Details
| Original language | English |
|---|---|
| Article number | 217 |
| Journal | Atmosphere |
| Volume | 11 |
| Issue number | 2 |
| Publication status | Published - 21 Feb 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.
Keywords
- GIS, QPE, Radar climatology, RADKLIM, RADOLAN, Rain gauge, Rainfall, Uncertainties, Weather radar
ASJC Scopus subject areas
- Environmental Science(all)
- Environmental Science (miscellaneous)
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In: Atmosphere, Vol. 11, No. 2, 217, 21.02.2020.
Research output: Contribution to journal › Article › Research › peer review
}
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 -