Numerical study of direct variational data assimilation algorithm in the urban scenario
A.V. Penenko1, Z.S. Mukatova1, V.V. Penenko1, A.V. Gochakov2, P.N. Antokhin3
1Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the RAS, 6, Ac. Lavrentieva ave., 630090, Novosibirsk, Russia
2Siberian Regional Hydrometeorological Research Institute, Russia, 630099, Novosibirsk, Sovetskaya, 30
3V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of the Russian Academy of Science, 1, Academician Zuev square, Tomsk, 634021, Russia
Keywords: усвоение данных, вариационный подход, схема расщепления, В«Умный городВ», data assimilation, variational approach, splitting scheme, “smart city
Abstract
The performance of a direct variational data assimilation algorithm with quasi-independent data assimilation at individual steps of the splitting scheme was evaluated in the realistic scenario of the air pollution assessment in the city of Novosibirsk. An algorithm with minimization of the spatial derivative of the uncertainty (control) function, which is adjusted to assimilate data, was considered in the case of sparse monitoring network. The use of the spatial derivative minimization allowed increasing smoothness of the uncertainty (control functions) reconstructed, which has a positive effect on the reconstruction quality in the scenario considered.
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