@article{AbonKneisCrisologoetal.2016,
  author    = {Abon, Catherine Cristobal and Kneis, David and Crisologo, Irene and Bronstert, Axel and David, Carlos Primo Constantino and Heistermann, Maik},
  title     = {Evaluating the potential of radar-based rainfall estimates for streamflow and flood simulations in the Philippines},
  series = {GEOMATICS NATURAL HAZARDS \& RISK},
  volume    = {7},
  journal   = {GEOMATICS NATURAL HAZARDS \& RISK},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1947-5705},
  doi       = {10.1080/19475705.2015.1058862},
  pages     = {1390 -- 1405},
  year      = {2016},
  abstract  = {This case study evaluates the suitability of radar-based quantitative precipitation estimates (QPEs) for the simulation of streamflow in the Marikina River Basin (MRB), the Philippines. Hourly radar-based QPEs were produced from reflectivity that had been observed by an S-band radar located about 90 km from the MRB. Radar data processing and precipitation estimation were carried out using the open source library wradlib. To assess the added value of the radar-based QPE, we used spatially interpolated rain gauge observations (gauge-only (GO) product) as a benchmark. Rain gauge observations were also used to quantify rainfall estimation errors at the point scale. At the point scale, the radar-based QPE outperformed the GO product in 2012, while for 2013, the performance was similar. For both periods, estimation errors substantially increased from daily to the hourly accumulation intervals. Despite this fact, both rainfall estimation methods allowed for a good representation of observed streamflow when used to force a hydrological simulation model of the MRB. Furthermore, the results of the hydrological simulation were consistent with rainfall verification at the point scale: the radar-based QPE performed better than the GO product in 2012, and equivalently in 2013. Altogether, we could demonstrate that, in terms of streamflow simulation, the radar-based QPE can perform as good as or even better than the GO product - even for a basin such as the MRB which has a comparatively dense rain gauge network. This suggests good prospects for using radar-based QPE to simulate and forecast streamflow in other parts of the Philippines where rain gauge networks are not as dense.},
  language  = {en}
}
@article{JacobiHeistermann2016,
  author    = {Jacobi, Stephan and Heistermann, Maik},
  title     = {Benchmarking attenuation correction procedures for six years of single-polarized C-band weather radar observations in South-West Germany},
  series = {The quarterly journal of experimental psychology},
  volume    = {7},
  journal   = {The quarterly journal of experimental psychology},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1947-5705},
  doi       = {10.1080/19475705.2016.1155080},
  pages     = {1785 -- 1799},
  year      = {2016},
  abstract  = {Rainfall-induced attenuation is a major source of underestimation for radar-based precipitation estimation at C-band. Unconstrained gate-by-gate correction procedures are known to be inherently unstable and thus not suited for unsupervised attenuation correction. In this study, we evaluate three different procedures to constrain gate-by-gate attenuation correction using reflectivity as the only input. These procedures are benchmarked against rainfall estimates from uncorrected radar data, using six years of radar observations from the single-polarized C-band radar in South-West Germany. The precipitation estimation error is obtained by comparing the radar-based estimates to rain gauge observations. All attenuation correction procedures benchmarked in this study lead to an effective improvement of precipitation estimation. The first method caps the corrections if the rain intensity increase exceeds a factor of two. The second method decreases the parameters of the attenuation correction iteratively for every radar beam calculation until attaining a stability criterion. The second method outperforms the first method and leads to a consistent distribution of path-integrated attenuation along the radar beam. As a third method, we propose a slight modification of Kraemer's approach which allows users to exert better control over attenuation correction by introducing an additional constraint that prevents unplausible corrections in cases of dramatic signal losses.},
  language  = {en}
}