Anne Jellema is Executive Director of 350.org.

The war on Iran and Lebanon is a deeply unjust and devastating conflict, killing civilians at home, destroying lives, and at the same time sending shockwaves through the global economy. We, at 350.org, have calculated, drawing on price forecasts from the International Monetary Fund (IMF) and Goldman Sachs, just how much that volatility is costing us. 

Even under the IMF’s baseline scenario – a de facto “best case” scenario with a near-term end to the war and related supply chain disruptions – oil and gas price spikes are projected to cost households and businesses globally more than $600 billion by the end of the year. Under the IMF’s “adverse scenario”, with prolonged conflict and sustained price pressures, we estimate those additional costs could exceed $1 trillion, even after accounting for reduced demand.

Which is why we urgently need a power shift. Governments are under growing pressure to respond to rising fuel and food costs and deepening energy poverty. And it’s becoming clearer to both voters and elected officials that fossil dependence is not only expensive and risky, but unnecessary. 

People who can are voting with their wallets: sales of solar panels and electric vehicles are increasing sharply in many countries. But the working people who have nothing to spare, ironically, are the ones stuck with using oil and gas that is either exorbitantly expensive or simply impossible to get.

Drain on households and economies

In India, street food vendors can’t get cooking gas and in the Philippines, fishermen can’t afford to take their boats to sea. A quarter of British people say that rising energy tariffs will leave them completely unable to pay their bills. This is the moment for a global push to bring abundant and affordable clean energy to all.

In April, we released Out of Pocket, our new research report on how fossil fuels are draining households and economies. We were surprised by the scale of what we found. For decades, governments have reassured people that energy price spikes are unfortunate but unavoidable – the result of distant conflicts, market forces or geopolitical shocks beyond anyone’s control. But the numbers tell a different story. 

What we are living through today is not an energy crisis. It is a fossil fuel crisis. In just the first 50 days of the Middle East conflict, soaring oil and gas prices have siphoned an estimated $158 billion–$166 billion from households and businesses worldwide. That is money extracted directly from people’s pockets and transferred, almost instantly, into fossil fuel company balance sheets. And this figure only captures the immediate impact of price spikes, not the permanent economic drain of fossil dependence. Fossil fuels don’t just cost us once, they cost us over and over again.

First, through our bills. Every time there is a war, an embargo or a supply disruption, fossil fuel prices surge. For ordinary people, this means higher costs for energy, transport and food. Many Global South countries have little or no fiscal space to buffer the shock; instead, workers and families pay the price.

Second, through our taxes. Governments around the world continue to pour vast sums of public money into fossil fuel subsidies. These are often justified as a way to protect the most vulnerable at the petrol pump or in their homes. But in reality, the benefits are overwhelmingly captured by wealthier households and corporations. The poorest 20% receive just a fraction of this support, while public finances are drained.

Third, through climate impacts. New research across more than 24,000 global locations gives a granular account of the true costs of extreme heat, sea level rise and falling agricultural yields. Using this data to update IMF modelling of the social cost of carbon, we found that fossil fuel impacts on health and livelihoods amount to over $9 trillion a year. This is the biggest subsidy of all, because these massive and mounting costs are not charged to Big Oil – they are paid for by governments and households, with the poorest shouldering the lion’s share. 

Massive transfer of wealth to fossil fuel industry

Adding up direct subsidies, tax breaks and the unpaid bill for climate damages, the total transfer of wealth from the public to the fossil fuel industry amounts to $12 trillion even in a “normal” year without a global oil shock. That’s more than 50% higher than the IMF has previously estimated, and equivalent to a staggering $23 million a minute.

The fossil fuel industry has become extraordinarily adept at profiting from instability. When conflict drives up prices, companies do not lose, they gain. In the current crisis, oil producers and commodity traders are on track to secure tens of billions of dollars in additional windfall profits, even as households face rising bills and governments struggle to manage the fallout.

Fossil fuel crisis offers chance to speed up energy transition, ministers say

This growing disconnect is impossible to ignore. Investors are advised to buy into fossil fuel firms precisely because of their ability to generate profits in times of crisis. Meanwhile, ordinary people are told to tighten their belts.

In 2026, unlike during the oil shocks of the 1970s, clean energy is no longer a distant alternative. Now, even more than when gas prices spiked due to Russia’s invasion of Ukraine in 2022, renewables are often the cheapest option available. Solar and wind can be deployed quickly, at scale, and without the volatility that defines fossil fuel markets.

How to transition from dirty to clean energy

The solutions are clear. Governments must implement permanent windfall taxes on fossil fuel companies to ensure that extraordinary profits generated during crises are redirected to support households. These revenues can be used to reduce energy bills, invest in public services, and accelerate the rollout of clean energy.

Second, we must shift subsidies away from fossil fuels and towards renewable solutions, particularly those that can be deployed quickly and equitably, such as rooftop and community solar. This is not just about cutting emissions. It is about building a more stable, fair and resilient energy system.

Finally, we need binding plans to phase out fossil fuels altogether, replacing them with homegrown renewable energy that can shield economies from future shocks. Because what the current crisis has made clear is this: as long as we remain dependent on fossil fuels, we remain vulnerable – to conflict, to price volatility and to the escalating impacts of climate change.

The true price of fossil fuels is no longer hidden. It is visible in rising bills, strained public finances and communities pushed to the brink. And it is being paid, every day, by ordinary people around the world.

It’s time for the great power shift. 

Full details on the methodology used for this report are available here.

The Great Power Shift is a new campaign by 350.org global campaign to pressure governments to bring down energy bills for good by ending fossil fuel dependence and investing in clean, affordable energy for all

The post What fossil fuels really cost us in a world at war appeared first on Climate Home News.

What fossil fuels really cost us in a world at war

Computer models that use artificial intelligence (AI) cannot forecast record-breaking weather as well as traditional climate models, according to a new study.

It is well established that AI climate models have surpassed traditional, physics-based climate models for some aspects of weather forecasting.

However, new research published in Science Advances finds that AI models still “underperform” in forecasting record-breaking extreme weather events.

The authors tested how well both AI and traditional weather models could simulate thousands of record-breaking hot, cold and windy events that were recorded in 2018 and 2020.

They find that AI models underestimate both the frequency and intensity of record-breaking events.

A study author tells Carbon Brief that the analysis is a “warning shot” against replacing traditional models with AI models for weather forecasting “too quickly”.

AI weather forecasts

Extreme weather events, such as floods, heatwaves and storms, drive hundreds of billions of dollars in damages every year through the destruction of cropland, impacts on infrastructure and the loss of human life.

Many governments have developed early warning systems to prepare the general public and mobilise disaster response teams for imminent extreme weather events. These systems have been shown to minimise damages and save lives.

For decades, scientists have used numerical weather prediction models to simulate the weather days, or weeks, in advance.

These models rely on a series of complex equations that reproduce processes in the atmosphere and ocean. The equations are rooted in fundamental laws of physics, based on decades of research by climate scientists. As a result, these models are referred to as “physics-based” models.

However, AI-based climate models are gaining popularity as an alternative for weather forecasting.

Instead of using physics, these models use a statistical approach. Scientists present AI models with a large batch of historical weather data, known as training data, which teaches the model to recognise patterns and make predictions.

To produce a new forecast, the AI model draws on this bank of knowledge and follows the patterns that it knows.

There are many advantages to AI weather forecasts. For example, they use less computing power than physics-based models, because they do not have to run thousands of mathematical equations.

Furthermore, many AI models have been found to perform better than traditional physics-based models at weather forecasts.

However, these models also have drawbacks.

Study author Prof Sebastian Engelke, a professor at the research institute for statistics and information science at the University of Geneva, tells Carbon Brief that AI models “depend strongly on the training data” and are “relatively constrained to the range of this dataset”.

In other words, AI models struggle to simulate brand new weather patterns, instead tending forecast events of a similar strength to those seen before. As a result, it is unclear whether AI models can simulate unprecedented, record-breaking extreme events that, by definition, have never been seen before.

Record-breaking extremes

Extreme weather events are becoming more intense and frequent as the climate warms. Record-shattering extremes – those that break existing records by large margins – are also becoming more regular.

For example, during a 2021 heatwave in north-western US and Canada, local temperature records were broken by up to 5C. According to one study, the heatwave would have been “impossible” without human-caused climate change.

The new study explores how accurately AI and physics-based models can forecast such record-breaking extremes.

First, the authors identified every heat, cold and wind event in 2018 and 2020 that broke a record previously set between 1979 and 2017. (They chose these years due to data availability.) The authors use ERA5 reanalysis data to identify these records.

This produced a large sample size of record-breaking events. For the year 2020, the authors identified around 160,000 heat, 33,000 cold and 53,000 wind records, spread across different seasons and world regions.

For their traditional, physics-based model, the authors selected the High RESolution forecast model from the Integrated Forecasting System of the European Centre for Medium-­Range Weather Forecasts. This is “widely considered as the leading physics-­based numerical weather prediction model”, according to the paper.

They also selected three “leading” AI weather models – the GraphCast model from Google Deepmind, Pangu-­Weather developed by Huawei Cloud and the Fuxi model, developed by a team from Shanghai.

The authors then assessed how accurately each model could forecast the extremes observed in the year 2020.

Dr Zhongwei Zhang is the lead author on the study and a researcher at Karlsruhe Institute of Technology. He tells Carbon Brief that many AI weather forecast models were built for “general weather conditions”, as they use all historical weather data to train the models. Meanwhile, forecasting extremes is considered a “secondary task” by the models.

The authors explored a range of different “lead times” – in other words, how far into the future the model is forecasting. For example, a lead time of two days could mean the model uses the weather conditions at midnight on 1 January to simulate weather conditions at midnight on 3 January.

The plot below shows how accurately the models forecasted all extreme events (left) and heat extremes (right) under different lead times. This is measured using “root mean square error” – a metric of how accurate a model is, where a lower value indicates lower error and higher accuracy.

The chart on the left shows how two of the AI models (blue and green) performed better than the physics-based model (black) when forecasting all weather across the year 2020.

However, the chart on the right illustrates how the physics-based model (black) performed better than all three AI models (blue, red and green) when it came to forecasting heat extremes.

The authors note that the performance gap between AI and physics-based models is widest for lower lead times, indicating that AI models have greater difficulty making predictions in the near future.

They find similar results for cold and wind records.

In addition, the authors find that AI models generally “underpredict” temperature during heat records and “overpredict” during cold records.

The study finds that the larger the margin that the record is broken by, the less well the AI model predicts the intensity of the event.

‘Warning shot’

Study author Prof Erich Fischer is a climate scientist at ETH Zurich and a Carbon Brief contributing editor. He tells Carbon Brief that the result is “not unexpected”.

He adds that the analysis is a “warning shot” against replacing traditional models with AI models for weather forecasting “too quickly”.

The analysis, he continues, is a “warning shot” against replacing traditional models with AI models for weather forecasting “too quickly”.

AI models are likely to continue to improve, but scientists should “not yet” fully replace traditional forecasting models with AI ones, according to Fischer.

He explains that accurate forecasts are “most needed” in the runup to potential record-breaking extremes, because they are the trigger for early warning systems that help minimise damages caused by extreme weather.

Leonardo Olivetti is a PhD student at Uppsala University, who has published work on AI weather forecasting and was not involved in the study.

He tells Carbon Brief that “many other studies” have identified issues with using AI models for “extremes”, but this paper is novel for its specific focus on extremes.

Olivetti notes that AI models are already used alongside physics-based models at “some of the major weather forecasting centres around the world”. However, the study results suggest “caution against relying too heavily on these [AI] models”, he says.

Prof Martin Schultz, a professor in computational earth system science at the University of Cologne who was not involved in the study, tells Carbon Brief that the results of the analysis are “very interesting, but not too surprising”.

He adds that the study “justifies the continued use of classical numerical weather models in operational forecasts, in spite of their tremendous computational costs”.

Advances in forecasting

The field of AI weather forecasting is evolving rapidly.

Olivetti notes that the three AI models tested in the study are an “older generation” of AI models. In the last two years, newer “probabilistic” forecast models have emerged that “claim to better capture extremes”, he explains.

The three AI models used in the analysis are “deterministic”, meaning that they only simulate one possible future outcome.

In contrast, study author Engelke tells Carbon Brief that probabilistic models “create several possible future states of the weather” and are therefore more likely to capture record-breaking extremes.

Engelke says it is “important” to evaluate the newer generation of models for their ability to forecast weather extremes.

He adds that this paper has set out a “protocol” for testing the ability of AI models to predict unprecedented extreme events, which he hopes other researchers will go on to use.

The study says that another “promising direction” for future research is to develop models that combine aspects of traditional, physics-based weather forecasts with AI models.

Engelke says this approach would be “best of both worlds”, as it would combine the ability of physics-based models to simulate record-breaking weather with the computational efficiency of AI models.

Dr Kyle Hilburn, a research scientist at Colorado State University, notes that the study does not address extreme rainfall, which he says “presents challenges for both modelling and observing”. This, he says, is an “important” area for future research.

Limiting global warming to 2C would not ‘rule out’ extreme impacts

Climate modelling

|

25.03.26

Guest post: Investigating how volcanic eruptions can affect climate projections

Climate modelling

|

23.06.25

Meeting 1.5C warming limit hinges on governments more than technology, study says

1.5C

|

16.08.24

‘Striking’ new NASA videos show CO2 emissions rapidly building up in atmosphere

Climate modelling

|

27.06.23

The post Traditional models still ‘outperform AI’ for extreme weather forecasts appeared first on Carbon Brief.

Traditional models still ‘outperform AI’ for extreme weather forecasts

Christopher Wright is the principal analyst at CarbonBridge, a decarbonisation consulting firm.

The Santa Marta Conference has rightly been hailed as a pivotal opportunity to re-imagine the world’s relationship with fossil fuels. However, the sixty-odd countries gathered this week represent only 15% of the world’s total fossil fuel production, and a small but critical handful of nations in attendance remain deeply committed to expanding their fossil fuel output.

While the discussions at Santa Marta have focused on overcoming economic dependency on fossil fuels, the reality on the ground for many of these countries is that fossil fuel production continues to rise. Despite the rapid global growth of renewable electrification, fossil fuel output has similarly increased.

This trend is evident even among the countries gathered at Santa Marta, where according to a CarbonBridge analysis, net fossil fuel production has grown over the last five years, particularly driven by expansions in oil and gas output.

Across all countries gathered in Santa Marta, approximately 14 countries are responsible for the lion’s share of oil production, which has increased by 4% since 2020. Similarly, just eight countries account for 96% of the conference’s natural gas production, which has collectively grown by 5% over the past decade.

While coal production has seen a slight decline since 2020, recent production increases in Turkey and Pakistan, with renewed growth in Australia, could similarly see increased production in the near future.

However, most surprisingly, only six countries present at Santa Marta account for over 80% of fossil fuel production among all nations in attendance: Canada, Australia, Brasil, Mexico, Norway and Nigeria.

For these nations, the transition journey ahead is complex. All six countries are aiming to significantly expand renewable energy capacities, and Norway stands as a global leader in electric vehicle adoption.

However, fossil fuel production is not merely a domestic concern for these countries; it plays a central role in their international exports, and remains a foundational pillar of their economic utures. In fact, a deeper look into trends and regulatory frameworks across this suite of countries indicates that their current trajectories are geared toward continued fossil fuel expansion.

Canada

In Canada, oil and gas production continues to climb, with 2025 marking a year of record highs. Oil production rose by 4% to reach 5.34 million barrels per day (MMb/d), while natural gas production surged by 3.4%, reaching 8.2 billion gigajoules. And only yesterday, Shell made a $13.5 bln bet on Canada’s oil and gas future.

Led by Prime Minister Mark Carney, Canada is set to implement an industrial carbon pricing scheme and could double Canada’s clean energy capacity over the next two years. However, he has also been vocal about his support for new oil and gas expansions, new pipeline developments, and has even set a goal to transform Canada’s largely non-existent liquefied natural gas (LNG) industry over the next 15 years, with aspirations to rival the production capacity of the US by 2040.

Brazil

Brazil’s state-owned oil company Petrobras has committed to a massive USD $109 billion expansion of their production to 2030. This hefty investment follows a record 11% production increase in 2025, with Petrobras pumping out 3.77 million barrels per day. Despite hosting the UN climate negotiations last year and generating 89% of the country’s electricity from low-carbon sources in 2025, Brazil’s drive for fossil fuel expansion highlights the gap between national climate transitions and critical export opportunities.

Australia

Australia, the world’s second-largest coal exporter, faces a similar dislocation between its domestic electricity transition and its export economy, as it prepares to assume a leadership role at COP31. Australia is home to the world’s highest solar power per capita and leads the world in home battery rollouts. However, it remains critically dependent on fossil fuel exports, even as questions arise over long-term demand. Currently, gas export volumes, which dipped in 2025, are projected to reach record levels by 2027; pending legal action against the Barossa, Scarborough, and Browse expansions. While thermal coal production is projected to decline slightly through 2030, increases in metallurgical coal are expected to offset these declines, in part due to recent pro-mining regulatory shifts in Queensland.

Mexico

Mexico is one of three major oil producers that make up over 60% of the conference’s annual oil production. However, its oil industry recorded the largest output declines of any major producer in Santa Marta over the last decade. The state-owned oil company Pemex, currently carries close to $100 billion in debt, and was granted $12bn in debt support from the government last year. When combined with import shifts from the US, and potential competition from Venezuela, there is a real chance that Mexico’s oil production could decline further going forward. However, the goal right now from Pemex and the Mexican government, is to increase current production by close to 10% by 2030.

Nigeria

Nigeria’s national oil company, NNPCL, has similarly seen declines over the last decade, but is now pursuing a $60 billion partnership to expand its oil and gas output and solidify its role as one of Africa’s largest fossil fuel producers. This comes even as the federal government was granted $800,000 to explore opportunities to transition away from oil expansion last year.

Norway

In contrast to these countries, Norway stands as one of the few major oil producers at the conference projected to decrease its fossil fuel output. With a forecasted 15% reduction in oil and gas production by 2030, Norway appears to be taking early steps toward a transition. However, the decline in production is more a reflection of the age of its existing oil fields than a proactive shift in government policy. Despite acknowledging the need to diversify its economy, the Norwegian government continues to explore new oil and gas fields, plans to launch new licensing rounds, and hopes to spur on further oil and gas investments, which have almost doubled since 2017.

For these nations, the road ahead is fraught with complexities. While the Santa Marta conference offers an opportunity for dialogue, and renewable energies will undoubtedly continue to expand, the largest fossil fuel producers gathered in Colombia remain structurally focused on growth, rather than phase-downs.

Dollars and cents continue to drive economic decisions, especially in the midst of a global energy crisis. Despite growing calls to utilise this opportunity to reshape development pathways, countries most economically embedded in existing energy markets will need far more convincing, before turning their backs on billions in fossil fuel revenues.

The post Six nations at Santa Marta could shape fossil fuel futures appeared first on Climate Home News.

Six nations at Santa Marta could shape fossil fuel futures