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Variational methods for targeted monitoring of atmospheric quality by specified cost criteria. / Penenko, V. V.

In: IOP Conference Series: Earth and Environmental Science, Vol. 211, No. 1, 012048, 17.12.2018.

Research output: Contribution to journalConference articlepeer-review

Harvard

Penenko, VV 2018, 'Variational methods for targeted monitoring of atmospheric quality by specified cost criteria', IOP Conference Series: Earth and Environmental Science, vol. 211, no. 1, 012048. https://doi.org/10.1088/1755-1315/211/1/012048

APA

Penenko, V. V. (2018). Variational methods for targeted monitoring of atmospheric quality by specified cost criteria. IOP Conference Series: Earth and Environmental Science, 211(1), [012048]. https://doi.org/10.1088/1755-1315/211/1/012048

Vancouver

Penenko VV. Variational methods for targeted monitoring of atmospheric quality by specified cost criteria. IOP Conference Series: Earth and Environmental Science. 2018 Dec 17;211(1):012048. doi: 10.1088/1755-1315/211/1/012048

Author

Penenko, V. V. / Variational methods for targeted monitoring of atmospheric quality by specified cost criteria. In: IOP Conference Series: Earth and Environmental Science. 2018 ; Vol. 211, No. 1.

BibTeX

@article{f34651a090ed41b098e4a9dfca513b7a,
title = "Variational methods for targeted monitoring of atmospheric quality by specified cost criteria",
abstract = "The creation of problem-oriented monitoring strategies for the study of natural processes in the atmosphere-Earth system based on use of mathematical models in combination with observational data is discussed. Major objects of a modeling system are described. These are: a model of processes of transport and transformation of substances in the gas and aerosol state, data and models of observations. We develop a variational approach that provides formulation, construction, and implementation of solutions to direct and inverse problems. To formulate the variational principle, some target functionals are defined. They serve for forecasting, assimilating observational data, controlling atmospheric quality, etc. Data assimilation techniques play a significant role in successful management of environmental objectives. The result of the study is a version of the so-called {"}seamless{"} modeling technology in which five classes of the required functions are calculated. These are state functions, adjoint functions, uncertainty functions, and two functions of sensitivity with respect to variations of model parameters and monitoring data. We can solve inverse problems of strategic operational assessments of hazardous situations and identification of sources of intensive technogenic impacts to organize the targeted monitoring.",
author = "Penenko, {V. V.}",
year = "2018",
month = dec,
day = "17",
doi = "10.1088/1755-1315/211/1/012048",
language = "English",
volume = "211",
journal = "IOP Conference Series: Earth and Environmental Science",
issn = "1755-1307",
publisher = "IOP Publishing Ltd.",
number = "1",
note = "International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems, ENVIROMIS 2018 ; Conference date: 05-07-2018 Through 11-07-2018",

}

RIS

TY - JOUR

T1 - Variational methods for targeted monitoring of atmospheric quality by specified cost criteria

AU - Penenko, V. V.

PY - 2018/12/17

Y1 - 2018/12/17

N2 - The creation of problem-oriented monitoring strategies for the study of natural processes in the atmosphere-Earth system based on use of mathematical models in combination with observational data is discussed. Major objects of a modeling system are described. These are: a model of processes of transport and transformation of substances in the gas and aerosol state, data and models of observations. We develop a variational approach that provides formulation, construction, and implementation of solutions to direct and inverse problems. To formulate the variational principle, some target functionals are defined. They serve for forecasting, assimilating observational data, controlling atmospheric quality, etc. Data assimilation techniques play a significant role in successful management of environmental objectives. The result of the study is a version of the so-called "seamless" modeling technology in which five classes of the required functions are calculated. These are state functions, adjoint functions, uncertainty functions, and two functions of sensitivity with respect to variations of model parameters and monitoring data. We can solve inverse problems of strategic operational assessments of hazardous situations and identification of sources of intensive technogenic impacts to organize the targeted monitoring.

AB - The creation of problem-oriented monitoring strategies for the study of natural processes in the atmosphere-Earth system based on use of mathematical models in combination with observational data is discussed. Major objects of a modeling system are described. These are: a model of processes of transport and transformation of substances in the gas and aerosol state, data and models of observations. We develop a variational approach that provides formulation, construction, and implementation of solutions to direct and inverse problems. To formulate the variational principle, some target functionals are defined. They serve for forecasting, assimilating observational data, controlling atmospheric quality, etc. Data assimilation techniques play a significant role in successful management of environmental objectives. The result of the study is a version of the so-called "seamless" modeling technology in which five classes of the required functions are calculated. These are state functions, adjoint functions, uncertainty functions, and two functions of sensitivity with respect to variations of model parameters and monitoring data. We can solve inverse problems of strategic operational assessments of hazardous situations and identification of sources of intensive technogenic impacts to organize the targeted monitoring.

UR - http://www.scopus.com/inward/record.url?scp=85059591758&partnerID=8YFLogxK

U2 - 10.1088/1755-1315/211/1/012048

DO - 10.1088/1755-1315/211/1/012048

M3 - Conference article

AN - SCOPUS:85059591758

VL - 211

JO - IOP Conference Series: Earth and Environmental Science

JF - IOP Conference Series: Earth and Environmental Science

SN - 1755-1307

IS - 1

M1 - 012048

T2 - International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information Systems, ENVIROMIS 2018

Y2 - 5 July 2018 through 11 July 2018

ER -

ID: 18072007