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CEN - Center for Earth System Research and Sustainability
Centerfor Earth System Research and Sustainability (CEN)

Photo: DKRZ

Climate & Earth System Models

CESAM - CEN Earth System Assimilation Model

The CESAM is a numerical Earth System Model build by coupling the MITgcm (MIT General Circulation Model) ocean model to the Plasim (Planet Simulator) model system.

The relevant components of Plasim include the spectral PUMA model including schemes for radiation, cloud cover, precipitation, runoff, soil temperature and wetness, surface fluxes, a thermodynamic sea ice model, and a terrestrial biosphere component (SIMBA).

The MITgcm is a state of the art finite volume model of the general oceanic circulation, including a model of sea-ice dynamics and rheology. The non-hydrostatic formulation enables the simulation of processes much smaller than the meso-scale. It is also designed to study the atmosphere and climate by employing a fluid isomorphism.

The CESAM code is designed to allow for the generation of tangent linear and adjoint code by automatic differentiation of the source code through TAF (Transformation of Algorithms in Fortran) available at FastOpt, i.e. efficient tangent or adjoint codes can be generated from the CESAM source code.

Applications of adjoint models include parameter and state estimation problems as well as sensitivity studies.

Contact: Dr. Armin Köhl, Email: koehl"AT"ifm.uni-hamburg.de(koehl"AT"ifm.uni-hamburg.de)

Publications:

Köhl, A., & Vlasenko, A. (2019). Seasonal prediction of northern European winter air temperatures from SST anomalies based on sensitivity estimates. Geophysical Research Letters, 46(11), 6109-6117.

Lyu, G., Köhl, A., Matei, I., & Stammer, D. (2018). Adjoint‐based climate model tuning: Application to the planet simulator. Journal of Advances in Modeling Earth Systems, 10(1), 207-222.

Stammer, D., Koehl, A., Vlasenko, A., Matei, I., Lunkeit, F., Schubert, S. (2018). A pilot climate sensitivity study using the CEN coupled adjoint model (CESAM). Journal of Climate, 31, 2031-2056. https://doi.org/10.1175/JCLI-D-17-0183.1

Blessing, S., Kaminski, T., Lunkeit, F., Matei, I., Giering, R., Köhl, A., Scholze,M., Herrmann,P., Fraedrich,K., & Stammer, D. (2014). Testing variational estimation of process parameters and initial conditions of an earth system model. Tellus A: Dynamic Meteorology and Oceanography, 66(1), 22606