This study ascribes the observations in increased Atlantic tropical cyclone activity to variations in atmospheric circulation as well as sea surface temperature (SST) increase. Using a novel weather-pattern-based statistical model, the authors find that the warming trend in the Atlantic has doubled the probability of extremely active tropical cyclone seasons.

Summary

Tropical cyclones are among the most damaging extreme weather events. An increase in Atlantic tropical cyclone activity has been observed, but attribution to global warming remains challenging due to large inter-annual variability and modeling challenges.

Here we show that the increase in Atlantic tropical cyclone activity since the 1980s can be robustly ascribed to variations in atmospheric circulation as well as sea surface temperature (SST) increase. Based on a novel weather-pattern-based statistical model, we find that the forced warming trend in Atlantic SSTs over the 1982–2020 period has doubled the probability of extremely active tropical cyclone seasons. For the year 2020, our results suggest that such an exceptionally intense season might have been made twice as likely by ocean surface warming.

In our statistical model, seasonal atmospheric circulation remains the dominant factor explaining the inter-annual variability and the occurrence of very active seasons. However, our study underscores the importance of rising SSTs that lead to more extreme outcomes in terms of cyclone intensity for the same seasonal atmospheric patterns.

Our findings provide a new perspective on the contribution of ocean warming to the increase in recent hurricane activity and illustrate how anthropogenic climate change has contributed to a decisive increase in Atlantic tropical cyclone season activity over the observational period.

Likelihood of extremely active hurricane season

Publications

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1.5°C-aligned 2030 and 2035 GHG emissions targets

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Spatially resolved emulated annual temperature projections for overshoot pathways

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Geological Net Zero and the need for disaggregated accounting for carbon sinks

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Climate Action Tracker: 2024 warming projection update

Despite an escalating climate crisis marked by unprecedented wildfires, storms, floods, and droughts, the Climate Action Tracker annual global temperature update shows global warming projections for 2100 are flatlining, with no improvement since 2021. The aggregate effect of current policies set the world on a path toward 2.7°C of warming.

Decarbonising light-duty vehicle road transport

The Climate Action Tracker provides updated 1.5ºC compatible benchmarks for the transport sector for the world as a whole and for seven individual countries; the US, EU, China, India, Brazil, South Africa and Indonesia.

Emissions Gap Report 2024: No more hot air … please!

The 2024 edition of UNEP’s Emissions Gap Report shows how much higher nations must aim. To get on a least-cost pathway for 1.5°C, emissions must fall 42 per cent by 2030, compared to 2019 levels. G20 nations, particularly the largest-emitting members, would need to do the heavy lifting.

The role of northern forests in limiting warming to 1.5°C

Northern forests are critical in the race to net zero CO₂ by mid-century. Protecting and restoring these forests, alongside steep and rapid reductions in fossil fuel emissions, is essential both to mitigating emissions and to supporting forest ecosystem services and biodiversity.

Methodology underpinning the State of Climate Action series: 2024 update

This technical note describes the State of Climate Action series’ methodology for identifying sectors that must transform, translating these transformations into global mitigation targets primarily for 2030, 2035 and 2050 and selecting indicators with datasets to monitor annual change. It also outlines the report’s approach for assessing progress made toward near-term targets and comparing trends over time.

Rapid urbanisation and climate change key drivers of dramatic flood impacts in Nepal

New study finds the devastating floods in Nepal late September were exacerbated by rapid urbanisation and climate change. The analysis found the relentless rain, which fell on saturated ground in the late monsoon, was made at least 10% heavier and 70% more likely by climate change.

LNG shipbuilding industry heading to huge oversupply

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Seasonal forecast of two-metre temperature and precipitation in Tanzania: A hybrid cluster and point-by-point machine learning approach

Seasonal forecasting of atmospheric parameters is important in various fields including agriculture. This study tests how machine learning can complement dynamic models using Tanzanian seasonal forecasts and finds this process uses far less computational power.

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Decarbonisation targets and 1.5℃ pathways

Comment

Extreme Atlantic hurricane seasons made twice as likely by ocean warming