BG3.18 EDI

Observations and simulations of the terrestrial carbon and water budget are fundamental to understanding biosphere-atmosphere interactions under a changing climate. Multiple processes determine how mass and energy exchange scale from the level of a leaf, to the whole plant, to the ecosystem level, and to the globe. Empirical studies are subject to the level at which observations are collected, and models imply a choice regarding the scale for which predictions are representative. Recent research has revealed systematic differences between observations taken at different levels, e.g., regarding exchange fluxes of carbon and water between the biosphere and the atmosphere. This can add to model-data mismatch and limits process understanding.
This session aims at bridging terrestrial ecosystem observations across multiple temporal and spatial scales and from multiple variables. We particularly invite research with a focus on how we can learn from multiple observations of carbon and water exchange fluxes. We encourage contributions with a focus on process modelling, machine learning, or with an empirical focus that aims at learning from parallel measurements, captured at the leaf (e.g. gas exchange), tree (e.g. sap flow and tree growth, dendroecology), and/or ecosystem level (eddy covariance towers, UAVs, aircrafts and satellites).

Convener: Mana GharunECSECS | Co-conveners: Arthur Geßler, Rossella Guerrieri, Corinna Rebmann, Benjamin StockerECSECS

Observations and simulations of the terrestrial carbon and water budget are fundamental to understanding biosphere-atmosphere interactions under a changing climate. Multiple processes determine how mass and energy exchange scale from the level of a leaf, to the whole plant, to the ecosystem level, and to the globe. Empirical studies are subject to the level at which observations are collected, and models imply a choice regarding the scale for which predictions are representative. Recent research has revealed systematic differences between observations taken at different levels, e.g., regarding exchange fluxes of carbon and water between the biosphere and the atmosphere. This can add to model-data mismatch and limits process understanding.
This session aims at bridging terrestrial ecosystem observations across multiple temporal and spatial scales and from multiple variables. We particularly invite research with a focus on how we can learn from multiple observations of carbon and water exchange fluxes. We encourage contributions with a focus on process modelling, machine learning, or with an empirical focus that aims at learning from parallel measurements, captured at the leaf (e.g. gas exchange), tree (e.g. sap flow and tree growth, dendroecology), and/or ecosystem level (eddy covariance towers, UAVs, aircrafts and satellites).