I apparently also ran out of memory for the site as too many people tried to view it at the same time. Updating it to a more robust hosting plan for the moment!
Fair enough but I find it dismaying to think enhanced greenhouse is locked in for 1.6 C to 2.6 C and people are talking about whether we can still stay under 1.5 C
I'm not sure I'd say its locked in per se; if all GHGs go to zero our best estimate is a net cooling (after a decade-scale warming bump) as CH4 and other shorter-lived species are removed from the atmosphere.
But thats assuming we can dramatically cut non-CO2 GHGs, which is challenging as a sizable portion come from agricultural systems.
Which is absolutely why we have to crank up albedo now and call the kettle (or Earth) black. It's a pipedream and the mother of moral hazards to assume we'll tame ghgs in time to avoid catastrophic climate meltdown.
Even if global average temperature declines after a warming bump I think we should not ignore or downplay the bump.
Admittedly I think it is public perceptions rather than expert knowledge that are affected and this is only a small part of public perceptions but when our leaders tossed it to public opinion/will of the people instead of treating it as their duty of care with due diligence public perceptions became critical to getting them to treat it with the seriousness needed.
I’m a particular fan of the “Joy Division” graph. I know the atmosphere is your thing but would love to see something like this (particularly projection v actual for the last 5 years) for sea temps.
The x-axis shows the distribution of anomalies for each year, with the height indicating the frequency of that anomaly occuring. The area under each of the curves adds up to 100%. Its just a standard probability density function: https://en.wikipedia.org/wiki/Probability_density_function
I think these great charts would be more impactful to an American audience if they used Fahrenheit instead of Celsius. A 2 deg C increase doesn’t “feel” like a 3.6 deg F increase.
"Most models overlook this, but the AIO (African Injection Oscillation) model shows that the stratosphere is the true 'creator' here. I've been tracking 70 hPa humidity levels, and the current data explains this extreme shift perfectly. It’s all about the stratospheric press. Follow my profile for the full research and charts."
In the Global Temperature Anomaly Distribution graph has the overall *shape* of the distribution changed in any consistent way eg become more left/right skewed, more bimodal etc?
The month vs year time series of temperatures is interesting and highlights the dominance of the Northern Hemisphere, i.e. land. So it would be great to see these for land vs ocean. This way the canceling effects between the two hemispheres would be ameliorated also.
Thanks Kevin; ERA5 conveniently provides a daily-updated GMST timeseries, but to my knowledge does not have readily available global land and ocean averages. To make a daily version of that would involve downloading and processing the full 0.25x0.25 resolution global field, which is on my list of things to do but is also a much bigger project (since we are talking about hundreds of gigabytes it not petabytes of data...).
This is great! Woud be good, as you add features (if you do) to add the ability to broaden the averaging window to mulityear-to-decadal timescales. Often in advice I've prepared (for the Australian government) I've created plots that average the most recent decade, the one before that, etc. For the purpose of making the point that although there is interannual variability, each decade since the ~1970s has been warmer than the decade prior. So, now in 2026, I'd compare the decade 2016-2025 to the decade 2006-2015, and so on. I've always done that in a rather clunky brute-force way, but the dashboard could automate and update regularly. 10-year window being arbitrary but easy for policymakers to understand.
A plot of warming by decade is useful, though might not be the best fit for a real time dashboard (since it only updates once a year). That being said, I strongly prefer using a locally linear regression to remove short-term variability rather than binning by arbitrary periods. E.g. the red line we use in our Berkeley Earth figures: https://berkeleyearth.org/global-temperature-report-for-2025/
Also reminded me that trend lines sometimes facilitate motivated reasoning. For 10+ years, some people kept pretending the trend started from the peak in 1998. "See, a plateau!"
I apparently also ran out of memory for the site as too many people tried to view it at the same time. Updating it to a more robust hosting plan for the moment!
Zeke, this is awesome! Great work putting that together. It's very clear even at a quick glance.
A 'What The Temperatures would be Without Sulfate Aerosols' graph might be instructive.
Wish I know the answer (aside from +0.2C to +1.2C warmer)!
Fair enough but I find it dismaying to think enhanced greenhouse is locked in for 1.6 C to 2.6 C and people are talking about whether we can still stay under 1.5 C
I'm not sure I'd say its locked in per se; if all GHGs go to zero our best estimate is a net cooling (after a decade-scale warming bump) as CH4 and other shorter-lived species are removed from the atmosphere.
But thats assuming we can dramatically cut non-CO2 GHGs, which is challenging as a sizable portion come from agricultural systems.
Which is absolutely why we have to crank up albedo now and call the kettle (or Earth) black. It's a pipedream and the mother of moral hazards to assume we'll tame ghgs in time to avoid catastrophic climate meltdown.
Am not a doomer. Am a realist.
Even if global average temperature declines after a warming bump I think we should not ignore or downplay the bump.
Admittedly I think it is public perceptions rather than expert knowledge that are affected and this is only a small part of public perceptions but when our leaders tossed it to public opinion/will of the people instead of treating it as their duty of care with due diligence public perceptions became critical to getting them to treat it with the seriousness needed.
I’m a particular fan of the “Joy Division” graph. I know the atmosphere is your thing but would love to see something like this (particularly projection v actual for the last 5 years) for sea temps.
I can't claim credit for the original idea; I think it was the BBC graphics team who made the first version back in 2024.
Yes, another vote for SSTs please ! 💙 🌊
What an incredible resource!
This is fabulous Zeke. What's the width of the "peaks" on the Unknown Pleasures chart?
The x-axis shows the distribution of anomalies for each year, with the height indicating the frequency of that anomaly occuring. The area under each of the curves adds up to 100%. Its just a standard probability density function: https://en.wikipedia.org/wiki/Probability_density_function
distribution of daily anomalies?
Yep
I think these great charts would be more impactful to an American audience if they used Fahrenheit instead of Celsius. A 2 deg C increase doesn’t “feel” like a 3.6 deg F increase.
"Most models overlook this, but the AIO (African Injection Oscillation) model shows that the stratosphere is the true 'creator' here. I've been tracking 70 hPa humidity levels, and the current data explains this extreme shift perfectly. It’s all about the stratospheric press. Follow my profile for the full research and charts."
Excellent work - looks great !
Future addition of SSTs would be very useful. 💙 🌊
You can perhaps request this from ECMWF. They are quite responsive to requests. It requires a good land sea mask.
Kevin
Dr Hausfather, GGGGREAT JOB! Always looking at gov sites for this and that but this is super!
Can albedo ( general ), aerosol, and cloud coverage be included?
Thanks!
In the Global Temperature Anomaly Distribution graph has the overall *shape* of the distribution changed in any consistent way eg become more left/right skewed, more bimodal etc?
If so, what does the tell us, if anything?
It has narrowed a bit over time, but thats primarily driven by cooler parts of the world (e.g. high latitude regions) warming faster than the tropics.
Zeke
This is wonderful
The month vs year time series of temperatures is interesting and highlights the dominance of the Northern Hemisphere, i.e. land. So it would be great to see these for land vs ocean. This way the canceling effects between the two hemispheres would be ameliorated also.
Thanks Kevin; ERA5 conveniently provides a daily-updated GMST timeseries, but to my knowledge does not have readily available global land and ocean averages. To make a daily version of that would involve downloading and processing the full 0.25x0.25 resolution global field, which is on my list of things to do but is also a much bigger project (since we are talking about hundreds of gigabytes it not petabytes of data...).
Brilliant, thankyou.
Can you please also post a simple graph tracking CO2 ppm from 1850 till present day
This is great! Woud be good, as you add features (if you do) to add the ability to broaden the averaging window to mulityear-to-decadal timescales. Often in advice I've prepared (for the Australian government) I've created plots that average the most recent decade, the one before that, etc. For the purpose of making the point that although there is interannual variability, each decade since the ~1970s has been warmer than the decade prior. So, now in 2026, I'd compare the decade 2016-2025 to the decade 2006-2015, and so on. I've always done that in a rather clunky brute-force way, but the dashboard could automate and update regularly. 10-year window being arbitrary but easy for policymakers to understand.
A plot of warming by decade is useful, though might not be the best fit for a real time dashboard (since it only updates once a year). That being said, I strongly prefer using a locally linear regression to remove short-term variability rather than binning by arbitrary periods. E.g. the red line we use in our Berkeley Earth figures: https://berkeleyearth.org/global-temperature-report-for-2025/
This is fantastic!
Also reminded me that trend lines sometimes facilitate motivated reasoning. For 10+ years, some people kept pretending the trend started from the peak in 1998. "See, a plateau!"