BIG NEWS – Verified by NOAA – Poor Weather Station Siting Leads To Artificial Long Term Warming

Sierra Foothill Commentary

Based on the data collected for the Surface Station Project and analysis papers describing the results, my friend Anthony Watts has been saying for years that “surface temperature measurements (and long term trends) have been affected by encroachment of urbanization on the placement of weather stations used to measure surface air temperature, and track long term climate.”

When Ellen and I traveled across the country in the RV we visited weather stations in the historical weather network and took photos of the temperature measurement stations and the surrounding environments.

Now, NOAA has validated Anthony’s findings — weather station siting can influence the surface station long temperature record. Here some samples that were taken by other volunteers :

clip_image004Detroit_lakes_USHCN

Impacts of Small-Scale Urban Encroachment on Air Temperature Observations

Ronald D. Leeper, John Kochendorfer, Timothy Henderson, and Michael A. Palecki
https://journals.ametsoc.org/doi/10.1175/JAMC-D-19-0002.1

Abstract

A field experiment was performed in Oak Ridge, TN, with four…

View original post 248 more words

Climate data shows no recent warming in Antarctica, instead a slight cooling

Reblogged from Watts Up With That:

Below is a plot from a resource we have not used before on WUWT, “RIMFROST“. It depicts the average temperatures for all weather stations in Antarctica. Note that there is some recent cooling in contrast to a steady warming since about 1959.

Data and plot provided by http://rimfrost.no 

Contrast that with claims by Michael Mann, Eric Steig, and others who used statistical tricks to make Antarctica warm up. Fortunately, it wasn’t just falsified by climate skeptics, but rebutted in peer review too.

Data provided by http://rimfrost.no 

H/T to Kjell Arne Høyvik‏  on Twitter

ADDED:

No warming has occurred on the South Pole from 1978 to 2019 according to satellite data (UAH V6). The linear trend is flat!

SVENSMARK’s Force Majeure, The Sun’s Large Role in Climate Change

Reblogged from Watts Up With That:

GUEST: HENRIK SVENSMARK

By H. Sterling Burnett

By bombarding the Earth with cosmic rays and being a driving force behind cloud formations, the sun plays a much larger role on climate than “consensus scientists” care to admit.

The Danish National Space Institute’s Dr. Henrik Svensmark has assembled a powerful array of data and evidence in his recent study, Force Majeure the Sun’s Large Role in Climate Change.

The study shows that throughout history and now, the sun plays a powerful role in climate change. Solar activity impacts cosmic rays which are tied to cloud formation. Clouds, their abundance or dearth, directly affects the earth’s climate.

Climate models don’t accurately account for the role of clouds or solar activity in climate change, with the result they assume the earth is much more sensitive to greenhouse gas levels than it is. Unfortunately, the impact of clouds and the sun on climate are understudied because climate science has become so politicized.

Full audio interview here:  Interview with Dr. Henrick Svensmark

 

H. Sterling Burnett, Ph.D. is a Heartland senior fellow on environmental policy and the managing editor of Environment & Climate News.

The reproducibility crisis in science

Reblogged from Watts Up With That:

Dorothy Bishop describes how threats to reproducibility, recognized but unaddressed for decades, might finally be brought under control.

From Nature:

More than four decades into my scientific career, I find myself an outlier among academics of similar age and seniority: I strongly identify with the movement to make the practice of science more robust. It’s not that my contemporaries are unconcerned about doing science well; it’s just that many of them don’t seem to recognize that there are serious problems with current practices. By contrast, I think that, in two decades, we will look back on the past 60 years — particularly in biomedical science — and marvel at how much time and money has been wasted on flawed research.

How can that be? We know how to formulate and test hypotheses in controlled experiments. We can account for unwanted variation with statistical techniques. We appreciate the need to replicate observations.

Yet many researchers persist in working in a way almost guaranteed not to deliver meaningful results. They ride with what I refer to as the four horsemen of the reproducibility apocalypse: publication bias, low statistical power, P-value hacking and HARKing (hypothesizing after results are known). My generation and the one before us have done little to rein these in.

In 1975, psychologist Anthony Greenwald noted that science is prejudiced against null hypotheses; we even refer to sound work supporting such conclusions as ‘failed experiments’. This prejudice leads to publication bias: researchers are less likely to write up studies that show no effect, and journal editors are less likely to accept them. Consequently, no one can learn from them, and researchers waste time and resources on repeating experiments, redundantly.

That has begun to change for two reasons. First, clinicians have realized that publication bias harms patients. If there are 20 studies of a drug and only one shows a benefit, but that is the one that is published, we get a distorted view of drug efficacy. Second, the growing use of meta-analyses, which combine results across studies, has started to make clear that the tendency not to publish negative results gives misleading impressions.

Low statistical power followed a similar trajectory. My undergraduate statistics courses had nothing to say on statistical power, and few of us realized we should take it seriously. Simply, if a study has a small sample size, and the effect of an experimental manipulation is small, then odds are you won’t detect the effect — even if one is there.

I stumbled on the issue of P-hacking before the term existed. In the 1980s, I reviewed the literature on brain lateralization (how sides of the brain take on different functions) and developmental disorders, and I noticed that, although many studies described links between handedness and dyslexia, the definition of ‘atypical handedness’ changed from study to study — even within the same research group. I published a sarcastic note, including a simulation to show how easy it was to find an effect if you explored the data after collecting results (D. V. M. Bishop J. Clin. Exp. Neuropsychol. 12, 812–816; 1990). I subsequently noticed similar phenomena in other fields: researchers try out many analyses but report only the ones that are ‘statistically significant’.

This practice, now known as P-hacking, was once endemic to most branches of science that rely on P values to test significance of results, yet few people realized how seriously it could distort findings. That started to change in 2011, with an elegant, comic paper in which the authors crafted analyses to prove that listening to the Beatles could make undergraduates younger (J. P. Simmons et al. Psychol. Sci. 22, 1359–1366; 2011). “Undisclosed flexibility,” they wrote, “allows presenting anything as significant.”

Analysis of new NASA AIRS study: 80% of U.S. Warming has been at Night

Reblogged from Watts Up With That:

By Dr. Roy Spencer

I have previously addressed the NASA study that concluded the AIRS satellite temperatures “verified global warming trends“. The AIRS is an infrared temperature sounding instrument on the NASA Aqua satellite, providing data since late 2002 (over 16 years). All results in that study, and presented here, are based upon infrared measurements alone, with no microwave temperature sounder data being used in these products.

That reported study addressed only the surface “skin” temperature measurements, but the AIRS is also used to retrieve temperature profiles throughout the troposphere and stratosphere — that’s 99.9% of the total mass of the atmosphere.

Since AIRS data are also used to retrieve a 2 meter temperature (the traditional surface air temperature measurement height), I was curious why that wasn’t used instead of the surface skin temperature. Also, AIRS allows me to compare to our UAH tropospheric deep-layer temperature products.

So, I downloaded the entire archive of monthly average AIRS temperature retrievals on a 1 deg. lat/lon grid (85 GB of data). I’ve been analyzing those data over various regions (global, tropical, land, ocean). While there are a lot of interesting results I could show, today I’m going to focus just on the United States.

AIRS temperature trend profiles averaged over the contiguous United States, Sept. 2002 through March 2019. Gray represents an average of day and night. Trends are based upon monthly departures from the average seasonal cycle during 2003-2018. The UAH LT temperature trend (and it’s approximate vertical extent) is in violet, and NOAA surface air temperature trends (Tmax, Tmin, Tavg) are indicated by triangles. The open circles are the T2m retrievals, which appear to be less trustworthy than the Tskin retrievals.

Because the Aqua satellite observes at nominal local times of 1:30 a.m. and 1:30 p.m., this allows separation of data into “day” and “night”. It is well known that recent warming of surface air temperatures (both in the U.S. and globally) has been stronger at night than during the day, but the AIRS data shows just how dramatic the day-night difference is… keeping in mind this is only the most recent 16.6 years (since September 2002):

The AIRS surface skin temperature trend at night (1:30 a.m.) is a whopping +0.57 C/decade, while the daytime (1:30 p.m.) trend is only +0.15 C/decade. This is a bigger diurnal difference than indicated by the NOAA Tmax and Tmin trends (triangles in the above plot). Admittedly, 1:30 a.m. and 1:30 pm are not when the lowest and highest temperatures of the day occur, but I wouldn’t expect as large a difference in trends as is seen here, at least at night.

Furthermore, these day-night differences extend up through the lower troposphere, to higher than 850 mb (about 5,000 ft altitude), even showing up at 700 mb (about 12,000 ft. altitude).

This behavior also shows up in globally-averaged land areas, and reverses over the ocean (but with a much weaker day-night difference). I will report on this at some point in the future.

If real, these large day-night differences in temperature trends is fascinating behavior. My first suspicion is that it has something to do with a change in moist convection and cloud activity during warming. For instance more clouds would reduce daytime warming but increase nighttime warming. But I looked at the seasonal variations in these signatures and (unexpectedly) the day-night difference is greatest in winter (DJF) when there is the least convective activity and weakest in summer (JJA) when there is the most convective activity.

One possibility is that there is a problem with the AIRS temperature retrievals (now at Version 6). But it seems unlikely that this problem would extend through such a large depth of the lower troposphere. I can’t think of any reason why there would be such a large bias between day and night retrievals when it can be seen in the above figure that there is essentially no difference from the 500 mb level upward.

It should be kept in mind that the lower tropospheric and surface temperatures can only be measured by AIRS in the absence of clouds (or in between clouds). I have no idea how much of an effect this sampling bias would have on the results.

Finally, note how well the AIRS low- to mid-troposphere temperature trends match the bulk trend in our UAH LT product. I will be examining this further for larger areas as well.

Fake climate science and scientists

Reblogged from Watts Up With That:

Alarmists game the system to enrich and empower themselves, and hurt everyone else

by Paul Driessen

The multi-colored placard in front of a $2-million home in North Center Chicago proudly proclaimed, “In this house we believe: No human is illegal” – and “Science is real” (plus a few other liberal mantras).

I knew right away where the owners stood on climate change, and other hot-button political issues. They would likely tolerate no dissension or debate on “settled” climate science or any of the other topics.

But they have it exactly backward on the science issue. Real science is not belief – or consensus, 97% or otherwise. Real science constantly asks questions, expresses skepticism, reexamines hypotheses and evidence. If debate, skepticism and empirical evidence are prohibited – it’s pseudo-science, at best.

Real science – and real scientists – seek to understand natural phenomena and processes. They pose hypotheses that they think best explain what they have witnessed, then test them against actual evidence, observations and experimental data. If the hypotheses (and predictions based on them) are borne out by their subsequent findings, the hypotheses become theories, rules, laws of nature – at least until someone finds new evidence that pokes holes in their assessments, or devises better explanations.

Real science does not involve simply declaring that you “believe” something, It’s not immutable doctrine. It doesn’t claim “science is real” – or demand that a particular scientific explanation be carved in stone. Earth-centric concepts gave way to a sun-centered solar system. Miasma disease beliefs surrendered to the germ theory. The certainty that continents are locked in place was replaced by plate tectonics (and the realization that you can’t stop continental drift, any more than you stop climate change).

Real scientists often employ computers to analyze data more quickly and accurately, depict or model complex natural systems, or forecast future events or conditions. But they test their models against real-world evidence. If the models, observations and predictions don’t match up, real scientists modify or discard the models, and the hypotheses behind them. They engage in robust discussion and debate.

They don’t let models or hypotheses become substitutes for real-world evidence and observations. They don’t alter or “homogenize” raw or historic data to make it look like the models actually work. They don’t hide their data and computer algorithms (AlGoreRythms?), restrict peer review to closed circles of like-minded colleagues who protect one another’s reputations and funding, claim “the debate is over,” or try to silence anyone who dares to ask inconvenient questions or find fault with their claims and models. They don’t concoct hockey stick temperature graphs that can be replicated by plugging in random numbers.

In the realm contemplated by the Chicago yard sign, we ought to be doing all we can to understand Earth’s highly complex, largely chaotic, frequently changing climate system – all we can to figure out how the sun and other powerful forces interact with each other. Only in that way can we accurately predict future climate changes, prepare for them, and not waste money and resources chasing goblins.

But instead, we have people in white lab coats masquerading as real scientists. They’re doing what I just explained true scientists don’t do. They also ignore fluctuations in solar energy output and numerous other powerful, interconnected natural forces that have driven climate change throughout Earth’s history. They look only (or 97% of the time) at carbon dioxide as the principle or sole driving force behind current and future climate changes – and blame every weather event, fire and walrus death on manmade CO2.

Even worse, they let their biases drive their research and use their pseudo-science to justify demands that we eliminate all fossil fuel use, and all carbon dioxide and methane emissions, by little more than a decade from now. Otherwise, they claim, we will bring unprecedented cataclysms to people and planet.

Not surprisingly, their bad behavior is applauded, funded and employed by politicians, environmentalists, journalists, celebrities, corporate executives, billionaires and others who have their own axes to grind, their own egos to inflate – and their intense desire to profit from climate alarmism and pseudo-science.

Worst of all, while they get rich and famous, their immoral actions impoverish billions and kill millions, by depriving them of the affordable, reliable fossil fuel energy that powers modern societies.

And still these slippery characters endlessly repeat the tired trope that they “believe in science” – and anyone who doesn’t agree to “keep fossil fuels in the ground” to stop climate change is a “science denier.”

When these folks and the yard sign crowd brandish the term “science,” political analyst Robert Tracinski suggests, it is primarily to “provide a badge of tribal identity” – while ironically demonstrating that they have no real understanding of or interest in “the guiding principles of actual science.”

Genuine climate scientist (and former chair of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology) Dr. Judith Curry echoes Tracinski. Politicians like Senator Elizabeth Warren use “science” as a way of “declaring belief in a proposition which is outside their knowledge and which they do not understand…. The purpose of the trope is to bypass any meaningful discussion of these separate questions, rolling them all into one package deal – and one political party ticket,” she explains.

The ultimate purpose of all this, of course, is to silence the dissenting voices of evidence- and reality-based climate science, block creation of a Presidential Committee on Climate Science, and ensure that the only debate is over which actions to take first to end fossil fuel use … and upend modern economies.

The last thing fake/alarmist climate scientists want is a full-throated debate with real climate scientists – a debate that forces them to defend their doomsday assertions, methodologies, data manipulation … and claims that solar and other powerful natural forces are minuscule or irrelevant compared to manmade carbon dioxide that constitutes less that 0.02% of Earth’s atmosphere (natural CO2 adds another 0.02%).

Thankfully, there are many reasons for hope. For recognizing that we do not face a climate crisis, much less threats to our very existence. For realizing there is no need to subject ourselves to punitive carbon taxes or the misery, poverty, deprivation, disease and death that banning fossil fuels would cause.

Between the peak of the great global cooling scare in 1975 until around 1998, atmospheric carbon dioxide levels and temperatures did rise in rough conjunction. But then temperatures mostly flat-lined, while CO2 levels kept climbing. Now actual average global temperatures are already 1 degree F below the Garbage In-Garbage Out computer model predictions. Other alarmist forecasts are also out of touch with reality.

Instead of fearing rising CO2, we should thank it for making crop, forest and grassland plants grow faster and better, benefitting nature and humanity – especially in conjunction with slightly warmer temperatures that extend growing seasons, expand arable land and increase crop production.

The rate of sea level rise has not changed for over a century – and much of what alarmists attribute to climate change and rising seas is actually due to land subsidence and other factors.

Weather is not becoming more extreme. In fact, Harvey was the first Category 3-5 hurricane to make US landfall in a record 12 years – and the number of violent F3 to F5 tornadoes has fallen from an average of 56 per year from 1950 to 1985 to only 34 per year since then.

Human ingenuity and adaptability have enabled humans to survive and thrive in all sorts of climates, even during our far more primitive past. Allowed to use our brains, fossil fuels and technologies, we will deal just fine with whatever climate changes might confront us in the future. (Of course, another nature-driven Pleistocene-style glacier pulling 400 feet of water out of our oceans and crushing Northern Hemisphere forests and cities under mile-high walls of ice truly would be an existential threat to life as we know it.)

So if NYC Mayor Bill De Blasio and other egotistical grand-standing politicians and fake climate scientists want to ban fossil fuels, glass-and-steel buildings, cows and even hotdogs – in the name of preventing “dangerous manmade climate change” – let them impose their schemes on themselves and their own families. The rest of us are tired of being made guinea pigs in their fake-science experiments.

Paul Driessen is senior policy advisor for the Committee For A Constructive Tomorrow (CFACT) and author of articles and books on energy, environmental and human rights issues.

UAH, RSS, NOAA, UW: Which Satellite Dataset Should We Believe?

Reblogged from DrRoySpencer.com:

April 23rd, 2019 by Roy W. Spencer, Ph. D.

NOTE: See the update from John Christy below, addressing the use of RATPAC radiosonde data.

This post has two related parts. The first has to do with the recently published study of AIRS satellite-based surface skin temperature trends. The second is our response to a rather nasty Twitter comment maligning our UAH global temperature dataset that was a response to that study.

The AIRS Study

NASA’s Atmospheric InfraRed Sounder (AIRS) has thousands of infrared channels and has provided a large quantity of new remote sensing information since the launch of the Aqua satellite in early 2002. AIRS has even demonstrated how increasing CO2 in the last 15+ years has reduced the infrared cooling to outer space at the wavelengths impacted by CO2 emission and absorption, the first observational evidence I am aware of that increasing CO2 can alter — however minimally — the global energy budget.

The challenge for AIRS as a global warming monitoring instrument is that it is cloud-limited, a problem that worsens as one gets closer to the surface of the Earth. It can only measure surface skin temperatures when there are essentially no clouds present. The skin temperature is still “retrieved” in partly- (and even mostly-) cloudy conditions from other channels higher up in the atmosphere, and with “cloud clearing” algorithms, but these exotic numerical exercises can never get around the fact that the surface skin temperature can only be observed with satellite infrared measurements when no clouds are present.

Then there is the additional problem of comparing surface skin temperatures to traditional 2 meter air temperatures, especially over land. There will be large biases at the 1:30 a.m./p.m. observation times of AIRS. But I would think that climate trends in skin temperature should be reasonably close to trends in air temperature, so this is not a serious concern with me (although Roger Pielke, Sr. disagrees with me on this).

The new paper by Susskind et al. describes a 15-year dataset of global surface skin temperatures from the AIRS instrument on NASA’s Aqua satellite. ScienceDaily proclaimed that the study “verified global warming trends“, even though the period addressed (15 years) is too short to say much of anything much of value about global warming trends, especially since there was a record-setting warm El Nino near the end of that period.

Furthermore, that period (January 2003 through December 2017) shows significant warming even in our UAH lower tropospheric temperature (LT) data, with a trend 0.01 warmer than the “gold standard” HadCRUT4 surface temperature dataset (all deg. C/decade):

AIRS: +0.24
GISTEMP: +0.22
ECMWF: +0.20
Cowtan & Way: +0.19
UAH LT: +0.18
HadCRUT4: +0.17

I’m pretty sure the Susskind et al. paper was meant to prop up Gavin Schmidt’s GISTEMP dataset, which generally shows greater warming trends than the HadCRUT4 dataset that the IPCC tends to favor more. It remains to be seen whether the AIRS skin temperature dataset, with its “clear sky bias”, will be accepted as a way to monitor global temperature trends into the future.

What Satellite Dataset Should We Believe?

Of course, the short period of record of the AIRS dataset means that it really can’t address the pre-2003 adjustments made to the various global temperature datasets which significantly impact temperature trends computed with 40+ years of data.

What I want to specifically address here is a public comment made by Dr. Scott Denning on Twitter, maligning our (UAH) satellite dataset. He was responding to someone who objected to the new study, claiming our UAH satellite data shows minimal warming. While the person posting this objection didn’t have his numbers right (and as seen above, our trend even agrees with HadCRUT4 over the 2003-2017 period), Denning took it upon himself to take a swipe at us (see his large-font response, below):

Scott-Denning-tweet-1-550x733

First of all, I have no idea what Scott is talking about when he lists “towers” and “aircraft”…there has been no comprehensive comparisons of such data sources to global satellite data, mainly because there isn’t nearly enough geographic coverage by towers and aircraft.

Secondly, in the 25+ years that John Christy and I have pioneered the methods that others now use, we made only one “error” (found by RSS, and which we promptly fixed, having to do with an early diurnal drift adjustment). The additional finding by RSS of the orbit decay effect was not an “error” on our part any more than our finding of the “instrument body temperature effect” was an error on their part. All satellite datasets now include adjustments for both of these effects.

Nevertheless, as many of you know, our UAH dataset is now considered the “outlier” among the satellite datasets (which also include RSS, NOAA, and U. of Washington), with the least amount of global-average warming since 1979 (although we agree better in the tropics, where little warming has occurred). So let’s address the remaining claim of Scott Denning’s: that we disagree with independent data.

The only direct comparisons to satellite-based deep-layer temperatures are from radiosondes and global reanalysis datasets (which include all meteorological observations in a physically consistent fashion). What we will find is that RSS, NOAA, and UW have remaining errors in their datasets which they refuse to make adjustments for.

From late 1998 through 2004, there were two satellites operating: NOAA-14 with the last of the old MSU series of instruments on it, and NOAA-15 with the first new AMSU instrument on it. In the latter half of this overlap period there was considerable disagreement that developed between the two satellites. Since the older MSU was known to have a substantial measurement dependence on the physical temperature of the instrument (a problem fixed on the AMSU), and the NOAA-14 satellite carrying that MSU had drifted much farther in local observation time than any of the previous satellites, we chose to cut off the NOAA-14 processing when it started disagreeing substantially with AMSU. (Engineer James Shiue at NASA/Goddard once described the new AMSU as the “Cadillac” of well-calibrated microwave temperature sounders).

Despite the most obvious explanation that the NOAA-14 MSU was no longer usable, RSS, NOAA, and UW continue to use all of the NOAA-14 data through its entire lifetime and treat it as just as accurate as NOAA-15 AMSU data. Since NOAA-14 was warming significantly relative to NOAA-15, this puts a stronger warming trend into their satellite datasets, raising the temperature of all subsequent satellites’ measurements after about 2000.

But rather than just asserting the new AMSU should be believed over the old (drifting) MSU, let’s look at some data. Since Scott Denning mentions weather balloon (radiosonde) data, let’s look at our published comparisons between the 4 satellite datasets and radiosondes (as well as global reanalysis datasets) and see who agrees with independent data the best:

Sat-datasets-vs-sondes-reanalyses-tropics-Christy-et-al-2018-550x413
Trend differences 1979-2005 between 4 satellite datasets and either radiosondes (blue) or reanalyses (red) for the MSU2/AMSU5 tropospheric channel in the tropics. The balloon trends are calculated from the subset of gripoints where the radiosonde stations are located, whereas the reanalyses contain complete coverage of the tropics. For direct comparisons of full versus station-only grids see the paper.

Clearly, the RSS, NOAA, and UW satellite datasets are the outliers when it comes to comparisons to radiosondes and reanalyses, having too much warming compared to independent data.

But you might ask, why do those 3 satellite datasets agree so well with each other? Mainly because UW and NOAA have largely followed the RSS lead… using NOAA-14 data even when its calibration was drifting, and using similar strategies for diurnal drift adjustments. Thus, NOAA and UW are, to a first approximation, slightly altered versions of the RSS dataset.

Maybe Scott Denning was just having a bad day. In the past, he has been reasonable, being the only climate “alarmist” willing to speak at a Heartland climate conference. Or maybe he has since been pressured into toeing the alarmist line, and not being allowed to wander off the reservation.

In any event, I felt compelled to defend our work in response to what I consider (and the evidence shows) to be an unfair and inaccurate attack in social media of our UAH dataset.

UPDATE from John Christy (11:10 CDT April 26, 2019):

In response to comments about the RATPAC radiosonde data having more warming, John Christy provides the following:

The comparison with RATPAC-A referred to in the comments below is unclear (no area mentioned, no time frame).  But be that as it may, if you read our paper, RATPAC-A2 was one of the radiosonde datasets we used.  RATPAC-A2 has virtually no adjustments after 1998, so contains warming shifts known to have occurred in the Australian and U.S. VIZ sondes for example.  The IGRA dataset used in Christy et al. 2018 utilized 564 stations, whereas RATPAC uses about 85 globally, and far fewer just in the tropics where this comparison shown in the post was made.  RATPAC-A warms relative to the other radiosonde/reanalyses datasets since 1998 (which use over 500 sondes), but was included anyway in the comparisons in our paper. The warming bias relative to 7 other radiosonde and reanalysis datasets can be seen in the following plot:

RATPAC-vs-7-others-550x413

Adjusting Good Data To Make It Match Bad Data

Reblogged from RealClimateScience.com:

mwr-035-01-0007b.pdf

On election day in 2016, both satellite data sets (UAH and RSS) showed a 15 year long hiatus in global warming, and bore no resemblance to the warming trend being generated by NOAA and NASA.  I captured this image in a November 16, 2016 blog post.

Gavin Schmidt Promises To Resign | The Deplorable Climate Science Blog

This is what the same graph looks like now.

Wood for Trees: Interactive Graphs

In the next image, I overlaid the current RSS graph on the 2016 image.  You can see how RSS was adjusted to match the NASA data.

I predicted this would happen on

Look for the satellite data to be adjusted to bring it into compliance with the fully fraudulent surface temperatures. The Guardian is now working to discredit UAH, so it seems likely that RSS will soon be making big changes – to match the needs of the climate mafia. Bookmark this post.

RSSChanges

Roy Spencer at UAH made the same prediction on January 9, 2017

“I expect there will soon be a revised TLT product from RSS which shows enhanced warming, too.

Here’s what I’m predicting:

1) neither John Christy nor I will be asked to review the paper

2) it will quickly sail through peer review (our UAH V6 paper is still not in print nearly 1 year after submission)

3) it will have many authors, including climate model people and the usual model pundits (e.g. Santer), which will supposedly lend legitimacy to the new data adjustments.

Let’s see how many of my 3 predictions come true.

-Roy”

Wood for Trees: Interactive Graphs

The reason I made this prediction was because Ted Cruz used an RSS graph in a Senate hearing in March of 2015. Carl Mears at RSS then came under intense pressure to make his data match the surface temperature data.

My particular dataset (RSS tropospheric temperatures from MSU/AMSU satellites) show less warming than would be expected when compared to the surface temperatures. All datasets contain errors. In this case, I would trust the surface data a little more because the difference between the long term trends in the various surface datasets (NOAA, NASA GISS, HADCRUT, Berkeley etc) are closer to each other than the long term trends from the different satellite datasets. This suggests that the satellite datasets contain more “structural uncertainty” than the surface dataset.

Ted Cruz says satellite data show the globe isn’t warming

You can see what Mears did to bring his data into compliance. This was his web page in November 2016.

Note that after 1998, the observations are likely to be below the simulated values, indicating that the simulation as a whole are predicting too much warming.

Climate Analysis | Remote Sensing Systems

But under intense pressure,  Mears altered his own data to bring it into compliance.  The large discrepancy became a small discrepancy.

there is a small discrepancy between the model predictions and the satellite observations.

Remote Sensing Systems

The image below overlays Mears’ old graph (V3) on his new one (V4.) It is clear what he did – he  eliminated the blue error interval, and started using the high side of the interval as his temperature.

RSS V3 shows no warming since 2002.

The warming was all created by tampering with the data to eliminate the error interval.

Spreadsheet

The corruption is now complete.  NASA has announced that new satellite data matches their surface temperature data. This was done to keep the President’s Commission on Climate Security from having accurate data to work with.

All government climate data goes through the same transition in support of global warming alarm. The past keeps getting cooler, and recent years keep getting warmer.

NASA 1999   NASA 2016

Government climate agencies appear to be using Orwell’s 1984 as Standard Operating Procedure.

Native American Wisdom on Polar bears and Kappiananngittuq

Reblogged from Watts Up With That:

By Jim Steele

Native American Wisdom and Kappiananngittuq:  Polar Bears and Bowhead whales

published Pacifica Tribune April 17, 2019

What’s Natural column

clip_image001

Native American Wisdom and Kappiananngittuq: Part 1

In 2010 Nunavut’s Minister of Environment Daniel Shewchuk wrote, “Inuit hunters have a close relationship with the land and wildlife. They have observed that the overall population of polar bears in Nunavut is not declining as some suggest, but rather is thriving. No known environmental or other factors are currently posing a significant or immediate threat to polar bears overall. Furthermore, Inuit knowledge and science corroborate that the species can and will adapt to changing and severe climatic conditions, as it has done for centuries.”

The Inuit truly practice the concept of “it takes a village”. Hunters sit down in kappiananngittuq and respectfully share their observations of wildlife and their movements. Kappiananngittuq is the Inuit word for a “safe place to discuss”. Based on community discussions, Inuit have steadfastly claimed it is “The Time of the Most Polar Bears”. Overhunting has been one of the world’s greatest threats to wildlife. And the growing number of polar bears is testimony to wise hunting regulations now honored by the Inuit.

In contrast, based on questionable computer models, some western scientists have argued two-thirds of all polar bears will be extinct by the year 2030. Climate scientists like Gavin Schmidt sitting in his New York office, suggested the Inuit are in total denial. Sadly, in climate politics there is no kappiananngittuq where people safely discuss divergent knowledge. If you dare disagree with models of gloom and doom, you are attacked as an ignorant denier.

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A well-fed polar bear


In part 2, I will present abundant scientific evidence supporting Inuit claims that it is the “time of the most polar bears”. But first I present an example of the Inuit’s amazing ability to correctly diagnose changes in Arctic wildlife populations. Kappiananngittuq discussions consistently resulted in accurate conclusions, far superior to western science.

Due to overharvesting during the early 20thcentury, Bowhead whales were undeniably on the brink of extinction. In response, commercial hunting of Bowheads along the Canadian Arctic was wisely banned in 1951. Inuit subsistence hunting continued until 1979 but was later prohibited. After extensive debate, a limited licensed subsistence hunt was eventually renewed in Nunavut in 1996.

When the Inuit first petitioned to hunt the Bowhead in the 1980s, scientists argued the Bowhead population had not yet recovered to the sustainable numbers needed to safely permit subsistence hunting. The Inuit insisted scientists grossly underrepresented the whale’s abundance due to faulty surveys. It is not exactly clear how the Inuit counted, but by compiling their community’s observations, they concluded there were three times more Bowhead than scientific models suggested.

Many non-Inuit were suspicious, insinuating Inuit estimates were a self-serving calculation driven by their desire to hunt more whales. Off-hand comments portrayed Inuit estimates as mere hunches lacking written documentation and verifiable observations. Inuit science was not considered on par with hi-tech calculations.

But scientific surveys frequently suffer from a wide range of biases and inaccuracies. Models are often just the best guesses of a small group of scientists that get translated into numbers and equations. The data that feed their models are often limited by scant observations.

In the 1970s, during the Bowhead’s spring migration, scientists perched on hilltops, or pressure ridges in the ice. They counted whales as they migrated north through the open-water “leads” along the north coast of Alaska. They erroneously assumed that when the winds changed and ice temporarily closed those leads, whales stopped migrating. Only after the winds again shifted and the leads reopened, did scientists continue their count. Based on such survey assumptions, scientists modeled that only 2000-3000 Bowhead whales existed. And such small numbers meant the whales were still endangered.

In contrast Inuit hunters had always ventured much further out on the ice. Based on experience, they argued that when open-water leads closed, the whale migration still continued. The swirling pack ice always generated chaotic but sufficient springtime cracks and leads, providing whales enough opportunities to breathe.

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Bowhead Whale creating breathing hole

Bowheads also break relatively thin ice to make their own breathing holes. Whales were never restricted to large open-water leads along the coast. Thus, Inuit hunters argued the scientists had been blind to the majority of migrating whales. To their credit, western scientists re-designed their surveys to address the Inuit’s criticisms. The Inuit were proven correct, and amazingly had correctly calculated that Bowhead populations were 3 times higher than scientists had estimated. I suggest we all could benefit by debating kappiananngittuq style.


Jim Steele is the retired director of San Francisco State University’s Sierra Nevada Field Campus and authored Landscapes and Cycles: An Environmentalist’s Journey to Climate Skepticism.

The noble corruption of climate science

Reblogged from Fabius Maximus Website:

Science & Nature

Summary:  This is a story of climate science, tracing from its enthusiastic beginnings as small field – warning of a global threat –to its rich and increasingly desperate present. It is a long story, with a climax at the end.

Sign of "Corruption above" - dreamstime_105297867
ID 105297867 © Adonis1969 | Dreamstime.

The climate change campaign hits a dead end

On 24 June 1988, James Hansen’s testimony to the Senate began the campaign to fight anthropogenic global warming. During the following 31 years we have heard increasingly dire forecasts of doom. Some describe the distant future, beyond any reasonable forecasting horizon (due to both technical and social uncertainties). Some describe the near future. Many attribute almost all current extreme weather to our emissions of greenhouse gases (GHG) – using impossible to validate methods.

Karl Popper said that successful predictions, especially of the unexpected, were the gold standard of science (see here). That is a problem for climate activists. The Earth has been warming since the mid-19th century, when the Little Ice Age ended. The rate of warming in the past four decades (since 1977) is roughly the same as that during the four decades up to 1945. Anthropogenic GHG became a major factor only after WWII. So warming has occurred as predicted, but a naive forecast (without considering GHG) would have also predicted warming. There are explanations for this, but it makes model validation difficult (perhaps why it is seldom attempted: see links in section f in the For More Info section of this post).

Worse, the weather has not cooperated. Major hurricanes avoided America for 11 years, ending in 2017. Warming slowed during what climate scientists called the “pause” or “hiatus” (see links about its causes). And most forms of extreme weather have no obvious increasing trend. So surveys show little public support in America for expensive measures to fight climate change.

Activists grow desperate.

The Uninhabitable Earth” by David Wallace-Wells in New York Magazine
“Famine, economic collapse, a sun that cooks us: what climate change could wreak
– sooner than you think.”
Expanded into a book: The Uninhabitable Earth: Life After Warming.

The five ways the human race could be WIPED OUT because of global warming.”
By Rod Ardehali at the Daily Mail. H/t to the daily links at Naked Capitalism.
Promo for Falter: Has the Human Game Begun to Play Itself Out?, a book by Bill McKibben.

Activists responded to the uncooperative weather by making ever-more dire predictions (many of which have passed their due date and been proven false).  All extreme weather was “climate change.” They made more vivid propaganda (e.g., the 10:10 video, showing a teacher exploding the heads of students who do not accept her propaganda). They increased the volume of their claims, with more 2-minute hate sessions for dissenters (with lies about even eminent climate scientists). The long-term effects of this are (hopefully) small, since these fear barrages have been the Left’s go-to tactic since the 1960s (see some classics of the genre).

But one tactic might have awful long-term consequences. Many activists are climate scientists (see the many stories about depression among them, overcome by fears about their worst-case scenarios, such as this and this). Some have reacted with noble lie corruption (from Plato’s The Republic). However well-intended, it might weaken the public’s trust in science (as might the replication crisis, of which this is an example, if they learn about it).

Broken stone with "Trust" carved in it.
ID 37813605 © Lane Erickson | Dreamstime.

The Noble Lie in action

Obvious evidence of this is climate scientists’ relentless focus on RCP8.5, the worst-case scenario in the IPCC’s Fifth Assessment Report. As a good worst-case should be, it is almost impossible to happen without unlikely assumptions (details here; also see Dr. Curry’s articles). Yet it receives the majority of mentions in the climate science literature – usually with no mention of its improbable nature (see this history). Activists exaggerate these papers, whose stories are uncritically reported by journalists. A decade of this bombardment has a fraction of the Left terrified, certain that we are doomed.

For a recent example, see “A glacier the size of Florida is on track to change the course of human civilization” by “Pakalolo” at the Daily Kos. Widely reposted, quite bonkers. See the details here.

Worse, climate scientists remain silent when activists exaggerate their work, even when they materially misrepresenting it. The most extreme doomster predictions are greeted by silence. Even over-top climate doomster claims receive only mild push-back. For example, see the reactions to “The Uninhabitable Earth” by David Wallace-Wells. WaPo: “Scientists challenge magazine story about ‘uninhabitable Earth’.” Climate Feedback: “Scientists explain what New York Magazine article on “The Uninhabitable Earth” gets wrong.” It was too much even for Michael Mann.

Yet leading climate scientists are quick to loudly condemn skeptics – even fellow climate scientists – for questioning aggressive claims about climate change. Allowing activists to call scientists “deniers” for challenging the current paradigm is imo among the most irresponsible actions by leaders of science, ever. By ancient law, silence means assent to activists’ behavior. They are guilty of “aiding and abetting.” For more about this, see About the corruption of climate science.

But in the past few years, activist scientists’ desperation appears to have pushed them to take another step away from science.

Papers to generate alarmist news!

As Marc Morano of Climate Depot says, recent studies often appear designed to produce media stories for alarmists. I see several of these every week. The most recent is “Key indicators of Arctic climate change: 1971–2017” in Environmental Research Letters (April 2019), by scientists at the International Arctic Research Center at the University of Alaska-Fairbanks and the Geological Survey of Denmark and Greenland in Copenhagen. Abstract:

“Key observational indicators of climate change in the Arctic, most spanning a 47 year period (1971–2017) demonstrate fundamental changes among nine key elements of the Arctic system. …Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion that increasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. …

“The Arctic biophysical system is now clearly trending away from its 20th Century state and into an unprecedented state, with implications not only within but beyond the Arctic. The indicator time series of this study are freely downloadable at AMAP.no.”

Ecowatch describes it in their usual apocalyptic fashion: “Researchers Warn Arctic Has Entered ‘Unprecedented State’ That Threatens Global Climate Stability.

The paper is odd in several ways. It is evidence showing the broken peer-review process. Five times they describe conditions in the arctic as “unprecedented.” But they start their analysis with data from the 1970’s. Given the various kinds of long-term natural fluctuations, five decades of data is too brief a period to draw such a bold conclusion.

The authors neglect to mention that the Arctic was also warm in the 1930’s. Which is strange since one of the authors, Uma S. Bhatt, was also a co-author of a major paper on the subject: “Variability and Trends of Air Temperature and Pressure in the Maritime Arctic, 1875–2000” in the Journal of Climate, June 2003. She did not even cite it in their new paper. Abstract …

“Arctic atmospheric variability during the industrial era (1875–2000) is assessed using spatially averaged surface air temperature (SAT) and sea level pressure (SLP) records. Air temperature and pressure display strong multidecadal variability on timescales of 50–80 yr [termed low-frequency oscillation (LFO)]. Associated with this variability, the Arctic SAT record shows two maxima: in the 1930s–40s and in recent decades, with two colder periods in between.

“In contrast to the global and hemispheric temperature, the maritime Arctic temperature was higher in the late 1930s through the early 1940s than in the 1990s. …Thus, the large-amplitude multidecadal climate variability impacting the maritime Arctic may confound the detection of the true underlying climate trend over the past century. LFO-modulated trends for short records are not indicative of the long-term behavior of the Arctic climate system.

“The accelerated warming and a shift of the atmospheric pressure pattern from anticyclonic to cyclonic in recent decades can be attributed to a positive LFO phase. It is speculated that this LFO-driven shift was crucial to the recent reduction in Arctic ice cover. Joint examination of air temperature and pressure records suggests that peaks in temperature associated with the LFO follow pressure minima after 5–15 yr. Elucidating the mechanisms behind this relationship will be critical to understanding the complex nature of low-frequency variability.”

Starting their analysis in the 1970s is misleading without disclosing that was a cold spell. There was concern then about global cooling (but not a consensus). See here and here for details. Starting in the 1970’s makes current conditions look extraordinary. Since we are in the warming period following the Little Ice Age, robust comparisons should include previous warm periods, such as the Medieval Warm Period and the Holocene climatic optimum.

A later paper provides more detail, showing the temperature anomaly in 2008 was aprox. 1°C warmer than the ~1940 peak: “Role of Polar Amplification in Long-Term Surface Air Temperature Variations and Modern Arctic Warming” by Roman V. Bekryaev et al. in Journal of Climate, 15 July 2010. Is that a one standard deviation from the long-term mean? Three? Are temperatures a normal distribution? They do not say. Climate science papers often use arcane statistics, but usually ignore the basics. (Here is an as yet unpublished estimate of arctic sea ice back to the 1880s. Here is a 2017 paper with arctic temperatures and sea ice extent back to 1900)

Two comments from climate scientists on this paper.

“It is normalization of data cherry picking.”
— Dr. Judith Curry (bio). She her analysis of arctic sea ice trends here and here. She writes at Climate Etc.

“Of course, if these changes are predominantly due to the Arctic Oscillation (AO) and/or the LFO, we should see a reversal. If not, the trend would continue. Time will eventually sort this out. But a proper literature summary should still be provided with papers that might disagree with the theme of a newer paper. All peer-reviewed perspectives on this subject should be given.”
— Dr. Roger Pielke Sr. (bio).

See other examples in the comments. These kind of stories are coming along like trolleys.

This is a follow-up to About the corruption of climate science.

Bleeding eye
“Bleeding Eye” by C. Bayraktaroglu.

Conclusions

Science has been politicized, distorting its results, before. It will be again. But climate science provides essential insights on several major public policy issues. Losing reliable guidance from it could have disastrous consequences. Worse, the high public profile of climate science means that a loss of public confidence in it might affect science as a whole.

Let’s hope that the leaders of climate science come to their senses soon, despite their personal, institutional, and ideological reasons to continue on this dark path.

For More Information

Hat tip on the ERL 2019 paper to Naked Capitalism’s daily links, who uncritically run climate alarmist articles, a one-side flow of information without context – terrifying their Leftist readers (other than that, their daily links are a valuable resource – which read every morning). Hat tip on the JoC 2003 paper to Marc Morano at Climate Depot; see his article about it.

Ideas! For some shopping ideas, see my recommended books and films at Amazon.

Please like us on Facebook and follow us on Twitter. For more information see all posts about doomsters, about fear (perhaps become our greatest weakness), about the RCPs, about the keys to understanding climate change, and especially these …