Our group uses and improves atmospheric transport models to enhance our current understanding of the carbon cycle and provide informed support for mitigation efforts. We use the transport models to simulate the dispersion of greenhouse gases (especially carbon dioxide and methane) to compare between reported emissions and measured concentration. The comparison allows conclusions about the location, timing, and magnitude of sources and sinks.
Greenhouse gases on different scales
Greenhouse gases are dynamically distributed in the global atmosphere. Therefore, in addition to sources and sinks, transport processes influence the actual concentration in the atmosphere. These transport processes act on scales ranging from global over regional to local. We, therefore, use different models to map the relevant processes on the respective scales:
Global atmospheric inverse model transport prior surface fluxes forward and assimilate measurements to generate global modeled atmospheric concentrations. By varying the surface fluxes, the differences between measured and modeled concentrations are minimized. In collaboration with Sourish Basu (Earth System Science Interdisciplinary Center, University of Maryland), we use the TM5-4DVAR transport model with input from meteorological data to determine the effects of transport and emissions on a continental scale. TM5-4DVar employs a 4-D variational method and optimizes fluxes on a 6° × 4° longitude–latitude grid.
To analyze mesoscale phenonoma, we use the Weather Research and Forecasting (WRF) Model to simulate the transport of greenhouse gases in the atmosphere. WRF is a modular Eulerian mesoscale model, which simulates atmospheric dynamics based on actual atmospheric conditions or idealized conditions. It allows for nesting a higher-resolved "child" domain in a coarser "parent" domain to zoom into specific regions. WRF-Chem simulates CO2 concentrations by coupling the atmospheric dynamics to CO2 surface fluxes. Our group runs the WRF-Chem model on high resolution to design and evaluate cost-effective observation strategies for fossil CO2 emissions from German metropolitan areas. Furthermore, by coupling with a Langrangian model, we will develop an inversion scheme.
To support political decision-makers in their mitigation efforts, inner-city-resolved CO2 information is needed. The high-resolution transport model GRAMM/GRAL is composed of a mesoscale model (GRAMM) coupled with computational fluid dynamics (CFD) modeling (GRAL). It is a Reynolds Averaged Navier Stokes (RANS) model that can run at 10m x10m resolution over long periods, ranging from months to years. The high temporal and spatial resolution makes the model suitable for monitoring suburban greenhouse gas dispersion. To achieve the required high spatial and temporal resolution with the available computational capacity, the GRAMM/GRAL model uses a so-called "catalog approach": the model simulates a catalog of stationary wind situations for different stability classes, wind speeds ,and wind directions. These 1000+ catalog entries represent a hypothetical simulated wind field library. We choose the wind field by minimizing the differences, between observed and simulated wind speed and direction. The group is collaborating with the group of Prof. Dr. Dominik Brunner (EMPA).
...from natural to social sciences and with stakeholders!
The work in the group benefits from the close scientific cooperation of researchers at Heidelberg University. Our overarching goal is to advance climate research in an action-oriented manner. The Heidelberg Center for the Environment (HCE) bundles the activities from different disciplines. Also, the group benefits from a lively exchange with decision-makers e.g. the city of Heidelberg. In this context, we apply the research results in a needs-oriented manner.
Dr. Sanam Vardag
Institut für Umweltphysik
Im Neuenheimer Feld 229 (3rd floor, room 330)
Phone: +49 6221 54 6511
Email: svardag ( at ) iup.uni-heidelberg.de
Dr. Sanam Vardag (group leader)
Leonie Kemeter (Master candidate)
Christopher Lüken-Winkels (PhD candidate)
Robert Maiwald (Master candidate)
Maximilian May (PhD candidate)
Eva-Marie Metz (PhD candidate)
Anna Sommani (PhD candidate)
Lukas Pilz (PhD candidate)
Lea Lilli zur Lage (Projektpraktikum)
Simone Wald (M. Sc)
Christopher Lüken-Winkels (M. Sc)