Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments

Journal of Geophysical Research Atmospheres

Volumn 118, Issue 18, 2013, Pages 10,490-10,505

  Hu, Xiao Ming ^a   Klein, Petra M ^a   Xue, Ming ^a  

^a UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

low level jet; nighttime boundary layer; ozone; planetary boundary layer scheme; wind resource; WRF Chem

Indexed keywords

AIR QUALITY; ATMOSPHERIC MOVEMENTS; ATMOSPHERIC TEMPERATURE; ATMOSPHERIC THERMODYNAMICS; BOUNDARY LAYERS; OZONE; WIND POWER;

LOW LEVEL JET; NIGHTTIME BOUNDARY LAYERS; PLANETARY BOUNDARY LAYERS; WIND RESOURCES; WRF/CHEM;

WEATHER FORECASTING;

AIR QUALITY; ATMOSPHERIC CHEMISTRY; BOUNDARY LAYER; CLIMATE MODELING; CLIMATE VARIATION; ESTIMATION METHOD; PLANETARY ATMOSPHERE; SIMULATION; VERTICAL MIXING; WIND FIELD;

GREAT PLAINS;

EID: 84885967314     PISSN: None     EISSN: 21698996     Source Type: Journal    
DOI: 10.1002/jgrd.50823     Document Type: Article

References (121)

1. Archer, C. L., and, M. Z. Jacobson, (2003), Spatial and temporal distributions of US winds and wind power at 80 m derived from measurements, J. Geophys. Res., 108 (D9), 4289, doi: 10.1029/2002JD002076.
2. Arnold, J. R., and, R. L. Dennis, (2001), First results from operational testing of the U.S. EPA Models-3/Community Multiscale Model for Air Quality (CMAQ), in Air Pollution Modeling and Its Application XIV, edited by, S.-E. Gryning, and, F. A. Schiermeier, pp. 651-658, Kluwer Acad., Norwell, Mass.
3. Atlaskin, E., and, T. Vihma, (2012), Evaluation of NWP results for wintertime nocturnal boundary layer temperatures over Europe and Finland, Q. J. Roy Meteor. Soc., 138 (667), 1440-1451, doi: 10.1002/Qj.1885.
4. Banta, R. M., R. K. Newsom, J. K. Lundquist, Y. L. Pichugina, R. L. Coulter, and, L. Mahrt, (2002), Nocturnal low-level jet characteristics over Kansas during CASES-99, Bound-Lay Meteorol., 105 (2), 221-252, doi: 10.1023/A:1019992330866.
5. Banta, R. M., Y. L. Pichugina, and, R. K. Newsom, (2003), Relationship between low-level jet properties and turbulence kinetic energy in the nocturnal stable boundary layer, J. Atmos. Sci., 60 (20), 2549-2555, doi: 10.1175/1520-0469(2003)060<2549:Rbljpa>2.0.Co;2.
6. Banta, R. M., Y. L. Pichugina, N. D. Kelley, R. M. Hardesty, and, W. A. Brewer, (2013), Wind Energy Meteorology: Insight into wind properties in the turbine-rotor layer of the atmosphere from high-resolution doppler lidar, Bull. Am. Meteorol. Soc., 94 (6), 883-902, doi: 10.1175/Bams-D-11-00057.1.
7. Bao, J. W., S. A. Michelson, P. O. G. Persson, I. V. Djalalova, and, J. M. Wilczak, (2008), Observed and WRF-simulated low-level winds in a high-ozone episode during the Central California Ozone Study, J. Appl. Meteorol. Climatol., 47 (9), 2372-2394, doi: 10.1175/2008jamc1822.1.
8. Beare, R. J., et al. (2006), An intercomparison of large-eddy simulations of the stable boundary layer, Bound-Lay Meteorol., 118 (2), 247-272, doi: 10.1007/s10546-004-2820-6.
9. Beljaars, A. C. M., and, A. A. M. Holtslag, (1991), Flux Parameterization over Land Surfaces for Atmospheric Models, J. Appl. Meteorol., 30 (3), 327-341, doi: 10.1175/1520-0450(1991)030<0327:Fpolsf>2.0.Co;2.
10. Berg, L. K., and, S. Y. Zhong, (2005), Sensitivity of MM5-simulated boundary layer characteristics to turbulence parameterizations, J. Appl. Meteorol., 44 (9), 1467-1483, doi: 10.1175/Jam2292.1.
11. Borge, R., V. Alexandrov, J. J. del Vas, J. Lumbreras, and, E. Rodriguez, (2008), A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula, Atmos. Environ., 42 (37), 8560-8574, doi: 10.1016/j.atmosenv.2008.08.032.
12. Bougeault, P., and, P. Lacarrere, (1989), Parameterization of orography-induced turbulence in a mesobeta-scale model, Mon. Weather Rev., 117 (8), 1872-1890, doi: 10.1175/1520-0493(1989)117<1872:Pooiti>2.0.Co;2.
13. Bravo, M., T. Mira, M. R. Soler, and, J. Cuxart, (2008), Intercomparison and evaluation of MM5 and Meso-NH mesoscale models in the stable boundary layer, Bound-Lay Meteorol., 128 (1), 77-101, doi: 10.1007/s10546-008-9269-y.
14. Brost, R. A., and, J. C. Wyngaard, (1978), A model study of the stably stratified planetary boundary layer, J. Atmos. Sci., 35 (8), 1427-1440, doi: 10.1175/1520-0469(1978)035<1427:amsots>2.0.co;2.
15. 5 through the nocturnal boundary layer, Atmos. Chem. Phys., 7 (1), 139-149, doi: 10.5194/acp-7-139-2007.
16. Brown, A. R., R. J. Beare, J. M. Edwards, A. P. Lock, S. J. Keogh, S. F. Milton, and, D. N. Walters, (2008), Upgrades to the boundary layer scheme in the Met Office numerical weather prediction model, Bound-Lay Meteorol., 128 (1), 117-132, doi: 10.1007/s10546-008-9275-0.
17. Carter, K. C., A. J. Deppe, and, W. A. Gallus, (2011), Simulations of nocturnal LLJs with a WRF PBL scheme ensemble and comparison to observations from the ARM project. 20th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc. P474.
18. Carvalho, D., A. Rocha, M. Gomez-Gesteira, and, C. Santos, (2012), A sensitivity study of the WRF model in wind simulation for an area of high wind energy, Environ. Modell. Software, 33, 23-34, doi: 10.1016/j.envsoft.2012.01. 019.
19. Chen, F., and, J. Dudhia, (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 (4), 569-585, doi: 10.1175/1520-0493(2001)129<0569:Caalsh>2.0.Co;2.
20. Chen, J. J., H. T. Mao, R. W. Talbot, and, R. J. Griffin, (2006), Application of the CACM and MPMPO modules using the CMAQ model for the eastern United States, J. Geophys. Res., 111, D23S25, doi: 10.1029/2006JD007603.
21. 2.5 forecast system for the Pacific Northwest, J. Geophys. Res., 113, D14305, doi: 10.1029/2007JD009554.
22. Cheng, F. Y., S. C. Chin, and, T. H. Liu, (2012), The role of boundary layer schemes in meteorological and air quality simulations of the Taiwan area, Atmos. Environ., 54, 714-727, doi: 10.1016/j.atmosenv.2012.01.029.
23. Coniglio, M. C., J. Correia, P. T. Marsh, and, F. Kong, (2013), Verification of convection-allowing WRF model forecasts of the planetary boundary layer using sounding observations, Weather Forecast, 28 (3), 842-862, doi: 10.1175/Waf-D-12-00103.1.
24. De Wekker, S. F. J., L. K. Berg, J. Allwine, J. C. Doran, and, W. J. Shaw, (2004), Boundary-layer structure upwind and downwind of Oklahoma City during the Joint Urban 2003 field study. Preprints. Fifth Conf. on Urban Environment, Vancouver, BC, Canada, Amer. Meteor. Soc., CD-ROM, 3.20.
25. Deppe, A. J., (2011), Improvements in numerical prediction of low level winds. Graduate Theses and Dissertations. Paper 10100. http://lib.dr.iastate. edu/etd/10100.
26. Deppe, A. J., W. A. Gallus, and, E. S. Takle, (2013), A WRF ensemble for improved wind speed forecasts at turbine height, Weather Forecast, 28 (1), 212-228, doi: 10.1175/WAF-D-11-00112.1.
27. Draxl, C., A. N. Hahmann, A. Peña, and, G. Giebel, (2012), Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes, Wind Energy, doi: 10.1002/we.1555.
28. Dudhia, J., (1989), Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46 (20), 3077-3107, doi: 10.1175/1520-0469(1989)046<3077:Nsocod>2.0. Co;2.
29. Eder, B., D. W. Kang, R. Mathur, S. C. Yu, and, K. Schere, (2006), An operational evaluation of the Eta-CMAQ air quality forecast model, Atmos. Environ., 40 (26), 4894-4905, doi: 10.1016/j.atmonsenv.2005.12.062.
30. Emmons, L. K., et al. (2010), Description and evaluation of the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4), Geosci. Model Dev., 3 (1), 43-67, doi: 10.5194/gmd-3-43-2010.
31. Engardt, M., (2008), Modelling of near-surface ozone over South Asia, J. Atmos. Chem., 59 (1), 61-80, doi: 10.1007/s10874-008-9096-z.
32. Fernando, H. J. S., and, J. C. Weil, (2010), Whither the stable boundary layer? A shift in the research agenda, Bull. Am. Meteorol. Soc., 91 (11), 1475-1484, doi: 10.1175/2010bams2770.1.
33. Fiebrich, C. A., and, K. C. Crawford, (2001), The impact of unique meteorological phenomena detected by the Oklahoma Mesonet and ARS Micronet on automated quality control, Bull. Am. Meteorol. Soc., 82 (10), 2173-2187, doi: 10.1175/1520-0477(2001)082<2173:Tioump>2.3.Co;2.
34. Floors, R., C. L. Vincent, S. E. Gryning, A. Peña, and, E. Batchvarova, (2013), The wind profile in the coastal boundary layer: Wind lidar measurements and numerical modelling, Bound-Lay Meteorol., 147 (3), 469-491, doi: 10.1007/s10546-012-9791-9.
35. Ganzeveld, L., et al. (2008), Surface and boundary layer exchanges of volatile organic compounds, nitrogen oxides and ozone during the GABRIEL campaign, Atmos. Chem. Phys., 8 (20), 6223-6243, doi: 10.5194/acp-8-6223-2008.
36. García-Díez, M., J. Fernández, L. Fita, and, C. Yagüe, (2013), Seasonal dependence of WRF model biases and sensitivity to PBL schemes over Europe, Quart. J. Roy. Meteor. Soc., 139 (671), 501-514, doi: 10.1002/qj.1976.
37. Garcia-Menendez, F., Y. Hu, and, M. T. Odman, (2013), Simulating smoke transport from wildland fires with a regional-scale air quality model: Sensitivity to uncertain wind fields, J Geophys Res. Atmos, 118, 6493-6504, doi: 10.1002/jgrd.50524.
38. Gilliam, R. C., and, J. E. Pleim, (2010), Performance assessment of new land surface and planetary boundary layer physics in the WRF-ARW, J. Appl. Meteorol. Climatol., 49 (4), 760-774, doi: 10.1175/2009jamc2126.1.
39. Gilliam, R. C., J. M. Godowitch, and, S. T. Rao, (2012), Improving the horizontal transport in the lower troposphere with four dimensional data assimilation, Atmos. Environ., 53, 186-201, doi: 10.1016/j.atmosenv.2011.10.064.
40. Grell, G. A., S. E. Peckham, R. Schmitz, S. A. McKeen, G. Frost, W. C. Skamarock, and, B. Eder, (2005), Fully coupled "online" chemistry within the WRF model, Atmos. Environ., 39 (37), 6957-6975, doi: 10.1016/j.atmosenv.2005.04.027.
41. Grisogono, B., (2010), Generalizing 'z-less' mixing length for stable boundary layers, Quart. J. Roy. Meteor. Soc., 136 (646), 213-221, doi: 10.1002/Qj.529.
42. Grisogono, B., and, D. Belusic, (2008), Improving mixing length-scale for stable boundary layers, Quart. J. Roy. Meteor. Soc., 134 (637), 2185-2192, doi: 10.1002/Qj.347.
43. Guenther, A., P. Zimmerman, and, M. Wildermuth, (1994), Natural volatile organic-compound emission rate estimates for United-States woodland landscapes, Atmos. Environ., 28 (6), 1197-1210, doi: 10.1016/1352-2310(94)90297-6.
44. Ha, K. J., and, L. Mahrt, (2001), Simple inclusion of z-less turbulence within and above the modeled nocturnal boundary layer, Mon. Weather Rev., 129 (8), 2136-2143, doi: 10.1175/1520-0493(2001)129<2136:Siozlt>2.0.Co;2.
45. Han, Z. W., H. Ueda, and, J. L. An, (2008), Evaluation and intercomparison of meteorological predictions by five MM5-PBL parameterizations in combination with three land-surface models, Atmos. Environ., 42 (2), 233-249, doi: 10.1016/j.atmosenv.2007.09.053.
46. Hanna, S. R., and, R. X. Yang, (2001), Evaluations of mesoscale models' simulations of near-surface winds, temperature gradients, and mixing depths, J. Appl. Meteorol., 40 (6), 1095-1104, doi: 10.1175/1520-0450(2001)040<1095: Eommso>2.0.Co;2.
47. Herwehe, J. A., T. L. Otte, R. Mathur, and, S. T. Rao, (2011), Diagnostic analysis of ozone concentrations simulated by two regional-scale air quality models, Atmos. Environ., 45 (33), 5957-5969, doi: 10.1016/j.atmosenv.2011.08. 011.
48. Hong, S. Y., (2010), A new stable boundary layer mixing scheme and its impact on the simulated East Asian summer monsoon, Quart. J. Roy. Meteor. Soc., 136 (651), 1481-1496, doi: 10.1002/Qj.665.
49. Hong, S. Y., J. Dudhia, and, S. H. Chen, (2004), A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation, Mon. Weather Rev., 132 (1), 103-120, doi: 10.1175/1520-0493(2004) 132<0103:Aratim>2.0.Co;2.
50. Hong, S. Y., Y. Noh, and, J. Dudhia, (2006), A new vertical diffusion package with an explicit treatment of entrainment processes, Mon. Weather Rev., 134 (9), 2318-2341, doi: 10.1175/Mwr3199.1.
51. Hu, X.-M., (2008), Incorporation of the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) into the Weather Research and Forecasting Model with Chemistry (WRF/Chem): Model development and retrospective applications, Ph.D. dissertation, N. C. State Univ., Raleigh, July. http://repository.lib.ncsu.edu/ir/handle/1840.16/5241.
52. Hu, X.-M., J. W. Nielsen-Gammon, and, F. Q. Zhang, (2010a), Evaluation of three planetary boundary layer schemes in the WRF model, J. Appl. Meteorol. Climatol., 49 (9), 1831-1844, doi: 10.1175/2010jamc2432.1.
53. Hu, X.-M., F. Q. Zhang, and, J. W. Nielsen-Gammon, (2010b), Ensemble-based simultaneous state and parameter estimation for treatment of mesoscale model error: A real-data study, Geophys. Res. Lett., 37, L08802, doi: 10.1029/2010GL043017.
54. Hu, X.-M., J. D. Fuentes, and, F. Q. Zhang, (2010c), Downward transport and modification of tropospheric ozone through moist convection, J. Atmos. Chem., 65 (1), 13-35, doi: 10.1007/s10874-010-9179-5.
55. Hu, X.-M., D. C. Doughty, K. J. Sanchez, E. Joseph, and, J. D. Fuentes, (2012), Ozone variability in the atmospheric boundary layer in Maryland and its implications for vertical transport model, Atmos. Environ., 46, 354-364, doi: 10.1016/j.atmosenv.2011.09.054.
56. Hu, X.-M., P. M. Klein, M. Xue, F. Q. Zhang, D. C. Doughty, R. Forkel, E. Joseph, and, J. D. Fuentes, (2013a), Impact of the vertical mixing induced by low-level jets on boundary layer ozone concentration, Atmos. Environ., 70, 123-130, doi: 10.1016/j.atmosenv.2012.12.046.
57. Hu, X.-M., P. M. Klein, M. Xue, J. K. Lundquist, F. Zhang, and, Y. Qi, (2013b), Impact of low-level jets on the nocturnal urban heat island intensity in Oklahoma City, J. Appl. Meteorol. Climatol., 52 (8), 1779-1802, doi: 10.1175/Jamc-D-12-0256.1.
58. Hu, X.-M., P. M. Klein, M. Xue, A. Shapiro, and, A. Nallapareddy, (2013c), Enhanced vertical mixing associated with a nocturnal cold front passage and its impact on near-surface temperature and ozone concentration, J. Geophys. Res. Atmos., 118, 2714-2728, doi: 10.1002/jgrd.50309.
59. Irwin, J. S., (1979), Theoretical variation of the wind profile power-law exponent as a function of surface-roughness and stability, Atmos. Environ., 13 (1), 191-194, doi: 10.1016/0004-6981(79)90260-9.
60. Janjic, Z. I., (1990), The step-mountain coordinate: Physical package, Mon. Weather Rev., 118 (7), 1429-1443, doi: 10.1175/1520-0493(1990)118<1429: Tsmcpp>2.0.Co;2.
61. Jankov, I., W. A. Gallus, M. Segal, B. Shaw, and, S. E. Koch, (2005), The impact of different WRF model physical parameterizations and their interactions on warm season MCS rainfall, Weather Forecast, 20 (6), 1048-1060, doi: 10.1175/Waf888.1.
62. Jankov, I., P. J. Schultz, C. J. Anderson, and, S. E. Koch, (2007), The impact of different physical parameterizations and their interactions on cold season QPF in the American River basin, J. Hydrometeorol., 8 (5), 1141-1151, doi: 10.1175/Jhm630.1.
63. Klein, P. M., X.-M. Hu, and, M. Xue, (2013), Impacts of mixing processes in the nocturnal atmospheric boundary layer on urban ozone concentrations, Bound-Lay Meteorol., doi: 10.1007/s10546-013-9864-4.
64. Kolling, J. S., J. E. Pleim, H. E. Jeffries, and, W. Vizuete, (2012), A multisensor evaluation of the Asymmetric Convective Model, Version 2, in southeast Texas, J. Air Waste Manage., 63 (1), 41-53, doi: 10.1080/10962247. 2012.732019.
65. Lareau, N. P., E. Crosman, C. D. Whiteman, J. D. Horel, S. W. Hoch, W. O. J. Brown, and, T. W. Horst, (2013), The persistent cold-air pool study, Bull. Am. Meteorol. Soc., 94 (1), 51-63, doi: 10.1175/Bams-D-11-00255.1.
66. LeMone, M. A., M. Tewari, F. Chen, and, J. Dudhia, (2013), Objectively determined fair-weather CBL depths in the ARW-WRF model and their comparison to CASES-97 observations, Mon. Weather Rev., 141 (1), 30-54, doi: 10.1175/Mwr-D-12-00106.1.
67. Li, X. L., and, Z. X. Pu, (2008), Sensitivity of numerical simulation of early rapid intensification of hurricane emily (2005) to cloud microphysical and planetary boundary layer parameterizations, Mon. Weather Rev., 136 (12), 4819-4838, doi: 10.1175/2008mwr2366.1.
68. Lin, J. T., and, M. B. McElroy, (2010), Impacts of boundary layer mixing on pollutant vertical profiles in the lower troposphere: Implications to satellite remote sensing, Atmos. Environ., 44 (14), 1726-1739, doi: 10.1016/j.atmosenv.2010.02.009.
69. Lundquist, J. K., and, J. D. Mirocha, (2008), Interaction of nocturnal low-level jets with urban geometries as seen in joint urban 2003 data, J. Appl. Meteorol. Climatol., 47 (1), 44-58, doi: 10.1175/2007jamc1581.1.
70. Mahrt, L., and, D. Vickers, (2002), Contrasting vertical structures of nocturnal boundary layers, Bound-Lay Meteorol., 105 (2), 351-363, doi: 10.1023/A:1019964720989.
71. Mao, Q., L. L. Gautney, T. M. Cook, M. E. Jacobs, S. N. Smith, and, J. J. Kelsoe, (2006), Numerical experiments on MM5-CMAQ sensitivity to various PBL schemes, Atmos. Environ., 40 (17), 3092-3110, doi: 10.1016/j.atmosenv.2005.12. 055.
72. McPherson, R. A., et al. (2007), Statewide monitoring of the mesoscale environment: A technical update on the Oklahoma Mesonet, J. Atmos. Oceanic Technol., 24 (3), 301-321, doi: 10.1175/Jtech1976.1.
73. Mebust, M. R., B. K. Eder, F. S. Binkowski, and, S. J. Roselle, (2003), Models-3 community multiscale air quality (CMAQ) model aerosol component-2. Model evaluation, J. Geophys. Res., 108 (D6), 4184, doi: 10.1029/2001JD001410.
74. Miao, J. F., D. Chen, K. Wyser, K. Borne, J. Lindgren, M. K. S. Strandevall, S. Thorsson, C. Achberger, and, E. Almkvist, (2008), Evaluation of MM5 mesoscale model at local scale for air quality applications over the Swedish west coast: Influence of PBL and LSM parameterizations, Meteor. Atmos. Phys., 99 (1-2), 77-103, doi: 10.1007/s00703-007-0267-2.
75. Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and, S. A. Clough, (1997), Radiative transfer for inhomogeneous atmospheres: RRTMa validated correlated-k model for the longwave, J. Geophys. Res., 102 (D14), 16,663-16,682, doi: 10.1029/97JD00237.
76. Mohan, M., and, S. Bhati, (2011), Analysis of WRF model performance over subtropical region of Delhi, India, Adv Meteorol., doi: 10.1155/2011/621235.
77. Nielsen-Gammon, J. W., X. M. Hu, F. Q. Zhang, and, J. E. Pleim, (2010), Evaluation of planetary boundary layer scheme sensitivities for the purpose of parameter estimation, Mon. Weather Rev., 138 (9), 3400-3417, doi: 10.1175/2010mwr3292.1.
78. Pleim, J. E., (2007a), A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing, J. Appl. Meteorol. Climatol., 46 (9), 1383-1395, doi: 10.1175/Jam2539.1.
79. 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. Meteorol. Climatol., 46 (9), 1396-1409, doi: 10.1175/Jam2534.1.
80. Pleim, J. E., (2011), Comment on "Simulation of surface ozone pollution in the central gulf coast region using WRF/Chem model: Sensitivity to PBL and land surface physics", Adv. Meteorol., 464753, doi: 10.1155/2011/464753.
81. Prabha, T., and, G. Hoogenboom, (2008), Evaluation of the Weather Research and Forecasting model for two frost events, Comput Electron Agr, 64 (2), 234-247, doi: 10.1016/j.compag.2008.05.019.
82. Prabha, T. V., G. Hoogenboom, and, T. G. Smirnova, (2011), Role of land surface parameterizations on modeling cold-pooling events and low-level jets, Atmos Res, 99 (1), 147-161, doi: 10.1016/j.atmosres.2010.09.017.
83. Richardson, H. L., (2012), Improving stable boundary layer parameterization in a mesoscale model to better represent nocturnal low-level jets, M.S. thesis, N. C. State Univ., Raleigh, July. http://www.lib.ncsu.edu/ resolver/1840.16/7948.
84. Salmond, J. A., and, I. G. McKendry, (2005), A review of turbulence in the very stable nocturnal boundary layer and its implications for air quality, Prog. Phys. Geogr., 29 (2), 171-188, doi: 10.1191/0309133305pp442ra.
85. Sanjay, J., (2008), Assessment of atmospheric boundary-layer processes represented in the numerical model MM5 for a clear sky day using LASPEX observations, Bound-Lay Meteorol., 129 (1), 159-177, doi: 10.1007/s10546-008- 9298-6.
86. Schumacher, R. S., A. J. Clark, M. Xue, and, F. Kong, (2013), Factors influencing the development and maintenance of nocturnal heavy-rain-producing convective systems in a storm-scale ensemble, Mon. Weather Rev., 141 (8), 2778-2801, doi: 10.1175/Mwr-D-12-00239.1.
87. Seigneur, C., et al. (2000), Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility, J. Air Waste Manage., 50 (4), 588-599.
88. Shimada, S., T. Ohsawa, S. Chikaoka, and, K. Kozai, (2011), Accuracy of the wind speed profile in the lower PBL as simulated by the WRF model, Sola, 7, 109-112, doi: 10.2151/sola.2011-028.
89. Shin, H. H., and, S. Y. Hong, (2011), Intercomparison of planetary boundary-layer parametrizations in the WRF model for a single day from CASES-99, Bound-Lay Meteorol., 139 (2), 261-281, doi: 10.1007/s10546-010-9583-z.
90. Sisterson, D. L., and, P. Frenzen, (1978), Nocturnal boundary-layer wind maxima and problem of wind power assessment, Environ. Sci. Technol., 12 (2), 218-221, doi: 10.1021/Es60138a014.
91. Skamarock, W. C., et al. (2008), A description of the advanced research WRF version 3. NCAR Tech. Note TN-475-STR, 113 pp.
92. Smedman, A. S., M. Tjernstrom, and, U. Hogstrom, (1993), Analysis of the turbulence structure of a marine low-level jet, Bound-Lay Meteorol., 66 (1-2), 105-126, doi: 10.1007/Bf00705462.
93. Smedman, A. S., H. Bergstrom, and, U. Hogstrom, (1995), Spectra, variances and length scales in a marine stable boundary layer dominated by a low level jet, Bound-Lay Meteorol., 76 (3), 211-232, doi: 10.1007/Bf00709352.
94. Srinivas, C. V., R. Venkatesan, and, A. B. Singh, (2007), Sensitivity of mesoscale simulations of land-sea breeze to boundary layer turbulence parameterization, Atmos. Environ., 41 (12), 2534-2548, doi: 10.1016/j.atmosenv. 2006.11.027.
95. Steeneveld, G. J., B. J. H. Van de Wiel, and, A. A. M. Holtslag, (2006), Modelling the Arctic Stable boundary layer and its coupling to the surface, Bound-Lay Meteorol., 118 (2), 357-378, doi: 10.1007/s10546-005-7771-z.
96. Steeneveld, G. J., T. Mauritsen, E. I. F. de Bruijn, J. V. G. de Arellano, G. Svensson, and, A. A. M. Holtslag, (2008), Evaluation of limited-area models for the representation of the diurnal cycle and contrasting nights in CASES-99, J. Appl. Meteorol. Climatol., 47 (3), 869-887, doi: 10.1175/2007jamc1702.1.
97. Sterk, H. A. M., G. J. Steeneveld, and, A. A. M. Holtslag, (2013), The role of snow-surface coupling, radiation, and turbulent mixing in modeling a stable boundary layer over Arctic sea ice, J Geophys Res. Atmos, 118, 1199-1217, doi: 10.1002/jgrd.50158.
98. Stockwell, W. R., F. Kirchner, M. Kuhn, and, S. Seefeld, (1997), A new mechanism for regional atmospheric chemistry modeling, J. Geophys. Res., 102 (D22), 25,847-25,879, doi: 10.1029/97JD00849.
99. Stockwell, W., R. Fitzgerald, D. Lu, and, R. Perea, (2013), Differences in the variability of measured and simulated tropospheric ozone mixing ratios over the Paso del Norte Region, J. Atmos. Chem., 70 (1), 91-104, doi: 10.1007/s10874-013-9253-x.
100. Storm, B., and, S. Basu, (2010), The WRF model forecast-derived low-level wind shear climatology over the United States Great Plains, Energies, 3 (2), 258-276, doi: 10.3390/En3020258.
101. Storm, B., J. Dudhia, S. Basu, A. Swift, and, I. Giammanco, (2009), Evaluation of the weather research and forecasting model on forecasting low-level jets: Implications for wind energy, Wind Energy, 12 (1), 81-90, doi: 10.1002/We.288.
102. x in the nocturnal boundary layer: 1. Observations during the Texas Air Quality Study 2000, J. Geophys. Res., 109, D12306, doi: 10.1029/2003JD004209.
103. Svensson, G., et al. (2011), Evaluation of the diurnal cycle in the atmospheric boundary layer over land as represented by a variety of single-column models: The second GABLS experiment, Bound-Lay Meteorol, 140 (2), 177-206, doi: 10.1007/s10546-011-9611-7.
104. Teixeira, J., et al. (2008), Parameterization of the atmospheric boundary layer, Bull. Am. Meteorol. Soc., 89 (4), 453-458, doi: 10.1175/Bams-89-4-453.
105. Todd, M. C., R. Washington, S. Raghavan, G. Lizcano, and, P. Knippertz, (2008), Regional model simulations of the Bodele low-level jet of northern Chad during the Bodele Dust Experiment (BoDEx 2005), J. Clim., 21 (5), 995-1012, doi: 10.1175/2007jcli1766.1.
106. Van de Wiel, B. J. H., R. J. Ronda, A. F. Moene, H. A. R. De Bruin, and, A. A. M. Holtslag, (2002), Intermittent turbulence and oscillations in the stable boundary layer over land, Part I: A bulk model, J. Atmos. Sci., 59 (5), 942-958, doi: 10.1175/1520-0469(2002)059<0942:Itaoit>2.0.Co;2.
107. Vautard, R., et al. (2012), Evaluation of the meteorological forcing used for the Air Quality Model Evaluation International Initiative (AQMEII) air quality simulations, Atmos. Environ., 53, 15-37, doi: 10.1016/j.atmosenv.2011. 10.065.
108. Viterbo, P., A. Beljaars, J. F. Mahfouf, and, J. Teixeira, (1999), The representation of soil moisture freezing and its impact on the stable boundary layer, Q. J. Roy Meteor. Soc., 125 (559), 2401-2426, doi:1256/Smsqj.55903.
109. Wexler, H., (1961), A boundary layer interpretation of the low-level jet, Tellus, 13 (3), 368-378.
110. Wolff, J., and, M. Harrold, (2013), Tracking WRF performance: How do the three most recent versions compare? The 14th annual WRF users' workshop, paper 2.6, http://www.mmm.ucar.edu/wrf/users/workshops/WS2013/ppts/2.6.pdf.
111. Xie, B., J. C. H. Fung, A. Chan, and, A. Lau, (2012), Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model, J. Geophys. Res., 117, D12103, doi: 10.1029/2011JD017080.
112. Xie, B., J. C. R. Hunt, D. J. Carruthers, J. C. H. Fung, and, J. F. Barlow, (2013), Structure of the planetary boundary layer over Southeast England: Modeling and measurements, J. Geophys. Res. Atmos., 118, 7799-7818, doi: 10.1002/jgrd.50621.
113. Yang, Q., L. K. Berg, M. Pekour, J. D. Fast, R. K. Newsom, M. Stoelinga, and, C. Finley, (2013), Evaluation of WRF-predicted near-hub-height winds and ramp events over a Pacific Northwest site with complex terrain, J. Appl. Meteorol. Climatol., 52 (8), 1753-1763, doi: 10.1175/Jamc-D-12-0267.1.
114. Yu, S. C., B. Eder, R. Dennis, S. H. Chu, and, S. E. Schwartz, (2006), New unbiased symmetric metrics for evaluation of air quality models, Atmos Sci Lett, 7 (1), 26-34, doi: 10.1002/Asl.125.
115. Yver, C. E., H. D. Graven, D. D. Lucas, P. J. Cameron-Smith, R. F. Keeling, and, R. F. Weiss, (2013), Evaluating transport in the WRF model along the California coast, Atmos. Chem. Phys., 13 (4), 1837-1852, doi: 10.5194/acp-13-1837-2013.
116. Žabkar, R., J. Rakovec, and, D. Koracin, (2011), The roles of regional accumulation and advection of ozone during high ozone episodes in Slovenia: A WRF/Chem modelling study, Atmos. Environ., 45 (5), 1192-1202, doi: 10.1016/j.atmosenv.2010.08.021.
117. Žabkar, R., D. Koračin, and, J. Rakovec, (2013), A WRF/Chem sensitivity study using ensemble modelling for a high ozone episode in Slovenia and the Northern Adriatic area, Atmos. Environ., 77 (0), 990-1004, doi: 10.1016/j.atmosenv.2013.05.065.
118. Zhang, D. L., and, W. Z. Zheng, (2004), Diurnal cycles of surface winds and temperatures as simulated by five boundary layer parameterizations, J. Appl. Meteorol., 43 (1), 157-169, doi: 10.1175/1520-0450(2004)043<0157: Dcoswa>2.0.Co;2.
119. Zhang, Y., M. K. Dubey, S. C. Olsen, J. Zheng, and, R. Zhang, (2009), Comparisons of WRF/Chem simulations in Mexico City with ground-based RAMA measurements during the 2006-MILAGRO, Atmos. Chem. Phys., 9 (11), 3777-3798, doi: 10.5194/acp-9-3777-2009.
120. Zhang, H., Z. Pu, and, X. Zhang, (2013), Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain, Weather Forecast, 28 (3), 893-914, doi: 10.1175/Waf-D-12-00109. 1.
121. Zilitinkevich, S. S., T. Elperin, N. Kleeorin, and, I. Rogachevskii, (2007), Energy- and flux-budget (EFB) turbulence closure model for stably stratified flows. Part I: Steady-state, homogeneous regimes, Bound-Lay Meteorol., 125 (2), 167-191, doi: 10.1007/s10546-007-9189-2.