@inproceedings{6c4f76825e864cf6b7e51f13d0ef053f,
title = "Variational methods for predicting climate-environmental processes with assimilation of observational data",
abstract = "Prospective issues of the organization of modeling technology for studying climatic and environmental processes and solving practical problems are discussed. We study the problems of predictability analysis and uncertainty estimates. To this goal, the combination of process models and observational data is carried out within the framework of the variational principle with weak constraints. This makes it possible to obtain the direct non-iterative algorithms for estimating the state and uncertainty functions.",
keywords = "data assimilation, forecasting, mathematical modeling, predictability, uncertainty assessment, variational approach, MODELS, CHEMISTRY",
author = "Penenko, {Vladimir V.}",
year = "2017",
month = jan,
day = "1",
doi = "10.1117/12.2287115",
language = "English",
isbn = "978-1-5106-1413-0",
volume = "10466",
series = "Proceedings of SPIE",
publisher = "SPIE",
editor = "GG Matvienko and OA Romanovskii",
booktitle = "23rd International Symposium on Atmospheric and Ocean Optics",
address = "United States",
note = "23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics ; Conference date: 03-07-2017 Through 07-07-2017",
}