Eduardo Weide Luiz: (Uni Köln)
Local assessment of renewable energy potential: The students will do a case study for the renewable energy potential of Lindenberg. Data from a day during FESSTVaL will be analysed, e.g., using wind lidars, all-sky imagers, and radiation measurements. This can include an estimate of PV and wind power using simple models. The aim is to develop an understanding of the temporal changes in meteorological conditions that influence the PV and wind power production.
Felix Ament (Uni Hamburg)
Chasing cold pools in a network: We will try to generate a big picture of cold pools. Therefore the spatial Apollo and WXT anaylsis of (hopefully) selected cold pool events are merged with radar observations (both local X-Band radar and DWD C-band radar) and satellite observations (Meteosat high resolution, visibilty) to link the near surface processes with cloud and precipitation dynamics.
Henning Rust (FU Berlin)
Integrating a Citizen Science Instrument into a professional network: Assemble a low cost citizen science instrument and evaluate it against professional instruments, also employing calibration chamber. Develope mulitvariate adjustment functions (e.g. for temperature and pressure) in order to correct for radiation errors etc. .
Ulrich Löhntert (Uni Köln)
Analysis of time synchronous ABL profiles: Analysis of ABL sub-mesoscale scale variability by means of additional, time-synchronous remote sensing and radisonde profiles of temperature and humidity distributed witihin the FESSTVaL domain. The goal is to educate students in ground-based remote sensing as well as in in-situ profiling with radiosondes. In addition, a goal is to detect sub-mesoscale variability and to discuss its origins. On a suited day in the beginning of the summer school, the group will launch time-synchonized sondes at the profiler sites. The variability from site to site will be compared to the variability of the ground-based profilers as well as to data from the high-resolution surface network.
Cathy Hohenegger (Uni Hamburg)
Measurement of evapotranspiration (ET): Derive ET from soil moisture measurements taken during FESSTVaL using different theoretical ansatz. Compare those estimates to direct measurements of the surface fluxes and to model estimates. Investigate the effects of the surface conditions on the agreement between the different estimates, observations, and model output.
Dave Turner (Uni Oklahoma)
Characterizing cumulus properties using spectral infrared observations: Improving thermodynamic retrievals from ground-based remote sensors by including Doppler lidar vertical motions into the prior.Improving thermodynamic retrievals from ground-based remote sensors by including LCL information into the prior
Julian Quimbao-Duarte (Uni Frankurt)
Turbulence properties of the boundary layer during FESSTVaL: Models vs Observations: Two types of numerical model will be evaluated using the observations of the FESSTVal field campaign. Simulations will be carried out with a simple bulk model to resolve the atmospheric boundary layer. The field campaign observations will be used to drive and validate the model. In addition, simulations for the same events will be performed using a single-column model (SCM) and validated with the field campaign observations. Both types of simulations may be performed by all the students, or sub-groups can be organized to divide the tasks. Ideally, several events should be selected (for both 2020 and 2021) in which a strong diurnal cycle is observed for both clear and cloudy skies. The performance of each model concerning observations is expected to be measured and analysed. In addition, an intercomparison between models will be carried out to highlight the strengths and weaknesses of each model. The following questions are expected to be resolved through the exercise: When do the simple models do a good job? When is their performance poor? What role does non-local turbulence transport play? The ultimate goal of the project is for students to get an insight into both land-atmosphere coupling (e.g. moist and heat exchanges), and turbulence processes in the atmospheric boundary layer through numerical modelling.