Articles | Volume 26, issue 5
https://doi.org/10.5194/nhess-26-1997-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-1997-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 May 2026
Research article |
| 04 May 2026
| 04 May 2026
Landfalling tropical cyclones significantly reduce Bangladesh's energy security
Kieran M. R. Hunt
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
National Centre for Atmospheric Science, University of Reading, Reading, UK
Hannah C. Bloomfield
Department of Civil and Geospatial Engineering, School of Engineering, Newcastle University, Newcastle upon Tyne, UK
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We assembled and openly shared daily electricity use records for twelve countries in South and Southeast Asia from 2013 to 2025. Data were gathered from official reports and agency websites, converted to a common format and time zone, and checked for missing days and extreme values. Our published dataset largely matches an independent monthly source. The dataset will support future studies of demand growth, weather effects, and electricity system planning and resilience.
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Oliver G. Coombes, Kieran M. R. Hunt, and Hannah C. Bloomfield
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We assembled and openly shared daily electricity use records for twelve countries in South and Southeast Asia from 2013 to 2025. Data were gathered from official reports and agency websites, converted to a common format and time zone, and checked for missing days and extreme values. Our published dataset largely matches an independent monthly source. The dataset will support future studies of demand growth, weather effects, and electricity system planning and resilience.
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Kieran M. R. Hunt, Jean-Philippe Baudouin, Andrew G. Turner, A. P. Dimri, Ghulam Jeelani, Pooja, Rajib Chattopadhyay, Forest Cannon, T. Arulalan, M. S. Shekhar, T. P. Sabin, and Eliza Palazzi
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Short summary
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Isa Dijkstra, Hannah C. Bloomfield, and Kieran M. R. Hunt
Adv. Geosci., 65, 127–140, https://doi.org/10.5194/adgeo-65-127-2025, https://doi.org/10.5194/adgeo-65-127-2025, 2025
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Energy systems across the globe are evolving to meet climate mitigation targets. This requires rapid reductions in fossil fuel use and much more renewable generation. Renewable energy is dependent on the weather. A consequence of this is that there will be periods of low renewable energy production, driven by particular weather conditions. We look at the weather conditions during these periods and show the Indian energy sector could prepare for these events out to 14 days ahead.
Kieran M. R. Hunt and Sandy P. Harrison
Clim. Past, 21, 1–26, https://doi.org/10.5194/cp-21-1-2025, https://doi.org/10.5194/cp-21-1-2025, 2025
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Kieran M. R. Hunt
Weather Clim. Dynam., 5, 345–356, https://doi.org/10.5194/wcd-5-345-2024, https://doi.org/10.5194/wcd-5-345-2024, 2024
Short summary
Short summary
This study investigates changes in weather systems that bring winter precipitation to south Asia. We find that these systems, known as western disturbances, are occurring more frequently and lasting longer into the summer months. This shift is leading to devastating floods, as happened recently in north India. By analysing 70 years of weather data, we trace this change to shifts in major air currents known as the subtropical jet. Due to climate change, such events are becoming more frequent.
Kieran M. R. Hunt and Andrew G. Turner
Weather Clim. Dynam., 3, 1341–1358, https://doi.org/10.5194/wcd-3-1341-2022, https://doi.org/10.5194/wcd-3-1341-2022, 2022
Short summary
Short summary
More than half of India's summer monsoon rainfall arises from low-pressure systems: storms originating over the Bay of Bengal. In observation-based data, we examine how the generation and pathway of these storms are changed by the
boreal summer intraseasonal oscillation– the chief means of large-scale control on the monsoon at timescales of a few weeks. Our study offers new insights for useful prediction of these storms, important for both water resources planning and disaster early warning.
Kieran M. R. Hunt, Gwyneth R. Matthews, Florian Pappenberger, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 26, 5449–5472, https://doi.org/10.5194/hess-26-5449-2022, https://doi.org/10.5194/hess-26-5449-2022, 2022
Short summary
Short summary
In this study, we use three models to forecast river streamflow operationally for 13 months (September 2020 to October 2021) at 10 gauges in the western US. The first model is a state-of-the-art physics-based streamflow model (GloFAS). The second applies a bias-correction technique to GloFAS. The third is a type of neural network (an LSTM). We find that all three are capable of producing skilful forecasts but that the LSTM performs the best, with skilful 5 d forecasts at nine stations.
Hannah C. Bloomfield, David J. Brayshaw, Matthew Deakin, and David Greenwood
Earth Syst. Sci. Data, 14, 2749–2766, https://doi.org/10.5194/essd-14-2749-2022, https://doi.org/10.5194/essd-14-2749-2022, 2022
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There is a global increase in renewable generation to meet carbon targets and reduce the impacts of climate change. Renewable generation and electricity demand depend on the weather. This means there is a need for high-quality weather data for energy system modelling. We present a new European-level, 70-year dataset which has been specifically designed to support the energy sector. We provide hourly, sub-national climate outputs and include the impacts of near-term climate change.
Hannah C. Bloomfield, David J. Brayshaw, Paula L. M. Gonzalez, and Andrew Charlton-Perez
Earth Syst. Sci. Data, 13, 2259–2274, https://doi.org/10.5194/essd-13-2259-2021, https://doi.org/10.5194/essd-13-2259-2021, 2021
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Energy systems are becoming more exposed to weather as more renewable generation is built. This means access to high-quality weather forecasts is becoming more important. This paper showcases past forecasts of electricity demand and wind power and solar power generation across 28 European countries. The timescale of interest is from 5 d out to 1 month ahead. This paper highlights the recent improvements in forecast skill and hopes to promote collaboration in the energy–meteorology community.
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Short summary
Bangladesh’s power grid is highly vulnerable to tropical cyclones. Using nearly a decade of daily data, we show landfalling storms cut national electricity supply by about 20 % on the day, with coastal regions hit hardest (up to 38 %). Damage comes from high winds, storm surge and heavy rain. Power imports from India often can’t help during big events because both areas are struck together. Building sturdier, climate-resilient infrastructure is essential.
Bangladesh’s power grid is highly vulnerable to tropical cyclones. Using nearly a decade of...
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