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A Description of the Advanced Research WRF Version 2
Open accessAbstract
The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Di-visions; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: EDD: Engineering, Design, or Development Reports Equipment descriptions, test results, instrumentation, and operating and maintenance manuals. IA: Instructional Aids Instruction manuals, bibliographies, film supplements, and other research or instructional aids. PPR: Program Progress Reports Field program reports, interim and working reports, survey reports, and plans for experiments. PROC: Proceedings Documentation of symposia, colloquia, conferences, workshops, and lectures. (Distribution may be limited to attendees.) STR: Scientific and Technical Reports Data compilations, theoretical and numerical investigations, and experimental results. The National Center for Atmospheric Research (NCAR) is operated by the University Corpora-tion for Atmospheric Research (UCAR) and is sponsored by the National Science Foundation. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Hernández-Ceballos, M., Skjøth, C., García-Mozo, H., Bolívar, J., & Galán, C. (2014) · International journal of biometeorology · doi:10.1007/s00484-014-0804-x · Cited by 55
“To meet this aim, this work compares trajectories obtained with HYSPLIT by using three high-resolution outputs from the mesoscale Weather Research and Forecasting (WRF-ARW) model (Skamarock et al. 2005) and GDAS datasets.”
MethodHernández-Ceballos, M., Adame, J., Bolívar, J., & de la Morena, B. A. (2013) · doi:10.1016/j.atmosres.2012.12.002 · Cited by 55
Zupanski, D., Zhang, S. Q., Zupanski, M., Hou, A., & Cheung, S. (2011) · doi:10.1175/2010jhm1271.1 · Cited by 55
“WRF-EDAS consists of the following components: (i) the Advanced Research WRF model (ARW-WRF; Skamarock et al. 2005), with NASA Goddard cloud microphysics and radiation schemes (GCE; Tao 2003); (ii) precipitation-affected radiance transfer models from NASA Goddard Satellite Data Simulation Unit…”
MethodEnsemble-Based Sensitivity Analysis Applied to African Easterly Waves
Torn, R. (2010) · doi:10.1175/2009waf2222255.1 · Cited by 55
A polarimetric radar forward operator for model evaluation
Pfeifer, M., Craig, G., Hagen, M., & Keil, C. (2008) · doi:10.1175/2008jamc1793.1 · Cited by 55
“…the nonhydrostatic weather forecasting model of the consortium for smallscale modeling (COSMO-DE; Steppeler et al. 2003), the French model Application of Research to Operations in Mesoscale (AROME; Ducrocq et al. 2005), and the American Weather Research and Forecasting (WRF; Skamarock et al. 2005).”
MethodShafer, C., Mercer, A., Doswell, C., Richman, M., & Leslie, L. (2008) · doi:10.1175/2008mwr2597.1 · Cited by 55
“Grell‐Devenyi convective scheme; not used for D04 and D05 Grell and Devenyi (2002) Yonsei University planetary boundary layer scheme Hong and Pan (1996) MM5-derived surface layer scheme Skamarock et al. (2005) Five-layer thermal diffusion land surface model Skamarock et al. (2005) Rapid radiative transfer model for lo…”
MethodInfluentialClark, A. J., Gallus, W. A., & Chen, T.-C. (2008) · Monthly Weather Review · doi:10.1175/2007mwr2029.1 · Cited by 48
“The Advanced Research WRF (ARW) dynamic core (Wicker and Skamarock 2002; Skamarock et al. 2005) was used in six of the MP members and the Nonhydrostatic Mesoscale Model (NMM) dynamic core (Janjić 2003) was used in two of the MP members.”
MethodOptimization Of The Issuance Of Evacuation Orders Under Evolving Hurricane Conditions
Yi, W., Nozick, L., Davidson, R., Blanton, B., & Colle, B. (2017) · doi:10.1016/j.trb.2016.10.008 · Cited by 55
Prakash, K., & Pant, V. (2016) · Deutsche Hydrographische Zeitschrift · doi:10.1007/s10236-016-1020-5 · Cited by 55
“…WRF-ARW (WRF version 3.7.1) is a non-hydrostatic, fully compressible atmospheric model with boundary layer physics schemes and a variety of physical parameterizations of sub-grid-scale processes for predicting mesoscales and microscales of motion (Skamarock et al. 2005; Skamarock and Klemp 2008).”
BackgroundInfluentialClimate Change and Heat-Related Excess Mortality in the Eastern USA
Limaye, V. S., Vargo, J., Harkey, M., Holloway, T., & Patz, J. A. (2018) · EcoHealth · doi:10.1007/s10393-018-1363-0 · Cited by 54
“The particular model combination and future year applied here is the warmest future summer simulated by the WRF-CCSM combination, a model pairing which best represented past conditions (Harkey and Holloway 2013; Abel et al. 2018).”
InfluentialKim, M.-K., Yang, H., & Kim, J.-H. (2020) · Remote Sensing · doi:10.3390/rs12213654 · Cited by 60
Velasquez, P., Messmer, M., & Raible, C. C. (2020) · Geoscientific model development · doi:10.5194/gmd-13-5007-2020 · Cited by 72
Modeling the urban heat island mitigation effect of cool coatings in realistic urban morphology
Liu, N.-R., & Morawska, L. (2020) · doi:10.1016/j.jclepro.2020.121560 · Cited by 54
Davidson, R. A., Nozick, L. K., Wachtendorf, T., Blanton, B., Colle, B. A., Kolar, R. L., DeYoung, S. E., Dresback, K. M., Yi, W., Yang, K., et al. (2018) · Risk Analysis · doi:10.1111/risa.12990 · Cited by 55
“An ensemble of hurricane scenarios is generated using the Weather and Research Forecasting (WRF) meso-scale meteorological model (Skamarock et al., 2007).”
MethodTheobald, M., Vivanco, M. G., Aas, W., Andersson, C., Ciarelli, G., Couvidat, F., Cuvelier, K., Manders, A., Mircea, M., Pay, M., et al. (2018) · Atmospheric Chemistry and Physics · doi:10.5194/acp-19-379-2019 · Cited by 54
“, 2015) by the Weather Research and Forecast (WRF) model (Skamarock et al., 2005) at a spatial resolution of 0.”
BackgroundInfluentialSathyanadh, A., Prabha, T. V., Balaji, B., Resmi, E. A., & Karipot, A. (2017) · Atmospheric Research · doi:10.1016/j.atmosres.2017.02.016 · Cited by 53
Eriksson, O., Lindvall, J., Breton, S., & Ivanell, S. (2015) · doi:10.1088/1742-6596/625/1/012028 · Cited by 54
Mesoscale Data Assimilation for a Local Severe Rainfall Event with the NHM–LETKF System
Kunii, M. (2013) · Weather and Forecasting · doi:10.1175/waf-d-13-00032.1 · Cited by 55
“Miyoshi and Kunii (2012) developed the LETKF with the Weather Research and Forecasting (WRF) Model (Skamarock et al. 2005) and conducted data assimilation experiments for Typhoon Sinlaku of September 2008.”
MethodWyszogrodzki, A., Liu, Y.-B., Jacobs, N., Childs, P. P., Zhang, Y.-X., Roux, G., & Warner, T. (2013) · Meteorology and atmospheric physics (Print) · doi:10.1007/s00703-013-0281-5 · Cited by 54
“For example, Cheng and Steenburgh (2005) and Molders (2008) showed a general tendency of the WRF model (Skamarock et al. 2005) to overestimate the 10-m wind speed over the western part of US and Alaska, respectively.”
BackgroundMethodFritz, C., & Wang, Z. (2013) · doi:10.1175/jas-d-13-0378.1 · Cited by 54
“a. Numerical model simulation description The model used in this study is the Advanced Research Weather Research and Forecasting (ARWWRF) Model, version 3.2.1 (Skamarock et al. 2005).”
MethodInfluentialLunde, T. M., Korecha, D., Loha, E., Sorteberg, A., & Lindtjørn, B. (2013) · Malaria Journal · doi:10.1186/1475-2875-12-28 · Cited by 56
Steeneveld, G., Tolk, L., Moene, A., Hartogensis, O., Peters, W., & Holtslag, A. (2011) · Journal of Geophysical Research Atmospheres · doi:10.1029/2011jd016303 · Cited by 54
Extreme rainfall and flooding from orographic thunderstorms in the central Appalachians
Smith, J. A., Baeck, M. L., Ntelekos, A. A., Villarini, G., & Steiner, M. (2011) · Water Resources Research · doi:10.1029/2010wr010190 · Cited by 65
“Ntelekos et al. [2008] carried out simulations of orographic thunderstorm systems that produced flash floods along the eastern United States, and we adopt similar model implementations in this study, on the basis of the Advanced Research version (2.2) of WRF [see Skamarock et al., 2007].”
MethodInfluentialYerramilli, A., Dodla, V., Challa, V., Myles, L., Pendergrass, W., Vogel, C., Dasari, H., Tuluri, F., Baham, J. M., Hughes, R. L., et al. (2011) · Air quality, atmosphere and health · doi:10.1007/s11869-010-0132-1 · Cited by 54
A model study on the influence of overshooting convection on TTL water vapour
Hassim, M., & Lane, T. (2010) · Atmospheric chemistry and physics · doi:10.5194/acp-10-9833-2010 · Cited by 54
“A full description of specific model details can be found inSkamarock et al. (2005). Because of its nonhydrostatic formulation, the WRF model is suitable for simulations that require grid spacings on the order of 250–1000 m to explicitly represent convection and clouds.”
MethodSchürmann, G., Algieri, A., Hedgecock, I., Manna, G., Pirrone, N., & Sprovieri, F. (2009) · doi:10.1016/j.atmosenv.2009.06.017 · Cited by 54
Hara, M., Takao, Y., Takahashi, H. G., Kimura, F., Noda, A., & Tokioka, T. (2009) · Journal of the Meteorological Society of Japan Ser II · doi:10.2151/jmsj.87a.413 · Cited by 54
Ou, T., Chen, D. L., Tang, J.-P., Lin, C.-G., Wang, X.-J., Kukulies, J., & Lai, H. (2023) · Climate Dynamics · doi:10.1007/s00382-023-06672-3 · Cited by 53
Evaluating fire growth simulations using satellite active fire data
Sá, A. C. L., Benali, A., Fernandes, P. M., Pinto, R. M. S., Trigo, R. M., Salis, M., Russo, A., Jerez, S., Soares, P. M. M., Schroeder, W., et al. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.12.023 · Cited by 59
Casanueva, A., Herrera, S., Fernández, J., & Gutiérrez, J. (2016) · Climatic Change · doi:10.1007/s10584-016-1683-4 · Cited by 53
The Potential Impact of Regional Climate Change on Fire Weather in the United States
Tang, Y., Zhong, S., Luo, L.-F., Bian, X., Heilman, W., & Winkler, J. (2015) · doi:10.1080/00045608.2014.968892 · Cited by 53
“…set of RCMs used in this study includes the Canadian Regional Climate Model (CRCM; Laprise et al. 1998; Caya and Laprise 1999), the Weather Research and Forecasting Grell model (WRFG; Grell and Devenyi 2002; Skamarock et al. 2005), and the Regional Climate Model version 3 (RCM3; Pal et al. 2007).”
BackgroundMethodJohnson, A., Wang, X.-G., Xue, M., Kong, F., Zhao, G., Wang, Y., Thomas, K., Brewster, K., & Gao, J.-D. (2014) · doi:10.1175/mwr-d-13-00204.1 · Cited by 53
“The control forecast ICs were obtained from the operational National Centers for Environmental Prediction (NCEP) North American Mesoscale Model (NAM) 0000 UTC NAM Data Assimilation System (NDAS; Rogers et al. 2009) analysis at 12-km grid spacing, interpolated to the 4-km WRF grid.”
MethodInfluentialSturtevant, B., Achtemeier, G., Charney, J., Anderson, D., Cooke, B., & Townsend, P. (2013) · doi:10.1016/j.agrformet.2012.09.008 · Cited by 53
“…conditions representing the time of the first moth collection (21 June–29 June 2007), using the Weather Research and Forecasting Model (WRF v3, Skamarock et al., 2005), to provide the weather inputs required to drive the SBW atmospheric transport model, following parameterizations listed in…”
BackgroundMethodInfluentialJohnson, A., Wang, X.-G., Xue, M., & Kong, F. (2011) · doi:10.1175/mwr-d-11-00016.1 · Cited by 53
“The ensemble consists of 20 members, with 10 members from the Advanced Research Weather Research and Forecasting model (ARW-WRF; Skamarock et al. 2005), 8 members from the WRF Nonhydrostatic Me-soscale Model (NMM; Janjic´ 2003), and 2 members from the CAPS Advanced Regional Prediction System (ARPS;…”
BackgroundSchultz, D., & Knox, J. (2007) · doi:10.1175/mwr3400.1 · Cited by 53
“A real-time Weather Research and Forecasting model (WRF; Skamarock et al. 2005) forecast performed by the National Center for Atmospheric Research Mesoscale and Microscale Meteorology Division also produced banded convection for this event (Fig.”
MethodYesubabu, V., Srinivas, C., Langodan, S., & Hoteit, I. (2016) · Quarterly Journal of the Royal Meteorological Society · doi:10.1002/qj.2654 · Cited by 53
“Simulations were conducted with the Advanced Research WRF (ARW) model (Skamarock et al., 2008) version 3.”
MethodInfluentialAtmospheric Variability and Infrasound Monitoring
de Groot-Hedlin, C., Hedlin, M., & Drob, D. (2010) · Springer eBooks · doi:10.1007/978-1-4020-9508-5_15 · Cited by 53
“…Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS) (Hodur 1997), the NOAA rapid update cycle (RUC) (Benjamin et al. 2004), and the Weather Research and Forecasting (WRF) system (Skamarock et al. 2005) are receiving much attention by the operational and atmospheric research communities.”
MethodWeather regimes and orographic circulation around New Caledonia.
Lefèvre, J., Marchesiello, P., Jourdain, N., Menkes, C., & Leroy, A. (2010) · Marine Pollution Bulletin · doi:10.1016/j.marpolbul.2010.06.012 · Cited by 53
Effects of wave-current interaction on the Pearl River Estuary during Typhoon Hato
Chen, Y., Chen, L., Zhang, H., & Gong, W.-P. (2019) · Estuarine, Coastal and Shelf Science · doi:10.1016/j.ecss.2019.106364 · Cited by 52
Open source QGIS toolkit for the Advanced Research WRF modelling system
Meyer, D., & Riechert, M. (2019) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2018.10.018 · Cited by 52
“WRF has been developed under two variants, found in its two fluid-flow solvers, or dynamical cores: the Advanced Research WRF (ARW) core (Skamarock et al., 2008, 2005), and the Non-hydrostatic Mesoscale Model (NMM) core (Janjić, 2003; Janjić et al., 2001) whose support has recently ended…”
BackgroundTasnim, K. M., Shibayama, T., Esteban, M., Takagi, H., Ohira, K., & Nakamura, R. (2014) · Natural Hazards · doi:10.1007/s11069-014-1387-x · Cited by 61
“A detailed description of WRF (ARW) was provided by Skamarock et al. (2005).”
MethodThe Development of a Hybrid EnKF-3DVAR Algorithm for Storm-Scale Data Assimilation
Gao, J., Xue, M., & Stensrud, D. J. (2013) · Advances in Meteorology · doi:10.1155/2013/512656 · Cited by 58
Oh, Kyung-Hee, Lee, Seok, Song, Kyu-Min, Lie, Heung-Jae, Kim, & Young-Taeg (2013) · Acta Oceanologica Sinica · doi:10.1007/s13131-013-0346-9 · Cited by 52
Using Frontogenesis to Identify Sting Jets in Extratropical Cyclones
Schultz, D., & Sienkiewicz, J. (2013) · doi:10.1175/waf-d-12-00126.1 · Cited by 52
“To diagnose the origin of these strong winds in the lower troposphere, an Advanced Research Weather Research and Forecasting Model (WRF-ARW; Skamarock et al. 2005) simulation starting at 1200 UTC 7 December was performed.”
MethodHernández-Ceballos, M., García-Mozo, H., Adame, J., Domínguez-Vilches, E., Bolívar, J., de la Morena, B. A., Pérez-Badía, R., & Galán, C. (2011) · doi:10.1007/s10453-011-9195-1 · Cited by 52
“Several numerical models such as FLEXPART (Stohl et al. 1998) and WRF (Skamarock et al. 2005) have been developed for the computation of back trajectories.”
MethodStudy on a mesoscale convective vortex causing heavy rainfall during the mei-yu season in 2003
Sun, J.-H., Zhao, S.-X., Xu, G.-K., & Meng, Q.-T. (2010) · doi:10.1007/s00376-009-9156-6 · Cited by 52
“research and operational models ( Skamarock et al., 2005 ).”
Lagrangian Coherent Structures near a Subtropical Jet Stream
Tang, W.-B., Mathur, M., Haller, G., Hahn, D., & Ruggiero, F. (2010) · doi:10.1175/2010jas3176.1 · Cited by 52
“The atmospheric dataset analyzed here was generated by the WRF modeling system using the Advanced Research WRF (ARW) version 2 dynamics solver core (Skamarock et al. 2005).”
MethodLi, X.-L., & Pu, Z. (2009) · doi:10.2151/jmsj.87.403 · Cited by 52
“A series of numerical simulations is conducted with the ARW model to examine the impact of cumulus and PBL schemes on the numerical simulations of Hurricane Emily (2005)’s early rapid intensification.”
MethodInfluentialHu, J.-L., Ying, Q., Chen, J., Mahmud, A., Zhao, Z., Chen, S.-H., & Kleeman, M. (2010) · doi:10.1016/j.atmosenv.2009.10.011 · Cited by 52
“Model predictions for PM species were then compared to ambient measurements in the heavily polluted San Joaquin Valley (SJV).”
BackgroundMethodInfluentialAlonso-González, E., López-Moreno, J., Gascoin, S., Ojeda, M. G., Sanmiguel‐Vallelado, A., Navarro‐Serrano, F., Revuelto, J., Ceballos, A., Esteban-Parra, M. J., & Essery, R. (2017) · doi:10.5194/essd-10-303-2018 · Cited by 51
“They coupled outputs from the Weather Research and Forecasting (WRF) model (Skamarock et al., 2008) driven by NCEP/NCAR reanalysis with a temperature index model (based on remote sensing), and their results had low error values.”
MethodSperati, S., Alessandrini, S., Pinson, P., & Kariniotakis, G. (2015) · Energies · doi:10.3390/en8099594 · Cited by 52
“For Catania, the participant with the second best result (i.e., id09) combined the output of the RAMS model provided by COST with the WRF ARW [32] model, initialized with boundary conditions from GFS.”
MethodFountoukis, C., Riipinen, I., van der Gon, H. D., Charalampidis, P., Pilinis, C., Wiedensohler, A., O'Dowd, C., Putaud, J., Moerman, M., & Pandis, S. (2012) · doi:10.5194/acp-12-8663-2012 · Cited by 51
“Each layer of PMCAMx-UF is aligned with the layers used in WRF.”
MethodInfluentialCarter, M., Shepherd, J. M., Burian, S., & Jeyachandran, I. (2012) · doi:10.1175/2011jtecha1524.1 · Cited by 51
“The ARW dynamic core is designed to integrate the compressible, nonhydrostatic Euler equations using a terrain-following mass vertical coordinate (Skamarock et al. 2005) and is structured to perform case studies based on real input data.”
MethodWoźniak, B., Bradtke, K., Darecki, M., Dera, J., Dudzińska‐Nowak, J., Dzierzbicka-Głowacka, L., Ficek, D., Furmanczyk, K. K., Kowalewski, M., Krężel, A., et al. (2011) · Oceanologia · doi:10.5697/oc.53-4.897 · Cited by 56
“In subsequent stages it is planned to implement local applications of the WRF model (Skamarock et al. 2008) especially for the requirements of the SatBałtyk project.”
MethodLakshmi, V., Hong, S., Small, E., & Chen, F. (2011) · doi:10.2166/nh.2011.071 · Cited by 51
“The Weather Research and Forecasting (WRF) model, a successor of the MM5 with the model coupling technique, is a mesoscale model for numerical weather forecasting and data assimilation system (Skamarock et al. 2005).”
MethodThe New York Bight Jet: Climatology and Dynamical Evolution
Colle, B., & Novak, D. (2010) · doi:10.1175/2009mwr3231.1 · Cited by 51
“2; Skamarock et al. 2005) was used to provide additional data for diagnosing the structural evolution and dynamics of the NYB jet.”
MethodThe Role of Momentum Transport in the Motion of a Quasi-Idealized Mesoscale Convective System
Mahoney, K., Lackmann, G., & Parker, M. (2009) · doi:10.1175/2009mwr2895.1 · Cited by 51
Tan, C.-Y., & Fang, W. (2018) · International Journal of Disaster Risk Science · doi:10.1007/s13753-018-0161-1 · Cited by 50
“Although numerical models, such as the Weather Research and Forecasting (WRF) model (Skamarock et al. 2005; Nolan et al. 2009), have been”
MethodImproving PM2.5 Air Quality Model Forecasts in China Using a Bias-Correction Framework
Lyu, B., Zhang, Y., & Hu, Y. (2017) · Atmosphere · doi:10.3390/atmos8080147 · Cited by 47
“1) [32] and an emissions proc ssi g compon nt.”
BackgroundWind farm simulations using an overset hp-adaptive approach with blade-resolved turbine models
Kirby, A. C., Brazell, M. J., Yang, Z., Roy, R., Ahrabi, B. R., Mavriplis, D., Sitaraman, J., & Stoellinger, M. (2017) · The international journal of high performance computing applications · doi:10.1177/1094342019832960 · Cited by 50
“The coupler incorporates a choice of two atmospheric solvers: the National Center for Atmospheric Research’s (NCAR) Weather Research and Forecasting (WRF) (Skamarock et al., 2005) model and the National Renewable Energy Laboratory’s (NREL) Simulation fOr Wind Farm Applications (SOWFA) (Churchfield et al.”
MethodImpacts of Anthropogenic Heat on Summertime Rainfall in Beijing
Nie, W.-S., Zaitchik, B., Ni, G., & Sun, T. (2017) · doi:10.1175/jhm-d-16-0173.1 · Cited by 50
“Modeling studies that have accounted for Q F have found that including AH improves the simulation of urban temperatures when compared to available observations (Benson-Lira et al. 2016; Best and Grimmond 2016; Chen et al. 2016; Yu et al. 2014).”
InfluentialGoldberg, D., Vinciguerra, T., Anderson, D., Hembeck, L., Canty, T., Ehrman, S., Martins, D., Stauffer, R., Thompson, A. M., Salawitch, R., et al. (2016) · Geophysical Research Letters · doi:10.1002/2015gl067332 · Cited by 50
Bridging InSAR and GPS Tomography: A New Differential Geometrical Constraint
Benevides, P., Nico, G., Catalao, J. P. S., & Miranda, P. (2016) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2015.2463263 · Cited by 50
“Weather Research and Forecasting (WRF) model [21] simulations were used to assess the results of the GPS tomography.”
MethodA non-linear least squares enhanced POD-4DVar algorithm for data assimilation
Tian, X., & Feng, X. (2015) · Tellus A Dynamic Meteorology and Oceanography · doi:10.3402/tellusa.v67.25340 · Cited by 63
Applying a mesoscale atmospheric model to Svalbard glaciers
Claremar, B., Obleitner, F., Reijmer, C., Pohjola, V., Waxegård, A., Karner, F., & Rutgersson, A. (2012) · Advances in Meteorology · doi:10.1155/2012/321649 · Cited by 50
“WRF is an advanced mesoscale atmospheric model and is capable to simulate atmospheric processes with high spatial and temporal resolution [33, 34].”
BackgroundCha, D., Jin, C., Lee, D.-K., & Kuo, Y. (2011) · doi:10.1029/2010jd015069 · Cited by 50
Lemone, M., Chen, F., Tewari, M., Dudhia, J., Geerts, B., Miao, Q., Coulter, R., & Grossman, R. (2010) · doi:10.1175/2009mwr3004.1 · Cited by 50
“The numerical simulations use the Advanced Research Weather Research and Forecasting (ARW-WRF) model (Skamarock et al. 2005), coupled to the Noah land surface model (LSM), which was initialized using the National Center for Atmospheric Research (NCAR) High-Resolution Land Data Assimilation System…”
MethodSelf-citationRahn, D. A., & Garreaud, R. (2009) · doi:10.5194/acp-10-4507-2010 · Cited by 50
Chemel, C., Russo, M. R., Pyle, J., Sokhi, R., & Schiller, C. (2009) · Monthly Weather Review · doi:10.1175/2008mwr2666.1 · Cited by 50
“In the present paper, we discuss results from the Advanced Research Weather Research and Forecasting (ARW) model (Skamarock et al. 2007) and the Met Office UM (Davies et al.”
MethodTelescoping, multimodel approaches to evaluate extreme convective weather under future climates
Trapp, R., Halvorson, B. A., & Diffenbaugh, N. (2007) · Journal of Geophysical Research Atmospheres · doi:10.1029/2006jd008345 · Cited by 50
Windborne debris risk analysis - Part II. Application to structural vulnerability modeling
Lin, N., Vanmarcke, E., & Yau, S.-C. (2010) · doi:10.12989/was.2010.13.2.207 · Cited by 50
Martian atmospheric collapse: Idealized GCM studies
Soto, A., Mischna, M., Schneider, T., Lee, C., & Richardson, M. (2015) · Icarus · doi:10.1016/j.icarus.2014.11.028 · Cited by 49
Suh, M., Oh, S., Lee, Y.-S., Ahn, J., Cha, D., Lee, D., Hong, S., Min, S., Park, S., & Kang, H. (2016) · Asia-Pacific Journal of Atmospheric Sciences · doi:10.1007/s13143-016-0017-9 · Cited by 57
“The WRF Model version 3.4 used in this study was developed by NCAR (Skamarock et al., 2005).”
MethodInfluentialLin, C.-Y., Su, C.-J., Kusaka, H., Akimoto, Y., Sheng, Y.-F., Huang, J.-C., & Hsu, H. (2015) · doi:10.5194/acp-16-1809-2016 · Cited by 49
Spatial distribution of thermodynamic conditions of severe storms in southwestern Europe
Gascón, E., Merino, A., Sánchez, J., Fernández-González, S., García-Ortega, E., López, L., & Hermida, L. (2015) · doi:10.1016/j.atmosres.2015.05.012 · Cited by 49
Chevuturi, A., Dimri, A. P., Das, S., Kumar, A., & Niyogi, D. (2015) · Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences · doi:10.1007/s12040-015-0622-5 · Cited by 49
Rayner, P., Utembe, S., & Crowell, S. (2014) · Atmospheric measurement techniques · doi:10.5194/amt-7-3285-2014 · Cited by 49
“The Weather Research and Forecasting (WRF) (Skamarock et al., 2005) www.atmos-meas-tech.net/7/3285/2014/ Atmos.”
BackgroundInfluentialHeat wave hazard classification and risk assessment using artificial intelligence fuzzy logic
Keramitsoglou, I., Kiranoudis, C. T., Maiheu, B., Ridder, K. D., Daglis, I. A., Manunta, P., & Paganini, M. (2013) · Environmental Monitoring and Assessment · doi:10.1007/s10661-013-3170-y · Cited by 47
Peterson, D., & Wang, J. (2013) · doi:10.1016/j.rse.2012.10.020 · Cited by 49
“…downscaled onto a 10 km grid with one-hour temporal resolution by the Weather Research and Forecasting (WRF) model (e.g. Grell et al., 2005; Skamarock et al., 2005; Wang et al., in press), and the MODIS fire observations, including the sub-pixel output, were geographically matched to the…”
MethodSingh, R., Kishtawal, C., Pal, P., & Joshi, P. (2011) · doi:10.1007/s00703-011-0127-y · Cited by 49
Takahashi, H. G., Yoshikane, T., Hara, M., Takata, K., & Yasunari, T. (2010) · International Journal of Climatology · doi:10.1002/joc.2119 · Cited by 48
“The advanced weather research and forecasting (WRF) modelling system (Skamarock et al., 2005), which is a nonhydrostatic RCM developed by the National Center for Atmospheric Research (NCAR), was chosen for this purpose.”
MethodChou, K.-H., & Wu, C.-C. (2008) · doi:10.1175/2007mwr2141.1 · Cited by 49
“Work is ongoing for all real-time cases of the future DOTSTAR program using the newly developed WRF ( Skamarock et al. 2005 ) model.”
MethodInfluentialEnd-to-end I/O Monitoring on Leading Supercomputers
Yang, B., Xue, W., Zhang, T., Liu, S.-C., Ma, X.-S., Wang, X., & Liu, W. (2022) · ACM Transactions on Storage · doi:10.1145/3568425 · Cited by 48
“In this sample execution, AWP co-runs with the weather forecast application WRF [69] using the 1:1 mode, each having 1024 processes on 256 compute nodes.”
MethodSpatial and temporal variability of turbulence dissipation rate in complex terrain
Bodini, N., Lundquist, J., Krishnamurthy, R., Pekour, M., Berg, L., & Choukulkar, A. (2019) · Atmospheric Chemistry and Physics · doi:10.5194/acp-19-4367-2019 · Cited by 48
“…(Yang et al., 2017; Berg et al., 2019) showed that up to 50% of the variance in the turbine-height wind speed predicted by the Weather Research and Forecasting model (Skamarock et al., 2005) in complex terrain only depends on the accuracy of the parametrization of turbulence10 dissipation rate.”
BackgroundSatellite-based PM2.5 estimation using fine-mode aerosol optical thickness over China
Yan, X., Shi, W.-Z., Li, Z., Li, Z.-Q., Luo, N., Zhao, W.-J., Wang, H.-F., & Yu, X. (2017) · doi:10.1016/j.atmosenv.2017.09.023 · Cited by 48
“The WRF model is a mesoscale numerical weather prediction system that has been validated for producing accurate simulation of meteorological data (Skamarock et al., 2005; Grguric et al., 2014).”
MethodZhao, C., Leung, L., Park, S.-H., Hagos, S., Lu, J., Sakaguchi, K., Yoon, J.-H., Harrop, B., Skamarock, W., & Duda, M. (2016) · Journal of Advances in Modeling Earth Systems · doi:10.1002/2016ms000727 · Cited by 48
Self-citationSimulating Titan’s methane cycle with the TitanWRF General Circulation Model
Newman, C. E., Richardson, M. I., Lian, Y., & Lee, C. (2015) · Icarus · doi:10.1016/j.icarus.2015.11.028 · Cited by 54
“The TitanWRF GCM is the Titan version of the planetWRF GCM (version 3.0.1.2) developed from the terrestrial Weather, Research and Forecasting (WRF) model (Skamarock et al., 2005).”
MethodInfluentialThe Effects of Highly Detailed Urban Roughness Parameters on a Sea-Breeze Numerical Simulation
Varquez, A. C., Nakayoshi, M., & Kanda, M. (2015) · Boundary-layer Meteorology · doi:10.1007/s10546-014-9985-4 · Cited by 48
How to construct future IDF curves, under changing climate, for sites with scarce rainfall records?
Liew, S., Raghavan, S., & Liong, S. (2014) · doi:10.1002/hyp.9839 · Cited by 48
“This model has also been described and documented by Skamarock et al., 2005, and detailed information can be found at: http:/www. wrf-model.org.”
MethodYucel, I., & Onen, A. (2014) · Natural hazards and earth system sciences · doi:10.5194/nhess-14-611-2014 · Cited by 48
“The Weather Research and Forecasting (WRF) model (Skamarock et al., 2005) of mesoscale NWP system that incorporates advanced numeric and data assimilation techniques (3DVAR), a multiple nesting capability, and numerous stateof-the-art physics options is suitable for extreme weather applications in…”
BackgroundZhang, Y.-C., Sun, J.-H., & Fu, S. (2014) · Advances in Atmospheric Sciences · doi:10.1007/s00376-013-2052-0 · Cited by 48
“The Weather Research and Forecasting (WRF) model, version 3.2 (Skamarock et al., 2005), was used for the current reported study.”
MethodInfluentialGe, Q., Zhang, X., & Zheng, J.-Y. (2014) · doi:10.1002/joc.3677 · Cited by 48
“(2009) and Wu et al. (2011), both of which illustrated warming effects of increased vegetation.”
InfluentialYuan, C., & Ng, E. (2013) · Urban Climate · doi:10.1016/j.uclim.2013.12.001 · Cited by 48
“WRF, as the next-generation prognostic weather model, is currently very popular and is increasingly being applied in urban environment research by coupling with the data set of the urban morphology (Chen et al., 2011).”
BackgroundSobash, R. A., & Stensrud, D. J. (2013) · Monthly Weather Review · doi:10.1175/mwr-d-12-00203.1 · Cited by 65
“The ARW-WRF was integrated as a cloud model with WRF single-moment 6-class microphysics scheme (WSM6; Hong and Lim 2006), open-boundary conditions, no terrain, surface physics, or boundary layer physics.”
MethodCheng, C. K., & Chan, J. (2012) · doi:10.1016/j.atmosenv.2012.06.019 · Cited by 48
“The WRF model is a non-hydrostatic model with a masscoordinate system (Skamarock et al., 2005).”
MethodA ‘hurricane‐like’ polar low fuelled by sensible heat flux: high‐resolution numerical simulations
Føre, I., Kristjánsson, J., Kolstad, E. W., Bracegirdle, T., Saetra, Ø., & Røsting, B. (2012) · doi:10.1002/qj.1876 · Cited by 48
Coastal landfast sea ice decay and breakup in northern Alaska: Key processes and seasonal prediction
Petrich, C., Eicken, H., Zhang, J., Krieger, J., Fukamachi, Y., & Ohshima, K. (2012) · doi:10.1029/2011jc007339 · Cited by 48
“htm), which is using the Weather Research and Forecasting (WRF) model [Skamarock et al., 2005] configured for the regional conditions of Arctic Alaska.”
MethodWhat shapes mesoscale wind anomalies in coastal upwelling zones?
Boé, J., Hall, A., Colas, F., McWilliams, J., Qu, X., Kurian, J., & Kapnick, S. (2011) · Climate Dynamics · doi:10.1007/s00382-011-1058-5 · Cited by 48
Theory, Observations, and Predictions of Orographic Precipitation
Colle, B., Smith, R. B., & Wesley, D. (2013) · Springer atmospheric sciences · doi:10.1007/978-94-007-4098-3_6 · Cited by 48
Metadata
- Authors
- Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., & Wang, W.
- Venue
- NSF National Center for Atmospheric Research
- Publisher
- NSF National Center for Atmospheric Research
- Published
- 2005
- OpenAlex
- W2152984210
- Cited by
- 2,504
- References
- 0
- Citations by year
- 2026: 9 · 2025: 32 · 2024: 61 · 2023: 76 · 2022: 105 · 2021: 154 · 2020: 129 · 2019: 160 · 2018: 155 · 2017: 118 · 2016: 143 · 2015: 127 · 2014: 123 · 2013: 159 · 2012: 154
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- Defense Technical Information Center (DTIC) (submittedVersion)
- UCAR/NCAR
- Topics
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Meteorological Phenomena and Simulations
- Physical Sciences › Engineering › Computational Mechanics › Computational Fluid Dynamics and Aerodynamics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Keywords
- numerical weather prediction, regional climate modeling, WRF model, model description
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