Articles | Volume 25, issue 7
https://doi.org/10.5194/hess-25-4159-2021
© Author(s) 2021. 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-25-4159-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jul 2021
Research article |
| 22 Jul 2021
| 22 Jul 2021
Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times
Irish Climate Analysis and Research UnitS (ICARUS), Department of Geography, Maynooth University, Maynooth, Co. Kildare, Ireland
Conor Murphy
Irish Climate Analysis and Research UnitS (ICARUS), Department of Geography, Maynooth University, Maynooth, Co. Kildare, Ireland
Shaun Harrigan
Forecast Department, European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Ciaran Broderick
Flood Forecasting Division, Met Éireann, Dublin 9, Ireland
Dáire Foran Quinn
Irish Climate Analysis and Research UnitS (ICARUS), Department of Geography, Maynooth University, Maynooth, Co. Kildare, Ireland
Saeed Golian
Irish Climate Analysis and Research UnitS (ICARUS), Department of Geography, Maynooth University, Maynooth, Co. Kildare, Ireland
Jeff Knight
Met Office Hadley Centre, Exeter, UK
Tom Matthews
Department of Geography and Environment, Loughborough University, Loughborough, UK
Christel Prudhomme
Forecast Department, European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK
Department of Geography and Environment, Loughborough University, Loughborough, UK
UK Centre for Ecology & Hydrology (UKCEH), Wallingford, UK
Adam A. Scaife
Met Office Hadley Centre, Exeter, UK
College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
Nicky Stringer
Met Office Hadley Centre, Exeter, UK
Robert L. Wilby
Department of Geography and Environment, Loughborough University, Loughborough, UK
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Cited
17 citations as recorded by crossref.
- Simulated Changes in Seasonal and Low Flows with Climate Change for Irish Catchments H. Meresa et al. 10.3390/w14101556
- Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System S. Harrigan et al. 10.5194/hess-27-1-2023
- Evaluating Bias-Correction Methods for Seasonal Dynamical Precipitation Forecasts S. Golian & C. Murphy 10.1175/JHM-D-22-0049.1
- Can Data Assimilation Improve Short-Term Prediction of Land Surface Variables? Y. Tian et al. 10.3390/rs14205172
- The Influence of the North Atlantic Oscillation and East Atlantic Pattern on Drought in British Catchments H. West et al. 10.3389/fenvs.2022.754597
- ML-Based Streamflow Prediction in the Upper Colorado River Basin Using Climate Variables Time Series Data P. Hosseinzadeh et al. 10.3390/hydrology10020029
- Surface Water Monitoring Systems—The Importance of Integrating Information Sources for Sustainable Watershed Management Y. Sudriani et al. 10.1109/ACCESS.2023.3263802
- Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. 10.5194/hess-27-4385-2023
- Hybrid forecasting: blending climate predictions with AI models L. Slater et al. 10.5194/hess-27-1865-2023
- Added value of seasonal hindcasts to create UK hydrological drought storylines W. Chan et al. 10.5194/nhess-24-1065-2024
- Innovative Knowledge-Based System for Streamflow Hindcasting: A Comparative Assessment of Gaussian Process-Integrated Neural Network with LSTM and GRU Models A. G R & A. S 10.1016/j.envsoft.2025.106433
- Uncertainties and their interaction in flood hazard assessment with climate change H. Meresa et al. 10.5194/hess-25-5237-2021
- Hydrometeorological Insights into the Forecasting Performance of Multi-Source Weather over a Typical Hill-Karst Basin, Southwest China C. Mo et al. 10.3390/atmos15020236
- The Spatio-Temporal Influence of Atmospheric Circulations on Monthly Precipitation in Great Britain H. West et al. 10.3390/atmos13030429
- Spatio-temporal propagation of North Atlantic Oscillation (NAO) rainfall deviations to streamflow in British catchments H. West et al. 10.1080/02626667.2022.2038791
- Dynamical–statistical seasonal forecasts of winter and summer precipitation for the Island of Ireland S. Golian et al. 10.1002/joc.7557
- Spatio-Temporal Variability in North Atlantic Oscillation Monthly Rainfall Signatures in Great Britain H. West et al. 10.3390/atmos12060763
16 citations as recorded by crossref.
- Simulated Changes in Seasonal and Low Flows with Climate Change for Irish Catchments H. Meresa et al. 10.3390/w14101556
- Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System S. Harrigan et al. 10.5194/hess-27-1-2023
- Evaluating Bias-Correction Methods for Seasonal Dynamical Precipitation Forecasts S. Golian & C. Murphy 10.1175/JHM-D-22-0049.1
- Can Data Assimilation Improve Short-Term Prediction of Land Surface Variables? Y. Tian et al. 10.3390/rs14205172
- The Influence of the North Atlantic Oscillation and East Atlantic Pattern on Drought in British Catchments H. West et al. 10.3389/fenvs.2022.754597
- ML-Based Streamflow Prediction in the Upper Colorado River Basin Using Climate Variables Time Series Data P. Hosseinzadeh et al. 10.3390/hydrology10020029
- Surface Water Monitoring Systems—The Importance of Integrating Information Sources for Sustainable Watershed Management Y. Sudriani et al. 10.1109/ACCESS.2023.3263802
- Towards robust seasonal streamflow forecasts in mountainous catchments: impact of calibration metric selection in hydrological modeling D. Araya et al. 10.5194/hess-27-4385-2023
- Hybrid forecasting: blending climate predictions with AI models L. Slater et al. 10.5194/hess-27-1865-2023
- Added value of seasonal hindcasts to create UK hydrological drought storylines W. Chan et al. 10.5194/nhess-24-1065-2024
- Innovative Knowledge-Based System for Streamflow Hindcasting: A Comparative Assessment of Gaussian Process-Integrated Neural Network with LSTM and GRU Models A. G R & A. S 10.1016/j.envsoft.2025.106433
- Uncertainties and their interaction in flood hazard assessment with climate change H. Meresa et al. 10.5194/hess-25-5237-2021
- Hydrometeorological Insights into the Forecasting Performance of Multi-Source Weather over a Typical Hill-Karst Basin, Southwest China C. Mo et al. 10.3390/atmos15020236
- The Spatio-Temporal Influence of Atmospheric Circulations on Monthly Precipitation in Great Britain H. West et al. 10.3390/atmos13030429
- Spatio-temporal propagation of North Atlantic Oscillation (NAO) rainfall deviations to streamflow in British catchments H. West et al. 10.1080/02626667.2022.2038791
- Dynamical–statistical seasonal forecasts of winter and summer precipitation for the Island of Ireland S. Golian et al. 10.1002/joc.7557
1 citations as recorded by crossref.
Latest update: 30 Mar 2025
Short summary
We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46 Irish catchments. We found that ESP is skilful in the majority of catchments up to several months ahead. However, the level of skill was strongly dependent on lead time, initialisation month, and individual catchment location and storage properties. We also conditioned ESP with the winter North Atlantic Oscillation and show that improvements in forecast skill, reliability, and discrimination are possible.
We benchmarked the skill of ensemble streamflow prediction (ESP) for a diverse sample of 46...
