Jean-François Exbrayat

Jean-François Exbrayat

Bamberg, Bayern, Deutschland
599 Follower:innen 500+ Kontakte

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Info

I am a Data Scientist with extensive experience in using model optimization and…

Aktivitäten

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Berufserfahrung

  • GfK Grafik

    GfK

    Nuremberg, Bavaria, Germany

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    Nuremberg, Bavaria, Germany

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    Edinburgh, Scotland, United Kingdom

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    Edinburgh, United Kingdom

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    Edinburgh, United Kingdom

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    Sydney, Australia

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    Giessen, Germany

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Ausbildung

  • Justus-Liebig-Universität Giessen Grafik

    Justus-Liebig-Universität Giessen

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    Hydrological modelling: development, calibration and validation of catchment-scale models that simulate runoff and water quality, study of the impact of climate change and evaluation of best management practices using modelling scenarios.

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    M.Sc. Thesis realised at Stockholm University with Prof. Jan Seibert, project entitled "Water quality modelling for Swedish catchments - A comparison of INCA-N and SWAT"

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    Bachelor's degree in Earth Sciences

Bescheinigungen und Zertifikate

Ehrenamt

  • Volunteer helping in visitor research

    Office of Environment and Heritage (NSW)

    – 1 Jahr 6 Monate

    Visitor survey to help in visitor management research.

Veröffentlichungen

  • Quantifying the net contribution of the historical Amazonian deforestation to climate change

    Recent large-scale carbon (C) emissions from deforestation have been estimated by combining remotely-sensed land use change information with satellite-based aboveground biomass (AGB) data. However, these estimates are constrained to the satellite era while regions such as the Amazon basin have been heavily impacted by deforestation before this period. Assessing the net contribution of past tropical deforestation to the growth in atmospheric CO2 is therefore challenging. We address this lack of…

    Recent large-scale carbon (C) emissions from deforestation have been estimated by combining remotely-sensed land use change information with satellite-based aboveground biomass (AGB) data. However, these estimates are constrained to the satellite era while regions such as the Amazon basin have been heavily impacted by deforestation before this period. Assessing the net contribution of past tropical deforestation to the growth in atmospheric CO2 is therefore challenging. We address this lack of data by constructing two maps of potential AGB with a machine learning algorithm trained on the relationship between AGB and climate and topography in intact forest landscapes of the Amazon basin. Reconstructions converge to a current deficit of 11.5–12% in AGB or a net loss of ~7–8 Pg C of AGB in the Amazon basin compared to current estimates. This represents a net contribution of ~1.8 ppm of atmospheric CO2 or 1.5% of the historical growth.

    Andere Autor:innen
    • Mathew Williams
    Veröffentlichung anzeigen

Projekte

  • Comparative predictions of discharge

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    A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a…

    A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments). They did not obtain time series of stream flow, soil moisture or groundwater response. (2) Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3) For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information.

    Andere Mitarbeiter:innen
    Projekt anzeigen

Auszeichnungen/Preise

  • Postdoctoral and early career researcher exchanges with Europe, North America, China & India (PECRE)

    Scottish Alliance for Geoscience, Environment and Society

    £3,000 travel grant to visit German laboratories for 6 weeks during autumn 2016

Sprachen

  • English

    Verhandlungssicher

  • French

    Muttersprache oder zweisprachig

  • German

    Fließend

Organisationen

  • European Geosciences Union

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