Articles | Volume 20, issue 1
https://doi.org/10.5194/hess-20-505-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-505-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Jan 2016
Research article |
| 29 Jan 2016
Development and verification of a real-time stochastic precipitation nowcasting system for urban hydrology in Belgium
L. Foresti
CORRESPONDING AUTHOR
Royal Meteorological Institute of Belgium, Brussels,
Belgium
M. Reyniers
Royal Meteorological Institute of Belgium, Brussels,
Belgium
A. Seed
Bureau of Meteorology, Melbourne, Australia
L. Delobbe
Royal Meteorological Institute of Belgium, Brussels,
Belgium
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36 citations as recorded by crossref.
- Weather Radar Data Processing and Atmospheric Applications: An Overview of Tools for Monitoring Clouds and Detecting Wind Shear M. Falconi & F. Marzano 10.1109/MSP.2019.2890934
- Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process J. Yan et al. 10.5194/hess-25-3819-2021
- Using nowcasting technique and data assimilation in a meteorological model to improve very short range hydrological forecasts M. Poletti et al. 10.5194/hess-23-3823-2019
- Exploring the use of underground gravity monitoring to evaluate radar estimates of heavy rainfall L. Delobbe et al. 10.5194/hess-23-93-2019
- CASA Prediction System over Dallas–Fort Worth Urban Network: Blending of Nowcasting and High-Resolution Numerical Weather Prediction Model C. Radhakrishnan & V. Chandrasekar 10.1175/JTECH-D-18-0192.1
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- Rainfall Nowcasting Using Commercial Microwave Links R. Imhoff et al. 10.1029/2020GL089365
- Multi-Task Collaboration Deep Learning Framework for Infrared Precipitation Estimation X. Yang et al. 10.3390/rs13122310
- Lagrangian Integro-Difference Equation Model for Precipitation Nowcasting 10.1175/JTECH-D-21-0013.1
- A Hybrid Model for Fast and Probabilistic Urban Pluvial Flood Prediction X. Li & P. Willems 10.1029/2019WR025128
- Impact of Lightning Data Assimilation on the Short-Term Precipitation Forecast over the Central Mediterranean Sea R. Torcasio et al. 10.3390/rs13040682
- Short-term daily precipitation forecasting with seasonally-integrated autoencoder D. Ponnoprat 10.1016/j.asoc.2021.107083
- Recent Advances in Real-Time Pluvial Flash Flood Forecasting A. Zanchetta & P. Coulibaly 10.3390/w12020570
- Generation and Verification of Rainfall Estimates from 10-Yr Volumetric Weather Radar Measurements E. Goudenhoofdt & L. Delobbe 10.1175/JHM-D-15-0166.1
- Pysteps: an open-source Python library for probabilistic precipitation nowcasting (v1.0) S. Pulkkinen et al. 10.5194/gmd-12-4185-2019
- Nowcasting of Precipitation in the High-Resolution Dallas–Fort Worth (DFW) Urban Radar Remote Sensing Network S. Pulkkinen et al. 10.1109/JSTARS.2018.2840491
- Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks A. Akbari Asanjan et al. 10.1029/2018JD028375
- A Deep Learning Multimodal Method for Precipitation Estimation A. Moraux et al. 10.3390/rs13163278
- Spatial and Temporal Evaluation of Radar Rainfall Nowcasting Techniques on 1,533 Events R. Imhoff et al. 10.1029/2019WR026723
- Operational and emerging capabilities for surface water flood forecasting L. Speight et al. 10.1002/wat2.1517
- Optical flow models as an open benchmark for radar-based precipitation nowcasting (rainymotion v0.1) G. Ayzel et al. 10.5194/gmd-12-1387-2019
- Weather radar rainfall data in urban hydrology S. Thorndahl et al. 10.5194/hess-21-1359-2017
- A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transform D. Nerini et al. 10.5194/hess-21-2777-2017
- Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates F. Marra & E. Morin 10.1016/j.atmosres.2017.09.020
- Enhanced object-based tracking algorithm for convective rain storms and cells C. Muñoz et al. 10.1016/j.atmosres.2017.10.027
- Relevance of merging radar and rainfall gauge data for rainfall nowcasting in urban hydrology B. Shehu & U. Haberlandt 10.1016/j.jhydrol.2020.125931
- Limits of precipitation nowcasting by extrapolation of radar reflectivity for warm season in Central Europe J. Mejsnar et al. 10.1016/j.atmosres.2018.06.005
- Hydrological application of radar rainfall nowcasting in the Netherlands D. Heuvelink et al. 10.1016/j.envint.2019.105431
- 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
- Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications M. Codo & M. Rico-Ramirez 10.3390/geosciences8080297
- All convolutional neural networks for radar-based precipitation nowcasting G. Ayzel et al. 10.1016/j.procs.2019.02.036
- Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling N. Peleg et al. 10.5194/hess-21-1559-2017
- Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review E. Cristiano et al. 10.5194/hess-21-3859-2017
- Estimating the occurrence and severity of hail based on 10 years of observations from weather radar in Belgium M. Lukach et al. 10.1002/met.1623
- Deep Learning for Precipitation Estimation from Satellite and Rain Gauges Measurements A. Moraux et al. 10.3390/rs11212463
2 citations as recorded by crossref.
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Saved (preprint)
Latest update: 22 Mar 2023
Short summary
The Short-Term Ensemble Prediction System (STEPS) is implemented in real time at the Royal Meteorological Institute of Belgium (STEPS-BE). The idea behind STEPS is to quantify the forecast uncertainty by adding stochastic perturbations to the deterministic extrapolation of radar images. In this paper we present the deterministic, probabilistic and ensemble verification of STEPS-BE forecasts using four precipitation cases that caused sewer system overflow in the cities of Leuven and Ghent.
The Short-Term Ensemble Prediction System (STEPS) is implemented in real time at the Royal...
