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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - SPACE (Space-time structure of climate change)

Teaser

Summary

In order to understand and predict the human influence on climate, it is particularly important to quantify the structure of internal climate variability and the sensitivity of the climate system to external forcing. Empirical evidence and physics suggest an intrinsic link between time scale and the associated spatial scale of climate variations: While fast variations such as weather are regional, glacial-interglacial cycles appear to be globally coherent. SPACE quantifies this presumed tendency of the climate system to reduce its degrees of freedom on longer time scales and uses it to constrain the sparse, noisy and at times contradictory evidence of past climate changes and to inform us about the amplitude, origins and mechanisms of climate variability.
By systematically analysing instrumental and paleo-records, we 1) determine the space-time structure of climate changes on annual to millennial time scales. This provides the prerequisite for mapping past climate changes and allow to confront climate models with robust estimates of climate variability across spatial scales; 2) provide a clearer separation of internal and external forced climate variability, by leveraging their distinct space-time structures; 3) examine the past relationship

Work performed

During the 18-month period covered in this report key staff was hired, the statistical basis was to estimate the space-time structure of climate variability from instrumental and paleo-data was established, a set of replicate sediment cores were analysed, the planned equipment was purchased and multiple research papers were published. A team of 3 postdocs, 1 PhD student and two student helpers was assembled to cover research components in all work packages. Several invited talks were given at international conferences and seminars. The team developed new methods to estimate the time-scale dependent spatial structure and applied this to climate model and instrumental data. At the same time, we analysed replicate proxy records cores to better separate local from large-scale climate variability and to characterize the time-uncertainty in proxy records. Both developments now set the basis for an estimate of the space-time structure from annual to millennial time-scales by combining instrumental observations and various paleo-climate archives. We also achieved the first quantitative reconstruction of changes in temperature variability between the Last Glacial Maximum and the Holocene based on a global network of marine and terrestrial temperature proxies in order to study the mean state dependency of climate variability. We found that the overall pattern of reduced variability could be explained by changes in the meridional temperature gradient, a mechanism that may point to further decreases in temperature variability in a warmer future. Finally, we estimated the signal to noise ratio of Holocene and Glacial temperature reconstructions. As the estimated signals to noise rations are rather low we decided to develop and optimize a method to reconstruct fast climate variability from sediment cores (Individual Foraminifera Analysis) to be able to further refine our estimates how climate variability may change in warmer world.

Final results

We derived the first time-scale dependent estimators for spatial degrees of freedom that allow us to characterize the space-time structure of gridded datasets and can be extended to also characterize the structure of the sparser paleo-datasets. We achieved the first quantitative reconstruction of changes in temperature variability between the Last Glacial Maximum and the Holocene. We characterized for the first time the information content of Holocene and Glacial compilations of temperature proxies and provided the first systematic characterization of the information contained in Individual Foraminifera Data, a new proxy to estimate climate variability from sediment records. All these advances all set the basis to systematically characterize and use the space-time structure of climate variability for a better understanding of the climate system.
Until the end of the project, we expect to have estimated the space-time structure of climate changes on annual to millennial time scales; a crucial step for mapping past climate changes. We further expect to leverage the distinct space-time structures of forced versus internal variability and disentangle the origins of climate variability during the Holocene, last millennium and last century. Finally, building on our first results and Individual Foraminifera Data we expect to know how seasonal to millennial climate variability has changed between colder and warmer climate states; test the ability of climate models to reproduce these changes and thus get a clearer picture how variability will change in a warmer future.