| Title |
Numerical Investigation of the Direct Variational Algorithm of Data Assimilation in the Urban Scenario |
| ID_Doc |
43593 |
| Authors |
Penenko, AV; Mukatova, ZS; Penenko, VV; Gochakov, AV; Antokhin, PN |
| Title |
Numerical Investigation of the Direct Variational Algorithm of Data Assimilation in the Urban Scenario |
| Year |
2018 |
| Published |
Atmospheric And Oceanic Optics, 31, 6 |
| DOI |
10.1134/S102485601806012X |
| Abstract |
The performance of a direct variational data assimilation algorithm with quasi-independent data assimilation at individual steps of the splitting scheme has been studied in a realistic scenario of air pollution assessment in the city of Novosibirsk by monitoring system data. For operation under conditions of a sparse monitoring network, an algorithm with minimization of the spatial derivative of the uncertainty (control) function adjusted to data assimilation is proposed. The use of the spatial derivative minimization increases the smoothness of the uncertainty (control functions) reconstructed, which has a positive effect on the reconstruction quality in the scenario considered. |
| Author Keywords |
data assimilation; variational approach; splitting scheme; smart city |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:000461399500017 |
| WoS Category |
Optics |
| Research Area |
Optics |
| PDF |
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