Mesoscale meteorological model TSUNM3 for the study and forecast of meteorological parameters of the atmospheric surface layer over a major population center
The paper describes the mathematical formulation and numerical method of the TSUNM3 high-resolution mesoscale meteorological model being developed at Tomsk State University. The model is nonhydrostatic and includes three-dimensional nonstationary equations of hydrothermodynamics of the atmospheric boundary layer with parameterization of turbulence, moisture microphysics, long-wave and short-wave (solar) radiation, and advective and latent heat flows in the atmosphere and at the boundary of its interaction with the underlying surface. The numerical algorithm is constructed using structured grids with uniform spacing in horizontal directions and condensing to the Earth surface in the vertical direction. When approximating the differential formulation of the problem, the finite volume method with the second order approximation in the spatial variables is used. Explicit-implicit approximations in time (Adams-Bashforth and Crank-Nicolson) are used to achieve second-order accuracy in time. The paper presents results of numerical forecasting of the main meteorological parameters of the atmosphere (temperature, humidity, wind speed and direction) and precipitation in different seasons in the Siberian region. The models were tested with the help of observations obtained using the Volna-4M sodar, MTR-5 temperature profile meter, and Meteo-2 ultrasonic weather stations of the Atmosfera Collective Use Center. The improved TSUNM3 model is shown to adequately reflect the precipitation time and intensity. However, in some cases, the times of its beginning and end do not always coincide, the difference can reach several hours. The precipitation phase state is reflected reliably. Over 70% of precipitation cases are confirmed by numerical calculations. The model satisfactorily predicts temperature and humidity characteristics. The quality of the precipitation forecast model is comparable to the modern mesoscale models, such as the Weather Research and Forecasting (WRF) model.
Keywords
математическое моделирование атмосферных процессов с высоким разрешением,
сравнение расчетов с измерениями ЦКП «Атмосфера»,
mathematical modeling of atmospheric processes with high resolution,
comparison of calculations with measurements of the Atmosfera Collective Use CenterAuthors
| Starchenko Alexander V. | Tomsk State University | starch@math.tsu.ru |
| Bart Andrey A. | Tomsk State University | bart@math.tsu.ru |
| Kizhner Lyubov I. | Tomsk State University | kdm@mail.tsu.ru |
| Danilkin Evgeniy A. | Tomsk State University | ugin@math.tsu.ru |
Всего: 4
References
Sokhi R., Baklanov A., Schlunzen H., et al. Mesoscale Modelling for Meteorological and Air Pollution Applications. New York: Anthem Press, 2018. 260 p.
Skamarock W.C., Klemp J.B., Dudhia J., GillD.O., Barker D.M., Duda D.M., Wang W., Powers J.G. A description of the advanced research WRF version 3 // NCAR Tech. Note. NCAR/TN-68CSTR, 2008. 100 p. DOI: 10.5065/D68S4MVH.
Yanez-Morroni G., Gironas J., Caneo M.Delgado R., Garreaud R. Using the Weather Research and Forecasting (WRF) model for precipitation forecasting in an andean region with complex topography // Atmosphere. 2018. V. 9. No. 8. P. 304. DOI: 10.3390/atmos9080304.
Ривин Г.С., Вильфанд Р.М., Киктев Д.Б., Розинкина И.А., Тудрий К.О., Блинов Д.В., Варенцов М.И., Самсонов Т.Е., Бундель А.Ю., Кирсанов А.А., Захарченко Д.И. Система численного прогнозирования явлений погоды, включая опасные, для Московского мегаполиса: разработка прототипа // Метеорология и гидрология. 2019. № 11. С. 33-45.
Starchenko A.V., Bart A.A., Bogoslovsky N.N., Danilkin E.A., Terentyeva M.V. A mathematical modelling of atmospheric processes above an industrial center // Proc. SPIE. 2014. V. 9292. P. 929249-1-929249-30. DOI: 10.1117/12.2075164.
Pielke R. Mesoscale Meteorological Modeling. San Diego, California: Academic Press, 2002. 676 p.
Hong S.-Y., Lim J.-O.J. The WRF single-moment 6-class microphysics scheme (WSM6) // J. Korean Meteorological Society, 2006. V. 42. No. 2. P. 129-151.
Bao J.-W., Michelson S.A., Grell E.D. Pathways to the Production of Precipitating Hydrometeors and Tropical Cyclone Development // Monthly Weather Review. 2016. V. 144. P. 2395-2420. DOI: 10.1175/MWR-D-15-0363.1.
Andren A. Evaluation of a turbulence closure scheme suitable for air pollution applications // J. Applied Meteorology and Climatology. 1990. V. 29. P. 224-239.
Smagorinsky J. General circulation experiments with the primitive equations: Part I. The basic experiment // Monthly Weather Review. 1963. V. 91. No. 2. P. 99-164.
Толстых М.А., Булдовский Г.С. Усовершенствованный вариант глобальной полулагранжевой модели прогноза полей метеоэлементов в версии с постоянным разрешением заблаговременностью до 10 суток и результаты его оперативных испытаний // Фундаментальные и прикладные гидрометеорологические исследования. СПб.: Гидрометеоиздат, 2003. С. 24-47.
Carpenter K. Note on the paper «Radiation condition for the lateral boundaries of limited-area numerical models» by Miller, M. and Thorpe, A. (V. 107. P. 615-628) // J. Royal Meteorology Society. 1982. V. 108. P. 717-719.
Монин А.С., Обухов А.М. Основные закономерности турбулентного перемешивания в приземном слое атмосферы // Труды Геофизического института АН СССР. 1954. № 24. C. 163-187.
Dyer A.J., Hicks B.B. Flux-gradient relationships in the constant flux layer // Quart. J. Roy. Meteorol. Soc. 1970. V. 96. P. 715-721.
Noilhan J., Mahfouf J.-F. The ISBA land surface parameterization scheme // Global and Planetary Change. 1996. V. 13. P. 145-159.
Hurley P. The Air Pollution Model (TAPM) Version 2 // CSIRO Atmospheric Research. 2002. Paper No. 55. P. 49. DOI: 10.4225/08/5863fe87915fd.
Mahrer Y., Pielke R.A. A numerical study of the airflow over irregular terrain // Beitr. Phys. Atmosph. 1977. V. 50. P. 98-113.
Dilley A.C., O’Brien D.M. Estimating downward clearsky long-wave irradiance at the surface from screen temperature and precipitable water // Quart. J. Roy. Meteorol. Soc. 1998. V. 124. P. 1391-1401.
Stephens G. Radiation profiles in extended water clouds. Part II: Parameterization schemes // J. Atmospheric Sciences. 1978. V. 35. P. 2123-2132.
Патанкар С. Численные методы решения задач теплообмена и динамики жидкости: пер. с англ. М.: Энергоатомиздат, 1984. 149 c.
Van Leer B. Towards the ultimate conervative difference scheme. II. Monotonicity and conservation combined in a second order scheme // J. Computational Physics. 1974. V. 14. P. 361-370.
Семёнова А.А., Старченко А.В. Разностная схема для нестационарного уравнения переноса, построенная с использованием локальных весовых интерполяционных кубических сплайнов // Вестник Томского государственного университета. Математика и механика. 2017. № 49. С. 61-74. DOI: 10.17223/19988621/49/6.
Starchenko A., Danilkin E., Semenova A., Bart A. Parallel algorithms for a 3D photochemical model of pollutant transport in the atmosphere // Communications in Computer and Information Science. 2016. V. 687. P. 158-171. DOI: 10.1007/978-3-319-55669-7.
Старченко А.В., Берцун В.Н. Методы параллельных вычислений. Томск: Изд-во Том. ун-та, 2013. 223 с.
Starchenko A.V., Bart A.A., Kizhner L.I., Odintsov S.L., Semyonov E.V. Numerical simulation of local atmospheric processes above a city // Proceedings of SPIE - The International Society for Optical Engineering. 2019. V. 11208. P. 1-9. DOI: 10.1117/12.2541630.
