Periodic Reporting for period 2 - MONOSTAR (Modelling non-stationary tree growth responses to global warming)
Reporting period: 2022-10-01 to 2024-03-31
Tree-rings are a key proxy archive for reconstructing high-resolution climate variability 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 against instrumental measurements. This association weakened during the second half of the 20th century, however, when tree-ring width and density chronologies from Northern Hemisphere forests were not able to track 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 reconstructions, 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 still missing.
The goal of MONOSTAR is 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 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 applied to quantify the non-linear mechanisms underlying divergence, and to deduce methodological recommendations that can be applied by any paleoclimatologist, working with different species and in different regions of the Northern Hemisphere, to mitigate late 20th century divergence and thus improve their climate reconstructions.
The goal of MONOSTAR is 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 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 applied to quantify the non-linear mechanisms underlying divergence, and to deduce methodological recommendations that can be applied by any paleoclimatologist, working with different species and in different regions of the Northern Hemisphere, to mitigate late 20th century divergence and thus improve their climate reconstructions.
Important work steps achieved during the first project years include the testing of forward growth modelling approaches and development of a tree-ring density and monitoring network across the Northern Hemisphere. Two kick-off meetings were held in Europe and North America to activate international collaborations necessary for conducting fieldwork in remote terrain and adopting forward models. Sixty-nine boreal and alpine tree sites in 17 countries have been sampled on 40 expeditions during three field seasons from 2021-2023 (see live map at: https://www.monostar.org/gallery). Five monitoring stations are up and running covering each Northern Hemisphere continent and delivering in-situ climate and growth data at highest temporal resolution. The work force needed to measure samples from the growing hemispheric network including stem cores, roots, needles, and soil probes has been established and is running at full capacity. Forty papers have been published in international journals with financial support from the Monostar project.
The vision is to develop a forward density model and a hemispheric scale tree-ring network to study non-linear growth responses to rapid climate warming and explain divergence using inverse modelling techniques. Given the rate and risk of anthropogenic warming, it appears critically important to explain 20th century non-linear growth responses and improve our understanding of naturally forced warm periods. The project outcome is therefore highly topical as it directly impacts the simulation of future climate relying on a realistic representation of pre-instrumental temperature variability. MONOSTAR will thereby not only fix a long-standing limitation of contemporary dendroclimatological research but support a number of other disciplines studying climate change and impact on ecology and society. The enormous data from the hemispheric and high-resolution networks, as well as the models and code, will freely be made available to stimulate subsequent paleoclimatic and ecological studies.