The Setup is like 1315

Reblogged from Watts Up With That:

Guest Commentary by David Archibald

The area planted for corn and soybeans this season is well below historic averages. This was mostly due to waterlogged fields and flooding which precluded planting. The planting windows for corn and soybeans are now closed. The USDA crop progress reports provide weekly updates by state. For example this is the state of the corn crop in Indiana to Monday June 17:

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Figure 1: Indiana corn crop progress to Monday June 17.

The emerged crop is one month behind where it was in 2018. Which means that maturity will be one month later at best, assuming that the rest of the summer isn’t abnormally cold.

Figure 2 shows that the same situation in soybeans in Indiana:

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Figure 2: Indiana soybean crop progress to Monday June 17.

The current expectation is that the US corn crop will be down 30% on 2018 which will push the price to about $9.00 per bushel at harvest. What could make the situation a lot worse is an early frost. The Corn Belt did warm slightly over the last 100 years due to the high solar activity of the second half of the 20th century. This is shown by the cumulative growing degree days (GDD) of the first decade of the 20th century (blue lines) compared to the first decade of the 21st century (red lines) in Figure 3 for Whitestown, Indiana:

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Figure 3: Cumulative GDD for Whitestown, Indiana

Normally, for the 21st century, the corn crop is in the ground by April 27 and the crop has reached maturity with 2,500 GDD well before the normal first frost date for Whitestown of October 10. The earliest recorded date for Whitestown is September 3. That was in 1908. If that is repeated in 2019 the crop will be only 80% through its growth cycle. Yield and quality will be well down and the total crop may be 50% or less of the 2018 level.

The US will be able to feed itself but at much higher prices. Currently some 40% of the corn crop goes to ethanol production and this could be redirected to animal feed without too much trouble. But protein production would still be well down. Each 56 lb bushel of corn used in ethanol production results in 18 lbs of dried distillers grains (DDG) containing the protein. This is used as a feed supplement to pigs, chickens and cattle. Both pigs and chickens have a 25% conversion efficiency of vegetable protein to animal protein. The global warmers want us to adopt vegetarianism in order to save the planet. The public is going to get a taste of that future coming up soon. However animal fat is essential for infant neurological development and brain function so we can’t go completely vegetarian.

What is happening in the Corn Belt is a mini version of the transition from the Medieval Warm Period to the Little Ice Age. The population of Europe exploded in benign conditions of the Medieval Warm Period from 1000 AD to 1300 AD, reaching population levels that weren’t matched again until the 19th century. In fact parts of rural France have less population today than at the beginning of the 14th century.

The breakover from the Medieval Warm Period to the Little Ice Age in Europe had sustained periods of bad weather characterised by severe winters and rainy and cold summers. The Great Famine of 1315 – 1317 started with bad weather in the spring of 1315. Crop failures lasted through 1316 until the summer of 1317. The population decline over the two years is thought to be about 10%, associated with “extreme levels of crime, disease, mass death, cannibalism and infanticide.” These conditions may be less in the Mormons amongst us who are instructed to keep one year’s worth of food in stock.

The Modern Warm Period ended in 2006. Current solar activity is back to levels of the Little Ice Age. To paraphrase Santayana, those who don’t remember history are condemned to being surprised and unprepared when it repeats itself.

A large and increasing number of nations are feeding their population growth with imported grain. That is going to be become more expensive to continue, with or without an early frost in the Corn Belt. Global warming hysteria has been a consequence of very benign conditions for the OECD countries where it is concentrated. That angst will be supplanted by more basic concerns.

David Archibald is the author of American Gripen: The Solution to the F-35 Nightmare

 

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Climate science’s ‘masking bias’ problem

Climate Etc.

by Judith Curry

How valid conclusions often lay hidden within research reports, masked by plausible but unjustified conclusions reached in those reports.  And how the IPCC institutionalizes such masking errors in climate science.

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Required Reading: NIPCC 2019 Summary on Fossil Fuels

Science Matters

Those who seek the truth about global warming/climate change should welcome this latest publication from the Nongovernmental International Panel on Climate Change (NIPCC). Excerpts from the Coauthors’ introduction in italics with my bolds. H/T Lubos Motl

Climate Change Reconsidered II: Fossil Fuels assesses the costs and benefits of the use of fossil fuels (principally coal, oil, and natural gas) by reviewing scientific and economic literature on organic chemistry, climate science, public health, economic history, human security, and theoretical studies based on integrated assessment models (IAMs). It is the fifth volume in the Climate Change Reconsidered series and, like the preceding volumes, it focuses on research overlooked or ignored by the United Nations’ Intergovernmental Panel on Climate Change (IPCC).

NIPCC was created by Dr. S. Fred Singer in 2003 to provide an independent peer review of the reports of the United Nations’ Intergovernmental Panel on Climate Change (IPCC). Unlike the…

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The Greenhouse Deception Explained

NOT A LOT OF PEOPLE KNOW THAT

By Paul Homewood

A nice and concise video, well worth watching and circulating:

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Scientific Hubris and Global Warming

Reblogged from Watts Up With That:

Scientific Hubris and Global Warming

Guest Post by Gregory Sloop

Notwithstanding portrayals in the movies as eccentrics who frantically warn humanity about genetically modified dinosaurs, aliens, and planet-killing asteroids, the popular image of a scientist is probably closer to the humble, bookish Professor, who used his intellect to save the castaways on practically every episode of Gilligan’s Island. The stereotypical scientist is seen as driven by a magnificent call, not some common, base motive. Unquestionably, science progresses unerringly to the truth.

This picture was challenged by the influential twentieth-century philosopher of science Thomas Kuhn, who held that scientific ”truth” is determined not as much by facts as by the consensus of the scientific community. The influence of thought leaders, rewarding of grants, and scorn of dissenters are used to protect mainstream theory. Unfortunately, science only makes genuine progress when the mainstream theory is disproved, what Kuhn called a “paradigm shift.” Data which conflict with the mainstream paradigm are ignored instead of used to develop a better one. Like most people, scientists are ultimately motivated by financial security, career advancement, and the desire for admiration. Thus, nonscientific considerations impact scientific “truth.”

This corruption of a noble pursuit permits scientific hubris to prosper. It can only exist when scientists are less than dispassionate seekers of truth. Scientific hubris condones suppression of criticism, promotes unfounded speculation, and excuses rejection of conflicting data. Consequently, scientific hubris allows errors to persist indefinitely. However, science advances so slowly the public usually has no idea of how often it is wrong.

Reconstructing extinct organisms from fossils requires scientific hubris. The fewer the number of fossils available, the greater the hubris required for reconstruction. The original reconstruction of the peculiar organism Hallucigenia, which lived 505 million years ago, showed it upside down and backwards. This was easily corrected when more fossils were found and no harm was done.

In contrast, scientific hubris causes harm when bad science is used to influence behavior. The 17th century microscopist Nicholas Hartsoeker drew a complete human within the head of a sperm, speculating that this was what might be beneath the “skin” of a sperm. Belief in preformation, the notion that sperm and eggs contain complete humans, was common at the time. His drawing could easily have been used to demonstrate why every sperm is sacred and masturbation is a sin.

Scientific hubris has claimed many. many lives. In the mid 19th century, the medical establishment rejected Ignaz Semmelweis’ recommendation that physicians disinfect their hands prior to examining pregnant women despite his unequivocal demonstration that this practice slashed the death rate due to obstetric infections. Because of scientific hubris, “medicine has a dark history of opposing new ideas and those who proposed them.” It was only when the germ theory of disease was established two decades later that the body of evidence supporting Semmelweis’ work became impossible to ignore. The greatest harm caused by scientific hubris is that it slows progress towards the truth.

Record keeping of earth’s surface temperature began around 1880, so there is less than 150 years of quantitative data about climate, which evolves at a glacial pace. Common sense suggests that quantitative data covering multiple warming and cooling periods is necessary to give perspective about the evolution of climate. Only then will scientists be able to make an educated guess whether the 1.5 degrees Fahrenheit increase in earth’s temperature since 1930 is the beginning of sustained warming which will negatively impact civilization, or a transient blip.

The inconvenient truth is that science is in the data acquisition phase of climate study, which must be completed before there is any chance of predicting climate, if it is predictable [vide infra]. Hubris goads scientists into giving answers even when the data are insufficient.

To put our knowledge about climate in perspective, imagine an investor has the first two weeks of data on the performance of a new stock market. Will those data allow the investor to know where the stock market will be in twenty years? No, because the behavior of the many variables which determine the performance of a stock market is unpredictable. Currently, predicting climate is no different.

Scientists use data from proxies to estimate earth’s surface temperature when the real temperature is unknowable. In medicine, these substitutes are called “surrogate markers.” Because hospital laboratories are rigorously inspected and the reproducibility, accuracy, and precision of their data is verified, hospital laboratory practices provide a useful standard for evaluating the quality of any scientific data.

Surrogate markers must be validated by showing that they correlate with “gold standard” data before they are used clinically. Comparison of data from tree growth rings, a surrogate marker for earth’s surface temperature, with the actual temperature shows that correlation between the two is worsening for unknown reasons. Earth’s temperature is only one factor which determines tree growth. Because soil conditions, genetics, rainfall, competition for nutrients, disease, age, fire, atmospheric carbon dioxide concentrations and consumption by herbivores and insects affect tree growth, the correlation between growth rings and earth’s temperature is imperfect.

Currently, growth rings cannot be regarded as a valid surrogate marker for the temperature of earth’s surface. The cause of the divergence problem must be identified and somehow remedied, and the remedy validated before growth rings are a credible surrogate marker or used to validate other surrogate markers.

Data from ice cores, boreholes, corals, and lake and ocean sediments are also used as surrogate markers. These are said to correlate with each other. Surrogate marker data are interpreted as showing a warm period between c.950 and c. 1250, which is sometimes called the “Medieval Climate Optimum,” and a cooler period called the “Little Ice Age” between the 16th and 19th centuries. The data from these surrogate markers have not been validated by comparison with a quantitative standard. Therefore, they give qualitative, not quantitative data. In medical terms, qualitative data are considered to be only “suggestive” of a diagnosis, not diagnostic. This level of diagnostic certainty is typically used to justify further diagnostic testing, not definitive therapy.

Anthropogenic global warming is often presented as fact. According to the philosopher Sir Karl Popper, a single conflicting observation is sufficient to disprove a theory. For example, the theory that all swans are white is disproved by one black swan. Therefore, the goal of science is to disprove, not prove a theory. Popper described how science should be practiced, while Kuhn described how science is actually practiced. Few theories satisfy Popper’s criterion. They are highly esteemed and above controversy. These include relativity, quantum mechanics, and plate tectonics. These theories come as close to settled science as is possible.

Data conflict about anthropogenic global warming. Using data from ice cores and lake sediments, Professor Gernot Patzelt argues that over the last 10,000 years, 65% of the time earth’s temperature was warmer than today. If his data are correct, human deforestation and carbon emissions are not required for global warming and intervention to forestall it may be futile.

The definitive test of anthropogenic global warming would be to study a duplicate earth without humans. Realistically, the only way is develop a successful computer model. However, modeling climate may be impossible because climate is a chaotic system. Small changes in the initial state of a chaotic system can cause very different outcomes, making them unpredictable. This is commonly called the “butterfly effect” because of the possibility that an action as fleeting as the beating of a butterfly’s wings can affect distant weather. This phenomenon also limits the predictability of weather.

Between 1880 and 1920, increasing atmospheric carbon dioxide concentrations were not associated with global warming. These variables did correlate between 1920 and 1940 and from around 1970 to today. These associations may appear to be compelling evidence for global warming, but associations cannot prove cause and effect. One example of a misleading association was published in a paper entitled “The prediction of lung cancer in Australia 1939–1981.” According to this paper, “Lung cancer is shown to be predicted from petrol consumption figures for a period of 42 years. The mean time for the disease to develop is discussed and the difference in the mortality rate for male and females is explained.” Obviously, gasoline use does not cause lung cancer.

The idea that an association is due to cause and effect is so attractive that these claims continue to be published. Recently, an implausible association between watching television and chronic inflammation was reported. In their book Follies and Fallacies in Medicine, Skrabanek and McCormick wrote, “As a result of failing to make this distinction [between association and cause], learning from experience may lead to nothing more than learning to make the same mistakes with increasing confidence.” Failure to learn from mistakes is another manifestation of scientific hubris. Those who are old enough to remember the late 1970’s may recall predictions of a global cooling crisis based on transient glacial growth and slight global cooling.

The current situation regarding climate change is similar to that confronting cavemen when facing winter and progressively shorter days. Every day there was less time to hunt and gather food and more cold, useless darkness. Shamans must have desperately called for ever harsher sacrifices to stop what otherwise seemed inevitable. Only when science enabled man to predict the return of longer days was sacrifice no longer necessary.

The mainstream position about anthropogenic global warming is established. The endorsement of the United Nations, U.S. governmental agencies, politicians, and the media buttresses this position. This nonscientific input has contributed to the perception that anthropogenic global warming is settled science. A critical evaluation of the available data about global warming, and anthropogenic global warming in particular, allow only a guess about the future climate. It is scientific hubris not to recognize that guess for what it is.

Grazing, desertification and climate change

“There is only one option, I’ll repeat to you, only one option left to climatologists and scientists, and that is to do the unthinkable, and to use livestock, bunched and moving, as a proxy for former herds and predators, and mimic nature. There is no other alternative left to mankind.”  –Allan Savory

Reblogged from Euan Mearns’ Energy Matters:

Posted on by Euan Mearns

Open thread…..

Yesterday I watched the GWPF cliff diving walrus porn video. Afterwards, Youtube took me to this video by Allan Savory. Noting that it had over 3 million views, my blood pressure rose in view of how environmental bullshit attracts so much attention. I started to watch and was then astonished by what Allan Savory had to say.

His core message runs totally counter to conventional wisdom. Savory of course has his detractors including George Monbiot – so this should provide enough encouragement for Energy Matters’ audience to watch and to listen.

TED provide a transcript of the video.

This is an open thread where I would welcome informed opinion on Allan Savory’s proposal.

The Sierra Club have a critical review: Allan Savory’s Holistic Management Theory Falls Short on Science.

Video exposé of the groundless Netflix bid to elevate walrus to climate change icon

polarbearscience

Last month, Netflix and WWF released a collaborative nature documentary that contained an egregiously: that Pacific walrus are being forced ashore by global warming where they suffer staggering population losses. But this is a story the film producers and WWF concocted for their own purposes, not a statement supported by scientific fact.

Video title screen

Over the last month, pointed questions have been asked about what really happened in Siberia while the film crew was there – and what didn’t. Scientific documents support the conclusion that Pacific walrus are currently thriving, have not been harmed by recent sea ice losses, and are not expected to be harmed in the foreseeable future, see here, here, here, and here.  This new video explains it all.

Netflix, Attenborough and cliff-falling walruses: The making of a false climate icon

Press release

In a GWPF video released today, Dr. Susan Crockford, a Canadian wildlife…

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Half of 21st Century Warming Due to El Nino

Reblogged from Dr.RoySpencer.com  [HiFast bold]

May 13th, 2019 by Roy W. Spencer, Ph. D.

A major uncertainty in figuring out how much of recent warming has been human-caused is knowing how much nature has caused. The IPCC is quite sure that nature is responsible for less than half of the warming since the mid-1900s, but politicians, activists, and various green energy pundits go even further, behaving as if warming is 100% human-caused.

The fact is we really don’t understand the causes of natural climate change on the time scale of an individual lifetime, although theories abound. For example, there is plenty of evidence that the Little Ice Age was real, and so some of the warming over the last 150 years (especially prior to 1940) was natural — but how much?

The answer makes as huge difference to energy policy. If global warming is only 50% as large as is predicted by the IPCC (which would make it only 20% of the problem portrayed by the media and politicians), then the immense cost of renewable energy can be avoided until we have new cost-competitive energy technologies.

The recently published paper Recent Global Warming as Confirmed by AIRS used 15 years of infrared satellite data to obtain a rather strong global surface warming trend of +0.24 C/decade. Objections have been made to that study by me (e.g. here) and others, not the least of which is the fact that the 2003-2017 period addressed had a record warm El Nino near the end (2015-16), which means the computed warming trend over that period is not entirely human-caused warming.

If we look at the warming over the 19-year period 2000-2018, we see the record El Nino event during 2015-16 (all monthly anomalies are relative to the 2001-2017 average seasonal cycle):

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Fig. 1. 21st Century global-average temperature trends (top) averaged across all CMIP5 climate models (gray), HadCRUT4 observations (green), and UAH tropospheric temperature (purple). The Multivariate ENSO Index (MEI, bottom) shows the upward trend in El Nino activity over the same period, which causes a natural enhancement of the observed warming trend.

We also see that the average of all of the CMIP5 models’ surface temperature trend projections (in which natural variability in the many models is averaged out) has a warmer trend than the observations, despite the trend-enhancing effect of the 2015-16 El Nino event.

So, how much of an influence did that warm event have on the computed trends? The simplest way to address that is to use only the data before that event. To be somewhat objective about it, we can take the period over which there is no trend in El Nino (and La Nina) activity, which happens to be 2000 through June, 2015 (15.5 years):

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Fig. 2. As in Fig. 1, but for the 15.5 year period 2000 to June 2015, which is the period over which there was no trend in El Nino and La Nina activity.

Note that the observed trend in HadCRUT4 surface temperatures is nearly cut in half compared to the CMIP5 model average warming over the same period, and the UAH tropospheric temperature trend is almost zero.

One might wonder why the UAH LT trend is so low for this period, even though in Fig. 1 it is not that far below the surface temperature observations (+0.12 C/decade versus +0.16 C/decade for the full period through 2018). So, I examined the RSS version of LT for 2000 through June 2015, which had a +0.10 C/decade trend. For a more apples-to-apples comparison, the CMIP5 surface-to-500 hPa layer average temperature averaged across all models is +0.20 C/decade, so even RSS LT (which usually has a warmer trend than UAH LT) has only one-half the warming trend as the average CMIP5 model during this period.

So, once again, we see that the observed rate of warming — when we ignore the natural fluctuations in the climate system (which, along with severe weather events dominate “climate change” news) — is only about one-half of that projected by climate models at this point in the 21st Century. This fraction is consistent with the global energy budget study of Lewis & Curry (2018) which analyzed 100 years of global temperatures and ocean heat content changes, and also found that the climate system is only about 1/2 as sensitive to increasing CO2 as climate models assume.

It will be interesting to see if the new climate model assessment (CMIP6) produces warming more in line with the observations. From what I have heard so far, this appears unlikely. If history is any guide, this means the observations will continue to need adjustments to fit the models, rather than the other way around.

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!

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.