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The Sun Itself May Set the Outer Limit of Weather Forecasting
In A Nutshell
- A new study estimates that the true theoretical limit of weather predictability is about 129 days, far beyond the “two to three weeks” figure scientists have cited since the 1960s.
- Today’s forecasts stay reliably useful out to about 14 days, and the study suggests future advances could theoretically extend that by up to 57 more days.
- Instead of guessing at atmospheric behavior that has never been observed, researchers built their estimate from well-measured data on the sun’s energy flowing in and out of the atmosphere.
- The researchers stress this is a theoretical ceiling, not a near-term forecast, and the results still need to be confirmed by other scientists.
Weather forecasters have gotten remarkably good at their jobs. A 10-day forecast today is more accurate than a 5-day forecast was decades ago. But there is a ceiling, a limit no amount of computing power, better satellites, or smarter models will ever push past. A team of researchers now believes it has calculated where that ceiling sits, and the answer is both surprising and counterintuitive.
According to a new study published in the journal Advances in Atmospheric Sciences, the estimated theoretical limit of weather predictability is approximately 129 ± 7 days, dramatically longer than the “two to three weeks” figure that has circulated among scientists since the 1960s. Perhaps more importantly, the study estimates that today’s forecasts, which stay reliably useful out to about 14 days, could potentially be extended by as many as 57 additional days with future advances in technology, though the authors frame this as theoretical potential, not a near-term forecast of what will actually happen.
That figure stands out sharply against prior modeling-based estimates, which suggested future improvements might squeeze out only 2 to 5 more days of useful forecasting. If the analysis holds up, the payoff for improving weather prediction is far larger than many have assumed.
A Quirk of Sunlight Puts a Hard Stop on Every Forecast
On paper, the atmosphere follows physical laws. Given a perfect snapshot of the atmosphere right now and a perfect computer model of how it evolves, one might expect to predict the future indefinitely. That intuition runs into a fundamental problem rooted in the sun itself.
Sunlight constantly pumps energy into the atmosphere, and that’s where the trouble starts. The tiniest particles of light streaming in from 93 million miles away behave in ways that can never be fully pinned down, no matter how good instruments get. Those tiny, random flickers ripple into the smallest wind and temperature patterns in the air, planting a seed of static that spreads. Over time, that static works its way from small patterns up to big ones, eventually scrambling even continent-sized weather systems. Once the sun has effectively replaced all the energy currently sitting in the atmosphere, any thread connecting today’s forecast to tomorrow’s actual weather has snapped. That’s not a glitch computers could someday fix. It’s baked into how any system that runs on outside energy behaves.
Well-Measured Sunlight Data, Not Guesswork, Set the New Limit
Prior attempts to pin down the predictability limit ran into a stubborn obstacle: the very small-scale atmospheric behavior that drives forecast error growth has never been directly observed, and computer models cannot simulate it accurately. That left scientists guessing at behavior they could not measure, producing estimates the researchers argue may be far too low.
This study took a different approach. Rather than trying to simulate those unobservable fine-scale processes, the team focused on quantities that are already well-measured: the total energy stored in the atmosphere and the rate at which energy flows in from the sun and back out as heat. Their core insight: the maximum time a forecast can stay connected to reality equals the time it takes incoming solar energy to fully replace the energy already in the atmosphere. Once that swap is complete, the noise carried in by sunlight has wiped out any trace of the original state.
For total atmospheric energy, the team used an established annual average estimate, then compared it against incoming and outgoing energy while excluding energy that never actually touches the atmosphere, like sunlight bounced straight back into space by clouds. Run the math, and the answer comes out to 129 ± 7 days.
Forecasts Could Stretch Far Beyond Today’s Two-Week Horizon
Breaking that gap down shows where the real opportunity lies. The 115 days researchers haven’t yet unlocked splits into two very different parts.
Roughly 57 days of additional accurate forecasting could theoretically be unlocked through better observations and models that pick up finer detail in the atmosphere. That’s the piece that matters most to ordinary people: real forecasts of actual weather, at actual places, weeks further out than anything available today, including the stretch a month or two out that current forecasts handle worst. Another roughly 57 days beyond that would add only a fuzzier kind of skill, useful mainly to specialized researchers rather than someone checking whether to pack an umbrella.
The researchers are careful to note that reaching the theoretical limit is a task for future technology, not something imminent, and they acknowledge the results still need to be checked by other scientists. Still, the approach is a real departure from decades of prior work. Instead of guessing at behavior nobody has ever actually seen, the team built its estimate entirely from things that are already well measured. That is why the number carries weight even though it upends a figure the field has trusted since the 1960s.
Science has long accepted that weather prediction has a ceiling. This study puts a specific number on it, changing the scale of what forecasters might one day achieve.
Disclaimer: This article is based on a peer-reviewed study and reflects the findings and interpretations of the study’s authors. The 129-day estimate is theoretical and has not yet been confirmed by independent research.
Paper Notes
Limitations
The authors are explicit about several limitations of this work. Most significantly, the results await confirmation or review by future independent studies, and the researchers themselves flag this directly in the paper. The 129-day estimate carries a 95% uncertainty range of plus or minus 7 days, arising from gaps in observational data, particularly over the Southern Hemisphere, and from uncertainties in the energy flux measurements used in the calculation. Additionally, while the methodology is designed to avoid assumptions about the unobservable fine-scale behavior that plagued prior approaches, the framework still relies on idealized conditions, including the assumption that the atmosphere is in approximate energetic balance. The paper also notes that some energy flux quantities used in the calculation are not directly observable and must be estimated from other observed data. The study is focused specifically on what the authors call “chronological” or internal predictability, meaning prediction of the actual sequence of future weather events. Longer-range statistical predictability, such as forecasting seasonal patterns based on ocean temperatures, is explicitly outside the scope of this paper.
Funding and Disclosures
According to the acknowledgements section of the paper, Wei Zhang and Ben Kirtman received support from NOAA under grant numbers NA20OAR4320472, NA22OAR4310603, NA23OAR4590384, and NA23OAR4310457, and from NSF under grant numbers AGS2241538 and AGS2223263. Ben Kirtman is identified as the William R. Middelthon Chair of Earth Sciences. Zoltan Toth conducted some of his work on this study while employed at NOAA’s Global Systems Laboratory. The authors declare that there are no conflicts of interest. The article is published open access under a Creative Commons Attribution 4.0 International License.
Publication Details
Paper Title: A New Approach to Estimating the Limit of Predictability | Authors: Wei Zhang, Zoltan Toth, Feifan Zhou, Jie Feng, Malaquias Peña, and Ben Kirtman | Journal: Advances in Atmospheric Sciences (2026) | DOI: 10.1007/s00376-026-5621-8 | Author Affiliations: Authors are affiliated with the Rosenstiel School of Marine, Atmospheric, and Earth Science at the University of Miami; Princeton University; NOAA’s Global Systems Laboratory (retired); the Institute of Atmospheric Physics at the Chinese Academy of Sciences; the University of Chinese Academy of Sciences; Fudan University; and the University of Connecticut, among other institutions.







