Investigating time-series and spatial fields from environmental archives to inform about past and future dynamics of climate and biodiversity

Our planet is undergoing an unprecedentedly rapid transformation. To predict future climate and environment dynamics, we have to learn from past time-series derived from observations as well as proxy data from natural archives to the full range of relevant time-scales. 

Paleoenvironmental proxies such as pollen, foraminifera and sedimentary ancient DNA contained in marine or lake sediments can provide the required information, but they are sparse, inherently noisy and at times provide contradictory evidence. This hampers both the quantitative reconstruction of earth system processes and the systematic testing of model outputs.

In the first part of the colloquium, we will introduce how proxy data are generated and how they are used to assess past changes in biodiversity and climate change and what their typical limitations are. In the second part we will focus on how they are used to assess climate variability. In order to adapt to future climate change we should not only understand changes in the mean state but also to the magnitude of climate variability. Whereas synoptic to interannual variations in the climate system are well documented,and current climate models are generally able to simulate them realistically, much less is known about the amplitude and mechanisms of climate variability on longer time-scales. Estimating that variability forms the basis for the detection and attribution of the anthropogenic component, determines the range of plausible future climate changes, and also provides information about the time-scales of the earth system components.