02/19/2026 – Climate- Science.press

Australia’s Problem Child, The BOM.

Disgraceful conduct from the Australian Government’s Bureau of Meteorology, BOM, is alleged and documented. This article is short, but most of its links are quite long because they are thorough. Please persevere, there are many hidden gems in this article. Use it as a reference library if you wish.

From Watts Up With That?

By Geoff Sherrington.

Scientist, Melbourne, Australia.

Please digest a 2006 email from Dr David Jones, Senior Climatologist at BOM to Prof Phil Jones, University of East Anglia. Also, at Climategate #0601.txt .

… “Fortunately, in Australia our sceptics are rather scientifically incompetent. It is also easier for us in that we have a policy of providing any complainer with every single station observation when they question our data (this usually snows them) and the Australian data is in pretty good order anyway. Truth be know (sic), climate change here is now running so rampant that we don’t need meteorological data to see it. Recent polls show that Australians now rate climate change as a greater threat than world terrorism.”

From the start, BOM were unwilling to exist outside their own cocoon of beliefs.

For me, Here is when it all began. Prof Phil Jones to my geologist colleague Warwick Hughes, early 1990s, about his Australian BOM observations – “Why should I make the data available to you, when your aim is to try and find something wrong with it.”

Almost all of many BOM criticisms by Australians have essentially the same starting point, the “raw” daily Tmax and Tmin historic temperature observations available to the public from the BOM web site Climate Data Online, CDO. Photos of some original observation sheets for Melbourne 1859 and 1860 are here. Note the frequent corrections in pen and ink. A broad question is why such raw data are seldom used for analysis.

BOM QUOTE. “Yes—the Bureau provides the public with raw, unadjusted temperature data for each station or site in the national climate database, as well as adjusted temperature data for 112 locations across Australia….
…. The Bureau does not alter or delete the original temperature data measured at individual stations.”

Are the “raw” data really raw? Examples of manipulation are here. (Please pardon my typo dates of JULY 2014 and JULY 2015 in the first figure. They should be1914 and1915.)

There are more claims of BOM adjusting data. “In December 2009 the BoM warmed the RAW mean minimum and maximum temperatures by about half a degree from the temperatures that had previously been recorded on the BOM website database for August 2009.”

Then there is metrication, because the originals were in Fahrenheit, when now we use Celsius. BOM temperatures went metric on 1^st September 1972. Fahrenheit degrees were converted to Celsius. This introduces an error when there are too few significant figures carried.

Another cause to doubt these BOM temperatures comes from two different and differing compilations. First, the Commonwealth of Australia Yearbooks for 1953 and 1954; second, a CSIR (before CSIRO) compilation of earlier temperatures printed in 1933.

There have been changes of instruments over the decades. At first, put simply, there were Liquid-In-Glass thermometers, LIG, in large Stevenson screens. LIG have measurement uncertainty errors of their own. Later, the screens became small and smaller, the agreement between screens was studied and again here, claiming a false 0.5 ⁰C warming; the thermometers became electronic with possibly different response times to changes.

The examples so far raise “uncertainty”. This observer was uncertain between 81.7 and 81.8 ⁰F. The BOM is uncertain if a change in December 2009 was natural or man-made. Uncertainty comes from changes of instruments and locations. There is parallax uncertainty when reading an LIG thermometer, etc etc.

An estimate of the total measurement uncertainty of all of the BOM historic temperature data is absent, but needed. The classic reference for uncertainty is from the International Bureau of Weights and Measures, BIPM in France, under Guide to Uncertainty in Measurement, GUM. BOM has stated its compliance with GUM. Importantly, GUM has no provision for the use of statistics with data that are guesses, as much BOM work like ACORN-SAT is alleged to be.

BOM has its uncertainty methods in Report ITR 716 of March 2022 quoted in reply to my 2018 question “If a person seeks to know the separation of two daily temperatures in degrees C that allows a confident claim that the two temperatures are different statistically, by how much would the two values be separated?” Getting this answer was like pulling teeth out. The answer was a non-answer because of a BOM rider that “This is not an estimate of the uncertainty of the ACORN-SAT’s temperature measurement in the field” – which is what was requested.

This cascade of often uncalculated uncertainties has caused production of adjusted temperature sets, although almost all were derived from the originals. BOM started in public with a “High Quality” set, then added 6 versions of Australian Climate Observation Reference Network – Surface Air Temperature, ACORN-SAT.

ACORN-SAT uses time series plots of temperature versus time and/or customary statistics to detect break points, some of which have plausible causes in metadata, others being “statistical” without a known cause. Usually, there is no known way to determine the magnitude of an adjustment. Recourse is made to inferred adjustments from the patterns of other stations, nearby to distant.

Note: There is an exception. To the author’s knowledge, the only type of adjustment free from subjective guesswork is found here on Bomwatch.com blog. It is based on water, like rain or lawn sprinkler maintenance, cooling weather station sites by evaporation. An outcome of this method by colleague Dr Bill Johnston is that few if any corrected Australian stations show any significant warming over many decades to now.

A typical conventional time series plot follows, showing Melbourne.

The number in the box before ”x” is the trend in ⁰C/year for maximum (blue) minimum (tan) temperatures. Visually, Tmax might have a break point at about 2010. There was a station change in year 2014, so it is accepted that some type of adjustment is warranted but how much adjustment? Author’s note: I do not endorse the linear least squares procedure for analysis of these time series graphs. I show it here because it is in widespread use by others.

In this case, comparisons with numerous stations show Melbourne as the odd man out and by how much. (Good luck with inferring a magnitude for adjustment from nearby stations).

This graph suggests that Tmax has increased at 0.7 ⁰C per century and Tmin at 1.53 ⁰C per century since 1856. These are not the numbers used for calculation of Australia’s national global warming. Adjusted ACORN-SAT numbers are used. The result is that the official claim is that Australia has warmed by 1.51 +/- 0.23 ⁰C in the last 134 years. This is claimed to be wrong. The better, unadjusted estimate is less than 1 ⁰C over that time.

Adjustments and cherry picking are used to create stories from this CDO data. Natural events like heatwaves are claimed to be becoming “catastrophic”. Two heatwave offenders, authors of a highly-cited paper are Lisa Alexander and Sarah Perkins-Kirkpatrick. Australian scientist Joelle Gergis as seen by Stephen McIntyre of Climate Audit blog is another part of this trio of young female scientists whose work often shows emotion and cherry picking, for example using 1950 or so as a start date for analysis.

Numerous Australian citizens and scientists have objected to the stories because they are not based on solid science. BOM has chosen the anti-science technique of ignoring dissenting articles. Many have been linked here. My apologies are extended to any authors who are not linked, by my error, but who know they should be on the list of dissidents.

The consequences of poor science by BOM include Australian political adoption of “Net zero Carbon” (whatever that means) leading to a loss of electrical generation from cheap and reliable hydrocarbon combustion. The Australian economy is suffering as other countries such as the US are distancing themselves from this poor science.

BOM should at least attempt to face and answer the many criticisms in this article. The BOM silence is deafening. Why do they decline to answer even a single slip-up???

My best answer is a quote from the movie “Dr Strangelove”. The full movie title is “Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb”. You are invited to drop the final “b” for relevance.

Air Force General Turgidson is in the Pentagon War Room with President Muffley just before a wayward nuclear bomb from an SAC B-52 is likely to trigger the Doomsday Machine and end Life on Earth.

Turgidson: The duty officer asked General Ripper to confirm the fact that he had issued the go code and he said, “Yes gentlemen, they are on their way in and no one can bring them back. For the sake of our country and our way of life, I suggest you get the rest of SAC in after them, otherwise we will be totally destroyed by red retaliation. My boys will give you the best kind of start, fourteen hundred megatons worth, and you sure as hell won’t stop them now. So let’s get going. There’s no other choice. God willing, we will prevail in peace and freedom from fear and in true health through the purity and essence of our natural fluids. God bless you all.” Then he hung up. We’re still trying to figure out the meaning of that last phrase, sir.

Muffley: There’s nothing to figure out General Turgidson. This man is obviously a psychotic.

Turgidson: Well, I’d like to hold off judgment on a thing like that, sir, until all the facts are in.

Muffley: (anger rising) General Turgidson, when you instituted the human reliability tests, you assured me there was no possibility of such a thing ever occurring.

Turgidson: Well, I don’t think it’s quite fair to condemn a whole program because of a single slip up, sir.

The Question Climate Alarmists Avoid: What IS the Correct CO₂ Concentration?

If CO₂ is classified as a pollutant (as per the U.S. EPA’s 2009 Endangerment Finding, which enabled regulation under the Clean Air Act), then there must be a scientifically defensible “safe” or “correct” threshold concentration in the atmosphere. Yet climate policy rarely specifies one beyond implying pre-industrial levels (~280 ppm) as the ideal baseline to return to.

No Clear Threshold Defined: Policies aim to limit warming (e.g., to 1.5–2°C) via emissions cuts, but don’t pinpoint an exact “safe” ppm level for CO₂. Is it 280 ppm (pre-industrial)? 350 ppm? 400 ppm?

Over the past 800,000 years (from ice cores), CO₂ fluctuated between 180–300 ppm during glacial-interglacial cycles.

For most of the Phanerozoic eon (last ~550 million years), CO₂ was often 1,000–4,000+ ppm during periods of lush vegetation and no “icehouse” Earth.

Photosynthesis responds strongly (nonlinearly) to CO₂ increases from ~280 ppm up to ~1,100 ppm. Commercial greenhouses deliberately enrich air to 800–1,000 ppm to boost crop yields.

Everyday examples undercut toxicity claims: Exhaled breath is 40,000 ppm CO₂.

Even burning all known fossil fuels might only reach ~1,000 ppm globally.

In a hypothetical “post-Endangerment” scenario, what concentration should we target?

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What Is the Correct CO2 Concentration?

From Irrational Fear

By Dr. Matthew Wielicki

A Scientific Thought Experiment in a Post-Endangerment World

The 2009 Endangerment Finding treated carbon dioxide as a pollutant that threatens public health and welfare. For more than a decade, that designation has functioned as the legal foundation for regulating fossil fuels, electricity generation, transportation, and much of the modern economy.

Now that the Finding is being reconsidered, it is worth stepping back from the regulatory framework and asking a much more basic scientific question.

What is the correct atmospheric concentration of CO2?

If carbon dioxide is truly a pollutant, then there must be a threshold. There must be some identifiable boundary at which CO2 shifts from being part of the natural carbon cycle to being harmful in a biological or climatic sense. If such a boundary exists, it should be visible in geology, in plant physiology, or in the empirical record of Earth’s climate.

But when we begin to examine those lines of evidence, the clarity we are promised does not appear.

In The Endangerment Finding Was Pre-Cooked, I walked through the Phanerozoic reconstruction of atmospheric CO2. Over the last 550 million years, concentrations frequently exceeded 1000 parts per million and at times reached several thousand.

Life did not collapse under those conditions. On the contrary, biodiversity expanded. Forests flourished. Marine ecosystems diversified. The idea that 400 ppm constitutes dirty air sits uneasily beside a geological record in which far higher concentrations coincided with biological abundance.

If today’s atmosphere is “endangering,” then vast stretches of Earth’s history would need to be reclassified as ecologically reckless. That conclusion should at least give us pause.

In Does More CO2 = More Heat?, I also explored the complex relationship between CO2 and temperature over deep time. The geological record does not display a simple linear mapping between atmospheric concentration and climate state.

Continental configuration, ocean circulation, solar luminosity, volcanic outgassing, and feedback processes all shape global temperature. CO2 plays a role, but it is not the only control knob.

If there is an upper danger threshold, it is not obvious in deep time.

The Ice Age Constraint

The more recent record complicates things further.

In Atmospheric CO2 Concentrations of the Past and Do We Really Know the Surface Temperature or CO2 Concentration of the Past?, I discussed the proxy records and their limitations. Even accepting the ice core framework at face value, atmospheric CO2 over the past 800,000 years fluctuated between roughly 180 and 300 ppm.

Those low points coincided with massive continental ice sheets. Glacial maxima were not periods of ecological flourishing. They were periods of climatic severity and instability.

Pre-industrial levels near 280 ppm did not represent a golden age of climatic balance. They were part of a cycle of repeated glaciations driven by orbital forcing. The Earth system oscillated between ice ages lasting nearly 100,000 years and comparatively brief interglacials.

That history raises an uncomfortable possibility.

Perhaps 280 ppm was not an optimal equilibrium. Perhaps it was closer to a lower boundary of climatic stability.

The Modern Biosphere Response

Meanwhile, as CO2 rose from roughly 280 ppm to more than 420 ppm, something measurable occurred.

In Greening Earth and Booming Crops, I examined satellite evidence showing widespread increases in global leaf area. Agricultural production has expanded dramatically over the past several decades. Water use efficiency has improved under elevated CO2 conditions.

Commercial greenhouse operators routinely enrich indoor air to concentrations between 800 and 1000 ppm in order to maximize plant growth. They do not regard 280 ppm as biologically ideal.

CO2 is not a trace contaminant in plant physiology. It is the fundamental substrate of photosynthesis.

If rising CO2 were inherently degrading the biosphere, we would not expect to observe widespread greening.

The Sea Level Complication

Perhaps, then, the danger lies in the sea level.

That argument is often presented as straightforward. Higher CO2 increases radiative forcing. Higher temperatures melt ice. Melting ice raises the sea level.

But in Sea Levels Were Significantly Higher in the Mid to Late Holocene at Pre Industrial Levels of CO2, I reviewed multiple peer-reviewed reconstructions showing that regional sea levels during the mid to late Holocene were, in many places, higher than today. These highstands occurred while atmospheric CO2 remained near 260 to 280 ppm.

Evidence from the Arabian Gulf, the southwestern Atlantic, and the southeast Australian coast indicates elevated sea levels under what we now describe as safe pre-industrial concentrations.

This does not mean CO2 has no climatic influence. It does mean that sea level does not map cleanly or uniquely onto atmospheric concentration. Glacio isostatic adjustment, meltwater redistribution, and regional dynamics complicate the picture.

Once again, the boundary between safe and dangerous becomes difficult to identify.

The Asymmetry

Taken together, these observations produce a striking asymmetry.

There is clear evidence that very low CO2 concentrations coincide with biospheric stress and glacial amplification.

There is far less clarity about a specific upper danger threshold anywhere near modern levels.

And yet policy treats 280 ppm as a moral baseline.

Why?

Why was the concentration that happened to exist before industrialization elevated to the status of climatic ideal?

Below the paywall, I will attempt to answer the original question directly. Not rhetorically. Not politically. But analytically.

If the objective were maximizing biospheric productivity, minimizing glacial instability, preserving adaptability, and supporting human flourishing, what atmospheric CO2 range would we rationally choose?

Subscribers receive the full stability framework, the plant physiology constraints, the radiative forcing context, and a direct answer grounded in the evidence reviewed above.

Game-Changer: Scientists Now Forecast Dangerous Solar Superstorms – Windows of Risk Revealed

An international team of scientists (including researchers associated with CERES-Science and others) has developed the first probabilistic forecasting system specifically for super flares- extremely powerful solar eruptions classified as “S-class” (soft X-ray flux exceeding X10, or more than 10 times stronger than typical X-class flares). These events release massive energy, potentially launching coronal mass ejections (CMEs) that could trigger severe geomagnetic storms on Earth, risking blackouts, satellite damage, communication disruptions, and radiation hazards for astronauts.

**NASA: Six Solar Flares Erupted February 1-4, 2026**

*(source: NASA* *https://x.com/nasagoddard/status/2019495176759124227?s=43*; https://science.nasa.gov/blogs/solar-cycle-25/)

These events release massive energy, potentially launching coronal mass ejections (CMEs) that could trigger severe geomagnetic storms on Earth, risking blackouts, satellite damage, communication disruptions, and radiation hazards for astronauts.

They’ve developed the first probabilistic forecasting model for S-class super Flares (extreme solar flares with soft X-ray flux > X10, far stronger than typical X-class events). These can drive massive coronal mass ejections (CMEs), leading to potentially catastrophic geomagnetic storms—think grid blackouts, satellite failures, GPS/radio disruptions, and high radiation risks.

This gives operators (power grids, satellites, space agencies) 1-2 years’ lead time to harden systems, delay launches, or activate contingencies-far better than current short-term (hours- days) CME arrival alerts from NOAA/SWPC.

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From The CERES- Science

Scientists Successfully Predict When and Where Dangerous Solar Storms Are Likely to Happen

Breakthrough forecasting method validated by surprise solar eruptions on the far side of the Sun

Mexico City, Mexico – February 14, 2026.

A team of scientists from around the world has created the first system that can predict when and where extremely powerful solar storms, called superflares, are most likely to happen. These storms can disrupt power grids, communications, and satellites, and even pose dangers to astronauts in space.

Instead of trying to predict the exact moment a solar storm will erupt (which is nearly impossible), this new approach identifies extended windows of time—ranging from several months to a year—when the Sun is more likely to produce these extreme events. The method also pinpoints which regions of the Sun are most at risk. The research has been published in the Journal of Geophysical Research: Space Physics.

How the Forecasting System Works

The scientists analyzed nearly 50 years of data (1975–2025) from satellites that monitor the Sun’s X-ray emissions. They discovered two key patterns:

1. They identified specific zones on the Sun where magnetic energy builds up over time, making those areas more likely to produce powerful eruptions.

2. They found a rhythmic pattern in solar activity based on two natural cycles: a 1.7-year cycle and a 7-year cycle. When these cycles line up in certain ways, the risk of superflares increases significantly.

Using advanced mathematical techniques and machine learning, the team combined these patterns to forecast high-risk time periods and locations on the Sun. For the current solar cycle (Solar Cycle 25), their model predicts two main danger windows:

• Mid-2025 through mid-2026 (focused on the Sun’s southern hemisphere, between 5°S–25°S latitude)

• Early-to-mid 2027 (focused on the Sun’s northern hemisphere, between 10°N–30°N latitude)

Real-World Implications

Lead researcher Dr. Victor M. Velasco Herrera, from the National Autonomous University of Mexico, explained:

“Traditional solar forecasting struggles with these extreme events because they happen so quickly and unpredictably. Our method gives space weather operators and satellite managers one to two years of advance warning about when conditions are most dangerous. This critical lead time allows them to prepare and protect communications systems, power grids, and astronaut safety.”

Dr. Velasco Herrera also noted the relevance for space missions:

“NASA is right to postpone the Artemis II mission to the Moon until March, but given how active the Sun is right now, our forecasts suggest that delaying the launch until the end of 2026 may be a much safer decision.”

Surprise Validation from the Far Side of the Sun

The team got an unexpected confirmation of their model’s accuracy during the research process itself. After they submitted their paper for publication (between October and December 2025), other scientists using the Solar Orbiter spacecraft discovered a series of massive superflares that had erupted on the far side of the Sun—the side we can’t see from Earth. These eruptions included an X11.1 class on May 14, 2024, an X9.5 and X9.7 on May 15, 2024 and an X16.5 class on May 20, 2024, as reported coincidentally on the same day by a NASA study.

Remarkably, these newly discovered far-side events matched the patterns the team had predicted, even though they had no knowledge of these storms when developing their forecasting system.

“This was pure luck, but also very revealing,” said Dr. Velasco Herrera. “We created our forecast without knowing about these far-side superflares. When they were discovered during our paper review process, they aligned perfectly with our predicted patterns. This shows that our physics-based approach works across the entire Sun, not just the side facing Earth.”

Co-author Dr. Willie Soon, from the Center for Environmental Research and Earth Sciences (CERES), added:

“Nature gave us the perfect test. These far-side discoveries essentially validated our method in real time, proving that the underlying patterns we identified are reliable and work everywhere on the Sun’s surface.”

Why This Matters

Solar super flares are the most powerful eruptions the Sun can produce. A direct hit from one of these storms could cause widespread power outages, damage satellites, disrupt GPS navigation, interfere with radio communications, and create radiation hazards for astronauts and airline passengers at high altitudes.

By providing advance warning of when and where these events are most likely to occur, this new forecasting system gives utilities, satellite operators, and space agencies valuable time to take protective measures—such as adjusting satellite orbits, preparing backup systems, or rescheduling space missions.

As Solar Cycle 25 continues to show strong activity, this breakthrough offers a significant improvement in our ability to prepare for and mitigate the impacts of extreme space weather.

The research paper, titled ‘A New Method for Probabilistic Spatiotemporal Forecasts of Solar Soft X-ray S-Class (> X10) Superflares,’ is now published in the Journal of Geophysical Research: Space Physics (American Geophysical Union), https://doi.org/10.1029/2025JA034977.

The author team includes scientists from Mexico, the United States, Hungary, Turkey, Russia, Czech Republic, and China.

Publication Details

V. M. Velasco Herrera, G. Velasco Herrera, W. Soon, A. Özgüç, N. Babynets, A. Tlatov, M. Švanda, S. Qiu, S. Baliunas, B. Kotan, G. González González, L. A. Bautista Flores, M. Pazos (2026). “A New Method for Probabilistic Spatiotemporal Forecasts of Solar Soft X-Ray “S-Class” (>X10) Superflares“. Journal of Geophysical Research: Space Physics. 131 (2), e2025JA034977. https://doi.org/10.1029/2025JA034977

Texas Showdown: ERCOT vs Winter Storm Fern

Texans recently experienced our worst winter storm since Uri in February 2021. Here in the DFW area, the temperature dropped below freezing early on Saturday morning, January 24, and stayed below 32 °F until the afternoon of January 27. In Dallas, we experienced freezing rain, sleet and snow for two straight days (January 24-25).

From Watts Up With That?

Guest “long-time, no-posts” by David Middleton

https://www.timeanddate.com/weather/usa/dallas/historic?month=1&year=2026

Fern impacted about half of the Lower 48…

2026-01_20260125_WeatherAlerts.
https://www.nesdis.noaa.gov/news/noaa-satellites-monitor-massive-winter-storm

Things were so rough that alleged energy expert and frequent ERCOT critic Ed Hirs was predicting the imminent collapse of the grid on Saturday afternoon…

The heavy stuff won’t be here until later, and the ERCOT grid is already showing stress.

But… Somehow the ERCOT grid held up just fine…

Winter Storm Fern – January 2026
Summary
During Winter Storm Fern, ERCOT successfully managed the Texas electric grid through a period of extreme cold and freezing precipitation, utilizing available tools and resources to ensure electricity demand was met safely and reliably. The statewide grid performed well; ERCOT did not need to call for conservation, did not issue an Energy Emergency Alert (EEA), and there were no systemwide power outages.

ERCOT

Any guesses as to which generation fuel carried the load?

Electric Reliability Council of Texas, Inc. (ERCO) electricity generation by energy source 1-na24-2026 – 1-28-2026, Central Time, EIA Hourly Grid Monitor.

Natural gas carried the load, despite the fact that more gas production was shut-in due to freeze-offs than during Uri.

How could this be? Firstly, natural gas production in January 2026 was about 20 Bcf/d higher than it was in February 2021. And, secondly, more than enough gas was available in storage to cover the short-fall.

While the deep freeze temporarily spiked natural gas prices to >$30/mcf, prices quickly fell back to pre-fern levels.

From January 24 through January 27, fossil fuels and nuclear power delivered 77% of the electricity, wind delivered delivered a fairly steady 15% and the combination of solar power and batteries delivered a paltry 8% of the electricity generation desoite this…

Solar Gains Traction
Texas managed to install as much solar power capacity to its grid last year as it did in 2024, despite the lack of federal support and with the additional pressure of tariffs, the Federal Reserve Bank of Dallas found.

Despite the range of headwinds, the Dallas Fed said utility-scale solar power will remain an important source of energy for the grid in Texas for years to come.

Texas is the top state for utility-scale solar power generation. Industrial Info is tracking 25 solar projects in the state in the construction phase with a high probability of completion that are worth an estimated $9.5 billion. Greenalia Power U.S. is behind the largest of those, with a $1.04 billion project slated for Childress, Texas.

Link

If ERCOT only had more solar power and batteries!

Solar actually performed very well on the afternoon of January 26, nearly knocking coal off the grid for an hour or two…

If it walks like a duck and quacks like a duck… Peak solar delivery occurred right when demand was bottoming out. When solar power works as intended, it totally disrupts the reliable components of the grid. Fortunately, it rarely works as intended. Just two days earlier, solar delivered almost nothing…

Miliband to ‘miss net zero targets unless he spends extra £75bn’

Only £75 billion!
£75 billion, I would remind people, is more than £2700 for every household in the country.

From NOT A LOT OF PEOPLE KNOW THAT

By Paul Homewood

h/t Ian Cunningham/Ian Magness

Only £75 billion!

From the Telegraph:

Ed Miliband will fail to meet his net zero targets unless he spends an extra £75bn on renewables, a leading energy consultancy has said.

Wood Mackenzie has warned the UK does not currently have enough wind and solar to decarbonise the grid, claiming nearly all of the Energy Secretary’s 2030 clean power targets are “out of reach”.

In a new report, Wood Mackenzie said the Government must spend at least an extra £75bn on net zero by the end of this decade to have any hope of achieving its target of almost entirely clean power by 2030.

The consultancy said: “The UK has reached crunch time on climate commitments, with nearly all 2030 energy transition targets now out of reach.”

Full story here.

The full report does not appear to have been published yet, but Wood Mackenzie’s Press Release covers it all (my highlights):

The United Kingdom has reached crunch time on climate commitments, with nearly all 2030 energy transition targets now out of reach despite cutting emissions in half since 1990, according to Wood Mackenzie’s ‘United Kingdom Energy Transition Outlook 2025’.

The analysis shows the UK must close a 12-percentage-point gap by 2030, requiring an additional £75 billion in accelerated investment this decade, while cumulative low-carbon spending needs will reach £1.5-2.1 trillion through 2060. A ban on North Sea exploration has locked in structural dependence on oil and gas imports, even as offshore wind deployment lags 20% behind government targets.

Shifting priorities threaten climate momentum

The UK slashed energy-related CO2 emissions from approximately 600 million tonnes per year in 1990 to 294 Mtpa in 2025, a 51% reduction over 35 years. The government followed this success with an ambitious 2035 Nationally Determined Contribution target. However, Wood Mackenzie’s base case projects only a 56% reduction by 2030 against the NDC target of 68%.

Amidst what the analysis describes as a “new world order,” national security priorities and economic pressures now compete with climate policy for government attention and budget allocation. Defence spending and cost-of-living concerns are pulling resources away from climate initiatives, and the climate-motivated energy transition is losing urgency. Yet domestic low-carbon energy has become central to UK autonomy and global influence, creating a strategic imperative that extends beyond emissions targets.

UK Energy Transition Outlook Shows 12-Point Gap on 2030 Climate Target Despite £1.5-2.1 Trillion Investment Pathway to 2060 | Wood Mackenzie

I’m not sure how you can compare 2035 NDCs with 2030. But we know already that there is no way Miliband can meet his original 2030 Clean Power targets for offshore wind. Even if a large dollop gets contracts in the next round, they are not going to be built in time.

We can therefore regard Wood Mackenzie’s “gap” as a programme for 2030-2035. That means reducing emissions from a projected 264 Mt in 2030 to 192 Mt in 2035.

According to them, we will need an extra 13 GW of wind power and 8 GW of solar power beyond 2030, if govt targets are to be met.

The breakdown of their £75 billion is:

£45 billion for offshore wind and low carbon power

£10 billion for hydrogen and carbon capture

£8 billion for grid infrastructure

£12 billion is unidentified.

The first chunk of £45 billion does, of course, have some value – the electricity produced. But the other £30 billion is simply money down the drain.

An extra 13 GW of wind and 8 GW of solar might produce about 30 TWh, after accounting for throwing away surplus power. With officially projected gas prices of around 70p/therm, the fuel cost of CCGT output works out at around £44/MWh.

So, to replace that 30 TWh would incur a marginal cost of £1.3 billion a year.

Wood Mackenzie therefore suggest that we spend £45 billion to save £1.3 billion a year. You don’t need fancy computer models to tell you that is poor value for money! The value added would not even cover interest payments on the debt, never mind depreciation and operational costs.

£75 billion, I would remind people, is more than £2700 for every household in the country.

Coal Power Back in Trend as Globe Tries to Keep Pace with Growing Demand for Power

Euronews.com here reports that coal is expanding rapidly as again more than fifty large coal-fired power plant units were connected to the grid worldwide.

From No Trick Zone

By P Gosselin

Euronews.com here reports that coal is expanding rapidly as again more than fifty large coal-fired power plant units were connected to the grid worldwide.

*Coal power plants rapidly came on online worldwide. Symbol image, created by Grok AI*

China is showing less concern for CO2’s possible impact on the climate and went ahead and commissioned significantly more coal-fired power plants than in previous years.

“China added a total of 78 gigawatts of new coal-fired power capacity last year – a significant jump compared to previous years,” reports Euronews, citing a joint report by the Centre for Research on Energy and the Clean Air and Global Energy Monitor.

So what was behind the coal power boom last year?

Apparently, China got frustrated by blackouts in 2021 and 2022 and thus moved to build reliable coal-fired power plants. Obviously, the massive quantity of installed wind and sun capacity failed to keep the lights on constantly and reliably. The 78 added gigawatts are equivalent to Germany’s total demand for power.

But that still won’t be enough. The report says the construction of a further 83 gigawatts of coal-fired power capacity also began last year.

While Europe shuts down, China and the rest of the world are expanding their coal-fired power generation rapidly.

The University of East Anglia Discovers the Urban Heat Island Effect

The UHI phenomenon- where cities are warmer than surrounding rural areas due to human activities, buildings, paved surfaces absorbing heat, reduced vegetation, and waste heat- was first systematically observed and described in the early 19th century by Luke Howard in his studies of London’s temperatures (around 1810–1830). He documented higher urban temperatures, especially at night, compared to rural sites.

Recent UEA work (published February 2026 in PNAS) focuses on how climate change amplifies or intensifies the UHI effect in many tropical and subtropical cities under ~2°C global warming.

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From Watts Up With That?

By Anthony Watts

From the “decades late and a dollar short” department comes the peer-reviewed exercise in the obvious. Of course, UEA was always a little bit slow. If they weren’t, we’d never have been given the gift of “Climategate.” – Anthony

Via Eurekalert:

Temperature of some cities could rise faster than expected under 2°C warming
New research led by the University of East Anglia (UEA) shows how many tropical cities are predicted to warm faster than expected under 2°C of global warming.

Cities are often warmer than rural areas due to a phenomenon known as the urban heat island, which can be influenced by various factors, such as regional climate and vegetation cover. This can lead to increased heat-related health risks for some urban populations.

Published in Proceedings of the National Academy of Sciences (PNAS), the study combined state-of-the-art climate change projections with machine learning models to show how these urban heat islands can be amplified in many tropical and subtropical cities under climate change – mostly in monsoon regions such as India, China and Western Africa.

The researchers produced projections for 104 medium-sized cities with populations ranging between 300,000 and one million.

Their results show the day-time land surface temperatures in 81 per cent of these cities are predicted to warm more than surrounding rural areas. In 16 per cent, they may rise between approximately 50 to 100 per cent higher than surrounding areas under 2°C of global warming, a benchmark likely to be reached in the second half of this century.

The cities studied are in the warmer parts of the world, which the authors say makes these increases even more significant for human health and the urban environment. Medium-sized cities also represent a large proportion of global cities, with more than 2.5 times as many in this category than those with a population over one million.

Lead author Dr Sarah Berk, who did the work while a PhD student in UEA’s School of Environmental Sciences, said: “Under climate change, cities face not only the challenge of increasing temperatures in their surrounding areas, but also the challenge of potential changes in their heat islands.

“However, while global climate models are essential for projecting future temperature changes, they are limited in their ability to capture the trends of smaller cities. Even high-resolution global models can only predict changes for the largest urban areas or megacities.

“To bridge this gap, in our study we projected changes in land surface temperature in medium-sized cities, showing that in many of them, the urban warming rate is faster than rural surroundings,” added Dr Berk, now at the University of North Carolina at Chapel Hill.

Co-author Prof Manoj Joshi, from the Climatic Research Unit at UEA, said: “Urban heat stress under climate change is an increasing concern, as many cities in the tropics and subtropics can be warmer than their rural surroundings, heightening their vulnerability to rising temperatures.

“This analysis shows even state-of-the-art projections likely underestimate future urban warming. For example, our results suggest that several cities in North- East China and northern India are projected to warm by 3°C, despite Earth System Model projections of their hinterlands showing a warming of 1.5-2°C.

“Our research enables more informed planning for the future risks to human health and the urban environment, highlighting the need to complement conventional climate modelling with approaches such as machine learning and AI.”

Prof Joshi added: “These findings also underscore the importance of investigating the effects of climate change on urban heat exposure, since climate change results in an increased frequency of extreme heat events, which can have severe human health impacts including increased mortality.”

The team excluded cities in mountain and coastal regions to remove influences of features such as hills, lakes and oceans, to ensure they captured relationships based on physical processes related to climate, rather than other differences.

In the five largest cities by population, the greatest changes are seen in Jalandhar (India), Fuyang (China) and Kirkuk (Iraq), which experience 0.7-0.8°C additional change in temperature compared to their rural surroundings.

The remaining two, Marrakech (Morocco) and Campo Grande (Brazil), see negligible differences between urban warming and that of their surroundings.

However, other cities experience significantly greater warming, for example Asyut (Egypt), Patiala (India) and Shangqui (China), which experience 1.5-2°C additional change, which is up to 100 per cent more than their hinterlands.

This work was supported by the Natural Environment Research Council and the ARIES Doctoral Training Partnership. It also involved researchers now at the Karlsruhe Institute of Technology.

‘Amplified warming in tropical and subtropical cities at 2°C climate change’, by Sarah Berk, Manoj Joshi, Peer Nowack, and Clare Goodess was published in PNAS on February 3.

Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2502873123

Texas Windpower: Will Negative Pricing Blow Out the Lights? (PTC vs. reliable new capacity)

The federal Production Tax Credit (PTC), which currently provides a $0.022/kWh subsidy to qualifying renewables, is set to expire at year-end. Just the prospect of expiration has dramatically slowed new construction of industrial wind capacity, despite a raft of other subsidies to politically correct energy.

From The Master Resource

By Josiah Neeley

Ed. note: This post by Josiah Neeley, originally published at MasterResource in November 2012, predicted the decline of reliable (dispatchable) power a decade before Storm Uri, the subject of yesterday’s post. Meanwhile, climate/renewable activists such as Chris Tomlinson (Houston Chronicle) was calling out the ‘fossil fuel-supporting Chicken Littles‘. Tomlinson (et al.) misinterpreted the event by focusing on the physical ‘why’ instead of the economic ‘why behind the why’ (here, here, and here).

“It is well known that Texas is undergoing a major challenge in maintaining resource adequacy due to improper price signals; less well known is that a significant portion of the problem can be laid directly on the doorstep of subsidies for wind generation.”

The Texas Public Policy Foundation has released a new paper looking at the effect of the production tax credit both on taxpayers and consumers. Bill Peacock and I found that PTC continuance puts the Texas electricity market at increased risk of price spikes and blackout by discouraging the construction of new reliable, on-peak generating capacity.

Texans are not only paying for the PTC’s direct annual cost of $622 million; they could pay billions of dollars more from forgone capacity given negative pricing where wind producers generate unneeded electricity just to pocket tax credits.

Background

It is well known that Texas is undergoing a major challenge in maintaining resource adequacy due to improper price signals; less well known is that a significant portion of the problem can be laid directly on the doorstep of subsidies for wind generation.

When wind is bid into the market at a negative price, superior forms of generation must match that price or risk getting knocked off the grid. This decreases the profitability of non-wind generation and makes companies less likely to invest in new capacity. This has already degraded Texas’s resource adequacy, and it could get worse before it gets better. This increases the risk of blackouts if unusual events reduce capacity and/or increase demand.

Donna Nelson, chairman of the Public Utility Commission of Texas (PUC) explains this well:

Federal incentives for renewable energy… have distorted the competitive wholesale market in ERCOT. Wind has been supported by a federal production tax credit that provides $22 per MWh of energy generated by a wind resource. With this substantial incentive, wind resources can actually bid negative prices into the market and still make a profit.

We’ve seen a number of days with a negative clearing price in the west zone of ERCOT where most of the wind resources are installed…. The market distortions caused by renewable energy incentives are one of the primary causes I believe of our current resource adequacy issue… [T]his distortion makes it difficult for other generation types to recover their cost and discourages investment in new generation.

The Northbridge Group recently published a study confirming the distortions in the market caused by the PTC. Northbridge found that the five-fold increase in wind generation since 2006 parallels the increase in negative pricing. In ERCOT, negative pricing occurred between 8 percent and 13 percent of the time from 2008 to 2011.

Percentage of Hours with Negative Real-Time Electric Energy Prices in ERCOT, 2006-11

The disruption of the Texas electrical market by negative wind prices is only going to get worse as more renewable-specific transmission lines are built, and as the frequency of negative pricing in new parts of the state comes to resemble the West Zone.

As another recent report by the Brattle Group noted:

Wind generation puts downward pressure on energy prices in all parts of ERCOT whenever the wind blows. However, the effect is greatest in the West Zone, where more than 70% of ERCOT’s wind capacity is located…

The CREZ project is primarily designed to move electricity generated by wind and other renewable resources from remote parts of Texas (i.e., West Texas and the Texas Panhandle) to the more heavily- populated areas of Texas (e.g., Austin, Dallas-Fort Worth, and San Antonio). This transmission expansion will also increase Texas’s ability to build more wind generation but may in the future erode non-wind generator economics more by depressing energy prices in the other three zones.

Wind generation puts downward pressure on energy prices in all parts of ERCOT whenever the wind blows. However, the effect is greatest in the West Zone, where more than 70% of ERCOT’s wind capacity is located…

The CREZ project is primarily designed to move electricity generated by wind and other renewable resources from remote parts of Texas (i.e., West Texas and the Texas Panhandle) to the more heavily- populated areas of Texas (e.g., Austin, Dallas-Fort Worth, and San Antonio). This transmission expansion will also increase Texas’s ability to build more wind generation but may in the future erode non-wind generator economics more by depressing energy prices in the other three zones.

The Real Cost of Wind

It is difficult to quantify the cost of the PTC’s distortions on the market, though the Foundation will address this issue more fully in an upcoming paper. But one method of doing so would be of looking at the cost of solving Texas’ resource adequacy challenges.

PUC Commissioner Ken Anderson recently did some “back of the envelope” calculations of the cost of imposing a PJM-style capacity market on ERCOT. He came up with a cost of over $3.6 billion per year. The portion of this cost that can be attributed to renewable energy subsidies is debatable, but these costs could easily exceed the costs of the direct subsidies, more than doubling the costs on consumers.

At a bare minimum, renewables energy subsidies in Texas are costing more than half a billion a year. Because of the PTC’s per megawatt hour subsidy, it causes substantially more distortion to the market than other renewable subsidies.

A credible case could be made that the PTC is more responsible than any other factor in causing ERCOT’s resource adequacy challenges and thus driving Texas toward some kind of forward capacity market.

Conclusion

Competition is working in the Texas electricity market. It is government interference with the market—led by the PTC—that is causing the current reliability challenges.

Texas need not abandon wholesale competition and move toward a capacity market. But this will be difficult to avoid as long as the PTC is in place. Congress should allow the PTC to expire; if not, we may see the end of Texas’ world-class energy-only electricity market.

—————-

[1] The PTC is only one of the subsidies available to renewable energy producers in Texas. Others available in Texas include Renewable Energy Credits (RECs) under the state’s Renewable Portfolio Standard, federal grants under the 2009 stimulus bill, and access to transmission through the Competitive Renewable Energy Zone (CREZ) program. Altogether, renewable energy subsidies in Texas, including PTC, will cost taxpayers and consumers about $12.9 billion over the same period. [The PTC, set to expire at year-end 2012, has been extended six (6) times since this post.]

———-

Josiah Neeley is a policy analyst for the Armstrong Center for Energy & the Environment at the Texas Public Policy Foundation, a non-profit, free-market research institute based in Austin. Bill Peacock, coauthor of this post, is the Vice President for Research and Director for the Center for Economic Freedom at the TPPF. [Update: Mr. Neeley is Senior Fellow and Energy Director, Texas at R-Street]

Wrong, Inside Climate News, Climate Change Isn’t Worsening Wildlife Viruses in New Jersey

Inside Climate News (ICN) recently published “Climate Change Could Make This Horrific New Jersey Wildlife Disease Worse” by Alex Megerle on February 17, 2026, claiming climate change, via warming temperatures, will intensify rana- virus outbreaks among New Jersey amphibians, producing indirect environmental and economic harms as a result. This is false, with points made in the article itself undermining the claim. Rana- virus outbreaks are driven by exposure and transmission routes in existing habitats, and ICN’s reporting concedes researchers still cannot identify consistent outbreak triggers from field variables in New Jersey, which makes the climate storyline a narrative add-on, not an evidence-based conclusion.

From The Climate Realism

By Anthony Watts

“Climate change could throw an extra wrench into the gears,” ecologist Kirsten Monsen-Collar, told Inside Climate News. “Rana- virus has a temperature range where it’s optimally active and infectious, and it tends to be more infectious at higher temperatures.

“A small temperature increase could make it more likely that pathogens will infect and spread faster within organisms, but going above their limit could actually prevent infection,” Monsen- Collar continued, noting that any predicted outcome and climate connection is speculation at best “We don’t know, we’re all kind of waving our hands, predicting, ‘Well, we think that this could happen . . . and we’re kind of just holding on to our seats, waiting to see what is going to happen.”

Concerning the wildlife-health references actually listed as transmission vectors for the disease, the World Organization for Animal Health explains that rana- viruses spread via direct contact with infected animals, ingestion of viral particles, and contact with contaminated surfaces, including water and soil. It also flags fomites, meaning human- mediated spread on gear and materials. That is the real- world “vector” discussion, and “temperature” is not on that list because temperature is not a transmission pathway. The same plain-language message shows up in state wildlife guidance like the Wisconsin Department of Natural Resources rana-virus page, which again emphasizes direct contact, contaminated water or soil, and ingestion of infected tissue or contaminated material as the routes of spread.

Temperature belongs in a different category entirely: it can influence how a virus performs inside a host, or how quickly disease progresses, but that is not how pathogens move from pond to pond or from animal to animal. Even a rana- virus explainer web page that explicitly mentions temperature as one of many factors affecting infection outcomes still describes transmission as happening by direct contact, through the water, and by consuming infected tissues or fomites, meaning the movement mechanism is exposure, not a thermometer reading. ICN blurs that line, treating “warmer is worse” as if it were a field-established driver of New Jersey die-offs. It is not. Rather, it is admitted speculation layered on top of thin and inconsistent local observations.

Now, zoom out to the climate claim. Climate change is not a state-level switch that flips disease dynamics in one jurisdiction on cue. Climate is defined as average conditions over long periods, and the World Meteorological Organization uses 30-year periods as the baseline for “normal” climate. If someone wants to blame “climate change” for rana- virus in New Jersey as a matter of evidence, the minimum requirement is straightforward: measured long-term warming at the specific waterbodies in question, during the relevant biological windows, paired with a measured, long- term increase in outbreak frequency or severity that tracks those local measurements. This article does not present that observational chain.

In fact, the ICN article undermines its own climate framing with the most important field detail it reports: researchers combined multiple years of sampling and “still struggled to see any consistent pattern,” and variables like pond size, depth, canopy cover, tree species, and proximity to human impact were “not clearly associated with presence or absence of the disease.” When the honest answer from the field record is “no consistent pattern,” asserting that climate change is or might make things worse is unwarranted. No causation can be found in uncertainty. Woefully, the story redirects the reader away from the messy, local, measurable drivers that actually control disease ecology, and thus take attention away from real world prevention measures having nothing to do with reducing greenhouse gas emissions.

The article also glides past a more practical and well-documented point: human activity is a direct mechanism for spreading amphibian pathogens between sites, which is why formal disinfection protocols exist in the first place. A Northeast Partners in Amphibian and Reptile Conservation field protocol lays out routine disinfection steps for gear because contaminated equipment and footwear move pathogens across locations. The United States Geological Survey publications on herpetofaunal pathogen disinfection similarly treat human- mediated transport, and not human caused climate change, as a serious problem worth addressing with standardized procedures. In a state as densely populated, developed, and heavily traveled as New Jersey, treating “warming” as the headline driver while downplaying boots, buckets, bait, sampling gear, stocking practices, and habitat disturbance is not “following the evidence,” it is hyping the “climate change causes everything bad,” narrative.

Inside Climate News is right to describe rana- virus as a serious wildlife disease. But attempting to link its spread to climate change is unwarranted. The story admits the outbreaks have no clear, consistent environmental trigger in the data, then pivots to climate change anyway, making this irresponsible reporting on a dangerous pathogen.

Day: February 19, 2026

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The University of East Anglia Discovers the Urban Heat Island Effect

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Wrong, Inside Climate News, Climate Change Isn’t Worsening Wildlife Viruses in New Jersey

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