📋 Tender Overview
Modelling Non-Stationary Tree Growth Responses To Global Warming
Tree Growth Tracking To Improve Climate Variability Reconstructiontree Rings Represent A Fundamental Archive For The High-Resolution Reconstruction Of Climate Alterability Over The Past 1–2 Ka At Regional And Global Levels. Accurate Reconstructions Require A Constant Relationship Between Tree Growth And Climate. However, During The Second Half Of The 20Th Century, Tree-Ring Width And Density Chronologies Were Not Able To Track The Rapidly Increasing Temperatures In Northern Hemisphere Forests. This Phenomenon, Called The "Divergence" Problem, Questions The Reliability Of Tree-Ring Based Temperature Reconstruction And Our Understanding Of The Earth’S Climate Response To Anthropogenic Greenhouse Gases. The Eu-Funded Monostar Project Will Develop A Model That Simulates Year-To-Year And Long-Term Alterations In Both The Tree-Ring Width And Density Of Varying Conifer Species Growing Under Diverse Climate Environments. The Model Will Be Combined With Data From A New Hemispheric Network Of Tree-Ring Width And Density Chronology As Well As In Situ Monitoring Data.
Funded Under
Excellent Science - European Research Council (Erc)
Total Cost
€ 2 497 500,00
Eu Contribution
€ 2 497 500,00
Coordinated By
Johannes Gutenberg-Universitat Mainz
Germany
Start Date
1 April 2021
End Date
31 March 2027
Objective
Tree-rings are a key proxy archive for reconstructing high resolution climate variability over the past 1-2ka at regional to global scales. Skillful reconstructions require a stationary relationship between tree growth and climate (Hutton’s principle of uniformitarianism), which is commonly evaluated by statistical calibration/verification trials against instrumental measurements. This association, however, weakened during the second half of the 20th century, when tree-ring width and density chronologies from Northern Hemisphere forests were not able to track the rapidly increasing temperatures. This so-called divergence problem was identified in the 1990s to be a large-scale phenomenon, and not only questions the reliability of tree-ring based temperature reconstruction, but also affects our understanding of the Earth’s climate sensitivity to anthropogenic greenhouse gases. A conclusive explanation for this central problem of contemporary paleoclimate research is, however, still missing. Here, I propose to develop a process model that simulates year-to-year and long-term variations in both tree-ring width and density of different conifer species growing under different climate regimes. Evidence from this model will be combined with data from a new, hemispheric scale network of tree-ring width and density chronologies, as well as in-situ monitoring data, to train the model, validate synthetic timeseries, and analyze spatially varying influences of climatological, air chemical and ecological drivers on tree growth. Model-data fusion and inverse modelling techniques will be ap
