The storm intensified as it continued northwards towards the island of Taiwan, becoming a category 4-equivalent Typhoon on the 24th, with maximum (10-minute) sustained winds of 185 km/h. It made a prolonged landfall in northeast Taiwan on the 24th, bringing both heavy rain and high winds that killed 10 people and injured more than 900, while the agricultural sector reported damages of roughly US$50 million (FocusTaiwan, 2024a, FocusTaiwan, 2024b). It subsequently made landfall as a weaker, but still destructive tropical storm on mainland China on July 25. Gaemi brought heavy rainfall to coastal and inland regions, particularly the Hunan province, as it weakened to a tropical depression. Cyclone-based rainfall is uncommon so far inland in China and the heavy precipitation led to flooding and a mudslide that killed 15 people, and another 15 people in neighbouring provinces.35 remained missing a week after the disaster, and 290,000 people were evacuated (CNN, 2024).

The influence of climate change on tropical cyclones is complex compared to other types of extreme weather events. However, attribution studies are increasingly focusing on these destructive events. Rapid attribution studies to date have focused primarily on severe rainfall from such storms. Here, we use several different approaches to investigate the influence of climate change on multiple aspects of Typhoon Gaemi. The study focuses on the three geographic regions that experienced severe impacts – northern Philippines, the island of Taiwan and Hunan province, and analyse whether and to what extent human-induced climate change affected wind speeds and rainfall. To study the conditions that formed and fuelled Gaemi, we also analyse the role of climate change in high sea surface temperatures and potential intensity, a metric combining sea surface temperature, air temperature and air humidity data to predict maximum typhoon wind speeds. The study combines the established World Weather Attribution protocol with a new approach using the Imperial College Storm Model (IRIS) to analyse the role of human-induced climate change in tropical cyclones. 

Main findings

• Typhoon Gaemi brought destructive winds and rainfall to large regions of southeast Asia, including the northern Philippines, Taiwan, and Hunan . At least 90 people were killed, thousands were injured and hundreds of thousands had to leave their homes. The extreme rainfall and high winds triggered landslides, widespread power outages and severe damage to infrastructure and agriculture. 
• In today’s climate, that has already been warmed by 1.2C due to the burning of fossil fuels, weather observations indicate that rainfall events as severe as those brought by Typhoon Gaemi now occur about once every 20 (5 – 30) years in the northern Philippines, about once every 5 (1.5 – 20) years in Taiwan, and about once every 100 (90 – 160) years in Hunan province.
• To determine the role of climate change we combine observations with climate models. In Taiwan and Hunan, the rainfall was about 14% and 9% heavier respectively due to climate change, and in both regions, the rainfall total was made about 60% more likely by climate change. If the world continues to burn fossil fuels, causing global warming to reach 2°C above pre industrial levels, devastating Typhoon rainfall events in both regions will become 30-50% more likely.
• In the northern Philippines, the analysis did not identify a significant trend up to today. Observations indicate that 3-day rainfall events have increased by about 12%, however, there is large uncertainty in these data sets. Climate models suggest both increases and decreases in rainfall in the current climate, but an increase in a future climate with 2°C of warming. 
• The IRIS model was used to investigate Gaemi’s strong winds by analysing category 4-equivalent storms in the Western North Pacific basin, a region that includes the South China and Philippine seas.
• By statistically modelling storms in a 1.2°C cooler climate, this model showed that climate change was responsible for an increase of about 30% in the number of such storms (now 6-7 times per year, up from 5 times), and equivalently that the maximum wind speeds of similar storms are now 3.9 m/s (around 7%) more intense.
• The conditions that formed and fueled Typhoon Gaemi were studied for links to climate change, using potential intensity and sea surface temperatures surrounding the storm track in July 2024. These conditions occur about every second year for potential intensity and about once every 15 years for sea surface temperatures.
• The influence of climate change on potential intensity is highly uncertain, as observations show a very large increase with warming (about a factor of 100 and a potential intensity increase of 6 m/s) that climate models do not capture. Sea surface temperatures as hot as those observed in July 2024 were almost impossible without climate change and have become about 1 degree warmer. If global warming reaches 2°C, sea surface temperatures are projected to be another 0.6°C warmer, and the conditions associated with Typhoon Gaemi will continue to increase in likelihood by a further factor of about 10. 
• Together, these findings indicate that climate change is enhancing conditions conducive to Typhoons, and when they occur the resulting rainfall totals and wind speeds are more intense. This is in line with other scientific findings that tropical cyclones are becoming more intense and wetter under climate change.
• Rural communities with climate sensitive livelihoods (e.g. agriculture), the urban poor residing in the lowest lying land, and those living on exposed hillsides susceptible to landslides were the most affected by the multitude of hazards stemming from the typhoon. 
• The regions affected by Typhoon Gaemi have early warning systems and comprehensive emergency response systems in place for tropical cyclones that help manage impacts. Flood risk associated with extreme rainfall is well-assessed in the affected regions, but existing urban plans and flood control infrastructure are not able to withstand the more extreme floods that are driven by climate change. Unplanned urban development, including in Metro Manila where the population has rapidly increased, is increasing the number of people at risk, especially in lower lying informal areas.

Researchers from India, Sweden, the United States, and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of extreme rainfall that led to devastating  landslides and floods.

The soils in Wayanad were highly saturated, which is common in the region during the rainy monsoon season, meaning the meteorological cause of the landslide was the heavy rainfall on the preceding day of the event. Wayanad has been determined to be the most susceptible district to landslides in Kerala  (Sharma, Saharia & Ramana, 2024). 

To characterise the event, we analyse the 1-day maximum rainfall (RX1day) during the monsoon season from June to September, focusing on a region of northern Kerala (red outline, figure1). 

Main findings

• The Wayanad landslides resulted in devastating loss of life and occurred in a mountainous region with loose, erodible soils after 140mm of precipitation fell on saturated soils. 
• In today’s climate, which is 1.3°C warmer than it would have been at the beginning of the industrial period, an event of this magnitude is expected to occur about once every 50 years. The event is the third heaviest 1-day rainfall event on record, with heavier spells in 2019 and in 1924, and surpasses the very heavy rainfall in 2018 that affected large regions of Kerala.
• To assess if human-induced climate change influenced the heavy rainfall, we first determine if there is a trend in the observations. Heavy one-day rainfall events have become about 17% more intense in the last 45 years, over a period when the climate has warmed by 0.85°C. Longer-term trends in the pre-satellite era are not clear, which may relate to lower quality weather data. 
• To quantify the role of human-induced climate change we analyse climate models with high enough resolution to capture precipitation over the relatively small study region. Overall, the available climate models indicate a 10% increase in intensity. Under a future warming scenario where the global temperature is 2°C higher than pre-industrial levels, climate models predict even heavier 1-day rainfall events, with a further expected increase of about 4% in rainfall intensity. 
• Given the small mountainous region with complex rainfall-climate dynamics, there is a high level of uncertainty in the model results. However, the increase in heavy one-day rainfall events is in line with a large and growing body of scientific evidence on extreme rainfall in a warming world, including in India, and the physical understanding that a warmer atmosphere can hold more moisture, leading to heavier downpours. 
• While the extreme rainfall was well forecast by the Indian Meteorological Department (IMD) and warnings were issued, the information was at the state-level, making it difficult to discern which localities would be impacted by landslides (one of the potential impacts of heavy rainfall listed in the warning) and would therefore require evacuation. Slope-specific landslide early warning systems can be extremely costly and difficult to implement, but those would provide the best opportunity for effective early action. Given this, reducing exposure of people and assets to landslide-prone places may be a more effective strategy. 
• While the linkage between land cover and land use changes and landslide risk in Wayanad is mixed in the limited existing studies, factors such as quarrying for building materials, and a 62% reduction in forest cover, may have contributed to the increased susceptibility of the slopes to landslides when the heavy rain fell. 
• The increase in climate change-driven rainfall found in this study is likely to increase the potential number of landslides that could be triggered in the future, raising the need for adaptation actions that may include the reinforcement of susceptible slopes, landslide early warning systems, and construction of retaining structures to protect vulnerable localities. 

These episodes occurred just outside of the region’s main winter rainfall season, which runs from November to early April. The unusually high rains and subsequent floods in April and May followed a three-month dry period from December to March

Researchers from Pakistan, the Netherlands, Sweden, the United States, Canada, France, Germany, and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the weather conditions at the time of the most impactful floods. 

To analyse the event, we focus on a region centred on Afghanistan, bounded on the west by the Iranian provinces of Razavi Khorasan, Sistan and Baluchestan, Hormozgan, Kerman, and South Khorasan, and on the east by Balochistan and Khyber Pakhtunkhwa provinces of Pakistan. This area covers the flood-impacted regions through April and May 2024. Due to the atypicality of this season, occurring outside of the usual rainfall period and featuring an unusual number of storms that made it wetter than normal, we choose the seasonal accumulated precipitation during April and May for the temporal definition. Fig. 1 shows the total rainfall during April-May 2024 and the anomaly with respect to 1991-2020 average, over the region.

Main findings 

• Afghanistan and Pakistan are highly vulnerable to flooding due to factors such as limited transboundary water management, unplanned urban expansion, and deforestation which are contributing to increased flood risks, in combination with socio-economic conditions and compounding natural hazards, e.g. earthquakes, landslides, and drought. While Iran is less vulnerable than the other countries studied, urban infrastructure-related vulnerabilities in some cities in the northeast contributed to the impacts.
  
• The floods also occurred on top of existing vulnerabilities linked to complex crises. Displaced populations were particularly impacted, especially as limited essential infrastructure was destroyed and already vulnerable populations were exposed to more waterborne diseases.
  
• The event, despite occurring outside the usual rainy season, is not a particularly rare event in today’s climate that has been warmed by 1.2°C with a return time of about ten years under the current El Niño Southern Oscillation (ENSO) conditions. 
• The declining El Niño Southern Oscillation, a naturally occurring climate phenomenon, is  important to explain the variability in the observed rainfall, consistent with previous research. In observations, as compared to a neutral ENSO year, the declining El Niño resulted in a consistent increase across all datasets by a factor of about two  in likelihood and about 8% in intensity.
• To assess the role of human-induced climate change we combine observation-based products and climate models that include the observed ENSO relationship and assess changes in the likelihood and intensity for the heavy rainfall in the study region. While the last 40 years of  observational data show an increase, climate models have a very different signal, depending on the model, with some showing an increase and some a decrease. Consequently, without further analysis into why the models show such different behaviour we can not attribute the observed increase, which is also not consistent across observation-based products, to human-induced climate change. 
• The disagreement between model results and observations prevents us from concluding with certainty that human-induced climate change is the main driver making this event more likely. However, given the observed trend over the last 40 years, the absence of evidence does not mean that human-induced climate change is not a driver of increasingly heavier rainfall in this region and season in a warmer climate.
  
• There are ample opportunities to improve climate adaptation and resilience through, for example, investing in building resilient infrastructure and reinforcing existing structures to withstand extreme events, implementing more comprehensive nature-based solutions, increasing the coverage of early warning systems, and improving flood risk management policy and planning. 

Researchers from Brazil, the United Kingdom, Sweden, the Netherlands, and the US collaborated to answer the question of whether and to what extent human-induced climate change altered the likelihood and intensity of the rainfall that caused the flooding. They also investigated the role of the El Niño Southern Oscillation (ENSO). 

Rainfall in Southern Brazil (comprising the states of Paraná, Santa Catarina, and Rio Grande do Sul) is characterised by a subtropical climate (transition between tropical and temperate climate) with a continuous supply of moisture from the Atlantic Ocean and the Amazon region thus no distinct rainy seasons exist. Rainfall varies from year to year depending on large scale climate phenomena such as ENSO. 

To capture the nature of the extreme rainfall that resulted in extreme flooding across Rio Grande do Sul, two event definitions are analysed in this study: the 4- and 10-day rainfall accumulations, averaged over the state of Rio Grande do Sul. The 4-day window captures the most severe single event in which record rainfall fell across several consecutive days, while the 10-day window (encompassing 26th April – 5th May, inclusive) captures the succession of heavy rainfall events, including the very wet individual days either side of the major 4-day peak (figure 1).

Main findings

• The unprecedented 2024 April-May floods in Rio Grande do Sul have affected over 90% of the state, an area equivalent to the UK, displacing 581,638 people and causing 169 deaths. While Rio Grande do Sul is often perceived as a well-off region, it still has significant pockets of poverty and marginalisation. Low income has been identified as a significant driver of flood impact. Informal settlements, indigenous villages, and predominantly quilombola (descendants of enslaved Africans) communities have been severely impacted. 
• The lack of a significant extreme flood event, until recently, in Porto Alegre led to reduced investment, and maintenance of its flood protection system, with the system reportedly beginning to fail at 4.5m of flooding despite its stated capacity to withstand water of 6m. This, in addition to the extreme nature of this event, contributed to the significant impacts of the flood and points to the need to objectively assess risk and strengthen flood infrastructure to be resilient to this and future, even more extreme, floods. 
• Both rainfall events characterised above, the 10-day and 4-day events, were found to be extremely rare in the current climate, with return periods of 100-250 years. To increase the statistical stability of the analysis given the relatively short data records, we use the 1 in 100 year event for the analysis in this study. This return period is also typically considered a benchmark for risk analysis. 
• The El Niño Southern Oscillation, a naturally occurring climate phenomenon, was found to be important to explain the variability in the observed rainfall, consistent with previous research. Most previous heavy rainfall events in the area occurred during El Niño years. 
• The role of El Nino alone is comparably large. In observations, compared to a neutral ENSO phase, the current (December-February) El Niño resulted in a consistent increase across all datasets and for both events: by a factor of 2-3 in likelihood and 4-8% in intensity for the 10-day event, and a factor of 2-5 in likelihood and 3-10% in intensity for the 4-day event. 
• To assess the role of human-induced climate change we combine observation-based products and climate models that include the observed ENSO relationship and assess changes in the likelihood and intensity for the 10-day and 4-day heavy rainfall over Rio Grande do Sul and find an increase in likelihood for both events of more than a factor of 2 and intensity increase of 6-9% due to the burning of fossil fuels. 
• These findings are corroborated when looking at a climate of 2oC of global warming since pre-industrial times where we find a further increase in likelihood of a factor of 1.3-2.7 and an increase in intensity of about 4% compared to present day. Again results are similar for both event definitions.
• While environmental protection laws exist in Brazil to protect waterways from construction and limit land use changes, they are not consistently applied or enforced, leading to encroachment on flood-prone land and therefore increasing the exposure of people and infrastructure to flood risks.
• Forecasts and warnings of the floods were available nearly a week in advance, but the warning may not have reached all of those at risk, and the public may not have understood the severity of the impacts or known what actions to take in response to the forecasts. It’s imperative to continue to improve the communication of risk that leads to appropriate, life-saving action.

Hundreds of people lost their lives in the floods and more than 700,000 were affected by the floods across all countries due to infrastructure damages, school closures, lost livestock and thousands of hectares of damaged crops. 

Researchers from Kenya, the Netherlands, Germany, Sweden, Denmark and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the rainfall that led to the severe flooding in the most affected region. 

The impacts were most severe in the region around Lake Tanganyika, Lake Victoria, the central Highlands (including Nairobi), southeast lowlands of  Kenya and coastal Tanzania between the end of March and most of April. To capture this event we looked at the 30-day maximum accumulated rainfall during the long rains (March to May) in the area outlined in red in Figure 1. 

Main findings

• Countries in East Africa have been facing disaster after disaster, including prolonged drought between 2020-23,  and multiple episodes of torrential rainfall leading to severe flooding. These disasters combine to create a complex humanitarian emergency that includes displacement, infrastructure loss, food insecurity, health risks, disrupted livelihoods, and overall weakened resilience. 
• Rapid urbanisation in cities across East Africa is amplifying flood risks, especially in large informal areas that are located on flood-prone land, lack adequate structural protections from the rains, and whose residents lack resources to recover and rebuild. Land-use changes, including deforestation and conversion to agricultural land are also occurring to different degrees in each of the countries studied, adding to flood risk. 
• The East African long rains were observed to show a drying trend towards the end of the 20th century, while climate models projected an increase in heavy rainfall with global warming. While this so-called East Africa Paradox is not as pronounced anymore, with observed precipitation increasing and a new generation of climate models showing weaker or no wettening trend, interpreting observations and climate models is still challenging in this region. 
• The observations, independent of the exact region and data product, do not show a long term trend, but instead a drying trend towards the end of 20th century up until around 2008 and a wettening in the last 15 years. Regardless of whether the recent recovery is being enhanced by human-induced climate change, the increased precipitation does bring an increased risk of flooding to the region.
• To understand if human-induced climate change is indeed playing a role, we also assess whether there are wettening or drying trends in the region for the long rains in climate models. While the trends are not statistically significant, they do show a wettening. On average, an event like this has become about twice as likely and 5% more intense in today’s climate, representing the effect of 1.2C of global warming. 
• Looking at the future, for a climate 2°C warmer than in preindustrial times, models suggest that rainfall intensity and likelihood will increase further.  
• We also examined whether the current phase of the El Nino Southern Oscillation or the Indian Ocean Dipole played a role in the intensity and likelihood of the wet March-May rainy season. Both modes of natural climate variability have been found to exhibit a negligible influence on the 2024 long rains in the study region. 
• Taking these findings and the known physical relationship that heavy rainfall is expected to increase in a warming world, we conclude that the observed increase in rainfall in the region over the last 15 years is in part driven by human-induced climate change. 
• Therefore, investing in flood resilience with future warming is paramount. 
• While early warning systems in each of the countries exist and warn of extreme rainfall, there is room to expand the action taken based on warnings to adequately protect people from the rainfall impacts. Social protection programs can fill gaps in instances where it’s not possible to avoid all impacts, in order to help people recover their assets and livelihoods after the disaster. 
• Disaster preparedness policies, flood preparedness and protection infrastructure, and early warning systems that are in place across Kenya, Tanzania and Burundi are all steps in the right direction, but must be integrated and implemented at scale in order to reduce impacts.

The 2023/24 storm season is the ninth season since the founding of the Western Europe storm naming group. The initiative began in 2015, when the Met Office and Met Éireann, Ireland’s national meteorological service, officially started to identify and name storms that have the potential to cause medium or high impacts, and expanded to include the Royal Netherlands Meteorological Institute (KNMI) in 2019. 

Scientists from the United Kingdom, Ireland, the Netherlands, Sweden and Germany, including scientists from each of the National Meteorological Services in the Western Europe storm naming group, collaborated to assess to what extent human induced climate change and the North Atlantic Oscillation (NAO) influenced the average storm severity, using the wind-based Storm Severity Index (SSI) over a wide region encompassing the United Kingdom and Ireland. The study also investigated the influence of climate change on the average precipitation on stormy days from October 2023 to March 2024, which was one of wettest Oct-Mar periods on record for the UK and the third on record for Ireland, and the wettest over the region south of 54N studied. The study uses peer-reviewed methods to assess changes in storm severity, associated precipitation and precipitation accumulated over the storm season. 

Main findings

• • The 2023/24 storm season, studied here by stormy day wind severity, associated rainfall, and accumulated seasonal rainfall in October-March, has brought deaths, flooding, transport disruptions and power outages, among other impacts, to the UK and Ireland.
  • Successive floods have compounded impacts on the agriculture and housing sectors, leading to cascading impacts on socioeconomic and psychosocial health, and eroding people’s coping capacity, particularly low-income groups. Combined with the cost-of-living crisis, the successive flood events are another layer of disruption at a time when people’s financial resilience is already being tested. 
  • The storm severity index (SSI) was used to define stormy days to study. The SSI considers both the strength of the wind and the area affected. In this analysis we looked at rainfall and wind speed on stormy days identified by the SSI.
  • In today’s climate with 1.2C of warming, stormy days with winds as intense as in the 2023/24 season occur about every 4 years. The associated precipitation is expected to occur about once every 5 years. The seasonal precipitation of the October-March period was more extreme, expected to occur about once every 20 years.
  • Analyses of observations are used to determine whether a trend can be observed in these measures. To determine the role of climate change in these observed changes, we combine observations with climate models.
  • The average precipitation on stormy days are observed to have become approximately 30% more intense, compared to a 1.2C cooler pre-industrial climate. Models agree on the direction of change, combining observations and models indicate that average precipitation on stormy days increased by about 20% due to human induced climate change, or equivalently the 2023/24 level has become about a factor of 10 more likely. 
  • The observed precipitation across Oct-Mar has a strong trend, with a magnitude increase of about 25%. Climate models utilised in this study broadly agree on the direction of the change, and the combination of  observation and model results indicates an increase in magnitude of 6% to 25%, or equivalently the 2023/24 level has become at least a factor of 4 more likely.
  • Models indicate that the trends in average precipitation on stormy days and seasonal precipitation continue into the future, in a climate that is 0.8C warmer than now. Average precipitation on stormy days becomes about another factor of 1.6 times more likely, or 4% more intense, and seasonal precipitation becomes about a factor of 1.5 more likely or 2% more intense.
  • Looking at average SSI on storm days, while some studies using other methods suggest an increase in storminess in a future climate, our analysis has shown a decreasing trend. Our results show that average SSI indices as observed this year became about a factor of 2 less likely. The synthesis of the models also shows a negative trend and, when combined with observations, the results indicate that  a stormy season as observed this year is nowadays a factor of about 1.4 less likely due to human induced climate change. 
  • This highlights the need for ongoing research into how climate change may influence the severity and frequency of windstorms in northern Europe.
  • NAO is a key driver of ‘storminess’ and has been accounted for in this analysis. However, the Oct-Mar 2023/24 averaged NAO was almost neutral.
  • Comprehensive flood risk management is required in the UK and Ireland that encompasses legislative frameworks, strategic planning, and substantial funding. Major UK cities are starting to integrate nature-based solutions into their designs. In Ireland, flood relief projects have been integrating nature-based solutions alongside traditional engineering solutions for over 20 years. Both the UK Met Office and Met Éireann are continuously improving their impact-based weather forecasting mechanisms to facilitate the translation of warning into action, in partnership with other government bodies to ensure their people’s safety. 

In Dubai, most of the rain fell on Monday 15th of April and exceeded all previous records of daily rainfall in the last 75 years, when records began (UAE government, 2024). 

Researchers from Saudi Arabia, Pakistan, Switzerland, the Netherlands, Sweden, the United States, Canada, France and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the weather conditions at the time of the most impactful floods. 

To characterise the event we focus on daily maximum precipitation (RX1day). As this event was the highest on record we also looked at the annual maximum, which usually falls within this season. Using this RX1day variable has the additional advantage that it is one of the routinely calculated indices in most climate projections, thus making it easy to compare our analysis with published literature.

For the spatial definition of the event we analysed the region that saw the biggest impacts during the 1-day heavy rainfall event, indicated by the red box in Figure 1. The region includes the UAE, the northern part of Oman, Bahrain and a small part of Saudi Arabia. 

Main Findings

• The UAE, Oman and the wider analysed region are located in a so-called hyper-arid region, with on average very little rainfall but with very high variability from year to year. Thus heavy rainfall events such as the one analysed here occur very rarely, leading to short records of similar events which results in high uncertainty in the assessment. 
• The El Niño Southern Oscillation, a naturally occurring climate phenomenon, was found to be important to explain the variability in the observed rainfall. Most previous heavy rainfall events in the area occurred during El Niño years. 
• To assess the role of human-induced climate change we first estimate if there is a trend in the observations associated with the warming up until today of 1.2°C and find that there is a trend, making heavy rainfall such as observed more likely. Based on the observations, the event was 10-40% more intense than it would have been had it occurred in an El Nino year in a 1.2°C cooler climate. 
• To further characterise and quantify the role of human-induced climate change we then also look at climate models with high enough resolution to capture precipitation over the comparably small study region. The available climate models do not consistently exhibit a trend even for the models that were evaluated to simulate rainfall in the region reasonably well. However there is high uncertainty in this finding, again, due to high year to year rainfall variability.  
• Based on the IPCC AR6 assessment, which includes scientific literature available up to January 2021, there is “medium confidence” that heavy precipitation would be detectably larger in the Arabian Peninsula at about 1.5°C of global warming compared to pre-industrial climate conditions, which is close to the current level of global warming.
• The disagreement between model results and observations prevents us from concluding with certainty that human-induced climate change is the main driver making this event more likely. However, while multiple reasons could explain the absence of a trend in our model results, we have no alternative explanation for a trend in observations other than the expectation of heavy rainfall increasing in a warmer climate.
• While the heavy rainfall was well forecasted by national meteorological agencies, floodwaters led to a high number of deaths and extensive damages to homes, shops, offices and cars in the UAE and Oman. The majority of flood related deaths occurred when people were travelling, and many people in Dubai were forced to abandon their cars in floodwaters. The researchers say this suggests warnings may not have reached some people or were not specific enough to the impacts expected in particular regions.
• The high flood risk varies across demographics. In Oman and the UAE,  80 and 85% of the total populations, respectively, live in flood-prone and low-lying areas that are highly exposed. Because of various challenges to their abilities to respond to flood risk, particularly vulnerable groups tend to include older adults, individuals with disabilities, women with caregiving responsibilities, racial/ethnic minorities, migrant workers, and lower-income groups.
• Across both countries, a high degree of surfaces with limited permeability and absorptive capacity from urban developments, inadequate drainage and the hyper-arid soils exacerbate the risk and severity of flash floods. 
• UAE and Oman adopt proactive disaster risk management strategies, with functional systems for early warning, early action, and emergency response to floods, along with long-term adaptation planning. However, reducing the high exposure to flood risk, more proactive urban planning and integration of impact-based forecasting in EWS are necessary to reduce impacts associated with similar events in the future.  
• Finally, cloud seeding was reported to not have been implemented in the context of this event, and additionally even in case of implementation has no influence on the amount of atmospheric moisture available, which was the main anomalous variable preceding the precipitation event. Hence, we can conclude that cloud seeding had no significant influence in the event

Researchers from the Philippines, the Netherlands, Germany, Sweden and the United Kingdom collaborated to assess to what extent human-induced climate change altered the likelihood and intensity of the weather conditions at the time of the most impactful floods. 

The impacts over Mindanao were primarily driven by the accumulated rainfall that persisted over Mindanao from 28 Jan to 1 Feb. To capture this event, we chose the maximum 5 days of accumulated rainfall during the December-February (DJF) period as the temporal extent. In terms of spatial extent, the Caraga and Davao regions that make up the east of the island of Mindanao were the most severely impacted, received the greatest rainfall totals, and are bounded to the west by mountains. Figure 1 shows the event region outlined in red. 

Main findings

• The terrain is mountainous, rendering rainfall highly variable within the region, and thus uncertainties in relatively short records from a sparse observation network are high. Regardless, there is a strong upward trend in extreme rainfall in this region.
• To capture the heavy rainfall connected to the recent flooding that led to widespread devastation,  we assess the 5-day maximum rainfall during December to February, the peak of the Northeast monsoon (Amihan) season.  We find that in today’s climate, a heavy rainfall spell  like this is expected with a 10% chance in any given year. 
• We then assess to what extent El Niño had an influence on the heavy rainfall and found that El Niño typically leads to on average to less rainfall in this region during the Northeast monsoon. In other words, had it not been an El Nino year we would have expected the rainfall to be more extreme. 
• To assess the role of climate change we first estimate if there is a trend in the observations associated with the warming up until today of 1.2C and find that there is indeed a strong trend, having made heavy rainfall such as observed more likely. 
• To identify whether this trend is due to human-induced climate change we then also look at climate models with high enough resolution to capture precipitation over the study region. The available climate models do not exhibit a trend even for the models that were evaluated as “good”.  This is surprising, as a comparably large body of scientific literature has identified an increase in heavy rainfall in most regions and seasons of the Philippines, including the region we studied.  
• Given that the trend in the observations is large, there is probably an aspect of the atmospheric circulation that is systematically misrepresented by the models. This prevents us, without further detailed assessment of underlying processes and their representation in the climate models, to draw an overarching attribution conclusion that quantifies the influence of climate change on this event. 
• Despite significant economic improvement, there is a higher-than-average rate of poverty across eastern Mindanao. Poverty negatively impacts communities’ ability to cope with extreme weather events, as their livelihood channels tend to be more limited and climate- sensitive, including farming and mining which the majority of residents are engaged in. 
• Recent protracted conflict has contributed to limited access to and quality of basic services including healthcare as well as considerable displacement. Across displaced populations, a range of development indicators remain lower than the national average, which, coupled with limited health services, increase people’s vulnerability and reduce their coping capacity to natural hazards.
• In rural areas, intensified deforestation increases the risk of landslides and floods, whereas in cities, the loss of urban wetlands and tree cover coupled with clogged waterways enhance the risk of flooding. Across the region of study, construction in areas declared ‘no-build zones’ raises these dangers considerably.
• Policies, laws, and funding of disaster risk management have largely stalled over the past decades and are primarily geared towards ex-post strategies, notably response. Crucially, despite the presence of automated sensors for rainfall and stream level in the region, these have not been recording data since at least 2022. Further, while forecasts and warnings were issued every 12h, warnings have limited granularity on local risk and lack instructions on where and when to evacuate. However, Early Action Protocols are in place for floods and typhoons, and PASAGA is currently developing a pilot project on impact-based forecasting which can further improve anticipatory action. 

To assess to what extent human-induced climate change altered the likelihood and intensity of the heavy precipitation that caused these impacts researchers from the World Weather Attribution initiative, Maynooth University and Met Éireann undertook an attribution study on the event.

We focused on two key indicators to allow us to differentiate the role of climate change in two important characteristics of the event: the 2-day extreme precipitation in October, and the 3-month total accumulated precipitation from July – September, both averaged over County Cork.

Main findings

• On the 17th and 18th October 2023, Storm Babet brought record rainfall amounts to the south of Ireland leading to significant flooding, with the town of Midleton, County Cork severely impacted. The intense 2-day rainfall fell on soils saturated by over 3 months of above average rainfall.
• Peak river flows coincided with a spring low tide, meaning that the river was able to efficiently drain into the sea. Had the event occurred at high tide and/or with substantial storm surge, flooding could have been much more extensive.
• From hydrological modelling, we find that high river flows in October upstream of Midleton are principally driven by extreme rainfall over 2-days and above average preceding rainfall over a longer period (leading to soil saturation), with little evidence of a significant contribution from recent land use changes.
• In order to assess whether and to what extent human-induced climate change was a driver of the rainfall leading to this flood we combine observations-based data products and climate models to look at both the extreme 2-day October and 3-month July-September accumulations over County Cork.
• We find that 2-day October rainfall at least as high as occurred on 17-18^th October 2023 has more than doubled in likelihood and increased in intensity by around 13% due to global warming since pre-industrial levels. This result has high confidence with agreement between models and observations. At 2 degrees of warming, there is also high confidence of further increases in the likelihood and intensity of such events. However, these projected changes are challenging to quantify due to model uncertainties, and so the reported results of a 20% increase in likelihood and 2% in intensity have low confidence.
• On the other hand, the observed high antecedent rainfall from July-September may have become less likely by about 25% and the rainfall totals have reduced by around 5%. However, this result has very low confidence due to high uncertainties across all datasets and the disagreement in the direction of change between models (drying) and observations (wetting).
• In summary, forensic analysis of the drivers of flooding in Midleton show that changes in extreme rainfall due to anthropogenic climate change drove more intense flooding in October 2023, and such changes are likely to continue with further warming. Despite the substantial damages, Midleton proverbially ‘dodged a bullet’ of a far worse disaster thanks to the chance spring low tide at the time of the peak river flow.

To assess to what extent human-induced climate change altered the likelihood and intensity of the heavy precipitation and high wind speeds that caused these impacts researchers from the World Weather Attribution initiative undertook an attribution study on the event.

The focus on two indicators allows us to differentiate the role of climate change in two important characteristics of the event: the 3-day mean precipitation (Rx3day), and the 3-day mean of maximum wind speed magnitude (WSx3day), averaged over the study region where the majority of impacts was observed, defined as a box of 40-50N, 25-45E (Figure 1) and considering only land areas. To account for the climate of the region, with relatively dry and warm summers and wet winters, we study the annual maxima based on July to June cycles.

Main findings 

• Storm Bettina hit the Crimean peninsula in the midst of the active Russia-Ukraine war adding to wide-ranging vulnerabilities across the storm affected areas.
• Storms like Bettina are fairly common in the region at this time of year, which is reflected in the return periods of the event which, in the current climate, are 1 in 3 years for the wind speeds and 1 in 20 years for the associated precipitation (which combines snow and rain).
• Because of human-induced warming, an increasingly larger proportion of precipitation associated with storms like this falls as rain instead of snow, leading to larger flood damages.
• We use observations-based data products and climate models to estimate the role of human-induced climate change in storms like this. The results are very different for rainfall compared to wind speeds. 
• For the precipitation as observed during Storm Bettina, we find that the burning of fossil fuels has increased the likelihood of its occurrence by about a factor of 2. The intensity of an event like this has increased by about 5 percent due to human-induced climate change. 
• Looking at the future, for a climate 2°C warmer than in preindustrial times, models suggest that rainfall intensity and likelihood will increase further. 
• For wind speeds as associated with storm Bettina we find that in observation based products there is a decrease in the likelihood and intensity, while climate models show decreases or increase, leading to no change on average. 
• For a climate 2°C warmer than in preindustrial times, climate models show overall a modest further increase in likelihood and intensity of wind speeds as observed in the 2023 Black Sea event.
• These findings suggest that the decrease we see in wind speeds in the observations are not due to climate change but other drivers e.g. natural variability. Given the model results and the scientific literature, the possibility of an increase in strong winds needs to be taken seriously, even if it cannot be attributed to climate change at this time. 
• Particularly vulnerable groups, notably elderly people, children, and people with disabilities, are more likely to be severely impacted by extreme weather shocks. In particular here, the armed conflict will have exacerbated situations of vulnerability and exposure notably by limiting the ability of communities to respond and recover after the storm and compounding situations of displacement. 
• Disaster response for the storm included flood evacuations, first aid provision, and the set-up of warming points by local governments, Red Cross national societies, and other organisations.