Fatally flawed paper: trees are proxies for the jet stream – and they say ‘now we have more extreme weather’

From the UNIVERSITY OF ARIZONA and the learn Liebigs Law before you make unsupportable claims department, comes this laughable paper that was conceived by the author, Valerie Trouet, at her parents house while reading the weather section of the newspaper. The headline of the press release says it all; alarmists trying once again to make a case for “extreme weather” in the present. But, this paper has at least two fatal flaws, read on to see why.

Jet stream changes since 1960s linked to more extreme weather

Increased fluctuations in the path of the North Atlantic jet stream since the 1960s coincide with more extreme weather events in Europe such as heat waves, droughts, wildfires and flooding, reports a University of Arizona-led team.

The research is the first reconstruction of historical changes in the North Atlantic jet stream prior to the 20th century. By studying tree rings from trees in the British Isles and the northeastern Mediterranean, the team teased out those regions’ late summer weather going back almost 300 years — to 1725.

“We find that the position of the North Atlantic Jet in summer has been a strong driver of climate extremes in Europe for the last 300 years,” said Valerie Trouet, an associate professor of dendrochronology at the University of Arizona Laboratory of Tree-Ring Research.

Having a 290-year record of the position of the jet stream let Trouet and her colleagues determine that swings between northern and southern positions of the jet became more frequent in the second half of the 20th century, she said.

“Since 1960 we get more years when the jet is in an extreme position.” Trouet said, adding that the increase is unprecedented.

When the North Atlantic Jet is in the extreme northern position, the British Isles and western Europe have a summer heat wave while southeastern Europe has heavy rains and flooding, she said.

When the jet is in the extreme southern position, the situation flips: Western Europe has heavy rains and flooding while southeastern Europe has extreme high temperatures, drought and wildfires.

“Heat waves, droughts and floods affect people,” Trouet said. “The heat waves and drought that are related to such jet stream extremes happen on top of already increasing temperatures and global warming — it’s a double whammy.”

Extreme summer weather events in the American Midwest are also associated with extreme northward or southward movements of the jet stream, the authors write.

“We studied the summer position of the North Atlantic jet. What we’re experiencing now in North America is part of the same jet stream system,” Trouet said.

This winter’s extreme cold and snow in the North American Northeast and extreme warmth and dryness in California and the American Southwest are related to the winter position of the North Pacific Jet, she said.

The paper, “Recent enhanced high-summer North Atlantic Jet variability emerges from three-century context,” by Trouet and her co-authors Flurin Babst of the Swiss Federal Research Institute WSL in Birmensdorf and Matthew Meko of the UA is scheduled for publication in Nature Communications on Jan. 12. The U.S. National Science Foundation and the Swiss National Science Foundation funded the research.

“I remember quite vividly when I got the idea,” Trouet said. “I was sitting in my mom’s house in Belgium.”

While visiting her family in Belgium during the very rainy summer of 2012, Trouet looked at the newspaper weather map that showed heavy rain in northwestern Europe and extreme heat and drought in the northeastern Mediterranean.

“I had seen the exact same map in my tree-ring data,” she said. The tree rings showed that hot temperatures in the Mediterranean occurred the same years that it was cool in the British Isles — and vice versa.

The part of an annual tree ring that forms in the latter part of the growing season is called latewood. The density of the latewood in a particular tree ring reflects the August temperature that year.

Other investigators had measured the annual latewood density for trees from the British Isles and the northeastern Mediterranean for rings formed from 1978 back to 1725.

Because August temperatures in those two regions reflect the summer position of the North Atlantic jet stream, Trouet and her colleagues used those tree-ring readings to determine the historical position of the jet stream from 1725 to 1978. For the position of the jet stream from 1979 to 2015, the researchers relied on data from meteorological observations.

“There’s a debate about whether the increased variability of the jet stream is linked to man-made global warming and the faster warming of the Arctic compared to the tropics,” Trouet said.

“Part of the reason for the debate is that the data sets used to study this are quite short — 1979 to present. If you want to see if this variability is unprecedented, you need to go farther back in time — and that’s where our study comes in.”

With the discovery of much older trees in the Balkans and in the British Isles, Trouet hopes to reconstruct the path of the North Atlantic jet stream as much as 1,000 years into the past. She is also interested in reconstructing the path of the North Pacific jet stream, which influences the climate and weather over North America.


The paper: http://ift.tt/2r1SQlL (open access)

Recent enhanced high-summer North Atlantic Jet variability emerges from three-century context


A recent increase in mid-latitude extreme weather events has been linked to Northern Hemisphere polar jet stream anomalies. To put recent trends in a historical perspective, long-term records of jet stream variability are needed. Here we combine two tree-ring records from the British Isles and the northeastern Mediterranean to reconstruct variability in the latitudinal position of the high-summer North Atlantic Jet (NAJ) back to 1725 CE. We find that northward NAJ anomalies have resulted in heatwaves and droughts in northwestern Europe and southward anomalies have promoted wildfires in southeastern Europe. We further find an unprecedented increase in NAJ variance since the 1960s, which co-occurs with enhanced late twentieth century variance in the Central and North Pacific Basin. Our results suggest increased late twentieth century interannual meridional jet stream variability and support more sinuous jet stream patterns and quasi-resonant amplification as potential dynamic pathways for Arctic warming to influence mid-latitude weather.

Below are a few of of the figures from the paper and press release.

First this article showing the author coring a tree. Maybe you didn’t notice the scientific dysfunction going on in full display but I did. Note which side of the tree she’s taking a core from, and note the branches above her are either non-existent or growth stunted.

Valerie Trouet taking a pencil-thin core from an old Bosnian pine (Pinus heldreichii) growing on Mount Olympus in Greece. CREDIT Greg King Copyright 2010

Why that tree? Maybe it’s because this “climate scientist” doesn’t understand the most basic bit if science about plant growth known as Liebigs Law of the Minimum. It’s not referenced in he paper at all.

I covered this law before on WUWT in relation to the Yamal “tree ring circus” of Briffa, Mann, and company claiming that trees (and tree rings) are accurate thermometers of the past, they aren’t and the reason is simply explained by Liebigs Law of the minimum:

A look at treemometers and tree ring growth (excerpts)

I touched on the idea of trees used for dendroclimatology being rain gauges before: Bristlecone Pines: Treemometers or rain gauges ? There has obviously been years of drought when trees also did not grow as much, so how do we separate temperature and moisture in the growth analysis?

But, right now what I really want to introduce readers to is Leibig’s Barrel.

Liebig’s Law of the Minimum, often simply called Liebig’s Law or the Law of the Minimum, is a principle developed in agricultural science by Carl Sprengel (1828) and later popularized by Justus von Liebig.

It states that growth is controlled not by the total of resources available, but by the scarcest resource (limiting factor). This concept was originally applied to plant or crop growth, where it was found that increasing the amount of plentiful nutrients did not increase plant growth. Only by increasing the amount of the limiting nutrient (the one most scarce in relation to “need”) was the growth of a plant or crop improved.This principle can be summed up in the aphorism, “The availability of the most abundant nutrient in the soil is as available as the availability of the least abundant nutrient in the soil.”


Liebig’s barrel – The growth potential of a plant or tree is like a barrel with staves of unequal length. Each stave might represent different factors; light, water, nutrients. The capacity of the barrel is limited by the length of the shortest stave (in this case, water), and can only be increased by lengthening that stave. When that stave is lengthened, another becomes the limiting growth factor.

Liebig used the image of a barrel—now called Liebig’s barrel—to explain his law. Just as the capacity of a barrel with staves of unequal length is limited by the shortest stave, so a plant’s growth is limited by the nutrient in shortest supply.

Liebig’s Law has been extended to biological populations (and is commonly used in ecosystem models). For example, the growth of an organism such as a plant may be dependent on a number of different factors, such as sunlight or mineral nutrients (e.g. nitrate or phosphate). The availability of these may vary, such that at any given time one is more limiting than the others. Liebig’s Law states that growth only occurs at the rate permitted by the most limiting. For instance, in the equation below, the growth of population O is a function of the minimum of three Michaelis-Menten terms representing limitation by factors I, N and P.

 \frac{dO}{dt} = min \left( \frac{I}{k_{I} + I}, \frac{N}{k_{N} + N}, \frac{P}{k_{P} + P} \right)

It is limited to a situation where there are steady state conditions, and factor interactions are tightly controlled.

The point I’m making with all this is: If  “the total growth response of a tree is the product of all environmental factors”, and  forest modelers have to separate temperature and precipitation diameter increments, plus create different models for different forest regions, how can then one accurately divine temperature over millenia from width analysis of tree ring growth from trees in a single region?

Or for that matter, how could anyone disentangle all the elements (temperature, precipitation, solar, shade, nutrients, etc.) and tell us it’s a proxy for the jet-stream position? The answer is: they can’t.

The task is hugely full of uncertainty. And when the lead researcher cores a tree that has one side that has obviously been shaded by another adjacent tree, as seen in the press release photo, that introduces a bias that has absolute nothing to do with the jet-stream, temperature, and precipitation. If Truett pre-selected trees that looked like, which she seems to be doing in the photo, she’s no better than the flawed science of the Yamal fiasco where a single tree biased the entire temperature record.

Further, it seems she didn’t pay attention to recent literature, such as Briffa and Melvin, 2011 and Brienen et al., 2012a,b

Basically, older trees grow slower, and that mimics the temperature signal paleo researchers like Mann look for. Unless you correct for this issue, you end up with a false temperature signal, like a hockey stick in modern times. Separating a valid temperature signal from the natural growth pattern of the tree becomes a larger challenge with this correction.

Dendrochronologists observed that the older a tree was, the slower it tended to grow, even after controlling for age- and time-driven effects. The result is an artificial downward signal in the regional curve (as the older ages are only represented by the slower growing trees) and a similar artificial positive signal in the final chronology (as earlier years are only represented by the slow growing trees), an effect termed modern sample bias. When this biased chronology is used in climate reconstruction it then implies a relatively unsuitable historic climate. Obviously, the detection of long term 15 trends in tree growth, as might be caused by a changing climate or carbon fertilization, is also seriously compromised (Brienen et al., 2012b). More generally, modern sample bias can be viewed as a form of “differing-contemporaneous-growth-rate bias”, where changes in the magnitude of growth of the tree ring series included in the chronology over time (or age, in the case of the regional curve) skew the final curve, especially 20 near the ends of the chronology where series are rapidly added and removed (Briffa and Melvin, 2011).

Or this one:

A likelihood perspective on tree-ring standardization: eliminating modern sample bias

J. Cecile, C. Pagnutti, and M. Anand
University of Guelph, School of Environmental Sciences, Guelph, Canada

NONE of those papers are in her list of citations which you can view here: http://ift.tt/2CWA9kL

It seems she was as good as selecting references as she was trees.

With this kind of incompetence, she ends up with garbage data, and the output becomes little more than a statistical coswallop based on her own beliefs and uncorrected biases.

It’s science, but not as we know it.

Here’s the “output” of her paper:


Figure 1: Latitudinal position of the August Northern Hemisphere Jet. Left wings of the violins represent the August Northern Hemisphere Jet latitudinal position distribution over the instrumental period (1920–2012) for 20° longitudinal slices. Right wings represent distribution during anomalous years when the North Atlantic Jet (NAJ; 10–30°W) latitudinal position exceeded 1 stdev northwards (a) or southwards (b). Gray shading indicates significant differences between the left and right distributions (one-sided Kolmogorov–Smirnov test; p < 0.05). Background map shows August surface temperature anomalies (°C; CRUTEM3.2160) composited over the anomalous years. Composite maps were created in R with color palette adapted from the KNMI Climate Explorer (https://climexp.knmi.nl)


Figure 2. BRIT and NEMED tree-ring chronologies. a, b Pearson’s correlation maps of BRIT (a) and NEMED (b) tree-ring chronologies with gridded 1° CRU TS4.047 August temperature anomaly fields (1901–1978) over Europe. Correlation coefficients higher than 0.3 are significant at the p < 0.01 significance level. c BRIT and NEMED (inversed) tree-ring chronologies (1725–1978) and d their sample replication over time. e The 31-year running Pearson’s correlation coefficients between the BRIT and NEMED chronologies are consistently negative over the full period, except for years (1740, 1812, 1816) when external forcings created cold conditions throughout Europe. Correlation coefficients below −0.374 (dashed line) are significant at the p < 0.05 level. Correlation maps in a, b were created in the KNMI Climate Explorer (https://climexp.knmi.nl)


Figure 3. Summer NAJ reconstruction and variance. The reconstruction of the latitudinal position of the August NAJ was scaled and calibrated against NAJ position calculated based on twentieth century reanalysis data and explains 40% of its variance over the period of overlap (1920–1978; a). The NCEP/NCAR reanalysis data (1948–2016) are plotted for comparison in a. The full NAJ reconstruction (1725–1978) including combined error estimations is plotted in b. Running 31-year window number of NAJ anomalies (c), number of northern (N) and southern (S) NAJ anomalies (d), and persistence of anomalies (e) are plotted on the central year of the window for reconstructed (blue) and 20C Reanalysis (red) NAJ time series. Anomalies are defined as years when NAJ >1 stdev, with standard deviation calculated based on a merged time series of reconstructed (1725–1919) and 20C Reanalysis (1920–1978) NAJ values. Horizontal dashed lines in c–e represent the highest 31-year values over the reconstruction period (1725–1978)


Figure 5. Late twentieth century variance increase in North Atlantic and North Pacific Basin. Running (31-year window) coefficients of variance of August NAJ time series (g) are compared to time series of observed (a) and modeled (b) quasi-resonant amplification (QRA) fingerprint15, of reconstructed zonal and meridional flow in the North Pacific36 (c), and of variance in the climate dynamics of the North (d, e) and Central (f) Pacific. Variance time series include the Pacific storm track33 (31-year standard deviation; d), California Current Winter Index32 (CCWI; 31-year standard deviation; e), and NIÑO4 SST index31 (31-year variance; f). The late twentieth century increased variance period (1960–present) is highlighted in gray. Horizontal dashed line in g represents the highest 31-year values over the reconstruction period (1725–1978 CE)


via Watts Up With That?


January 13, 2018 at 03:12PM

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