An efficient computational method for mesoscale weather forecasting

TitleAn efficient computational method for mesoscale weather forecasting
Publication TypeJournal Article
Year of Publication2020
AuthorsPrusov, VA, Doroshenko, AY
Abbreviated Key TitleDopov. Nac. akad. nauk Ukr.
DOI10.15407/dopovidi2020.03.010
Issue3
SectionInformation Science and Cybernetics
Pagination10-18
Date Published3/2020
Language English
Abstract

Mathematical problems associated with the numerical solution of equations for the predictive models of regional atmospheric circulation are considered. A methodology is considered for effective regional solutions of boundary- value problems with a prehistory on the basis of the “one-way interaction” approach. Within this approach, a method is proposed for filling the data given on the macroscale grid nodes in the mesoscale network based on the spline interpolation and a precise (the fourth-order of accuracy) numerical method for the approximation of the first- and second-order derivatives in differential equations. Thereby, solving problems for ordinary differential equations can be carried out effectively by the interpolation.

Keywordsdifferential equations, interpolation, mesoscale weather forecasting
References: 

1. Asselin, R. (1972). Integration of a semi-implicit model with time-dependent boundary conditions. Atmosphere, 10, pp. 44-55. Doi: https://doi.org/10.1080/00046973.1972.9648331
2. Davies, H. C. (1976). A lateral boundary formulation for multi-level prediction models. Quart. J. Roy. Meteorol. Soc., 102, pp. 405-418. Doi: https://doi.org/10.1002/qj.49710243210
3. Doroshenko, A. Yu. & Prusov, V. A. (2005). Methods of efficient modeling and forecasting regional atmospheric processes. In Advances in Air Pollution Modeling for Environmental Security (pp. 143-152). NATO Science Series, Vol. 54. Dordrecht: Springer. Doi: https://doi.org/10.1007/1-4020-3351-6_13
4. Prusov, V. A. & Doroshenko, A. Yu. (2006). Modeling natural and technogenic atmospheric processes. Kyiv: Naukova Dumka (in Ukrainian).
5. Miyakoda, K. & Rosati, A. (1977). One-way nested grid models: The interface condition and the numerical accuracy. Mon. Weather. Rev., 105, pp. 1092-1107. Doi: https://doi.org/10.1175/1520-0493(1977)105<1092:OWNGMT>2.0.CO;2
6. Manabe, S. (Ed.). (1985). Issues in atmospheric and oceanic modeling. Part A and Part B. Orlando: Academic Press.
7. Prusov, V. & Doroshenko, A. (2018). Computational techniques for modeling atmospheric processes. Hershey, PA, USA: IGI Global. Doi: https://doi.org/10.4018/978-1-5225-2636-0
8. Doroshenko, A., Ivanenko, P., Ovdii, O. & Yatsenko, O. (2016). Automated program design – an example solving a weather forecasting problem. Open Physics, 14, Iss. 1, pp. 410-419. Doi: https://doi.org/10.1515/phys-2016-0048