Number of the records: 1  

Integration of flux tower data and remotely sensed data into the SCOPE simulator: A Bayesian approach

  1. 1.
    SYSNO ASEP0522666
    Document TypeA - Abstract
    R&D Document TypeThe record was not marked in the RIV
    R&D Document TypeNení vybrán druh dokumentu
    TitleIntegration of flux tower data and remotely sensed data into the SCOPE simulator: A Bayesian approach
    Author(s) Raj, Rahul (UEK-B) RID, SAI, ORCID
    Lukeš, Petr (UEK-B) ORCID, SAI, RID
    Homolová, Lucie (UEK-B) RID, ORCID, SAI
    Brovkina, Olga (UEK-B) RID, SAI, ORCID
    Šigut, Ladislav (UEK-B) RID, ORCID, SAI
    Bagher, B.
    Source TitleThe 3rd ICOS Science Conference, Book of abstracts. - Praha, 2018
    S. 131-132
    Number of pages2 s.
    Publication formOnline - E
    ActionThe 3rd ICOS Science Conference
    Event date11.09.2018 - 13.09.2018
    VEvent locationPraha
    CountryCZ - Czech Republic
    Event typeWRD
    Languageeng - English
    CountryCZ - Czech Republic
    Keywordsscope ; forest ; gross primary productivity ; modelling
    Subject RIVJB - Sensors, Measurment, Regulation
    OECD categoryRemote sensing
    Institutional supportUEK-B - RVO:86652079
    AnnotationQuantification of gross primary production (GPP) together with the continuous monitoring of its temporal variations are indispensable to obtain reliable data for indicating the capacity of forests to sequester carbon. GPP can be quantified us ing two sources: (a) process-based simulator (PBS); and (b) flux tower measurements of the net ecosystem exchange (NEE) of CO2. Additionally, remotely sensed optical data, which can be linked to the vegetation properties, carry valuable information to express canopy photosynthesis (i.e., GPP). A PBS has an advantage over flux tower and remotely sensed optical data because it can be run at time scales beyond the limit of direct measurements. Simulation of GPP by PBS at a high accuracy, however, depends up on how well the parameterization is achieved. A process-based simulator SCOPE (Soil-Canopy-Observation of Photosynthesis and Energy balance) links top of canopy observations of radiance with land surface processes (that include GPP simulation). Some parameters of SCOPE are difficult to obtain from field observations. Reliable estimates of parameters can, however, be obtained using calibration against observations of output. In this study, we present a Bayesian framework to calibrate SCOPE simulator against the estimates of GPP (separated from NEE), and the top of canopy
    WorkplaceGlobal Change Research Institute
    ContactNikola Šviková, svikova.n@czechglobe.cz, Tel.: 511 192 268
    Year of Publishing2020
Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.