Ruben Imhoff
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View article: pySTEPS/pysteps: pysteps v1.19.0
pySTEPS/pysteps: pysteps v1.19.0 Open
What's Changed Add importer for DWD radar data products and reprojection onto a regular grid as part of #464 by @m-rempel in https://github.com/pySTEPS/pysteps/pull/483 Add deterministic version of external nowcast blending by @Joep1999 in…
View article: BlockGPT: Spatio-Temporal Modelling of Rainfall via Frame-Level Autoregression
BlockGPT: Spatio-Temporal Modelling of Rainfall via Frame-Level Autoregression Open
Predicting precipitation maps is a highly complex spatiotemporal modeling task, critical for mitigating the impacts of extreme weather events. Short-term precipitation forecasting, or nowcasting, requires models that are not only accurate …
View article: Machine Learning for Predicting Spatially Variable Lateral Hydraulic Conductivity: A Step Toward Efficient Hydrological Model Calibration and Global Applicability
Machine Learning for Predicting Spatially Variable Lateral Hydraulic Conductivity: A Step Toward Efficient Hydrological Model Calibration and Global Applicability Open
Recent advances in machine learning (ML) techniques show promise for estimating soil hydraulic properties from soil data sets. Pedo‐transfer functions (PTFs) can facilitate the mapping of the complex relationship between soil properties an…
View article: Nowcasting tropical rainfall events using Commercial Microwave Links
Nowcasting tropical rainfall events using Commercial Microwave Links Open
To mitigate the impact of severe storms, accurate and timely high-resolution precipitation forecasts are crucial. In the tropics, however, many low- and middle-income countries typically lack the near surface rainfall sensors to provide su…
View article: Rain-on-wet-soil compound floods in lowlands: the combined effect of large rain events and shallow groundwater on discharge peaks in a changing climate
Rain-on-wet-soil compound floods in lowlands: the combined effect of large rain events and shallow groundwater on discharge peaks in a changing climate Open
In lowland catchments, the severity of pluvial floods is determined by both the magnitude of rainfall events and the initial catchment wetness. The aim of this study was to determine the importance of initial wetness on flood peaks in lowl…
View article: Integrating Prediction of Precipitation and Hydrology for Early Actions: The InPRHA Project within the World Weather Research Programme
Integrating Prediction of Precipitation and Hydrology for Early Actions: The InPRHA Project within the World Weather Research Programme Open
Despite advancements in science and technology, flood prediction and preparedness remain challenging due to uncertainties in forecasting atmospheric and hydrologic processes, limited real-time data, and communication barriers. The Integrat…
View article: Enhancing Research-to-Operations in Hydrological Forecasting: Innovations across Scales and Horizons
Enhancing Research-to-Operations in Hydrological Forecasting: Innovations across Scales and Horizons Open
Over the past 20 years, the Hydrological Ensemble Prediction Experiment (HEPEX) international community of practice has advanced the science and practice of hydrological ensemble prediction and its application in impact- and risk-based dec…
View article: Advances in Project IMA, the Seamless Prediction Programme of the Royal Meteorological Institute of Belgium
Advances in Project IMA, the Seamless Prediction Programme of the Royal Meteorological Institute of Belgium Open
Seamless prediction systems provide frequently updated forecasts across different timescales by combining observations, such as weather radar data, with numerical weather prediction (NWP) models. These systems are increasingly needed by us…
View article: Advancing Terrestrial ECVs through High-Resolution Hydrological Modeling: Insights from the 4DHydro Project
Advancing Terrestrial ECVs through High-Resolution Hydrological Modeling: Insights from the 4DHydro Project Open
Accurate representation of terrestrial Essential Climate Variables (tECVs) is crucial for practically understanding the Earth's climate system and supporting policy decisions. This study initiates benchmarking practices within the Land Sur…
View article: Assessing the Impact of Weather Conditions on Radar-Based Rainfall Estimation in the Tropics: A Case Study in Thailand
Assessing the Impact of Weather Conditions on Radar-Based Rainfall Estimation in the Tropics: A Case Study in Thailand Open
In hydrological modeling and forecasting, rainfall data is a key factor in determining the model’s accuracy. The higher the accuracy of the estimated rainfall, the more accurate the model’s predictions can be. Rain gauges can b…
View article: Opportunities and challenges for Rainfall Nowcasting with Commercial Microwave Links in the Tropics
Opportunities and challenges for Rainfall Nowcasting with Commercial Microwave Links in the Tropics Open
In general, quantitative precipitation estimates from weather radars are used as input into nowcasting models to produce high-resolution accurate and timely precipitation forecasts, up to several hours ahead. However, the global distributi…
View article: Data-driven dynamic motion field generation for rainfall nowcasting
Data-driven dynamic motion field generation for rainfall nowcasting Open
Rainfall nowcasting algorithms rely primarily on extrapolation, where recent radar rainfall observations are projected forward in time based on a motion field that is determined with past data. While additional (stochastic) processes may b…
View article: Multi-model hydrological reference dataset over continental Europe and an African basin
Multi-model hydrological reference dataset over continental Europe and an African basin Open
Although Essential Climate Variables (ECVs) have been widely adopted as important metrics for guiding scientific and policy decisions, the Earth Observation (EO) and Land Surface and Hydrologic Model (LSM/HM) communities have yet to treat …
View article: Precipitation Nowcasting Using Physics Informed Discriminator Generative Models
Precipitation Nowcasting Using Physics Informed Discriminator Generative Models Open
Nowcasting leverages real-time atmospheric conditions to forecast weather over short periods. State-of-the-art models, including PySTEPS, encounter difficulties in accurately forecasting extreme weather events because of their unpredictabl…
View article: A fast high resolution distributed hydrological model for forecasting, climate scenarios and digital twin applications using wflow_sbm
A fast high resolution distributed hydrological model for forecasting, climate scenarios and digital twin applications using wflow_sbm Open
We investigated improvements to further speed up the multi-threaded scaling of the distributed hydrological model wflow_sbm. To gain insight in the speed improvements for operational applications, we connected the improved code to ECMWF's …
View article: Mitigating blade erosion damage through nowcast-driven erosion-safe mode control
Mitigating blade erosion damage through nowcast-driven erosion-safe mode control Open
The erosion-safe mode (ESM) is a novel mitigation strategy that reduces rainfall-induced erosion damage by lowering the tip-speed of the turbine during precipitation events. The ESM requires accurate information about future expected rainf…
View article: Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications
Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications Open
The wflow_sbm hydrological model, recently released by Deltares, as part of the Wflow.jl (v0.7.3) modelling framework, is being used to better understand and potentially address multiple operational and water resource planning challenges f…
View article: Nowcasting of High-Intensity Rainfall for Urban Applications in the Netherlands
Nowcasting of High-Intensity Rainfall for Urban Applications in the Netherlands Open
Radar rainfall nowcasting has mostly been applied to relatively large (often rural) domains (e.g., river basins), although rainfall nowcasting in small urban areas is expected to be more challenging. Here, we selected 80 events with high r…
View article: Do catchment characteristics drive extreme discharge tail behavior in the Meuse catchment? Insights from 1,040 years of synthetic discharge data. 
Do catchment characteristics drive extreme discharge tail behavior in the Meuse catchment? Insights from 1,040 years of synthetic discharge data.  Open
Understanding extreme discharge behavior is of importance for flood design and risk management. For example, estimates of large extreme discharge return periods such as the 100-year return period or higher are often needed as a basis for f…
View article: Towards seamless rainfall and flood forecasting in the Netherlands: improvements to and validation of blending in pysteps
Towards seamless rainfall and flood forecasting in the Netherlands: improvements to and validation of blending in pysteps Open
Flood early warning in fast responding catchments challenges our forecasting systems. It requires frequently updated, accurate and high-resolution rainfall forecasts to provide timely warning of rainfall amounts that will reach a catchment…
View article: Machine learning for predicting spatially variable lateral hydraulic conductivity: a step towards efficient hydrological model calibration and global applicability
Machine learning for predicting spatially variable lateral hydraulic conductivity: a step towards efficient hydrological model calibration and global applicability Open
Recent advances in the application of machine learning techniques to estimate soil hydraulic properties using soil datasets have shown promising results. PedoTransfer Functions (PTFs) can facilitate the mapping of the complex relationship …
View article: The development and evaluation of a seamless rainfall forecasting system for Ghana using Meteosat data and the GFS model.
The development and evaluation of a seamless rainfall forecasting system for Ghana using Meteosat data and the GFS model. Open
There is an urgent need for reliable now- and forecasting of (extreme) precipitation on the African continent. Early warning for extreme rainfall contributes to disaster preparedness and can decrease the associated risks. Moreover, reliabl…
View article: A flood prediction framework: integrating seamless predictions into urban hydrological modeling 
A flood prediction framework: integrating seamless predictions into urban hydrological modeling  Open
In recent times, the escalating occurrences of intense precipitation and flooding have exposed substantial socio-economic repercussions, with projections indicating a further rise in their impact due to climate change. Addressing this issu…
View article: Project IMA: Lessons Learned from Building the Belgian Operational Seamless Ensemble Prediction System
Project IMA: Lessons Learned from Building the Belgian Operational Seamless Ensemble Prediction System Open
 In recent years, several national meteorological services (NMSs) have invested considerable resources in the development of a seamless prediction system: rapidly updating forecasts that integrate the latest observations, covering tim…
View article: Revealing spatial patterns of lateral hydraulic conductivity through sensitivity analysis of wflow_sbm 
Revealing spatial patterns of lateral hydraulic conductivity through sensitivity analysis of wflow_sbm  Open
Moving toward high-resolution gridded hydrologic models asks for novel parametrization approaches. The use of transfer functions and advances in scaling and regionalization play an important role to ensure flux matching across scales. Howe…
View article: Extreme Precipitation Nowcasting using Transformer-based Generative Models
Extreme Precipitation Nowcasting using Transformer-based Generative Models Open
This paper presents an innovative approach to extreme precipitation nowcasting by employing Transformer-based generative models, namely NowcastingGPT with Extreme Value Loss (EVL) regularization. Leveraging a comprehensive dataset from the…