[1] |
Ancell, B. C., C. F. Mass, and G. J. Hakim, 2011: Evaluation of surface analyses and forecasts with a multiscale ensemble Kalman filter in regions of complex terrain. Mon. Wea. Rev., 139, 2008–2024. doi: 10.1175/2010MWR3612.1 |
[2] |
Byun, D., F. Ngan, X. S. Li, et al., 2008: Evaluation of Retrospective MM5 and CMAQ Simulation of TexAQS-II Period with CAMS Measurements. Texas Commission on Environmental Quality Final Rep., Grant No. 582-5-64594-FY07-02, 30 pp. |
[3] |
Cao, F. Q., L. Dan, and Z. G. Ma, 2015: Simulative study of the impact of the cropland change on the regional climate over China. Acta Meteor. Sinica, 73, 128–141. (in Chinese) doi: 10.11676/qxxb2015.001 |
[4] |
Chen, B., A. F. Stein, N. Castell, et al., 2012: Modeling and surface observations of arsenic dispersion from a large Cu-smel-ter in southwestern Europe. Atmos. Environ., 49, 114–122. doi: 10.1016/j.atmosenv.2011.12.014 |
[5] |
Chen, H. S., and Y. Zhang, 2013: Sensitivity experiments of impacts of large-scale urbanization in East China on East Asian winter monsoon. Chinese Sci. Bull., 58, 809–815. doi: 10.1007/s11434-012-5579-z |
[6] |
Chen, H. S., X. Li, and W. J. Hua, 2015: Numerical simulation of the impact of land use/land cover change over China on regional climates during the last 20 years. Chinese J. Atmos. Sci., 39, 357–369. (in Chinese) doi: 10.3878/j.issn.1006-9895.1404.14114 |
[7] |
Cheng, F. Y., Y. C. Hsu, P. L. Lin, et al., 2013: Investigation of the effects of different land use and land cover patterns on mesoscale meteorological simulations in the Taiwan area. J. Appl. Meteor. Climatol., 52, 570–587. doi: 10.1175/JAMC-D-12-0109.1 |
[8] |
Cheng, W. Y. Y., and W. J. Steenburgh, 2005: Evaluation of surface sensible weather forecasts by the WRF and the Eta models over the western United States. Wea. Forecasting, 20, 812–821. doi: 10.1175/WAF885.1 |
[9] |
Comarazamy, D. E., J. E. González, J. C. Luvall, et al., 2013: Climate impacts of land-cover and land-use changes in tropical islands under conditions of global climate change. J. Climate, 26, 1535–1550. doi: 10.1175/JCLI-D-12-00087.1 |
[10] |
Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077–3107. doi: 10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2 |
[11] |
Ek, M. B., K. E. Mitchell, Y. Lin, et al., 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 |
[12] |
Gómez-Navarro, J. J., C. C. Raible, and S. Dierer, 2015: Sensitivity of the WRF model to PBL parametrisations and nesting techniques: Evaluation of surface wind over complex terrain. Geosci. Model Dev., 8, 3349–3363. doi: 10.5194/gmd-8-3349-2015 |
[13] |
Hanna, S. R., and R. X. Yang, 2001: Evaluations of mesoscale models’ simulations of near-surface winds, temperature gradients, and mixing depths. J. Appl. Meteor., 40, 1095–1104. doi: 10.1175/1520-0450(2001)040<1095:EOMMSO>2.0.CO;2 |
[14] |
He, J. J., Y. Yu, N. Liu, et al, 2014: Impact of land surface information on WRF’s performance in complex terrain area. Chinese J. Atmos. Sci., 38, 484–498. (in Chinese) doi: 10.3878/j.issn.1006-9895.2013.13186 |
[15] |
Hirsch, A L., A. J. Pitman, J. Kala, et al., 2015: Modulation of land-use change impacts on temperature extremes via land–atmosphere coupling over Australia. Earth Interactions, 19, 1–24. doi: 10.1175/EI-D-15-0011.1 |
[16] |
Hu, X.-M., P. M. Klein, and M. Xue, 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. doi: 10.1002/jgrd.50823 |
[17] |
Jiménez, P. A., and J. Dudhia, 2012: Improving the representation of resolved and unresolved topographic effects on surface wind in the WRF model. J. Appl. Meteor. Climatol., 51, 300–316. doi: 10.1175/JAMC-D-11-084.1 |
[18] |
Jiménez, P. A., and J. Dudhia, 2013: On the ability of the WRF model to reproduce the surface wind direction over complex terrain. J. Appl. Meteor. Climatol., 52, 1610–1617. doi: 10.1175/JAMC-D-12-0266.1 |
[19] |
Jin, L. L., Z. J. Li, Q. He, et al., 2016: Observation and simulation of near-surface wind and its variation with topography in Urumqi, West China. J. Meteor. Res., 30, 961–982. doi: 10.1007/s13351-016-6012-3 |
[20] |
Kabat, P., M. Claussen, S. Whitlock, et al., 2004: Vegetation, Water, Humans and the Climate: A New Perspective on an Interactive System. Springer, Berlin Heidelberg, 566 pp, doi: 10.1007/978-3-642-18948-7. |
[21] |
Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181. doi: 10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2 |
[22] |
Kim, Y., and G. L. Wang, 2007: Impact of vegetation feedback on the response of precipitation to antecedent soil moisture anomalies over North America. J. Hydrometeor., 8, 534–550. doi: 10.1175/JHM612.1 |
[23] |
Lee, S. H., S. W. Kim, W. M. Angevine, et al., 2011: Evaluation of urban surface parameterizations in the WRF model using measurements during the Texas Air Quality Study 2006 field campaign. Atmos. Chem. Phys., 11, 2127–2143. doi: 10.5194/acp-11-2127-2011 |
[24] |
Lee, T. J., R. A. Pielke, R. C. Kessler, et al., 1989: Influence of cold pools downstream of mountain barriers on downslope winds and flushing. Mon. Wea. Rev., 117, 2041–2058. doi: 10.1175/1520-0493(1989)117<2041:IOCPDO>2.0.CO;2 |
[25] |
Lim, Y. K., M. Cai, E. Kalnay, et al., 2008: Impact of vegetation types on surface temperature change. J. Appl. Meteor. Climatol., 47, 411–424. doi: 10.1175/2007JAMC1494.1 |
[26] |
Liu, J. Y., W. H. Kuang, Z. X. Zhang, et al., 2014: Spatiotemporal characteristics, patterns and causes of land-use changes in China since the late 1980s. Acta Geogra. Sinica, 69, 3–14. (in Chinese) doi: 10.11821/dlxb201401001 |
[27] |
Lorente-Plazas, R., P. A. Jiménez, J. Dudhia, et al., 2016: Evaluating and improving the impact of the atmospheric stability and orography on surface winds in the WRF model. Mon. Wea. Rev., 144, 2685–2693. doi: 10.1175/MWR-D-15-0449.1 |
[28] |
Mass, C. F., D. Ovens, K. Westrick, et al., 2002: Does increasing horizontal resolution produce more skillful forecasts? Bull. Amer. Meteor. Soc., 83, 407–430. doi: 10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2 |
[29] |
Meng, X. H., J. P. Evans, and M. F. McCabe, 2014: The impact of observed vegetation changes on land–atmosphere feedbacks during drought. J. Hydrometeor., 15, 759–776. doi: 10.1175/JHM-D-13-0130.1 |
[30] |
Mesinger F., G. DiMego, E. Kalnay, et al., 2006: North American regional reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360. doi: 10.1175/BAMS-87-3-343 |
[31] |
Mlawer, E. J., S. J. Taubman, P. D. Brown, et al., 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16663–16682. doi: 10.1029/97JD00237 |
[32] |
Ngan, F., D. Byun, H. Kim, et al., 2012: Performance assessment of retrospective meteorological inputs for use in air quality modeling during TexAQS 2006. Atmos. Environ., 54, 86–96. doi: 10.1016/j.atmosenv.2012.01.035 |
[33] |
Ngan, F., H. Kim, P. Lee, et al., 2013: A study of nocturnal surface wind speed overprediction by the WRF-ARW model in southeastern Texas. J. Appl. Meteor. Climatol., 52, 2638–2653. doi: 10.1175/JAMC-D-13-060.1 |
[34] |
Oke, T. R., 1987: Boundary Layer Climates. Cambridge Univer-sity Press, Cambridge, 435 pp. |
[35] |
Pan, X. D., X. Li, Y. H. Ran, et al., 2012: Impact of underlying surface information on WRF modeling in Heihe River basin. Plateau Meteor., 31, 657–667. (in Chinese) |
[36] |
Pei, L. S., N. Moore, S. Y. Zhong, et al., 2014: WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the Southern Great Plains of the United States. J. Climate, 27, 7703–7724. doi: 10.1175/JCLI-D-14-00015.1 |
[37] |
Pleim, J. E., 2007a: A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing. J. Appl. Meteor. Climatol., 46, 1383–1395. doi: 10.1175/JAM2539.1 |
[38] |
Pleim, J. E., 2007b: A combined local and nonlocal closure model for the atmospheric boundary layer. Part II: Application and evaluation in a mesoscale meteorological model. J. Appl. Meteor. Climatol., 46, 1396–1409. doi: 10.1175/JAM2534.1 |
[39] |
Price, J. C., 1977: Thermal inertia mapping: A new view of the earth. J. Geophys. Res., 82, 2582–2590. doi: 10.1029/JC082i018p02582 |
[40] |
Price, J. C., 1980: The potential of remotely sensed thermal infrared data to infer surface soil moisture and evaporation. Water Resour. Res., 16, 787–795. doi: 10.1029/WR016i004p00787 |
[41] |
Pu, Z. X., H. L. Zhang, and J. A. Anderson, 2013: Ensemble Kalman filter assimilation of near-surface observations over complex terrain: Comparison with 3DVAR for short-range forecasts. Tellus A, 65, 19620. doi: 10.3402/tellusa.v65i0.19620 |
[42] |
Rife, D. R., C. A. Davis, Y. B. Liu, et al., 2004: Predictability of low-level winds by mesoscale meteorological models. Mon. Wea. Rev., 132, 2533–2569. doi: 10.1175/MWR2801.1 |
[43] |
Rowell, D. P., and J. R. Milford, 1993: On the generation of Afri-can squall lines. J. Climate, 6, 1181–1193. doi: 10.1175/1520-0442(1993)006<1181:OTGOAS>2.0.CO;2 |
[44] |
Ruiz, J. J., C. Saulo, and J. Nogués-Paegle, 2010: WRF model sensitivity to choice of parameterization over South America: Validation against surface variables. Mon. Wea. Rev., 138, 3342–3355. doi: 10.1175/2010MWR3358.1 |
[45] |
Santos-Alamillos, F. J., D. Pozo-Vázquez, J. A. Ruiz-Arias, et al., 2013: Analysis of WRF model wind estimate sensitivity to physics parameterization choice and terrain representation in Andalusia (southern Spain). J. Appl. Meteor. Climatol., 52, 1592–1609. doi: 10.1175/JAMC-D-12-0204.1 |
[46] |
Scheitlin, K. N., and P. G. Dixon, 2010: Diurnal temperature range variability due to land cover and airmass types in the Southeast. J. Appl. Meteor. Climatol., 49, 879–888. doi: 10.1175/2009JAMC2322.1 |
[47] |
Sheng, L. F., K. H. Schlunzen, and Z. M. Wu, 2000: Three-dmensional numerical simulation of the mesoscale wind structure over Shandong Peninsula. Acta Meteor. Sinica, 14, 98–107. |
[48] |
Siuta, D., G. West, and R. Stull, 2017: WRF hub-height wind forecast sensitivity to PBL scheme, grid length, and initial condition choice in complex terrain. Wea. Forecasting, 32, 493–509. doi: 10.1175/WAF-D-16-0120.1 |
[49] |
Smith, R. B., and Y.-L. Lin, 1982: The addition of heat to a stratified airstream with application to the dynamics of orographic rain. Quart. J. Roy. Meteor. Soc., 108, 353–378. doi: 10.1002/qj.49710845605 |
[50] |
Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Springer, Netherlands, 666 pp, doi: 10.1007/978-94-009-3027-8. |
[51] |
Tao, S. Y., 1980: Heavy Rainfalls in China. Science Press, Beijing, 225 pp. (in Chinese) |
[52] |
Wang, C. H., and S. L. Jin, 2013: Error features and their possible causes in simulated low-level winds by WRF at a wind farm. Wind Energy, 17, 1315–1325. doi: 10.1002/we.1635 |
[53] |
Whiteman, C. D., 2000: Mountain Meteorology: Fundamentals and Applications. Oxford University Press, Oxford, 355 pp. |
[54] |
Wu, Z. M., and K. H. Schlunzen, 1992: Numerical study on the local wind structures forced by the complex terrain of Qingdao area. Acta Meteor. Sinica, 6, 355–366. |
[55] |
Xin, J. Y., C. S. Gong, S. G. Wang, et al., 2016: Aerosol direct radiative forcing in desert and semi-desert regions of northwestern China. Atmos. Res., 171, 56–65. doi: 10.1016/j.atmosres.2015.12.004 |
[56] |
Yucel, I., 2006: Effects of implementing MODIS land cover and albedo in MM5 at two contrasting U. S. regions. J. Hydrometeor., 7, 1043–1060. doi: 10.1175/JHM536.1 |
[57] |
Zhang, D.-L., and W. Z. Zheng, 2004: Diurnal cycles of surface winds and temperatures as simulated by five boundary layer parameterizations. J. Appl. Meteor., 43, 157–169. doi: 10.1175/1520-0450(2004)043<0157:DCOSWA>2.0.CO;2 |
[58] |
Zhang, F. M., Y. Yang, and C. H. Wang, 2015: The effects of assimilating conventional and ATOVS data on forecasted near-surface wind with WRF-3DVAR. Mon. Wea. Rev., 143, 153–164. doi: 10.1175/MWR-D-14-00038.1 |
[59] |
Zhang, H. L., Z. X. Pu, and X. B. Zhang, 2013: Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain. Wea. Forecasting, 28, 893–914. doi: 10.1175/WAF-D-12-00109.1 |
[60] |
Zhang, Y., X. Y. Wen, and C. J. Jang, 2010: Simulating chemistry–aerosol–cloud–radiation–climate feedbacks over the con-tinental U.S. using the online-coupled Weather Research Forecasting Model with chemistry (WRF/Chem). Atmos. Environ., 44, 3568–3582. doi: 10.1016/j.atmosenv.2010.05.056 |
[61] |
Zheng, D., R. van der Velde, Z. Su, et al., 2014: Assessment of roughness length schemes implemented within the Noah land surface model for high-altitude regions. J. Hydrometeor., 15, 921–937. doi: 10.1175/JHM-D-13-0102.1 |
[62] |
Zheng, D., R. van der Velde, Z. Su, et al., 2017: Assessment of Noah land surface model with various runoff parameterizations over a Tibetan river. J. Geophy. Res. Atmos., 122, 1488–1504. doi: 10.1002/2016JD025572 |
[63] |
Zheng, D., R. van der Velde, Z. Su, et al., 2017: Evaluation of Noah frozen soil parameterization for application to a Tibetan Meadow Ecosystem. J. Hydrometeor.. doi: 10.1175/JHM-D-16-0199.1 |
[64] |
Zhong, S. Y., and J. Fast, 2003: An evaluation of the MM5, RAMS, and Meso-Eta models at subkilometer resolution using VTMX field campaign data in the Salt Lake valley. Mon. Wea. Rev., 131, 1301–1322. doi: 10.1175/1520-0493(2003)131<1301:AEOTMR>2.0.CO;2 |