Climate alarmists have been waiting nearly 8 years, since the last significant El Niño, for another chance to claim natural climate variation as an expression of their chosen non-natural theories. Tremble – or not – as the study authors predict ‘a cascade of climate crises’. – – – A strong El Niño event is going to wreak havoc on global surface temperature and trigger several climate crises in 2023–2024, according to researchers from the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences. [Talkshop comment – the hype has already started].
The El Niño event, known for releasing massive heat into the atmosphere, is poised to change atmospheric circulation patterns, influence tropical-extratropical interactions, and impact subtropical jets, monsoons, and even polar vortices, and finally results in a rapid surge in Global Mean Surface Temperature (GMST), says Phys.org.
The study was published in The Innovation Geoscience on Sept. 15.
GMST, which integrates global land surface temperature and sea surface temperature, is one of the vital indicators of climate variability and global warming.
Its interannual variability is primarily dominated by ENSO events, with El Niño events being particularly influential due to their capacity to release immense heat into the atmosphere, leading to anomalies in atmospheric circulation and changes in the surface energy balance.
Earlier in 2023, the ensemble prediction system developed by IAP has predicted that there will be an El Niño event in boreal autumn and may be maintained throughout winter.
Based on historical climate data and prior studies, the IAP team revealed the potential extent and consequences of the extreme warming expected in 2023–2024.
Their findings indicate a 17% probability that the 2023 GMST will become the highest recorded since 1950, and a staggering 61% probability that it will rank among the top three. In 2024, these probabilities suddenly rise to 56% and 79%, respectively. [Talkshop comment – ‘staggering’? None of this proves anything.]
During the development of a strong El Niño in 2023, warm anomalies are expected to predominantly affect the tropical central-eastern Pacific, the Eurasian continent, and Alaska. However, in the following year, 2024, warm anomalies are likely to encompass the entire continents, significantly increasing the chance of land-based heat waves, droughts, and wildfires.
According to Prof. Zheng Fei, corresponding author of the study, “In addition to the surge in surface temperatures, the strong El Niño in 2023-2024 is predicted to trigger a cascade of climate crises.”
Climate crises associated with the predicted strong El Niño in 2023-2024 (A) 12-month forecasts of ensemble-mean Niño3.4 index that started from Oct. 2022 to Aug. 2023 made by IAP ENSO EPS (solid color lines), the shading shows the ensemble spread of forecasted Niño3.4 index starting from Aug. 2023, and the black solid line represents the observed Niño3.4 index from Aug. 2022 to Jul. 2023. (B) Annual time series of GMST anomalies during 1950-2022 (Datasets: BEST, GISTEMP v4). The first and second years of nine strong El Niño events are indicated by orange and red bars, respectively. (C) The statistically forecasted probability for GMSTs to be 1st to 3rd in 2023 and in 2024. (D)-(E) Distribution of STAs in the first and second years of strong El Niño composited by the nine events in B. (F) Annual time series of the OHC0-2000m during 2005-2022 (blue dots), the corresponding linear trend (gray dashed line), and the estimated OHC0-2000m in 2023-2024 (red and orange bars) based on linear regression methods with a 90% confidence interval. Credit: The Innovation Geoscience (2023). DOI: 10.59717/j.xinn-geo.2023.100030
Guest post by Antonis Christofides, Demetris Koutsoyiannis, Christian Onof and Zbigniew W. Kundzewicz
On the chicken-and-egg problem of CO2 and temperature.
Bare facts vs. mechanism
A car is travelling at 80 km/h, and a ray of light is travelling parallel to the car, in the same direction. Its speed relative to the Earth is 300,000 km/s. What is its speed relative to the car? Today we know that the answer “300,000 km/s minus 80 km/h” is wrong. But in 1887, people thought that it was self-evident and undisputable—after all, it’s basic logic and simple arithmetic. At that time, physicists Michelson and Morley had devised a method with sufficient accuracy to measure the small differences in the speed of light, and in an effort to discover details about its movement, they conducted one of the most famous experiments in the history of science. The results were baffling. The speed of light was constant in all directions—the direction of the Earth’s movement, the opposite direction, and the perpendicular direction. There was no explanation for that—it defied all logic.
However, we have to look at the bare facts, regardless how impossible they seem. Michelson and Morley did not feel compelled to provide an alternative theory of light, or of anything. They concluded that their results “refute Fresnel’s explanation of aberration” and that Lorentz’s theory “also fails.” Had they written “we have no idea what’s going on” it would have been the same. Making their negative results public opened the road to further research. It was a long road, and it took almost twenty years of work by distinguished scientists before arriving at the theory of relativity.
It goes without saying that this is hardly the first or the last mystery in the history of science. One that is still unsolved is the changing mass of the International Prototype of the Kilogram. Until a few years ago, the kilogram was defined as the mass of a platinum-iridium object stored in the International Bureau of Weights and Measures in Paris. It has been found that its mass changes over time by something like 0.000005% per century, and no-one knows why exactly. That no-one knows the mechanism does not alter the fact that the mass does change.
How a clear case of causality can become a noisy mess
Imagine a beach being hit by small waves. Once in a while, a series of noticeably larger waves arrive. There’s a port 10 km further, and ships are departing from it. We might notice that the departures of the ships are correlated to the instances of larger waves, and suspect that there could be a causal relationship.
In reality, in this case we understand the mechanism through which the ships cause the waves; but if we assume we don’t, here is how we might try to investigate: we might draw a chart like the following, where the horizontal axis is time, the orange line shows ship departures (the vertical axis showing the size of the ship) and the blue line shows sea level. If every departure was reliably followed by a temporary increase in wave height, we could conclude that the departures of the ships potentially cause the increase in wave height, especially if we noticed that the size of the ship is correlated to the size of the increase in wave height.
We say “potentially” because we can never be certain about causation. It could be that the departures and the waves both have a common cause. Even if someone was shot in the head, we can’t be certain it was the bullet that killed him—he might have suffered a stroke just before the bullet entered his brain (Agatha Christie’s Poirot has resolved several mysteries of similar type). So we can hardly be 100% certain that X causes Y. One thing is clear, however: the waves do not cause the ships to depart. The reason is that first the ship departs and later the waves hit the beach. The effect cannot precede the cause.
Even in this simple case where there’s an impulse (the departing ship) followed by a response, things can quickly get complicated. Ships could be going in many different directions, and the response would not always appear in an equal time interval after the impulse. For some impulses the response could be totally absent (e.g. for ships that depart in a direction away from the beach). The interval between departures could be smaller than the time it takes for the response to arrive, and the intertwining of impulses and responses could be confusing. Sometimes responses might appear out of the blue, without impulse (for example, there could be arriving ships that cause that, which we might not have taken into account). It might not be as easy to distinguish the wave response from the other waves if the sea is rough. Add all these factors together, and the blue line could be a big noisy mess.
And in a real world example, like in the question of whether CO₂ concentration affects the temperature, both lines can be a big noisy mess.
Investigating potential causes
So here is the question: given two processes, how can we determine if one is a potential cause of the other? We deal with this question in two papers we published last year in the Proceedings of the Royal Society A (PRSA): Revisiting causality using stochastics: 1. Theory (preprint); 2. Applications (preprint). We reviewed existing theories of causation, notably probabilistic theories, and found that all of them have considerable limitations.
For example, Granger’s theory and statistical test have already been known to be identifying correlation (for making predictions), not causation, despite the popular term “Granger causality”. What is more, they ignore the fact that processes exhibit dependence in time. Hence, formally testing hypotheses in geophysics by such tests can be inaccurate by orders of magnitude due to that dependence.
As another example, Pearl’s theories make use of causal graphs, in which the possible direction of causation is assumed to be known a priori. This implies that we already have a way of identifying causes. Moreover, insofar as those theories assume, in their use of the chain rule for conditional probabilities, that the causality links in the causal graphs are of Markovian type, their application to complex systems is problematic.
Another misconception in some of earlier studies is the aspiration that by using a statistical concept other than the correlation coefficient (e.g. a measure of information) we can detect genuine causality.
Having identified the weaknesses in existing theories and methodologies, we proceeded to develop a new method to study the question whether process X is a potential cause of process Y, or the other way round. This has several key characteristics which distinguish it from existing methods.
Our framework is for open systems (in particular, geophysical systems), in which:
External influences cannot be controlled or excluded.
Only a single realization is possible—repeatability of a geophysical process is infeasible.
Our framework is not formulated on the basis of events, but of stochastic processes. In these:
Time runs continuously. It is not a sequence of discrete time instances.
There is dependence in time.
It is understood that only necessary conditions of causality can be investigated using stochastics (or other computational tools and theories)—not sufficient ones. The usefulness of this, less ambitious, objective of seeking necessary conditions lies in their ability:
To falsify an assumed causality.
To add statistical evidence, in an inductive context, for potential causality and its direction.
The only “hard” requirement kept from previous studies is the temporal precedence of the cause over the effect. Sometimes it can happen that causation goes both ways; for example, hens lay eggs and eggs hatch into hens (and it was Plutarch who first used the metaphor of hen and egg for this problem). Conveniently, we call such systems “potentially hen-or-egg causal”. Our method also identifies these, and also determines in these cases which of the two directions is dominant.
To deal with dependence in time, often manifested in high autocorrelation of the processes, we proposed the differencing of the time series, which substantially decreases the autocorrelation. In other words, instead of investigating the processes X and Y and find spurious results (as has been the case in several earlier studies), we study the changes thereof in time, ΔX and ΔY.
A final prominent characteristic of our method is its simplicity. It uses the data per se, rather than involved transformations thereof such as the cross- and auto-correlation functions or their Fourier transforms —the power spectra and cross-spectra. The results are thus more reliable and easier to interpret.
Atmospheric temperature and CO₂ concentration
In our PRSA papers we implemented our method in several case studies, such as rainfall-runoff and El Niño-temperature. One of the case studies was CO₂ concentration and temperature, and this one gave strong indications that temperature is potentially the cause and CO₂ the effect, while the opposite causality direction can be excluded as violating the necessary condition of time precedence.
However, the scope of these two papers was to formulate a general methodology for the detection of causality rather than to study a specific system in detail, and the case studies were brief. With regard to the relationship between temperature and CO₂ concentration, we hadn’t gone into details as to the effect of seasonality and time scale, or the exploration of many sources of data. So in our latest paper, published a week ago in Sci (“On hens, eggs, temperatures and CO2: Causal links in Earth’s atmosphere”), we studied the issue in detail. We used CO₂ data from Mauna Loa and from the South Pole, and temperature data from various sources (our published results are for the NCAR/NCEP reanalysis, but in the previous papers we used satellite data too). We used both historical data and the outputs of climatic models. We examined time scales ranging from months to decades.
The results are clear: changes in CO₂ concentration cannot be a cause of temperature changes. On the contrary, temperature change is a potential cause of CO₂ change on all time scales. As we conclude in the paper, “All evidence resulting from the analyses of the longest available modern time series of atmospheric concentration of [CO₂] at Mauna Loa, Hawaii, along with that of globally averaged T, suggests a unidirectional, potentially causal link with T as the cause and [CO₂] as the effect. This direction of causality holds for the entire period covered by the observations (more than 60 years).”
The math is a bit too complicated to present here. However all three papers have been reviewed extensively by referees and editors (notice in the last paper that four editors were involved as seen on the front page of the paper). The results in the earlier papers were criticized, formally by a commentary in the same journal and informally in blogs and social media. Some concerns expressed by critics, such as about lengths of time series, effect of seasonality, effect of timescale, are dealt with in this new paper. No-one has however developed any critique of the methodology.
In addition, the following graphic (taken from the graphical abstract of the paper and inserted here as a quiz) aims to make things even clearer. In this we plot the time series on the annual scale to avoid too many points. Hopefully even the annual scale of this graph (in contrast to the monthly scale we used in our detailed results) suffices to suggest that there is very little doubt as to the potential causality direction.
Do climate models faithfully represent the causality direction found in the real world data? This question is also investigated in our new paper. The reply is clearly negative: the models suggest a causality direction opposite to the one found when the real measurements are used. Thus, our methodology defines a type of data analysis that, regardless of the claims we infer about the detection of causality per se, assesses modelling performance by comparing observational data with model results. In this, it contributes in studying an epistemological problem and, in particular, it casts doubt over the widespread claims that “in silico experimentation” with climate models is the only option we have and that this can be justified by the (insufficiently validated) assumption of an “increasing realism of climate system models”.
One might think that the potential causality direction we determined is counterintuitive in the light of the well-known greenhouse effect, and that the effect of temperature on CO₂ concentration would be subtle. But no, it is quite pronounced. In fact, human emissions are only 4% of the total, natural emissions dominate, and the increase of the latter because of temperature rise is more than three times the human emissions. This it is visible in a graph we included in an Appendix to the paper.
Figure A1 from Koutsoyiannis et al. (2023): Annual carbon balance in the Earth’s atmosphere in Gt C/year, based on the IPCC estimates. The balance of 5.1 Gt C/year is the annual accumulation of carbon (in the form of CO2) in the atmosphere.
Of course, several questions remain. Why does the temperature increase? And why does the temperature rise potentially cause an increase in CO₂ concentration? Is the temperature change a real cause of the CO₂ concentration change, or could they both be the result of some further causal factor? It’s not hard to speculate. Yet we briefly investigate quantitatively possible mechanisms for these causal relationship in the appendices to the paper. However, if we stick to the facts, two things are clear: (i) changes in CO₂ concentration have not been warming the planet; (ii) climate models do not reflect what the observational data tell us on this issue.
JC comment: I find this analysis to be very interesting. The global carbon cycle is definitely “unsettled science.” I think what this paper shows is that CO2 is an internal feedback in the climate system, not a forcing (I think that Granger causality would reveal this?). Yes, this all depends on how we define the system, and humans and their emissions are currently acting outside of the system in most climate models and are considered as an external forcing. Again, as emphasized in the paper, human emissions are small fraction of natural emissions so this issue of internal versus external isn’t straightforward. By analogy, in the 1970’s climate models specified cloud cover, and hence clouds acted as an external forcing. However, clouds vary in response to the climate, and now with interactive clouds, clouds are now correctly regarded as a feedback and not a forcing.
Australia’s mostly government funded scientific research organisation, CSIRO, has participated in the United Nations IPCC program to identify human impacts on climate. CSIRO has contributed to the various assessment reports through evolving climate models over the past 20 years.
This article examines how well the CSIRO climate models serve the Australian community that fund their work.
El Nino Southern Oscillation (ENSO)
The phases of the Tropical Pacific have a significant impact on the weather that most Australians experience. The Eastern States of Australia, where most of the population live, experience dry and hot conditions during the El Nino phase that often result in droughts while the La Nina phase is associated with higher rainfall and often regional flooding.
This statement from the Australia Bureau of Meteorology:
Australia’s weather is influenced by many climate drivers. El Niño and La Niña have perhaps the strongest influence on year-to-year climate variability in Australia. They are a part of a natural cycle known as the El Niño–Southern Oscillation (ENSO) and are associated with a sustained period (many months) of warming (El Niño) or cooling (La Niña) in the central and eastern tropical Pacific. The ENSO cycle loosely operates over timescales from one to eight years.
Identification of the Pacific phases dates back to the 17th century when South American fishermen observed warmer waters off their coast during the El Nino phase resulting in the origin of the phase names. Henry Blanford, the Imperial Meteorological Reporter to the government of India, identified a connection between dry conditions in India and other regions of the globe associated with ENSO phases in the late 1800s. A statistical connection was formalised in the 1920s.
The best indication of the shifting phases is the ocean surface temperature in the central Pacific identified as the Nino 3.4 region that extends across the equator from 5S to 5N and along the equator from 120W to 170W. There are reliable Nino 3.4 surface temperature records dating back to the late 1800s because of the regions importance to global weather.
Nino3.4 Satellite Sea Surface Temperature
Satellite based monitors have been providing high spatial resolution spectral data as the basis for determining the sea surface temperature globally since the early 1980s. The US based centre for environmental prediction (NCEP) produces a sea surface temperature data set that uses the satellite data to interpolate between surface based measurements at moored buoys; combining the accuracy of in-situ measurements with high spatial resolution. Chart 1 plots the NCEP interpolated data for the Nino 3.4 region throughout the satellite era.
The measured temperature has averaged 27C for the 42 years of the data collection and currently has a slight downward trend of 0.63C/century. El Nino phase is associated with regional temperature above 28C while La Nina phase is present when the temperature is below 26C. The significant El Nino occurrences around 1982, 1998 and 2016 stand out in the plot.
Coupled Model Intercomparison Project (CMIP)
The CMIP framework dates back to 1995 and set an agreed basis for the inputs to climate models produced by numerous research groups around the world for comparing their model output.
CMIP3
CMIP3 was established for the third assessment report that projects climate state from the year 2000. The Special Report for Emissions Scenarios (SRES) provided a number of scenarios with a range of inputs but only two are noted here:
SRES A1b projects atmospheric CO2 to reach 703ppm by 2100
SRES A2 projects CO2 to reach 836ppm by 2100
Chart 2 shows the surface temperature prediction for the Nino34 region produced by CSIRO’s Mk3.0 model using the worst case SRES A2 scenario:
The model output starts 3C below the measured average temperature at year 2000 then reaches the current average by 2100. So, although the there is a warming trend of 2.79C/century, the modelled temperature under the worst case CO2 emissions only reaches the present temperature by 2100. The upward trend of the model output during the 23 year overlap with measured data is 4.19C/century compared with measured cooling trend of 0.51C/century.
CMIP5
By 2007 and the fifth assessment report, the emission scenarios had been renamed to Representative Concentration Pathways (RCP). The CO2 emissions associated with the pathways are:
RCP 2.6 projects CO2 to reach 421ppm by 2100
RCP 4.5 projects CO2 to reach 538ppm by 2100
RCP 6 projects CO2 to reach 670ppm by 2100
RCP 8.5 projects CO2 to reach 936ppm by 2100
Chart 3 shows the predicted temperature for the Nino 3.4 region based on CSIRO’s Mk3.6 model using the RCP 8.5 scenario.
Chart 3 has hindcasting back to 1980 where the average is 3C below the measured average at that time but ends up averaging 29C by 2100 to give a linear upward trend of 4.48C/century. The model produces a warming trend from 1980 to 2023 of 1.85C/century compared with measured cooling trend of 0.63C/century.
CMIP6
The emission scenarios for the sixth assessment report were set out in 2015 as Shared Socioeconomic Pathways (SSP) with CO2 emissions as listed:
SSP126, 440ppm by 2100
SSP245, 600ppm by 2100
SSP370, 860ppm by 2100
SSP585, 1130ppm by 2100
Chart 4 shows the predicted surface temperature in the Nino3.4 region for SSP585 from CSIRO’s ACCESS CM2 model:
Chart 4 also displays hindcasting to 1980. The overlap with measured data has a warming trend of 1.72C/century, which is in the opposite direction to the cooling trend of 0.63C/century with measured data. The starting temperature of 26C is now closer to the measured average of 27C while the temperature averages 31C by 2100. By 2080, the model is predicting regional open ocean surface temperature to sustain temperature above 30C. This is physically impossible with the current atmospheric mass.
The maximum sustainable temperature of 30C is regarded as well known. It has been stated in scientific literature dating to the 1970s. A 1991 paper by Ramanathan and Collins even linked the temperature regulation to cirrus cloud formation. It also appears that the Russian INM model is consistent with this limit as shown in Chart 5.
Chart 5 displays the surface temperature prediction for the Nino3.4 region under the worst case scenario. It starts well below the current average but reaches the current average by 2100. It has a warming trend of 2.73C/century, which is opposite direction to the observed cooling trend. However it does not predict the physically impossible like the CSIRO’s ACCESS model.
Open Ocean Temperature Limit of 30C
It is possible to now observe the way that oceans and the atmosphere above limit heat input to regulate the open ocean surface temperature on a daily basis looking at ocean warm pools using satellite data. There is also historic data recorded by ocean moored buoys that provide surface level observation at specific locations. Chart 6 examines surface temperature data for the moored buoy in the middle of the Bay of Bengal located at 15N, 90E.
The chart covers an annual cycle for two years 10 years apart with daily temperature readings. The chart includes the calculated monthly top of the atmosphere solar EMR. The solar EMR is almost constant at 15N through May, June, July and August. In 2008, the temperature regulation began shortly after the surface reached 30C around day 120 then continued to regulate till almost day 300. In 2018 the temperature overshot to almost 32C before the regulation set in around day 150 and continued regulating to day 280.
Chart 7 includes the measured surface insolation for 2018 to clearly show how the cloud formation associated with the monsoon limits surface sunlight to hold the surface temperature at or just below 30C.
Near clear sky conditions prevail from day 30 through to day 150. The monsoon sets in around day150 and persists in steady cyclic mode till day 265 as the ToA solar EMR is reducing. During this period, the average surface insolation is 169W/m^2, which is only 39% of the ToA solar EMR. The temperature climbs under clear sky from day 265 to 280 till it exceeds 30C then cloud forms again to bring the temperature back under 30C. After day 300, the ToA solar EMR is too low for the surface to reach 30C.
Both the Bay of Bengal and Arabian Sea have limited northern extent and both regions of the Indian Ocean become warm pools through April and May before the atmosphere approaches equilibrium with the surface enabling convective instability causing the monsoon to set in. This contrast with the tropical western Pacific where warm pools persist most of the year as shown in Chart 8.
The tropical Atlantic is more constrained longitudinally and typically only approaches or reaches the 30C limit in late September as shown in Chart 9.
CSIRO Model Claims Versus Performance
The outputs of the various CSIRO models over the three assessment reports are not directly comparable because the highest CO2 emissions scenario has increased with successive reports. However the INM and CSIRO model comparison for CMIP6 with SSP585 emissions produce vastly different results with the INM a result closer to the measured data but still with a warming trend; opposite of what has been observed through the satellite era..
The description for CSIRO’s ACCESS climate model states the following:
Around the world there are over 100 global climate models available and used by international research teams to better understand our historical and future climate. Each climate model has different strengths and biases. Most climate models are developed by research groups in the Northern Hemisphere. As a result, these models may not always focus on the climate drivers and phenomena most important or relevant to Australia.
ACCESS equips Australia with the ability to focus on global climate as well as the weather and climate of the Australasian region and the Southern Hemisphere. The development of ACCESS has also built the capability and capacity of Australian researchers and technicians in climate science, observations and highperformance computational modelling. This means that Australia has the modelling capability to be able to conduct its own global and regional climate experiments using ACCESS and can critically assess the results of climate experiments done by others internationally.
The measured data shows that the ACESS model falls a long way short of achieving anything of value for weather and climate prediction in Australia. It does not come close to forecasting the ENSO phases that are so critical to climate states in Australia. The Russian INM model is at least in the ballpark and does not make unphysical projections.
With regard the Southern Hemisphere, it has been experiencing lower peak ToA solar EMR since 1600. This is now reflected in cooling trend in the Southern Ocean of 0.64C/century since 1980. The ACCESS climate model has a warming trend of 3C/century in the Southern Ocean – again, the trend is in the wrong direction.
The CSIRO and its ACCESS modelling team are no longer serving Australia. Rather they are deeply embedded in the corruption of science evident in climate models they claim are useful but are clearly not. This is what the ACCESS Team claimed for the CMIP6 results:
ACCESS models and expertise of researchers has helped significantly to understand Australia’s future climate, as part of the International Coupled Model Intercomparison Project (CMIP6)
Only a scoundrel with a gullible audience could make such stupid, untestable claim about the future. The modelling CSIRO did back in 2000 that now has 23 years of testable output is far from validated. The current ACCESS model clearly produces unphysical nonsense.
Climate Change
Climate has always changed. One of the major flaws with climate modelling is that the modellers arbitrarily choose a pre-industrial starting point with the assumption that there was a state of climate equilibrium at that point in time. In reality, there is compelling evidence that following the regional peak sunlight gives insight into the direction of observed climate trends.
The output of the sun varies slightly through the 11 year solar cycle however there is large spatial and temporal variation in solar EMR reaching the top of Earth’s atmosphere due to its orbital relationship with the sun. Chart 10 shows the variation in monthly average ToA solar EMR as a function of latitude for selected months in 2023.
The location with the highest monthly ToA solar EMR is the North Pole currently averaging 520W/m^2 in June. As observed in Chart 6 above, the four months shown have close to the same monthly average solar EMR at 15N. Note that there is a mid latitude peak in June located at 44N.
Chart 11 examines how the peak daily mid latitude ToA solar EMR has changed over time and will change in the future. The peak daily solar intensity usually coincides with the summer solstice.
The lowest peak daily solar EMR of 483.7W/m^2 occurred at 44N in 1584. It is now at 483.9W/m^2 and will reach its next high of 505.4W/m^2 in 10900.
The lowest peak solar EMR coincides with historically low recorded temperatures in the NH as well as other evidence of a cold period commonly known as the Little Ice Age. The NH has been warming now for at least 200 years based on the slow rise in sea level over the past two centuries. Autumn snowfall and extent across the NH has been trending up for at least 70 years consistent with warmer NH ocean surface in late September. The maximum extent of snow coverage is also trending up. The Southern Ocean has already started to cool as the SH peak solar EMR declines.
The region with the most rapid rise in seasonal temperature is the Greenland Plateau in January; displayed in Chart 12.
The trend over the satellite era is upward at 9.1C/century. This can only be the result of increased winter ocean air advection resulting in increased snowfall. The elevation of the plateau has indeed increased 170mm in the past decade. Hindcasting in the CSIRO ACCESS model with CMIP6 SSP585 emissions scenario for the same region yields a January trend of just 3.9C/century. This highlights the inability of the ACCESS model to predict observed changes in the region exhibiting the most warming since 1980.
The proportion of ocean surface reaching 30C is increasing as the NH ocean surface warms up in response to increasing peak ToA solar EMR. The ocean area reaching 30C in April, before the Indian monsoon sets in, has increased by 30% over the two decades from 2003 to 2023. This trend will continue due to the increasing peak solar intensity across the NH.
Climate has always changed and will continue to change. Climate modellers are not providing any useful insight into why climate has changed. The ACCESS model produces unphysical nonsense that has no relationship to observations or even produces plausible projections.
The Author
Richard Willoughby is a retired electrical engineer having worked in the Australian mining and mineral processing industry for 30 years with roles in large scale operations, corporate R&D and mine development. A further ten years was spent in the global insurance industry as an engineering risk consultant where he developed an enduring interest in natural catastrophes and changing climate.
The Power and Impact scale rates the storm intensity during the highest impact (they do not have to make “landfall”, just cause the conditions). That has been increased to 9 from 8 (see Power and Impact scale). In cases like Ian, two different impact numbers that were added together – 4 for Florida and 1.75 for the Carolinas. The ultimate impact is Donna in 1960 (4 in Florida, 3 in the Carolinas, and 2 in New England) for a total of 9. A whole season was wrapped into one storm. Note that Canada is not included in this forecast.
These numbers have been upped slightly. I am saying six tropical storm impacts because I believe that when the season is done, the feature that was un-named on Memorial Day weekend off the Southeast Coast that caused a wipe out the holiday weekend in the Carolinas, hurricane-force winds to a Carnival Cruise Ship, and storm force winds on the coast, will get classified. You can’t classify that January system and then let that one go. We do realize this is somewhat of a numbers game and is totally subjective.
So far, NHC has classified five storms. The two African waves set off much hype as they were so early on, but they fell apart. Since Cindy, nothing has developed outside of Africa. That is how it is normally until August. What is interesting is that the pattern is doing it with record-warm water comparable to the busiest of seasons. This further buttresses my argument about how the distortion of the warming can bring down activity if you boil it down to the old Texas A & M rule: Hurricanes are ways to redistribute heat out of the Tropics. If it’s already being done horizontally and vertically (i.e., warm all over), what’s the need for them?
So with five storms already classified and 16 ACE points, we are ahead of that. One of the storms, Don, became a hurricane. Because it was around so long, it had 7 of the 16 ACE points. The January system had 1.4 ACE points. Don did not originate in the Tropics (nor did the January system or what became Arlene). Essentially the African wave season has produced only 7 of the 16 points. If we were only at 7, we would be below normal for the date.
The big fear here is a spray gun season that all comes in a few weeks. 2008 was classic with seven named impact storms in a row, and then none:
1985:
Herein lies the problem. The congregation of tracks may wind up similarly, and the September Sea Level Pressure forecast by the Euro alludes to that. In the same manner, its precipitation forecast from mid-September to November last year hinted at the late-season activity well before the storms that hit were named.
Globally the western Pacific is doing what were saying it was going to do. The El Niño, of course, is raging full scale and is heading to what we said from early in the season:
This is in line with the preseason analogs, which were way, way under our totals. However, the warm Atlantic and the Multivariate Enso index are other factors. The MEI is not responding like the ONI because it incorporates atmospheric aspects, so it means that there is a big disconnect between the observed El Niño (Sea surface temperature-wise SST) and other similar years, likely due to the distortion of the entire global pattern brought about by distorted warming. So we can’t just rely on those analogs. We did not in the preseason, and the MEI gives us reason to believe that while El Niño will limit this season’s potential, it will not chop it down as much as the other strong ones did.
The old PSU rule was the real hurricane season starts August 15 and ends Oct 15. 75% of the ace is in that time span, and so it may be this year. I have made changes to the impact areas where we believe a higher-than-average ACE will occur.
The September ECMWF forecast looks a lot like the Septembers of 1954, 1985, 1989, 2003, 2004, 2005, 2008 & 2017, with the western trough and ridging up through eastern Canada. Scaling prevents the kind of definition that is seen in the actual analog:
The Sea Level Pressure pattern forecast certainly supports it:
The northward shift in the model makes sense compared to the analogs because of El Niño trying to limit features in the Caribbean. So our forecast map is assuming September is going to be a big month. Again the PSU rule of August 15-October 15 is unlike last year, centering the season in the middle. Last year we picked out analog/model correlations and nailed the late-season activity. It will be interesting to see if this is correct.
The spread of landfalling majors in these years ranges from Harvey on the western flank in 2007 to Carol and Edna in 1954 to the east (Juan, if you count 2003 in Canada).
It is interesting to note how the last three seasons have worked versus this one. 2020 was a wild start to finish. 2021 was early, and 2022 was late. This one is in the middle. So this turns into a “bang for the buck forecast”. I have upped the majors to 1-2 hits. If there is a spray of 5 or 6 storms impacting the U.S., three or four hurricanes, and 1-2 majors, it would mean the Power and Impact points would be higher, so I nudged that up.
The Verdict
The western Pacific is performing according to plan. I think 75% of the ACE may occur in September, and there may be a flurry of activity, depending on the MJO, similar to what we have seen before, where several storms impact the U.S. all at once. The Texas hurricane season should shut down in October, and I suspect after October 15, the rest of the U.S. will too, but who knows what will get named out in the middle of nowhere that may head for Europe?
This is actually a pretty threatening impact forecast. We need to watch the MJO. So far, we have been saved by western Pacific activity, as development there usually means the Atlantic is quiet. They are way ahead of the game this season. The quiet in the Atlantic is not likely to last, and there is a chance that the current quiet will turn into a riot for a few weeks; so far there is nothing on the horizon but rumors of storms, but later this month and especially in September, that should all change.
Note that next year may be a doozy of a season. I believe this is a bounce-back El Niño in response to the longest and strongest MEI El Niño on record, so we should collapse it and go back to a La Niña base state. SSTs will remain warm, and so that may be a season number-wise (at least for totals) two times higher than this year.
Joe Bastardi is a pioneer in extreme weather and long-range forecasting. He is the author of “The Climate Chronicles: Inconvenient Revelations You Won’t Hear From Al Gore — and Others” which you can purchase at the CFACT bookstore.
His new book The Weaponization of Weather in the Phony Climate war can be found here. phonyclimatewar.com
A steady and remarkable rise in average global ocean temperatures this year is now outpacing anything seen in four decades of satellite observations, causing many scientists to suddenly blare alarm over the risks and realities of climate change. But even those typically aligned on climate science can’t agree on what, exactly, triggered such rapid warming and how alarmed they should be.
Some climate researchers suspect that a drastic reduction in air pollution from ships has allowed more sunlight to radiate into oceans, a conclusion others vigorously criticize. Meteorologists also say a weakening of Atlantic winds may be encouraging warming; normally these winds help cool waters and carry sun-blocking plumes of Saharan dust.
Scientists nonetheless agree on this: Conditions are ever ripening for extreme heat waves, droughts, floods and storms, all of which have proven links to ocean warming.
In the Pacific Ocean, warming temperatures are to be expected during El Niño — its impacts on weather around the world stem from warmer-than-normal surface waters along the equatorial Pacific. But the extreme warmth extends beyond the Pacific. Record warmth is also occurring in the equatorial and northern Atlantic — and in the tropics, where hurricanes form.
“This is totally bonkers and people who look at this stuff routinely can’t believe their eyes,” Brian McNoldy, a hurricane researcher at the University of Miami, wrote on Twitter. “Something very weird is happening.”
Antarctic sea ice concentration on June 27, 2023, with white representing solid ice and dark blue representing open ocean. The median ice edge for 1981–2010 is drawn in orange. (Credit: Map by NOAA Climate.gov, based on data from the National Snow and Ice Data Center)
And of course there is the added warning about Antarctic sea ice not freezing as rapidly as usual in SH winter. The media always refers to “climate change” as the causal factor, which is code for rising CO2 and humans to blame. For a more reasonable discussion, see Antarctic Sea Ice Varies, It’s Complicated.
What About Natural Factors?
Because the power, glory and money comes from CO2 hysteria and taking over the energy industry, the theories are all about the atmosphere. Realists know that Oceans Make Climate, and look for more direct means by which sea temperatures can warm.
The HadSST4 AMO dataset was finally updated and showed dramatic 2023 warming in the North Atlantic. Let’s consider two possibilities.
An international team of scientists led by CICOES researcher David Butterfield work together to rapidly find and explore large hydrothermal vents on the world’s longest mountain range.
Sometimes Mid-Atlantic ridge is called the “40,000-mile Volcano”
Scientists have discovered three new hydrothermal vent fields over a 434-mile-long stretch of the Mid-Atlantic Ridge during the first scientific expedition aboard Schmidt Ocean Institute’s recently launched research vessel Falkor (too).
The multidisciplinary science team representing 11 institutions from the United States, Canada, and France used advanced ocean technologies to make the discovery. Scientists used autonomous and remotely operated underwater vehicles resulting in 65 square miles (170 square kilometers) of seafloor mapped at one-meter scale resolution, an area approximately the size of Manhattan Island.
The discovery of the active hydrothermal vents is the first on this section of the world’s longest underwater mountain range, the Mid-Atlantic Ridge, in more than 40 years. One of the discovered vent fields was located at the Puy des Folles volcano and has five active sites over 6.95 square miles (18 square kilometers). High-temperature ‘black smoker’ vents were also found at the Grappe Deux vent system and Kane Fracture Zone.
This discovery of new hydrothermal vents under the Atlantic ocean reminds of hundreds of thousands of sea mounts active on the ocean floor, with a high concentration in the North Atlantic For a more complete discussion of bottom up ocean warming, See Post:
The eruption of the submarine Hunga volcano in January 2022 was associated with a powerful blast that injected volcanic material to altitudes up to 58 km. From a combination of various types of satellite and ground-based observations supported by transport modeling, we show evidence for an unprecedented increase in the global stratospheric water mass by 13% relative to climatological levels, and a 5-fold increase of stratospheric aerosol load, the highest in the last three decades. Owing to the extreme injection altitude, the volcanic plume circumnavigated the Earth in only 1 week and dispersed nearly pole-to-pole in three months.The unique nature and magnitude of the global stratospheric perturbation by the Hunga eruption ranks it among the most remarkable climatic events in the modern observation era, with a range of potential long-lasting repercussions for stratospheric composition and climate.
The perturbation of stratospheric water vapour burden by 13% is tremendous and has no frame of comparison in the entire observation record dating back to 1985. As there are no efficient sinks of water vapour in the stratosphere, this perturbation is expected to last over several years. Indeed, in 9 months since the eruption, the water vapour mass anomaly has gradually decreased only by 2.5% (4.3 ± 0.1% annual rate), which should lead to the perturbation timescale of over 3 years, assuming the further linear decay trend. The persistent stratospheric moist anomaly may lead to changes in atmospheric radiative balance; stratospheric dynamics as well as amplification of the polar ozone depletion through wider occurrence of polar stratospheric clouds. The ability to assess the longer-term impacts of the HT eruption on stratospheric chemistry will depend strongly on the quality and availability of global satellite observations such as MLS in the coming years.
In addition to blasting seawater to the stratosphere, the event shook the ocean floor worldwide.
The massive volcanic blast in the Pacific last year was felt 18,000km away on the other side of the world, on the floor of the Atlantic Ocean. The cataclysmic eruption of Hunga-Tonga Hunga-Ha’apai on 15 January 2022 sent pressure waves through Earth’s atmosphere that connected with the sea surface and triggered 50 highly sensitive seismometers placed 5,000m under water on the seabed. It was one of a number of intriguing phenomena picked up by the instrument network in the Azores-Madeira-Canary Islands region. Source: BBC
Summary
Let’s stop pretending we can alter nature by spending trillions of dollars “fighting climate change.” Better to solve actual problems we are causing and can fix, rather than obsessing over imaginary ones.
Of course, in any one year there is always going to be extreme weather events.
But Dr Gallant said this year, records were not just being broken — they were being smashed.
“It’s really made us stand up and take notice, because it’s not just in one place,” she said.
A sign of what’s to come
It is still too too early to say whether the individual weather events were made more likely by climate change, or other natural influences like El Niño.
But Dr Gallant said what was clear was the nature of weather events had changed, and it told a story of what the world may be in for in the year to come, particularly in the realm of heat.
“We’re entering territory where climate change is starting to become a much more dominant signal than it has been in the past, and things are only going to get more interesting,” she said.
How can Dr Gallant say the nature of weather events has changed, that the current cluster of weather events is a sign of things to come, while simultaneously admitting she doesn’t know whether climate change or the likely gathering El Nino has affected current weather events?
If Dr. Gallant was to make a firm statement, like “the incidence of extreme weather events will double over the next 10 years”, or “Antarctic sea ice will disappear completely by 2030”, those would be testable prediction.
But the global climate has a history of embarrassing climate scientists who make testable predictions.
Perhaps climate scientists have learned caution, through watching their colleagues endure multiple ice free arctic and end of snow humiliations over the years.
The world is once again in the grip of a semi-regular climate alarm. I’m not referring to the latest onset of the El Niño cycle, declared in action on July 4th by the United Nations, but the amplified rhetoric about the pace and scale of warming temperatures that always accompanies such El Niño periods.
Do you remember what happened last time we had a record El Niño in 2015/16? Global temperatures increased rapidly – as they do during such an event – and, according to some, it was full speed ahead to a runaway thermal apocalypse … until global temperatures started to fall again.
Earlier this month, the world broke global temperature records for several days, inevitably leading to renewed speculation about the onset of runaway global warming. The Guardian asked if we have entered a more erratic and dangerous phase with the onset of an El Niño event on top of human-made global heating.
Well, not really, or at least not on the basis of the data we have so far.
The global temperature data which started these claims are of course preliminary and are in any case a mixture of real data and input from models so a note of caution is needed. Nonetheless it is expected that the temperature records will be confirmed in coming months.
The real situation is, as they say, a little more complicated than many of the exaggerated claims.
In recent months the atmospheric circulation over the North Atlantic has been unusual. The Azores High – a semi-permanent area of high pressure – was much weaker than normal. To put this into context, for the past decade the Azores High was about or above average at this time of year. This years variation resulted in low wind speeds occurring at the same time as a so-called marine heatwave in the north Atlantic.
The lower wind speeds lead to a reduction in the mixing of surface water with the cooler water below, allowing the sea surface temperatures to increase. Another consequence is a reduction in the transport of dust from the Sahara westward over the north Atlantic. Usually Saharan dust reflects solar radiation back into space before it reaches the ocean surface, thereby cooling it. Another contributing factor is the decreasing particulate pollution over the northern hemisphere as the air gets cleaner over Europe and North America.
Now add all those effects to the multi-decadal fluctuation of north Atlantic circulation and the consequential transport of heat about which we have a very incomplete understanding.
Then there is the El Niño starting to snake its way across Pacific equatorial waters. All of this is against a backdrop of a global warming trend which, aside from the El Niño, hasn’t shown much of an increase, if at all in almost the past decade.
So looking at the events of the past few months, and the records broken, you would have to say it’s complicated and best left to a post-El Niño analysis. No such caution for the Met Office and the Guardian however: “If a few decades ago, some people might have thought climate change was a relatively slow-moving phenomenon, we are now witnessing our climate changing at a terrifying rate,” they quote Prof Peter Stott, who leads the UK Met Office’s climate monitoring and attribution team.
Given the complexity and disparity of recent events I look forward to the Met Office’s post-El Niño analysis of such extreme and rather premature hype.
Warning: This article contains quotes from Friederike Otto, Michael Mann, John Cook and the Institute for Strategic Dialogue’s Jennie King.
With the amount of free speech one sees on the internet nowadays, who can doubt that The Truth is in dire need of protection? I speak, of course, of the threat from climate change denial, that most pernicious of weeds, currently choking the garden of online verity with its weedy lies. And its thriving, don’t you know? If anything it’s worse than when Exxon first planted it, way back in the days when climate scientists were forced into slave labour for Big Oil and made to lie about the true evils of carbon dioxide. Something obviously needs to be done to restore the internet’s borders and lawns so that they can once again provide a safe playground for our children. Legislation could do the trick perhaps, but, in the meantime, who is out there who could possibly come to our rescue with the hoe of justice and the trowel of truth?
As I have acknowledged before now, John Cook of FLICC fame is a man of some stature. Furthermore, Professor Friederike Otto’s ground-breaking work, demonstrating how hotter weather is impossible without extra heat, has previously attracted my attention. And as for Michael Mann, what he doesn’t know about statistics is quite frankly not worth fiddling with. But put them all together and you have something far greater than the sum of its parts. What you have is an assembly of avengers. In fact, all that would be missing from the perfect superhero line-up would be a guest appearance from a spokesperson for the Institute for Strategic Dialogue. If only Jennie King were here, she’d know what to do.
Thankfully, the dream team is not just the stuff of dreams, it is the stuff of stuff – the sort of stuff that journalists have already been writing. Take, for example, the stuff that Stuart Braun wrote for DW recently. It starts by asking the question we all want answering: Why is climate denial still thriving online?
The Fantastic Four are already standing in the wings, eager to make their heroic entrance, but first Stuart needs to fully justify their invocation:
An extreme global heatwave has been blamed on climate change, yet online misinformation has evolved to counter the facts — despite platforms like TikTok banning climate denial.
By ‘online misinformation’, I presume he is referring to the correction that El Niño is actually playing the dominant role. But let us not get distracted from the crusade. Stuart continues:
Record global temperatures on July 3 kicked off the hottest week ever recorded as intense heatwaves gripped the planet. Climate scientist Friederike Otto of London’s Grantham Institute for Climate Change and the Environment called the heat “a death sentence for people and ecosystems.”
An early opening blow from Otto there. Die you miserable deniers! But who’s that lurking in the next paragraph? Why, it’s one of those dastardly misinformers:
Yet the next day, a political journalist in the UK, Isabel Oakeshott, tweeted that “climate change headbangers panicking about a few hot days last month can calm down … It’s 13 degrees and pouring.” She added that she was “about to light the woodburner.” Within a day, over 2.2 million people had seen the tweet.
An incredulous Braun asks:
Amid the worst heatwaves ever recorded in the US, China, Mexico, Siberia and beyond, and near-unanimous scientific consensus that humans have induced global heating — in large part by burning fossil fuels — how does such denial continue to flourish?
I dunno, Stuart. But XR Cambridge seemed to have Oakeshott’s number when they sarcastically tweeted:
Pakistan, you can stop complaining about the unprecedented floods now because actually it’s 13C in the Cotswolds in @IsabelOakeshott’s garden so 1/3 of the country underwater and loads of deaths and livelihoods destroyed probably didn’t happen.
Except it is well established that a third of Pakistan ending up underwater didn’t happen. But let us not get distracted from the crusade. Stuart has more climate denial weediness to uproot:
“So how are they going to charge their EVs when there is no electricity?” another wrote, implying that renewable energy is not a reliable power source — despite wind and solar being the cheapest and fastest-growing forms of energy.
Implying? Cheapest? Has the Oxford English Dictionary been updated recently without me being informed? Anyway, let’s not get distracted from the crusade. John Cook is about to fly in through a window:
These are old rhetorical tricks that today are targeted less at climate science than solutions, says John Cook, a climatologist and senior research fellow at the University of Melbourne, and author of the Skeptical Science blog that has long debunked climate misinformation. The idea that “solutions will be harmful” or “solutions won’t work” is a repackaging of old attacks on the cost of climate action from the 1990s, he added.
KERPOW!!! THWOK!!! ARRGH!!!
Then, after a nice sunset photo of one of those aesthetically pleasing windfarms we all want in our back yard (suitably packaged with the caption “Solar and wind power is now cheaper than fossil alternatives”), we have a surprise contribution from the Center for Countering Digital Hate:
“The goal posts have moved,” said Callum Hood, head of research at the global Center for Countering Digital Hate (CCDH). Climate denial now employs deflection and “sows doubt” to ultimately delay the energy transition. The logic runs that “doing something is worse than doing nothing,” Hood explained, referring also to the notion of “climate inactivism” coined by climate researcher and author Michael Mann.
Curse you Michael, with your coined notions! I have no power to withstand such magic. And as for my digital hate, that can surely be no match for Jennie King’s strategic dialogue:
“There are clear vulnerabilities in the way social media platforms are designed and governed at present which allows such content to rise to the surface,” said Jennie King, head of climate research & policy at the Institute of Strategic Dialogue (ISD), a global think tank researching extremism and disinformation.
There follows a lot of stuff about ‘algorithmic bias’, ‘echo chambers’, ‘superpolluter publishers’, the Russian state, the ‘toxic ten’, and broken promises from Google and Facebook, before Stuart once again calls upon Jennie’s superpowers with:
“Misinformation thrives in moments of crisis,” said Jennie King of intersecting health, cost of living, energy and inflation crises in recent years…”The weaponization of ‘genuine trauma’ was evident in the first waves of the [Covid-19] pandemic when the term ‘climate lockdown’ emerged across social media, promotors claiming the lockdown was a dress rehearsal for a coming wave of ‘green tyranny’,” King explained.
I have to admit that I hadn’t quite realised it was we climate deniers that were weaponizing ‘genuine trauma’ during the pandemic. There was me thinking it was the government. But let us not get distracted from the crusade. We still need to know how we can fight online climate change denial. Jennie King returns to the fray:
Like Facebook, TikTok promised to ban climate denial content in April. But Jennie King says such attempts at content moderation are “crude” and “unenforceable,” adding that “it is not criminal to deny climate change.” The ultimate solution would be to “demonetize” climate denial, she believes, something big tech companies have so far largely failed to do.
Well, we have yet to see what is enforceable. Roll on the Online Safety Bill. Meanwhile, John Cook has his own final solution to offer:
John Cook, meanwhile, has long advocated for “pre-emptive inoculating messages” that neutralize what he calls “climate disbeliefs” by explaining “the flawed argumentation technique used in the misinformation,” and that reinforce the scientific consensus on climate change.
Well, all I can say is this. If this article by Stuart Braun is supposed to be a good example of Cook’s ‘inoculating messages’, then one shouldn’t find it in the least bit surprising that climate change denial is on the rise. Talk about the vaccination helping to spread the disease!
So, if you’ll excuse me, I have to go now to sow more doubt and digitize my hate. This climate change isn’t going to deny itself, don’t you know?
Evidence that what is today called ‚climate change‘ can naturally occur, and has occurred, over a relatively short timescale – described here as ‚remarkable‘. Maybe history is trying to tell us future climate conditions are more unpredictable than advocates of IPCC doctrines would have us believe. – – – An El Niño event has officially begun, says Science Daily.The climate phenomenon, which originates in the tropical Pacific and occurs in intervals of a few years will shape weather across the planet for the next year or more and give rise to various climatic extremes. El Niño-like conditions can also occur on longer time scales of decades or centuries. This has been shown to have occurred in the recent past by an international research team led by Ana Prohaska of the University of Copenhagen and Dirk Sachse of the German Research Centre for Geosciences (GFZ).Their analysis of biomarkers — organic molecules or molecular fossils from vascular plants — in the sediments of a lake in the Philippines indicates an unusually dry phase in the region during the Little Ice Age between 1600 and 1900 A.D.The results have now been published in the journal Communications Earth and Environment. They show how important the understanding of past dynamics of the tropical Pacific ocean-atmosphere climate is for the improvement of climate models and the prediction of future climate changes. . . . El Niño-like phenomena on longer time scalesWhile El Niño is an interannual climate phenomenon, the climate system of the tropical Pacific can also exhibit El Niño-like behaviour on longer time scales of decades and centuries, which is linked to the east-west gradient of sea surface temperatures in the Pacific.Such behaviour has been shown to have transpired in the recent past by a team led by Ana Prohaska, assistant professor at the University of Copenhagen and formerly a visiting scientist at the GFZ, and Dirk Sachse, working group leader in GFZ Section 4.6 „Geomorphology“ and director of Topic 5 „Landscapes of the Future“ of the Helmholtz research programme „Changing Earth — Sustaining our Future,“ in the journal Communications Earth and Environment.They describe such a pronounced shift to El Niño-like conditions in the second half of the Little Ice Age, lasting from about 1630 to 1900 A.D.What is particularly remarkable is the short period of only one generation within which conditions changed for a period of more than 200 years.
The UAH global lower-troposphere anomaly for June 2023 is up by 0.01 K from the 0.37 K in May to 0.38 K. The New Pause thus remains at 8 years 10 months:
Nere is the entire dataset from December 1978 to June 2023:
IPCC (1990), in the business-as-usual emissions scenario A in its First Assessment Report, predicted 0.3 [0.2, 0.5] K decade–1 global warming from 1990-2090. Scenarios B, C and D all predicted less warming, but they also all predicted fewer sins of emission than Scenario A. Scenario B, for instance, predicted that annual emissions would not increase from 1990-2025. In reality, however, emissions have increased by more than half since 1990. Scenario A, then, is the emissions scenario on which we must judge IPCC’s predictions, which have proven to be grossly excessive. For the warming rate since 1990 has been only 0.137 K decade–1, showing IPCC’s original range of predictions to be 220% [150%, 370%] of observed reality.
Here is the UAH temperature record since 1990:
The latest el Niño is now well underway. On past form, it will soon bring the current Pause to an end. Already, the unspeakable BBC is licking its chops and predicting new record global temperatures.
The Realitometer, unchanged since last month, continues to show the excess of prediction over observed reality:
Meanwhile, the Climate Realists of Norway have undertaken the arduous task of establishing an international journal of climate science and philosophy. The journal is, perhaps, unique in that it allows challenges to the official narrative. Science of Climate Change (https://scienceofclimatechange.org). Volume 1.1 appeared on 1 August 2021 with a memorial of professor Nils-Axel Moerner, two book reviews and seven full-length papers (including one by me on What is Science and what is not?. The journal is free to read, but asks authors for a small fee to cover publication costs.
I remember Energy and Environment with affection. That journal used to provide a home for peer-reviewed papers that the guardians of the Party Line would not permit to be published elsewhere. Now Science of Climate Change is fulfilling a similar role. Contributions to the new journal are welcome.
Vol. 2.2 published a paper by the late Ernst-Georg Beck, Reconstruction of Atmospheric CO2 Background Levels since 1826 from Direct Measurements near Ground (https://doi.org/10.53234/scc202112/16). A dataset of annually averaged CO2 background levels directly measured from 1826 to 1960 was presented. It was based on a selection process of about 100,000 single samples from more than 200,000 available near ground on land and sea, mainly in the northern hemisphere. One of Beck’s findings was the CO2 level around 1940 peaked at 370 ppmv.
Beck’s paper sparked a good debate, of which a large part can be seen in Vol. 3.2, the latest of seven editions to date (https://scienceofclimatechange.org/volume-3-2-june-2023). Vol 3.2 starts with an essay by Richard Mackey focusing on how observed oscillations in several atmospheric and oceanic subsystems are largely responsible for Earth’s weather and climate. Rotation forces the oscillations and is the primary reason for the climate change we observe. This is currently overlooked.
Ferdinand Engelbeen commented on the article mentioned above by Ernst-Georg Beck. His article had been posted for open review, which attracted several comments on both sides. Professor Hermann Harde showed that the equations for release of CO2 from land and ocean due to higher temperatures can explain the observed peak. In short, there was a debate on a climatic question. That, on its own, is rare and valuable.
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Global warming, climate change, all these things are just a dream come true for politicians. I deal with evidence and not with frightening computer models because the seeker after truth does not put his faith in any consensus. The road to the truth is long and hard, but this is the road we must follow. People who describe the unprecedented comfort and ease of modern life as a climate disaster, in my opinion have no idea what a real problem is.
