Climate Factors | Science Matters

SH Drives UAH Temps Cooler July 2025

The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots. It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition. Yes, there was warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.

As an overview consider how recent rapid cooling completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016). The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022 At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Then there was an usual El Nino warming spike of uncertain cause, unrelated to steadily rising CO2, and now dropping steadily back toward normal values.

For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~65 ppm, an 18% increase.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

gmt-warming-events

The animation is an update of a previous analysis from Dr. Murry Salby. These graphs use Hadcrut4 and include the 2016 El Nino warming event. The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4. This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C. Previously the 1997-98 El Nino produced a plateau increase of 0.4C. Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate. On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles. And in 2024 we saw an amazing episode with a temperature spike driven by ocean air warming in all regions, along with rising NH land temperatures, now dropping below its peak.

Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT

July 2025 SH Drives UAH Temps Lower

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea. While you heard a lot about 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in. The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995. Spring and Summer 2023 saw a series of warmings, continuing into 2024 peaking in April, then cooling off to the present.

UAH has updated their TLT (temperatures in lower troposphere) dataset for July 2025. Due to one satellite drifting more than can be corrected, the dataset has been recalibrated and retitled as version 6.1 Graphs here contain this updated 6.1 data. Posts on their reading of ocean air temps this month are behind the update from HadSST4. I posted recently on SSTs June 2025 Ocean SSTs: NH Warms, SH Cools.These posts have a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Sometimes air temps over land diverge from ocean air changes. In July 2024 all oceans were unchanged except for Tropical warming, while all land regions rose slightly. In August we saw a warming leap in SH land, slight Land cooling elsewhere, a dip in Tropical Ocean temp and slightly elsewhere. September showed a dramatic drop in SH land, overcome by a greater NH land increase. 2025 has shown a sharp contrast between land and sea, first with ocean air temps falling in January recovering in February. Then land air temps, especially NH, dropped in February and recovered in March. Now in July SH ocean dropped markedly, pulling down the Global ocean anomaly despite a rise in the Tropics. SH land also cooled by half, driving Global land temps down despite Tropics land warming.

Note: UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021. v6.1 data was recalibrated also starting with 2021. In the charts below, the trends and fluctuations remain the same but the anomaly values changed with the baseline reference shift.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system. Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy. Measuring water temperature directly avoids distorted impressions from air measurements. In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates. Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST. Thus cooling oceans portend cooling land air temperatures to follow. He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months. This latter point is addressed in a previous post Who to Blame for Rising CO2?

After a change in priorities, updates are now exclusive to HadSST4. For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6.1 which are now posted for July 2025. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the revised and current dataset.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI). The graph below shows monthly anomalies for ocean air temps since January 2015.

In 2021-22, SH and NH showed spikes up and down while the Tropics cooled dramatically, with some ups and downs, but hitting a new low in January 2023. At that point all regions were more or less in negative territory.

After sharp cooling everywhere in January 2023, there was a remarkable spiking of Tropical ocean temps from -0.5C up to + 1.2C in January 2024. The rise was matched by other regions in 2024, such that the Global anomaly peaked at 0.86C in April. Since then all regions have cooled down sharply to a low of 0.27C in January. In February 2025, SH rose from 0.1C to 0.4C pulling the Global ocean air anomaly up to 0.47C, where it stayed in March and April. In May drops in NH and Tropics pulled the air temps over oceans down despite an uptick in SH. At 0.43C, ocean air temps were similar to May 2020, albeit with higher SH anomalies. Now in July Global temps are down to 0.32C due to SH dropping from 0.48C to 0.21C.

Land Air Temperatures Tracking in Seesaw Pattern

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly. The land temperature records at surface stations sample air temps at 2 meters above ground. UAH gives tlt anomalies for air over land separately from ocean air temps. The graph updated for July is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land. The seesaw pattern in Land temps is similar to ocean temps 2021-22, except that SH is the outlier, hitting bottom in January 2023. Then exceptionally SH goes from -0.6C up to 1.4C in September 2023 and 1.8C in August 2024, with a large drop in between. In November, SH and the Tropics pulled the Global Land anomaly further down despite a bump in NH land temps. February showed a sharp drop in NH land air temps from 1.07C down to 0.56C, pulling the Global land anomaly downward from 0.9C to 0.6C. In March that drop reversed with both NH and Global land back to January values, holding there in April. In May sharp drops in NH and Tropics land air temps pulled the Global land air temps back down close to February value. In July SH land dropped sharply, down from 0.47C to 0.23C, and NH land also cooled by 0.08C pulling Global land air down as well.

The Bigger Picture UAH Global Since 1980

The chart shows monthly Global Land and Ocean anomalies starting 01/1980 to present. The average monthly anomaly is -0.03, for this period of more than four decades. The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20. An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022. March and April brought warmer Global temps, later reversed

With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Then in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016. In 2024 March and April took the Global anomaly to a new peak of 0.94C. The cool down started with May dropping to 0.9C, and in June a further decline to 0.8C. October went down to 0.7C, November and December dropped to 0.6C. Now in July Global Land and Ocean is down to 0.36C

The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps. Clearly NH and Global land temps have been dropping in a seesaw pattern, nearly 1C lower than the 2016 peak. Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force. TLT measures started the recent cooling later than SSTs from HadSST4, but are now showing the same pattern. Despite the three El Ninos, their warming had not persisted prior to 2023, and without them it would probably have cooled since 1995. Of course, the future has not yet been written.

Why Current GHG Effect is Simply Not Scary

Posted on August 4 by Ron Clutz

Donald Rapp makes things clear and concise in his 2024 paper How Increased CO2 Warms the Earth-Two Contexts for the Greenhouse Gas Effect. Excerpts in italics with my bolds, exhibits and some added images.

Physicist Donald Rapp retired from the Jet Propulsion Laboratory and has authored many books including Ice Ages and Interglacials: Measurements, Interpretation and Models; Assessing Climate Change: Temperatures, Solar Radiation and Heat Balance; and Use of Extraterrestrial Resources for Human Space Missions to Moon or Mars (Astronautical Engineering). Most recently he published Revisiting 2,000 Years of Climate Change (Bad Science and the “Hockey Stick”)

Abstract

The widespread explanations of the greenhouse effect taught to millions of schoolchildren are misleading. The objective of this work is to clarify how increasing CO2 produces warming in current times. It is found that there are two contexts for the greenhouse gas effect. In one context, the fundamental greenhouse gas effect, one imagines a dry Earth starting with no water or CO2 and adding water and CO2 . This leads to the familiar “thermal blanket” that strongly inhibits IR transmission from the Earth to the atmosphere. The Earth is much warmer with H2 O and CO2 . In the other context, the current greenhouse gas effect, CO2 is added to the current atmosphere. The thermal blanket on IR radiation hardly changes. But the surface loses energy primarily by evaporation and thermals. Increased CO2 in the upper atmosphere carries IR radiation to higher altitudes. The Earth radiates to space at higher altitudes where it is cooler, and the Earth is less able to shed energy. The Earth warms to restore the energy balance. The “thermal blanket” is mainly irrelevant to the current greenhouse gas effect. It is concluded that almost all discussions of the greenhouse effect are based on the fundamental greenhouse gas effect, which is a hypothetical construct, while the current greenhouse gas effect is what is happening now in the real world.

Adding CO2 does not add much to a “thermal blanket” but instead,
drives emission from the Earth to higher, cooler altitudes.

Background

Were it not for the Sun, the Earth would be a frozen hulk in space. The Sun sends a spectrum of irradiance to the Earth, the Earth warms, and the Earth radiates energy out to space. This process continues until the Earth warms enough to radiate about as much energy to space as it receives from the Sun, reaching an approximate steady state. If for some reason, the Earth is unable to radiate all the energy received from the Sun, the Earth will warm until it can radiate all the energy received. It is widely accepted that rising CO2 concentration reduces the ability of the Earth to radiate energy to space. In a dynamic situation where the CO2 concentration is continually increasing with time, the Earth will continuously warm as it tries to “catch up” to the effect of increasing CO2 and reestablish a steady state. It is a conundrum that while it is widely accepted that rising CO2 concentration produces global warming, the exact mechanism by which warming is induced in the current atmosphere by rising CO2 is not widely understood. The concept of a “thermal blanket” imposed by greenhouse gases to warm the Earth has merit in some contexts but is mainly irrelevant to the question of how adding CO2 to the current atmosphere produces warming.

Before attempting to deal with the question of how rising CO2 concentration affects the current Earth’s climate, it is appropriate to first discuss the Earth’s energy budget. The exact values for each energy flow are not important, but the relative values are important to show which processes dominate.

Finally, we provide an explanation of how adding CO2 to the current atmosphere produces global warming in the current atmosphere. The mechanism is not widely known and is likely to be surprising to some. Warming does not occur by increasing the thickness of the thermal blanket but instead occurs by raising the altitude at which the Earth radiates to space.

IR radiation

A fundamental law of physics states that all bodies emit a spectrum of radiant power proportional to the fourth power of their absolute temperature. A body at absolute temperature T (K) emits power per unit area: P = σ T 4 = 5.67 x 10 -8 T 4 (W/m 2 ) For example, a body at T = 280 K is said to emit 348 W/m 2 . However, this law of physics is academic and not directly applicable to real-world experience. In the real world, we never have a single isolated body emitting radiation, instead, we deal with pairs of bodies where the warmer one radiates a net flux to the cooler one. (If you stand next to a body at 280 K, you don’t feel an incoming heat flux of 348 W/m 2 ). For example, if there is one body at 280 K and a second body at 275 K, the warmer body will radiate through a vacuum to the cooler body at a net of 24 W/m 2 . That is a real-world parameter that can be measured. But the academic model involves calculating the emission of the warm body as 348 W/m 2 and the emission of the cooler body as 324 W/m 2 , and subtracting, the net transfer from the warm body to the cool body is 24 W/m 2 . But the calculated values are academic and cannot be measured in the real world with 348 W/m 2 in one direction and 324 W/m 2 in the opposite direction. Those values are only of academic use to infer the measurable net of about 24 W/m 2 . See the simple model in Figure 1 presented here for illustration.

Figure 1: Radiant heat transfer between warm and cool bodies

The two contexts of the greenhouse effect

We are all aware of the widely discussed greenhouse effect that warms the Earth as the concentration of greenhouse gases increases. But just how does it work? Here, we define two contexts for greenhouse gas effects:

1) The fundamental greenhouse gas effect can be described by a “gedanken experiment” in which one imagines a dry Earth starting with no water or CO 2 and begins adding water and CO 2 . The original atmosphere, lacking water and CO 2 , will transmit IR radiation completely. As a result, the Earth will be quite cool. As H 2 O and CO 2 are added to the atmosphere, the transmission of IR radiation from the Earth’s surface is increasingly inhibited, and the Earth warms. As the Earth warms, evaporation and thermals transmit more energy from the Earth to the atmosphere. By the time H 2 O and CO 2 levels reach current levels, the atmosphere is almost opaque to IR radiation, and a “thermal blanket” greatly reduces IR transmission from the Earth to the atmosphere. The Earth cools primarily by evaporation and thermals, and it is much warmer than if CO 2 and water were absent. The notion of a “thermal blanket” of IR absorbing gases warming the Earth has validity in this context starting with a transmitting atmosphere and adding greenhouse gases. However, once the thermal blanket is established with ~ 400 ppm CO 2 , adding more CO 2 has only a small effect on reducing IR radiation from the surface.

2) The current greenhouse gas effect deals with the question: How does the addition of CO 2 to the atmosphere affect the global average temperature in 2024 and beyond, with CO 2 around 400+ ppm? It was shown previously that starting with no water or CO 2 , adding H 2 O and CO 2 to the atmosphere generates a “thermal blanket” for radiation. But once that “thermal blanket” is well established and the lower atmosphere is very opaque to IR radiation, what is the effect of adding even more CO 2 ? Dufresne, et al. provide a detailed technical analysis to show how the current greenhouse effect works [7]. However, this reference is complex and written for expert specialists in IR transmission through the atmosphere. In the sections that follow, a simpler, qualitative interpretation will be presented.

Figure 3: Energy flows in the Earth’s system. (Based on LTWS references).

Energy budget of the earth

Energy transfer in the Earth system can take place by thermal transfers (“thermals”) where winds carry warm air up to colder regions, evaporation from the surface (removes heat), and condensation in the atmosphere (deposits heat) and radiation (further discussion follows).

After analyzing the data in the LTWS references (see Section 1.2), a rough estimate of key energy flows per unit time in the Earth system is given as follows. The exact numbers are not critical; only their relative values are important for this discussion.

These results can be visualized in Figure 3 which is based on the references LTWS. As shown in Figure 3, incoming solar irradiance (341 W/ m 2 ) is partly reflected by the lower atmosphere back out to space (79 W/m 2 ), partly reflected by the Earth’s surface back out to space (23 W/m 2 ), partly absorbed by the lower atmosphere (76 W/m 2 ), and finally about 163 W/m 2 is absorbed by the surface.

Radiation from the Earth’s surface to the lower atmosphere requires further discussion. The LTWS references show high up and down radiation flows. For example, Trenberth, et al. did not show radiation transfer between the Earth’s surface as a simple 25 W/m 2 net radiative transfer from the surface to the lower atmosphere. Instead, they showed 356 W/m 2 radiated upward from the surface and 333 W/m 2 of “back radiation” from the atmosphere to the surface [2]. The figure 356 W/m 2 radiated upward from the surface corresponds to the theoretical radiation from a blackbody at 281.5 K. The claimed downward figure is difficult to explain. But both of these figures are academic. What is happening is that the warm Earth is radiating upward through an optically thick gas of H 2 O and CO 2 absorbers, and the radiant transfer through that thick gas is estimated to be only a mere ~25 W/m 2 . This is the “thermal blanket” so often referred to in discussions of global warming. The thermal blanket is real. But the problem with so many discussions of the greenhouse effect is that there is a preoccupation with radiant energy transfer between the Earth and the atmosphere (which is “blanketed”) while neglecting the more important transfers of energy to the atmosphere by processes other than radiation.

Figure 4: Pressure, temperature, and relative humidity vs. altitude [8].

The terms “lower atmosphere” and “upper atmosphere” are defined next. Following Miscolczi, Figure 4 shows that the demarcation between upper and lower atmospheres occurs at an altitude of roughly 12 km above which H 2 O is frozen out and the temperature roughly stabilizes [8].

Energy transfer in the lower atmosphere takes place by conduction,
convection, and radiation. Energy transfer in the upper atmosphere
takes place primarily by radiation.

The greenhouse effect

The greenhouse effect can only be fully understood by comprehensive modeling of upward energy flows in the Earth system. Excellent studies by Dufresne, et al. and Pierrehumbert provide detailed physics [7,9]. Here, we interpret these results qualitatively.

Within the Earth system of land, ocean, atmosphere, and clouds, energy transfer is taking place continuously. There is a net energy flow upward toward higher altitudes. From the surface of the Earth, much of the upward flow of energy in the lower atmosphere is through evaporation and convection. The lower atmosphere is almost opaque to IR radiation due to water vapor and CO 2.

Figure 5: Qualitative sketch to show radiation is dominant at the highest altitude. By adding CO2 to the atmosphere, radiative energy transport is carried to a higher altitude where it is colder, reducing the radiant power emitted by the upper atmosphere.

Radiation energy transfer will persist out toward a high altitude until the CO 2 concentration diminishes. Each CO 2 molecule that absorbs an IR photon can reradiate in all directions, but in a thin atmosphere, some upward IR radiation will be lost, and on a net basis, this allows the Earth to radiate out to space. The presence of an IR transmitting/absorbing gas (CO 2 ) will allow energy transport to higher altitudes. The highest altitude where there is enough thin gas to maintain radiation is the region of the atmosphere that mainly radiates energy outward to space. This is illustrated on the left side of Figure 5. Figure 5 was created here to illustrate how the predominant energy transfer mechanisms gradually change to IR radiation at higher altitudes, and the presence of CO 2 carries the IR radiation to higher altitudes.

Conclusion

There are two different contexts for discussion of the effect of greenhouse gases on the Earth’s climate.

In one context, one can imagine an Earth with no water vapor or CO 2 in the atmosphere. This Earth can radiate effectively to space and is relatively cold. As water vapor and CO 2 are added to the atmosphere, the IR-opacity of the atmosphere increases and the Earth system warms. The greenhouse gases act as a “thermal blanket” to warm the Earth by impeding upward IR radiation. This is labeled the fundamental greenhouse gas effect. However, once the thermal blanket is established, adding more CO 2 has only a minimal effect on the thermal blanket, and reduced upward IR radiation from the surface does not produce significant warming. This is referred to by Dufresne, et al. [7] as the “saturation paradox”.

In the other context, we are concerned with the effect of adding more CO 2 to the current atmosphere where the CO 2 concentration is already 400+ ppm, and the thermal blanket is already in place, restricting upward IR-radiation. This is labeled the current greenhouse gas effect, and it is quite different from the fundamental greenhouse gas effect. In the current atmosphere, energy transfer from the Earth to the atmosphere is primarily by evaporation and thermals, and IR-radiant energy transfer is significantly impeded by an almost opaque lower atmosphere. The “thermal blanket” is in place, but it doesn’t change much as CO 2 is added to the atmosphere. Adding CO 2 to the current atmosphere slightly increases the opacity of the lower atmosphere but this is of little consequence.

In the upper atmosphere, CO 2 is the major means of energy transport by IR radiation. The greatest effect of adding CO 2 to the current atmosphere is to extend the upward range of IR-radiant transmission to higher altitudes. The main region where the Earth radiates to space is thereby extended to higher altitudes where it is colder, and the Earth cannot radiate as effectively as it could with less CO 2 in the atmosphere. The Earth warms until the region in the upper atmosphere where the Earth radiates to space is warm enough to balance incoming solar energy.

My Comment:

The explanation above is clear and understandable in qualititative terms. It does not reference empirical evidence regarding a GHG effect from a raised effective radiating level (ERL). Studies investigating this theory find that the effect is too small to appear in the data.

Refresher: GHG Theory and the Tests It Fails

Postscript on Raised Effective Radiating Level

The following diagram by Andy May shows the pattern of emissions by GHGs, mainly H2O and CO2.

Helpfully, it shows the altitudes where the emissions occur. As stated in the text above, the upper and lower tropopsphere shift occurs about 12km high, with variations lower at poles and higher in tropics. Note the large CO2 notch appears at 85km, which puts it into the thermosphere, where temperatures increase with altitude. Raising the ERL there means greater cooling, not less. The Ozone notch at 33km is in the stratosphere, where temperatures also rise with altitude. Otherwise almost all of the IR effect is from H2O.

DOE Climate Team: Twelve Keys in Assessing Climate Change

Posted on July 31 by Ron Clutz

Last week saw the release of A Critical Review of Impacts of Greenhouse Gas Emissions on the U.S. Climate by the U.S. DOE Climate Working Group. This post provides the key points from the twelve chapters of the document, comprised of the chapter summaries plus some salient explanations. This is a synopsis and readers are encouraged to access additional detailed information at the link in red above. I added some pertinent images along with some from the report.

Report to U.S. Energy Secretary Christopher Wright July 23, 2025
Climate Working Group:
John Christy, Ph.D.
Judith Curry, Ph.D.
Steven Koonin, Ph.D.
Ross McKitrick, Ph.D.
Roy Spencer, Ph.D.

Introduction

This report reviews scientific certainties and uncertainties in how anthropogenic carbon dioxide (CO2) and other greenhouse gas emissions have affected, or will affect, the Nation’s climate, extreme weather events, and selected metrics of societal well-being. Those emissions are increasing the concentration of CO2 in the atmosphere through a complex and variable carbon cycle, where some portion of the additional CO2 persists in the atmosphere for centuries.

Chapter 1 Carbon Dioxide as a Pollutant

Carbon dioxide (CO2) differs in many ways from the so-called Criteria Air Pollutants. It does not affect local air quality and has no human toxicological implications at ambient levels. The growing amount of CO2 in the atmosphere directly influences the earth system by promoting plant growth (global greening), thereby enhancing agricultural yields, and by neutralizing ocean alkalinity. But the primary concern about CO2 is its role as a greenhouse gas (GHG) that alters the earth’s energy balance, warming the planet. How the climate will respond to that influence is a complex question that will occupy much of this report.

Chapter 2 Direct impact of CO2 on the Environment

CO2 enhances photosynthesis and improves plant water use efficiency, thereby promoting plant growth. Global greening due in part to increased CO2 levels in the atmosphere is well-established on all continents. The growing CO2 concentration in the atmosphere has the important positive effect of promoting plant growth by enhancing photosynthesis and improving water use efficiency. That is evident in the “global greening” phenomenon discussed below, as well as in the improving agricultural yields discussed in Chapter 10.

The IPCC has only minimally discussed global greening and CO2 fertilization of agricultural crops. The topic is briefly acknowledged in a few places in the body of the IPCC 6th and earlier Assessment Reports but is omitted in all Summary documents. Section 2.3.4.3.3 of the AR6 Working Group I report, entitled “global greening and browning,” points out that the IPCC Special Report on Climate Change and Land had concluded with high confidence that greening had increased globally over the past 2-3 decades.

It then discusses that there are variations in the greening trend among data sets, concluding that while they have high confidence greening has occurred, they have low confidence in the magnitude of the trend. There are also brief mentions of CO2 fertilization effects and improvements in water use efficiency in a few other chapters in the AR6 Working Groups I and II Reports. Overall, however, the Policymaker Summaries, Technical Summaries, and Synthesis Reports of AR5 and AR6 do not discuss the topic.

Source: Tom Segelstad Carbon isotope mass balance in CO2

CO2 absorption in sea water makes the oceans less alkaline. While this process is often called “ocean acidification”, that is a misnomer because the oceans are not expected to become acidic; “ocean neutralization” would be more accurate. Even if the water were to turn acidic, it is believed that life in the oceans evolved when the oceans were mildly acidic with pH 6.5 to 7.0 (Krissansen-Totton et al., 2018).

The recent decline in pH is within the range of natural variability on millennial time scales. Most ocean life evolved when the oceans were mildly acidic. Decreasing pH might adversely affect corals, although the Australian Great Barrier Reef has shown considerable growth in recent years.

It is being increasingly recognized that publication bias (alarming ocean acidification results preferred by high-impact research publications) exaggerates the reported impacts of declining ocean pH. An ICES Journal of Marine Science Special Issue addressed this problem with an article entitled, Towards a Broader Perspective on Ocean Acidification Research. In the Introduction to that Special Issue, H. I. Browman stated, “As is true across all of science, studies that report no effect of ocean acidification are typically more difficult to publish.” (Browman, 2016).

In summary, ocean life is complex and much of it evolved when the oceans were acidic relative to the present. The ancestors of modern coral first appeared about 245 million years ago. CO2 levels for more than 200 million years afterward were many times higher than they are today. Much of the public discussion of the effects of ocean “acidification” on marine biota has been one-sided and exaggerated.

Chapter 3 Human Influences on the Climate

The global climate is naturally variable on all time scales. Anthropogenic CO2 emissions add to that variability by changing the total radiative energy balance in the atmosphere.
The IPCC has downplayed the role of the sun in climate change but there are plausible solar irradiance reconstructions that imply it contributed to recent warming.
Climate projections are based on IPCC emission scenarios that have tended to exceed observed trends.
Most academic climate impact studies in recent years are based upon the extreme RCP 8.5 scenario that is now considered implausible; its use as a business-as-usual scenario has been misleading.
Carbon cycle models connect annual emissions to growth in the atmospheric CO2 stock. While models disagree over the rate of land and ocean CO2 uptake, all agree that it has been increasing since 1959.
There is evidence that urbanization biases in the land warming record have not been completely removed from climate data sets.

There are about 850 Gt of carbon (GtC) in the Earth’s atmosphere, almost all of it in the form of CO2. Each year, biological processes (plant growth and decay) and physical processes (ocean absorption and outgassing) exchange about 200 GtC of that carbon with the Earth’s surface (roughly 80 GtC with the land and 120 GtC with the oceans). Before human activities became significant, removals from the atmosphere were roughly in balance with additions. But burning fossil fuels (coal, oil, and gas) removes carbon from the ground and adds it to the annual exchange with the atmosphere. That addition (together with a much smaller contribution from cement manufacturing) amounted to 10.3 GtC in 2023, or only about 5 percent of the annual exchange with the atmosphere.

The carbon cycle accommodates about 50 percent of humanity’s small annual injection of carbon into the air by naturally sequestering it through plant growth and oceanic uptake, while the remainder accumulates in the atmosphere (Ciais et al., 2013). For that reason, the annual increase in atmospheric CO2 concentration averages only about half of that naively expected from human emissions. The historical near constancy of that 50 percent fraction means that the more CO2 humanity has produced, the faster nature removed it from the atmosphere.

While land vegetation has been responding positively to more atmospheric CO2, uptake of extra CO2 by ocean biological processes remains too uncertain to be measured reliably.

Historical temperature data over land has been collected mainly where people live. This raises the problem of how to filter out non-climatic warming signals due to Urban Heat Islands (UHI) and other changes to the land surface. If these are not removed the data might over- attribute observed warming to greenhouse gases. The IPCC acknowledges that raw temperature data are contaminated with UHI effects but claims to have data cleaning procedures that remove them. It is an open question whether those procedures are sufficient.

The challenge in measuring UHI bias is relating local temperature change to a corresponding change in population or urbanization, rather than to a static classification variable such as rural or urban. Spencer et al. (2025) used newly available historical population archives to undertake such an analysis and found evidence of significant UHI bias in U.S. summertime temperature data.

In summary, while there is clearly warming in the land record, there is also evidence that it is biased upward by patterns of urbanization and that these biases have not been completely removed by the data processing algorithms used to produce climate data sets.

Chapter 4 Climate Sensitivity to CO2 Forcing

There is growing recognition that climate models are not fit for the purpose of determining the Equilibrium Climate Sensitivity (ECS) of the climate to increasing CO2. The IPCC has turned to data driven approaches including historical data and paleoclimate reconstructions, but their reliability is diminished by data inadequacies.

Data-driven ECS estimates tend to be lower than climate model-generated values. The IPCC AR6 upper bound for the likely range of ECS is 4.0°C, lower than the AR5 value of 4.5°C. This lowering of the upper bound seems well justified by paleoclimatic data. The AR6 lower bound for the likely range of ECS is 2.5°C, substantially higher than the AR5 value of 1.5°C. This raising of the lower bound is less justified; evidence since AR6 finds the lower bound of the likely range to be around 1.8°C.

In principle, ECS is an emergent property of GCMs—that is, it is not directly parameterized or tuned but rather emerges in the results of the simulation. Otherwise plausible GCMs and parameter selections have been discarded because of perceived conflict with an expected warming rate, or aversion to a model’s climate sensitivity being outside an accepted range (Mauritsen et al. 2012). This practice was commonplace for the models used in AR4; modelers have moved away from this practice with time. However, even in a CMIP6 model, the MPI (Max Planck Institute) modelers chose an ECS value of 3°C and then tuned the cloud parameterizations to match their intended result.

The Transient Climate Reponse (TCR) provides a more useful observational constraint on climate sensitivity. TCR is the global temperature increase that results when CO2 is increased at an annual rate of 1 percent over a period of 70 years (i.e., doubled gradually). Relative to the ECS, observationally determined values of TCR avoid the problems of uncertainties in ocean heat uptake and the fuzzy boundary in defining equilibrium arising from a range of timescales for the longer-term feedback processes (e.g., ice sheets). TCR is better constrained by historical warming, than ECS. AR6 judged the very likely range of TCR to be 1.2–2.4°C. In contrast to ECS, the upper bound of TCR is more tightly constrained. For comparison, the TCR values determined by Lewis (2023) are 1.25 to 2.0°C, showing much better agreement with AR6 values than was seen in a comparison of the ECS values.

Figure 8: Warming in the tropical troposphere according to the CMIP6 models.
Trends 1979–2014 (except the rightmost model, which is to 2007), for 20°N–20°S, 300–200 hPa.

Chapter 5 Discrepancies Between Models and Instrumental Observations

Climate models show warming biases in many aspects of their reproduction of the past several decades. In response to estimated changes in forcing they produce too much warming at the surface (except in the models with lowest ECS), too much warming in the lower-and mid-troposphere and too much amplification of warming aloft.

Climate models also produce too much recent stratospheric cooling, invalid hemispheric albedos, too much snow loss, and too much warming in the Corn Belt. The IPCC has acknowledged some of these issues but not all.

The wide range of choices made by modelers to characterize the physical processes in the models (see Box: Climate Modeling in Section 5.1 above) is seen by the large spread of trends in the middle troposphere, ±40 percent about the median (Figure 5.6). This vividly illustrates the uncertainties in attempts to model (parameterize) a complex system involving turbulence, moist thermodynamics, and energy fluxes over the full range of the tropical atmosphere’s time and space scales. The atmosphere’s temperature profile is a case where models are not merely uncertain but also show a common warming bias relative to observations. This suggests that they misrepresent certain fundamental feedback processes.
The IPCC AR6 did not assess this issue.

An important element of the expected general “fingerprint” of anthropogenic climate change is simultaneous warming of the troposphere and cooling of the stratosphere. The latter feature is also influenced by ozone depletion and recovery. AR6 acknowledged that cooling had been observed but only until the year 2000. The stratosphere has shown some warming since, contrary to model projections.

The climate models were found to poorly explain the observed trends [in Northern Hemisphere snow cover]. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant.

Beyond the models’ ability to reproduce features of today’s climate, the critical issue for society is how well they predict responses to subtle human influences, such as greenhouse gas emissions, aerosol cooling, and landuse changes. The most crucial aspect that models must capture correctly is “feedbacks.” These occur when climate changes either amplify or suppress further warming. In general, the modeled net effect of all feedbacks doubles or triples the direct warming impact of CO₂.

Economic losses normalized for wealth (upper panel) and the number of people affected normalized for population size (lower panel). Sample period is 1980–2010. Solid lines are IRW trends for the corresponding data. EM-DAT database.

Chapter Six Extreme Weather

This chapter is concerned with detection of trends in extreme weather, while Chapter 8 considers causal attribution, with Section 8.4 specifically addressing extreme weather. If no trend is detected, then clearly there is no basis for attribution. But even where a trend is observed, attribution to human-caused warming does not necessarily follow.

With these caveats in mind, we examine the evidence for changes in selected weather and climate extremes. A recurring theme is the wide gap between public perceptions and scientific evidence. It has become routine in media coverage, government and private sector discussions, and even in some academic literature to make generalized assertions that extreme weather of all types is getting worse due to GHGs and “climate change.” Yet expert assessments typically have not drawn such sweeping conclusions and instead have emphasized the difficulty both of identifying specific trends and establishing a causal connection with anthropogenic forcing.

Most types of extreme weather exhibit no statistically significant long-term trends over the available historical record. While there has been an increase in hot days in the U.S. since the 1950s, a point emphasized by AR6, numbers are still low relative to the 1920s and 1930s. Extreme convective storms, hurricanes, tornadoes, floods and droughts exhibit considerable natural variability, but long-term increases are not detected. Some increases in extreme precipitation events can be detected in some regions over short intervals, but the trends do not persist over long periods and at the regional scale. Wildfires are not more common in the U.S. than they were in the 1980s. Burned area increased from the 1960s to the early 2000’s, however it is low compared to the estimated natural baseline level. U.S. wildfire activity is strongly affected by forest management practices.

Chapter 7 Changes in Sea Level

Since 1900, global average sea level has risen by about 8 inches. Sea level change along U.S. coasts is highly variable, associated with local variations in processes that contribute to sinking and also with ocean circulation patterns. The largest sea level increases along U.S. coasts are Galveston, New Orleans, and the Chesapeake Bay regions – each of these locations are associated with substantial local land sinking (subsidence) unrelated to climate change.

Extreme projections of global sea level rise are associated with an implausible extreme emissions scenario and inclusion of poorly understood processes associated with hypothetical ice sheet instabilities. In evaluating AR6 projections to 2050 (with reference to the baseline period 1995-2014), almost half of the interval has elapsed by 2025, with sea level rising at a lower rate than predicted. U.S.tide gauge measurements reveal no obvious acceleration beyond the historical average rate of sea level rise.

The concern over sea level rise is not about the roughly eight inches of global rise since 1900. Rather,it is about projections of accelerated rise based upon simulations of a warming climate through the 21st century. . .There is deep uncertainty surrounding projections of sea level rise to 2100 owing to uncertainties in ice sheet instabilities, particularly for the higher emissions scenarios.

In February 2022, NOAA issued its projections of sea level rise for various sites along the U.S. coast (Sweet et al., 2022). They claim that by 2050, the sea will have risen one foot at The Battery in Manhattan (relative to 2020). A one-foot rise in thirty years would be more than twice the current rate and about three times the average rate over the past century. In that historical context, NOAA’s projection is remarkable—as shown in Figure 7.6, it would require a dramatic acceleration beyond anything observed since the early 20th century. But even more noteworthy is that Sweet et al. (2022) say this rise is “locked in”—it will happen no matter what future emissions are. We should know in a decade or so whether that prediction has legs.

Chapter 8 Uncertainties in Climate Change Attribution

“Attribution” refers to identifying the cause of some aspect of climate change, specifically with reference to anthropogenic activity. There is an ongoing scientific debate around attribution methods, particularly regarding extreme weather events. Attribution is made difficult by high natural variability, the relatively small expected anthropogenic signal, lack of high-quality data, and reliance on deficient climate models. The IPCC has long cautioned that methods to establish causality in climate science are inherently uncertain and ultimately depend on expert judgement.

Substantive criticism of the main IPCC assessments of the role of CO2 in recent warming focus on inadequate assessment of natural climate variability, uncertainties in measurement of solar variability and in aerosol forcing, and problems in the statistical methods used for attribution.

As discussed in Chapter 6 natural variability dominates patterns of extreme weather systems and simplistic assertions of trend detection are frequently undermined by regional heterogeneity and trend reversals over time. Table 8.1 makes the related point that it is not currently possible to attribute changes in most extreme weather types to human influences. Taking wind as an example, the IPCC claims that an anthropogenic signal has not emerged in average wind speeds, severe windstorms, tropical cyclones or sand and dust storms, nor is one expected to emerge this century even under an extreme emissions scenario. The same applies to drought and fire weather.

The IPCC does not make attribution claims for most climate impact drivers related to extreme events. Statements related to statistics of global extremes (e.g. event probability or return times, magnitude and frequency) are not generally considered accurate owing to data limitations and are made with low confidence. Attribution of individual extreme weather events is challenging due to their rarity. Conflicting claims about the causes of the 2021 Western North America Heatwave illustrate the perils of hasty attribution claims about individual extreme events.

There are three areas of substantive criticism of the IPCC’s assessment of the causes of the recent warming: inadequate assessment of natural climate variability, inappropriate statistical methods, and substantial discrepancies between models and observations. The last is discussed in Chapter 5, while this chapter discusses the first two factors. All of these criticisms are relevant to the IPCC’s attribution of the recent warming, which also underpins extreme event attribution.

A sharp recent increase in global average temperatures has raised the question of short-term drivers of climate. One such candidate is the fraction of absorbed solar radiation which has also increased abruptly in recent years. The question is whether the change is an internal feedback to warming caused by greenhouse gases, or whether something else increased the fraction of absorbed radiation which then caused the recent warming.

Fig. 1. Qualitative tendencies in decadal SSR (Surface Solar Radiation) changes over the periods 1950s to 1980s, 1980s to 2000, and post-2000 in different world regions that are well covered by historic SSR records.

Arguably the most striking change in the Earth’s climate system during the 21st century is a significant reduction in planetary albedo since 2015, which has coincided with at least two years of record global warmth. Figure 8.2 shows the planetary albedo variations since 2000, when there are good satellite observations. The 0.5 percent reduction in planetary albedo since 2015 corresponds to an increase of 1.7 W/m2 in absorbed solar radiation averaged over the planet (Hansen and Karecha, 2025). For comparison, Forster et al. (2024) estimate the current forcing from the increase in atmospheric CO2 compared to preindustrial times to be 2.33 W/m2.

Changes in surface characteristics cannot explain this decrease in planetary albedo since 2015:

• Arctic sea ice extent has declined by about 5 percent since 1980, although following 2007 there has been a pause in the Arctic sea ice decline (England et al., 2025)

• Regarding Antarctic sea ice, the IPCC AR6 concludes that “There has been no significant trend in Antarctic sea ice area from 1979 to 2020 due to regionally opposing trends and large internal variability.” (Summary for Policymakers, A.1.5)

• Northern hemispheric annual snow cover has been slowly declining since 1967, with barely
significant trends. The data show the Northern Hemisphere has snowier winters, accompanied by more rapid melt in spring and summer.

• Global greening (Chapter 2) is contributing to the decrease in planetary albedo, as forests have a lower albedo than open lands or snow. However, there is some evidence that forests increase cloud cover (high reflectivity), which counteracts the direct albedo decrease associated with increasing forested area.

Figure 8.2. Earth’s albedo (reflectivity, in percent), with seasonality removed. From Hansen and Karecha (2025)

In summary, the decline in planetary albedo and the concurrent decline in cloudiness have emphasized the importance of clouds and their variations to global climate variability and change. A change of 1- 2 percent in global cloud cover has a greater radiative impact on the climate than the direct radiative effect of doubling CO2. While it is difficult to untangle causes of the recent trend, the competing explanations for the cause of the declining cloud cover have substantial implications for assessing the Equilibrium Climate Sensitivity and for the attribution of the recent warming. An additional 10 years of data should help clarify
whether this is a strong positive cloud feedback associated with warming or a temporary fluctuation driven by natural variability.

Chapter 9 Climate Change and US Agriculture

There has been abundant evidence going back decades that rising CO2 levels benefit plants, including agricultural crops, and that CO2-induced warming will be a net benefit to U.S. agriculture. The increase in ambient CO2 has also boosted productivity of all major U.S. crop types. There is reason to conclude that on balance climate change has been and will continue to be neutral or beneficial for most U.S. agriculture.

A major deficiency of all these [econometric] studies is that they omit the role of CO2 fertilization. Climate change as it relates to this report is caused by GHG emissions, chiefly CO2. The econometric analyses referenced above focus only on temperature and precipitation changes and do not take account of the beneficial growth effect of the additional CO2 that drives them. As explained in Chapter 2, CO2 is a major driver of plant growth, so this omission biases the analysis towards underestimation of the benefits of climate change to agriculture.

A 2021 report from the U.S. National Bureau of Economic Research (Taylor and Schlenker 2021) used satellite-measured observations of outdoor CO2 levels across the United States, matched to county-level agricultural output data and other economic variables. After controlling for the effects of weather, pollution and technology the authors concluded that CO2 emissions had boosted U.S. crop production since 1940 by 50 to 80 percent, attributing much larger gains than had previously been estimated using FACE experiments. They found that every ppm of increase in CO2 concentration boosts corn yields by 0.5 percent, soybeans by 0.6 percent, and wheat by 0.8 percent.

Notwithstanding the abundant evidence for the direct benefits of CO2 and of CO2-induced warming on crop growth, in 2023 the U.S. Environmental Protection Agency (EPA 2023) boosted its estimate of the Social Cost of Carbon (SCC) about five-fold based largely on a very pessimistic 2017 estimate of global agricultural damages from climate warming (Moore et al., 2017). One of the two damage models used by the EPA attributed nearly half of the 2030 SCC to projected global agricultural damages based on the Moore et al. (2017) analysis. This study was a meta-analysis of crop model studies simulating yield changes for agricultural crops under various climate warming scenarios. Moore et al. projected declining global crop yields for all crop types in all regions due to warming.

In summary, there is abundant evidence going back decades that rising CO2 levels benefit plants,including agricultural crops, and that CO2-induced warming will be a net benefit to U.S. agriculture. To the extent nutrient dilution occurs there are mitigating strategies available that will need to be researched and adapted to local conditions.

Chapter 10 Managing Risks of Extreme Weather

Trends in losses from extreme weather and climate events are dominated by population increases and economic growth. Technological advances such as improved weather forecasting and early warning systems have substantially reduced losses from extreme weather events. Better building codes, flood defenses, and disaster response mechanisms have lowered economic losses relative to GDP. The U.S. economy’s expansion has diluted the relative impact of disaster costs, as seen in the comparison of historical and modern GDP percentages. Heat-related mortality risk has dropped substantially due to adaptive measures including the adoption of air conditioning, which relies on the availability of affordable energy. U.S. mortality risks even under extreme warming scenarios are not projected to
increase if people are able to undertake adaptive responses.

There is strong evidence that people adapt to weather risks. Lee and Dessler (2023) reported that 86 percent of temperature-related deaths across 40 cities in the U.S. were due to cold-related mortality, and that due to adaptation the relative risk of death declined in hot and cold cities alike as seasonal temperatures increased. Allen and Sheridan (2018) found that short, early-season cold events were 2 to 5 times deadlier than hot events, but the mortality risk of both cold and hot extremes drops to nearly zero if the events occur late in the season.

In the context of large declines in heat-related mortality, rising temperatures are associated with a net saving of lives since they reduce mortality from cold events. AR6 Working Group 2 Chapter 16.2.3.5 (O’Neill et al. 2022) acknowledges that heat-related mortality risk is declining over time:

Heat-attributable mortality fractions have declined over time in most countries owing to general improvements in health care systems, increasing prevalence of residential air conditioning, and behavioral changes. These factors, which determine the susceptibility of the population to heat, have predominated over the influence of temperature change.

Yet the IPCC misrepresents the overall situation in its AR6 Synthesis report. Section A.2.5 of that document states: “In all regions increases in extreme heat events have resulted in human mortality and morbidity (very high confidence).” But it is silent on the larger decline of deaths during extreme cold events.

Chapter 11 Climate Change, the Economy, and Social Cost of Carbon

Economists have long considered climate a relatively unimportant factor in economic growth, a view echoed by the IPCC itself in AR5. Mainstream climate economics has recognized that CO2-induced warming might have some negative economic effects, but they are too small to justify aggressive abatement policy and that trying to “stop” or cap global warming even at levels well above the Paris target would be worse than doing nothing. An influential study in 2012 suggested that global warming would harm growth in poor countries, but the finding has subsequently been found not to be robust. Studies that take full account of modeling uncertainties either find no evidence of a negative effect on global growth from CO2 emissions or find poor countries as likely to benefit as rich countries.

Figure 11.2: Decline in U.S. GDP per degree of warming. Source: CEA-OMB (2023)

Social Cost of Carbon (SCC) estimates are highly uncertain due to unknowns in future economic growth, socioeconomic pathways, discount rates, climate damages, and system responses. The SCC is not intrinsically informative as to the economic or societal impacts of climate change. It provides an index connecting large networks of assumptions about the climate and the economy to a dollar value. Some assumptions yield a high SCC and others yield a low or negative SCC (i.e. a social benefit of emissions). The evidence for or against the underlying assumptions needs to be established independently; the resulting SCC adds no additional information about the validity of those assumptions. Consideration of potential tipping points does not justify major revisions to SCC estimates.

Although the literature refers to “estimates” of the SCC, it is not estimated in the way other economic statistics are estimated. For instance, data on market transactions including prices and quantities can be used to estimate the current inflation rate or the growth rate of per capita real Gross Domestic Product, and there are well-understood uncertainties associated with these quantities. But there are no market data available to measure many, if not most, of the marginal damages or benefits believed to be associated with CO2 emissions, so these need to be imputed using economic models.

For example, an influential component of some SCC calculations is the perceived social cost associated with a changed risk of future mortality due to extreme weather. There is no market in which people can directly attach a price to that risk. At best economists can try to infer such values by looking at transactions in related markets such as real estate or insurance, but isolating the component of price changes attributable to atmospheric CO2 levels is very difficult.

It is increasingly being argued that the SCC is too variable to be useful for policymakers. Cambridge Econometrics (Thoung, 2017) stated it’s “time to kill it” due to uncertainties. The UK and EU no longer use SCC for policy appraisal, opting for “target-consistent” carbon pricing (UK Department for Energy Security and Net Zero 2022, Dunne 2017). However, the uncertainty of SCC estimates doesn’t mean that other regulatory instruments are inherently better or more efficient. Many emissions regulations (such as electric vehicle mandates, renewable energy mandates, energy efficiency regulations and bans on certain types of home appliances) cost far more per tonne of abatement than any mainstream SCC estimate, which
is sufficient to establish that they fail a cost-benefit test.

Chapter 12 Global Climate Impact of US Emissions Policies

U.S. policy actions are expected to have undetectably small direct impacts on the global climate and any effects will emerge only with long delays.

The emissions rates and atmospheric concentrations of criteria air contaminants are closely connected because their lifetimes are short and their concentrations are small; when local emissions are reduced the local pollution concentration drops rapidly, usually within a few days. But the global average CO2 concentration behaves very differently, since emissions mix globally and the global carbon cycle is vast and slow. Any change in local CO2 emissions today will have only a very small global effect, and only with a long delay.

Consequently, any reduction in U.S. emissions would only modestly slow, but not prevent, the rise of global CO2 concentration. And even if global emissions were to stop tomorrow, it would take decades or centuries to see a meaningful reduction in the global CO2concentration and hence human influences on the climate. The practice of referring to unilateral U.S. reductions as “combatting climate change” or “taking action on climate” on the assumption we can stop climate change therefore reflects a profound misunderstanding of the scale of the issue.

Concluding thoughts

This report supports a more nuanced and evidence-based approach for informing climate policy that explicitly acknowledges uncertainties. The risks and benefits of a climate changing under both natural and human influences must be weighed against the costs, efficacy, and collateral impacts of any “climate action”, considering the nation’s need for reliable and affordable energy with minimal local pollution. Beyond continuing precise, un-interrupted observations of the global climate system, it will be important to make realistic assumptions about future emissions, re-evaluate climate models to address biases and uncertainties, and clearly acknowledge the limitations of extreme event attribution studies. An approach that acknowledges both the potential risks and benefits of CO2, rather than relying on flawed models and extreme scenarios, is essential for informed and effective decision-making.

SH and Tropics Lead UAH Cooling June 2025

Posted on July 21 by Ron Clutz

For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa. While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 ppm, a 15% increase.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

gmt-warming-events

Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT

June 2025 SH and Tropics Lead UAH Temps Lower

UAH has updated their TLT (temperatures in lower troposphere) dataset for June 2025. Due to one satellite drifting more than can be corrected, the dataset has been recalibrated and retitled as version 6.1 Graphs here contain this updated 6.1 data. Posts on their reading of ocean air temps this month are behind the update from HadSST4. I posted recently on SSTs June 2025 Ocean SSTs: NH Warms, SH Cools.These posts have a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Sometimes air temps over land diverge from ocean air changes. In July 2024 all oceans were unchanged except for Tropical warming, while all land regions rose slightly. In August we saw a warming leap in SH land, slight Land cooling elsewhere, a dip in Tropical Ocean temp and slightly elsewhere. September showed a dramatic drop in SH land, overcome by a greater NH land increase. 2025 has shown a sharp contrast between land and sea, first with ocean air temps falling in January recovering in February. Then land air temps, especially NH, dropped in February and recovered in March. Now in June SH land dropped markedly and NH land down slightly, while ocean air temps rose slightly in NH, offset by cooling in SH and Tropics.

After a change in priorities, updates are now exclusive to HadSST4. For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6.1 which are now posted for June 2025. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the revised and current dataset.

After sharp cooling everywhere in January 2023, there was a remarkable spiking of Tropical ocean temps from -0.5C up to + 1.2C in January 2024. The rise was matched by other regions in 2024, such that the Global anomaly peaked at 0.86C in April. Since then all regions have cooled down sharply to a low of 0.27C in January. In February 2025, SH rose from 0.1C to 0.4C pulling the Global ocean air anomaly up to 0.47C, where it stayed in March and April. In May drops in NH and Tropics pulled the air temps over oceans down despite an uptick in SH. At 0.43C, ocean air temps were similar to May 2020, albeit with higher SH anomalies. Now in June Global ocean air anomaly is little changed despite a slight rise in NH.

Land Air Temperatures Tracking in Seesaw Pattern

Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land. The seesaw pattern in Land temps is similar to ocean temps 2021-22, except that SH is the outlier, hitting bottom in January 2023. Then exceptionally SH goes from -0.6C up to 1.4C in September 2023 and 1.8C in August 2024, with a large drop in between. In November, SH and the Tropics pulled the Global Land anomaly further down despite a bump in NH land temps. February showed a sharp drop in NH land air temps from 1.07C down to 0.56C, pulling the Global land anomaly downward from 0.9C to 0.6C. In March that drop reversed with both NH and Global land back to January values, holding there in April. In May sharp drops in NH and Tropics land air temps pulled the Global land air temps back down close to February value. In June the Global land air drop was significant, down from 0.67C to 0.55C despite a small rise in the Tropics.

The Bigger Picture UAH Global Since 1980

The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.

Note on Ocean Cooling Not Yet Fully Appearing in UAH Dataset

The above chart shows sea surface temperature anomalies (SSTA) in the North Atlantic 0 to 60N. The index is derived from ERSSTv.5 by subtracting the global anomalies from the North Atlantic anomalies, the differences as shown in the chart. The baseline of 0.0C is the average for the years 1951 to 1980. The mean anomaly since 1980 is in purple at 0.33C, and persisted throughout up to 2018. The orange line is the average anomaly in the the last six years, 2019 to 04/2025 inclusive, at 0.84C. The remarkable spikes in 2023 and 2024 drove that rise to exceed 1.4C, which has been cut in half over the last 10 months. As Dr. Humlum observed, such oceanic changes usually portend air temperature changes later on.

Climate Model Assumptions Contrary to Balloon Data

Posted on July 21 by Ron Clutz

Recently Michael Connolly presented the evidence contradicting assumptions built into GCMs (Global Climate Models). This post consists of the exhibits he used, and additional Connolly comments in italics from a similar talk this month to Doctors for Disaster Preparedness. (Video embedded later in post.)

Michael Connolly:

I’m an engineer and a scientist. As an engineer, I use computer models to design and make things. As a scientist, I look at the data to see if my computer models are correct. So, what we did at the center for environmental research and earth sciences (CERES) is that we looked at the data from 20 million radio balloons.

We then asked, can we look at this data and see how we can use it to check the computer models? And we found there’s two types of balloons. One: the average weather balloon does about a 100 measurements as it goes up to the stratosphere. But the ones which measure ozone do a measurement about once every second. So you have maybe four or 5,000 measurements on each sample. But all of the climate models, and by the way, nobody in the climate model community bothered to check the data to see if their models were correct, which I find very bizarre. But what all of the model community do is they divide the earth into a number of little boxes. So on a horizontal scale the boxes are about 1,000 mi long and on a vertical scale they’re about less than a mile in height.

They then make a number of assumptions about how the air behaves within each of these boxes. So their first assumption is that the air in each box is in a state which we call thermodynamic equilibrium. which I’ll explain in a few minutes. So they assume that on a horizontal scale the air in a box is in equilibrium over a distance of a 1,000 miles. But on a vertical scale only in equilibrium for slightly less than a mile.

And they also assume that the different boxes are not in thermodynamic equilibrium with each other. Because if it turns out that the boxes are in thermodynamic equilibrium with each other, all of the assumptions of the climate models collapse because Einstein and his co-authors over a 100 years ago showed that if a system was in thermodynamic equilibrium, if you put in a greenhouse gas into that system, it would absorb more energy. But if it’s in thermodynamic equilibrium, it emits more energy. So increasing the level of greenhouse gases will increase the rate of absorption but also increase the rate of emission. So there’s no net change due to the radiation. So if it turns out that the assumption that the the different boxes aren’t in thermodynamic equilibrium is false, then the whole theory of man-made global warming collapses.

So how do we know if something is in thermodynamic equilibrium or not? Well, what you do is you take a system and you do all the measurements of the different parameters involved and if you can describe the system in what’s called an equation of state with using these parameters, then we say the state is in thermodynamic equilibrium. So in other words, obeying an equation of state is one side of the coin of being in thermodynamic equilibrium. They’re both different sides of the same coin.

So for the air, the equation of state is this. It’s called the ideal gas law. And this is the equation that’s used by the climate modelers in treating the different boxes as being in thermodynamic equilibrium. You can see down there it tells you the relationship between the different parameters, but it doesn’t tell you how much energy it would take to change the temperature of a system. For that you need to know the heat capacity of the system. And it doesn’t tell you anything about potential energy. In other words, if I take a cubic meter of air and lift it up and keep it at the same temperature and pressure, it would obey the same equation, but it would have gravitational potential energy because it takes energy to lift it up. That’s not reflected in the equation of state.

As a chemist I thought there was something dead obvious to do. The equation of state can be rewritten in a different form called the molar density form, and this form has been used by chemists for hundreds of years to determine the molecular weight of new gases. So we asked what happens if we describe the atmosphere in terms of molar density form instead of the energy form? We were the first and still the only people to have done this.

When we did that we got a big surprise. We found that if you plot the molar density versus pressure you get these two straight lines. Now this means that the atmosphere in the troposphere, that’s the lower bit, is obeying an equation of state. So that means it’s in thermodynamic equilibrium. And when you get to the tropopause it turns into another straight line. Now this is quite common in studying materials. If you can describe it in terms of one equation of state and then it changes into another equation of state, we call it a change of phase. For example, you can describe water using the gaseous water using the gas laws, but then when it turns into liquid water, you have to use a different equation of state.

Now we studied all the different weather balloons from all around the world and we found that this phenomenon occurred in all of them. The only difference was that in the tropics the change of phase occurred at a higher altitude and in the Arctic and polar regions it occurred at a lower altitude. So, when we were here in Tucson 5 years ago, we made a video for the entire year of all of the radio balloon data for Tucson for 2018. And the reason for this video is that looking at a static graph like that, you don’t see any changes. Now, in the models that they’re using, the different boxes are isolated from each other, if you put energy into one of the boxes, it would kind of stay there. But if they’re in thermodynamic equilibrium, you put energy into one box, then all of the boxes will change because all of the energy will be distributed throughout the system. When you look at the video, the behavior of the boundary layer position moves up and down.

But also the temperature: if it moves to the right, the temperature is increasing. If it moves to the left, the temperature is decreasing. And what you will see once you watch the video, it’s all synchronized. In other words, if a change occurs, if the troposphere is warming up and the temperature is moving to the right, the tropopause moves down, the tropopause moves in the opposite direction. So in other words, when the troposphere heats up, the tropopause cools down. when the troposphere cools down the tropopause heats up and it does so in a synchronized way. So that synchronization shows that it’s thermodynamically connect connected. The idea that all of these boxes are not in thermodynamic equilibrium is contradicted by this data. [The referenced video starts at 10 minutes into the embedded presentation below.]

So that’s the first assumption. Now looking at the second assumption.
Back in the day, 18th century or something, Hadley was looking to explain the trade winds. So he came up with this idea of what happens: The very hot temperatures landing on the equator heated up the atmosphere. here and this hot air then rose up. Then as it rose up it started to move towards the poles and as it moved towards the poles it cooled down and you got this circular phenomenon. They came up with three different types of circular cells: the Hadley cells; the Ferrel cells and the Polar cells. But all of these this theoretical stuff was based on ground measurements.

And again uh nobody bothered to check whether this is true or not. So I’ll just show how we checked it. But first of all I just want to explain what’s meant by mass flux. So if you take a square meter and you measure the air flowing through it and what weight of air that is the mass flux. So in the weather balloons they give you the speed of the air and they give you the direction in which it’s it’s going. So you can use this to calculate the mass flux. So we said fine. So can we use this to check the idea of the Hadley cells and it turns out that you can. So we did and we published a paper two years ago.

We found first of all if you take a balloon and you launch it up through one of these cells then if Hadley is correct you would expect the hot air was rising here in the tropics and that drags in the air from the colder regions and then it hits the tropopause. Now, when Hadley came up with the idea, nobody knew the tropopause existed, and it’s only 30 years before I was born that it was actually discovered. So, that’s telling something about my age.

Anyway, if you send a balloon up through the atmosphere, you would expect the mass flux flow to flow in that direction down at the lower levels. And then as you go up at some stage it would shift over and start going in the opposite directions. So since that was available that mass flux we could measure from the balloon data we did that and we got a surprise.

There was absolutely no circulation patterns at all. Instead what the atmosphere was doing. So if we point here you can see these ones are the lower ones. So you have the direction the north south direction of the mass flux. These are the ones at the lower half of the troposphere. These are the ones in the opposite half of the troposphere.

For a Hadley cell you would expect these ones to be flowing in the opposite direction to these ones. But instead what we find is they all flow in the same direction. And in a very unusual pattern. What happens is here it’s flowing south then the atmosphere slows down over a couple of days goes back and forth and so on. So instead of this circular pattern what’s happening is the whole atmosphere is moving like a giant pendulum back and forth. So we have the atmosphere going one way, then after a few days it turns around and comes back in the opposite direction. And this is for Iceland but we found the exact same thing occurred for all the different stations.

So in that published paper we we took a station from each of the different five climate types and we found the exact same sort of thing happened. Now people said: okay so maybe it’s going back and forward on a daily basis but over a period of a year it might average out. So we average the data over the five years for each of the stations.

And since we published that paper, we’ve analyzed over 250 of the weather stations in the tropics. And we found for these 82% of them are Hadley. 73 in the northern hemisphere. So the majority are not Hadley cells. And in the southern hemisphere they’re equally balanced. But the problem with even the ones that were Hadley cells is you can see here the mass flux grow flowing in this direction the area under the curve is not the same as the one up above. And if it was a proper Hadley cell, they’d have to be the same. So what we found is for none of them this worked out. So they don’t exist, right?

June 2025 Ocean SSTs: NH Warms, SH Cools

Posted on July 17 by Ron Clutz

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

The ocean covers 71% of the globe and drives average temperatures;
SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
A major El Nino was the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated. HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3. The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4. More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for the current version HadSST4.1.1.0 is here. The charts and analysis below is produced from the current data.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through June 2025. A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016, followed by rising temperatures in 2023 and 2024 and cooling in 2025.

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes. That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period. A small warming was driven by NH summer peaks in 2021-22, but offset by cooling in SH and the tropics, By January 2023 the global anomaly was again below the mean.

Then in 2023-24 came an event resembling 2015-16 with a Tropical spike and two NH spikes alongside, all higher than 2015-16. There was also a coinciding rise in SH, and the Global anomaly was pulled up to 1.1°C last year, ~0.3° higher than the 2015 peak. Then NH started down autumn 2023, followed by Tropics and SH descending 2024 to the present. After 12 months of cooling in SH and the Tropics, the Global anomaly came back down, led by NH cooling the last 8 months from its 1.3C peak in August, down to 0.8C in March and April. Remarkably, April 2025 SST anomalies in all regions and globally are the coolest since March 2023. May showed little change in the Global anomaly, while in June declines in SH along with the Tropics mostly offset an upward bump in NH.

Comment:

The climatists have seized on this unusual warming as proof their Zero Carbon agenda is needed, without addressing how impossible it would be for CO2 warming the air to raise ocean temperatures. It is the ocean that warms the air, not the other way around. Recently Steven Koonin had this to say about the phonomenon confirmed in the graph above:

El Nino is a phenomenon in the climate system that happens once every four or five years. Heat builds up in the equatorial Pacific to the west of Indonesia and so on. Then when enough of it builds up it surges across the Pacific and changes the currents and the winds. As it surges toward South America it was discovered and named in the 19th century It iswell understood at this point that the phenomenon has nothing to do with CO2.

Now people talk about changes in that phenomena as a result of CO2 but it’s there in the climate system already and when it happens it influences weather all over the world. We feel it when it gets rainier in Southern California for example. So for the last 3 years we have been in the opposite of an El Nino, a La Nina, part of the reason people think the West Coast has been in drought.

It has now shifted in the last months to an El Nino condition that warms the globe and is thought to contribute to this Spike we have seen. But there are other contributions as well. One of the most surprising ones is that back in January of 2022 an enormous underwater volcano went off in Tonga and it put up a lot of water vapor into the upper atmosphere. It increased the upper atmosphere of water vapor by about 10 percent, and that’s a warming effect, and it may be that is contributing to why the spike is so high.

A longer view of SSTs

To enlarge, open image in new tab.

The graph above is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations. Previous posts focused on the rise and fall of the last El Nino starting in 2015. This post adds a longer view, encompassing the significant 1998 El Nino and since. The color schemes are retained for Global, Tropics, NH and SH anomalies. Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July. 1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino.

The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2.

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8, a lower peak warming in 2009-10, following by cooling in 2011-12. Again SSTs are average 2013-14.

Now a different pattern appears. The Tropics cooled sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off. But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average. In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16. NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.) Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021. In 2021-22 there were again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, then in October to January 2023 by deeper cooling in NH and Tropics.

Then in 2023 the Tropics flipped from below to well above average, while NH produced a summer peak extending into September higher than any previous year. Despite El Nino driving the Tropics January 2024 anomaly higher than 1998 and 2016 peaks, following months cooled in all regions, and the Tropics continued cooling in April, May and June along with SH dropping. After July and August NH warming again pulled the global anomaly higher, September through January 2025 resumed cooling in all regions, continuing February through April 2025, with little change in May and June despite upward bumps in NH.

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH. The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before. After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

Contemporary AMO Observations

Through January 2023 I depended on the Kaplan AMO Index (not smoothed, not detrended) for N. Atlantic observations. But it is no longer being updated, and NOAA says they don’t know its future. So I find that ERSSTv5 AMO dataset has current data. It differs from Kaplan, which reported average absolute temps measured in N. Atlantic. “ERSST5 AMO follows Trenberth and Shea (2006) proposal to use the NA region EQ-60°N, 0°-80°W and subtract the global rise of SST 60°S-60°N to obtain a measure of the internal variability, arguing that the effect of external forcing on the North Atlantic should be similar to the effect on the other oceans.” So the values represent SST anomaly differences between the N. Atlantic and the Global ocean.

The chart above confirms what Kaplan also showed. As August is the hottest month for the N. Atlantic, its variability, high and low, drives the annual results for this basin. Note also the peaks in 2010, lows after 2014, and a rise in 2021. Then in 2023 the peak was holding at 1.4C before declining. An annual chart below is informative:

Note the difference between blue/green years, beige/brown, and purple/red years. 2010, 2021, 2022 all peaked strongly in August or September. 1998 and 2007 were mildly warm. 2016 and 2018 were matching or cooler than the global average. 2023 started out slightly warm, then rose steadily to an extraordinary peak in July. August to October were only slightly lower, but by December cooled by ~0.4C.

Then in 2024 the AMO anomaly started higher than any previous year, then leveled off for two months declining slightly into April. Remarkably, May showed an upward leap putting this on a higher track than 2023, and rising slightly higher in June. In July, August and September 2024 the anomaly declined, and despite a small rise in October, ended close to where it began. Note 2025 started much lower than the previous year and is headed sharply downward, well below the previous two years, now in May and June aligning with 2010.

The pattern suggests the ocean may be demonstrating a stairstep pattern like that we have also seen in HadCRUT4.

The purple line is the average anomaly 1980-1996 inclusive, value 0.17. The orange line the average 1980-2024, value 0.4, also for the period 1997-2012. The red line is 2013-2024, value 0.67. As noted above, these rising stages are driven by the combined warming in the Tropics and NH, including both Pacific and Atlantic basins.

Curiosity: Solar Coincidence?

The news about our current solar cycle 25 is that the solar activity is hitting peak numbers now and higher than expected 1-2 years in the future. As livescience put it: Solar maximum could hit us harder and sooner than we thought. How dangerous will the sun’s chaotic peak be? Some charts from spaceweatherlive look familar to these sea surface temperature charts.

Summary

The oceans are driving the warming this century. SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.” The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect. The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? And is the sun adding forcing to this process?

Footnote: Why Rely on HadSST4

HadSST is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST4 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

2025 Update: No, CO2 Doesn’t Drive the Polar Vortex

Posted on July 2 by Ron Clutz

July 2025 Update

Linnea Lueken published this week at Climate Realism Thanks, NewScientist, for Admitting Climate Change Isn’t Making the Jet Stream More Erratic. Excerpts in italics with my bolds and added images.

NewScientist, a publication dedicated to popularizing science, recently published a post titled “Extreme winter weather isn’t down to a wavier jet stream,” reporting on a new study that shows, the jet stream is not getting wavier in winter months due to climate change. NewScientist writes that “[i]ncreasingly erratic winter weather in the northern hemisphere isn’t a result of the polar jet stream getting more wavy, according to new research . . ..”

This is true, and it has been evident for some time, but runs counter
to assertions commonly made by climate alarmists.

Although the vast bulk of the article is devoted to insisting that climate change is causing worsening winter and summer weather, claims regularly debunked at Climate Realism, the publication deserves some credit for reporting the study’s results concerning the jet stream, which was, in fact, the focus of the research itself.

The new reports findings are not actually that “new,” in the sense that Climate Realism has reported on research that came to the same conclusion several times in the past few years, here, here, and here, for instance. There is copious evidence showing that not only are cold snaps not uncommon, but that the jet stream’s (and more specifically, polar vortex) influence on extreme winter weather has been acknowledged since at least 1853. Years of studies looking at the frequency of and intensity of polar vortex events have found no consistent trends. As pointed out by my colleague Anthony Watts in this post on the subject:

“a 2021 study in the journal Geophysical Research Letters found no statistically significant increase in jet stream waviness or meandering in recent decades,”

and he explains there has never been a consensus among scientists when it comes to the issue of polar vortex/jet stream behavior.

The post at NewScientist goes on to explain the new study, saying “recent erratic behaviour isn’t out of the ordinary,” and that the jet stream has been both wavier and less wavy than it is today. Unfortunately, that is where the NewScientist and the authors of the paper it was discussing ceased to follow the evidence. One of the study’s authors reassured NewScientist that climate change is still “affecting extreme weather events in all sorts of really important ways,” and that the jet stream is actually becoming wavier in the summertime, “where it is getting slower, with bigger waves, which leads to things like big heatwaves, drought, and wildfires.”

This would be compelling if existing data backed up the claim,
but, in fact, big heatwaves, drought, and wildfires have not
become more frequent or severe in recent decades.

Heatwaves were much more severe in the earlier decades of the 20^th century, and overall drought has been declining while precipitation increases. Now that it is summer, many outlets are attempting to claim that hot weather is driven by climate change. In doing so they almost always ignore where heat records are being set, as it is often at airports and other heat-absorbing locations, and ignore historical records that show hot summers are not unprecedented.

Similarly, data shows that wildfires were worse in the past with research from NASA and the European Space Agency showing that acreage lost to wildfires has declined markedly over the past few decades.

The NewScientist, and the AGU study it references, should have quit when they were ahead. They should have published their unalarming findings about climate change’s lack of an impact on the winter jet stream without then assuring people that despite their study’s findings, they really are true believers and climate change is making weather worse. The latter point is refuted by real world data.

Simulation of jet stream pattern July 22. (VentuSky.com)

Background from Previous Post

We are heading into winter this year at the bottom of a solar cycle, and ocean oscillations due for cooling phases. The folks at Climate Alarm Central (CAC) are well aware of this, and are working hard so people won’t realize that global cooling contradicts global warming. No indeed, contortionist papers and headlines are warning us all that CO2 not only causes hothouse earth, overrun with rats and other vermin. CO2 also causes ice ages when it feels like it.

Update Nov. 26, 2019: Much ado about the polar jet stream recently with a publication by Tim Woolings A battle for the jet stream is raging above our heads. The Claims are not new:

The jet has always varied – and has always affected our weather patterns. But now climate change is affecting our weather too. As I explore in my latest book, it’s when the wanderings of the jet and the hand of climate change add up that we get record-breaking heatwaves, floods and droughts – but not freezes.

The same supposition was made last year in an article by alarmist Jason Samenow at Washington Post. Study: Freak summer weather and wild jet-stream patterns are on the rise because of global warming. Excerpts in italics with my bolds

In many ways, the summer of 2018 marked a turning point, when the effects of climate change — perhaps previously on the periphery of public consciousness — suddenly took center stage. Record high temperatures spread all over the Northern Hemisphere. Wildfires raged out of control. And devastating floods were frequent.

Michael Mann, climate scientist at Pennsylvania State University, along with colleagues, has published a new study that connects these disruptive weather extremes with a fundamental change in how the jet stream is behaving during the summer. Linked to the warming climate, the study suggests this change in the atmosphere’s steering current is making these extremes occur more frequently, with greater intensity, and for longer periods of time.

The study projects this erratic jet-stream behavior will increase in the future, leading to more severe heat waves, droughts, fires and floods.

The jet stream is changing not only because the planet is warming up but also because the Arctic is warming faster than the mid-latitudes, the study says. The jet stream is driven by temperature contrasts, and these contrasts are shrinking. The result is a slower jet stream with more wavy peaks and troughs that Mann and his study co-authors ascribe to a process known as “quasi-resonant amplification.”

The altered jet-stream behavior is important because when it takes deep excursions to the south in the summer, it sets up a collision between cool air from the north and the summer’s torrid heat, often spurring excessive rain. But when the jet stream retreats to the north, bulging heat domes form underneath it, leading to record heat and dry spells.

The study, published Wednesday in Science Advances, finds that these quasi-resonant amplification events — in which the jet stream exhibits this extreme behavior during the summer — are predicted to increase by 50 percent this century if emissions of carbon dioxide and other greenhouse gases continue unchecked.

Whereas previous work conducted by Mann and others had identified a signal for an increase in these events, this study for the first time examined how they may change in the future using climate model simulations.

“Looking at a large number of different computer models, we found interesting differences,” said Stefan Rahmstorf from the Potsdam Institute for Climate Impact Research and a co-author of the study, in a news release. “Distinct climate models provide quite diverging forecasts for future climate resonance events. However, on average they show a clear increase in such events.”

Although model projections suggest these extreme jet-stream patterns will increase as the climate warms, the study concluded that their increase can be slowed if greenhouse gas emissions are reduced along with particulate pollution in developing countries. “[T]he future is still very much in our hands when it comes to dangerous and damaging summer weather extremes,” Mann said. “It’s simply a matter of our willpower to transition quickly from fossil fuels to renewable energy.”

Mann has been leading the charge to blame anticipated cooling on fossil fuels, his previous attempt claiming CO2 is causing a slowdown of AMOC (part of it being the Gulf Stream), resulting in global cooling, even an ice age. The same idea underlay the scary 2004 movie Day After Tomorrow.

day-after-tomorrow Other scientists are more interested in the truth than in hype. An example is this AGU publication by D.A Smeed et al. The North Atlantic Ocean Is in a State of Reduced Overturning Excerpts in italics with my bolds.

Figure 3

Indices of subsurface temperature, sea surface height (SSH), latent heat flux (LHF), and sea surface temperature (SST). SST (purple) is plotted using the same scale as subsurface temperature (blue) in the upper panel. The upper panel shows 24 month filtered values of de‐seasonalized anomalies along with the non‐Ekman part of the AMOC. In the lower panel, we show three‐year running means of the indices going back to 1985 (1993 for the SSH index).

Changes in ocean heat transport and SST are expected to modify the net air‐sea heat flux. The changes in the total air‐sea flux (Figure S4, data obtained from the National Centers for Environmental Prediction‐National Center for Atmospheric Research reanalysis; Kalnay et al., 1996) are almost all due to the change in LHF. The third panel of Figure 3 shows the changes in LHF between the two periods. There is a strong signal with increased heat loss from the ocean over the Gulf Stream. That the area of increased heat loss coincides with the location of warming SST indicates that the changes in air‐sea fluxes are driven by the ocean.

Whilst the AMOC has only been continuously measured since 2004, the indices of SSH, heat content, SST, and LHF can be calculated farther back in time (Figure 3, bottom). Over this longer time period, all four indices are strongly correlated with one another (Table S5; correlations were calculated using the nonparametric method described in McCarthy et al., 2015). These data suggest that measurement of the AMOC at 26°N started close to a maximum in the overturning. Prior to 2007 the indices show variability on a time scale of 8 to 10 years and no trend is evident, but since 2014 all indices have had values lower than any other year since 1985.

Previous studies have shown that seasonal and interannual changes in the subtropical AMOC are forced primarily by changing wind stress mediated by Rossby waves (Zhao & Johns, 2014a, 2014b). There is growing evidence (Delworth et al., 2016; Jackson et al., 2016) that the longer‐term changes of the AMOC over the last decade are also associated with thermohaline forcing and that the changed circulation alters the pattern of ocean‐atmosphere heat exchange (Gulev et al., 2013). The role of ocean circulation in decadal climate variability has been challenged in recent years with authors suggesting that external, atmospheric‐driven changes could produce the observed variability in Atlantic SSTs (Clement et al., 2015). However, the direct observation of a weakened AMOC supports a role for ocean circulation in decadal Atlantic climate variability.

Our results show that the previously reported decline of the AMOC (Smeed et al., 2014) has been arrested, but the length of the observational record of the AMOC is still short relative to the time scales of important decadal variations that exist in the Atlantic. Understanding is therefore constantly evolving. What we identify as a changed state of the AMOC in this study may well prove to be part of a decadal oscillation superposed on a multidecadal cycle. Overlaying these oscillations is the impact of anthropogenic change that is predicted to weaken the AMOC over the next century. The continuation of measurements from the RAPID 26°N array and similar observations elsewhere in the Atlantic (Lozier et al., 2017; Meinen et al., 2013) will enable us to unravel and reveal the role of ocean circulation in the changing Atlantic climate in the coming decades.

Regarding the more recent attempt to link CO2 with jet stream meanderings, we have this paper providing a more reasonable assessment. Arctic amplification: does it impact the polar jet stream? by Valentin P. Meleshko et al. Excerpts below in italics with my bolds.

Analysis of observation and model simulations has revealed that northward temperature gradient decreases and jet flow weakens in the polar troposphere due to global climate warming. These interdependent phenomena are regarded as robust features of the climate system. An increase of planetary wave oscillation that is attributed to Arctic amplification (Francis and Vavrus, 2012; Francis and Vavrus, 2015) has not been confirmed from analysis of observation (Barnes, 2013; Screen and Simmonds, 2013) or in our analysis of model simulations of projected climate. However, we found that GPH variability associated with planetary wave oscillation increases in the background of weakening of zonal flow during the sea-ice-free summer. Enhancement of northward heat transport in the troposphere was shown to be the main factor responsible for decrease of northward temperature gradient and weakening of the jet stream in autumn and winter. Arctic amplification provides only minor contribution to the evolution of zonal flow and planetary wave oscillation.

It has been shown that northward heat transport is the major factor in decreasing the northward temperature gradient in the polar atmosphere and increasing the planetary-scale wave oscillation in the troposphere of the mid-latitudes. Arctic amplification does not show any essential impact on planetary-scale oscillation in the mid and upper troposphere, although it does cause a decrease of northward heat transport in the lower troposphere. These results confound the interpretation of the short observational record that has suggested a causal link between recent Arctic melting and extreme weather in the mid-latitudes.

There are two additional explanations of factors causing the wavy jet stream, AKA Polar Vortex. Dr Judah Cohen of AER has written extensively on the link between Autumn Siberian snow cover and the Arctic oscillation. See Snowing and Freezing in the Arctic for a more complete description of the mechanism.

Finally, a discussion with Piers Corbyn regarding the solar flux effect upon the jet stream at Is This Cold the New Normal?

Video transcript available at linked post.

The Real Climate Science Crisis: CAGW Hypothesis Lacks Scientific Evidence

Posted on June 28 by Ron Clutz

From C3 headlines The Real Climate Science Crisis: The Catastrophic Anthropogenic Global Warming (CAGW) Hypothesis Is Without Scientific Evidence. Excerpts in italics with my added images.

For a hypothesis to reach the status of being a legit theory, it requires withstanding the onslaught of observed empirical evidence. The CAGW hypothesis is no such animal.

Known by its more contemporary aliases, such as ”climate crisis,” “climate emergency,” “climate collapse,” or “existential threat,” the CAGW has zero empirical evidence to support it.

Unlike the related hypothesis regarding greenhouse gases (GHG) and global warming, at least the GHG hypothesis has warming global temperature data that somewhat coincides with increasing atmospheric CO2 levels, putting aside the growing possibility that the purported cause-and-effect direction is probably the reverse.

In order to reach a CAGW climate disaster, global warming
temperatures must change rapidly in an accelerating manner
that will initiate a ‘tipping point’ for the climate.

The rapid acceleration would present its occurrence in a continuous increasing of the slope, i.e., trend, of temperatures, such as monthly temperatures. Each subsequent month would represent a greater temperature magnitude increase than the month before, hypothetically.

But those tipping point precursors are not occurring in the real-world climate.

For example, it is agreed by all climate scientists that oceans play a very major role in the world’s climate and its global temperatures due to their being both the world’s largest carbon sink and its largest heat content storage.

However, despite these characteristics, in totality, the global oceans HAVE NOT warmed since the year 2014. And certainly, there is no empirical evidence that oceans exhibit constant temperature increases of magnitude.

Quite the contrary, combined oceans exhibit a regular pattern of temperature decreases and increases, as the adjacent plot of NOAA’s monthly ocean data indicates.

Specifically, this is a plot (dark blue) of moving 5-year temperature changes ending each month of the 60-year period from March 1963 through March 2023.

[Explanation: the first data point is the temperature change for the 60 months ending on March 30, 1963; and the chart’s last temperature change data point is for the five 5 years (i.e. 60 months) ending on March 2023.]

The chart also includes a plot (green) of the moving 60-month CO2 level changes over the same sixty year period, plus a linear trend for both CO2 changes and ocean temperature changes.

The trend of the 60-month CO2 changes significantly exceeds the slight positive trend of ocean temperature changes by a factor of 117x. This huge differential undercuts the belief that global warming is primarily the result of GHGs. Which is confirmed by the paltry R^2 of +0.06 – an almost non-existent relationship between 5-year atmospheric CO2 changes and 5-year changes in ocean temperature.

Not only are the large increases in CO2 levels not causing a concerning uptick of temperature change magnitude, it also has not lead to any type of acceleration, per the linear trend since 1963.

Specifically, with a trend of a tiny +0.0001°C, that would project out 20 years to be an increase of 5-year temperature changes to an insignificant amount of +0.024°C – definitely not an existential threat of ‘runaway warming’ or a CAGW ‘climate crisis’ as portrayed by bureaucrats, politicians and Hollywood celebrities.

So, if 5 years of increasing amounts of CO2 in the atmosphere barely influence 5-year changes in temperature over a 60-year span, either in magnitude or acceleration rate, then it is highly unlikely that this trace gas would cause a catastrophic climate disaster or an extinction event.

Thus, it is fair to state that for all those scientists pushing a narrative of an imminent climate change catastrophe from CO2 without the requisite empirical evidence, this has become the real climate science crisis facing society.

Scafetta: Climate Models Have Issues

Posted on June 25 by Ron Clutz

On June 18, 2025 Nicola Scafetta published Detection, attribution, and modeling of climate change: key open issues. Excerpts in italics with my bolds and added images.

Abstract

The Coupled Model Intercomparison Project (CMIP) global climate models (GCMs) assess that nearly 100% of global surface warming observed between 1850–1900 and 2011–2020 is attributable to anthropogenic drivers like greenhouse gas emissions. These models also generate future climate projections based on shared socioeconomic pathways (SSPs), aiding in risk assessment and the development of costly “Net-Zero” climate mitigation strategies.

Figure 1. Anthropgenic and natural contributions. (a) Locked scaling factors, weak Pre Industrial Climate Anomalies (PCA). (b) Free scaling, strong PCA Source: Larminat, P. de (2023)

Yet, as this study discusses, the CMIP GCMs face significant scientific challenges in attributing and modeling climate change, particularly in capturing natural climate variability over multiple timescales throughout the Holocene. Other key concerns include the reliability of global surface temperature records, the accuracy of solar irradiance models, and the robustness of climate sensitivity estimates. Global warming estimates may be overstated due to uncorrected non-climatic biases, and the GCMs may significantly underestimate solar and astronomical influences on climate variations.

The equilibrium climate sensitivity (ECS) to radiative forcing could be lower than commonly assumed; empirical findings suggest ECS values lower than 3°C and possibly even closer to 1.1 ± 0.4 °C. Empirical models incorporating natural variability suggest that the 21st-century global warming may remain moderate, even under SSP scenarios that do not necessitate Net-Zero emission policies.

These findings raise important questions regarding the necessity and urgency of implementing aggressive climate mitigation strategies. While GCMs remain essential tools for climate research and policymaking, their scientific limitations underscore the need for more refined modeling approaches to ensure accurate future climate assessments. Addressing uncertainties related to climate change detection, natural variability, solar influences, and climate sensitivity to radiative forcing will enhance predictions and better inform sustainable climate strategies.

Discussion

Scientific challenges in climate detection, attribution, and modeling stem from three primary issues:

1. the inherent uncertainty of what measurements really indicate complicates the detection of climate change and its causative factors;
2. the anthropogenic contribution is superimposed to natural climate variability, necessitating comprehensive understanding and accurate modeling of the latter;
3. key physical processes, such as cloud formation and solar contributions to climate dynamics, remain poorly characterized.

Figure 1:

(A) Compilation of the radiative forcing functions utilized in the CMIP5 GCMs (adapted from IPCC,2013, Figure 8.18).
(B) Variations in observed global surface temperature (black) alongside the CMIP3 and CMIP5 model simulations incorporating only natural forcing and combined natural-anthropogenic forcing (adapted from IPCC, 2013, FAQ 10.1, Figure 1).
(C) Compilation of the radiative forcing functions utilized in the CMIP6 GCMs (adapted from IPCC, 2021, Figure 2.10).
(D) Observed global surface temperature variations (black) alongside the CMIP6 model simulations incorporating only natural forcing and combined naturalanthropogenic forcing (adapted from IPCC, 2021, Figure SPM.1).

Notably, in both (B) and (D), the observational data necessary
to validate the GCM predictions that consider only natural forcings
are not reported because they do not exist.

While all available GCMs indicate that the positive feedbacks surpass the negative ones thus amplifying the effects of radiative forcing, large uncertainties associated with crucial feedback mechanisms — particularly those related to water vapor and cloud formation — remain substantial.

Feedback mechanisms include:

• Water Vapor Feedback — A positive feedback governed by the Clausius-Clapeyron law, which links ocean vaporation rates to temperature increases;
• Albedo Feedback — A positive feedback arising from changes in surface reflectivity due to ice and snow
cover variations;
• Cloud Feedback — Particularly challenging to quantify, as cloud formation, type, and distribution are sensitive to warming; certain clouds cool the surface by reflecting solar radiation, while others trap emitted
heat, making their net contribution highly uncertain;
• Lapse Rate Feedback — A negative feedback involving modifications to atmospheric temperature vertical
gradients;
• Carbon Cycle Feedback — Activated by warming-induced CO2 release from soils and oceans (per Henry’s law), further increasing atmospheric CO2 concentrations;
• Vegetation Feedback — Temperature and precipitation changes alter vegetation cover, which influences
carbon storage and surface albedo.

The CMIP6 GCMs are also employed to simulate future climate scenarios based on hypothetical radiative forcing functions derived from Shared Socioeconomic Pathways (SSPs). The ones mainly adopted in the IPCC AR6 are:
• SSP1-2.6 — low greenhouse gas emissions, with robust adaptation and mitigation measures leading to
Net-Zero CO2 emissions between 2050–2075;
• SSP2-4.5 — intermediate emissions, where CO2 levels remain near current levels until 2050 and subsequently decline without achieving Net-Zero by 2100;
• SSP3-7.0 — high emissions, with CO2 concentrations doubling by 2100 under minimal policyintervention;
• SSP5-8.5 — very high emissions, with CO2 levels tripling by 2075 under a worst-case scenario devoid of
mitigation measures.

Figure 3: CMIP6 GCM ensemble mean simulations spanning from 1850 to 2100, employing historical effective radiative forcing functions from 1850 to 2014 (see Figure 1C) and the forcing functions based on the SSP scenarios 1-2.6, 2-4.5, 3-7.0, and 5-8.5. Curve colors are scaled according to the equilibrium climate sensitivity (ECS) of the models. The right panels depict the risks and impacts of climate change in relation to various global Reasons for Concern (RFCs) (IPCC, 2023). (Adapted from Scafetta, 2024).

Conclusion

Over the span of approximately three decades, from the publication of the First Assessment Report (FAR, IPCC, 1990) to the Sixth Assessment Report (AR6, IPCC, 2021), the Intergovernmental Panel on Climate Change (IPCC) has significantly ~~advanced~~ marked up its understanding of the role of anthropogenic emissions in driving global warming.

In the 1990s the IPCC posited that both natural mechanisms and human activities could have contributed roughly equally (∼50% each) to the observed warming of the 20th century. However, since the years 2000s the prevailing scientific opinion has shifted, and the IPCC (AR6, 2021) now asserts that human activities are almost exclusively responsible (∼100%) for the global warming and climate change observed from 1850–1900 to 2011–2020.

The most recent assessment reports IPCC (2021, 2023) underscore this conclusion with striking clarity. As shown in Figure 2, the average contribution of natural factors — solar and volcanic forcing and internal natural variability — to global warming during the aforementioned period is estimated to be approximately 0°C. Consequently, from the CMIP GCM perspective, concerns about future climate warming due to additional anthropogenic greenhouse gas (GHG) emissions are well-founded. However, this conclusion depends on the reliability of global surface temperature records and the robustness of the physical science underpinning global climate models (GCMs).

The findings outlined above underscore significant uncertainties in climate modeling, climate data, solar records, and solar-climate interactions, leaving unresolved the key question of whether observed warming is primarily driven by anthropogenic factors, natural processes, or their interplay. Empirical methodologies, such as those utilized by Scafetta (2023a, 2024) and Connolly et al. (2023), highlight this ongoing ambiguity.

Concerns are mounting regarding the limitations of the CMIP GCMs employed by the IPCC in its assessment reports from 2007, 2013, and 2021. These models appear unable to accurately replicate natural climate variability across different timescales, highlighting critical unresolved issues in fundamental climate dynamics.Also the magnitude of solar variability across temporal scales requires further investigation, particularly given the strong correlations identified between solar proxy records and climate patterns throughout the Holocene. Schmutz (2021) argued that such strong correlations challenge the validity of the low-variability TSI models, such as those proposed by Matthes et al. (2017), Kopp et al., 2016 and Wu et al. (2018). Since these models serve as solar forcing inputs for the CMIP6 GCMs, their choice needs to be reconsidered.

Climate science remains far from settled, yet trillions of dollars continue to be allocated toward policies aimed at mitigating extreme hypothetical warming scenarios based on potentially flawed GCM outputs. Historically, atmospheric CO2 levels have been 10 to 20 times higher than current concentrations during approximately 95% of Earth’s history since complex life emerged 600 million years ago (Davis, 2017). Notably, CO2 concentrations often lag temperature changes across different timescales, suggesting temperature fluctuations may drive CO2 variations rather than vice versa (Shakun et al., 2012; Koutsoyiannis, 2024).

Advancing climate science requires directly confronting uncertainties in detection, attribution, and modeling. Further research on unresolved issues is critical for improving climate risk assessment and developing more effective strategies for addressing future environmental challenges.

It’s Summertime, Hottest Year Claims Ensue

Posted on June 21 by Ron Clutz

Matthew Wielicki explains the scientific malpractice in his Financial Post article Junk Science Week: The hottest year ever?. Excerpts in italics wtih my bolds and added images

Advocates and the media claim 2024 was the hottest year ever.
Archeological data suggest it wasn’t,
while modern data suffer from biases

An image produced by NASA and used when it declared 2024 as the warmest year on record. Photo by NASA

In 2024, mainstream media and political leaders aggressively promoted the alarming narrative that Earth had just experienced its hottest year ever recorded. National Geographic dramatically proclaimed, “2024 was the hottest year ever … and the coldest year of the rest of your life,” while the Vancouver Sun declared unequivocally, “Scientists confirm 2024 was Canada’s and world’s hottest year on record.” Canadian political figures reinforced this narrative, with prime minister Justin Trudeau characterizing the year’s warmth as an urgent call for immediate climate action.

I’m an earth science professor-in-exile. Claims such as these
immediately provoke critical skepticism.

This persistent narrative, relentlessly advanced by a powerful climate-industrial complex comprising governments, activist organizations and the media, is designed not merely to inform, but to generate a state of perpetual urgency. As global greenhouse gas (GHG) emissions continue to rise despite decades of climate policy interventions, the need to claim climate conditions are increasingly severe becomes a strategic imperative, regardless of scientific accuracy or historical context. This approach not only distorts genuine scientific inquiry but fosters anxiety and despair, particularly affecting young people already inundated with predictions of catastrophe.

The answers to four fundamental questions expose the weaknesses and biases inherent in the mainstream climate narrative:

1. Can we accurately measure historical global temperatures?

Claims about unprecedented global heat depend heavily on comparing modern temperature records, which are gathered by instrument and capture annual or monthly fluctuations, to historical temperature estimates derived from proxy data such as ice cores, tree rings, sediment layers and coral reefs. But proxy data inherently smooths out short-term fluctuations, providing generalized temperature estimates spanning centuries or millennia. This mismatch between high-resolution modern data and low-resolution historical proxies inevitably exaggerates the perceived severity of contemporary warming.

For example, widely cited reconstructions and favourites of The Intergovernmental Panel on Climate Change (IPCC) explicitly acknowledge their inability to capture temperature variability occurring over periods shorter than 300 years. The rapid temperature changes of recent decades appear unprecedented when put side by side with these smoothed historical averages. This methodological flaw significantly undermines the credibility of claims asserting that current global temperatures are historically unique or alarming.

2. Was 2024 really unprecedentedly warm?

Extensive historical and geological evidence demonstrates significant natural warming vastly exceeding modern temperatures. The Holocene Thermal Maximum (five to nine thousand years ago) saw temperatures significantly warmer than today, including in Canada. Archeological evidence, such as ancient forests revealed by retreating glaciers in the Rockies, conclusively supports periods of substantial natural warmth.

During the Eemian interglacial period (115-130 thousand years ago), Greenland experienced temperatures three to five degrees C warmer than now, despite substantially lower CO₂ concentrations in the atmosphere. These scientifically documented periods confirm that Earth’s climate naturally experiences considerable variability, rendering claims of unprecedented modern warmth scientifically untenable and historically uninformed.

3. Are we measuring the effects of CO₂ or urban heat islands

Most modern temperature records fuelling alarmist headlines originate from urban areas influenced by the Urban Heat Island Effect (UHIE). UHIE results from urban infrastructure, such as concrete, asphalt and buildings, retaining and radiating heat, significantly increasing local temperatures independent of broader climate trends. Toronto’s significant infrastructure growth has noticeably raised local temperatures, heavily skewing data. Similarly, Las Vegas’ highest recorded temperatures coincided with significant expansion around Harry Reid International Airport, illustrating the dominant role of urbanization rather than atmospheric CO₂ emissions.

Recent research indicates that up to 65 per cent of urban warming is from local urbanization rather than global greenhouse gas increases. Attributing urban heat predominantly to CO₂ emissions significantly misrepresents the true dynamics of local temperature increases.

4. Do rising CO2 levels really heat the oceans?

Recent alarmist coverage in outlets like the Financial Times highlights near-record ocean temperatures, linking them directly to rising CO₂ levels. The EU’s Copernicus programme noted that May 2025 ocean temperatures were the second highest ever recorded, with scientists raising concerns about the oceans’ diminishing capacity to absorb CO₂ and excess heat.

But this narrative critically overlooks fundamental scientific facts. Oceans possess a heat capacity orders of magnitude greater than the atmosphere. The notion that atmospheric CO₂ significantly heats ocean water directly is scientifically unfounded, as infrared radiation from CO₂ penetrates mere millimetres into the ocean’s surface, not nearly deep enough to meaningfully alter ocean temperature. Ocean temperature fluctuations are primarily driven by natural phenomena such as El Niño.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

Moreover, historical data on ocean temperatures is highly uncertain, relying predominantly on sparse measurements and indirect proxies. Claiming near-record ocean temperatures without acknowledging these substantial uncertainties misleads the public about the robustness and reliability of these measurements.

Critical conclusion: One thing remains certain: it will never be “too hot” in Canada, despite alarmist rhetoric suggesting otherwise. The exaggerated claims that 2024 was “the hottest year ever” are not grounded in rigorous scientific analysis but serve primarily as political and ideological propaganda. This relentless propagation of fear fosters anxiety, despair, and nihilism, especially among young people — serious consequences largely ignored by climate alarmists.

The scientific community, policy-makers and the public at large need to insist on transparency, rigour and honesty in climate discourse. Recognizing the motivations behind alarmist claims is essential to ensuring public trust and effective policy. Climate science should strive to educate, not frighten, promoting balanced understanding rather than catastrophic narratives disconnected from historical context and scientific rigour.

Matthew Wielicki, Ph.D. in geochemistry from UCLA, publishes the Substack site Irrational Fear, which provides data-driven critiques aimed at fostering a balanced and scientifically grounded understanding of climate science.

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