Quantum Noise in Sunlight Caps Weather Forecasts at 129 Days

Sabine Hossenfelder

Irreducible quantum uncertainty from solar photons cascades through atmospheric scales to make deterministic forecasting impossible beyond 129 days, leaving statistical climate models intact.

AI-assisted summary of The Butterfly Effect is Much Stranger Than We Thought — original source. Check the original for full context.

Source published: 2026-09-03

Key ideas

A new study indicates that quantum mechanics imposes an absolute theoretical limit of 129 days on deterministic weather forecasting, beyond which exact prediction is impossible regardless of computational power. (3:19)
The finding builds on Edward Lorenz's original, often misunderstood formulation of the butterfly effect: a Zeno-like convergent series where increasing measurement precision yields diminishing returns toward a hard horizon. (1:25)
The physical mechanism behind the 129-day wall is the irreducible quantum indeterminacy of incoming solar photons cascading upward through turbulent atmospheric fluid dynamics. (3:19)
Long-term climate projections remain fundamentally sound because they rely on statistical averages and boundary-forced trends rather than deterministic, date-specific weather states. (3:19)
While giving the study a 5/10 skepticism rating over its assumption of complete information loss, Sabine Hossenfelder argues that quantum chaos is a critically neglected field vital to technologies like quantum computing and nuclear fusion. (5:20)

Detailed notes

## Background Published by Sabine Hossenfelder on YouTube on September 3, 2026, this video examines new research establishing a hard quantum boundary on weather forecasting. According to the description, quantum physics renders weather prediction strictly impossible after 129 days, illustrating that the true meaning of Edward Lorenz's butterfly effect extends far deeper into fields like quantum computing and nuclear fusion.

## TL;DR Sabine Hossenfelder breaks down a recent physics paper demonstrating that deterministic weather forecasting hits an impenetrable physical wall at 129 days due to quantum mechanics. She clarifies that Edward Lorenz's original conception of the butterfly effect was a convergent, Zeno-like series of diminishing predictive returns, establishing a finite horizon even with infinite measurement precision. In the new study, unavoidable quantum uncertainty from incoming solar photons cascades upward into macroscopic atmospheric turbulence, wiping out deterministic forecasts while leaving statistical climate models unaffected. Assigning the paper a 5 out of 10 on her bullshit meter, she underscores that quantum chaos is an underrated field with critical implications for technologies such as quantum computing.

## Atmosphere & style The video delivers Sabine's trademark deadpan, analytical tone, weaving dry humor and personal quips into a rigorous breakdown of atmospheric physics. It feels sharp and conceptually lucid, taking viewers through mathematical paradoxes and fluid dynamics without losing accessible grounding. The delivery balances healthy scientific skepticism with an engaging, brisk pace, culminating in an abrupt, comedic demonstration of predictive limits.

## Bulletin - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) A new study indicates that quantum mechanics imposes an absolute theoretical limit of 129 days on deterministic weather forecasting, beyond which exact prediction is impossible regardless of computational power. - [01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) The finding builds on Edward Lorenz's original, often misunderstood formulation of the butterfly effect: a Zeno-like convergent series where increasing measurement precision yields diminishing returns toward a hard horizon. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) The physical mechanism behind the 129-day wall is the irreducible quantum indeterminacy of incoming solar photons cascading upward through turbulent atmospheric fluid dynamics. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) Long-term climate projections remain fundamentally sound because they rely on statistical averages and boundary-forced trends rather than deterministic, date-specific weather states. - [05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) While giving the study a 5/10 skepticism rating over its assumption of complete information loss, Sabine Hossenfelder argues that quantum chaos is a critically neglected field vital to technologies like quantum computing and nuclear fusion.

## Key takeaways - [00:00](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=0s) Integrating quantum mechanics into chaos theory transforms long-range atmospheric forecasting from practically difficult into theoretically impossible beyond a definitive temporal boundary. - [01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) The textbook interpretation of the butterfly effect—that tiny initial differences merely cause exponential divergence over time—diverges from Edward Lorenz's actual conceptual argument. - [01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) Lorenz's original concept, described by physicist Tim Palmer as the 'real butterfly effect,' operates like Zeno's paradox, where successive doublings of measurement precision yield a convergent series of diminishing forecast extensions. - [01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) Because the series of predictive returns converges to a finite sum, even an observer with infinite measurement precision would hit an impassable prediction horizon. - [01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) This finite predictive horizon is relevant across nonlinear physics, including plasma turbulence in nuclear fusion, robotics, and black holes. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) Applying this framework to Earth's atmosphere establishes a strict deterministic weather forecasting cutoff at exactly 129 days. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) Deterministic forecasting crashes into the 129-day limit even assuming infinite supercomputing capacity, perfect physical equations, and zero macroscopic measurement error. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) Rather than relying on abstract mathematical limits, researchers traced the unavoidable initial disturbance to the quantum uncertainty inherent in incoming solar photons. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) Irreducible quantum uncertainty at the photon level progressively cascades upward through turbulent atmospheric eddies until macroscopic predictability is destroyed. - [03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) The 129-day forecasting wall does not invalidate climate models, as climate science projects long-term statistical averages and probabilities rather than deterministic regional weather states. - [05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) The paper receives a 5 out of 10 on the 'bullshit meter' due to skepticism over whether quantum fluctuations genuinely obliterate all information from the system's initial state. - [05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) Quantum chaos remains one of the most underrated frontiers in foundational physics, carrying crucial implications for the feasibility and noise limits of multi-billion-dollar quantum computing hardware.

## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=0s) Quantum Physics and the Prediction Wall

The butterfly effect is far stranger than common intuition suggests. While chaos theory is widely recognized for making long-term forecasting notoriously difficult, a team of researchers has demonstrated that factoring in quantum mechanics transforms forecasting from merely difficult to strictly impossible past a hard temporal boundary. Calculating this specifically for Earth's atmosphere—one of the most notoriously complex chaotic systems in existence—raises an immediate and crucial question: does this fundamental limit also destroy our ability to model and predict the long-term climate?

Before diving into the atmospheric physics, Sabine touches upon personal stress, noting dryly that physical and mental health can suffer severe damage from it—"Ask me how I know." She highlights the video's sponsor, BetterHelp, an online network designed to match users with credentialed therapists via video, phone, or direct messaging. Navigating mental health struggles should not require expending one's final ounce of energy just to hunt down an available provider, an obstacle she faced personally. Addressing past criticisms of the service, she notes that the platform has instituted substantial changes, now holds a 4.8 out of 5 rating on the App Store, and has served over six million people.

- The study identifies an absolute quantum threshold beyond which atmospheric prediction cannot occur. - Sponsoring partner BetterHelp provides online therapy matching, offering flexible communication formats and a sign-up discount for viewers.

---

[01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) What Edward Lorenz Actually Meant: The "Real" Butterfly Effect

The concept of the butterfly effect traces directly back to meteorologist Edward Lorenz, who discovered that planetary weather behaves with extraordinary sensitivity to initial conditions. In popular culture, this is immortalized by the poetic idea that the flap of a butterfly's wings in Brazil could trigger a tornado in Texas. Formally, this standard interpretation states that if two initial states differ by even a minuscule margin, their trajectories will diverge exponentially over time. However, as climate physicist Tim Palmer has repeatedly emphasized, this textbook version misses what Lorenz was actually trying to demonstrate: what Palmer dubs the "real butterfly effect."

Lorenz's original paper laid out an argument resembling Zeno's paradox. Suppose you refine the precision of your initial atmospheric measurements by a factor of two; you might extend your accurate forecast window by a factor of one half. Improve measurement precision by another factor of two, and you gain only another $(1/2)^2$, then $(1/2)^3$, and so on. Because this geometric series converges to a finite sum, an observer possessing even infinite measurement precision would still hit an impenetrable predictive horizon beyond which no deterministic calculation could see. Lorenz never provided a rigorous mathematical derivation of this phenomenon—he offered a compelling conceptual argument—and the idea has been largely overlooked in modern scientific literature. Yet if this hard horizon exists in nature, it applies universally across nonlinear physics, governing phenomena in nuclear fusion, robotics, quantum computing, and black holes.

```mermaid flowchart TD accTitle: Lorenz Real Butterfly Effect vs Standard Chaos accDescr: Diagram contrasting standard exponential divergence with Lorenz's convergent Zeno-like prediction horizon.

subgraph Standard["Standard View of Chaos"] S1["Tiny Initial Difference (Δx)"] --> S2["Exponential Divergence Over Time"] S2 --> S3["Predictions Degrade Gradually"] end

subgraph Lorenz["The Real Butterfly Effect (Lorenz / Palmer)"] L1["Measurement Precision 2×"] --> L2["Added Time Window +1/2"] L2 --> L3["Further Precision 2× -> +(1/2)²"] L3 --> L4["Convergent Zeno Series"] L4 --> L5["Impenetrable Prediction Wall"] end ```

- **Popular Chaos:** Trajectories diverge rapidly, but greater precision historically implied an arbitrarily extended prediction window. - **The "Real" Butterfly Effect:** A convergent series of diminishing predictive returns establishes a hard temporal wall, irrespective of infinite measurement accuracy. - **Wider Scope:** Applies to any chaotic system where micro-scale fluctuations cascade upscale, including plasmas in fusion reactors and astrophysical event horizons.

---

[03:19](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=199s) The 129-Day Quantum Limit on Weather Forecasts

Investigating whether Earth's atmosphere possesses such a finite prediction barrier, the authors of the new study concluded that a definitive wall exists: exactly 129 days. Beyond day 129, deterministic weather forecasting is not merely computationally impractical; it is theoretically impossible. Even if one possessed a flawless mathematical model of the atmosphere, limitless supercomputing resources, and zero initial measurement error at macroscopic scales, the forecast would still crash into this wall.

The authors' reasoning departs from Lorenz's original logic. Lorenz posited that inevitable micro-disturbances at the molecular scale would systematically contaminate progressively larger scales until predictability collapsed. Rather than wrestling with the mathematical abstractions of taking limits down to infinitely tiny spatial scales, the researchers investigated the concrete physical sources of unavoidable environmental disturbances. Their conclusion centers on sunlight: Earth is constantly bombarded by quanta of light from the sun, but quantum mechanics strictly forbids anyone from knowing the precise quantum state of every incoming photon. This irreducible quantum uncertainty acts at the smallest physical scales and steadily cascades upward into turbulent atmospheric energy. Calculating the exact rate at which this photon energy disperses through atmospheric fluid dynamics yields the 129-day limit.

Crucially, this hard stop does not invalidate climate science. While weather forecasting attempts to determine specific regional conditions at a precise moment—such as whether it will rain in Paris on July 14, 2030—climate models project statistical averages over decades and centuries. Climate projections calculate shifts in average ocean temperatures relative to rising greenhouse gases or estimate the changing probability of extreme weather anomalies. The 129-day limit simply defines the exact point in time at which statistical averaging becomes the only possible predictive tool available.

```mermaid flowchart LR accTitle: Solar Quantum Cascades and Atmospheric Predictability accDescr: Flowchart illustrating how quantum uncertainty in solar photons cascades into macroscopic atmospheric scales, creating a 129-day weather limit without affecting climate averages.

subgraph QuantumOrigin["Quantum Source"] P["Incoming Solar Quanta"] --> U["Fundamental Quantum Uncertainty"] end

subgraph Cascade["Atmospheric Upscaling"] U --> M["Molecular Scale Disruptions"] M --> T["Turbulent Energy Cascade"] T --> A["Full Atmospheric Dispersion"] end

subgraph Outcomes["Forecasting Horizons"] A -->|"Day 1 to 129"| W["Deterministic Weather Window"] A -->|"Beyond Day 129"| C["Weather Impossible: Climate Averages Only"] end ```

- **The Threshold:** Atmospheric determinism completely breaks down at 129 days. - **The Physical Mechanism:** Unavoidable quantum indeterminacy inherent in incoming solar radiation spreads upward through atmospheric eddy scales. - **Weather vs. Climate:** Weather tracks exact deterministic paths; climate computes statistical ensembles and broad boundary-forced averages, leaving climate models fundamentally unaffected by this limit.

---

[05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) Grading the Study and the Underrated Field of Quantum Chaos

Sabine awards the paper a "5 out of 10 on the bullshit meter." Her primary hesitation stems from the authors' assumption that quantum effects completely wash out and erase all information carried by the initial state. Despite that skepticism, she regards the work as a conceptually vital addition to modern physics, lamenting that physicists across other disciplines often neglect the intersection of quantum mechanics and classical chaos.

In her view, quantum chaos represents perhaps the most underrated research frontier in foundational physics today. Understanding these limits is essential before pouring billions of dollars into scaling quantum computers, where fundamental boundaries on precision and stability could dictate hardware feasibility. Concluding with a deadpan illustration of how predictive power degrades over time, Sabine asks how many words it takes when predicting human speech before all predictive capability vanishes entirely, abruptly answering: "Broccoli." She closes with a playful jab at large language models: "Do you think ChatGPT would have made this joke? Thanks for watching. See you tomorrow."

- **Paper Rating:** 5/10 on the bullshit meter due to unresolved questions about whether quantum fluctuations genuinely obliterate all initial-state information. - **Broader Implications:** Quantum chaos has critical real-world stakes for the viability and error margins of multi-billion-dollar quantum computing efforts. - **Linguistic Predictability Punchline:** The breakdown of predictive modeling demonstrated in real time with a single absurd word ("Broccoli").

## Notable quotes > [00:00](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=0s) Ask me how I know. — Sabine Hossenfelder

> [01:25](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=85s) real butterfly effect — Tim Palmer

> [05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) 5 out of 10 on the bullshit meter — Sabine Hossenfelder

> [05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) Broccoli. — Sabine Hossenfelder

> [05:20](https://www.youtube.com/watch?v=8RHLYIZCPG4&t=320s) Do you think ChatGPT would have made this joke? Thanks for watching. See you tomorrow. — Sabine Hossenfelder

## Mentioned BetterHelp, Edward Lorenz, Tim Palmer, ChatGPT, Sabine Hossenfelder, App Store

## Video description Head to https://betterhelp.com/sabinehossenfelder to get 10% off your first month with our paid partner, BetterHelp. Therapy can be a meaningful space to reflect, grow, and create positive change in your life.

The butterfly effect is much stranger than most people think, and the famous line about a butterfly in Brazil isn't what Lorenz actually meant. A group of researchers has now worked out that quantum physics puts a hard wall on weather prediction, at 129 days. Not difficult after that. Impossible. And this has implications far beyond the weather forecast because chaos enters in everything from nuclear fusion to robotics to black hole physics. Let's take a look.

Paper: https://doi.org/10.1007/s00376-026-5621-8

#science #sciencenews #physics #quantumphysics #butterflyeffect #chaostheory

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[Source](https://www.youtube.com/watch?v=8RHLYIZCPG4)

中文简报

太阳量子不确定性为全球天气预报设定129天上限入射太阳光中不可知的量子态会级联放大为宏观大气扰动，为确定性预报设定了129天的绝对界限，但并不影响长期的统计气候模型。该视频重温了爱德华·洛伦茨（Edward Lorenz）最初提出的蝴蝶效应概念，解释了即使具备无限的测量精度，混沌动力学也只能得出有限的预测视界。Sabine探讨了近期的一项研究，该研究表明入射太阳辐射中不可避免的量子不确定性会级联放大至宏观天气模式，从而在129天处形成不可逾越的预测极限。她向观众说明，这一理论极限并不会否定长期气候模型，因为后者依赖的是统计平均值而非确定性的逐日天气预报。尽管她在自己的“胡扯度量仪”（BS meter）上给这项研究打了5分（满分10分），但她强调量子力学与混沌理论的交叉点仍是一个被严重忽视的重要领域，且与量子计算等技术密切相关。一项新研究计算出确定性天气预报的绝对理论上限为129天；超过这一时限，无论计算能力有多强或建模精度有多高，预测在物理上都是不可能实现的。 (3:19) 129天的预报视界由具有不可知量子态的入射太阳光子引起，它们产生的微观扰动向上级联放大，最终主导全球大气环流。 (3:19) Edward Lorenz最初提出的蝴蝶效应概念不仅是对初始条件的敏感依赖，更是一种类似于芝诺悖论的现象，即即使拥有无限的测量精度，也只能获得有限的预测时间范围。 (1:25) 尽管存在129天的限制，长期气候模型在方法论上仍然可靠，因为它们预测的是统计平均值和概率变化，而非具体的每日天气状况。 (4:46)

Reading summary

While chaos theory is widely known for making long-term forecasting difficult, a new study factoring quantum mechanics into atmospheric physics claims that deterministic weather prediction becomes strictly impossible beyond 129 days. Host Sabine Hossenfelder examines how this hard prediction wall connects to Edward Lorenz's overlooked original theory, why it leaves long-term climate modeling intact, and where the study's assumptions may fall short. Lorenz and the "Real" Butterfly Effect (1:25) In popular culture, meteorologist Edward Lorenz's butterfly effect is understood as extreme sensitivity to initial conditions—the idea that a butterfly flapping its wings in Brazil could trigger a tornado in Texas. Under this standard view, two slightly different starting states diverge exponentially over time, which historically implied that greater measurement precision could arbitrarily extend a forecast's valid window. However, climate physicist Tim Palmer has emphasized that this textbook interpretation misses what he calls the "real butterfly effect" from Lorenz's original paper. Lorenz proposed a conceptual argument resembling Zeno's paradox. If doubling the precision of initial atmospheric measurements extends a forecast window by a factor of 1/2, doubling it again adds only (1/2)², and then (1/2)³. Because this geometric series converges to a finite sum, even an observer with infinite measurement precision would eventually hit an impenetrable predictive horizon. Although Lorenz never provided a rigorous mathematical derivation and the concept has been largely overlooked, the existence of such a hard boundary in nature would apply universally across nonlinear physics, affecting fields from nuclear fusion and robotics to quantum computing and black holes. Solar Photons and the 129-Day Forecast Wall (3:19) Investigating whether Earth's atmosphere possesses a finite prediction barrier, the authors of the new study calculated an absolute limit of 129 days. Beyond this threshold, deterministic weather forecasting is theoretically impossible, even if researchers possessed a flawless mathematical model, limitless supercomputing power, and zero initial measurement error at macroscopic scales. To reach this figure, the researchers departed from Lorenz's original logic. Rather than wrestling with the abstract mathematics of taking limits down to infinitely small spatial scales, they identified a concrete physical source of micro-scale disruption: sunlight. Earth is constantly bombarded by solar photons, and quantum mechanics strictly forbids knowing the exact quantum state of every incoming photon. The authors calculated the rate at which this irreducible quantum uncertainty cascades upward into turbulent atmospheric fluid dynamics, concluding that it completely overwhelms deterministic predictability at day 129. Deterministic Weather Versus Statistical Climate Models (3:19) A hard quantum limit on atmospheric prediction raises an immediate question about the validity of long-term climate science. Hossenfelder clarifies that the 129-day barrier does not undermine climate models because weather and climate rely on fundamentally different types of prediction. Weather forecasting seeks to calculate specific regional conditions at an exact future moment, such as whether it will rain in Paris on July 14, 2030. In contrast, climate models project statistical averages and boundary-forced trends over decades and centuries, such as estimating shifts in average ocean temperatures relative to rising greenhouse gases or calculating the changing probability of extreme weather anomalies. Rather than invalidating climate projections, the 129-day threshold simply defines the exact temporal boundary where deterministic tracking fails and statistical averaging becomes the only viable predictive tool. Hossenfelder ultimately gives the study a "5 out of 10 on the bullshit meter," expressing skepticism toward the authors' assumption that quantum effects completely wash out and erase all information from an initial state. Despite this reservation, she praises the paper for exploring the neglected intersection of quantum mechanics and classical chaos. She contends that quantum chaos is perhaps the most underrated frontier in foundational physics today, warning that researchers must understand these fundamental limits on precision and stability before pouring billions of dollars into scaling quantum computers.

Source quotes

[0:00] Sabine Hossenfelder: Ask me how I know. [1:25] Tim Palmer: real butterfly effect [5:20] Sabine Hossenfelder: 5 out of 10 on the bullshit meter [5:20] Sabine Hossenfelder: Broccoli. [5:20] Sabine Hossenfelder: Do you think ChatGPT would have made this joke? Thanks for watching. See you tomorrow.

Original transcript

[0:00] The butterfly effect is much stranger than we thought. A group of researchers just showed that [0:06] if you take into account quantum physics, then it doesn't just make predictions difficult, it makes [0:12] predictions impossible after a certain time. They worked this out concretely for one of the [0:19] most complicated chaotic systems we know, Earth's atmosphere. Does this mean that we can't predict [0:26] the climate either? Let's have a look. Stress can damage your health both physically and mentally. [0:34] Ask me how I know. If you struggle with mental health problems or know someone who does, today's [0:40] paid partner BetterHelp can help. BetterHelp matches you online with a credential therapist [0:46] based on your needs. You can talk by video, phone, or messaging, whatever works for you. I [0:52] think BetterHelp is a service that the world needs because especially with mental health problems, [0:57] it shouldn't eat up someone's last remaining energy to find a therapist. For me, this was a [1:03] real obstacle. Yes, I know they've seen criticism in the past, but they've made changes and now have [1:09] a 4.8 out of 5 rating in the App Store. More than 6 million people have gotten BetterHelp this [1:16] way. Use betterhelp.com/sabine or my code during sign up for 10% off your first month. And now, [1:25] back to the science news. The name butterfly effect goes back to meteorologist Edward Lorenz [1:31] who found out that the weather on our planet is extremely sensitive to small perturbations. [1:38] The flap of a butterfly's wings in Brazil could set off a tornado in Texas. More formally, [1:44] if you start with two initial states that are just a tiny little bit different, then over time, [1:49] the difference between them can grow dramatically. This part of the butterfly effect is quite well [1:55] known, but few people knew that this actually wasn't Lorenz's point. His point was what climate [2:02] scientist Tim Palmer has called the real butterfly effect. If you read Lorenz's original paper, [2:08] you'll see that he was really arguing that weather prediction suffers from a sort of Zeno effect. If [2:15] you improve the precision by which you know the initial conditions by a factor of say 2, then [2:20] you can increase the time over which you can make an accurate prediction by one half. Improve the [2:26] precision by another factor of 2, and you add another one half squared, then one half cubed, and [2:31] so on. This means that even if you could measure the initial conditions to infinite precision, [2:37] you'd not be able to make predictions beyond a certain time horizon, even though the system's [2:43] fully deterministic. Whether this real butterfly effect is actually "real" in the sense of happening [2:49] in nature has never been settled, because Lorenz didn't, strictly speaking, derive it. He just made [2:56] a compelling argument. I found it both interesting and somewhat concerning that this real butterfly [3:01] effect has gotten almost entirely lost in the literature, because if it happens in nature, [3:07] it doesn't just happen for the weather forecast. It'd be a general property of chaotic systems [3:13] relevant for everything from nuclear fusion to quantum computing to black holes. In any case, [3:19] the authors of the new paper now looked at this question, whether there is such a finite horizon [3:24] for predictions for the weather, and they found that yes, there is, and it's 129 days. [3:31] After that time, they say weather forecast isn't just practically, but even theoretically [3:37] impossible. Even if you knew the initial state perfectly, had a perfect model, [3:42] and unlimited computing power, you still wouldn't be able to get past the 129 days. Their argument, [3:49] however, is rather different from the argument that Lorenz made. Lorenz made a general argument [3:55] which said that inevitable changes on small scales like molecules would spread to larger and larger [4:00] scales, eventually making predictions impossible. The authors of the new paper have sidestepped the [4:07] question of just what happens at the limit to infinitely small scales by instead asking [4:13] what the physical causes for unavoidable disturbances are and what we know about [4:18] them. Their answer is kind of obvious. Earth constantly receives quanta of light from the sun, [4:24] but we don't know the exact quantum state of the sunlight. We can't know it. Quantum [4:28] physics forbids it. This quantum uncertainty first affects very small scales, but from there [4:34] it spreads to larger and larger scales until it has spread through the entire atmosphere. [4:39] They calculate how long it take for the energy of the quanta to spread, and that gives them the 129 [4:46] days. What does this mean for climate models that make predictions over years or hundreds of years? [4:52] The maybe somewhat surprising answer is pretty much nothing because climate models already [4:57] deal with averages. They'll tell you the average ocean temperature as a function of average carbon [5:03] dioxide or the probability of certain extreme events. They won't tell you whether it rains [5:08] in Paris on July 14th, 2030. The calculation for the butterfly effect tells you how long it [5:15] takes until average prediction is the best you can do. It doesn't make the average prediction [5:20] any better or worse. I give this paper a 5 out of 10 on the [ __ ] meter. That's because [5:26] I'm not super convinced by their argument that quantum effects entirely erase the information [5:31] of the initial state. Still, I think that this paper's conceptually an important contribution [5:37] to the literature and I wish that physicists in other disciplines would pay more attention to [5:43] this. The intersection of quantum physics and chaos is maybe the most underrated research [5:49] direction in the foundations of physics today. When you want to know if there's a fundamental [5:53] limit to the precision your quantum computer can reach before spending a few billion dollars on it, [6:00] maybe that's just me. If you try to predict what someone will say from what [6:05] they've previously said, how many words does it take until you lose all predictive power? [6:12] Broccoli. Do you think ChatGPT would have made this joke? Thanks for watching. See you tomorrow.