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Forschungsarbeit

Quality assessment scheme for flux measurements under changing land use conditions

Von Wolfgang Babel (01.03.2010)

Spatial heterogeneity has a strong influence on the reliability of meteorologically measured fluxes (see fig. 1), which transfer energy and matter between a given type of land surface and the atmosphere. Some quality assessment techniques and respective tools already exist to evaluate the data quality of such fluxes from heterogeneous landscapes. In contrast, the aim of this thesis is to lay a foundation for a framework, how the footprint concept (see fig. 2) can contribute to estimate spatial representativeness of flux data used for upscaling. This specific goal is motivated by the recently launched projects CEOP-AEGIS and MESO-TiP, both aiming at water balances and ecologic processes on a regional scale over the Tibetan Plateau. In spring, solar radiation generate high potential temperatures over the plateau, which in turn trigger the onset of the East Asian monsoon circulation. Monitoring and prediction of this circulation as well as estimating the water yield of the large Asian rivers (e.g. Yellow river, Yangtze, Brahmaputra and Salween headwaters are located on the Tibetan plateau) advance food security and early warning systems of floods.

Figure 1: Eddy covariance system[Bildunterschrift / Subline]: Figure 1: Eddy covariance system, equipped with sonic anemometer, UV (Krypton) Hygrometer, IR gas analyzer and conventional temperature / moisture sensor, measuring sensible heat flux, latent heat flux (evapotranspiration) and CO2 flux between surface and atmosphere at Nam Tso lake, Tibetan plateau.

Therefore model experiments are carried out with observed flux data (sensible heat flux, latent heat flux and momentum flux) and a simple artificial landscape, containing only two types of land-use. The source weight functions required to estimate the contribution of a certain land-use type are calculated from a forward Lagrangian stochastic model. Additionally the performance of SVAT model runs are evaluated and compared with the observed flux deviance in  general. Observed fluxes are then assigned to the target and surrounding land-use of the artificial landscape and comparisons are conducted dependent on the land-use contribution of the fluxes.

Due to the pronounced relationships between flux magnitude and the size of its source area, integration of the footprint concept offers a promising approach to quantify flux errors over heterogeneous terrain. Quantifying this relationship is helpful to estimate an effective influence of fluxes from adjacent land-use on the target flux. As one would expect, parameterization remains the crucial step for SVAT modeling, therefore the findings for model performance cannot be transferred to other case studies, as following specific requirements complicate their usage: Model performance on low fluxes turned out to be decisive, while calibration usually focuses on large fluxes and the planned extrapolation of the model to unknown surrounding fluxes require a sound reproduction of the ongoing processes. Facing those problems a more statistical approach to quantify and correct footprint related flux errors whenever possible is seen to be more promising than flux correction by modeling the surrounding flux.

Figure 2: Supplement footprints Figure 3: Proposed scheme for the conversion of measured fluxes to a representative flux of the whole grid cell of a mesoscale model (typically 1-3km).[Bildunterschrift / Subline]: Figure 2 (left): Supplement footprints: Atmospheric measurements of fluxes and concentrations at a certain measurement height do not reflect the properties of the surface right below. The source area, typically located in the upwind region, is called footprint. This area can be defined by a so-called source weight function as displayed, where η denotes the relative contribution of a grid cell within x and y to the measured signal. Figure 3 (right): Proposed scheme for the conversion of measured fluxes to a representative flux of the whole grid cell of a mesoscale model (typically 1-3km). Shades of green: Target (dominant) land use and other land use types within a grid cell; color gradient from yellow to violet: exemplary footprint function.

Wolfgang Babel
Wolfgang Babel
* 1974, Germany

Stationen
  • March 2009
  • M.Sc. in Global Change Ecology
  • since Sept. 2008
  • PhD student at the University of Bayreuth, Department Micrometeorology
  • Okt. 2006 - March 2009
  • Study in the Elite Graduate Program Global Change Ecology, University of Bayreuth
  • Okt. 2004 - Okt. 2006
  • Study in Geoecology, University of Bayreuth

Praktika
  • April and Sept. 2007
  • Internship at UFZ Leipzig, Department Computational Landscape Ecology; Topic: Temporal Dynamics of Precipitation Patterns and River Discharge

Vorträge
  • 2009
  • Quality assessment framework to utilize turbulent flux data for mesoscale models, EGU General Assembly in Vienna