16 citations as recorded by crossref.

1. A Novel Bias Correction Method for Extreme Events L. Trentini et al. https://doi.org/10.3390/cli11010003
2. An Efficient Method to Correct Under-Dispersion in Ensemble Streamflow Prediction of Inflow Volumes for Reservoir Optimization R. Arsenault et al. https://doi.org/10.1007/s11269-016-1425-4
3. Inverse process-window identification of key parameters for burst-pressure consistency in type IV cylinders J. Wang et al. https://doi.org/10.1016/j.compositesa.2026.109981
4. Correcting mean areal precipitation forecasts to improve urban flooding predictions by using long short-term memory network D. Nguyen & D. Bae https://doi.org/10.1016/j.jhydrol.2020.124710
5. A 24-variable low-order coupled ocean–atmosphere model: OA-QG-WS v2 S. Vannitsem & L. De Cruz https://doi.org/10.5194/gmd-7-649-2014
6. Assessing the utility of statistical downscaling for subseasonal temperature forecasts E. Duzenli et al. https://doi.org/10.1038/s41598-026-45067-2
7. Assessment of calibration assumptions under strong climate changes B. Van Schaeybroeck & S. Vannitsem https://doi.org/10.1002/2016GL067721
8. Fretting Fatigue Life Prediction for Aluminum Alloy Based on Particle-Swarm-Optimized Back Propagation Neural Network X. Li et al. https://doi.org/10.3390/met14040381
9. Ensemble post‐processing using member‐by‐member approaches: theoretical aspects B. Van Schaeybroeck & S. Vannitsem https://doi.org/10.1002/qj.2397
10. Spatial mode-based calibration (SMoC) of forecast precipitation fields from numerical weather prediction models P. Zhao et al. https://doi.org/10.1016/j.jhydrol.2022.128432
11. Evaluating the impact of post-processing medium-range ensemble streamflow forecasts from the European Flood Awareness System G. Matthews et al. https://doi.org/10.5194/hess-26-2939-2022
12. Bias correction and post-processing under climate change S. Vannitsem https://doi.org/10.5194/npg-18-911-2011
13. Climate Services Toolbox (CSTools) v4.0: from climate forecasts to climate forecast information N. Pérez-Zanón et al. https://doi.org/10.5194/gmd-15-6115-2022
14. Exploratory analysis of statistical post‐processing methods for hydrological ensemble forecasts M. Boucher et al. https://doi.org/10.1002/hyp.10234
15. A review on statistical postprocessing methods for hydrometeorological ensemble forecasting W. Li et al. https://doi.org/10.1002/wat2.1246
16. A Probabilistic Approach to Forecast the Uncertainty with Ensemble Spread B. Van Schaeybroeck & S. Vannitsem https://doi.org/10.1175/MWR-D-14-00312.1