Earth System Diagnostics

Quantitiative interpretation of paleoclimate data

I enjoy working across disciplines and combining observational data, statistics and modeling. My current research focus is the estimation of climate variability and the mean temperature changes in the current warm period, the Holocene. This knowledge is relevant for predicting the spread of future climate changes and allows a direct test of climate models. In the ECUS project, I’m coordinating a small team of researchers and students and working on a better use of the paleoclimate record to sharpen our knowledge about the climate system.

The spectrum of climate across climate zones and states and relevance for modelling future climate variability

I am a PostDoc in the PalMod project. I use palaeoclimate proxies to characterise continental-scale and global climate variability across the last glacial cycle. Given the noisy and biased nature of palaeoclimate proxy data, much of my research involves quantifying proxy-specific processes to be able to distinguish climate variability signals from artefacts due to proxy recording. Extracted information on spatio-temporal climate variability provides the observational basis to test the ability of Earth System Models utilised in the PalMod project to simulate the full spectrum of climate and to study the implications of the proxy-based inferences for future projections of climate variability. Special attention is paid on investigating spatial patterns of low-frequency climate variability to provide insights on the importance of internal and external mechanisms in driving long-term climate variability.

High resolution SST proxies.

My PhD project is based on mass spectral imaging of marine sediment cores to create high temporal resolution sea surface temperature time series. The aim is to quantify stratigraphic noise and the spatial representativeness of marine proxy records. With this newly gained confidence about the robustness of the proxies it becomes possible to reconstruct climate variability on societal relevant time scales and to evaluate climate models.

The project is part of ERC SPACE (Space-time structure of climate change) and the RECORDER research unit of the cluster of excellence: “The Ocean Floor – Earth’s Uncharted Interface”. It is joint effort of the Earth System Diagnostics group of Alfred-Wegener-Institut, Potsdam and the Organic Geochemistry group of MARUM, Bremen.

Paleo-Climate reconstruction using Bayesian methods

My PhD project aims to reconstruct past surface temperature evolution from borehole temperature measurements. Initially, a forward heat transfer model is implemented that predicts borehole temperature profiles for a given time dependent surface temperature. This model is inverted to reconstruct the surface temperature of the past from borehole temperature measurements. Existing inversion methods for boreholes are highly model-dependent. This project aims to improve the borehole inversion methods as well as the climate field reconstruction technique by optimally combining various information sources, like water isotope data from ice cores with the spatial covariance structure from simplified climate models or reanalysis data.

Insights from tree-ring records into past climatic changes

Originally trained as a forest ecologist, I came to paleoclimatology through dendrochronology – the study of tree rings. Tree rings offer unique insights into past climate variability, but in order to use then as proxy records for climate researchers much first disentangle a variety of biological, climatic, and ecological influences on tree growth to extract the signal of climate. I came to Potsdam as a postdoc to lend my expertise in dendrochronology to the ESG research group. Prior to arriving in Germany, I completed a Master’s and PhD at the University of Minnesota, in the USA.

Interpretation of temperature signals derived from ice cores

Ice cores are a key archive to reconstruct millennial-scale climate changes in temperature, but are, due to the inherent noise levels of the proxy data, less reliable in recording the smaller Holocene climate variations. However, quantitative knowledge of the natural Holocene polar climate variability is a key to determine the range of plausible future anthropogenic climate change.

My Ph.D. project aims at improving our understanding of the climate signal and the
non-climate variability recorded in water isotopes from polar ice cores. Currently, I use extensive isotope data obtained from the two-dimensional sampling of snow trenches at Kohnen station, Antarctica, to disentangle these two contributions. Of my work I particularly like to combine the observations with statistical modeling and numerical  approaches to understand the physics of the ice-core proxy recorder system.

Quantifying Natural Climate Variability in Space and Time​

My research aims to combine evidence from a wide range of climate sensitive proxies and model simulations in order to build a comprehensive picture of climate variability over land and ocean, and across scales. In the recent past when instrumental data are available, internal fluctuations were intermingled with the forced human-induced warming and hard to study objectively. At the local scale, their magnitude is thought to be of similar magnitude as that of the human-induced warming, and they may thus significantly offset or further future warming. It is thus essential to better characterize the internal climate fluctuations characteristic of multi-decadal timescales and longer using paleoclimate data and achieve consistency with model simulations used for future projections. My PhD work has focused on the spatial structure of millennial scale temperature variability using a large database of pollen-based reconstructions combined with the analysis of instrumental data and model simulations.

Variability of Vegetation and Climate

My PhD project started in July 2021 and focuses on quantifying the variability of vegetation in the Northern Hemisphere. Especially in models, vegetation is often expected to directly respond to climate. However, in reality, this is likely not the case. By using paleoecological data, and reconstructed and modeled climate data, I aim to find out more about which climate-independent vegetation dynamics exist and what their causes might be. During my time as a PhD candidate at AWI also participated in expeditions to describe arctic vegetation and quantify biomass in Siberia (2021) and Canada (2022).

My background is in Environmental Sciences with a focus on ecology and my main research interests include climate-vegetation interactions, climate change biology and conservation, and data science for ecology and climatology.

Variability of past climate from proxies

I started out as an ecologist, but now I study the variability of past climate. My research focusses on how best to work with the error and uncertainty in proxy records so that we can correctly understand past climate events and variability. I have created models and R packages for forward modelling sedimentary climate proxies (sedproxy), and calculating timescale dependent proxy error (psem). I also have an R package (hamstr) for age-depth modelling of sediment cores. While at AWI I have been working for the Palmod project, I will soon start a new DFG funded project looking at climate proxies from coral archives.

Climate variability based on ice core isotope records

Increasing the usability of high-resolution firn cores from the East Antarctic Plateau as a climate proxy would enhance our understanding of the Holocene climate system as well as local impacts of human-induced global warming. To achieve this, I assessed the amount and drivers of stratigraphic noise within stable water isotope records across the East Antarctic Plateau (master's thesis 2020/21). This will enable us to predict, model and correct for this noise and to make adjusted decisions on sampling locations within the next expeditions.

After my masters thesis, I worked in a project on dendro-climatology. However, I came back to the ESD team in June 2022: I plan to investigate natural climate variability within the Holocene based on ice core isotope records from Greenland and Antarctica. This can help verifying climate models and assessing variability changes with global warming. I will also elaborate on forward modeling of the isotopic climate signal in ice cores and inherent noise processes.

Estimating and accounting for diffusion in deep ice cores

The currently ongoing Beyond EPICA Oldest Ice Core drilling project offers an exciting opportunity to recover ice dating back to 1.5 million years ago. Thus the stable water isotopes in this ice core could be used to reconstruct the temperatures over this time period, including the enigmatic Mid-Pleistocene Transition. However, due to ice diffusion and the extreme thinning of the ice layers at the bottom of the ice core, the oldest section of the record is greatly smoothed, causing a loss of information up to millennial timescales.

My PhD project aims to correct for this diffusion, first quantifying it by estimating the diffusion length in the Dome C ice core, and then applying a deconvolution technique to back-diffuse the isotope signal. This will involve statistical methods and spectral analysis of the isotope time series, where the effect of diffusion is simpler to calculate. I will also explore a new measurement technique with the aim of minimising the measurement noise, which will allow more high frequency information to be restored and therefore produce a better reconstruction of the past climate.

Investigation of the process of signal formation in paleo climate archives

My PhD project aims for a better understanding of the process of signal formation in paleo climate archives (e.g. ice cores, marine sediments). For this, I am investigating the imprint of the temperature signal in firn and ice cores by analysing the relationship between changes in the snow surface height and changes in the isotopic composition in the upper snow layer. This project contains practical work during field work and in laboratories as well as theoretical work and statistical analyses. A comparison of the measured isotopic composition in surface snow to a simple isotope model based on meteorological parameters from our study site, allows us to estimate the contribution of different processes (e. g. snowfall, wind-driven redistribution, diffusion, sublimation) to the final isotopic signal. This work aims to contribute to a (possible) improvement of climate reconstructions from ice cores.
As a second climate archive, I will explore the horizontal and vertical variability and heterogeneity of marine sediments by measuring and analysing the parameters d18O and Mg/Ca, which are usually used to reconstruct temperature, as well as the radiocarbon age in a two dimensional way from a box core.

A spectral view on the space-time structure of climate variability

My research focus is on the characterization of the space-time structure of climate variability across a large range of scales. In particular, a spectral view is adopted such that the scaling behaviour in both space and time (i.e., in the wavenumber and frequency domain) can be investigated. This type of analysis is applied to the output of long paleo-climate model simulations, to reanalysis and to instrumental data, and it is compared to stochastic-diffusive energy balance models, for which the spectral scaling behaviour can be obtained analytically.

All in all, my aim is to achieve an as simple as possible conceptual picture of the spectral space-time structure, in order to (i) provide a systematic basis for time-scale-dependent interpretation of paleo-climate proxies, and (ii) to help distinguish between externally driven versus internal variability of the climate system, by searching for characteristic spectral space-time fingerprints of these components.

Specifically, I am currently developing spectral measures of the effective spatial degrees of freedom of large-scale climate fields, and I am also investigating the frequency-dependent spatial spectra of climate model simulations with different external forcings by decomposing fields into spherical harmonics.

Reconstructing past ocean water conditions using geochemistry in foraminifera

I am a paleoceanographer using the geochemistry of the calcite shells of foraminifera, single-celled organisms, to reconstruct how water mass conditions have changed in the past and how they may change in the future. I also work to develop the tools we use for these reconstructions, which are called proxies by investigating how under modern conditions different geochemical signatures are incorporated into the shells. Within ECUS and SPACE I am contributing the geochemical part to the question what is determining proxy-variability, i.e. what variability is natural and what is caused by analytical and procedural uncertainties. This will show how we can use the natural variability in proxy data as additional parameters recording climate change, e.g. seasonal or ENSO-variability.

Statiscal methods for Holocene climate variability analysis

I started a PhD at AWI in summer 2020. My PhD project is about centennial to millenial Holocene climate variability and based on tropical marine sediment core data and statistical method development. The aim is to understand how much of the total variability in the temperature proxy data of those cores represents an imprint of a climate signal and what variability component has to be considered as noise.

My background is mathematics and philosophy and I am particularly interested in theoretical and statistical aspects of climate research.