Talks and Poster Presentations (with Proceedings-Entry):

M. Demuzere, S. Decubber, D. Miralles, C. Papagiannopoulou, W. Waegeman, N. Verhoest, W. Dorigo:
"Sensitivity of Global Ecosystems to Climate Anomalies in Observations and Earth System Models";
Talk: 7th International Workshop on Climate Informatics, Boulder, CO, USA; 2017-09-20 - 2017-09-22; in: "Proceedings of the 7th International Workshop on Climate Informatics: CI 2017.", NCAR Technical Note NCAR/TN-536+PROC (2017), ISBN: 978-0-9973548-2-9; 21 - 24.

English abstract:
Vegetation is a key player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and shortterm disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a random forest (RF) predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. These observation-based results will then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.