Articles | Volume 23, issue 9
https://doi.org/10.5194/hess-23-3711-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-3711-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Sep 2019
Research article |
| 16 Sep 2019
| 16 Sep 2019
Quantitative precipitation estimation with weather radar using a data- and information-based approach
Malte Neuper
Institute of Water Resources and River Basin Management, Karlsruhe Institute of Technology – KIT, Karlsruhe, Germany
Institute of Water Resources and River Basin Management, Karlsruhe Institute of Technology – KIT, Karlsruhe, Germany
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Cited
24 citations as recorded by crossref.
- Radar-Based Precipitation Nowcasting Based on Improved U-Net Model Y. Tan et al. 10.3390/rs16101681
- Debates: Does Information Theory Provide a New Paradigm for Earth Science? Emerging Concepts and Pathways of Information Physics R. Perdigão et al. 10.1029/2019WR025270
- Enhancing the Performance of Quantitative Precipitation Estimation Using Ensemble of Machine Learning Models Applied on Weather Radar Data E. Mihuleţ et al. 10.3390/atmos14010182
- Flood forecasting based on radar precipitation nowcasting using U-net and its improved models J. Li et al. 10.1016/j.jhydrol.2024.130871
- Radar Quantitative Precipitation Estimation (QPE) Calibration Methods: A Systematic Literature Review N. Osman & W. Tahir 10.48084/etasr.7534
- Use of radar data for characterizing extreme precipitation at fine scales and short durations K. Lengfeld et al. 10.1088/1748-9326/ab98b4
- The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review Z. Sokol et al. 10.3390/rs13030351
- Adaptive clustering: reducing the computational costs of distributed (hydrological) modelling by exploiting time-variable similarity among model elements U. Ehret et al. 10.5194/hess-24-4389-2020
- Event controls on intermittent streamflow in a temperate climate N. Kaplan et al. 10.5194/hess-26-2671-2022
- Quality-Based Combination of Multi-Source Precipitation Data A. Jurczyk et al. 10.3390/rs12111709
- Opportunities and challenges for precipitation forcing data in post‐wildfire hydrologic modeling applications T. Partridge et al. 10.1002/wat2.1728
- Implementation of a UAV-aided calibration method for a mobile dual-polarization weather radar G. Buckingham et al. 10.1016/j.ejrs.2024.04.005
- The 3D Neural Network for Improving Radar-Rainfall Estimation in Monsoon Climate N. Roslan et al. 10.3390/atmos12050634
- Estimates of tree root water uptake from soil moisture profile dynamics C. Jackisch et al. 10.5194/bg-17-5787-2020
- Long-term multi-source precipitation estimation with high resolution (RainGRS Clim) A. Jurczyk et al. 10.5194/amt-16-4067-2023
- SciKit-GStat Uncertainty: A software extension to cope with uncertain geostatistical estimates M. Mälicke et al. 10.1016/j.spasta.2023.100737
- Evaluating the Applicability of the PUSH Framework to Quasi-Global Infrared Precipitation Retrievals at 0.5°/Daily Spatial/Temporal Resolution S. Khan & V. Maggioni 10.1007/s13143-020-00185-3
- Nonlinearity and Multivariate Dependencies in the Terrestrial Leg of Land‐Atmosphere Coupling H. Hsu & P. Dirmeyer 10.1029/2020WR028179
- Preface: Linking landscape organisation and hydrological functioning: from hypotheses and observations to concepts, models and understanding C. Jackisch et al. 10.5194/hess-25-5277-2021
- Technical note: Complexity–uncertainty curve (c-u-curve) – a method to analyse, classify and compare dynamical systems U. Ehret & P. Dey 10.5194/hess-27-2591-2023
- Automatic quality control of telemetric rain gauge data providing quantitative quality information (RainGaugeQC) K. Ośródka et al. 10.5194/amt-15-5581-2022
- Multi-scale investigation of conditional errors in radar-rainfall estimates B. Seo & W. Krajewski 10.1016/j.advwatres.2021.104041
- The role and value of distributed precipitation data in hydrological models R. Loritz et al. 10.5194/hess-25-147-2021
- Similarity of catchment dynamics based on the interaction between streamflow and forcing time series: Use of a transfer entropy signature M. Neri et al. 10.1016/j.jhydrol.2022.128555
24 citations as recorded by crossref.
- Radar-Based Precipitation Nowcasting Based on Improved U-Net Model Y. Tan et al. 10.3390/rs16101681
- Debates: Does Information Theory Provide a New Paradigm for Earth Science? Emerging Concepts and Pathways of Information Physics R. Perdigão et al. 10.1029/2019WR025270
- Enhancing the Performance of Quantitative Precipitation Estimation Using Ensemble of Machine Learning Models Applied on Weather Radar Data E. Mihuleţ et al. 10.3390/atmos14010182
- Flood forecasting based on radar precipitation nowcasting using U-net and its improved models J. Li et al. 10.1016/j.jhydrol.2024.130871
- Radar Quantitative Precipitation Estimation (QPE) Calibration Methods: A Systematic Literature Review N. Osman & W. Tahir 10.48084/etasr.7534
- Use of radar data for characterizing extreme precipitation at fine scales and short durations K. Lengfeld et al. 10.1088/1748-9326/ab98b4
- The Role of Weather Radar in Rainfall Estimation and Its Application in Meteorological and Hydrological Modelling—A Review Z. Sokol et al. 10.3390/rs13030351
- Adaptive clustering: reducing the computational costs of distributed (hydrological) modelling by exploiting time-variable similarity among model elements U. Ehret et al. 10.5194/hess-24-4389-2020
- Event controls on intermittent streamflow in a temperate climate N. Kaplan et al. 10.5194/hess-26-2671-2022
- Quality-Based Combination of Multi-Source Precipitation Data A. Jurczyk et al. 10.3390/rs12111709
- Opportunities and challenges for precipitation forcing data in post‐wildfire hydrologic modeling applications T. Partridge et al. 10.1002/wat2.1728
- Implementation of a UAV-aided calibration method for a mobile dual-polarization weather radar G. Buckingham et al. 10.1016/j.ejrs.2024.04.005
- The 3D Neural Network for Improving Radar-Rainfall Estimation in Monsoon Climate N. Roslan et al. 10.3390/atmos12050634
- Estimates of tree root water uptake from soil moisture profile dynamics C. Jackisch et al. 10.5194/bg-17-5787-2020
- Long-term multi-source precipitation estimation with high resolution (RainGRS Clim) A. Jurczyk et al. 10.5194/amt-16-4067-2023
- SciKit-GStat Uncertainty: A software extension to cope with uncertain geostatistical estimates M. Mälicke et al. 10.1016/j.spasta.2023.100737
- Evaluating the Applicability of the PUSH Framework to Quasi-Global Infrared Precipitation Retrievals at 0.5°/Daily Spatial/Temporal Resolution S. Khan & V. Maggioni 10.1007/s13143-020-00185-3
- Nonlinearity and Multivariate Dependencies in the Terrestrial Leg of Land‐Atmosphere Coupling H. Hsu & P. Dirmeyer 10.1029/2020WR028179
- Preface: Linking landscape organisation and hydrological functioning: from hypotheses and observations to concepts, models and understanding C. Jackisch et al. 10.5194/hess-25-5277-2021
- Technical note: Complexity–uncertainty curve (c-u-curve) – a method to analyse, classify and compare dynamical systems U. Ehret & P. Dey 10.5194/hess-27-2591-2023
- Automatic quality control of telemetric rain gauge data providing quantitative quality information (RainGaugeQC) K. Ośródka et al. 10.5194/amt-15-5581-2022
- Multi-scale investigation of conditional errors in radar-rainfall estimates B. Seo & W. Krajewski 10.1016/j.advwatres.2021.104041
- The role and value of distributed precipitation data in hydrological models R. Loritz et al. 10.5194/hess-25-147-2021
- Similarity of catchment dynamics based on the interaction between streamflow and forcing time series: Use of a transfer entropy signature M. Neri et al. 10.1016/j.jhydrol.2022.128555
Latest update: 20 Nov 2024
Short summary
In this study, we apply a data-driven approach to quantitatively estimate precipitation using weather radar data. The method is based on information theory concepts. It uses predictive relations expressed by empirical discrete probability distributions, which are directly derived from data rather than the standard deterministic functions.
In this study, we apply a data-driven approach to quantitatively estimate precipitation using...
