Climate Forecasting in the Era of Category 6 Hurricanes

From predicting D-Day waves in WWII to the AI forecast and hurricanes becoming so strong that a new category is needed

In 1943, amidst the chaos of World War II, young oceanographer Walter Munk stumbled upon a critical revelation while aiding the war effort in Washington, DC: the erratic behavior of waves could jeopardize Allied plans to land troops in North Africa, causing huge casualties before the troops ever set foot on land.

The problem was the shifting shape of the ocean surface.

Waves at the proposed landing site were consistently higher than the safe limit, making the landing likely to fail unless it occurred on a calm day. The only options for success were blind luck or something no one had ever attempted: predicting waves, an endeavor unprecedented in naval strategy.

Teaming up with his previous boss and mentor, Harald Sverdrup, the Director of the Scripps Institution of Oceanography, they convinced the skeptical US Navy.

And so, they embarked on a project that would change the course of history.

A Forecast to Turn the Tides

Their approach was straightforward: understand the entire journey of waves from their inception to shore.

When air blows on a smooth surface like a glass of water, it pushes downwards, creating a dimple. This disturbance ripples across the surface due to surface tension. Similarly, waves in the ocean begin with the ever-shifting swirls of the turbulent air above, which create puffs of faster wind and changes in pressure, distorting the surface. As the wind blows sideways, it pushes on the upwind side of each ripple, causing the ripple to grow into a longer-lasting ocean wave, traveling in different directions with energy given by the wind.

Munk and Sverdrup, although lacking detailed knowledge, recognized that the mixture of wave sizes depended on the wind speed and the distance it had been blowing over the ocean. They used weather forecasts to predict wind-caused waves in the open ocean.

However, the problem for landing craft wasn’t the wind sea; it was about anticipating the aftermath of distant storms — the swells — that could wreak havoc on landing sites.

Waves are a shape that must travel. So they had to account for the transformation of waves from storm to shore, where some lose their energy but others keep going. These smooth, leftover waves, known as swell, continue to move outward across the sea surface, carrying their energy even after the wind has died down. And can easily keep going until they reach a coastline.

Munk and Sverdrup accounted for the transformation of waves from storm to shore, where waves become steeper before breaking. By considering these three stages separately, they successfully predicted the wave height experienced by the landing craft.

The wave prediction model, although it was rough and ready, got the big picture right. And their predictions proved pivotal in history.

In the early summer of 1944, the end of WWII was near. The Allied forces were ready to launch Operation Overlord from the British coast in an attempt to retake Western Europe from a weakened Germany. The success of this operation relied on a surprise crossing of the English Channel, with 132,000 troops landing in northern France by ship in a single day. Another 24,000 troops would be transported by air. But it also depended on favorable weather conditions, including a full moon and the right tides.

And it was Munk’s forecasts that influenced General Eisenhower’s decision to delay the D-Day invasion. The difference between potentially disastrous waves on June 5th and a more manageable sea on June 6th determined the outcome of the invasion that turned the tide of World War II. The ocean waves that could have caused one of the greatest wartime disasters for the Allies arrived on June 5th, but a day later, the ocean shape had changed; and so the most decisive amphibious landing in human history had far milder waves to contend with.

Munk and Sverdrup’s work laid the foundation for today’s wave and swell forecasts, shaping maritime operations worldwide. Yet, their story isn’t just about waves; it’s a reminder of the impact that understanding the ever-changing climate can dictate the fate of human history.

Transforming Forecasting with Deep Learning

So ever since World War II, computers have revolutionized weather forecasting, simulating the future state of the atmosphere and predicting everything from severe storms to heatwaves.

The gradual but steady improvement in weather forecasting, known as the “quiet revolution,” has significantly improved the accuracy of forecasts since Munk’s days. Today, a 6-day forecast is as reliable as a 3-day forecast from 30 years ago. This has saved lives and money by ensuring that severe storms and heatwaves catch people off guard.

However, traditional weather models come at a high cost, with billions of dollars spent on energy-intensive supercomputers that run continuously to produce a limited number of forecasts per day.

Now, artificial intelligence (AI) is reshaping this landscape.

Tech titans like Google, Huawei, and Nvidia have harnessed AI to predict weather patterns up to 10 days in advance with an accuracy topping traditional models. Google also has a short-term AI weather model that makes rolling 24-hour predictions that are more accurate than nearly any weather agency’s. Even the European Centre for Medium-Range Weather Forecasts (ECMWF), a leader in weather prediction, has embraced this shift, developing experimental AI forecasts. And other weather agencies are scrambling to catch up.

Unlike traditional models reliant on solving complex equations, these AI models employ “deep learning” to forecast based on learned patterns from 40 years of ECMWF “reanalysis” data — observations and short-term model forecasts that represent modelers’ best and most complete picture of past weather. As in with D-Day wave forecasting, this is progress on a task that was thought infeasible just a few years ago: AI models deliver forecasts in a fraction of the time, running on a desktop in mere minutes instead of hours on supercomputers, meaning they are also less energy intensive.

The new AI models aren’t perfect: they are an ongoing process. But as they evolve to learn directly from real-time weather observations, their potential for revolutionizing weather forecasting grows exponentially.

Meanwhile, challenges remain, especially when predicting extreme weather events in an increasingly unpredictable world.

One that may have to add a new hurricane category.

Brace For Impact: Hurricanes Bringing Off-Charts Intensity

With climate change fueling tropical cyclones, it might be time to upgrade the hurricane scale to include a Category 6 for these monstrous storms.

A recent study in the Proceedings of the National Academy of Sciences argues that the escalating fury of tropical cyclones due to global warming demands a new classification: Category 6. Typically, hurricanes in the Atlantic and typhoons in the Pacific are graded on the Saffir-Simpson Hurricane Wind Scale from Category 1 to 5 based on their maximum sustained winds. However, the scale stops at Category 5 for storms with winds exceeding 157 mph.

However, according to this study, it’s time to acknowledge the unprecedented ferocity of these storms by extending the scale to include Category 6 for exceptionally intense tropical cyclones. Here’s why:

1. Rising Intensity:

While the total number of hurricanes has remained steady, climate change has been fueling more destructive hurricanes over the past four decades.

The IPCC says it is likely that the global proportion of Category 3–5 tropical cyclone instances has increased globally over the past 40 years, and the ratio of Category 4–5 TCs will very likely increase globally with warming. And even basic physics supports that hurricanes get more intense as the climate warms, with climate models showing evidence of strengthening tropical cyclones, with recent major Tropical Cyclones (TCs) have reached extreme wind speeds above the 157 mph threshold.

Jeff Masters, a meteorologist at Yale Climate Connection, told Bloomberg Green that “every 1 degree Celsius increase in ocean temperature increases a hurricane’s destructive potential by 50%”. And the new study suggesting the addition of Category 6 has also found that with every two degrees Celsius of global warming above pre-industrial levels, the risk of one of these Category 6 storms increases by up to 50 percent near the Philippines and doubles in the Gulf of Mexico. The highest risk of these storms is in parts of Southeast Asia and Australia, the Philippines, and the Gulf of Mexico.

As temperatures rise, so do evaporation and heat transfer from the oceans to the air. So when storms navigate across warm oceans, they pull in more water vapor and heat. A hotter ocean, fueled by climate change, provides the energy for hurricanes to rapidly strengthen, resulting in devastating superstorms like Typhoon Goni, Hurricane Patricia with a top speed of 215mph when it formed near Mexico in 2015, or Typhoon Haiyan, which killed more than 6,000 people in the Philippines in 2013.

And then, there’s Otis, initially expected to be a tropical storm upon reaching the coast. Its winds accelerated faster than any other storm in the eastern Pacific on record, shocking meteorologists and the entire population of Acapulco, which was hit by the most powerful hurricane ever to strike Mexico. It transformed into a “catastrophic Category 5” hurricane, leaving everyone wondering: How did forecasters miss such a massive development?

2. Scientific Consensus:

Extending the scale aligns with having a theoretical understanding of the factors driving maximum hurricane intensity. Climate change bringing future warmer scenarios is a key player in ramping up the destructive potential of tropical cyclones, as supported by both empirical data and high-resolution climate models.

The authors are not calling for the addition to the scale just yet, but rather want it to raise awareness about the risk that major hurricanes fueled by global warming may cause.

“Our motivation is to reconsider how the open-endedness of the Saffir-Simpson Scale can lead to underestimation of risk, and, in particular, how this underestimation becomes increasingly problematic in a warming world,” study co-author Michael Wehner said in a statement.

Hurricane Sandy was just barely a Category 1 when it hit New York and New Jersey in 2012, but it still killed 43 people in New York City alone and at least 125 in the United States. A 2021 study found that the effects of climate change increased Sandy’s roughly $70 billion in damage by about $8 billion.

By introducing Category 6, emergency planners and the public gain crucial insight into the severity of impending storms, aiding in preparedness and response efforts. While some may argue that the practical difference between a Category 5 and 6 storm is negligible — both will wipe your house off the foundation and leave many casualties behind — the need for accurate information in critical situations cannot be overstated.

“Even under the relatively low global warming targets of the Paris Agreement, which seeks to limit global warming to just 1.5°C [2.7 degrees Fahrenheit] above pre industrial temperatures by the end of this century, the increased chances of Category 6 storms are substantial in these simulations,” said Wehner.

These Makes No Sense

Recent published research delivers a stark conclusion: half of our economies could be destroyed by 2070. 50% of GDP. Gone. This isn’t merely a monetary loss — it’s a future burned, drowned, incinerated, droughted, and flooded.

And the research doesn’t come from mere “alarmists” or advocacy groups; it stems from one of the most credible and conservative sources — the British Institute of Actuaries. Their objectivity is crucial. Actuaries have no incentive to exaggerate; their essence lies in precision and accuracy. They calculate risk, the backbone of the insurance industry. And living settlements in potential Category 6 Hurricane targets are not some risk insurance companies are willing to take.

The Wall Street Journal recently highlighted the urgency of the situation, revealing that ” Buying Home and Auto Insurance Is Becoming Impossible.” The reasons are stark and unambiguous: the past decade has borne witness to a relentless barrage of natural disasters fueled by warmer temperatures that amplify storms and exacerbate droughts.

The Journal was entirely clear about the likely consequences:

“Climate change will destabilize the global insurance industry,” research firm Forrester Research predicted in a fall report. Increasingly extreme weather will make it harder for insurance companies to model and predict exposures, accurately calculate reserves, offer coverage and pay claims, the report said.

As climate-related catastrophes become more frequent and powerful, they strain even the adaptive capabilities of developed nations, rendering vast territories uninsurable, overturning major investments, and crashing markets.

And in this tumultuous landscape, nobody is immune. Not even the sacrosanct, relentless-growth-at-all-costs economy. Because insurance woes are merely the tip of the iceberg.

Actuarial tables, once the bedrock of risk assessment, falter in the face of uncertainty. Climate change, responsible for claiming millions of lives since 2000, and destabilizing our planet, is upending the reliability of our predictive models as we hurtle into uncharted territories. Not even the timely emergence of AI as a powerful forecasting tool can give as a clear outlook.

Meanwhile, “Google searches related to “climate anxiety” are at a record high after steadily increasing over the past five years, the search giant said in an email to TIME. Searches worldwide related to “climate anxiety” or “eco-anxiety” increased by 4,590% from 2018 to 2023, according to the company’s data.”

And this comes hand in hand with the insurmountable cost-of-living crisis.

This is a new feeling, a new human experience. And a shared one.It’s not a pleasant one, for sure.

So it’s only fair to ask: what’s the point of a system like this?

Just read the following statements in the inequality report Oxfam releases every year:

“Since 2020, the richest five men in the world have doubled their fortunes. During the same period, almost five billion people globally have become poorer. Hardship and hunger are a daily reality for many people worldwide. At current rates, it will take 230 years to end poverty, but we could have our first trillionaire in 10 years.

Meanwhile, the dramatic increase in extreme wealth witnessed since 2020 has become set in stone. Billionaires are now US$3.3 trillion or 34% richer than they were at the beginning of this decade of crisis, with their wealth growing three times as fast as the rate of inflation.”

What’s the logic or reason in more than half the world getting poorer, while just a tiny handful of people get so rich they could make every single person in the world (!) $417.72 better off, more than the GDP per capita of the poorest 3 countries in 2023?

This makes no real sense.

We’ve reached the point where we need paradigmatic reinvention. We should be learning from our mistakes, my friends. That’s the essence of wisdom. And chief among our mistakes, is the climate crisis.

So, again, this is not a pleasant feeling. But we can make it a meaningful one.

Because there’s no forecast as to what lies ahead.

Be loud.

Thank you for your thorough reading and support! Subscribe for immediate insights and join the 400+ Antarctic Sapiens community for weekly thought-provoking content.