@misc{CrisologoWarrenMuehlbaueretal.2018,
  author    = {Crisologo, Irene and Warren, Robert A. and M{\"u}hlbauer, Kai and Heistermann, Maik},
  title     = {Enhancing the consistency of spaceborne and ground-based radar comparisons by using beam blockage fraction as a quality filter},
  series = {Atmospheric Measurement Techniques},
  journal   = {Atmospheric Measurement Techniques},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418198},
  pages     = {14},
  year      = {2018},
  abstract  = {We explore the potential of spaceborne radar (SR) observations from the Ku-band precipitation radars onboard the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellites as a reference to quantify the ground radar (GR) reflectivity bias. To this end, the 3-D volume-matching algorithm proposed by Schwaller and Morris (2011) is implemented and applied to 5 years (2012-2016) of observations. We further extend the procedure by a framework to take into account the data quality of each ground radar bin. Through these methods, we are able to assign a quality index to each matching SR-GR volume, and thus compute the GR calibration bias as a quality-weighted average of reflectivity differences in any sample of matching GR-SR volumes. We exemplify the idea of quality-weighted averaging by using the beam blockage fraction as the basis of a quality index. As a result, we can increase the consistency of SR and GR observations, and thus the precision of calibration bias estimates. The remaining scatter between GR and SR reflectivity as well as the variability of bias estimates between overpass events indicate, however, that other error sources are not yet fully addressed. Still, our study provides a framework to introduce any other quality variables that are considered relevant in a specific context. The code that implements our analysis is based on the wradlib open-source software library, and is, together with the data, publicly available to monitor radar calibration or to scrutinize long series of archived radar data back to December 1997, when TRMM became operational.},
  language  = {en}
}
@misc{VormoorHeistermannBronstertetal.2018,
  author    = {Vormoor, Klaus Josef and Heistermann, Maik and Bronstert, Axel and Lawrence, Deborah},
  title     = {Hydrological model parameter (in)stability},
  series = {Hydrological Sciences Journal},
  journal   = {Hydrological Sciences Journal},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-413008},
  pages     = {18},
  year      = {2018},
  abstract  = {This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of -5 to -17\%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa.},
  language  = {en}
}