal and vertical atmospheric conditions on air quality over the Pearl River Delta region. Atmos Environ 180:69–78

    Google Scholar 

  • Troccoli A, Muller K, Coppin P, Davy R, Russell C, Hirsch AL (2012) Long-term wind speed trends over Australia. J Climate 25(1):170–183

    Google Scholar 

  • Turner DB (1964) A diffusion model for an urban area. J Appl Meteorol 3(1):83–91

    Google Scholar 

  • Vautard R, Cattiaux J, Yiou P, Thépaut JN, Ciais P (2010) Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nat Geosci 3(11):756–761

    Google Scholar 

  • Wharton S, Lundquist JK (2012a) Assessing atmospheric stability and its impacts on rotor-disk wind characteristics at an onshore farm. Wind Energy 15(4):525–546

    Google Scholar 

  • Wharton S, Lundquist JK (2012b) Atmospheric stability affects wind turbine power collection. Environ Res Lett 7(1):17–35

    Google Scholar 

  • Xu M, Chang CP, Fu C, Qi Y, Robock A, Robinson D, Zhang HM (2006) Steady decline of east Asian monsoon winds, 1969–2000: evidence from direct ground measurements of wind speed. J Geophys Res: Atmos. 111:D24111

    Google Scholar 

  • Xue W, Guo J, Zhang Y, Zhou S, Wang Y, Miao Y, Liu L, Xu H, Li J, Chen D, Liu H (2019) Declining diurnal temperature range in the North China Plain related to environmental changes. Clim Dyn 52(9–10):6109–6119

    Google Scholar 

  • Yang J, Li A, Xie P, Liu W, Wu F, Wang Y, Zeng Y (2012) The application of MM5 wind data in monitoring of regional pollution based on passive DOAS under different atmospheric stability conditions in China. In: 2nd International conference on remote sensing, environment and transportation engineering, 2012, pp 1–7

  • Yang B, Qian Y, Berg LK, Ma PL, Wharton S, Bulaevskaya V, Yan H, Hou Z, Shaw WJ (2017) Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model. Boundary-Layer Meteorol 162(1):117–142

    Google Scholar 

  • Yang Y, Yim SH, Haywood J, Osborne M, Chan JC, Zeng Z, Cheng JC (2019) Characteristics of heavy particulate matter pollution events over Hong Kong and their relationships with vertical wind profiles using high-time-resolution doppler Lidar measurements. J Geophys Res Atmos 124(16):9609–9623

    Google Scholar 

  • Yim SHL, Fung JC, Lau AK, Kot SC (2007) Developing a high-resolution wind map for a complex terrain with a coupled MM5/CALMET system. J Geophy Res Atmos 112:D05106

    Google Scholar 

  • Zhang Z, Wang F, Costabile F, Allegrini I, Liu F, Hong W (2012) Interpretation of ground-level ozone episodes with atmospheric stability index measurement. Environ Sci Pollut Res 19(8):3421–3429

    Google Scholar 

  • Zhang W, Guo J, Miao Y, Liu H, Song Y, Fang Z, He J, Lou M, Yan Y, Li Y, Zhai P (2018) On the summertime planetary boundary layer with different thermodynamic stability in China: a radiosonde perspective. J Clim 31(4):1451–1465

    Google Scholar 

  • Zhang Y, Guo J, Yang Y, Wang Y, Yim SHL (2020a) Vertical wind shear modulates particulate matter pollutions: a perspective from Radar wind profiler observations in Beijing. China Remote Sens 12(3):546

    Google Scholar 

  • Zhang Y, Gao L, Cao L, Yan Z, Wu Y (2020b) Decreasing atmospheric visibility associated with weakening winds from 1980 to 2017 over China. Atmos Environ 224:117314

    Google Scholar 

  • Zhao B, Mao K, Cai Y, Shi J, Li Z, Qin Z (2020) A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003–2017. Earth Syst Sci Data 12:2555–2577

    Google Scholar 

Download references

Acknowledgements

This work was supported by the Ministry of Science and Technology of China (Grant 2017YFC1501401 and 2017YFC0212803), Chinese Academy of Sciences (Grant GXDA20040502), National Natural Science Foundation of China (42001294), and Chinese Academy of Meteorological Sciences (Grants 2018Y012, 2018B08 and 2021KJ029). The authors would like to acknowledge China Meteorological Administration for making the wind-tower data available for this study.

Author information

Authors and Affiliations

  1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China

    Jian Li, Jianping Guo, Hui Xu & Yanmin Lv

  2. Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China

    Jing Li

Authors
  1. Jian Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianping Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hui Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yanmin Lv
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jianping Guo or Hui Xu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, J., Guo, J., Xu, H. et al. Assessing the Surface-Layer Stability over China Using Long-Term Wind-Tower Network Observations. Boundary-Layer Meteorol 180, 155–171 (2021). https://doi.org/10.1007/s10546-021-00620-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10546-021-00620-6

Keywords

Search

Navigation