Occasional Thoughts on Climate Change

[bluewave]

Really extreme to see parts of France go +10° F for the first half of summer using the warmest 1991-2020 climate normals.

With a +4.2°C deviation from the already warmed 1991-2020 baseline, the tally for the first half of the meteorological summer is eye-opening. The 2026 anomaly forces us to scale up the graph, to the point of literally compressing 2003 (+2.8°C "only"). ➡️From the Center-West to Burgundy, we're seeing unprecedented values of +5 to +6°C. ➡️The rainfall deficit is just as stark, ranging from -30% in the north to -100% in the Var. The Center-West, where the vegetation is already completely scorched, hovers between -60 and -80%. ➡️Over the past month, nearly every day has been spent above the heatwave threshold, with only a 4-day pause at the start of July. ➡️The third heatwave should wrap up this weekend. But in the southwest, temperatures will remain heatwave-level (34 to 38°C) for an indeterminate period. Given the hot air mass south of Europe, we're far from safe from a 4th heatwave later in the summer.

 

France is dry and scorched. After already surpassing 2003 with the hottest day ever observed in France, the year 2026 now exceeds the droughts of 1976 and 2022. The soil moisture index reaches its lowest level ever measured for a July 9. And the situation continues to worsen. A new hairdryer effect is expected in the central west starting Sunday. From the sky, France appears literally burned: parched meadows, defoliation of forests, summer crops in great distress (corn, soy, sunflower), and early winter harvests contribute to this color. As if that weren't enough, we have just broken the NATIONAL RECORD for the hottest night ever observed with 30.6°C in Céret in the Pyrénées-Orientales at the "coolest" point of the morning. Photo from the NAOO-21 / VIIRS satellite (true color).

 

[frontranger8]

3 hours ago, bluewave said:

Really extreme to see parts of France go +10° F for the first half of summer using the warmest 1991-2020 climate normals.

With a +4.2°C deviation from the already warmed 1991-2020 baseline, the tally for the first half of the meteorological summer is eye-opening. The 2026 anomaly forces us to scale up the graph, to the point of literally compressing 2003 (+2.8°C "only"). ➡️From the Center-West to Burgundy, we're seeing unprecedented values of +5 to +6°C. ➡️The rainfall deficit is just as stark, ranging from -30% in the north to -100% in the Var. The Center-West, where the vegetation is already completely scorched, hovers between -60 and -80%. ➡️Over the past month, nearly every day has been spent above the heatwave threshold, with only a 4-day pause at the start of July. ➡️The third heatwave should wrap up this weekend. But in the southwest, temperatures will remain heatwave-level (34 to 38°C) for an indeterminate period. Given the hot air mass south of Europe, we're far from safe from a 4th heatwave later in the summer.

 

France is dry and scorched. After already surpassing 2003 with the hottest day ever observed in France, the year 2026 now exceeds the droughts of 1976 and 2022. The soil moisture index reaches its lowest level ever measured for a July 9. And the situation continues to worsen. A new hairdryer effect is expected in the central west starting Sunday. From the sky, France appears literally burned: parched meadows, defoliation of forests, summer crops in great distress (corn, soy, sunflower), and early winter harvests contribute to this color. As if that weren't enough, we have just broken the NATIONAL RECORD for the hottest night ever observed with 30.6°C in Céret in the Pyrénées-Orientales at the "coolest" point of the morning. Photo from the NAOO-21 / VIIRS satellite (true color).

 

Thankfully, it appears some relief is imminent.

[chubbs]

Good 2-part blog from last year on Canadian wildfire history outlining the role of forest management and climate. Canadian forest fires are less numerous than in the past; but, larger and burning a wider area. The cause of fires has transitioned from mostly man-made in the past to mostly ignited by lightning today.

https://thetradeoff.substack.com/p/north-americas-forests-used-to-burn

https://thetradeoff.substack.com/p/part-2-many-of-north-americas-forests

[gallopinggertie]

Current SST anomalies and contour chart. The western Mediterranean Sea is 5C above normal, with temperatures over 30C south of Sicily! Even the Black Sea is pushing into the range of temps warm enough to support tropical cyclones. 

[donsutherland1]

A “must read” piece on climate, data, and data manipulation:

https://www.theclimatebrink.com/p/hot-days-cold-thermometers

[GaWx]

8 hours ago, donsutherland1 said:

A “must read” piece on climate, data, and data manipulation:

https://www.theclimatebrink.com/p/hot-days-cold-thermometers

Thanks, Don! 

 This is the first time I can recall becoming aware of this observation time bias potentially causing overcounting of high max temps due to double counting of these highs as a result of observers getting 24 hour max prior to 1940s during late afternoon, near the time of most very hot highs, as opposed to mainly doing it near sunrise 1940s+.

 Do you have a source with more details on this? How widespread was this practice of getting 24 hour max late in afternoon? Do you by chance know how often this would result in double counting hot highs?

[donsutherland1]

17 minutes ago, GaWx said:

Thanks, Don! 

 This is the first time I can recall becoming aware of this observation time bias potentially causing overcounting of high max temps due to double counting of these highs as a result of observers getting 24 hour max prior to 1940s during late afternoon, near the time of most very hot highs, as opposed to mainly doing it near sunrise 1940s+.

 Do you have a source with more details on this? How widespread was this practice of getting 24 hour max late in afternoon? Do you by chance know how often this would result in double counting hot highs?

This paper has some information on time of observation bias. Hundreds of stations once recorded afternoon resets.

https://www.ncei.noaa.gov/pub/data/ushcn/papers/menne-etal2009.pdf

[chubbs]

7 hours ago, GaWx said:

Thanks, Don! 

 This is the first time I can recall becoming aware of this observation time bias potentially causing overcounting of high max temps due to double counting of these highs as a result of observers getting 24 hour max prior to 1940s during late afternoon, near the time of most very hot highs, as opposed to mainly doing it near sunrise 1940s+.

 Do you have a source with more details on this? How widespread was this practice of getting 24 hour max late in afternoon? Do you by chance know how often this would result in double counting hot highs?

We have a good example in Chester County PA. Here are high temperatures for July 1934 and 1936 for 4 local stations. Phoenixville ran much warmer than the other stations probably due to poor shelter placement. Phoenixville also carried over hot temperatures to the next day when the other stations cooled. This shows that the Phoenixville max/min thermometer was flipped near the time of peak temperature while the other stations were not. Phoenixville completely dominates the # of 95 and 100F days in Chester County in the 1930-40s, but the data is spurious. This is why I don't trust plots of historic max temperatures  in the US, unless the data has been scrutinized for bad data. Only takes one or two  bad apple stations to create a spurious result. 

[donsutherland1]

2 hours ago, chubbs said:

We have a good example in Chester County PA. Here are high temperatures for July 1934 and 1936 for 4 local stations. Phoenixville ran much warmer than the other stations probably due to poor shelter placement. Phoenixville also carried over hot temperatures to the next day when the other stations cooled. This shows that the Phoenixville max/min thermometer was flipped near the time of peak temperature while the other stations were not. Phoenixville completely dominates the # of 95 and 100F days in Chester County in the 1930-40s, but the data is spurious. This is why I don't trust plots of historic max temperatures  in the US, unless the data has been scrutinized for bad data. Only takes one or two  bad apple stations to create a spurious result. 

Yes, Phoenixville had a 4 pm time of observation:

[donsutherland1]

Phoenix is on track to tie its all-time record highest minimum temperature today. Minimum temperatures of 90° or above and 95° or above have increased in frequency in recent years due to a combination of the urban heat island effect and anthropogenic climate change.

[GaWx]

On 7/22/2026 at 12:40 PM, donsutherland1 said:

A “must read” piece on climate, data, and data manipulation:

https://www.theclimatebrink.com/p/hot-days-cold-thermometers

Chris put out this yesterday. I hate his confrontational juvenile behavior, which is totally unnecessary. Ignoring that and acknowledging that 1936 was made much worse due to very dry soils/drought, does he have a valid point about a possible double standard in the treatment of 1936 and 2026 European heatwaves? After all, they were both regional and 1936 covered a much larger area I believe:

This is the 2nd part:

The recent European heatwave was also regional. But for whatever reason, that is supposedly “incontrovertible proof” of catastrophic, rapid global climate change. I really want to know how any person can have this level of mental retardation.

 

 *Also, I’ve been reading some things regarding the magnitude of the Obs Time Bias possibly being exaggerated. I’ll probably post some of this later to get your thoughts.

 

[donsutherland1]

38 minutes ago, GaWx said:

Chris put out this yesterday. I hate his confrontational juvenile behavior, which is totally unnecessary. Ignoring that and acknowledging that 1936 was made much worse due to very dry soils/drought, does he have a valid point about a possible double standard in the treatment of 1936 and 2026 European heatwaves? After all, they were both regional and 1936 covered a much larger area I believe:

This is the 2nd part:

The recent European heatwave was also regional. But for whatever reason, that is supposedly “incontrovertible proof” of catastrophic, rapid global climate change. I really want to know how any person can have this level of mental retardation.

 

 *Also, I’ve been reading some things regarding the magnitude of the Obs Time Bias possibly being exaggerated. I’ll probably post some of this later to get your thoughts.

 

His understanding of climate/weather is poor. He knows day-to-day weather, but cannot put the pieces together in the larger context, much less as it relates to climate. That, IMO, is a big reason that he is not working in the profession he studied. His poor social skills are the other big reason.

A quick comparison is in order for illustrative purposes:

The Dust Bowl:
- Occurred in a cooler climate regime (globally, the 1930s were relatively cool compared to recent decades)
- Was a regional phenomenon from drought coupled with bad land use practices that amplified the severity of the drought, drying the soil even more and amplifying the heating

June 2026 European Heatwave:
- Occurred in a much warmer global climate (June 2026 ranked as the second warmest June on record)
- Occurred within the context of rapid warming in Europe (climate change-forced quasi resonant amplification is contributing)
- Spain is undergoing aridification
- The extreme heat is an outcome one would expect from a rapidly warming climate

Confusing or conflating the two events as he does means confusing weather with climate. The Dust Bowl demonstrates how regional weather and land misuse can produce catastrophe, whereas the 2026 European heatwave demonstrates how ordinary atmospheric variability now operates within a warmer climate system that makes exceptional heat more intense, extensive and likely.

[donsutherland1]

16 hours ago, GaWx said:

Chris put out this yesterday. I hate his confrontational juvenile behavior, which is totally unnecessary. Ignoring that and acknowledging that 1936 was made much worse due to very dry soils/drought, does he have a valid point about a possible double standard in the treatment of 1936 and 2026 European heatwaves? After all, they were both regional and 1936 covered a much larger area I believe:

This is the 2nd part:

The recent European heatwave was also regional. But for whatever reason, that is supposedly “incontrovertible proof” of catastrophic, rapid global climate change. I really want to know how any person can have this level of mental retardation.

 

 *Also, I’ve been reading some things regarding the magnitude of the Obs Time Bias possibly being exaggerated. I’ll probably post some of this later to get your thoughts.

 

I forgot a third reason he likely isn't employed in his field of study, and it's probably the most significant one: Profound dishonesty. Ethics still matters in many professions.

Here's the latest example:

He refers to the following document: https://archive.ipcc.ch/pdf/ipcc-principles/ipcc-principles.pdf 

Notice that this document was prepared in 1998. That is a decade after the IPCC was established. At that time, scientific understanding of contemporary climate change and the predominant role of human activities were far better understood.

If one wants to find the IPCC's original purpose, one has to go back to the founding documents. That was UNGA Res. 43-53. 

Its original mission was not limited to human-induced climate change. It covered climate change in its entirety.

 

 

[bluewave]

 

Low-level clouds over the earth's oceans play a prominent role in keeping our planet cool by reflecting sunlight away from the surface. But their response to climate change has been hard to model. Now, researchers at Caltech and Google have uncovered important new insights about how clouds might respond to warming sea-surface temperatures and rising CO2 levels using a large and powerful dataset of simulations developed by the group.

"One of the largest open questions in climate prediction is how low clouds will respond to global warming," says Zhaoyi Shen, lead research scientist at Caltech's Ronald and Maxine Linde Center for Global Environmental Science and a co-author on a paper outlining the team's findings published July 24 in Science Advances. "Our results show potentially large rapid adjustments of low clouds to high CO2 concentrations, which suggests the earth's climate might be more sensitive to high CO2 levels than some climate models currently project."

The team also found that the thinning of low clouds—uniform layers or large, lumpy expanses below 6,000 feet that cover massive portions of subtropical seas—amplify global warming through a feedback loop: Rising sea surface temperatures lead to fewer clouds, meaning less reflected sunlight and a warmer planet.

"This supports the growing body of evidence from the last few years," says Tapio Schneider, the Theodore Y. Wu Professor of Environmental Science and Engineering at Caltech and co-author of the paper; Schneider is also a principal scientist at Google. "We can now confidently rule out the idea that this effect is zero or that it somehow dampens global warming."

While virtually all global climate models show that the earth is getting warmer, they differ widely on predictions of the exact long-term temperature rise triggered by sustained increases in atmospheric CO2. A large part of the challenge in reaching a scientific consensus has been the inability to resolve the fine-scale atmospheric turbulence that drives low-level cloud formation and dissipation.

By combining a modeling framework for simulations developed by Shen with the power of Google computing resources, the research team used simulated large-scale weather data from a trusted global climate model developed by the National Oceanic and Atmospheric Administration to drive thousands of high-resolution large-eddy simulations.

The simulations used atmospheric and surface-level conditions from 500 randomly selected locations across the tropical Pacific Ocean, taken during four different months to represent seasonal changes. Each location–season combination was then used to drive large-eddy simulations for four climate change scenarios: a 4 degrees Celsius sea-surface temperature increase from baseline; a quadrupling of atmospheric CO2 alone; a 4 degrees Celsius warming with doubled CO2; and a 4 degrees Celsius warming with quadrupled CO2.

"We found that clouds respond directly to CO2 changes, a fact well understood in physics but perhaps a surprise to many," Schneider says. "Simply altering atmospheric CO2 shifts how infrared radiation moves through the air, directly affecting clouds even if temperatures are artificially held steady. Crucially, this effect is nonlinear; it accelerates as CO2 levels rise."

3D renderings show examples of large-eddy simulations (LES) generated by the research team. The center panel represents locations sampled in the Pacific Ocean. In each corner, volumetric renderings of cloud water mass fraction in LES driven by a global climate model output for today's climate at four representative locations (black circles) during July reveal distinct low-cloud patterns (clockwise from lower left: shallow cumulus, stratocumulus, coastal stratocumulus with fog, and stratocumulus over cumulus). The bottom plane renders surface buoyancy.Credit: Sheide Chammas / Google

The team used more than 7,000 simulations in their investigation, which represents a massive increase in sample size compared to earlier work. For example, an earlier study by Shen combined data from 500 simulations, which was itself an increase from the dozens of simulations in previous experiments.

The massive upscaling was made computationally feasible using a large-eddy simulation code that leverages Google's tensor processing unit (TPU) clusters to build a robust collection of cloud states under different conditions. TPUs are specialized computer chips designed to accelerate artificial intelligence (AI) and machine learning workloads.

"This experiment demonstrates the scale of computation made possible by Google's hardware capabilities," says Yi-Fan Chen, a software engineering director at Google and lead of the Google team that carried out the research. "It's computing at an extraordinary scale, demonstrating how processors originally developed for AI and machine learning can accelerate scientific discovery, enabling simulations that were previously out of reach."

In addition to modeling the future, the dataset can help researchers elucidate the planet's past climates, such as during the Eocene Epoch (which began 56 million years ago and ended 33.9 million years ago), when CO2 levels were up to four times higher than today. Plus, the dataset is public, meaning anyone with a laptop can use it to build their own models.

"This new public dataset has the potential to help the broader scientific community evaluate and train turbulence, convection, and cloud models for global climate models," says Shen. Shen is also part of the Climate Modeling Alliance (CliMA), a Caltech-based coalition of scientists, engineers, and applied mathematicians from Caltech and MIT. "At the Climate Modeling Alliance, we are currently developing a new climate model designed to learn from data using AI and machine learning, and I am using this dataset to calibrate our model's new turbulence and convection schemes."

Schneider, who leads CliMA, says the group is already using the data extensively and that he is excited to see what others can glean from it.

"I hope researchers come up with new and creative ways of representing clouds in climate models and that we finally reduce these massive uncertainties in climate predictions," he says. "It's not going to happen overnight to change all sorts of climate models around the world, but over time, I think this can happen."

The Science Advances paper is titled "High-resolution simulations reveal positive global warming feedback from Pacific low clouds." Additional authors from Google are Sheide Chammas, Qing Wang, Rob Carver, Jeffrey B. Parker, Cenk Gazen, Matthias Ihme, Yi-Fan Chen, and John Anderson. The work was supported by the National Science Foundation and Schmidt Sciences.

[donsutherland1]

44 minutes ago, bluewave said:

 

Low-level clouds over the earth's oceans play a prominent role in keeping our planet cool by reflecting sunlight away from the surface. But their response to climate change has been hard to model. Now, researchers at Caltech and Google have uncovered important new insights about how clouds might respond to warming sea-surface temperatures and rising CO2 levels using a large and powerful dataset of simulations developed by the group.

"One of the largest open questions in climate prediction is how low clouds will respond to global warming," says Zhaoyi Shen, lead research scientist at Caltech's Ronald and Maxine Linde Center for Global Environmental Science and a co-author on a paper outlining the team's findings published July 24 in Science Advances. "Our results show potentially large rapid adjustments of low clouds to high CO2 concentrations, which suggests the earth's climate might be more sensitive to high CO2 levels than some climate models currently project."

The team also found that the thinning of low clouds—uniform layers or large, lumpy expanses below 6,000 feet that cover massive portions of subtropical seas—amplify global warming through a feedback loop: Rising sea surface temperatures lead to fewer clouds, meaning less reflected sunlight and a warmer planet.

"This supports the growing body of evidence from the last few years," says Tapio Schneider, the Theodore Y. Wu Professor of Environmental Science and Engineering at Caltech and co-author of the paper; Schneider is also a principal scientist at Google. "We can now confidently rule out the idea that this effect is zero or that it somehow dampens global warming."

While virtually all global climate models show that the earth is getting warmer, they differ widely on predictions of the exact long-term temperature rise triggered by sustained increases in atmospheric CO2. A large part of the challenge in reaching a scientific consensus has been the inability to resolve the fine-scale atmospheric turbulence that drives low-level cloud formation and dissipation.

By combining a modeling framework for simulations developed by Shen with the power of Google computing resources, the research team used simulated large-scale weather data from a trusted global climate model developed by the National Oceanic and Atmospheric Administration to drive thousands of high-resolution large-eddy simulations.

The simulations used atmospheric and surface-level conditions from 500 randomly selected locations across the tropical Pacific Ocean, taken during four different months to represent seasonal changes. Each location–season combination was then used to drive large-eddy simulations for four climate change scenarios: a 4 degrees Celsius sea-surface temperature increase from baseline; a quadrupling of atmospheric CO2 alone; a 4 degrees Celsius warming with doubled CO2; and a 4 degrees Celsius warming with quadrupled CO2.

"We found that clouds respond directly to CO2 changes, a fact well understood in physics but perhaps a surprise to many," Schneider says. "Simply altering atmospheric CO2 shifts how infrared radiation moves through the air, directly affecting clouds even if temperatures are artificially held steady. Crucially, this effect is nonlinear; it accelerates as CO2 levels rise."

3D renderings show examples of large-eddy simulations (LES) generated by the research team. The center panel represents locations sampled in the Pacific Ocean. In each corner, volumetric renderings of cloud water mass fraction in LES driven by a global climate model output for today's climate at four representative locations (black circles) during July reveal distinct low-cloud patterns (clockwise from lower left: shallow cumulus, stratocumulus, coastal stratocumulus with fog, and stratocumulus over cumulus). The bottom plane renders surface buoyancy.Credit: Sheide Chammas / Google

The team used more than 7,000 simulations in their investigation, which represents a massive increase in sample size compared to earlier work. For example, an earlier study by Shen combined data from 500 simulations, which was itself an increase from the dozens of simulations in previous experiments.

The massive upscaling was made computationally feasible using a large-eddy simulation code that leverages Google's tensor processing unit (TPU) clusters to build a robust collection of cloud states under different conditions. TPUs are specialized computer chips designed to accelerate artificial intelligence (AI) and machine learning workloads.

"This experiment demonstrates the scale of computation made possible by Google's hardware capabilities," says Yi-Fan Chen, a software engineering director at Google and lead of the Google team that carried out the research. "It's computing at an extraordinary scale, demonstrating how processors originally developed for AI and machine learning can accelerate scientific discovery, enabling simulations that were previously out of reach."

In addition to modeling the future, the dataset can help researchers elucidate the planet's past climates, such as during the Eocene Epoch (which began 56 million years ago and ended 33.9 million years ago), when CO2 levels were up to four times higher than today. Plus, the dataset is public, meaning anyone with a laptop can use it to build their own models.

"This new public dataset has the potential to help the broader scientific community evaluate and train turbulence, convection, and cloud models for global climate models," says Shen. Shen is also part of the Climate Modeling Alliance (CliMA), a Caltech-based coalition of scientists, engineers, and applied mathematicians from Caltech and MIT. "At the Climate Modeling Alliance, we are currently developing a new climate model designed to learn from data using AI and machine learning, and I am using this dataset to calibrate our model's new turbulence and convection schemes."

Schneider, who leads CliMA, says the group is already using the data extensively and that he is excited to see what others can glean from it.

"I hope researchers come up with new and creative ways of representing clouds in climate models and that we finally reduce these massive uncertainties in climate predictions," he says. "It's not going to happen overnight to change all sorts of climate models around the world, but over time, I think this can happen."

The Science Advances paper is titled "High-resolution simulations reveal positive global warming feedback from Pacific low clouds." Additional authors from Google are Sheide Chammas, Qing Wang, Rob Carver, Jeffrey B. Parker, Cenk Gazen, Matthias Ihme, Yi-Fan Chen, and John Anderson. The work was supported by the National Science Foundation and Schmidt Sciences.

These latest findings aren't really a surprise. Jessica Tierney et al., came across cloud-related changes that amplified Eocene warming during a high CO2 regime. These findings suggest that the so-called "hot models" might be actually be the more realistic ones in simulating a high C02 climate with high sensitivity. 

[donsutherland1]

Monthly and all-time record heat returned to heatwave- and wildfire-swept France today.