Cluster C- Projects

C01

Land surface and sub-surface data assimilation


Dr. Anne Springer
University of Bonn  |  +49 228 73-6149  |  [Email protection active, please enable JavaScript.]

Dr. Carsten Montzka
Forschungszentrum Jülich  |  +49 2461 613289  |  [Email protection active, please enable JavaScript.]


Summary

In C01 we will develop a coupled multi-scale, multi-source data assimilation (DA) system at the continental scale, where remotely sensed surface soil moisture, total water storage changes and land surface temperature data will constrain a coupled reanalysis from groundwater to the land surface. We will evaluate to what extent the reanalysis exhibits skill to represent observed trends, reproduce interannual variability, and to simulate extreme events. A special focus is laid on investigating strategies to correct for anthropogenic impacts on the hydrological system (irrigation, groundwater abstraction) through DA.

 

C02

Modulation of soil water fluxes by changes in vegetation properties and management


Prof. Dr. Frank Ewert
University of Bonn  |  +49 228 73-2041  |  [Email protection active, please enable JavaScript.]

Dr. Thomas Gaiser
University of Bonn  |  +49 228 73-2050  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Guillaume Lobet
Forschungszentrum Jülich  |  +49 2461 61-9013  |  [Email protection active, please enable JavaScript.]


Summary

We will investigate the impact of changes in agricultural and forest management during the last decades on land surface – atmosphere interactions. We will improve the parameterization of land surface model CLM so that it can reproduce the effects of changes in management on regional heat, water and carbon fluxes. Therefore, we will link a suite of models starting from mechanistic single plant models that couple carbon and water flow within the plant with the external environment over specific crop models at the field scale to the Community Earth System Model CLM.

 

C03

Towards ecosystem reanalysis by coupling of water and carbon cycles


Prof. Dr. Harrie-Jan Hendricks-Franssen
Forschungszentrum Jülich  |  +49 2461 614462  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Wulf Amelung
University of Bonn  |  +49 228 73-2780  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Jürgen Kusche
University of Bonn  |  +49 228 73-2629  |  [Email protection active, please enable JavaScript.]


Summary

For simulating the impact of land use and land cover change on the water and carbon cycles, modelling of soil respiration and photosynthesis has to be improved. We hypothesize that continental-scale net ecosystem exchange (NEE) from a reanalysis with improved ecosystem parameters and refined representation of soil respiration (SR) will better explain observed total water storage (TWS) variability. To test this hypothesis, we will estimate ecosystem parameters from long time series at highly equipped sites in combination with measured temperature and soil moisture sensitivity of heterotrophic soil respiration. Model outputs will then be compared with changes in TWS observed by GRACE.

 

16 | PhD student
in the field of land surface modelling

75% (E13 TVöD) | All positions are fixed-term, initially until December 31st, 2025, with the possibility of an extension

In project C03, we are looking for a PhD student in the field of land surface modelling, with a background in hydrology and/or ecology, modelling experience and a good background in statistics. Experience with inverse modelling or data assimilation would be of advantage.

 

C04

Snow data assimilation and its impacts on hydrological cycle and atmospheric fluxes


Dr. Bibi S. Naz
Forschungszentrum Jülich  |  +49 2461 619717  |  [Email protection active, please enable JavaScript.]

Prof. Dr. Gabrielle J. M. De Lannoy
KU Leuven, Belgium  |  +32 1637 6713  |  [Email protection active, please enable JavaScript.]


Summary

In C04, we aim to improve continental-scale snow estimates in land surface model which often bear uncertainties due to both input data and model errors. For this purpose, we will develop and implement a multi-scale, multi-sensor snow data assimilation scheme in the fully coupled terrestrial systems modeling platform. This will be implemented by jointly assimilating the remote sensing snow observation such as snow cover fraction and snow water equivalent into the community land model (CLM). Further, we will assess the impact of snow data assimilation on surface energy states and fluxes for fully coupled land-atmosphere simulations.

 

19 | PhD student
in the field of remote sensing and snow hydrology

75% (E13 TVöD) | All positions are fixed-term, initially until December 31st, 2025, with the possibility of an extension

In project C04, we are looking for a PhD student in the field of remote sensing and snow hydrology, with a background in hydrology, hydrological modelling and remote sensing. Experience in data assimilation and programming skills would be of an advantage.

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