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Helmholtz Research School
Mechanisms and Interactions of Climate Change in Mountain Regions

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Description of Doctoral Projects 2015

Doctoral project 1:

Analysis of meso- and microscale hydrometeorological fluxes in TERENO preAlpine using WRF-LES

Supervisor: Prof. Dr. Harald Kunstmann (KIT/IMK-IFU, Research Group 'Regional Climate &
Hydrology', contact:

Mentors: Dr. Patrick Laux (KIT/IMK-IFU, Research Group 'Regional Climate & Hydrology'),
Dr. Matthias Mauder (KIT/IMK-IFU, Research Group 'Transport Processes in the Atmospheric Boundary Layer (TABLe)')

Affiliation: KIT/IMK-IFU Garmisch-Partenkirchen & University of Augsburg


State-of-the-art regional climate models are limited by their grid resolution, i.e. they cannot adequately capture the small-scale spatial variability of meteorological dynamics and land–atmosphere exchanges. This is particularly true over complex terrain. Large eddy simulation (LES) is a mathematical concept for turbulence used in computational fluid dynamics, which allows one to resolve large eddies in the atmospheric boundary layer at resolutions in the order of tens of meters. These simulations are expected to offer a more realistic representation of surface- and near-surface flows, and thus may better capture the surface heterogeneity in these flows. Currently, real-world meteorological LES applications are rare because of lacking realistic fine-scale boundary conditions. TERENO preAlpine, and in particular ScaleX will provide the technical infrastructure to initialize and validate real-case LES simulations, and MICMoR will contribute to a better structured cooperation between different research groups.


  • Identification of optimal configuratons for nested WRF-LES runs for the TERENO preAlpine region (e.g. Fendt site) in order to allow realistic fine-scale boundary conditions for small-scale LES simulations (e.g. PALM-LES model) and
  • Conducting real-case LES simulations for TERENO preAlpine and investigate whether increased resolutions and finer scales allow to improve the description of hydrometeorological fluxes at the surface (e.g. latent and sensible heat, precipitation).


Following a multiple nested approach, mesoscale WRF stand-alone and WRF-LES will be applied for real-world simulations aiming at final resolutions of 50m. Lateral boundary conditions derived by reanalysis data and different physical parameterizations for PBL, radiation and convection will be applied. The performance of each nesting step will be analyzed. It is expected that the WRF-LES output will provide more accurate 3d initialization data to conduct real-case LES simulations at horizontal resolutions of 10m. In a first attempt, cloud-free episodes will be conducted to avoid errors related to the WRF cumulus and radiative parameterizations. Later on, the performance of LES simulations for cloudy situations will be analyzed.


Doctoral project 2:

Climatic impacts on phenology of grassland and crops along a transect through altitudinal zones using remote sensing

Supervisor: Prof. Dr. Christopher Conrad (University of Würzburg, Institute of Geography and
Geology, Würzburg; contact:

Mentors: Dr. Doris Klein (German Aerospace Center (DLR), German Remote Sensing Data Center, Oberpfaffenhofen), Dr. Sarah Asam (European Academy of Bozen (EURAC), Institute for Applied Remote Sensing, Bozen, Italy)

Affiliation: University of Würzburg


Phenological development of plants is very sensitive to climate variability. Even in managed ecosystems climatic variations are the determining factor for phenological development. Accurate information about the long term occurrence of distinct phenological stages in turn would enable the detection of trends of e.g. the onset of the vegetation period. Having information about such trends especially along a climatic gradient would show the effect of ongoing changes in terms of climatic factors (e.g. temperature, precipitation, onset of snow melt) on vegetation cover. Spatially distributed phenological data could hence help to identify phenological sensitivity of vegetation cover to ongoing changes depending on the geographic settings (topography, soil, climate). There are numerous studies on the use of remote sensing for detecting phenological patterns/phases from remote sensing time series. However, there is still a mismatch between observed phenological patterns at the plant level and land surface phenological features, which can be derived from remotely sensed time series. One major limitation is the scale difference, because remote sensing pixels usually consist of a number of species whilst in situ observations refer to individual species.


The aim of the dissertation is to improve approaches for detecting spatio-temporal phenological patterns of grassland and crops from the submontane to the lowland level at the example of an altitudinal gradient through the Ammer Catchment (TERENO pre-alpine). A multi-stage approach is envisaged to close the gap between in situ observations and satellite remote sensing.


It is suggested to move the PhD towards a modeling of actual phenology, e.g. by applying machine learning algorithms or comparable approaches such as mixed-effect-modeling on a big data cube. This approach can make use of remote sensing observations (optical and SAR, e.g. provided by Sentinel-1/2), meteorological observations available through the TERENO observation network, results of phenophase approaches (e.g. growing degree days), soil characteristics, and topographic (elevation, slope, aspect) information for precise modeling of BBCH observations of agricultural crops and extensively managed grasslands (e.g. Natura 2000 sites). The daily alpine-wide snow cover and vegetation index time series (2002 – 2014) and derived products generated at coarse resolution by EURAC could be also used as input for phenological time series analysis.
It is foreseen to complement the conducted analysis with meteorological and phenological data collected at other inner Alpine observation sites such as the Mazia valley or the Ahrntal in order to increase the sample plots at different alpine altitudinal, expositions, and climatological growth conditions. Comparisons with data collected in other TERENO sites (Harz-Central German Lowland Observatory, Northeastern Germany lowland observatory), which represent the lowland altitudinal zones, are also envisaged to assess the results for their robustness, transferability and significance.


Doctoral project 3:

Emission of allergenic grass pollen from TERENO prealpine observatory sites

Supervisor: Prof. Dr. Annette Menzel (TUM München-Weihenstephan, Dept. Ecology and Ecosystem Management, Professorship of Ecoclimatology, contact:

Mentors: Prof. Dr. Susanne Jochner (Katholische Universität Eichstätt-Ingolstadt), N.N.

Affiliation: TUM München-Weihenstephan


Grass pollen is the most common cause of respiratory allergies in Europe associated with >50% of allergic rhinitis. With climate change, an earlier start, but also longer pollen season have been observed, an increase of pollen amounts for many genera most likely due to higher atm. CO2 concentrations as well as increasing prevalence rates. Diurnal, intra-seasonal and inter-seasonal variability of grass pollen concentrations have been reported e.g. for Australia as well as regionally varying concentrations in Berlin, Germany and Aarhus, Denmark. A clear management effect of constant hay cutting dates vs. advancing flowering dates has been detected for Germany. Out of >10000 species in the grass family, the most abundant pollen emitters are timothy, orchard grass, meadow foxtail and rye and thus the choice of species matters. A low release height and short atmospheric suspension time leads to small footprint areas and thus facilitates prevention by management options. This study will integrate the MICMoR research fields of biosphere (grassland TERENO sites) and atmosphere (biogenic aerosols) with climate change and land-use / agricultural management.


  • To assess and study the impacts of global / climate change, elevation and management on timing, amount and regional transport of allergenic grass pollen at the TERENO preAlpine observatory Ammer-catchment.
  • To provide information about management options reducing concentrations and thus grass-induced pollinosis.


  • Analyse long-term changes and their drivers based on phenological data of the German Weather Service, pollen trap data of the PID (Polleninformationsdienst) and phenological camera as well as snow height sensor data of TERENO.
  • Identify spatiotemporal patterns of grass flowering and atm. pollen concentrations derived from Burkhard pollen traps running at UFS Schneefernerhaus, KIT Garmisch and at a new site in the Graswang-Rottenbuch-Fendt-region and relate them to meteorological parameters (TERENO), circulation types, long-range transport (HYSPLIT, FLEXTRA), land-use information (CORINE, remote sensing), and regional phenological surveys.
  • Determine events with relevant concentrations inducing hay-fever symptoms assessed from continuously running pollen traps as well as locally during short-term measurement campaigns using 10 personal pollen samplers and airborne pollen sampled with unmanned aerial vehicles.
  • Assess various agricultural management options including testing of seed mixtures in experiments [cooperation with LfL], alteration of hay cutting / mowing dates, land use change in the vicinity of settlements as well as provide recommendations for personal mitigating behaviour.