Investigating past climate states is important for understanding the dynamics of the Earth's climate system and for validating climate models. The Last Glacial Maximum (19-23 ka, LGM) was a climatic state substantially different from today and the main patterns of the ocean circulation during this time remain uncertain. Results from proxy data and models show significant differences. Combining climate models with proxy data via data assimilation is a powerful means to obtain more reliable estimates of the climate state. Data assimilation is frequently used in the field of weather forecasting, but it is still not well-established in the community of paleo climatology.
In my PhD project I work on the development and application of data assimilation methods to estimate the ocean state during the LGM. I employ the Massachusetts Institute of Technology general circulation model (MITgcm), which includes a water isotope module that simulates stable water isotopes in the whole water column such that d¹⁸O data reconstructed from benthic and planktonic foraminifera can be assimilated.
The project consists of two parts. In the first part I utilize the so called adjoint method for variational data assimilation. The adjoint method is comparatively powerful and has been applied successfully in the past, but it requires so called “automatic differentiation” (AD) of the model code. The MITgcm was developed for this purpose, but AD cannot be applied to many other models. The second part of my project consists of the development and application of a new method that does not require AD. The new method will be applied to estimate the LGM ocean state and the results can be compared to results obtained from the adjoint method.
C. Breitkreuz, A. Paul, T. Kurahashi-Nakamura, M. Losch, M. Schulz. A dynamical reconstruction of the global monthly mean oxygen isotopic composition of seawater, Journal of Geophysical Research: Oceans, 123, 2018. https://doi.org/10.1029/2018JC014300
C. Breitkreuz, A. Paul, P. J. van Leeuwen, M. Schulz. A new particle filter method to estimate the state of the ocean during the Last Glacial Maximum, EGU General Assembly, Vienna, Austria, April 2018
T. Kurahashi-Nakamura, A. Paul, C. Breitkreuz, J. García-Pintado, M. Losch. Evaluating the performance of a numerical ocean model by a comparison with a paleoceanographic state estimate for the LGM, EGU General Assembly, Vienna, Austria, April 2018
C. Breitkreuz, A. Paul, T. Kurahashi-Nakamura, M. Losch, M. Schulz. A dynamical reconstruction of the pre-industrial ocean state constrained by global d¹⁸O data, EGU General Assembly, Vienna, Austria, April 2017
|03/2016 - today||PhD student at MARUM|
|9/2017 - 11/2017||Research stay at the University of Reading, UK|
|2013 - 2016||
M. Sc. Industrial mathematics with application field geosciences, University of Bremen
|2009 - 2013||
B. Sc. Industrial mathematics with application field geosciences, University of Bremen
|9/2011 - 3/2012||
Erasmus semester at the Universtiy of Gothenburg, Sweden