Articles | Volume 5, issue 1
https://doi.org/10.5194/wcd-5-345-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-5-345-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Increasing frequency and lengthening season of western disturbances are linked to increasing strength and delayed northward migration of the subtropical jet
Kieran M. R. Hunt
CORRESPONDING AUTHOR
Department of Meteorology, University of Reading, Reading, UK
National Centre for Atmospheric Sciences, University of Reading, Reading, UK
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This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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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.
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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.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-4474, https://doi.org/10.5194/egusphere-2025-4474, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
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.
Priya Bharati, Pranab Deb, and Kieran Mark Rainwater Hunt
Weather Clim. Dynam., 6, 197–210, https://doi.org/10.5194/wcd-6-197-2025, https://doi.org/10.5194/wcd-6-197-2025, 2025
Short summary
Short summary
Our study highlights that the negative phase of the Pacific Decadal Oscillation (PDO) enhanced winter snowfall in the Karakoram and the Western Himalayas (KH) from 1940 to 2022. This is driven by deep convection, adiabatic cooling, and a wave-like atmospheric pattern linked to the subtropical jet (STJ). The PDO–STJ relationship offers insights into decadal snowfall predictability in KH, emphasizing the PDO's role in regional climate dynamics.
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
Weather Clim. Dynam., 6, 43–112, https://doi.org/10.5194/wcd-6-43-2025, https://doi.org/10.5194/wcd-6-43-2025, 2025
Short summary
Short summary
Western disturbances (WDs) are storms that predominantly affect north India and Pakistan during the winter months, where they play an important role in regional water security, but can also bring a range of natural hazards. In this review, we summarise recent literature across a range of topics: their structure and lifecycle, precipitation and impacts, interactions with large-scale weather patterns, representation in models, how well they are forecast, and their response to changes in climate.
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
Short summary
Short summary
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
Short summary
Short summary
In this study, we train machine learning models on tree rings, speleothems, and instrumental rainfall to estimate seasonal monsoon rainfall over India over the last 500 years. Our models highlight multidecadal droughts in the mid-17th and 19th centuries, and we link these to historical famines. Using techniques from explainable AI (artificial intelligence), we show that our models use known relationships between local hydroclimate and the monsoon circulation.
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.
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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.
This study investigates changes in weather systems that bring winter precipitation to south...