Periodic Reporting for period 4 - GC2.0 (Global Change 2.0: Unlocking the past for a clearer future)
Berichtszeitraum: 2021-03-01 bis 2022-08-31
The overarching goal of the project was to understand how climate change affects the terrestrial biosphere and how changes in vegetation cover and other land-surface properties in turn affect the climate. The focus was on the examination of biosphere-climate interactions in the past, when the changes could be documented using palaeoenvironmental evidence from multiple types of record, in order to be able to evaluate how large the impacts might be under future climate changes. The palaeo-record provides examples of the response of the terrestrial biopshere to different external forcings and under climate states radically different from present. It also provides examples of rapid climate changes that were as fast and as large as those projected by the end of the 21st century.
An important part of the project was therefore to evaluate how well the state-of-the-art climate models capture past climate changes and changes in climate variability and extremes. To make these evaluations it was necessary to improve existing palaeoenvironmental data syntheses, to develop improved methods for making quantitative reconstructions of climate, vegetation and other land-surface properties, and to develop new models that translate climate variables into predictions of vegetation and fire regimes.
A major focus of the project was on developing a better understanding of the direct impact of changes in atmospheric carbon dioxide on key processes independently of the impact of climate changes on these processes, because of the need to understand the degree to which increasing carbon dioxide levels might offset the deleterious impacts of global warming on the terrestrial biosphere. In addition to an improved understanding of the role of the terrestrial biosphere in climate change and an assessment of the limitations of state-of-the-art models to simulate these influences, the project has laid the groundwork for the development of a simpler and more robust approach to modelling the land surface
An important part of the project was therefore to evaluate how well the state-of-the-art climate models capture past climate changes and changes in climate variability and extremes. To make these evaluations it was necessary to improve existing palaeoenvironmental data syntheses, to develop improved methods for making quantitative reconstructions of climate, vegetation and other land-surface properties, and to develop new models that translate climate variables into predictions of vegetation and fire regimes.
A major focus of the project was on developing a better understanding of the direct impact of changes in atmospheric carbon dioxide on key processes independently of the impact of climate changes on these processes, because of the need to understand the degree to which increasing carbon dioxide levels might offset the deleterious impacts of global warming on the terrestrial biosphere. In addition to an improved understanding of the role of the terrestrial biosphere in climate change and an assessment of the limitations of state-of-the-art models to simulate these influences, the project has laid the groundwork for the development of a simpler and more robust approach to modelling the land surface
We focused on expansion of pollen, charcoal, speleothem isotope and lake water-balance records of past climate changes. We addressed known limitations in pollen-based quantitative climate reconstructions methods, in particular the problem that regression techniques compress reconstructions towards the middle of the sampled climate range by accounting for sampling frequency and upweighting taxa with narrow climate ranges. Reconstructions of moisture-related variables using modern data cannot account of the physiological impacts of changing atmospheric CO2 on photosynthesis and overestimate dryness when CO2 is low. We developed a physiology-based method to correct this bias. We developed a new, quantitative approach to reconstruct past vegetation that takes account of within-biome compositional variability and can be used to make more realistic assessments of modelled vegetation changes. Sedimentary charcoal records are used to provide a semi-quantitative estimate of fire but are difficult to compare with modelled outputs. We developed a calibration of the charcoal record to produce quantitative estimates of burnt area.
Assessments of vegetation and fire models in both modern and past climate states show that they are only moderately successful in reproducing observations. We have analysed the causes of this and used novel analytical techniques to pinpoint areas for improvement. We developed a model to predict fire size, intensity and burnt area using climate, vegetation, topographic and ignition-related variables, and accounts for the influence of human activities on fire under modern conditions. We have also made progress towards a new vegetation model by using eco-evolutionary optimality theories to develop simple treatments of key processes including photosynthesis, respiration, gross primary production, allocation and plant hydraulics.
A major focus of the project was on evaluating the role of changes in atmospheric CO2 on vegetation, fires and other land surface properties. We have shown that lowering CO2 by ca 100 ppm influences vegetation productivity, causing a substantial reduction in forest cover over much of the world and increasing runoff. This lower CO2 is also the driver for reductions in burnt area at the LGM. It also has a significant impact on fire intensity, although atmospheric drying is also important for this.
The magnitude (and even the sign) of land-surface feedbacks to climate is a major source of uncertainty for climate predictions. Modern observations are too short to provide strong constraints on these feedbacks. We used the palaeorecord to provide estimates of the feedbacks from wildfires and biospheric greenhouse gas emissions. The positive carbon cycle feedback from increased fire is a large contribution to the overall climate-carbon cycle feedback on centennial time scales. Our estimates of greenhouse gas feedbacks show these are not well represented in current models, in particular published high- and low-end values for CO2, are unrealistic.
Assessments of vegetation and fire models in both modern and past climate states show that they are only moderately successful in reproducing observations. We have analysed the causes of this and used novel analytical techniques to pinpoint areas for improvement. We developed a model to predict fire size, intensity and burnt area using climate, vegetation, topographic and ignition-related variables, and accounts for the influence of human activities on fire under modern conditions. We have also made progress towards a new vegetation model by using eco-evolutionary optimality theories to develop simple treatments of key processes including photosynthesis, respiration, gross primary production, allocation and plant hydraulics.
A major focus of the project was on evaluating the role of changes in atmospheric CO2 on vegetation, fires and other land surface properties. We have shown that lowering CO2 by ca 100 ppm influences vegetation productivity, causing a substantial reduction in forest cover over much of the world and increasing runoff. This lower CO2 is also the driver for reductions in burnt area at the LGM. It also has a significant impact on fire intensity, although atmospheric drying is also important for this.
The magnitude (and even the sign) of land-surface feedbacks to climate is a major source of uncertainty for climate predictions. Modern observations are too short to provide strong constraints on these feedbacks. We used the palaeorecord to provide estimates of the feedbacks from wildfires and biospheric greenhouse gas emissions. The positive carbon cycle feedback from increased fire is a large contribution to the overall climate-carbon cycle feedback on centennial time scales. Our estimates of greenhouse gas feedbacks show these are not well represented in current models, in particular published high- and low-end values for CO2, are unrealistic.
1) Construction of the palaeoenvironmental and palaeoclimate databases and made available as public resources.
2) New methodologies have been developed and tested to make robust reconstructions of climate parameters, vegetation cover and fire regimes through time.
3) New protocols for climate model simulations have been developed and published.
4) Regional analyses of the palaeoenvironmental data have been carried out to determine the impacts of past climate changes on land surface processes.
5) Analyses of the drivers of changes in land surface processes in the modern era have been carried out in order to verify that there is good coherence between the palaeo and modern analyses.
6) Analyses of palaeoclimate model experiments made by members of the Palaeoclimate Modelling Intercomparison Project (PMIP), including evaluation against palaeoenvironmental and palaeoclimatic reconstructions, have been completed and published.
7) New process-based models of vegetation and fire have been developed, evaluated under modern conditions and applied with palaeoclimate scenarios in order to disentangle impacts of changes in climate from those of atmospheric CO2 on the terrestrial biosphere.
8) The role of anthropogenic drivers of changes in vegetation and fire regimes has been investigated in order to establish that persistent mismatches between climate model simulations and palaeoenvironmental observations are real and not a result of human interventions on the landscape.
9) Addressing the question of why climate models persistently fail to predict the effects of the land surface on regional climates showed that there are significant and fundamental problems with the current generation of land-surface models. In response to this, an entirely new approach to representing vegetation based on eco-evolutionary optimality theory has been developed within the project. Completion of the development of a new land surface model is beyond the scope of the current project, but the preliminary results stemming from GC2.0 research look very promising.
10) Project results have been disseminated via publications and presentations at conferences and workshops (including virtual meetings), with over 30 presentations at international meetings,70 papers published during the project, and a further 14 papers in progress.
2) New methodologies have been developed and tested to make robust reconstructions of climate parameters, vegetation cover and fire regimes through time.
3) New protocols for climate model simulations have been developed and published.
4) Regional analyses of the palaeoenvironmental data have been carried out to determine the impacts of past climate changes on land surface processes.
5) Analyses of the drivers of changes in land surface processes in the modern era have been carried out in order to verify that there is good coherence between the palaeo and modern analyses.
6) Analyses of palaeoclimate model experiments made by members of the Palaeoclimate Modelling Intercomparison Project (PMIP), including evaluation against palaeoenvironmental and palaeoclimatic reconstructions, have been completed and published.
7) New process-based models of vegetation and fire have been developed, evaluated under modern conditions and applied with palaeoclimate scenarios in order to disentangle impacts of changes in climate from those of atmospheric CO2 on the terrestrial biosphere.
8) The role of anthropogenic drivers of changes in vegetation and fire regimes has been investigated in order to establish that persistent mismatches between climate model simulations and palaeoenvironmental observations are real and not a result of human interventions on the landscape.
9) Addressing the question of why climate models persistently fail to predict the effects of the land surface on regional climates showed that there are significant and fundamental problems with the current generation of land-surface models. In response to this, an entirely new approach to representing vegetation based on eco-evolutionary optimality theory has been developed within the project. Completion of the development of a new land surface model is beyond the scope of the current project, but the preliminary results stemming from GC2.0 research look very promising.
10) Project results have been disseminated via publications and presentations at conferences and workshops (including virtual meetings), with over 30 presentations at international meetings,70 papers published during the project, and a further 14 papers in progress.