TY - JOUR

T1 - Radar-based precipitation climatology in germany-developments, uncertainties and potentials

AU - Kreklow, Jennifer

AU - Tetzlaff, Björn

AU - Burkhard, Benjamin

AU - Kuhnt, Gerald

N1 - Funding Information: Funding: This research was partially funded by the Hessian Agency for Nature Conservation, Environment and Geology (HLNUG) within the project “KLIMPRAX–Starkregen”, working package 1.4. The publication of this article was funded by the Open Access Fund of the Leibniz Universität Hannover.

PY - 2020/2/21

Y1 - 2020/2/21

N2 - 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.

AB - 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.

KW - GIS

KW - QPE

KW - Radar climatology

KW - RADKLIM

KW - RADOLAN

KW - Rain gauge

KW - Rainfall

KW - Uncertainties

KW - Weather radar

UR - http://www.scopus.com/inward/record.url?scp=85081161824&partnerID=8YFLogxK

U2 - 10.3390/atmos11020217

DO - 10.3390/atmos11020217

M3 - Article

VL - 11

JO - Atmosphere

JF - Atmosphere

SN - 2073-4433

IS - 2

M1 - 217

ER -