Variational methods for predicting climate-environmental processes with assimilation of observational data

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

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.

Original languageEnglish
Title of host publication23rd International Symposium on Atmospheric and Ocean Optics
Subtitle of host publicationAtmospheric Physics
EditorsGG Matvienko, OA Romanovskii
PublisherSPIE
Number of pages5
Volume10466
ISBN (Electronic)9781510614130
ISBN (Print)978-1-5106-1413-0
DOIs
Publication statusPublished - 1 Jan 2017
Event23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics - Irkutsk, Russian Federation
Duration: 3 Jul 20177 Jul 2017

Publication series

NameProceedings of SPIE
PublisherSPIE-INT SOC OPTICAL ENGINEERING
Volume10466
ISSN (Print)0277-786X

Conference

Conference23rd International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics
CountryRussian Federation
CityIrkutsk
Period03.07.201707.07.2017

Keywords

  • data assimilation
  • forecasting
  • mathematical modeling
  • predictability
  • uncertainty assessment
  • variational approach
  • MODELS
  • CHEMISTRY

Fingerprint

Dive into the research topics of 'Variational methods for predicting climate-environmental processes with assimilation of observational data'. Together they form a unique fingerprint.

Cite this