Global warming, climate change, all these things are just a dream come true for politicians. I deal with evidence and not with frightening computer models because the seeker after truth does not put his faith in any consensus. The road to the truth is long and hard, but this is the road we must follow. People who describe the unprecedented comfort and ease of modern life as a climate disaster, in my opinion have no idea what a real problem is.
CERES satellite data show Earth’s planetary albedo has declined since 2000, increasing absorbed solar radiation. A large part of this decline is attributed to reductions in the coverage or optical thickness of reflective (especially low) clouds — often described as “cloud contraction” or decreases in high-reflectivity cloud regimes. This is one of the main reasons Earth’s energy imbalance has roughly doubled over the CERES record.
AI generated by Grok
Clouds remain one of the largest uncertainties in climate science (feedbacks, representation in models, attribution of trends).
Satellite records show declining reflectivity/albedo in recent decades, and dynamical shifts in cloud regimes are documented.
Clouds both cool and warm the Earth
Cooling effect (shortwave / albedo effect)
Clouds reflect incoming sunlight back to space.
This reduces the amount of solar energy absorbed by the surface and atmosphere.
Low, thick, bright clouds (stratus, stratocumulus) are especially effective at this.
Globally, this cooling effect is strong — without clouds, Earth would be significantly warmer.
Warming effect (longwave / greenhouse effect)
Clouds absorb infrared (heat) radiation emitted by the Earth’s surface and re-emit some of it back downward.
This traps heat in the lower atmosphere, similar to greenhouse gases.
High, thin clouds (cirrus) are particularly effective at this because they are cold and let a lot of sunlight through while still blocking outgoing heat.
Net effect
On average, clouds have a net cooling effect on the current climate (the shortwave cooling is larger than the longwave warming).
However, the balance varies strongly by cloud type, altitude, thickness, and location:
Low clouds → net cooling
High clouds → often net warming
Mid-level clouds → more mixed
When the climate warms, clouds themselves change (amount, height, thickness, type).
These changes create cloud feedbacks:
If low reflective clouds decrease → less cooling → positive feedback (amplifies warming)
If high clouds rise higher → stronger greenhouse effect → positive feedback
Other changes can produce negative feedbacks
This is why cloud feedbacks remain the largest source of uncertainty in climate sensitivity estimates (as assessed by the IPCC).
Clouds cool Earth by reflecting sunlight and warm it by trapping heat.
The net result today is cooling, but how that balance shifts in a warmer world is still one of the key open questions in climate science.
CERES satellite data show
Earth’s planetary albedo has declined since 2000, increasing absorbed solar radiation. A large part of this decline is attributed to reductions in the coverage or optical thickness of reflective (especially low) clouds — often described as “cloud contraction” or decreases in high-reflectivity cloud regimes. This is one of the main reasons Earth’s energy imbalance has roughly doubled over the CERES record.
CERES (Clouds and the Earth’s Radiant Energy System) provides the primary continuous satellite record of Earth’s top-of-atmosphere (TOA) radiation budget, including planetary albedo, since March 2000.
CERES instruments (on Terra, Aqua, Suomi-NPP, and NOAA-20) measure:
Reflected shortwave (solar) radiation
Outgoing longwave (thermal infrared) radiation
Planetary (TOA) albedo is calculated as:
The flagship climate data product is CERES Energy Balanced and Filled (EBAF) (currently Edition 4.2 / 4.2.1). It provides monthly global, zonal, and 1°×1° regional means of all-sky and clear-sky fluxes, with the global net TOA flux constrained to match independent estimates of ocean heat uptake. Data extend through at least early 2026 in recent releases.
Official portal: https://ceres.larc.nasa.gov/ (data ordering, visualization tools, quality summaries, and documentation available there).
CERES is widely regarded as the gold-standard observational record for TOA radiation budget trends.
Uncertainties remain in exact attribution of cloud vs. aerosol vs. surface contributions and in the precise magnitude of longer-term trends due to instrument transitions and calibration, but the overall direction (declining albedo → rising ASR and EEI) is robust across editions and independent datasets.
(Received 12 May 2026; revised 6 July 2026; accepted 14 July 2026; published 22 July 2026.)
Authors: Gianni Bellocchi, Vinay Kumar, Fredrik Charpentier Ljungqvist and Nazzareno Diodato
Abstract (slightly cleaned from the PDF extraction)
Earth has reflected progressively less solar radiation since the start of the satellite era (1979), amplifying the planetary energy imbalance. Satellite analyses attribute the trend primarily to circulation-driven contraction of reflective cloud regimes, whereas process-based studies emphasize surface reflectivity changes. We argue that these perspectives are dynamically linked: as cloud cover contracts, diminishing atmospheric masking elevates the realized climatic leverage of surface albedo. This coupling makes surface reflectivity an increasingly important and manageable regulator of solar absorption under clearer-sky conditions. We propose an integrated governance framework that explicitly incorporates albedo management alongside carbon management.
Structure and key points
Growing energy imbalance CERES data show Earth’s energy imbalance roughly doubled since the early 2000s (≈0.5 → 1.0 W m⁻²). Ocean heat content confirms the acceleration. The authors describe a “clearing-sky” phase (declining aerosols, reduced low-cloud cover, cryosphere reflectivity loss) that lets more shortwave radiation reach the surface, increasing the importance of surface albedo. Regional amplification is noted (e.g., grasslands rising above 1.7 W m⁻²).
Cloud-regime contraction as a leading driver Citing Tselioudis et al., the paper states that contraction of high-reflectivity cloud regimes accounts for ≈0.37 W m⁻² decade⁻¹, or roughly 80 %, of the observed increase in absorbed solar radiation over 2001–2024. This is linked to large-scale dynamical shifts (narrowing of the ITCZ and poleward shift of mid-latitude storm tracks). Cloud contraction is presented as increasing (not replacing) the radiative influence of the surface by reducing atmospheric
Surface albedo as a strategic, manageable lever Land-use and management can change surface albedo by 0.05–0.20. The authors discuss practices such as cover cropping, residue retention, and high-albedo urban materials. They note the paradox that biogeophysical (albedo) and biogeochemical (carbon) effects can have opposite signs (e.g., afforestation can darken the surface while sequestering carbon) and therefore call for joint evaluation.
Historical (Mediterranean) context Multi-centennial cloudiness reconstructions show cloud cover peaking around the coldest phase of the Little Ice Age (~1600 CE) and then declining toward modern minima. The decline began during the later Little Ice Age, preceding strong anthropogenic greenhouse-gas forcing. Suggested contributors include natural variability (post-volcanic recovery, solar activity, AMO) and historical land-use change (European deforestation reducing moisture recycling and convective clouds).
The paper is a perspective, not original observational research.
It synthesizes existing satellite, energy-budget, and paleo/historical evidence and advocates for “albedo governance” as a policy complement to carbon management.
CERES data has been widely discussed in climate research because even small changes in reflectivity can alter Earth’s energy balance measurably over time.
Albedo (or Earth’s global reflectivity) in this post is defined as the amount of solar shortwave (SW) radiation that the Earth reflects into space, as measured at the top of the atmosphere or TOA, divided by the total solar radiation reaching Earth also measured at the TOA.
In the CERES EBAF satellite context (Loeb et al., 2009, 2018, 2021), and using their variable names, this is toa_sw_all_mon divided by solar_mon, where “mon” means monthly and “sw” means shortwave radiation. In this post we compute yearly global latitude-area-weighted means from the monthly values for most of the illustrations to avoid seasonal effects, which are very large. As seen in figure 1, there is a distinct albedo peak that falls roughly between 2004 and 2007 and afterward the albedo falls until 2025, with a second smaller, but still dramatic peak in 2020.
Figure 1. Upper left: the area-weighted global mean outgoing shortwave radiation at the TOA (W/m2). Upper right: the computed albedo as a percent. Lower left: Outgoing longwave emissions from Earth (W/m2). Lower right: surface shortwave absorption (W/m2). To see this and the other figures in higher resolution click on the figure.
Nearly all CERES EBAF variables show an anomaly during the 2004-2007 albedo peak, which falls in the middle of the famous pause in global warming. Notable exceptions are the cloud radiative effect (CRE) variables. The albedo peak anomaly, at least according to CERES EBAF, does not appear to be a cloud feature, but a surface feature.
I need to mention here that CERES EBAF variables have been adjusted, at the TOA, so that the Earth Energy Imbalance (EEI) equals that calculated from changes in ocean heat content. This is explained further in another post. Thus, the measurements in this post are not raw satellite measurements but are from a model.
It is interesting that the emitted longwave radiation at the TOA (lower left, figure 1) is also anomalous during this peak. LW (longwave) downwelling radiation is high in this period, but shows no distinct anomaly, as would be expected if cloud cover caused the albedo anomaly. All the trends given in the figures are ordinary least squares (OLS) linear trends.
Solar incoming SW
Figure 2. Upper left: the total incoming solar SW by month in blue, and the monthly anomaly in red. Upper right: only the monthly anomaly incoming SW. Lower left: the yearly averaged solar incoming SW. Lower right: the trend in solar incoming SW from 2001-2025. Notice that solar incoming SW radiation is decreasing in the Northern Hemisphere and increasing in the Southern Hemisphere, the zero contour falls at about 7°N. The numbers and bars in the plots identify the solar cycles.
The increasing solar SW in the Southern Hemisphere in figure 2 is due to changing orbital precession, as explained in figure 4 in this post. Figure 2 is intended to show how small the solar cycle signal is in comparison to seasonal effects. The cycle is extracted by creating 2001-2025 monthly insolation means and then subtracting them from each respective monthly mean. The lower left graph shows the calendar year average solar SW at the TOA. The solar cycles are barely visible in this graph, but it shows the increasing insolation trend from around 2004 to the solar cycle 25 peak. Clearly over small time periods it is not a good idea to conflate solar cycles with insolation.
Comparing figures 1 and 2, we can see that reflected SW is a function of changing albedo and not incoming radiation changes. However, absorbed SW (lower right figure 1) at the surface does track the changing annual insolation (lower left, figure 2), as expected. I was a bit surprised that outgoing LW increased during the albedo peak. One of my earlier posts explains that the net TOA radiation (positive inward, toa_net_all) which is equal to the inward solar radiation in (figure 2) minus the toa_sw_all minus toa_lw_all (both from figure 1) can be used to compute an estimate of ECS. Computing ECS (equilibrium climate sensitivity to CO2) from observations necessarily assumes all other factors do not change over the measurement period. This is clearly not true over this 25-year measurement period. Thus, albedo changes (regardless of the reason) affect any ECS estimate made.
Clouds
The short-term change in albedo seen in figure 1 could be assumed to be due to changing cloud cover and cloud characteristics. The CERES EBAF variables related to clouds are summarized in figures 3 and 4.
Figure 3. Upper left: global mean cloud area. Upper right: global mean cloud pressure and altitude. Lower left: global mean cloud temperature. Lower right: map of mean cloud area.
Figure 3 shows the global cloud area, cloud top pressure and temperature, and a map of global mean cloud area per grid cell. The remaining variable is the cloud optical depth or tau (τ), which is shown in figure 4.
Figure 4. Cloud Tau (τ) or optical depth. The upper graph is the change in tau by year and the lower map is a map of mean tau for 2025. As τ increases, cloud brightness and the amount of reflected sunlight increases, which increases surface cooling.
As the graph in figure 4 shows, the long-term trend in τ is zero, although there is an unremarkable peak within the albedo peak period. Oddly, while the albedo peak shows distinctly in most CERES EBAF variables, it is high but unremarkable in the cloud-specific variables. It coincides with a longwave toa-out anomaly as shown in figure 1, as well as a matching surface upwelling longwave anomaly that is not shown (see the PowerPoints slides linked at the end of this post for details). It also falls in a surface downwelling SW anomaly.
It is important to mention that the lack of a cloud anomaly in the albedo anomaly period does not necessarily mean one does not exist. The CERES cloud variables rely heavily on MODIS and are not computed solely in the general CERES EBAF inversion. The MODIS data has had problems with cross talk and drift as explained in Moeller and Frey, 2017 (see their figure 1). So, we cannot exclude the possibility that the CRE variables during the albedo anomaly period have data or processing problems that do not affect the other variables.
Surface
The remaining set of CERES EBAF variables are the surface or “sfc” variables. I do not think any of the CERES EBAF surface variables are measured, they are all modeled, especially the upwelling and downwelling SW variables. Two surface SW variables, the SW reflected by the surface under clear skies and all skies, are shown in figure 5. The albedo anomaly shows up prominently in these graphs, unlike in the cloud graphs.
Figure 5 Upper left: the global mean SW up from the surface. Upper right: the TOA SW out. Lower left: the surface SW up under clear skies. Lower right: the clear sky SW up trend from 2001-2025. Most of the map is very near zero (pale blue), but there are noticeable negative trend anomalies in the polar regions.
Within the CERES-EBAF framework, the albedo anomaly appears in surface-related variables rather than cloud variables. Whether this reflects a physical surface change or a data processing artifact remains unclear. The variable sfc_net_sw is the net downward SW flux and it should reflect the albedo anomaly as a dip, which it does as shown in figure 6.
Figure 6. Top: Area-weighted net downward SW to the surface. The albedo peak shows as a negative anomaly as expected. Bottom: The cell-by-cell trend in net downward albedo. The trends are small and no map pattern emerges.
The variable graphed in figure 6 has two components and is equal to: sfc_sw_down_all – sfc_sw_up_all. The means of these two variables are shown in figure 7.
Figure 7. The upper graph is the surface global mean reflected SW and the lower graph is the total incoming SW at the surface. The difference (incoming – outgoing) is shown in figure 6.
Both the surface incoming and reflected SW graphs show anomalies in the albedo peak period, but they are offset with the incoming anomaly occurring earlier. The incoming anomaly coincides with a yearly mean solar minimum and the trend in the incoming SW graph in figure 7 is unsurprisingly similar to the incoming solar radiation shown in figure 2. The upper reflected SW graph is similar in magnitude (~0.3 W/m2) and shape to the albedo peak shown in figure 1. Thus, just as Earth approached the solar cycle 23/24 minimum, the surface albedo increased anomalously. I cannot explain this but find it very interesting.
Without this information, one would think that the albedo peak between 2004 and 2007 was due to a change in cloud cover, but we see no cloud cover anomaly at that time. The most visible anomaly is the surface albedo anomaly, and it shows up in the SW data and in LW data. The next obvious suspect is a change in sea ice, but the NSIDC data shows no anomaly at that time as shown in figure 8.
Figure 8. National Snow and Ice Data Center (NSIDC) global sea ice area in millions of square kilometers. The period from 2004 to 2007 shows a reduction in sea ice, which is the opposite of what we expect.
n fact, the albedo peak from 2004-2007 shows a reduction in global sea ice area, which is the opposite of what we expect. Albedo anomalies can arise from snow cover, vegetation changes, or regionally. Figure 8 shows just one of many possible surface variables that could have caused the anomaly.
CERES-EBAF Computation Anomalies
Most of the CERES-EBAF variables match the descriptions in the documentation, but there are some exceptions. Two are highlighted in figure 9.
Figure 9. According to the documentation, the total cloud effect (sfc_cre_net_tot) should equal sfc_cre_net_lw + sfc_cre_net_sw, but their annual global means do not match. Likewise, sfc_cre_net_sw should equal sfc_net_sw_all (skies) – sfc_net_sw_clr_t (the total grid cell cloud-free incoming SW) but does not.
The difference between the total supplied surface cloud radiative effect (CRE) and the value computed from summing the net lw and sw at the surface is large, 1.47 W/m2. Although the variable sfc_cre_net_sw is part of the definition of sfc_cre_net_tot, the difference between net_sw_all (skies) – net_sw_clr_t (clear sky for the total cell area) and sfc_cre_net_sw is different and smaller than the first difference.
Another odd documentation problem is the definition of toa_cre_sw. It is defined as “all-sky flux minus clear-sky (for total region) flux.” Using CERES EBAF variable names, that is, toa_sw_all – toa_sw_clr_t, yet the value in the EBAF file is the negative of the value defined. Toa_sw_all (outgoing all-sky SW) is always larger than toa_sw_clr_t, thus the definition defines a positive number, not the negative sw_cre_sw we see in the EBAF dataset. Incoming SW (solar_mon in figure 2) at the TOA is the solar flux coming in, the values whose name begins with “toa_sw” are all supposed to be positive outgoing flux. Thus, toa_sw_all will always be larger than toa_sw_clr_t and toa_cre_sw should be positive using the definition, but what we get is a negative number. This is OK, but the documentation should be fixed.
All these problems were reported to the CERES EBAF team on May 18. I received an acknowledgement that they received my email and their opinion on the smaller sfc_cre_net_sw discrepancy. I asked about the larger problems by email, but was told the critical person needed to answer my questions was on vacation. If I get a reply on these issues, I will update this post and put up a separate post letting all of you know what the CERES team says. I don’t think I need to wait, as I have investigated all this in every way I can imagine at this point.
They think the smaller sfc_cre_net_sw problem might be due to computational differences in how the area-weighted global means are calculated. Perhaps, but as you can see in the supplementary information to this post (link below), all other computational cross checks of the 41 CERES EBAF variables match to two or more decimal places. One can reasonably ask, why do these two exceptions exist?
As a further check, I ran a program against the data to look for missing grid cell values, thinking that if some of the variables had missing values in some cells and others did not, that could cause the discrepancy. I only found one variable that had any missing cell values: sfc_cre_net_tot_mon, which is the surface CRE net total (downward) radiation flux variable. It had 10 missing values in the 25 years examined and it was the only variable with any missing values. Each year of each grid has 64,800 grid cells, so one in 64,800 is nothing. The ten over 25 years are not enough to explain the 1.5 W/m2 difference between the variable and its computational equivalent, but it might signal another problem. The cloud radiative effect variables come from a model and not direct measurements. In any case, I notified the CERES team of the problem, we’ll see what they find out. This sort of problem is how science advances.
Discussion
The albedo peak from 2004-2007 is very apparent in the CERES EBAF surface radiation data. In the period studied, 2001-2025, it contains the maximum albedo and the maximum surface reflected SW. This is also the period with the minimum SW absorbed by the surface, both under clear skies and all sky conditions. This would normally suggest more snow and ice than normal, but we do not observe a sea-ice anomaly in that period.
Oddly, it is also the time when all sky longwave radiation up from the surface was maximal, both under clear and all skies. Downward SW is low during this period but corresponds to low input from the Sun and it is a time when solar output is declining. Longwave flux down to the surface is high, but not unusually so.
The calculation discrepancies observed appear to be in the CRE variables alone and probably do not affect the other variables, at least as far as I can tell. The cloud effect (CRE) variables do not show an anomaly during this period, but do show one afterward, around 2008-2012 or so. I do not understand these discrepancies; they could be real or computational problems but wanted to document them. This essay is just a brief look at the more interesting things I noticed going through all the CERES EBAF data.
If you are interested in more of the details I uncovered in my study, you can download my PowerPoint slide notes on the 41 CERES EBAF variables here.
Works Cited
Loeb, N. G., Doelling, D., Wang, H., Su, W., Nguyen, C., Corbett, J., & Liang, L. (2018). Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product. Journal of Climate, 31(2). Retrieved from https://journals.ametsoc.org/view/journals/clim/31/2/jcli-d-17-0208.1.xml
Loeb, N. G., Johnson, G. C., Thorsen, T. J., Lyman, J. M., Rose, F. G., & Kato, S. (2021). Satellite and Ocean Data Reveal Marked Increase in Earth’s Heating Rate. Geophysical Research Letters, 48(13). https://doi.org/10.1029/2021GL093047
Loeb, N. G., Wielicki, B. A., Doelling, D. R., Smith, G. L., Keyes, D. F., Kato, S., . . . T. Wong, 2. (2009). Toward Optimal Closure of the Earth’s Top-of-Atmosphere Radiation Budget. J. Climate, 22, 748-766. https://doi.org/10.1175/2008JCLI2637.1
Just days before President Trump announced that the EPA would no longer be guided on climate change by the so-called “endangerment finding,” the Washington Post’s newsroom decided to take another bite at the old “Earth is getting hotter” apple.
Dry land with cracked soil and a lonely tree. Global warming concept. Soil erosion. Ecology. Deforestation
Just days before President Trump announced that the EPA would no longer be guided on climate change by the so-called “endangerment finding,” the Washington Post’s newsroom decided to take another bite at the old “Earth is getting hotter” apple.
Contrary to their intent, the resulting story, headlined, “Scientists thought they understood global warming. Then the past three years happened,” made the Trump administration’s decision seem entirely logical.
The story, published Feb. 11, is a lesson in the perils of an entity supposedly focused on journalism conducting its own analysis in the field of climate science, and then producing a story that could not be more confusing if it was intentionally trying to supplant Abbott and Costello’s “Who’s On First?” as the most hilarious comedic routine ever founded on the concept of confusion.
“According to a Washington Post analysis,” the Post’s lead paragraph declared, “the fastest warming rate on record occurred in the last 30 years.” The Post noted that it based its analysis on “a dataset from NASA to analyze global average surface temperatures from 1880 to 2025.”
The story was presumably in the works before the U.S. was hit with one of the most frigid stretches in recent years. Never mind. The Post had that covered.
“Even as the United States languishes under a frigid cold snap, the rest of the world is still experiencing unusually warm temperatures,” the Post assured us. Why just consider Nuuk, Greenland (or “Nuuk, Nuuk” as the Three Stooges might have called it) which “saw temperatures in January more than 20 degrees Fahrenheit above average. Parts of Australia, meanwhile, have seen temperatures push past 120 degrees Fahrenheit amid a record heat wave.”
Some places get cold. Some places get hot. Welcome to Earth, visitors. The Post was worried because “for about 40 years — from 1970 to 2010 — global warming proceeded at a fairly steady rate,” inching up about 0.19 degrees Celsius per decade. “Then, that rate began to shift,” the Post reported. “The warming rate ticked up a notch. Temperatures over the past decade have increased by close to 0.27 degrees C per decade — about a 42 percent increase.”
If this seems utterly confusing, you’re not alone. The Post led off by saying that the fastest warming rate on record “occurred in the last 30 years,” which would be since about 1996. But then it said that from 1970-2010, global warming was “pretty steady.” Huh?
It’s never quite clear why “the last 3 years” is featured in the headline and mentioned a couple of times within the story. Don’t try too hard to make sense of it. These people are journalists, er, I mean scientists, er, science reporters – well, dammit, they’re sure not mathematicians. Give them a break.
Follow the story’s winding road: Sulfate aerosols in the atmosphere actually helped cool things off. But they’re bad to breathe, so when countries cracked down on such things, it just heated things up again. Plus, there are fewer low-lying clouds, letting more heat from the sun get through. On the other hand, “Clouds have long been one of the greatest uncertainties in climate science. Clouds are probably helping to cool the Earth, like aerosols, but how much is an open question.” Like everything else.
Please read the following section closely – more than once if you have to – and then let’s review.
About two decades ago, according to the Post, “Countries also began shifting from coal and oil to wind and solar power. As a result, global sulfur dioxide emissions have fallen about 40 percent since the mid-2000s; China’s emissions have fallen even more. That effect has been compounded in recent years by a new international regulation that slashed sulfur emissions from ships by about 85 percent. That explains part of why warming has kicked up a bit.”
Wait, coal, oil and sulfur emissions helped keep the Earth cooler? And cutting down on those emissions have made the Earth warmer? Here’s the Post’s explanation: “For decades, a portion of the warming unleashed by greenhouse gas emissions was ‘masked’ by sulfate aerosols. These tiny particles cause heart and lung disease when people inhale polluted air, but they also deflect the sun’s rays.” So, pick your poison.
The Post did quote one expert who’s not yet buying the too-hot-to-handle narrative. Chris Smith, a research fellow at the University of Leeds, told the Post, “It’s still too early to definitively conclude there’s an increase in the rate of warming,” and he wants to see a few more years of additional data.
The Post, on the other hand, may not have that kind of time. In early February, the Post announced another round of layoffs, and while initial estimates guessed a loss of about one-third of its newsroom, “an accounting by the Washington-Baltimore Newspaper Guild, the union that represents Post journalists, finds that the paper’s management eliminated closer to half of the journalists it used to employ,” according to The Washingtonian.
It never occurs to the far-left (formerly mainstream) media that its demise might be attributable to more than economic factors or the rise of the internet. Just as important is the clear bias and agenda- driven politics that resulted in a loss of trust by millions of Americans who are not part of the far-left bubble that the media increasingly served.
The era of climate change hysteria is thankfully nearing its end. Some of its biggest promoters are sharing its fate.
Another new study affirms clouds and aerosols play a key role in explaining trends in solar surface radiation (SSR), which is “essential for the global energy cycle driving the climate system.”
Warming across Germany in the last 3 decades can be explained by declining cloud and aerosol albedo and consequent rising solar radiation. Not CO2.
Another new study affirms clouds and aerosols play a key role in explaining trends in solar surface radiation (SSR), which is “essential for the global energy cycle driving the climate system.”
Over Germany, five independent observational datasets all agree that SSR increased by 4 W/m² per decade (~10 W/m²) from 1995-2020.
A 4 W/m² per decade increase in SSR easily explains recent warming. It especially explains warming far better than the alleged 20-times smaller clear-sky-only CO2 impact (0.2 W/m² per decade) over this span.
Supporting this new research, a 2024 study (Wacker et al.) utilizing a German “testbed site” reports total and direct shortwave (SW) radiation forcing rose by 3.5 and 9.3 W/m² per decade, respectively, from 1996-2021.
From the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science, and the “Hey whatever happened to that CO2 master control knob?” department, comes this encouraging news where real data-driven science was performed instead of the typical modeling madness.
Earth’s growing heat imbalance driven more by clouds than air pollution, study finds
Satellite and reanalysis data show aerosol changes in the Northern and Southern Hemispheres largely cancel out, shifting attention to cloud changes due to surface warming and natural climate variability.
MIAMI — Earth is taking in more energy than it releases back to space—a growing “energy imbalance” that is fueling global warming. A new study led by scientists at the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science finds that recent changes in air pollution are not the main reason this imbalance has increased.
Aerosols—tiny airborne particles from sources such as pollution, wildfires, and volcanoes—can affect how clouds form and how much sunlight Earth reflects back to space. While aerosols can influence climate regionally, the new research shows their recent global impact has been small.
Published November 28 in the journal Science Advances, the study analyzed nearly two decades of satellite observations combined with modern atmospheric reanalysis data. The researchers found that aerosol changes have affected the climate in opposite ways in the two hemispheres.
In the Northern Hemisphere, cleaner air in heavily industrialized regions has reduced the number of particles that help clouds reflect sunlight, allowing more solar energy to reach Earth’s surface. In contrast, the Southern Hemisphere has seen large increases in natural aerosols from events such as the 2019–2020 Australian wildfires and the 2022 Hunga Tonga–Hunga Ha’apai volcanic eruption. These particles made clouds brighter and more reflective, sending more sunlight back to space. Together, the opposing effects largely cancel each other out, resulting in little net global influence from aerosols on Earth’s rising heat imbalance.
The study also shows that the recent increase in Earth’s energy imbalance is driven mainly by changes in reflected sunlight, rather than by changes in heat escaping to space. From 2003 to 2023, Earth gained heat at a rate of about half a watt more energy per square meter each decade, largely because the planet is absorbing more sunlight.
Fig. 1. Decadal trends (2003–2023) and monthly anomalies in the natural logarithm of aerosol proxies. (A) Spatial maps of trends in the natural logarithm of the aerosol index (AI) from MODIS satellite and (B) sulfate aerosol mass concentration at 925 hPa (SO4) from MERRA-2 reanalysis for the period 2003–2023. (C–E) Vertical profiles of ln (SO4) monthly anomalies over the boxed regions in (B): (C) East Asia, (D) North America, and (E) the Southeastern Pacific. The dashed line in each panel represents the 925 hPa pressure level. Credit: Park, Soden. University of Miami Rosenstiel School
To track how aerosols are changing over time, the researchers used two independent indicators. One came from satellites that observe how aerosols in the air affect the passage of sunlight through the atmosphere. The other came from reanalysis data, which combine observations and models to estimate sulfate particles produced by pollution, volcanoes, and wildfires. Despite their different approaches, both methods revealed the same pattern—declining aerosols in the Northern Hemisphere and increasing aerosols in the Southern Hemisphere—indicating that aerosols have had little overall effect on the global energy trend.
“Understanding this hemispheric “balancing act” helps society focus on the true forces behind global warming—changes in cloud behavior linked to surface warming and natural climate variability—rather than mistakenly attributing recent warming to cleaner air,” said Chanyoung Park, lead author of the study and a doctoral student in the Department of Atmospheric Sciences at the Rosenstiel School. “Even though the Northern Hemisphere may experience some regional warming due to reduced aerosols, this does not translate to a significant global impact. This clarity supports better climate planning, more accurate public communication, and informed policy decisions.”
The findings also highlight a potential limitation in some climate modeling studies, which focus mainly on pollution reductions in the Northern Hemisphere and may underestimate the growing influence of natural aerosol events in the Southern Hemisphere.
“Earth’s energy imbalance tells us how fast heat is building up in the climate system,” said Brian Soden, a co-author of the study and a professor in the Department of Atmospheric Sciences at the Rosenstiel School. “Many earlier studies suggested that cleaner air might explain much of the recent increase, but our results show that aerosol changes largely cancel out between the Northern and Southern Hemispheres. That means we need to look more closely at changes in clouds and natural climate variability to understand why the planet is continuing to gain heat.”
When the Australian government set up a “Senate select committee to investigate misinformation and disinformation in climate science and energy”, I didn’t find out until a few hours before the deadline for submissions from the general public. Things were made a little more complicated by the fact that I was travelling overseas at the time, with only a mobile phone to prepare a submission on.
When the Australian government set up a “Senate select committee to investigate misinformation and disinformation in climate science and energy”, I didn’t find out until a few hours before the deadline for submissions from the general public. Things were made a little more complicated by the fact that I was travelling overseas at the time, with only a mobile phone to prepare a submission on.
It was a reasonable assumption that the government was not going to let any submission from the public sway them away from their position that anything that even questioned climate “science” was just misinformation or disinformation. So in a sense, sending in a submission was a waste of effort. On the other hand, if they didn’t receive submissions that challenged their position, then they would obviously claim that they were justified when they subsequently brought in legislation banning climate “misinformation” – which surely is their objective (or something like that). I therefore felt that it was important that I send in a submission, and hopefully many others have too.
The submission had to refer to a specific clause or clauses in the terms of reference, but apart from that there were few restrictions.
I have now been advised that my submission has been received, but goodness knows whether anyone in government will actually read it. Anyway, this is it:
– – –
I refer to The Senate Select Committee on Information Integrity on Climate Change and Energy, and specifically to the terms of reference item (a) the prevalence of [] misinformation and disinformation related to climate change [];
My name is Michael Jonas, I live at Exeter, NSW, my qualification is an MA in Mathematics at Oxford University UK, and I have spent much time over the last few decades investigating climate science from a mathematical perspective. Please note that this is very relevant because (i) climate models are a mathematical construct, and (ii) science is founded on mathematics (it is a well-known maxim in science that if the maths is wrong then the science is wrong).
I have particular expertise and interest in computer modelling, having been involved in the design and development of computer models before the IPCC was created.
My main points:
– Scepticism based on maths or science is routinely dismissed as misinformation. – This avoids scrutiny where scrutiny is needed. – Everything should be treated on its merits in open and free discussion.
Misinformation
Scepticism about climate change is routinely classlfied as misinformation by those who promote the mainstream position on climate change. This very conveniently gets them out of having to justify their position in an open and free discussion. The foundations of their position are shaky (see below) and would be exposed in an open discussion. As the US Supreme Court judge, Louis Brandeis, said about exactly this kind of situation in 1913, “sunlight is said to be the best of disinfectants”.
The simple fact is that a lot of the misinformation about climate change comes from its proponents.
Climate models
As I said above, these are a mathematical construct, so are within my area of expertise. I have examined aspects of the climate models and have documented in a published paper how they are mathematically invalid – their structure is the structure used in the short term calculations of weather models, but mathematically this structure cannot work for the climate. A totally different structure is needed for the longer term nature of climate. The paper is titled “General circulation models cannot predict climate” and is accessible at
This study draws on Chaos Theory to investigate the ability of a General Circulation Model to predict climate. The conclusion is that a General Circulation Model’s grid-level physical processes and parameterisations cannot predict climate beyond maybe a few weeks. [] The longer the timescale is, the less relevant the grid-level physical processes and parameterisations in a General Circulation Model become. [] A General Circulation Model calculates weather at each time step and this is then amalgamated into a final prediction of climate. This process is back to front. A realistic long term climate model would calculate climate and then weather would be deduced from the climate.
Clouds
Another area that I investigated was the overall behaviour of clouds. The question that I asked myself was: in which part of climate physics are the climate models most likely to be most wrong? The answer was in the behaviour of clouds. Mathematical analysis of the data showed that cloud behaviour was not dependent on CO2, whereas the IPCC reports and the climate models that they are based on all showed cloud behaviour being dependent on CO2. This makes an enormous difference to the models’ outcomes, because about half of all the models’ predicted warming comes from clouds and is attributed to CO2. If instead, as I found, cloud behaviour is independent of CO2, then the predicted warming from CO2 is halved and becomes quite benign. Nothing to worry about at all
My paper is titled “Clouds independently appear to have as much or greater effect than man-made CO2 on radiative forcing”. It is accessible at
The patterns of behaviour of clouds, both for cloud area and cloud optical thickness, are studied over the period of available data, 1983 to 2017. There was a decrease in cloud cover over the study period, while global surface temperatures increased. The patterns of clouds and temperature indicate that the cloud cover decrease could not have been caused by the increased surface temperature. [] The climate models, which have zero or negative cloud impact on radiative forcing independently from CO2, need to take this into account in order to avoid over-estimating the influence of CO2.
Summary
I find it quite distressing that ideas stemming from genuine mathematical and scientific analyses that cast doubt on the mainstream climate message are routinely dismissed as misinformation, when much of the mainstream climate message could itself quite reasonably be classified as misinformation.
What we need to do to rectify the situation is to stop using the term “misinformation” and instead to have an open and free discussion about all aspects of the climate.
If we can do this, I am confident that we will find that climate change is far less of a threat than it is thought to be, and is actually quite benign.
From the Friends of Science Society Newsletter, where they give our own Willis Eschenbach props and suggestions for his important recent work – Anthony
From the Friends of Science Society Newsletter, where they give our own Willis Eschenbach props and suggestions for his important recent work – Anthony
The Clouds and the Earth’s Radiant Energy System (CERES) project provides satellite-based observations of Earth’s radiation budget and clouds. CERES instruments on several satellites measure longwave and shortwave radiation from the Earth. The longwave radiation is the radiation emitted upward to space from the Earth’s surface and clouds. The upward shortwave radiation is the reflected solar radiation which doesn’t enter the climate system. If the outgoing longwave radiation is less than the absorbed solar radiation, there is a positive top-of-atmosphere radiative imbalance (imbalance) which increases the global average temperature.
Equilibrium climate sensitivity (ECS) is a measure of how much the Earth’s global average surface temperature will eventually increase in response to a doubling of atmospheric carbon dioxide concentration. Image by Anthony Watts
Willis Eschenbach used the CERES database, which gives the monthly radiative fluxes in each 1° latitude by 1° longitude starting March 2000, to calculate the equilibrium climate sensitivity (ECS) to greenhouse gases. He produced a graph of imbalance versus the surface temperature by 1° latitude by 1° longitude with time averaged over 24 years. Eschenbach applied a lowess fit to the data. He calculated the slope of that fit and calculated the area weighted imbalance per degree of temperature change. Eschenbach asks “How much does the earth have to warm up to restore the 3.7 watts per square meter (W/m2) of TOA radiation imbalance that is said to result from a doubling of CO2 (2xCO2)?” Willis says the amount of warming required to rebalance the imbalance is called the ECS, but I believe that isn’t correct. The imbalance is not at an equilibrium state but is the result of a continual increase of greenhouse gases.
The transient climate response (TCR) is the change in temperature after a doubling of CO2 at a constant increase of a 1%/year, which would result in a doubling in 70 years. The actual average CO2 increase from 2000 to 2024 was 0.567%/year. Willis calculates the imbalance at 6.6 W/m2 per °C of surface temperature change. This equates to a TCR 3.7/6.6 = 0.56 °C, which is the TCR at 0.567%/year CO2 increase. I call this the “slowTCR”, to distinguish it from the normal TCR with a 1%/yr CO2 increase. Using a simple 1-D climate model tuned to 3-D models, with CO2 increasing at the actual rate, I calculated that the slowTCR of 0.56 °C corresponds to an ECS of 0.68 °C, which seem much too low compared to other observation-based estimates.
I did a similar calculation using the same CERES data. Each data point is 1° latitude by 4° longitude. I applied a 4th-order polynomial fit to the average 25-year data (16200 data points) as shown in this graph. I made another graph of the slope of the fitted curve and calculated a global average imbalance of 3.95 W/m2 per °C of surface temperature change, which corresponding to a slowTRC of 0.94 °C and an ECS of 1.14 °C. The lowess fit heavily discounts data further away from the mean to discount outliers. The polynomial fit might be better as all the data is of equally high quality. Changing the best fit method has a large effect on the results.
Several papers, see here and , here, argue that cloud cover can change due to atmospheric circulation changes caused by a temperature change. The analysis by Eschenbach and myself using time averaged CERES data doesn’t account for this possible effect and assumes that any potential temperature-caused air circulation changes will not significantly change the relationship between imbalance and temperature over the next few decades of climate change. Therefore, I did the same calculation using the four coldest years of the CERES data (2000, 2001,2008, 2011) and the four warmest years (2018, 2019,2023, 2024). The global average temperature difference between these year groups is 0.68 °C. If the air circulation changes were causing more warming, the result of the warm years would show a lower imbalance change per temperature change than the cold years. In fact, the warm years analysis has a slightly smaller change of 0.13 W/m2/°C, so it appears that this effect is leading to more warming. Therefore, the method we used to estimate ECS is likely inaccurate. It is not a simple task to estimate the ECS.
This article begins with observations of top of atmosphere radiation balance over a moored buoy located in the middle of the Bay of Bengal in conjunction with surface data from the moored buoy for the same time. It progresses into more recent observations of daily OLR emission from above all ice free ocean surface to establish that the average effective emission temperature for every location across the global oceans is below the freezing temperature for water.
This article begins with observations of top of atmosphere radiation balance over a moored buoy located in the middle of the Bay of Bengal in conjunction with surface data from the moored buoy for the same time. It progresses into more recent observations of daily OLR emission from above all ice free ocean surface to establish that the average effective emission temperature for every location across the global oceans is below the freezing temperature for water.
A model for broad spectrum transmission of OLR to space through the atmosphere over a warm pool is explained and sequenced through a series of time intervals to appreciate how ice forms as a consequence of long wave radiation heat loss at altitude.
The article concludes by making the case for convective overshooting playing a key role in the observed SST regulating process.
Introduction
The Bay of Bengal is one of the best locations across the oceans to observe the development of convective instability. The solar intensity at 15N exceeds 425W/m² from the time the solar zenith moves north of the Equator in March to the time the zenith moves south of the Equator in September. That means there is sufficient solar intensity to reach and maintain the ocean surface temperature (SST) at its sustainable limit of 30C for almost 6 months. Chart 1 provides monthly data from CERES top of atmosphere (ToA) observations available from NASA NEO showing the radiation balance at 15N and 90E for 2017.
Chart 2 provides surface based data collected from the moored buoy at 15N, 90E at daily time resolution from the same location as Chart 1 for the same period.
The SST is observed to rise from day 16 to day 100 when a cyclone passed over the moored buoy then again increases to overshoot the sustainable temperature of 30C till cyclic instability sets in with associated rainfall from day 150. By day 300, the solar zenith moves south of the Equator and the solar intensity at 15N is insufficient to maintain the cyclic instability and the temperature declines.
Combining observation displayed in Charts 1 and 2 enables the conclusion that the regulating process has moisture convergence from surrounding ocean to the vicinity of the moored buoy because the Net radiation averages 100W/m² while the SST tracks between 28.5 and 30C. So despite the net heat flux to the atmosphere, there is no corresponding increase in surface temperature. The additional heat input is the result of local precipitation exceeding evaporation.
Chart 3 combines daily surface and ToA data for July 2017 to improve the time resolution over Chart 1.
An important observation of Chart 3 occurs on 21st July. Here there is intense rain indicative of convective instability centred in the vicinity of the moored buoy but it coincides with low reflected short wave (SWR) and high outgoing long wave radiation (OLR). This indicates that the cumulonimbus anvil associated with monsoonal rain does not contribute significantly to daily short-wave reflection. It also indicates that the OLR is emitting from higher temperature during and immediately after the instability than during the development of convective potential.
Here it is worth plotting the correlations between SWR and OLR and surface sunlight to OLR per Chart 4.
The result that the SWR is negatively correlated to OLR with a coefficient greater than unity demonstrates the cloud effect over warm pools produces radiation cooling rather than heating.
The Role of Ice in the Atmosphere
Chart 5 expands the observation of OLR to all ice-free ocean surface and comes forward in time to 20 March 2025 when the solar zenith is over the Equator.
The effective radiating temperature for OLR emissions over oceans for 31,800 grid cells is shown in Chart 6.
The effective emission temperature over oceans ranges from 216K to 272.6K. Given that molecules capable of emitting OLR will be losing heat, the H₂O molecules in the atmosphere with temperature below 273K will be solidifying to ice. Accordingly the vast majority of OLR emissions above ocean surface will be from ice. The ice will be at high altitude over warm pools at 303K.
OLR Emissions above Ocean Warm Pools at 303K
Ocean warm pools exhibit cyclic convective instability over a period of a few days. Chart 3 above exhibits 5 to 6 cycles in a month or averages a cycle every 5 to 6 days. In the location where the instability is initiated, the convective plume transports heat from low altitude to high altitude resulting in intense rainfall as the expanding air cools at altitude. After instability there is an initial period of clear sky with close to saturated conditions. In reality, the column will rarely be fully balanced but ranges from water deficit to super-saturated. Chart 7 shows the atmospheric profile for water vapour and temperature under perfectly saturated conditions over 303K surface.
For the purpose of this analysis, the modelled column has 200 layers of 100m thickness. This results in the bottom layer having a total of 3mm of water. There is very little water above 15,000m and negligible emissive power above 18,000m so the temperature is almost constant; just below 200K. Water dominates the OLR emissive power of the column so when there is little to no water, the emissive power is negligible.
Chart 8 examines the broad spectrum OLR absorption up the column based on a water vapour OLR absorption constant of 10% per mm. The OLR fraction transmitted to space is based on working down the column applying Beer’s Law.
It becomes apparent that nearly all OLR emitted below 3000m is reabsorbed while OLR to space progressively increases above 5,000m to reach its maximum above 15,000m
Having established the OLR absorption and transmission profile for the saturated column, it is now possible to determine the OLR transmitting power of the column and the rate of heat loss at altitude per Chart 9.
These calculations apply Kirchhoff’s Law of Radiation with the simplifying assumption of bulk absorption for the OLR spectrum such that there is just one value for absorption or emissivity at each layer. This then enables using the Stefan Boltzmann equation for OLR transmission up the column and to space, which is assumed to be at 0K. The resulting radiating power is 275W/m², which corresponds to an effective radiating temperature of 263K. However, it is clear that there is heat being lost from the column below freezing and noteworthy that there is OLR radiation heating below 2,400m.
The loss of heat at altitude results in ice and condensate production over time as shown in Chart 10.
A time step of 2500 seconds has been chosen to simplify the mass flow of ice cascading down the column with time. The terminal velocity of sub 100 micron ice particles is taken as 4cm/s so they will fall 100m (one layer) in 2500 seconds. Chart 11 shows the transmitting power and rate of heat loss at 2500 seconds after saturated state taking the absorption coefficient for water condensate as 50% per mm and ice at 90% per mm.
The transmitting power has reduced slightly to 271W/m² but there is not much change in the altitude or amount of heat loss. After seven iterations, the development of the ice and its influence becomes clearer as shown in Chart 12.
After 17,500 seconds, the transmitting power is down to 253W/m² and it is now apparent that the heat loss is occurring at higher altitude while less heat is being lost below the 273K altitude. Also, the altitude of radiation heat gain has increased to 2,900m.
This simple model is only valid for overnight analysis or 19 iterations: shown in Chart 13. It is not valid for sunlit atmosphere where short wave absorption plays a significant role in the development and dissipation of the ice along with other complicating factors.
So after 13 hours of overnight heat loss following late afternoon convective storm over 303k ocean, the OLR transmission is down to 226W/m² and heat loss is centred around 11,000m with very little heat loss from water condensate or water vapour. There is now long wave heat gain up to 3,800. The ice accumulation at various time iterations is shown in Chart 14.
After 13 hours without sunlight, there is a total of 2.8kg of ice per square metre and it dominates both the OLR transmission and solar EMR thermalisation. A sunlit model results in greater complexity and a story too long for this article.
Discussion
This overnight example gives insight into the initial ice development. Through the daylight, solar EMR is absorbed by the ice and some sublimates during the peak daylight but there is insufficient heat input to induce upward mass flow. Over a few nights and days of cycling heat loss and heat gain, the ice becomes layered but with continual descent of ice or associated water vapour. The column becomes increasingly unstable as the ice and water condensate descends and the region above the level of free convection (LFC) deflates to increases in density while the region below the LFC gains energy with reducing density.
The water condensate that falls below the LFC is vaporised by the heat gain from absorbed solar EMR and OLR from lower altitudes. The column also gains water vapour from the surface insolation. It takes upward of five days to reach the maximum convective potential. A column above 303K SST with maximum convective potential is devoid of cloud so there is usually clear skies ahead of instability occurring. The SWR is high immediately after instability then gradually reduces as the high altitude ice develops. SWR is usually low before instability occurs.
The full sunlit ice development model, reasonably tuned to observations, achieves a balance in heat gain below the LFC equal to the loss of heat above the LFC. This only occurs when the SST is at 303K. When the SST is lower, there is not enough energy below the LFC to fully saturate the region above the LFC during instability. If the SST was able to exceed 303K and the region below the column was in equilibrium with the surface, then instability will cause convective overshooting with very high-altitude ice that remains persistent due to its small size having very low terminal velocity. Going back to Chart 2 it is apparent that convective overshooting occurred at the onset of the instability when the temperature dropped from above 31C to below 30C in two days. The OLR for the 1st June averaged 147W/m² (225K), which is only possible starting from convective overshoot.
In looking at convective overshooting, it is regularly observed above tropical cyclones where daily OLR can be less than 100W/m² (204K). One of the more unusual places that experiences convective overshooting is Missouri. Here it is associated with similar atmospheric instability but the instability is caused by the mixing of high altitude dry air stream and moist mid altitude air stream to produce tornados.
Conclusions
Efforts to understand the inherent stability of Earth’s climate and the basis of climate trends without a deep understanding of ice accumulation and loss from land; sea ice growth and all ice melt on oceans and ice nucleation, sublimation and terminal velocity in the atmosphere are doomed to fail. Ice dominates Earth’s radiation balance by orders of magnitude over any gas including water vapour.
I, and others long before me, recognised that ocean atmospheres exhibit an SST regulating process that prevents temperature sustaining more than 30C (303K). Prior to this analysis I had mentally pictured the regulating process as a fuel regulating governor with fine control that progressively reduced the fuel (surface sunlight) until 30C was reached. The analogy is now changed to one where the engine can be flooded and sputters when the throttle is opened too fast. It is possible to overfuel the engine with more heat below the LFC than needed to rebalance the heat loss above the LFC.
Earth’s atmosphere over tropical oceans can be viewed as a finally tuned engine reaching peak performance, in terms of heat uptake when SST is at 303K. Convective instability is similar to ignition in the Carnot cycle. If the engine fails to fire at the right time and the surface temperature overshoots then any ensuing convective instability will overshoot and the surface will cool below 303K before it reaches instability again.
As a consequence of this analysis, I have elevated the significance of convective overshooting on my list of climate control factors.
The Author
Richard Willoughby is a retired electrical engineer having worked in the Australian mining and mineral processing industry for 30 years with roles in large scale operations, corporate R&D and mine development. A further ten years was spent in the global insurance industry as an engineering risk consultant where he developed an enduring interest in natural catastrophes and changing climate.
At the beginning of July, global temperatures continued to fall significantly. Nevertheless, panic was spread in Germany by public media. The Greens even called for a work-free heat-free on days above 25 degrees Celsius. A maximum temperature of 25 degrees is the definition for a summer day in Germany. We now have about 40 – 50 of them per year, in the 50s it was still 20-30 days. But what is the cause of this? Does CO2 heat up the summer days? That is more than questionable.
As the chart above shows, the global mean temperature in June fell slightly compared to the previous month. The deviation from the long-term average of the satellite measurements is now 0.48 degrees Celsius. At the beginning of July, global temperatures continued to fall significantly. Nevertheless, panic was spread in Germany by public media. The Greens even called for a work-free heat-free on days above 25 degrees Celsius. A maximum temperature of 25 degrees is the definition for a summer day in Germany. We now have about 40 – 50 of them per year, in the 50s it was still 20-30 days. But what is the cause of this? Does CO2 heat up the summer days? That is more than questionable.
There is heat panic in Germany – but temperatures are falling
globally For the media as well as left-wing and green parties, it was the dominant topic last week: the summer heat. It was now very clear: the climate change narrative was confirmed by the heat panic in Germany. If you look at the temperature development of recent years in the next graph, you can see a significant increase in 2023, a persistence at a high level in 2024 and a clear downward trend since January 2025. Globally, we are currently more than half a degree Celsius below the summer of 2024. We are heading for zero degrees Celsius for the Copernicus data, the average value from 1991 to 2020 Copernicus.eu.
None of the quality media considered it necessary to relax the scaremongering in Germany by saying that there is no sign of extraordinary global warming worldwide in 2025. Climate researchers are puzzled as a whole about what may have caused the particular warming of 2022-2024. Their models are based on the fact that the thermal radiation emitted by the Earth is reflected back more strongly with an increase in CO2 (greenhouse effect, see next image). However, the main cause of the particular warming of 2022-24 was not CO2, but a strong El Nino – a natural phenomenon – and an increase in direct solar radiation caused by the decrease in aerosols caused by the ban on sulfur-containing diesel on ships in 2021. And indeed, direct sunlight (yellow on the left in the next image) has increased and the thermal radiation (red on the right) emitted into space has also increased. (Source: M.Lackner according to IPCC)
And this is true not only for the last 3 years, but for the last 25 years. If one examines the measurements of NASA’s CERES satellites, one finds that the warming of the last 25 years is mainly due to an increase in direct short-wave solar radiation and less to the greenhouse effect of the increased CO2 content of the air. Why 25 years? That’s how far back the measurements of NASA’s CERES satellite program go. The evaluation of the satellite measurements showed that 80% of the warming is due to the thinning of the clouds and the resulting increase in direct short-wave solar radiation. This leaves 20% of the warming for the CO2 greenhouse effect. It gets interesting when we trace the connection further back. And here is an informative graph from the German Weather Service about the change in sunshine duration in Germany.
You can clearly see the decrease in sunshine duration from 1950 to 1980 and the subsequent increase until today. At the same time, the temperature in Germany decreased slightly between 1960 and 1980. The sulphur and dust particles in the air have an influence on the duration of sunshine and cloud development. They rose sharply between 1950 and 1980 – not only in Germany – and aerosol dust and sulfuric acid particles are ideal cloud formers. They form cloud nuclei where the moist air condenses into clouds. After the introduction of exhaust gas purification in Germany and the USA for industrial plants and power plants in the 1980s, and later for motor vehicles, as well as the collapse of heavy industry in Eastern Europe in 1989, aerosol pollution in the air decreased, which led to less cloud formation. In addition, clean air also leads to less reflection of solar radiation on the dust particles. After 2000, China also made progress with exhaust gas purification programs, so that the trend towards cleaner, aerosol-free air has continued to prevail to this day.
In the meantime, the fact that the clouds are receding is also being noted by the climate mainstream. In order to be able to adhere to the theory of CO2, the sole climate-determining greenhouse gas, the following line of retreat is now being established: CO2 warms the air through the greenhouse effect. This warming leads to a change in the cloud regime, so that more short-wave direct sunlight can then come to Earth. Here is the weak point of this argumentation: Until now, it has always been claimed that warming is a consequence of the increase in long-wave radiation reflected back to Earth. So far, the models have not resulted in an increase in short-wave radiation. Worse still, fewer clouds mean that the greenhouse effect is weakened and more long-wave thermal radiation can be radiated into space. So the measurements contradict the models. In other words, the models are inadequate. However, these models are the basis of politics in Europe and Germany with their devastating climate policy, according to which net zero CO2 would have to be achieved by 2045.
However, it is possible that a warming of the oceans can change the clouds. This applies to the limited greenhouse effect of CO2 (see above), but it also applies to the natural warming and cooling of the oceans. For hundreds of years, the oceans have oscillated in a cycle of warm and cold phases of about 60-70 years (AMO – Atlantic Multidecadal Oscillation). And now it gets exciting: The clouds dance in the same beat. At high sea temperatures, the clouds are permeable, at low temperatures they allow less sunlight to reach the earth. They run in exactly opposite directions. In the next diagram we can see the course of sunshine duration and AMO.
A publication in Nature scientific reports also points to this connection. (Lüdecke, Plath, Lüning). The authors examined the AMO with the sunshine duration in Copenhagen, Krakow, Potsdam, De Bilt (Holland), Vienna, Zugspitze and Trieste. In all cases, the duration of sunshine follows the cycles of Atlantic temperatures (AMO). Here is the comparison of Potsdam. (Note the different time scales)
What conclusions can we draw from this
1. Analysis of NASA data on solar radiation and radiation shows that the models are useless for political decisions on climate issues
2. There is a connection between aerosols in the air and cloud formation and thus solar radiation
3. It cannot be ruled out that CO2 also makes a minor contribution.
In a few years, we will know what the main drivers of cloud change are. The potential of aerosols has been exhausted and the decrease in air pollution cannot be increased much further. The AMO, which has declined significantly since the beginning of this year, remains the key to this still unsolved mystery. If the AMO enters its negative phase, the cloud cover will in all probability increase again. Then there will be a decrease in direct solar radiation and thus a decrease in the increase in warming. And the role of CO2 as a limited effective greenhouse gas would have to be redefined.
The recent paper by Tselioudis et al., titled “Contraction of the World’s Storm-Cloud Zones the Primary Contributor to the 21st Century Increase in the Earth’s Sunlight Absorption”, is a fascinating—and deeply problematic—addition to the climate science canon. It offers yet another reminder that so-called “settled science” in climate modeling is anything but settled. In fact, it inadvertently illustrates how fragile the predictive power of climate models is, especially when fundamental atmospheric processes like cloud coverage are shown to be both more dynamic and less understood than previously claimed.
The recent paper by Tselioudis et al., titled “Contraction of the World’s Storm-Cloud Zones the Primary Contributor to the 21st Century Increase in the Earth’s Sunlight Absorption”, is a fascinating—and deeply problematic—addition to the climate science canon. It offers yet another reminder that so-called “settled science” in climate modeling is anything but settled. In fact, it inadvertently illustrates how fragile the predictive power of climate models is, especially when fundamental atmospheric processes like cloud coverage are shown to be both more dynamic and less understood than previously claimed.
Not that any of this is news to WUWT readers. Dr. Roy Spencer has been noting almost identical observations for over a decade as noted here,
Now let’s look at the broader scientific community catching up to Dr. Spencer.
Abstract
Recent Earth energy budget observations show an increase in the sunlight absorbed by the Earth of 0.45 W/m2 per decade, caused primarily by a decrease in cloud reflection. Here we decompose the solar radiative budget trends into general circulation and cloud controlling process components. Regimes representing the midlatitude and tropical storm zones are defined, and the trends in the areal coverage of those regimes which are potentially induced by circulation changes are separated from trends in the cloud radiative effect within each regime which are potentially induced by changes in local cloud controlling processes. The regime area change component, which manifests itself as a contraction of the midlatitude and tropical storm regimes, constitutes the largest contribution to the solar absorption trend, causing decreased sunlight reflection of 0.37 W/m2 per decade. This result provides a crucial missing piece in the puzzle of the 21st century increase of the Earth’s solar absorption.
Key Points
Satellite observations show that in the past 24 years the worlds storm cloud zones have been contracting at a rate of 1.5%–3% per decade
This contraction allows more solar radiation to reach the Earth’s surface and constitutes the largest contribution to the observed 21st century trend of increased solar absorption
Plain Language Summary
Analysis of satellite observations shows that in the past 24 years the Earth’s storm cloud zones in the tropics and the middle latitudes have been contracting at a rate of 1.5%–3% per decade. This cloud contraction, along with cloud cover decreases at low latitudes, allows more solar radiation to reach the Earth’s surface. When the contribution of all cloud changes is calculated, the storm cloud contraction is found to be the main contributor to the observed increase of the Earth’s solar absorption during the 21st century.
To understand the full implications of this study, we need to parse its findings in plain terms. The paper concludes that the Earth has absorbed significantly more solar radiation over the past 24 years—0.45 W/m² per decade. The primary culprit? A reduction in cloud cover, specifically a contraction of the midlatitude and tropical storm-cloud zones. This change has resulted in less solar radiation being reflected back into space and more being absorbed by the Earth’s surface. Crucially, 0.37 W/m² of this uptick is attributed solely to this contraction in cloud coverage, a result of large-scale atmospheric circulation changes:
“This cloud contraction, along with cloud cover decreases at low latitudes, allows more solar radiation to reach the Earth’s surface. When the contribution of all cloud changes is calculated, the storm cloud contraction is found to be the main contributor to the observed increase of the Earth’s solar absorption during the 21st century.”
Let’s pause there. Climate science has long emphasized the role of anthropogenic greenhouse gases—especially CO2—in trapping outgoing longwave radiation, contributing to surface warming. Yet here we have empirical satellite observations showing that changes in shortwave radiation absorption, due to cloud dynamics, dominate recent trends in Earth’s energy imbalance. That revelation alone should be enough to shake the very foundations of climate policy, which has funneled trillions into carbon control with scant attention paid to cloud feedback mechanisms.
More damning still is the admission that these changes are likely tied to “general circulation shifts,” specifically poleward movements of storm tracks and contractions of the Intertropical Convergence Zone (ITCZ). These are phenomena long suspected in model projections but never given such a central, quantifiable role in the planetary energy budget. And here’s the kicker: these circulation shifts are said to have emerged gradually, to the tune of 1.3% to 3% per decade:
“In all three zones, the area coverage of the L‐TCC regime shows statistically significant decreases with extremes of 1.84 ± 0.38% to 3.20 ± 0.97% per decade… indicating a contraction of the midlatitude storm regions and a narrowing of the ITCZ region.”
These aren’t theoretical projections—they are based on hard satellite data from the MODIS and CERES instruments. Models, by contrast, have only roughly hinted at these changes, and often fail to reproduce them with consistency.
The paper outlines that most of the shortwave cloud radiative effect (SWCRE) change—the key measure of how much solar energy is reflected by clouds—comes not from changes in cloud properties themselves, but from the shrinking geographic area of major cloud regimes:
“In all zones, the dominant trend is the SW cloud radiative warming that is coming from the contraction of the S‐SWCRE regimes and the corresponding expansion of the W‐SWCRE regimes.”
That’s the kind of subtle, high-leverage feedback mechanism that models tend to get wrong or underrepresent entirely. And that’s a problem. Because if your model can’t accurately simulate cloud regime shifts—which appear to contribute more than 80% of the increase in solar absorption—then your forecasts for future warming are at best incomplete, and at worst, wildly misleading.
Tselioudis et al. even admit this shortcoming, noting:
“It is imperative to test the skills of climate models in simulating the observed storm‐cloud area contraction, and to use both modeling and observational analyses to understand the interactions between atmospheric dynamics shifts and storm cloud changes.”
What this paper also inadvertently confirms is the unreliability of using long-term climate models to dictate aggressive, disruptive policies like Net Zero. The models are missing key physical processes—cloud behavior, aerosol effects, and large-scale atmospheric shifts. As the paper notes:
“The general circulation shift component constitutes the dominant term of the recent increase in absorbed solar radiation and provides a crucial missing piece in the puzzle of the 21st century radiative warming and the large heat anomaly of 2023.”
Yet these shifts are only just beginning to be understood, and their driving forces—whether natural variability, solar activity, ocean cycles, or some interaction thereof—remain far from nailed down.
Worse still, the authors openly speculate that low-latitude cloud reductions could be driven by aerosol changes—particularly the decline in ship emissions:
“This component shows a significant cloud radiative warming of 0.21 W/m²/decade that can be attributed to aerosol indirect effects on clouds including effects from the reduction of aerosol ship emissions.”
That’s right: the same well-meaning efforts to reduce pollution from ocean-going vessels may have accelerated warming by allowing more sunlight to hit the surface. Climate mitigation whack-a-mole strikes again.
In sum, Tselioudis et al.’s paper is a quietly revolutionary work—not because it introduces a new alarmist narrative, but because it destabilizes the prevailing one. It shows that:
Cloud feedbacks, especially those driven by circulation shifts, have enormous and previously underestimated impacts on Earth’s radiative balance.
These changes are driven by complex, poorly understood dynamics that current climate models struggle to replicate.
Policy decisions predicated on “settled science” have been made in the absence of understanding a major component of the Earth’s energy system.
If climate science were a functioning scientific discipline rather than a priesthood, this paper would trigger a major course correction. It would cast doubt on the simplistic link between CO2 and warming, redirecting focus toward cloud physics, ocean-atmosphere interactions, and circulation dynamics. It would foster humility in the face of atmospheric complexity—not arrogance born from model outputs.
But don’t expect that anytime soon. Instead, expect the usual suspects to spin this as evidence of “even worse than we thought” warming, conveniently omitting the part where their models didn’t predict it and their policies had nothing to do with it.
In the meantime, this paper should serve as ammunition for any skeptic pointing out the absurdity of building trillion-dollar policies on the backs of incomplete and overconfident simulations. The cloud regimes are shifting. The models aren’t keeping up. And neither is the narrative.
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