Abstract
We assessed the sensitivity of 10-m wind speed to land surface schemes (LSSs) and the processes affecting wind speed in China during the summer of 2003 using the ARWv3 mesoscale model. The derived hydrodynamic equation, which directly reflects the effects of the processes that drive changes in the full wind speed, shows that the convection term CON (the advection effect) plays the smallest role; thus, the summer 10-m wind speed is largely dominated by the pressure gradient (PRE) and the diffusion (DFN) terms, and the equation shows that both terms are highly sensitive to the choice of LSS within the studied subareas (i.e., Northwest China, East China, and the Tibetan Plateau). For example, Northwest China had the largest DFN, with a PRE four times that of CON and the highest sensitivity of PRE to the choice of LSS, as indicated by a difference index value of 63%. Moreover, we suggest that two types of mechanisms, direct and indirect effects, affect the 10-m wind speed. Through their simulated surface fluxes (mainly the sensible heat flux), the different LSSs directly provide different amounts of heat to the surface air at local scales, which influences atmospheric stratification and the characteristics of downward momentum transport. Meanwhile, through the indirect effect, the LSS-induced changes in surface fluxes can significantly modify the distributions of the temperature and pressure fields in the lower atmosphere over larger scales. These changes alter the thermal and geostrophic winds, respectively, as well as the 10-m wind speed. Due to the differences in land properties and climates, the indirect effect (e.g., PRE) can be greater than the direct effect (e.g., DFN).
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References
Badger J, Frank H, Hahmann AN, Giebel G (2014) Wind-climate estimation based on mesoscale and microscale modeling: statistical–dynamical downscaling for wind energy applications. J Appl Meteorol Clim 53:1901–1919
Barthelmie RJ, Crippa P, Wang H, Smith CM, Krishnamurthy R, Choukulkar A, Calhoun R, Valyou D, Marzocca P, Matthiesen D, Brown G, Pryor SC (2014) 3D wind and turbulence characteristics of the atmospheric boundary layer. Bull Am Meteorol Soc 95:743–756
Beljaars A C M, Brown AR, Wood N (2004) A new parameterization of turbulent orographic form drag. Q J R Meteor Soc 130:1327–1347
Bintanja R, Severijns C, Haarsma R, Hazeleger W (2014) The future of Antarctica’s surface winds simulated by a high-resolution global climate model: 2. Drivers of 21st century changes. J Geophys Res Atmos 119:7160–7178. doi:10.1002/jgrd.v119.12
Carvalho D, Rocha A, Gómez-Gesteira M, Santos C (2012) A sensitivity study of the WRF model in wind simulation for an area of high wind energy. Environ Model Softw 33:23–34
Chen F, Dudhia J (2001) Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129:569–585
Cheng X, Zeng, Q-C, Hu F (2011) Characteristics of gusty wind disturbances and turbulent fluctuations in windy atmospheric boundary layer behind cold fronts. J Geophys Res 116: D06101. doi:10.1029/2010JD015081
Crawford KC, Hudson HR (1973) The diurnal wind variation in the lowest 1500 ft in central Oklahoma: June 1966–May 1967. J Appl Meteorol 12:127–132
Dai A, Deser C (1999) Diurnal and semidiurnal variations in global surface wind and divergence fields. J Geophys Res 104:31109–31125
Draxl C, Hahmann AN, Peña A, Giebel G (2014) Evaluating winds and vertical wind shear from weather research and forecasting model forecasts using seven planetary boundary layer schemes. Wind Energy 17(1):39–55
Dudhia J (1996) A multi-layer soil temperature model for MM5. Preprint. 6th PSU/NCAR Mesoscale Model Users’ Workshop, Boulder, pp 49–50
Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational Mesoscale Eta Model. J Geophys Res 108:8851. doi:10.1029/2002JD003296
Emeis S (2013) Wind energy meteorology: atmospheric physics for wind power generation. Springer, Berlin, pp 24–76
Grell GA, Dudhia J, Stauffer DR (1995) A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note NCAR/TN-398 1 STR, p 122
Hahmann AN, Vincent CL, Peña A, Lange J, Hasager CB (2015) Wind climate estimation using WRF model output: method and model sensitivities over the sea. Int J Climatol 35:3422–3439
He YP, Monahan AH, Jones CG, Dai A, Biner S, Caya D, Winger K (2010) Probability distributions of land surface wind speeds over North America. J Geophys Res 115:D04103
He Y, Monahan AH, McFarlane NA (2013) Diurnal variations of land surface wind speed probability distributions under clear-sky and low-cloud conditions. Geophys Res Lett 40:3308–3314
Heckel PE (2015) The ethics of energy sustainability: an energy ethics workbook. Springer, Berlin, pp 61–66
Horvath K, Koracin D, Vellore R, Jiang JH, Belu R (2012) Sub-kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models. J Geophys Res 117:D11111
Hu XM, Klein PM, Xue M (2013) Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments. J Geophys Res 118:10490–10505
Ioannidou L, Yu W, Bélair S (2014) Forecasting of surface winds over eastern canada using the canadian offline land surface modeling system. J Appl Meteorol Clim 53:1760–1774
Jiang Y, Luo Y, Zhao ZC, Shi Y, Xu YL, Zhu JH (2010) Projections of wind changes for 21st century in China by three regional climate models. Chin Geogr Sci 20:226–235
Jiménez PA, Dudhia J (2012) Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF model. J Appl Meteorol 51:300–316
Jiménez PA, Dudhia J, Navarro J (2011) On the surface wind speed probability density function over complex terrain. Geophys Res Lett 38:L22803
Koster RD, Dirmeyer PA, Guo Z, Bonan G, Chan E, Cox P, Gordon CT, Kanae S, Kowalczyk E, Lawrence D, Liu P, Lu CH, Malyshev S, McAvaney B, Mitchell K, Mocko D, Oki T, Oleson K, Pitman A, Sud YC, Taylor CM, Verseghy D, Vasic R, Xue Y, Yamada T (2004) Regions of strong coupling between soil moisture and precipitation. Science 305:1138–1141
Lin CG, Yang K, Qin J, Fu R (2013) Observed coherent trends of surface and upper-air wind speed over China since 1960. J Clim 26:2891–2903
Monahan AH, He Y, Mafarlane N, Dai A (2011) The probability distribution of land surface wind speeds. J Clim 24:3892–3909
Orr A, Phillips T, Webster S, Elvidge A, Weeks M, Hosking S, Turner J (2014) Met office unified model high-resolution simulations of a strong wind event in Antarctica. Q J R Meteorol Soc 140:2287–2297
Pielke RA (2001) Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev Geophys 39:151–177
Pielke RA (2002) Mesoscale meteorological modeling. Elsevier, Netherlands
Santos-Alamillos FJ, Pozo-Vázquez D, Ruiz-Arias JA, Lara-Fanego V, Tovar-Pescador J (2013) Analysis of WRF model wind estimate sensitivity to physics parameterization choice and terrain representation in Andalusia (Southern Spain). J Appl Meteorol Clim 52:1592–1609
Schär C, Vidale PL, Lüthi D, Frei C, Häberli C, Liniger MA, Appenzeller C (2004) The role of increasing temperature variability in European summer heatwaves. Nature 427:332–336
Schwierz C, Köllner-Heck P, Mutter EZ, Bresch DN, Vidale P, Wild M, Schär C (2010) Modelling European winter wind storm losses in current and future climate. Clim Change 101:485–514
Shimada S, Ohsawa T, Chikaoka S, Kozai K (2011) Accuracy of the wind speed profile in the lower PBL as simulated by the WRF model. SOLA 7:109–112
Skamarock WC, Klemp JB, Dudhia J et al (2008) A description of the advanced research WRF version 3. NCAR/TN–475 + STR. National Center for Atmospheric Research, Boulder
Smirnova TG, Brown JM, Benjamin SG (1997) Performance of different soil model configurations in simulating ground surface temperature and surface fluxes. Mon Weather Rev 125:1870–1884
Smirnova TG, Brown JM, Benjamin SG, Kim D (2000) Parameterization of cold-season processes in the MAPS land surface scheme. J Geophys Res 105:4077–4086
Stull RB (1987) An introduction to boundary layer meteorology. Kluwer Academic Publishers, Netherlands, p 177
Trier SB, Chen F, Manning KW, Lemone MA, Davis CA (2008) Sensitivity of the PBL and precipitation in 12-day simulations of warm-season convection using different land surface models and soil wetness conditions. Mon Weather Rev 136:2321–2343
van den Broeke MR, van Lipzig NP (2003) Factors controlling the near-surface wind field in Antarctica. Mon Weather Rev 131:733–743
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 3:756–761
Wang CH, Shi R (2007) Simulation of the land surface processes in the western Tibetan Plateau in summer. J Glaciol Geocryol 29:73–80 (Chinese)
Wen XH, Lu SH, Jin JM (2012) Integrating remote sensing data with WRF for improved simulations of oasis effects on local weather processes over an arid region in Northwestern China. J Hydrometeorol 13:573–587
Xiu A, Pleim JE (2001) Development of a land surface model. Part I: Application in a mesoscale meteorological model. J Appl Meteorol 40:192–209
Yang K, Guo X, He J, Qin J, Koike T (2011) On the climatology and trend of the atmospheric heat source over the Tibetan Plateau: an experiments-supported revisit. J Clim 24:1525–1541
Yang K, Wu H, Qin J, Lin CG, Tang WJ, Chen YY (2014) Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: a review. Glob Planet Change 12:79–81
Zeng X-M, Wu ZH, Song S, Xiong SY, Zheng YQ, Zhou ZG, Liu H (2012) Effects of land surface schemes on the simulation of a heavy rainfall event by WRF. Chinese J Geophys 55:16–28 (Chinese)
Zeng X-M, Wang B, Zhang Y, Song S, Huang X, Zheng Y, Chen C, Wang G (2014) Sensitivity of high-temperature weather to initial soil moisture: a case study using the WRF model. Atmos Chem Phys 14:9623–9639
Zeng X-M, Wang N, Wang Y, Zheng Y, Zhou Z, Wang G, Chen C, Liu H (2015) WRF-simulated sensitivity to land surface schemes in short and medium ranges for a high-temperature event in East China: a comparative study. J Adv Model Earth Syst 7:1305–1325
Zeng X-M, Wang B, Zhang Y, Zheng Y, Wang N, Wang M, Yi X, Chen C, Zhou Z, Liu H (2016) Effects of land surface schemes on WRF-simulated geopotential heights over China in summer 2003. J Hydrometeorol 17(3):829–851. doi:10.1175/JHM-D-14-0239.1
Zhang DL, Zheng WZ (2004) Diurnal cycles of surface winds and temperatures as simulated by five boundary layer parameterizations. J Appl Meteorol 43(1):157–169
Zhang HL, Pu ZX, Zhang XB (2013) Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain. Weather Forecast 28:893–914
Zheng QL, Song QL (1997) Numerical experiments for the influence of the surface drag effect of the Qinghai Xizang plateau on the general circulation in spring. J Appl Meteorol Sci 8:335–341 (Chinese)
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The authors would like to thank two anonymous reviewers for their helpful comments on the manuscript. This work was financially funded by National Natural Science Foundation of China (Grant Nos. 41675007 and 41275012).
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Zeng, XM., Wang, M., Wang, N. et al. Assessing simulated summer 10-m wind speed over China: influencing processes and sensitivities to land surface schemes. Clim Dyn 50, 4189–4209 (2018). https://doi.org/10.1007/s00382-017-3868-6
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DOI: https://doi.org/10.1007/s00382-017-3868-6