Sub-kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models
Sub‐kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with o...
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Published in | Journal of Geophysical Research: Atmospheres Vol. 117; no. D11 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Washington, DC
Blackwell Publishing Ltd
16.06.2012
American Geophysical Union |
Subjects | |
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Abstract | Sub‐kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50‐m towers in west‐central Nevada during July and December 2007. Moment‐based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near‐surface wind shear; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root‐mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub‐diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy‐containing motions. Neither of the verification metrics showed systematic improvement in the models' accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment‐based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy‐containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer‐than‐diurnal than for sub‐diurnal periods. Finally, the study shows that at least near‐kilometer horizontal grid spacing is necessary for dynamical downscaling of near‐surface wind speed climate over complex terrain; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy‐containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows.
Key Points
WRF performance is superior to MM5; model error is higher closer to the ground
The improvement with horizontal grid resolution is not systematic
The most profound improvement was found for wind shear and bias of std. dev |
---|---|
AbstractList | Sub‐kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50‐m towers in west‐central Nevada during July and December 2007. Moment‐based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near‐surface wind shear; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root‐mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub‐diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy‐containing motions. Neither of the verification metrics showed systematic improvement in the models' accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment‐based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy‐containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer‐than‐diurnal than for sub‐diurnal periods. Finally, the study shows that at least near‐kilometer horizontal grid spacing is necessary for dynamical downscaling of near‐surface wind speed climate over complex terrain; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy‐containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows.
WRF performance is superior to MM5; model error is higher closer to the ground
The improvement with horizontal grid resolution is not systematic
The most profound improvement was found for wind shear and bias of std. dev Sub-kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50-m towers in west-central Nevada during July and December 2007. Moment-based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near-surface wind shear; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root-mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub-diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy-containing motions. Neither of the verification metrics showed systematic improvement in the models' accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment-based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy-containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer-than-diurnal than for sub-diurnal periods. Finally, the study shows that at least near-kilometer horizontal grid spacing is necessary for dynamical downscaling of near-surface wind speed climate over complex terrain; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy-containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows. Sub‐kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50‐m towers in west‐central Nevada during July and December 2007. Moment‐based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near‐surface wind shear; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root‐mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub‐diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy‐containing motions. Neither of the verification metrics showed systematic improvement in the models' accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment‐based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy‐containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer‐than‐diurnal than for sub‐diurnal periods. Finally, the study shows that at least near‐kilometer horizontal grid spacing is necessary for dynamical downscaling of near‐surface wind speed climate over complex terrain; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy‐containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows. Key Points WRF performance is superior to MM5; model error is higher closer to the ground The improvement with horizontal grid resolution is not systematic The most profound improvement was found for wind shear and bias of std. dev |
Author | Koracin, Darko Belu, Radian Jiang, Jinhua Vellore, Ramesh Horvath, Kristian |
Author_xml | – sequence: 1 givenname: Kristian surname: Horvath fullname: Horvath, Kristian email: kristian.horvath@gmail.com, kristian.horvath@cirus.dhz.hr organization: Meteorological and Hydrological Service, Zagreb, Croatia – sequence: 2 givenname: Darko surname: Koracin fullname: Koracin, Darko organization: Desert Research Institute, Reno, Nevada, USA – sequence: 3 givenname: Ramesh surname: Vellore fullname: Vellore, Ramesh organization: Desert Research Institute, Reno, Nevada, USA – sequence: 4 givenname: Jinhua surname: Jiang fullname: Jiang, Jinhua organization: Desert Research Institute, Reno, Nevada, USA – sequence: 5 givenname: Radian surname: Belu fullname: Belu, Radian organization: School of Technology and Professional Studies, Drexel University, Philadelphia, Pennsylvania, USA |
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Cites_doi | 10.1175/2008BAMS2487.1 10.1175/1520‐0493(1985)113<1050:ATSSFT>2.0.CO;2 10.1175/1520‐0477(2002)083<0699:ACSOTD>2.3.CO;2 10.1175/1520‐0493(2003)131<2857:RVCSFR>2.0.CO;2 10.1175/MWR3183.1 10.1175/2010MWR3432.1 10.1007/s00382‐010‐0826‐y 10.1175/JCLI3837.1 10.1175/1520‐0469(1974)031<1791:AHOTCM>2.0.CO;2 10.1175/1520‐0450(2004)043<0170:TKCPAU>2.0.CO;2 10.1175/2011JAMC2638.1 10.1175/1520‐0477(1997)078<2599:ATOLBC>2.0.CO;2 10.1175/1520‐0493(1992)120<0197:TEEOMW>2.0.CO;2 10.1175/1520‐0469(2004)061<1816:TNMITT>2.0.CO;2 10.1175/BAMS‐87‐12‐1747 10.1029/2002JD003296 10.1002/we.288 10.1175/BAMS‐87‐3‐343 10.1029/2007JD009461 10.1007/s10584‐009‐9583‐5 10.1051/jp4:2006139008 10.1175/1520‐0493(2004)132<0519:EFOWPU>2.0.CO;2 10.1175/1520‐0493(1998)126<0028:WATWSO>2.0.CO;2 10.1029/97JD00237 10.1017/CBO9780511546013 10.1111/j.1600-0870.2006.00186.x 10.1093/oso/9780195132717.001.0001 10.1175/1520‐0493(2001)129<2040:MABLDA>2.0.CO;2 10.1175/2010JCLI3514.1 10.1175/1520‐0493(1999)127<0308:LSORCA>2.0.CO;2 10.1109/TAU.1967.1161901 10.1002/qj.49711548803 10.1175/2009JAMC2351.1 10.1175/1520‐0493(2004)132<0368:NSOTFI>2.0.CO;2 10.1002/qj.129 10.1029/RG020i004p00851 10.1175/MWR3052.1 10.1175/1520‐0477(2002)083<0407:DIHRPM>2.3.CO;2 10.1175/1520‐0434(2003)018<0249:MMSOHE>2.0.CO;2 10.1007/s10546‐005‐3780‐1 10.1175/1520‐0493(2001)129<0587:CAALSH>2.0.CO;2 10.1175/JAM2322.1 10.1007/978-1-935704-13-3_16 10.1175/1520‐0493(1988)116<2417:SSBOTM>2.0.CO;2 10.1029/2007JD009216 10.1175/MWR2801.1 10.1016/j.renene.2009.02.024 10.1002/qj.49712454804 10.1175/1520‐0493(2000)128<3664:ASNTFD>2.0.CO;2 10.1175/1520‐0469(1989)046<3077:NSOCOD>2.0.CO;2 10.1175/2009JAMC2175.1 |
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Copyright | 2012. American Geophysical Union. All Rights Reserved. 2015 INIST-CNRS Copyright American Geophysical Union 2012 Copyright Blackwell Publishing Ltd. Jun 2012 |
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References | Qian, J.-H., A. Seth, and S. Zebiak (2003), Reinitialized versus continuous simulations for regional climate downscaling, Mon. Weather. Rev., 131, 2857-2874, doi:10.1175/1520-0493(2003)131<2857:RVCSFR>2.0.CO;2. Cuxart, J., et al. (2006), Single-column model intercomparison for a stably stratified atmospheric boundary layer, Boundary Layer Meteorol., 118, 273-303, doi:10.1007/s10546-005-3780-1. Cairns, M. M., and J. Corey (2003), Mesoscale model simulations of high-wind events in the complex terrain of western Nevada, Weather Forecast., 18, 249-263, doi:10.1175/1520-0434(2003)018<0249:MMSOHE>2.0.CO;2. Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis. Contribution of the Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., Cambridge Univ. Press, Cambridge, U. K. Koracin, D., and C. E. Dorman (2001), Marine atmospheric boundary layer divergence and clouds along California in June 1996, Mon. Weather Rev., 129, 2040-2056, doi:10.1175/1520-0493(2001)129<2040:MABLDA>2.0.CO;2. Mellor, G. L., and T. Yamada (1974), A hierarchy of turbulence closure models for planetary boundary layers, J. Atmos. Sci., 31, 1791-1806, doi:10.1175/1520-0469(1974)031<1791:AHOTCM>2.0.CO;2. Takacs, L. L. (1985), A two-step scheme for the advection equation with minimized dissipation and dispersion errors, Mon. Weather Rev., 113, 1050-1065, doi:10.1175/1520-0493(1985)113<1050:ATSSFT>2.0.CO;2. Leung, L. R., Y. H. Kuo, and J. Tribbia (2006), Research needs and directions of regional climate modeling using WRF and CCSM, Bull. Am. Meteorol. Soc., 87, 1747-1751, doi:10.1175/BAMS-87-12-1747. Trapp, R. J., E. D. Robinson, M. E. Baldwin, N. S. Diffenbaugh, and B. R. J. Schwedler (2011), Regional climate of hazardous convective weather through high-resolution dynamical downscaling, Clim. Dyn., 37, 677-688, doi:10.1007/s00382-010-0826-y. Pan, Z., E. Takle, W. Gutowski, and R. Turner (1999), Long simulation of regional climate as a sequence of short segments, Mon. Weather Rev., 127, 308-321, doi:10.1175/1520-0493(1999)127<0308:LSORCA>2.0.CO;2. Jeglum, M. E., W. J. Steenburgh, T. P. Lee, and L. F. Bosart (2010), Multi-reanalysis climatology of intermountain cyclones, Mon. Weather Rev., 138, 4035-4053, doi:10.1175/2010MWR3432.1. vonStorch, H., H. Langenberg, and F. Feser (2000), A spectral nudging technique for dynamical downscaling purposes, Mon. Weather Rev., 128, 3664-3673, doi:10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2. Grubišić, V., et al. (2008), The Terrain-Induced Rotor Experiment: A field campaign overview including observational highlights, Bull. Am. Meteorol. Soc., 89, 1513-1533, doi:10.1175/2008BAMS2487.1. Rife, D. L., C. A. Davis, and Y. Liu (2004), Predictability of low-level winds by mesoscale meteorological models, Mon. Weather Rev., 132, 2553-2569, doi:10.1175/MWR2801.1. Wyngaard, J. C. (2004), Toward numerical modeling in the "terra incognita," J. Atmos. Sci., 61, 1816-1826, doi:10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2. Conil, S., and A. Hall (2006), Local regimes of atmospheric variability: A case study of Southern California, J. Clim., 19, 4308-4325, doi:10.1175/JCLI3837.1. Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough (1997), Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102(D14), 16,663-16,682, doi:10.1029/97JD00237. Rife, D. L., and C. A. Davis (2005), Verification of temporal variations in mesoscale numerical wind forecasts, Mon. Weather Rev., 133, 3368-3381, doi:10.1175/MWR3052.1. Kain, J. S. (2004), The Kain-Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170-181, doi:10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2. 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, 81-90, doi:10.1002/we.288. Thompson, G., R. M. Rasmussen, and K. Manning (2004), Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis, Mon. Weather Rev., 132, 519-542, doi:10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2. Mass, C. F., D. Ovens, K. Westrick, and B. A. Colle (2002), Does increasing horizontal resolution produce more skillful forecast?, Bull. Am. Meteorol. Soc., 83, 407-430, doi:10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2. 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. Jiménez, P. A., J. F. Gonzálaz-Rouco, E. García-Bustamente, J. Navarro, J. P. Montávez, J. Vilá-Guerau de Arellano, J. Dudhia, and A. Munoz-Roldan (2010), Surface wind regionalization over complex terrain: Evaluation and analysis of a high-resolution WRF simulation, J. Appl. Meteorol. Climatol., 49, 268-287, doi:10.1175/2009JAMC2175.1. Feser, F. (2006), Enhanced detectability of added value in limited-area model results separated into different spatial scales, Mon. Weather Rev., 134, 2180-2190, doi:10.1175/MWR3183.1. Warner, T. T., R. A. Peterson, and R. E. Treadon (1997), A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction, Bull. Am. Meteorol. Soc., 78, 2599-2617, doi:10.1175/1520-0477(1997)078<2599:ATOLBC>2.0.CO;2. Anthes, R. A., Y.-H. Kuo, E.-Y. Hsie, S. Low-Nam, and T. W. Bettge (1989), Estimation of skill and uncertainty in regional numerical models, Q. J. R. Meteorol. Soc., 115, 763-806, doi:10.1002/qj.49711548803. Giorgi, F. (2006), Regional climate modeling: Status and perspectives, J. Phys. IV, 139, 101-118, doi:10.1051/jp4:2006139008. Colle, B. A., and C. F. Mass (1998), Windstorms along the western side of the Washington Cascade Mountains. Part I: A high-resolution observational and modeling study of the 12 February 1995 event, Mon. Weather Rev., 126, 28-52, doi:10.1175/1520-0493(1998)126<0028:WATWSO>2.0.CO;2. Mesinger, F., et al. (2006), North American regional reanalysis, Bull. Am. Meteorol. Soc., 87, 343-360, doi:10.1175/BAMS-87-3-343. Chen, F., and J. Dudhia (2001), Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 Modeling System. Part II: Preliminary model validation, Mon. Weather Rev., 129, 587-604, doi:10.1175/1520-0493(2001)129<0587:CAALSH>2.0.CO;2. Welch, P. D. (1967), The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms, IEEE Trans. Audio Electroacoust., 15(2), 70-73, doi:10.1109/TAU.1967.1161901. Reisner, J., R. M. Rasmussen, and R. T. Bruintjes (1998), Explicit forecasting of supercooled liquid water in winter storms using the MM5 forecast model, Q. J. R. Meteorol. Soc., 124, 1071-1107, doi:10.1002/qj.49712454804. Rife, D. L., J. O. Pinto, A. J. Monaghan, C. A. Davis, and J. R. Hannan (2010), Global distribution and characteristics of diurnally varying low-level jets, J. Clim., 23, 5041-5064, doi:10.1175/2010JCLI3514.1. Belušić, D., M. Žagar, and B. Grisogono (2007), Numerical simulation of pulsations in the bora wind, Q. J. R. Meteorol. Soc., 133, 1371-1388, doi:10.1002/qj.129. Belu, R., and D. Koracin (2009), Wind characteristics and wind energy potential in western Nevada, Renewable Energy, 34, 2246-2251, doi:10.1016/j.renene.2009.02.024. Stewart, J. Q., C. D. Whiteman, W. J. Steenburgh, and X. Bian (2002), A climatological study of thermally driven wind systems if the U.S. intermountain west, Bull. Am. Meteorol. Soc., 83, 699-708, doi:10.1175/1520-0477(2002)083<0699:ACSOTD>2.3.CO;2. Zängl, G., B. Chimani, and C. Häberli (2004), Numerical simulations of the foehn in the Rhine valley on 24 October 1999 (MAP IOP 10), Mon. Weather Rev., 132, 368-389, doi:10.1175/1520-0493(2004)132<0368:NSOTFI>2.0.CO;2. Rockel, B., C. L. Castro, R. A. Pielke Sr., H. vonStorch, and G. Leoncini (2008), Dynamical downscaling: Assessment of model system dependent retained and added variability for two different regional climate models, J. Geophys. Res., 113, D21107, doi:10.1029/2007JD009461. Lo, J. C.-F., Z.-L. Yang, and R. A. Pielke Sr. (2008), Assessment of three dynamical climate downscaling methods using the Weather Research and Forecasting (WRF) model, J. Geophys. Res., 113, D09112, doi:10.1029/2007JD009216. Mellor, G. L., and T. Yamada (1982), Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851-875, doi:10.1029/RG020i004p00851. Hahmann, A. N., D. Rostkier-Edelstein, T. T. Warner, F. Vandenberghe, Y. Liu, R. Babarsky, and S. P. Swerdlin (2010), A reanalysis system for the generation of mesoscale climatographies, J. Appl. Meteorol. Climatol., 49, 954-972. Whiteman, C. D. (2000), Mountain Meteorology: Fundamentals and Applications, Oxford Univ. Press, New York. Laprise, R. (1992), The Euler equations of motion with hydrostatic pressure as an independent variable, Mon. Weather Rev., 120, 197-207, doi:10.1175/1520-0493(1992)120<0197:TEEOMW>2.0.CO;2. Murphy, A. H. (1988), Skill scores based on the mean square error and their relationships to the correlation coefficient, Mon. Weather Rev., 116, 2417-2424, doi:10.1175/1520-0493(1988)116<2417:SSBOTM>2.0.CO;2. Žagar, N., M. Žagar, J. Cedilnik, G. Gregorič, and J. Rakovec (2006), Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA-40 over complex terrain, Tellus, Ser. A, 58, 445-455. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grummann, V. Koren, G. Gayno, and J. D. Tarpley (2003), Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108(D22), 8851, doi:10.1029/2002JD003296. Horvath, K., A. Bajić, and S. Ivatek-Šahdan (2011), Dynamical downscaling of wind speed in comp 2004; 43 2004; 61 1974; 31 1992; 120 2005; 133 1989; 115 2006; 58 2008 2007 1996 2006; 19 1994 2003; 18 1993 2011; 37 2001; 129 2006; 118 1989; 46 2006; 139 1999; 127 2006; 134 2003; 131 2009; 34 1997; 102 2010; 23 2009; 12 2004; 132 2003; 108 2010; 49 2009; 95 2006; 45 2001 2000 2010; 138 2006; 87 2002; 83 2000; 128 2007; 133 1982; 20 2011; 50 1997; 78 1985; 113 2008; 89 1998; 126 1967; 15 2008; 113 1998; 124 1988; 116 e_1_2_9_31_1 e_1_2_9_52_1 e_1_2_9_50_1 e_1_2_9_10_1 e_1_2_9_35_1 e_1_2_9_56_1 e_1_2_9_12_1 e_1_2_9_33_1 e_1_2_9_54_1 e_1_2_9_14_1 e_1_2_9_39_1 e_1_2_9_16_1 e_1_2_9_37_1 e_1_2_9_18_1 e_1_2_9_41_1 e_1_2_9_20_1 e_1_2_9_22_1 e_1_2_9_45_1 e_1_2_9_24_1 e_1_2_9_43_1 e_1_2_9_8_1 e_1_2_9_6_1 e_1_2_9_4_1 e_1_2_9_2_1 e_1_2_9_26_1 e_1_2_9_49_1 e_1_2_9_28_1 e_1_2_9_47_1 e_1_2_9_30_1 e_1_2_9_53_1 e_1_2_9_51_1 e_1_2_9_11_1 e_1_2_9_34_1 e_1_2_9_13_1 e_1_2_9_32_1 e_1_2_9_55_1 e_1_2_9_15_1 e_1_2_9_38_1 e_1_2_9_17_1 e_1_2_9_36_1 e_1_2_9_19_1 e_1_2_9_42_1 e_1_2_9_40_1 e_1_2_9_21_1 e_1_2_9_46_1 e_1_2_9_23_1 e_1_2_9_44_1 e_1_2_9_7_1 e_1_2_9_5_1 e_1_2_9_3_1 e_1_2_9_9_1 e_1_2_9_25_1 e_1_2_9_27_1 e_1_2_9_48_1 e_1_2_9_29_1 |
References_xml | – reference: Intergovernmental Panel on Climate Change (2007), Climate Change 2007: The Physical Science Basis. Contribution of the Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by S. Solomon et al., Cambridge Univ. Press, Cambridge, U. K. – reference: Qian, J.-H., A. Seth, and S. Zebiak (2003), Reinitialized versus continuous simulations for regional climate downscaling, Mon. Weather. Rev., 131, 2857-2874, doi:10.1175/1520-0493(2003)131<2857:RVCSFR>2.0.CO;2. – reference: Rife, D. L., and C. A. Davis (2005), Verification of temporal variations in mesoscale numerical wind forecasts, Mon. Weather Rev., 133, 3368-3381, doi:10.1175/MWR3052.1. – reference: Jiménez, P. A., J. F. Gonzálaz-Rouco, E. García-Bustamente, J. Navarro, J. P. Montávez, J. Vilá-Guerau de Arellano, J. Dudhia, and A. Munoz-Roldan (2010), Surface wind regionalization over complex terrain: Evaluation and analysis of a high-resolution WRF simulation, J. Appl. Meteorol. Climatol., 49, 268-287, doi:10.1175/2009JAMC2175.1. – reference: Mellor, G. L., and T. Yamada (1982), Development of a turbulence closure model for geophysical fluid problems, Rev. Geophys., 20, 851-875, doi:10.1029/RG020i004p00851. – reference: Jeglum, M. E., W. J. Steenburgh, T. P. Lee, and L. F. Bosart (2010), Multi-reanalysis climatology of intermountain cyclones, Mon. Weather Rev., 138, 4035-4053, doi:10.1175/2010MWR3432.1. – reference: Chen, F., and J. Dudhia (2001), Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 Modeling System. Part II: Preliminary model validation, Mon. Weather Rev., 129, 587-604, doi:10.1175/1520-0493(2001)129<0587:CAALSH>2.0.CO;2. – reference: Zängl, G., B. Chimani, and C. Häberli (2004), Numerical simulations of the foehn in the Rhine valley on 24 October 1999 (MAP IOP 10), Mon. Weather Rev., 132, 368-389, doi:10.1175/1520-0493(2004)132<0368:NSOTFI>2.0.CO;2. – reference: Rockel, B., C. L. Castro, R. A. Pielke Sr., H. vonStorch, and G. Leoncini (2008), Dynamical downscaling: Assessment of model system dependent retained and added variability for two different regional climate models, J. Geophys. Res., 113, D21107, doi:10.1029/2007JD009461. – reference: Žagar, N., M. Žagar, J. Cedilnik, G. Gregorič, and J. Rakovec (2006), Validation of mesoscale low-level winds obtained by dynamical downscaling of ERA-40 over complex terrain, Tellus, Ser. A, 58, 445-455. – reference: Murphy, A. H. (1988), Skill scores based on the mean square error and their relationships to the correlation coefficient, Mon. Weather Rev., 116, 2417-2424, doi:10.1175/1520-0493(1988)116<2417:SSBOTM>2.0.CO;2. – reference: 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. – reference: Trapp, R. J., E. D. Robinson, M. E. Baldwin, N. S. Diffenbaugh, and B. R. J. Schwedler (2011), Regional climate of hazardous convective weather through high-resolution dynamical downscaling, Clim. Dyn., 37, 677-688, doi:10.1007/s00382-010-0826-y. – reference: Conil, S., and A. Hall (2006), Local regimes of atmospheric variability: A case study of Southern California, J. Clim., 19, 4308-4325, doi:10.1175/JCLI3837.1. – reference: Whiteman, C. D. (2000), Mountain Meteorology: Fundamentals and Applications, Oxford Univ. Press, New York. – reference: Kain, J. S. (2004), The Kain-Fritsch convective parameterization: An update, J. Appl. Meteorol., 43, 170-181, doi:10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2. – reference: vonStorch, H., H. Langenberg, and F. Feser (2000), A spectral nudging technique for dynamical downscaling purposes, Mon. Weather Rev., 128, 3664-3673, doi:10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2. – reference: Laprise, R. (1992), The Euler equations of motion with hydrostatic pressure as an independent variable, Mon. Weather Rev., 120, 197-207, doi:10.1175/1520-0493(1992)120<0197:TEEOMW>2.0.CO;2. – reference: Mass, C. F., D. Ovens, K. Westrick, and B. A. Colle (2002), Does increasing horizontal resolution produce more skillful forecast?, Bull. Am. Meteorol. Soc., 83, 407-430, doi:10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2. – reference: Colle, B. A., and C. F. Mass (1998), Windstorms along the western side of the Washington Cascade Mountains. Part I: A high-resolution observational and modeling study of the 12 February 1995 event, Mon. Weather Rev., 126, 28-52, doi:10.1175/1520-0493(1998)126<0028:WATWSO>2.0.CO;2. – reference: Chow, F. K., A. P. Weigel, R. L. Street, M. W. Rotach, and M. Xue (2006), High-resolution large-eddy simulations of flow in a steep alpine valley. Part I: Methodology, verification, and sensitivity experiments, J. Appl. Meteorol. Climatol., 45, 63-86, doi:10.1175/JAM2322.1. – reference: Giorgi, F. (2006), Regional climate modeling: Status and perspectives, J. Phys. IV, 139, 101-118, doi:10.1051/jp4:2006139008. – reference: Lo, J. C.-F., Z.-L. Yang, and R. A. Pielke Sr. (2008), Assessment of three dynamical climate downscaling methods using the Weather Research and Forecasting (WRF) model, J. Geophys. Res., 113, D09112, doi:10.1029/2007JD009216. – reference: Anthes, R. A., Y.-H. Kuo, E.-Y. Hsie, S. Low-Nam, and T. W. Bettge (1989), Estimation of skill and uncertainty in regional numerical models, Q. J. R. Meteorol. Soc., 115, 763-806, doi:10.1002/qj.49711548803. – reference: Belu, R., and D. Koracin (2009), Wind characteristics and wind energy potential in western Nevada, Renewable Energy, 34, 2246-2251, doi:10.1016/j.renene.2009.02.024. – reference: Feser, F. (2006), Enhanced detectability of added value in limited-area model results separated into different spatial scales, Mon. Weather Rev., 134, 2180-2190, doi:10.1175/MWR3183.1. – reference: Stewart, J. Q., C. D. Whiteman, W. J. Steenburgh, and X. Bian (2002), A climatological study of thermally driven wind systems if the U.S. intermountain west, Bull. Am. Meteorol. Soc., 83, 699-708, doi:10.1175/1520-0477(2002)083<0699:ACSOTD>2.3.CO;2. – reference: Hahmann, A. N., D. Rostkier-Edelstein, T. T. Warner, F. Vandenberghe, Y. Liu, R. Babarsky, and S. P. Swerdlin (2010), A reanalysis system for the generation of mesoscale climatographies, J. Appl. Meteorol. Climatol., 49, 954-972. – reference: Cairns, M. M., and J. Corey (2003), Mesoscale model simulations of high-wind events in the complex terrain of western Nevada, Weather Forecast., 18, 249-263, doi:10.1175/1520-0434(2003)018<0249:MMSOHE>2.0.CO;2. – reference: Warner, T. T., R. A. Peterson, and R. E. Treadon (1997), A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction, Bull. Am. Meteorol. Soc., 78, 2599-2617, doi:10.1175/1520-0477(1997)078<2599:ATOLBC>2.0.CO;2. – reference: 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, 81-90, doi:10.1002/we.288. – reference: Pan, Z., E. Takle, W. Gutowski, and R. Turner (1999), Long simulation of regional climate as a sequence of short segments, Mon. Weather Rev., 127, 308-321, doi:10.1175/1520-0493(1999)127<0308:LSORCA>2.0.CO;2. – reference: Takacs, L. L. (1985), A two-step scheme for the advection equation with minimized dissipation and dispersion errors, Mon. Weather Rev., 113, 1050-1065, doi:10.1175/1520-0493(1985)113<1050:ATSSFT>2.0.CO;2. – reference: Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grummann, V. Koren, G. Gayno, and J. D. Tarpley (2003), Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108(D22), 8851, doi:10.1029/2002JD003296. – reference: Mesinger, F., et al. (2006), North American regional reanalysis, Bull. Am. Meteorol. Soc., 87, 343-360, doi:10.1175/BAMS-87-3-343. – reference: Caldwell, P., H.-N. S. Chin, D. C. Bader, and G. Bala (2009), Evaluation of a WRF dynamical downscaling simulation over California, Clim. Change, 95, 499-521, doi:10.1007/s10584-009-9583-5. – reference: Rife, D. L., C. A. Davis, and Y. Liu (2004), Predictability of low-level winds by mesoscale meteorological models, Mon. Weather Rev., 132, 2553-2569, doi:10.1175/MWR2801.1. – reference: Koracin, D., and C. E. Dorman (2001), Marine atmospheric boundary layer divergence and clouds along California in June 1996, Mon. Weather Rev., 129, 2040-2056, doi:10.1175/1520-0493(2001)129<2040:MABLDA>2.0.CO;2. – reference: Wyngaard, J. C. (2004), Toward numerical modeling in the "terra incognita," J. Atmos. Sci., 61, 1816-1826, doi:10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2. – reference: Rife, D. L., J. O. Pinto, A. J. Monaghan, C. A. Davis, and J. R. Hannan (2010), Global distribution and characteristics of diurnally varying low-level jets, J. Clim., 23, 5041-5064, doi:10.1175/2010JCLI3514.1. – reference: Leung, L. R., Y. H. Kuo, and J. Tribbia (2006), Research needs and directions of regional climate modeling using WRF and CCSM, Bull. Am. Meteorol. Soc., 87, 1747-1751, doi:10.1175/BAMS-87-12-1747. – reference: Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough (1997), Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102(D14), 16,663-16,682, doi:10.1029/97JD00237. – reference: Reisner, J., R. M. Rasmussen, and R. T. Bruintjes (1998), Explicit forecasting of supercooled liquid water in winter storms using the MM5 forecast model, Q. J. R. Meteorol. Soc., 124, 1071-1107, doi:10.1002/qj.49712454804. – reference: Belušić, D., M. Žagar, and B. Grisogono (2007), Numerical simulation of pulsations in the bora wind, Q. J. R. Meteorol. Soc., 133, 1371-1388, doi:10.1002/qj.129. – reference: Mellor, G. L., and T. Yamada (1974), A hierarchy of turbulence closure models for planetary boundary layers, J. Atmos. Sci., 31, 1791-1806, doi:10.1175/1520-0469(1974)031<1791:AHOTCM>2.0.CO;2. – reference: Grubišić, V., et al. (2008), The Terrain-Induced Rotor Experiment: A field campaign overview including observational highlights, Bull. Am. Meteorol. Soc., 89, 1513-1533, doi:10.1175/2008BAMS2487.1. – reference: Horvath, K., A. Bajić, and S. Ivatek-Šahdan (2011), Dynamical downscaling of wind speed in complex terrain prone to bora-type flows, J. Appl. Meteorol. Climatol., 50, 1676-1691, doi:10.1175/2011JAMC2638.1. – reference: Welch, P. D. (1967), The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms, IEEE Trans. Audio Electroacoust., 15(2), 70-73, doi:10.1109/TAU.1967.1161901. – reference: Cuxart, J., et al. (2006), Single-column model intercomparison for a stably stratified atmospheric boundary layer, Boundary Layer Meteorol., 118, 273-303, doi:10.1007/s10546-005-3780-1. – reference: Thompson, G., R. M. Rasmussen, and K. Manning (2004), Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis, Mon. Weather Rev., 132, 519-542, doi:10.1175/1520-0493(2004)132<0519:EFOWPU>2.0.CO;2. – volume: 134 start-page: 2180 year: 2006 end-page: 2190 article-title: Enhanced detectability of added value in limited‐area model results separated into different spatial scales publication-title: Mon. Weather Rev. – volume: 18 start-page: 249 year: 2003 end-page: 263 article-title: Mesoscale model simulations of high‐wind events in the complex terrain of western Nevada publication-title: Weather Forecast. – volume: 133 start-page: 3368 year: 2005 end-page: 3381 article-title: Verification of temporal variations in mesoscale numerical wind forecasts publication-title: Mon. Weather Rev. – volume: 108 issue: D22 year: 2003 article-title: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model publication-title: J. Geophys. Res. – volume: 87 start-page: 1747 year: 2006 end-page: 1751 article-title: Research needs and directions of regional climate modeling using WRF and CCSM publication-title: Bull. Am. Meteorol. Soc. – volume: 116 start-page: 2417 year: 1988 end-page: 2424 article-title: Skill scores based on the mean square error and their relationships to the correlation coefficient publication-title: Mon. Weather Rev. – year: 2001 – volume: 132 start-page: 368 year: 2004 end-page: 389 article-title: Numerical simulations of the foehn in the Rhine valley on 24 October 1999 (MAP IOP 10) publication-title: Mon. Weather Rev. – volume: 128 start-page: 3664 year: 2000 end-page: 3673 article-title: A spectral nudging technique for dynamical downscaling purposes publication-title: Mon. Weather Rev. – volume: 34 start-page: 2246 year: 2009 end-page: 2251 article-title: Wind characteristics and wind energy potential in western Nevada publication-title: Renewable Energy – volume: 127 start-page: 308 year: 1999 end-page: 321 article-title: Long simulation of regional climate as a sequence of short segments publication-title: Mon. Weather Rev. – volume: 83 start-page: 699 year: 2002 end-page: 708 article-title: A climatological study of thermally driven wind systems if the U.S. intermountain west publication-title: Bull. Am. Meteorol. Soc. – volume: 126 start-page: 28 year: 1998 end-page: 52 article-title: Windstorms along the western side of the Washington Cascade Mountains. Part I: A high‐resolution observational and modeling study of the 12 February 1995 event publication-title: Mon. Weather Rev. – year: 1994 – volume: 95 start-page: 499 year: 2009 end-page: 521 article-title: Evaluation of a WRF dynamical downscaling simulation over California publication-title: Clim. Change – volume: 115 start-page: 763 year: 1989 end-page: 806 article-title: Estimation of skill and uncertainty in regional numerical models publication-title: Q. J. R. Meteorol. Soc. – volume: 23 start-page: 5041 year: 2010 end-page: 5064 article-title: Global distribution and characteristics of diurnally varying low‐level jets publication-title: J. Clim. – volume: 87 start-page: 343 year: 2006 end-page: 360 article-title: North American regional reanalysis publication-title: Bull. Am. Meteorol. Soc. – volume: 45 start-page: 63 year: 2006 end-page: 86 article-title: High‐resolution large‐eddy simulations of flow in a steep alpine valley. Part I: Methodology, verification, and sensitivity experiments publication-title: J. Appl. Meteorol. Climatol. – volume: 132 start-page: 2553 year: 2004 end-page: 2569 article-title: Predictability of low‐level winds by mesoscale meteorological models publication-title: Mon. Weather Rev. – year: 2008 – volume: 20 start-page: 851 year: 1982 end-page: 875 article-title: Development of a turbulence closure model for geophysical fluid problems publication-title: Rev. Geophys. – volume: 46 start-page: 3077 year: 1989 end-page: 3107 article-title: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two‐dimensional model publication-title: J. Atmos. Sci. – volume: 139 start-page: 101 year: 2006 end-page: 118 article-title: Regional climate modeling: Status and perspectives publication-title: J. Phys. IV – volume: 118 start-page: 273 year: 2006 end-page: 303 article-title: Single‐column model intercomparison for a stably stratified atmospheric boundary layer publication-title: Boundary Layer Meteorol. – volume: 102 start-page: 16,663 issue: D14 year: 1997 end-page: 16,682 article-title: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated‐k model for the longwave publication-title: J. Geophys. Res. – volume: 12 start-page: 81 year: 2009 end-page: 90 article-title: Evaluation of the Weather Research and Forecasting model on forecasting low‐level jets: Implications for wind energy publication-title: Wind Energy – volume: 49 start-page: 268 year: 2010 end-page: 287 article-title: Surface wind regionalization over complex terrain: Evaluation and analysis of a high‐resolution WRF simulation publication-title: J. Appl. Meteorol. Climatol. – volume: 133 start-page: 1371 year: 2007 end-page: 1388 article-title: Numerical simulation of pulsations in the bora wind publication-title: Q. J. R. Meteorol. Soc. – volume: 83 start-page: 407 year: 2002 end-page: 430 article-title: Does increasing horizontal resolution produce more skillful forecast? publication-title: Bull. Am. Meteorol. Soc. – volume: 15 start-page: 70 issue: 2 year: 1967 end-page: 73 article-title: The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms publication-title: IEEE Trans. Audio Electroacoust. – volume: 124 start-page: 1071 year: 1998 end-page: 1107 article-title: Explicit forecasting of supercooled liquid water in winter storms using the MM5 forecast model publication-title: Q. J. R. Meteorol. Soc. – volume: 49 start-page: 954 year: 2010 end-page: 972 article-title: A reanalysis system for the generation of mesoscale climatographies publication-title: J. Appl. Meteorol. Climatol. – volume: 61 start-page: 1816 year: 2004 end-page: 1826 article-title: Toward numerical modeling in the “terra incognita,” publication-title: J. Atmos. Sci. – year: 2007 – start-page: 165 year: 1993 end-page: 170 – year: 1996 – year: 2000 – volume: 43 start-page: 170 year: 2004 end-page: 181 article-title: The Kain‐Fritsch convective parameterization: An update publication-title: J. Appl. Meteorol. – volume: 78 start-page: 2599 year: 1997 end-page: 2617 article-title: A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction publication-title: Bull. Am. Meteorol. Soc. – volume: 113 year: 2008 article-title: Assessment of three dynamical climate downscaling methods using the Weather Research and Forecasting (WRF) model publication-title: J. Geophys. Res. – volume: 113 year: 2008 article-title: Dynamical downscaling: Assessment of model system dependent retained and added variability for two different regional climate models publication-title: J. Geophys. Res. – volume: 31 start-page: 1791 year: 1974 end-page: 1806 article-title: A hierarchy of turbulence closure models for planetary boundary layers publication-title: J. Atmos. Sci. – volume: 132 start-page: 519 year: 2004 end-page: 542 article-title: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis publication-title: Mon. Weather Rev. – volume: 37 start-page: 677 year: 2011 end-page: 688 article-title: Regional climate of hazardous convective weather through high‐resolution dynamical downscaling publication-title: Clim. Dyn. – volume: 19 start-page: 4308 year: 2006 end-page: 4325 article-title: Local regimes of atmospheric variability: A case study of Southern California publication-title: J. Clim. – volume: 131 start-page: 2857 year: 2003 end-page: 2874 article-title: Reinitialized versus continuous simulations for regional climate downscaling publication-title: Mon. Weather. Rev. – volume: 129 start-page: 2040 year: 2001 end-page: 2056 article-title: Marine atmospheric boundary layer divergence and clouds along California in June 1996 publication-title: Mon. Weather Rev. – volume: 89 start-page: 1513 year: 2008 end-page: 1533 article-title: The Terrain‐Induced Rotor Experiment: A field campaign overview including observational highlights publication-title: Bull. Am. Meteorol. Soc. – volume: 138 start-page: 4035 year: 2010 end-page: 4053 article-title: Multi‐reanalysis climatology of intermountain cyclones publication-title: Mon. Weather Rev. – volume: 50 start-page: 1676 year: 2011 end-page: 1691 article-title: Dynamical downscaling of wind speed in complex terrain prone to bora‐type flows publication-title: J. Appl. Meteorol. Climatol. – volume: 58 start-page: 445 year: 2006 end-page: 455 article-title: Validation of mesoscale low‐level winds obtained by dynamical downscaling of ERA‐40 over complex terrain publication-title: Tellus, Ser. A – volume: 113 start-page: 1050 year: 1985 end-page: 1065 article-title: A two‐step scheme for the advection equation with minimized dissipation and dispersion errors publication-title: Mon. Weather Rev. – volume: 129 start-page: 587 year: 2001 end-page: 604 article-title: Coupling an advanced land surface‐hydrology model with the Penn State–NCAR MM5 Modeling System. Part II: Preliminary model validation publication-title: Mon. Weather Rev. – volume: 120 start-page: 197 year: 1992 end-page: 207 article-title: The Euler equations of motion with hydrostatic pressure as an independent variable publication-title: Mon. Weather Rev. – ident: e_1_2_9_17_1 doi: 10.1175/2008BAMS2487.1 – ident: e_1_2_9_47_1 doi: 10.1175/1520‐0493(1985)113<1050:ATSSFT>2.0.CO;2 – ident: e_1_2_9_45_1 doi: 10.1175/1520‐0477(2002)083<0699:ACSOTD>2.3.CO;2 – ident: e_1_2_9_38_1 doi: 10.1175/1520‐0493(2003)131<2857:RVCSFR>2.0.CO;2 – ident: e_1_2_9_16_1 – ident: e_1_2_9_14_1 doi: 10.1175/MWR3183.1 – ident: e_1_2_9_23_1 doi: 10.1175/2010MWR3432.1 – ident: e_1_2_9_49_1 doi: 10.1007/s00382‐010‐0826‐y – ident: e_1_2_9_10_1 doi: 10.1175/JCLI3837.1 – ident: e_1_2_9_32_1 doi: 10.1175/1520‐0469(1974)031<1791:AHOTCM>2.0.CO;2 – ident: e_1_2_9_25_1 doi: 10.1175/1520‐0450(2004)043<0170:TKCPAU>2.0.CO;2 – ident: e_1_2_9_19_1 doi: 10.1175/2011JAMC2638.1 – ident: e_1_2_9_51_1 doi: 10.1175/1520‐0477(1997)078<2599:ATOLBC>2.0.CO;2 – ident: e_1_2_9_28_1 doi: 10.1175/1520‐0493(1992)120<0197:TEEOMW>2.0.CO;2 – ident: e_1_2_9_54_1 doi: 10.1175/1520‐0469(2004)061<1816:TNMITT>2.0.CO;2 – ident: e_1_2_9_29_1 doi: 10.1175/BAMS‐87‐12‐1747 – ident: e_1_2_9_13_1 doi: 10.1029/2002JD003296 – ident: e_1_2_9_44_1 – ident: e_1_2_9_46_1 doi: 10.1002/we.288 – ident: e_1_2_9_34_1 doi: 10.1175/BAMS‐87‐3‐343 – ident: e_1_2_9_43_1 doi: 10.1029/2007JD009461 – ident: e_1_2_9_6_1 doi: 10.1007/s10584‐009‐9583‐5 – ident: e_1_2_9_22_1 – ident: e_1_2_9_15_1 doi: 10.1051/jp4:2006139008 – ident: e_1_2_9_48_1 doi: 10.1175/1520‐0493(2004)132<0519:EFOWPU>2.0.CO;2 – ident: e_1_2_9_9_1 doi: 10.1175/1520‐0493(1998)126<0028:WATWSO>2.0.CO;2 – ident: e_1_2_9_35_1 doi: 10.1029/97JD00237 – ident: e_1_2_9_20_1 doi: 10.1017/CBO9780511546013 – ident: e_1_2_9_55_1 doi: 10.1111/j.1600-0870.2006.00186.x – ident: e_1_2_9_53_1 doi: 10.1093/oso/9780195132717.001.0001 – ident: e_1_2_9_27_1 doi: 10.1175/1520‐0493(2001)129<2040:MABLDA>2.0.CO;2 – ident: e_1_2_9_42_1 doi: 10.1175/2010JCLI3514.1 – ident: e_1_2_9_37_1 doi: 10.1175/1520‐0493(1999)127<0308:LSORCA>2.0.CO;2 – ident: e_1_2_9_52_1 doi: 10.1109/TAU.1967.1161901 – ident: e_1_2_9_2_1 doi: 10.1002/qj.49711548803 – ident: e_1_2_9_18_1 doi: 10.1175/2009JAMC2351.1 – ident: e_1_2_9_56_1 doi: 10.1175/1520‐0493(2004)132<0368:NSOTFI>2.0.CO;2 – ident: e_1_2_9_4_1 doi: 10.1002/qj.129 – ident: e_1_2_9_33_1 doi: 10.1029/RG020i004p00851 – ident: e_1_2_9_40_1 doi: 10.1175/MWR3052.1 – ident: e_1_2_9_21_1 – ident: e_1_2_9_31_1 doi: 10.1175/1520‐0477(2002)083<0407:DIHRPM>2.3.CO;2 – ident: e_1_2_9_5_1 doi: 10.1175/1520‐0434(2003)018<0249:MMSOHE>2.0.CO;2 – ident: e_1_2_9_11_1 doi: 10.1007/s10546‐005‐3780‐1 – ident: e_1_2_9_7_1 doi: 10.1175/1520‐0493(2001)129<0587:CAALSH>2.0.CO;2 – ident: e_1_2_9_8_1 doi: 10.1175/JAM2322.1 – ident: e_1_2_9_26_1 doi: 10.1007/978-1-935704-13-3_16 – ident: e_1_2_9_36_1 doi: 10.1175/1520‐0493(1988)116<2417:SSBOTM>2.0.CO;2 – ident: e_1_2_9_30_1 doi: 10.1029/2007JD009216 – ident: e_1_2_9_41_1 doi: 10.1175/MWR2801.1 – ident: e_1_2_9_3_1 doi: 10.1016/j.renene.2009.02.024 – ident: e_1_2_9_39_1 doi: 10.1002/qj.49712454804 – ident: e_1_2_9_50_1 doi: 10.1175/1520‐0493(2000)128<3664:ASNTFD>2.0.CO;2 – ident: e_1_2_9_12_1 doi: 10.1175/1520‐0469(1989)046<3077:NSOCOD>2.0.CO;2 – ident: e_1_2_9_24_1 doi: 10.1175/2009JAMC2175.1 |
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Snippet | Sub‐kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were... Sub-kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were... |
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SubjectTerms | Accuracy Atmospheric boundary layer Atmospheric sciences Boundary conditions Climate models Climate science Daytime Dispersion Diurnal Domains dynamical downscaling Earth sciences Earth, ocean, space Eddies Errors Exact sciences and technology Frequencies Geophysics Kinetic energy Mean winds Mesoclimatology Mesoscale models Mesoscale phenomena Mixed layer MM5 Model accuracy Modelling moment-based verification Physics Resolution Spectra spectral verification Summer Surface wind Telescoping Temporal variability Temporal variations Terrain Verification Vertical wind shear Weather forecasting Wind shear Wind speed Winds WRF |
Title | Sub-kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models |
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