Modeling weather conditions in the port area and coastal zone of Tiksi Bay

Wind energy is one of the most important directions in the development of renewable energy sources in the Russian Federation. The most important trends in the wind industry are objectives for the design of new wind farms, the tasks of maintenance and monitoring of wind farm design challenges of wind turbines, the development of Russian software, etc. A number of topical basic and applied problems are appeared in connection with the construction of new wind farms on the territory of the Russian Federation. In this paper, one of these tasks is considered: the study of the wind situation in the area of Tiksi village, due to the installation of a new wind farm there. The wind forecast is based on the Advanced Research WRF (Weather Research and Forecasting) mesoscale model using the Global Forecast System data.  The presented results are obtained on a series of nested grids with spatial resolution of 1, 3 and 9 km. A method for wind farm study and monitoring of a near the village of Tiksi is proposed, which is based on interpolation the results obtained from WRF-ARW to a smaller scale model within the future use of Simulator fOr Wind Farm Applications (SOWFA) library in OpenFOAM platform.

1. . Gordin V. A. Mathematics, Computer, Weather Forecasting, and Other Scenarios of Mathematical Physics. M., Fizmatlit, 2010. 733 p. (in Russian).

2. . Lykossov V. N., Glazunov A. V., Kulyamin D. V., Mortikov E. V., Stepanenko V. M. Supercomputer Modeling in Physics of the Climate System. M: Moscow University Press, 2012. 408 p. (in Russian).

3. . Zilitinkevich S.S Atmospheric Turbulence and Planetary Boundary Layers. M., Fizmatlit, 2014. 252 p. (in Russian).

4. . Jiménez PA, Navarro J, Palomares AM, Dudhia J. Mesoscale modeling of offshore wind turbine wakes at the wind farm resolving scale: a composite-based analysis with the weather research and forecasting model over Horns Rev. Wind Energy, 2014, vol. 18, pp. 559–566.

5. . Javier Sanz Rodrigo, Roberto Aurelio Chávez Arroyo, Patrick Moriarty, Matthew Churchfield, Branko Kosovic, Pierre-Elouan Réthoré, Kurt Schaldemose Hansen, Andrea Hahmann, Jeffrey D. Mirocha and Daran Rife. Mesoscale to microscale wind farm flow modeling and evaluation. WIREs Energy Environ, 2016. DOI: 10.1002/wene.214.

6. . Yang, Xiaolei & Sotiropoulos, Fotis & Conzemius, Robert & Wachtler, John & Strong, Mike. Large-eddy simulation of turbulent flow past wind turbines/farms: The Virtual Wind Simulator (VWiS). Wind Energy, 2014, vol. 18. DOI: 10.1002/we.1802.

7. . Rodrigo, J & Allaerts, Dries & Avila, Matias & Barcons, Jordi & Cavar, D & Chavez, Roberto & Churchfield, M & Kosovic, Branko & Lundquist, Julie & Meyers, Johan & Muñoz-Esparza, Domingo & Palma, JMLM & Tomaszewski, Jessica & Troldborg, N & van der Laan, M. Paul & Veiga Rodrigues, Carlos. Results of the GABLS3 diurnal-cycle benchmark for wind energy applications. Journal of Physics: Conference Series, 2017, 854(1):012037. DOI: 10.1088/1742-6596/854/1/012037.

8. . Fedorov A.N., Torgovkin Y.I., Shestakova A.A., Vasiliev N.F., Makarov V.S. et al., Ch. ed. M.N. Zheleznyak The permafrost-landscape map of the Republic of Sakha (Yakutia). Scale 1: 1,500,000. Yakutsk: IIM SB RAS, 2018 (in Russian).

9. . Periglacial features around Tiksi. Russian-German Cooperation SYSTEM LAPTEV SEA The Expedition LENA 2002. Edited by Mikhail N. Grigoriev, Volker Rachold, Dmitry Yu. Bolshiyanov, Eva-Maria Pfeiffer, Lutz Schirrmeister, Dirk Wagner and Hans-Wolfgang Hubberten. 2003. 195 p.

10. . National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce. 2000, updated daily. NCEP FNL Operational Model Global Tropospheric Analyses, continuing from July 1999. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https://doi.org/10.5065/D6M043C6.

11. . Vel'tishchev N. F., Zhupanov V. D., Chislennye prognozy pogody po negidrostaticheskim modelyam obshchego pol'zovaniya WRF-ARW i WRF-NMM (Numerical weather forecasts by non-hydrostatic open-source models WRF-ARW and WRF-NMM), In: 80 let Gidromettsentru Rossii (80 years to the Hydrometeorological Center of Russia), 2010, pp. 94-135.

12. . Lapo P.О., Shakur V.N, Prakharenia M. The results of verification of the WRF-ARW model in the Hydromet of the Republic of Belarus. Proceedings of Hydrometcentre of Russia, issue. 258, 2015, pp. 67–77.

13. . Yijia Zheng, Yucong Miao, Shuhua Liu, Bicheng Chen, Hui Zheng, and Shu Wang, “Simulating Flow and Dispersion by Using WRF-CFD Coupled Model in a Built-Up Area of Shenyang, China,” Advances in Meteorology, 2015, vol. 2015, 15 p. DOI: 10.1155/2015/528618.

14. . Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., … Huang, X. -yu. A Description of the Advanced Research WRF Model Version 4. No. NCAR/TN-556+STR. 2019. doi:10.5065/1dfh-6p97

15. . Kraposhin M.V., Strijhak S.V. The problem-oriented library SOWFA for solving the applied tasks of wind energy. Trudy ISP RAN/Proc. ISP RAS, vol. 30, issue 6, 2018, pp. 259–274 (in Russian). DOI: 10.15514/ISPRAS-2018-30(6)-14

16. . Thompson G., Rasmussen R. M. and Manning K. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part I: Description and sensitivity analysis. Mon. Wea. Rev., vol. 132, no. 2, 2004, pp. 519-642.

17. . Tiedtke, M. A comprehensive mass flux scheme for cumulus parameterization in largescale models. Mon. Wea. Rev., vol. 117, 1989, pp. 1779-1800. DOI: 10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2

18. . Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins. Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., vol. 113, issue D13103. 2008. DOI: https://doi.org/10.1029/2008JD009944

19. . Janjic Z.I. The step-mountain Eta coordinate model: Future developments of convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., vol. 122, no. 5, 1990, pp. 927-945.

20. . Janjic Z.I. The surface layer in the NCEP Eta model. 11th Conf. on NWP, Norfolk, VA, Amer. Meteor. Soc., 1996, pp. 354-355.

21. . Janjic Z.I. Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model, NCEP Office Note, no. 437, 2002, 61 p.

22. . Monin, A.S. and A.M. Obukhov. Basic laws of turbulent mixing in the surface layer of the atmosphere. Contrib. Geophys. Inst. Acad. Sci., USSR, vol. 151, mo. 24, 1954, 163–187 (in Russian).

23. . Chen, F., and J. Dudhia, Coupling an advanced land-surface/ hydrology model with the Penn State/ NCAR MM5 modeling system. Part I: Model description and implementation. Mon. Wea. Rev., vol. 129, 2001, pp. 569–585.

24. . The NCAR Command Language (Version 6.4.0) [Software]. 2017. Boulder, Colorado: UCAR/NCAR/CISL/VETS. http://dx.doi.org/10.5065/D6WD3XH5

25. . Shikhov A.N., Sviyazov E.M. forecasting of the dynamics of snow melting in the Western Ural region, using WRW/ARW mesoscale model, issue 4, 2013. URL: http://www.science-education.ru/ru/article/view?id=9962

26. . Nabokova E. V. The experience of using the WRF model in respect 2 parameterization methods of urban sub-layer for wind velocity and temperature prediction. Proceedings of the Hydrometcentre of Russia, "Atmospheric physics and weather forecast", issue 344, pp. 180-195, 2010.

27. . Fitch, A. C. et al. Local and Mesoscale Impacts of Wind Farms as Parameterized in a Mesoscale NWP Model. Monthly Weather Review. 2012. DOI:http://dx.doi.org/10.1175/MWR-D-11-00352.1