Are we using bad data?

Score another win for the skeptics.
Ross McKitrick: The important climate study you won’t hear about
Guest Blogger
…the atmosphere has warmed at half the average rate predicted by climate models over the same period.

". . . Zou’s team notes that their findings “have strong implications for trends in climate model simulations and other observations” because the atmosphere has warmed at half the average rate predicted by climate models over the same period. They also note that their findings are “consistent with conclusions in McKitrick and Christy (2020),” namely that climate models have a pervasive global warming bias. In other research, Christy and mathematician Richard McNider have shown that the satellite warming rate implies the climate system can only be half as sensitive to GHGs as the average model used by the IPCC for projecting future warming.

Strong implications, indeed, but you won’t learn about it from the IPCC. That group regularly puts on a charade of pretending to review the science before issuing press releases that sound like Greta’s Twitter feed. In the real world the evidence against the alarmist predictions from overheated climate models is becoming unequivocal. One day, even the IPCC might find out."

 

Gavin Schmidt trying to wish his problem away.
The error of the mean: a dispute between Gavin Schmidt and Nicola Scafetta
Andy May
By Andy May Here we go again, writing on the proper use of statistics in climate science. Traditionally, the most serious errors in statistical analysis are made in the social…

 

Another Day, Another CO2-Is-A-Climate-Driver Inconsistency
By Kenneth Richard on 13. April 2023

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The global mean surface temperature (GMST) effects of a 1 W/m² radiative forcing, or positive/negative energy imbalance, has been gleaned from the observations from the 1991 Mt. Pinatubo eruption. CO2’s climate effects are claimed to be many times larger than observations indicate.
The observed climate sensitivity (CS) to a perturbation to Earth’s Energy Imbalance (EEI) is, in a new study (Pauling et al., 2023), defined as -0.4°C per -9 W/m², or 0.044°C per W/m². These values were gleaned from observations from Mt. Pinatubo.



Image Source: Pauling et al., 2023

 

Fiddling with temperature down under.
Bureau Releases Limited Parallel Data from Brisbane Airport

April 15, 2023 By jennifer


How accurate is the official temperature history for your city or town? Statistical analysis of 3 years of maximum temperature data for Brisbane airport shows the temperatures recorded from the probe in an automatic weather station are … [Read more...]

 

Mercury Thermometers Versus Probes in Automatic Weather Stations

April 19, 2023 By jennifer


The Australian Bureau of Meteorology has replaced most of its mercury thermometers with platinum resistance probes in automatic weather stations. My assessment of nearly twenty years of parallel data from Mildura, and just three years of … [Read more...]

 

Parallel Temperature Data, Except for Cape Otway Lighthouse

April 21, 2023 By jennifer


At Cape Otway Lighthouse overlooking Bass Strait, the highest daily January temperature ever recorded is 43.3°C on 24th January 1982, and the lowest January temperature ever recorded is 3.3°C on 2nd January 1900. In between some 30,000 (365 x 82) … [Read more...]

 

Australia-wide assessment: climate change or instrument change?

April 23, 2023 By jennifer


In the five years following the installation of probes in automatic weather stations (AWS) as they replaced mercury thermometers across Australia, the annual frequency of extremely hot days increased by an average 18.7%. This new analysis by … [Read more...]

 

Urbanization Effects on GHCN Temperature Trends, Part IV: UHI Effects on Tmax and Tmin
April 28th, 2023
This is part 4 of my series on quantifying Urban Heat Island (UHI) effects on surface air temperatures as reported in the monthly GHCN datasets produced by NOAA.

In previous posts I showed results based upon monthly-average Tavg, which is the average of of daily maximum (Tmax) and minimum (Tmin) temperatures. Since late 2019, NOAA produces monthly average datasets for only Tavg, but since there are large differences in the UHI effects between Tmin and Tmax (urban warming is much larger at night than during the day, thus affecting Tmin more), John Christy wanted me to compute results for the older Tmax and Tmin datasets archived by NOAA.

As I have discussed previously, our computations of UHI are, I believe, rather novel since we do not classify stations as urban or rural. That is how most researchers have approached the problem. But as I have mentioned before, UHI warming occurs much more rapidly at very low population densities (PD) than it does at high population densities for the same population increase. As a result, a small population increase at a rural station can produce the same spurious warming as a large population increase at an urban station. This means that previous published results showing little difference between rural and urban trends did not actually demonstrate that homogenization methods actually remove UHI effects from temperature trends.

Instead of classifying stations as either rural or urban, we use regression to compute the slope of temperature-vs-population density in many sub-intervals of 2-station pair average population density, from near-zero PD to very high PD values. Then we integrate these regression slopes through the full range of population densities.

Since NOAA’s GHCN Tmax and Tmin dataset (v3) does not have nearly as many stations as their newer (v4) Tavg dataset, I have combined the 2-station matchups for May, June, and July rather than showing results for an individual month. I have used all matchups every ten years from 1880, 1890, 1900,… 2010 that are within 150 km and 300 m elevation of each other. All land stations from 20N to 80N latitude are included. I have computed results for both the unadjusted data as well as the adjusted (homogenized) data.

The results (below) show that the total UHI effect in summer for highly-populated stations averages 3.5 times as large in Tmin as it does in Tmax. Each curve is based upon approximately 300,000 monthly 2-station matchups.


The nonlinearity of the relationship is, as other investigators have found, very strong.

Note that the UHI effect shows up more strongly in the adjusted GHCN data than in the unadjusted data. I cannot explain this. It is not because of the weeding out of bad temperature data, because that only affects regression coefficients if noise is reduced in the independent variable (2-station population density differences), and not in the dependent variable (2-station temperature differences). The 2-station PD differences do not change between the raw and adjusted GHCN data.

As I have mentioned before, the above results do not tell us the extent to which GHCN temperature trends have been affected by urbanization effects. SPOILER ALERT: My preliminary work on this suggests UHI effects are rather large between 1880 and 1980 or so, then become quite small compared to observed temperature trends. But it must be remembered that here we are using population density as a proxy for UHI, which is not necessarily optimum. It is possible for UHI effects to increase as prosperity increases for a population density that remains the same.

 

Urbanization Effects on GHCN Temperature Trends, Part V: Tmin Warming at U.S. vs. non-U.S. Stations
May 1st, 2023
In my last post (Part IV) I showed how urbanization (as measured by population density) affects GHCN monthly-average Tmax and Tmin near-surface air temperatures during the warm season in the Northern Hemisphere. We are utilizing a technique that recognizes rural thermometer sites can experience large spurious warming with very small increases in population density, as has been known for over 50 years.

The urban heat island (UHI) effects on Tmin averaged 3.5 times as large as on Tmax, an unsurprising result and qualitatively consistent with previous studies. Also, I showed that the homogenization procedure NOAA uses to adjust the Tmax and Tmin temperatures caused greater UHI effects compared to raw (unadjusted) data, a result I cannot explain.

Again I will emphasize that these UHI warming results are based upon spatial comparisons between neighboring stations, and do not say anything quantitative about how much urbanization effects have spuriously warmed long-term temperature trends over land. That is indeed the goal of our study, but we have not reached that point in the analysis yet.

Here in Part V of my series on UHI I just want to show the difference between U.S. and non-U.S. stations, in this cased for adjusted (homogenized) Tmin data. This is shown in the following two plots, which are the same except the second plot has a logarithmic scale in population density.



The non-U.S. stations have a more rapid rise in UHI warming at very low population densities than the U.S. stations do, but less rapid warming at high population densities. Possible reasons for this include country differences in thermometer siting and differences in waste heat generation. I’m sure you can think of other possible reasons.

As can be seen most (over 80%) of the GHCN 2-station matchups come from the U.S. Other countries have considerably fewer 2-station matchups, for example Canada (7.8% of the Northern Hemisphere total), Japan (4.7%), Turkey (2.8%), South Korea (1.3%), and China (1.1%). These low totals are not necessarily due to a lack of stations, but to a lack of station pairs within 150 km and 300 m elevation of each other needed for my current method of analysis.

 

Bureau Can’t Dodge Differences in Temperature Data

May 1, 2023 By jennifer


Since Graham Lloyd’s article ‘Mercury Rising in BOM probe row’ was published on the front page of The Weekend Australian earlier this month, there has been some confusion regarding the availability of the parallel temperature data. These are the … [Read more...]

 

Hot, Hot, Hot
Issues & Insights



Global climate models are running warmer than reality. Read More

 

Introducing the Realitometer
Guest Blogger
Month by inexorable month, the Realitometer will show just how absurdly exaggerated were and are the official predictions of global warming on which easily-manipulated governments . . .

 

More about bad data.
The Coronation & The Guardian, Temperatures, Misinformation (Part 2)

May 7, 2023 By jennifer 2 Comments


I watched the coronation of King Charles III last night with my 92-year-old mother. She is from the same generation as the late Queen Elizabeth II, both of them having lived through World War II in London. The air raids, the bombings, the not knowing … [Read more...]

 

Jokers, Killing Dissent – While calling it Debate

May 12, 2023 By jennifer

Back in 2014, when Tony Abbott was Prime Minister of Australia, and after a series of damning articles in The Australian newspaper showing the extent to which the Bureau of Meteorology remodel historic temperature series exaggerating warming, there … [Read more...]about Jokers, Killing Dissent – While calling it Debate

Filed Under: Disinformation, InformationTagged With: climate, Temperatures

Jokers, and Temperature as Radio Chatter
May 11, 2023 By jennifer


I gave a talk yesterday, over Zoom , as you do nowadays, explaining that the Australian Bureau of Meteorology don’t really know how to measure temperatures anymore, so they take the recordings they have, and remodel them until it looks like how they … [Read more...]

 

Fake Analysis by Greg Ayers and Jane Warne – Because End Justifies Means

May 14, 2023 By jennifer


I estimate the Bureau have about 200,000 parallel temperature records. These are handwritten records of temperatures measured at the same place and the same time from a traditional mercury thermometer and the newer resistance probes. I have been … [Read more...]

 

Averaging Last Seconds Versus Bureau Peer-Review

May 15, 2023 By jennifer


In September 2017, I meet with Carl Otto Weiss. He is an Advisor to the European Institute for Climate and Energy and a former President of the German Meteorological Institute, Braunschweig. He was not particularly interested in my work on how the … [Read more...]

 

What if the airport radar was generating false record-high temperatures through random electrical noise?
By Jo Nova

Electronic sensors can pick up phantom electrical noise
In the last thirty years the Bureau has installed electronic thermometers all over the country. But unlike the old glass ones, the new sensitive equipment can not only pick up freak gusts of hot air, they can also pick up electrical interference. Theoretically, electronic thermometers could report phantom measurements induced by large electric fields, like perhaps by an airport radar as it sweeps through the electronics.

Indeed as Lance Pidgeon points out, the cable that runs from the platinum resistance probe runs out of the Stevenson screen, down the pole, under the ground and pops up at the electronic data-logger some 6 to 10 meters away. This makes for a nice long aerial ready to pick up “noise” and feed it into the data-logger. Those airport radars produce huge electric fields — all it takes is slight induction of a voltage difference across the 10m cable and voila… the data logger records a “warmer” second.

Here’s the small forgotten airport radar at Heathrow standing about 12 stories high. Imagine the power that puts out?


David Monniaux

Electromagnetic interference could also be triggered by mobile phones or radio waves, lightning, two-way radio or television broadcasting as well. Theoretically, at least, it’s possible that any “hottest ever temperature recorded” in newspaper headlines could have been generated the moment the pilot messaged the control tower. Or it could be a maintenance truck driving past, someone in the car park starting their engine or anything electronic really. This was never an issue with a glass thermometer.

As Jennifer Marohasy explains, electronic engineers appreciate this point immediately:

As an analogue engineer recently explained to me, because of all the radio interference at airports, it is not really a place to be recording temperatures with resistance probes. Yet this is exactly where most of these temperature recording devices are now located – and not just in Australia, but across the world. So, the average global mean temperature may not only include the blast from a jet plane landing at Cordoba, Spain, but also the chatter from pilots and the control tower because temperature is now primarily measured as changes in electrical current and at airports. . . .

 

Bureau Capitulates: But Overseas Model Unlikely to Solve All Temperature Measurement Issues

May 26, 2023 By jennifer


It has only taken ten years, that is how long a few of us have been detailing major problems with how the Australian Bureau of Meteorology measures daily temperatures. Now, I’m informed, the Bureau are ditching the current system and looking to … [Read more...]

 

No, that's just false. Newton's "Principia Mathematica," by far the most important scientific work ever published, was rejected in peer review.

 

And no link

why am I not surprised? Academics use citations for a reason

 

<yawn> And those who have no facts or logic to offer demand citations for indisputable facts for a reason. If you want to dispute the facts, feel free to make a fool of yourself. Otherwise, you are just bloviating.

 

No citation for a claim is an academic standard

You claim is possibly true but why should I spend my life verifying your claims

BTW read my sig

 

Well, THAT is clear bulltwang



even IF and I emphasise IF airport radars were affecting the temperature readings do you honestly think that places like Thargomindah even HAVE a radar? I mean to land RFDS you have to line the graded strip near the town which is the “landing strip” with cars at night and switch the headlights on

 

It was published in 1687, well before this "academic peer review" nonsense used religiously to "prove" climate change, er- I mean global cooling, er- global warming, or whatever name you're using this year, was ever dreamed of. Back when scientific ideas lived or died solely on the basis of being useful and empirically verifiable.

Unlike the last 50 or 60 years of the politicization of science.

 

Again - academic rigor demands citations

your claim you support it