A Supercomputer-Based Modeling System for Short-Term Prediction of Urban Surface Air Quality

Статья в журнале

This paper proposes a mathematical model and an effective supercomputer-based numerical method for short-term prediction of extreme meteorological conditions and atmospheric air quality over limited stretches of land encompassing large population centers. The mathematical model includes a pollutant transport model with a reduced chemical mechanism and a non-hydrostatic mesoscale meteorological model with a modern moisture microphysics parametrization scheme. The numerical method relies on the use of the finite volume method and semi-implicit difference schemes of the second order of approximation, which are solved using the TDMA method with a linear dependence of the number of arithmetic operations on the size of the grid. This property of the numerical method ensures high efficiency when parallelized: not less than 70% when using up to 256 computing cores with a horizontal grid size of 0.5–1.0 km. Development of parallel programs was carried out using the Message Passing Interface parallel programming technology, two-dimensional decomposition of the grid area along horizontal (west to east and south to north) directions, and introduction of additional fictitious grid nodes along the perimeter of the decomposition subdomains.

Журнал:

• Supercomputing Frontiers and Innovations
• South Ural State University (Челябинск)
• Индексируется в Scopus

Библиографическая запись: Supercomputer-Based Modeling System for Short-Term Prediction of Urban Surface Air Quality [Electronic resource] / A. V. Starchenko [et al.] // Supercomputing Frontiers and Innovations. – 2022. – Vol. 9. – Iss. 1. – P. 17–31. – DOI: 10.14529/jsfi220102

Индексируется в:

• Scopus ( https://www.scopus.com/record/display.uri?eid=2-s2.0-85131416368&origin=resultslist&sort=plf-f )
• РИНЦ ( https://elibrary.ru/item.asp?id=49156348 )
• ВАК ( https://elibrary.ru/item.asp?id=49156348 )