Anastassia, thanks again for stretching my understanding. This old brain struggles with a lot of it. But during Covid I started following the work of the Integrated Assessment Modeling Consortium, IAMC: https://www.iamconsortium.org/ . They are the ones who came up with the four Scenarios and they are given credit by the NGFS (Network for Greening the Financial System, a network of Central Banks and Supervisors: https://www.ngfs.net/en ) In turn McKinsey and Company (multinational consulting firm) gave credit to the NGFS' work when they published their largely ignored but still posted 2022 landmark report The net-zero transition, What it would cost, what it could bring: https://www.mckinsey.com/capabilities/sustainability/our-insights/the-net-zero-transition-what-it-would-cost-what-it-could-bring#/ So since the 2016 Green Study Group of the G20 morphed into the NGFS national governments through their banks have tried to solve the problem of political will; sadly better models won't change things. The Scenario we are following is the least fleshed out but it is the path we are on, Too Little Too Late.
Thank you for sharing your concerns. What I am saying is that we now have a unique chance to quantify how ecosystems control climate. For that, we need a better understanding of the underlying physics, not wasting time on dead ends. This knowledge can be useful later when/if our civilization is through the current predicament.
Higher resolution will offer better forecasting but without the inclusion of bioaerosols and how these effect both precipitation points and cloud and rain longevity and intensity you are still left in a state of blindness to possibility. Take the 2017 hurricane season in the USA, there was no mention of the precursors in April of the massive rain and flood induced nutrient outflow through the Mississippi into the gulf where the accumulation of bioaerosols would have greatly enhanced hurricane Harvey which hit Texas then would feed into the next through ocean current nutrient transport into Irma which was centered around Cuba, and even into the third due to increased longer range atmospheric transport of bioaerosols into the Maria system. Since the advent of man made fertilizer we have increased global nutrient concentrations way above naturally occurring values and this feeds through the system in many ways one of which is the disruption of the nutrient based bioaerosol production and its atmospheric feed back loops. We all agree that an increase in temperature is modifying the atmosphere so why do we not confer that the disruption of bioaerosol production which alters precipitation and ice nucleation points will do the same? One just has to look at the difference in convective rainfall systems between grassland and forestry systems to understand the role of bioaerosols have in the biotic pump.
From my perspective, the difference in precipitating convective systems between grassland and forests may not be due solely to bioaerosols. I would say that different evapotranspiration and rougness play a greater role. As I mentioned before, I think that bioaerosols are used by the biota to generate non-precipitating shallow clouds for temperature regulation. Hugely interesting and unexplored questions though
Anastassia, much appreciation for the work on bioregulation. In a sense it was proven already as a major component of temperature decline in Western Europe during the Little Ice Age:
The Arctic jet stream at January 31 is over Texas and South of the Russian Federation, the Antarctic jet stream is fragmented.
The temperature maps on the site indicate fast melting of polar ice. Have you (and team) modeled what would happen when reforesting deserts like Atacama and Sahara?
My argument is also with the midek itself not just courseness as per the podcast For example sulphur aerosols modelled by the IPCC are a thin, global layer- whereas in reality. They were concentrated along circulation-aligned corridors, especially shipping lanes and legacy industrial regions
In the North Atlantic, major shipping lanes sit directly over deep-water formation zones tied to overturning circulation. Sulphur aerosols there enhanced low-cloud cover and suppressed shortwave solar input precisely at those sensitive nodes. This is what the thin smear model of aerosols misses.
When regulations removed those aerosols via IMO2020 , cloud cover dropped and solar absorption increased locally, injecting energy into the coupled ocean–atmosphere system at a circulation hinge, not as a smooth global forcing.
There are other examples, venting reductions in gulf oil and gas wells, together with IMO2020 reduced significantly reduced cloud condensation nuclei over Central America , thereby changing rainfall patterns ro the point tge Panama Canal may no longer be viable
Models that spatially homogenize aerosols and treat them as a purely radiative offset miss these multifaceted interaction entirely. Even higher resolution won’t fix that if aerosol–cloud–circulation coupling is misrepresented.
This seems like another way the same structural issue you describe manifests: energy, condensation, and circulation are being decoupled in places where their geometry matters most. CCN Aerosols used to come from forest biota , then the industrial age introduced CCN via sulphur aerosols. They are at the core of cloud formation, precipitation, radiation models, yet they are modelled insanely in the IPCC models.
Thank you for your comment. I completely agree that changes in energy flows in the equatorial and tropical regions can have an outsized impact on global atmospheric circulation and global climate.
From my point of view, it’s hard to say with any confidence that ship aerosols can explain what we are seeing. Aerosols by themselves do not create clouds; cloud formation depends strongly on the background air circulation. When the air is descending, clouds simply cannot persist, no matter how many aerosols are present, because any condensate will evaporate in subsiding air. This makes the problem inherently complex. This explains why the role of aerosols in cloud formation remains so difficult to quantify and highly uncertain.
During the 2023 thermal anomaly, many of the world’s major forest regions—especially the Amazon—shifted into regimes of descending air that suppressed cloud formation. Forests continued to produce bioaerosols, but under these circulation conditions they were essentially unable to do their usual job. This breakdown of the normal circulation likely contributed to the anomalous warming we discussed in this commentary:
Regarding the statement that “CCN aerosols used to come from forest biota,” I would argue that they still do. Forests act as control systems that respond to disturbances by compensating for them, and control systems do not fail in a simple, linear way. What we saw in 2023–2024 looks more like a major disruption of normal biospheric functioning—one that may well be reversible (at least, I hope so). Unfortunately, biospheric processes are left out of the standard discussion altogether.
Thank you also for sharing your insights at The Great Simplification. Knowledge about the often unseen interdependencies between the major blocks of our civilization is absolutely crucial for having at least some sense of what is going on. I learned a lot.
I was going to say that this was another case of GIGO - Garbage In = Garbage Out, but in fact our Data In might be wonderfully precise, accurate and at a very fine resolution, but if the equations handling that data are inadequate or incomplete, we will continue to get GO, whatever the resolution. I suppose we have to get a modeller on board (Ali from Regenesis says he can model some influence of trees) and derive a model with better, more complete equations, and then run that against the data we have. If we can produce a model with the Biotic Pump fully described by the included equations, and this model produces much better accuracy (between prediction and actual data) even at 10km horizontal and 1km vertical resolution, then we will have shown that the problem is not the resolution, but the weather system we are trying to describe with our equations.
Try the insurance companies - a predictable climate and adequate terrestrial water is worth their everything. I believe the would (and certainly should) finance such research.
Thank you, these last 2 posts have been a fascinating insight into your work, the academic context the work is held in and the ecological models used by this academic context. All very clear, especially to the layperson. It seems from the layperson perspective that you have found a fundamental part of our climate system, and that is not being acknowledged by the academic context, and that its acknowledgement is very much needed. I understand that it is not in the corporate interest to have a functioning model of climate - the ramifications being that we will have to curtail extraction of all ecological biomes.
I am reminded of the complexity of the spheres upon spheres used to describe the motions of celestial bodies prior to the elegance of Keppler's laws of planetary motion and Newton's description of gravity.
"The problem is that the external constraint we know for the climate system is the differential distribution of absorbed solar radiation."
The weakening of the magnetic poles allowing a lot more energy above the UV spectrum isn't and hasn't been included ever. This added energy at the top of the atmosphere goes a long way to explaining what we see as "faster than expected" changes. As the changes in the strength of the magnetosphere continue in a downward trend more energy will be entering the system. This energy is nowhere in the climate models. Shortly after the climate warming goals were instilled in policy back in the early nineties, we had some really sensitive satellites put in orbit to monitor the atmospheric temperatures. The first problem popped up right away, they showed a cooling in the upper atmosphere. So the solution wasn't to check what might be missing from the models! The solution was the terribly expensive and well test instruments on the satellites must be wrong. The data didn't fit the theory. So they changed the way the incoming data was interpreted. In other words change the data to fit the model. Models are the astrologers of the digital world, trust them at you own peril. Remember it was models that gave us the lock downs.
Thank you for the shout-out and for sharing another striking, well-grounded article. It is, of course, a well-known principle that when adjusting one aspect of a system breaks another, it usually indicates something is missing, often a physical relationship. Ideally, any complex numerical model should satisfy analytical thermodynamic constraints, including fluxes of mass and heat, especially when considering the system as a whole. While such checks are rarely, if ever, performed on complex GCMs, the concept is straightforward: if satisfying these constraints requires unphysical numerical tuning or limiters, it points to a gap in understanding.
I would recommend exploring discussion with Axel Kleidon on thermodynamic constraints. Robert Fajber may also be receptive to discussions on hydrological interactions with atmospheric circulation (https://rfajber.github.io/). While Fajber remains focused on classical temperature differences/heating rates, I suspect he may have noticed some issues.
Anastassia, thanks again for stretching my understanding. This old brain struggles with a lot of it. But during Covid I started following the work of the Integrated Assessment Modeling Consortium, IAMC: https://www.iamconsortium.org/ . They are the ones who came up with the four Scenarios and they are given credit by the NGFS (Network for Greening the Financial System, a network of Central Banks and Supervisors: https://www.ngfs.net/en ) In turn McKinsey and Company (multinational consulting firm) gave credit to the NGFS' work when they published their largely ignored but still posted 2022 landmark report The net-zero transition, What it would cost, what it could bring: https://www.mckinsey.com/capabilities/sustainability/our-insights/the-net-zero-transition-what-it-would-cost-what-it-could-bring#/ So since the 2016 Green Study Group of the G20 morphed into the NGFS national governments through their banks have tried to solve the problem of political will; sadly better models won't change things. The Scenario we are following is the least fleshed out but it is the path we are on, Too Little Too Late.
Thank you for sharing your concerns. What I am saying is that we now have a unique chance to quantify how ecosystems control climate. For that, we need a better understanding of the underlying physics, not wasting time on dead ends. This knowledge can be useful later when/if our civilization is through the current predicament.
Higher resolution will offer better forecasting but without the inclusion of bioaerosols and how these effect both precipitation points and cloud and rain longevity and intensity you are still left in a state of blindness to possibility. Take the 2017 hurricane season in the USA, there was no mention of the precursors in April of the massive rain and flood induced nutrient outflow through the Mississippi into the gulf where the accumulation of bioaerosols would have greatly enhanced hurricane Harvey which hit Texas then would feed into the next through ocean current nutrient transport into Irma which was centered around Cuba, and even into the third due to increased longer range atmospheric transport of bioaerosols into the Maria system. Since the advent of man made fertilizer we have increased global nutrient concentrations way above naturally occurring values and this feeds through the system in many ways one of which is the disruption of the nutrient based bioaerosol production and its atmospheric feed back loops. We all agree that an increase in temperature is modifying the atmosphere so why do we not confer that the disruption of bioaerosol production which alters precipitation and ice nucleation points will do the same? One just has to look at the difference in convective rainfall systems between grassland and forestry systems to understand the role of bioaerosols have in the biotic pump.
From my perspective, the difference in precipitating convective systems between grassland and forests may not be due solely to bioaerosols. I would say that different evapotranspiration and rougness play a greater role. As I mentioned before, I think that bioaerosols are used by the biota to generate non-precipitating shallow clouds for temperature regulation. Hugely interesting and unexplored questions though
Anastassia, much appreciation for the work on bioregulation. In a sense it was proven already as a major component of temperature decline in Western Europe during the Little Ice Age:
https://phys.org/news/2011-10-team-european-ice-age-due.html
It's unlikely climate models can be developed fast enough to incorporate the feedbacks mentioned here: https://arctic-news.blogspot.com/p/feedbacks.html
Many of them are positive and visible on satellite maps already:
https://climatereanalyzer.org/wx/todays-weather/?var_id=ws250-mslp&ortho=1&wt=1
The Arctic jet stream at January 31 is over Texas and South of the Russian Federation, the Antarctic jet stream is fragmented.
The temperature maps on the site indicate fast melting of polar ice. Have you (and team) modeled what would happen when reforesting deserts like Atacama and Sahara?
Thank you for your kind words. No we did not perform such modelling.
My argument is also with the midek itself not just courseness as per the podcast For example sulphur aerosols modelled by the IPCC are a thin, global layer- whereas in reality. They were concentrated along circulation-aligned corridors, especially shipping lanes and legacy industrial regions
In the North Atlantic, major shipping lanes sit directly over deep-water formation zones tied to overturning circulation. Sulphur aerosols there enhanced low-cloud cover and suppressed shortwave solar input precisely at those sensitive nodes. This is what the thin smear model of aerosols misses.
When regulations removed those aerosols via IMO2020 , cloud cover dropped and solar absorption increased locally, injecting energy into the coupled ocean–atmosphere system at a circulation hinge, not as a smooth global forcing.
There are other examples, venting reductions in gulf oil and gas wells, together with IMO2020 reduced significantly reduced cloud condensation nuclei over Central America , thereby changing rainfall patterns ro the point tge Panama Canal may no longer be viable
Models that spatially homogenize aerosols and treat them as a purely radiative offset miss these multifaceted interaction entirely. Even higher resolution won’t fix that if aerosol–cloud–circulation coupling is misrepresented.
This seems like another way the same structural issue you describe manifests: energy, condensation, and circulation are being decoupled in places where their geometry matters most. CCN Aerosols used to come from forest biota , then the industrial age introduced CCN via sulphur aerosols. They are at the core of cloud formation, precipitation, radiation models, yet they are modelled insanely in the IPCC models.
Thank you for your comment. I completely agree that changes in energy flows in the equatorial and tropical regions can have an outsized impact on global atmospheric circulation and global climate.
From my point of view, it’s hard to say with any confidence that ship aerosols can explain what we are seeing. Aerosols by themselves do not create clouds; cloud formation depends strongly on the background air circulation. When the air is descending, clouds simply cannot persist, no matter how many aerosols are present, because any condensate will evaporate in subsiding air. This makes the problem inherently complex. This explains why the role of aerosols in cloud formation remains so difficult to quantify and highly uncertain.
During the 2023 thermal anomaly, many of the world’s major forest regions—especially the Amazon—shifted into regimes of descending air that suppressed cloud formation. Forests continued to produce bioaerosols, but under these circulation conditions they were essentially unable to do their usual job. This breakdown of the normal circulation likely contributed to the anomalous warming we discussed in this commentary:
https://bioticregulation.substack.com/p/seeing-forests-through-clouds-a-300
Regarding the statement that “CCN aerosols used to come from forest biota,” I would argue that they still do. Forests act as control systems that respond to disturbances by compensating for them, and control systems do not fail in a simple, linear way. What we saw in 2023–2024 looks more like a major disruption of normal biospheric functioning—one that may well be reversible (at least, I hope so). Unfortunately, biospheric processes are left out of the standard discussion altogether.
Thank you also for sharing your insights at The Great Simplification. Knowledge about the often unseen interdependencies between the major blocks of our civilization is absolutely crucial for having at least some sense of what is going on. I learned a lot.
Hi Anastassia, thank you for another very comprehensive report.
I'm wondering if you know of Dr. Sailesh Rao from Climate Healer's ?
srao@climatehealers.org
He could use your assistance and expertise in this area I think 🙂
I was going to say that this was another case of GIGO - Garbage In = Garbage Out, but in fact our Data In might be wonderfully precise, accurate and at a very fine resolution, but if the equations handling that data are inadequate or incomplete, we will continue to get GO, whatever the resolution. I suppose we have to get a modeller on board (Ali from Regenesis says he can model some influence of trees) and derive a model with better, more complete equations, and then run that against the data we have. If we can produce a model with the Biotic Pump fully described by the included equations, and this model produces much better accuracy (between prediction and actual data) even at 10km horizontal and 1km vertical resolution, then we will have shown that the problem is not the resolution, but the weather system we are trying to describe with our equations.
We would also need a budget.
Try the insurance companies - a predictable climate and adequate terrestrial water is worth their everything. I believe the would (and certainly should) finance such research.
Thank you, these last 2 posts have been a fascinating insight into your work, the academic context the work is held in and the ecological models used by this academic context. All very clear, especially to the layperson. It seems from the layperson perspective that you have found a fundamental part of our climate system, and that is not being acknowledged by the academic context, and that its acknowledgement is very much needed. I understand that it is not in the corporate interest to have a functioning model of climate - the ramifications being that we will have to curtail extraction of all ecological biomes.
Thank You, Anastassia.
I am reminded of the complexity of the spheres upon spheres used to describe the motions of celestial bodies prior to the elegance of Keppler's laws of planetary motion and Newton's description of gravity.
"The problem is that the external constraint we know for the climate system is the differential distribution of absorbed solar radiation."
The weakening of the magnetic poles allowing a lot more energy above the UV spectrum isn't and hasn't been included ever. This added energy at the top of the atmosphere goes a long way to explaining what we see as "faster than expected" changes. As the changes in the strength of the magnetosphere continue in a downward trend more energy will be entering the system. This energy is nowhere in the climate models. Shortly after the climate warming goals were instilled in policy back in the early nineties, we had some really sensitive satellites put in orbit to monitor the atmospheric temperatures. The first problem popped up right away, they showed a cooling in the upper atmosphere. So the solution wasn't to check what might be missing from the models! The solution was the terribly expensive and well test instruments on the satellites must be wrong. The data didn't fit the theory. So they changed the way the incoming data was interpreted. In other words change the data to fit the model. Models are the astrologers of the digital world, trust them at you own peril. Remember it was models that gave us the lock downs.
Thank you for the shout-out and for sharing another striking, well-grounded article. It is, of course, a well-known principle that when adjusting one aspect of a system breaks another, it usually indicates something is missing, often a physical relationship. Ideally, any complex numerical model should satisfy analytical thermodynamic constraints, including fluxes of mass and heat, especially when considering the system as a whole. While such checks are rarely, if ever, performed on complex GCMs, the concept is straightforward: if satisfying these constraints requires unphysical numerical tuning or limiters, it points to a gap in understanding.
I would recommend exploring discussion with Axel Kleidon on thermodynamic constraints. Robert Fajber may also be receptive to discussions on hydrological interactions with atmospheric circulation (https://rfajber.github.io/). While Fajber remains focused on classical temperature differences/heating rates, I suspect he may have noticed some issues.