|
REFERENCES
[1] W. C.Skamarock, J. B. Klemp, J.Dudhia, D. O. Gill, D. M. Barker, W. Wang, J.G. Powers, “A description of the advanced research WRF Version 2. NCAR Tech. Notes. Natl. Cent. for Atmos. Res., Boulder, Colorado. 2005 [1] W. C.Skamarock, J. B. Klemp, J.Dudhia, D. O. Gill, D. M. Barker, W. Wang, J.G. Powers, “A description of the advanced research WRF Version 2. NCAR Tech. Notes. Natl. Cent. for Atmos. Res., Boulder, Colorado. 2005
[2] A.L.Kondowe, Impact of Convective Parameterization Schemes on the Quality of Rainfall Forecast over Tanzania Using WRFModel, Natural Science, 2014, V.6, pp.691-699
[3] Z. T. Segele, Lance M. Leslie and Peter J. Lamb, “Weather Research and Forecasting Model simulations of extended warm-season heavy precipitation episode over the US Southern Great Plains: data assimilation and microphysics sensitivity experiments”, Tellus A 2013, V. 65, pp.1-26.
[4] G.T. De Silva, S. Herath, S.B.Weerakoon and Rathnayake U.R., Application of WRF with different cumulus parameterization schemes for precipitation forecasting in a tropical river basin, Proc. of the 13th Asian Congress of Fluid Mechanics 17-21 December 2010, Dhaka, Bangladesh, pp.513-516
[5] G. S. Zepka and Jr. O. Pinto, “A Method to Identify the Better WRF Parameterizations Set to Describe Lightning Occurrence”, 3rd meteorological Lightning Conference, 21-22 April, 2010, Orlando, Florida, USA pp.1-10
[6] Y. Yair, B. Lynn, C. Price, V. Kotroni, K. Lagouvardos,; E. Morin, A. Mugnai and Llasat M. d. C., “Predicting the potential for lightning activity in Mediterranean storms based on the Weather Research and Forecasting (WRF) model dynamic and microphysical fields”. J. Geophys. Res., 115,
[7] J. S. Kain, “The Kain–Fritsch Convective Parameterization” An Update. J. Appl. Meteor., 2004, 43, 170–181.
[8] E. K. Gilliland, , and C. M. Rowe, “A comparison of cumulus parameterization schemesin the WRF model” . Preprints, 21st Conf. on Hydrology, San Antonio, TX, Amer.Meteor. Soc., 2007, P2.16.
[9] W. Wang and N. L. Seaman, “A comparison study of convective parameterization schemes in a mesoscale model”. Mon. Wea. Rev., 1997, 125, 252-278.
[10] L.-M. Ma and Z.-M. Tan, 2009: Improving the behavior of the cumulus parameterization for tropical cyclone prediction: convection trigger. Atmos. Res., 92, 190-211.
[11] S.Y. Hong, J. Dudhia, and S.H. Chen, “A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation”. Mon. Wea. Rev., 2004, 132, 103–120.
[12] B.S. Ferrier, Y. Jin, Y. Lin, T Black, E. Rogers, G. DiMego, “Implementation of a new gridscale cloud and precipitation scheme in the NCEP Eta model”. Preprints 15th Conf. on Numerical Weather Prediction,San Antonio, TX, Amer. Meteor. Soc., 2002, 280–283.
[13] Y. L. Lin, R. D.Farley, H. D. Orville,“Bulk Parameterization of the Snow Field in a Cloud Model”. J. Appl. Meteor., 1983, 22, 1065– 1092.
[14] Z.I.Janjić, “The Step-Mountain Eta Coordinate Model: Further Developments of the Convection, Viscous Sublayer, and Turbulence Closure Schemes. Mon. Wea. Rev., 1994, 122, 927–945.
[15] Z.I. Janjić, ”Comments on “Development and Evaluation of a Convection Scheme for Use in Climate Models”. J. Atmos. Sci., 2000, 57, 3686.
[16] G. A. Grell and Dévényi, D.“A generalized approach to parameterizing convection combining ensemble and data assimilation techniques”. Geophys. Res. Lett.,2002, 29 (14), 1693, doi: 10.1029/2002GL015311.
[17] J. D. Duda, “WRF simulations of mesoscale convective systems at convection-allowing resolutions Graduate Theses and Dissertations. , 2011. Paper 10272.
[18] J. S. Kain and J. M. Fritsch, “The role of the convective “trigger function” in numerical forecasts of mesoscale convective systems”. Meteor. and Atmos. Phys.,1992, 49, 93–106.
[19] J. S Kain,., and J. M. Fritsch, “Convective parameterization for mesoscale models: The Kain–Fritsch scheme”. The Representation of Cumulus Convection in Numerical Models, Meteor.Monogr., No. 24, Amer. Meteor. Soc.,1993, 165–170.
[20] S.Yavinchan, , R. H. B. Exell, and D. Sukawat, 2011: Convective parameterization in a model for the prediction of heavy rain in southern Thailand. J. Meteor. Soc. Japan, 89A,pp. 201– 224.
[21] A. S.Monin, A. M. Obukhov,” Basic laws of turbulent mixing in the surface layer of the atmosphere “Tr. Geofiz. Inst., Akad. Nauk SSSR, 24, 1954, pp.1963–1967. (in Russian).
[22] S.Y. Hong, and J. O. J. Lim, “The WRF singlemoment 6-class microphysics scheme (WSM6)”. J. Korean Meteor. Soc., vol. 42, 2006, pp.129–151.
[23] A.E.Cohen, S.M.Cavallo, M.C.Coniglo, H.E. Brooks, “AReview of Planetary Boundary Layer Parameterization Schemes and Their Sensitivity in Simulating Southeastern U.S. Cold Season Severe Weather Environments”, vol.30, 2015, pp.591-612
[24] I., W. A. Jankov, M.Gallus, Segal, B. Shaw, and S. E. Koch, 2005: The impact of different WRF Model physical parameterizations and their interactions on warm season MCS rainfall. Wea. Forecasting, 20, 1048–1060, doi:10.1175/WAF888.1.
[25] T. Davitashvili, R. Kvatadze, N. Kutaladze, “Weather Prediction Over Caucasus Region Using WRF-ARW Model, MIPRO, 2011, Proceedings of the 34th International Convection, 2011, Print ISBN: 978-1-4577- 0996-8, Opatija, Croatia, pp.326-330
[26] T. Davitashvili, G. Kobiashvili, R. Kvatadze, N. Kutaladze, G. Mikuchadze, “WRF-ARW Application for Georgia” Report of SEEGRID-SCI User Forum, 2009, Istanbul, Turkey, pp.7-10
|
PDF
