Details
| Original language | English |
|---|---|
| Pages (from-to) | 81-85 |
| Number of pages | 5 |
| Journal | IAHS-AISH Proceedings and Reports |
| Volume | 373 |
| Publication status | Published - 12 May 2016 |
| Event | 7th International Water Resources Management Conference of IAHS-ICWRS 2016 - Bochum, Germany Duration: 18 May 2016 → 20 May 2016 |
Abstract
Pure radar rainfall, station rainfall and radar-station merging products are analysed regarding extreme rainfall frequencies with durations from 5 min to 6 h and return periods from 1 year to 30 years. Partial duration series of the extremes are derived from the data and probability distributions are fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at the station location is taken; for the merging products, spatial interpolation methods are applied. The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behaviour of the radar rainfall. The merging products between radar and station data on the other hand lead usually to an underestimation. They can only outperform the station observations for longer durations. The main problem for a good estimation of extremes seems to be the poor radar data quality.
ASJC Scopus subject areas
- Earth and Planetary Sciences(all)
- General Earth and Planetary Sciences
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In: IAHS-AISH Proceedings and Reports, Vol. 373, 12.05.2016, p. 81-85.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - The value of weather radar data for the estimation of design storms – an analysis for the Hannover region
AU - Haberlandt, Uwe
AU - Berndt, Christian
N1 - Funding information: We thank the German Weather Service (DWD) for providing the precipitation and radar data.
PY - 2016/5/12
Y1 - 2016/5/12
N2 - Pure radar rainfall, station rainfall and radar-station merging products are analysed regarding extreme rainfall frequencies with durations from 5 min to 6 h and return periods from 1 year to 30 years. Partial duration series of the extremes are derived from the data and probability distributions are fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at the station location is taken; for the merging products, spatial interpolation methods are applied. The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behaviour of the radar rainfall. The merging products between radar and station data on the other hand lead usually to an underestimation. They can only outperform the station observations for longer durations. The main problem for a good estimation of extremes seems to be the poor radar data quality.
AB - Pure radar rainfall, station rainfall and radar-station merging products are analysed regarding extreme rainfall frequencies with durations from 5 min to 6 h and return periods from 1 year to 30 years. Partial duration series of the extremes are derived from the data and probability distributions are fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at the station location is taken; for the merging products, spatial interpolation methods are applied. The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behaviour of the radar rainfall. The merging products between radar and station data on the other hand lead usually to an underestimation. They can only outperform the station observations for longer durations. The main problem for a good estimation of extremes seems to be the poor radar data quality.
UR - http://www.scopus.com/inward/record.url?scp=85032635073&partnerID=8YFLogxK
U2 - 10.5194/piahs-373-81-2016
DO - 10.5194/piahs-373-81-2016
M3 - Conference article
AN - SCOPUS:85032635073
VL - 373
SP - 81
EP - 85
JO - IAHS-AISH Proceedings and Reports
JF - IAHS-AISH Proceedings and Reports
SN - 0144-7815
T2 - 7th International Water Resources Management Conference of IAHS-ICWRS 2016
Y2 - 18 May 2016 through 20 May 2016
ER -