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@ARTICLE{Kreklow:887690,
      author       = {Kreklow, Jennifer and Tetzlaff, Björn and Burkhard,
                      Benjamin and Kuhnt, Gerald},
      title        = {{R}adar-{B}ased {P}recipitation {C}limatology in
                      {G}ermany—{D}evelopments, {U}ncertainties and
                      {P}otentials},
      journal      = {Atmosphere},
      volume       = {11},
      number       = {2},
      issn         = {2073-4433},
      address      = {Basel, Switzerland},
      publisher    = {MDPI AG},
      reportid     = {FZJ-2020-04351},
      pages        = {217 -},
      year         = {2020},
      abstract     = {Precipitation is a crucial driver for many environmental
                      processes and weather radars are capable of providing
                      precipitation information with high spatial and temporal
                      resolution. However, radar-based quantitative precipitation
                      estimates (QPE) are also subject to various potential
                      uncertainties. This study explored the development,
                      uncertainties and potentials of the hourly operational
                      German radar-based and gauge-adjusted QPE called RADOLAN and
                      its reanalyzed radar climatology dataset named RADKLIM in
                      comparison to ground-truth rain gauge data. The
                      precipitation datasets were statistically analyzed across
                      various time scales ranging from annual and seasonal
                      aggregations to hourly rainfall intensities in regard to
                      their capability to map long-term precipitation
                      distribution, to detect low intensity rainfall and to
                      capture heavy rainfall. Moreover, the impacts of season,
                      orography and distance from the radar on long-term
                      precipitation sums were examined in order to evaluate
                      dataset performance and to describe inherent biases. Results
                      revealed that both radar products tend to underestimate
                      total precipitation sums and particularly high intensity
                      rainfall. However, our analyses also showed significant
                      improvements throughout the RADOLAN time series as well as
                      major advances through the climatologic reanalysis regarding
                      the correction of typical radar artefacts, orographic and
                      winter precipitation as well as range-dependent
                      attenuation.},
      cin          = {IBG-3},
      ddc          = {550},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000519238800057},
      doi          = {10.3390/atmos11020217},
      url          = {https://juser.fz-juelich.de/record/887690},
}