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.
“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:
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.
Reblogged from Watts Up With That:
By Jim Steele
Published in Pacifica Tribune May 14, 2019
Our Urban “Climate Crisis”
Based on a globally averaged statistic, some scientists and several politicians claim we are facing a climate crisis. Although it’s wise to think globally, organisms are never affected by global averages. Never! Organisms only respond to local conditions. Always! Given that weather stations around the globe only record local conditions, it is important to understand over one third of the earth’s weather stations report a cooling trend (i.e. Fig 4 below ) Cooling trends have various local and regional causes, but clearly, areas with cooling trends are not facing a “warming climate crisis”. Unfortunately, by averaging cooling and warming trends, the local factors affecting varied trends have been obscured.
It is well known as human populations grow, landscapes lose increasing amounts of natural vegetation, experience a loss of soil moisture and are increasingly covered by heat absorbing pavement and structures. All those factors raise temperatures so that a city’s downtown area can be 10°F higher than nearby rural areas. Despite urban areas representing less than 3% of the USA’s land surface, 82% of our weather stations are located in urbanized areas. This prompts critical thinkers to ask, “have warmer urbanized landscapes biased the globally averaged temperature?” (Arctic warming also biases the global average, but that dynamic must await a future article.)
Satellite data reveal that in forested areas the maximum surface temperatures are 36°F cooler than in grassy areas, and grassy areas’ maximum surface temperatures can be 36°F cooler than the unvegetated surfaces of deserts and cities. To appreciate the warming effects of altered landscapes, walk barefoot across a cool grassy lawn on a warm sunny day and then step onto a burning asphalt roadway.
In natural areas like Yosemite National Park, maximum air temperatures are cooler now than during the 1930s. In less densely populated and more heavily forested California, maximum air temperatures across the northern two thirds of the state have not exceeded temperatures of the 1930s. In contrast, recently urbanized communities in China report rapid warming of 3°F to 9°F in just 10 years, associated with the loss of vegetation.
Although altered urban landscapes undeniably raise local temperatures, some climate researchers suggest warmer urban temperatures do not bias the globally averaged warming trend. They argue warming trends in rural areas are similar to urbanized areas. So, they theorize a warmer global temperature is simply the result of a stronger greenhouse effect. However, such studies failed to analyze how changes in vegetation and wetness can similarly raise temperatures in both rural and urban areas. For example, researchers reported overgrazing had raised grassland temperatures 7°F higher compared to grassland that had not been grazed. Heat from asphalt will increase temperatures at rural weather stations just as readily as urban stations.
To truly determine the effects of climate change on natural habitats requires observing trends from tree ring data obtained from mostly pristine landscapes. Instrumental data are overwhelmingly measured in disturbed urbanized areas. Thus, the difference between instrumental and tree ring temperature trends can illustrate to what degree landscapes changes have biased natural temperature trends. And those trends are strikingly different!
The latest reconstructions of summer temperature trends from the best tree ring data suggest the warmest 30-year period happened between 1927 and 1956. After 1956, tree rings recorded a period of cooling that lowered global temperatures by over 1°F. In contrast, although tree rings and instrumental temperatures agreed up to 1950, the instrumental temperature trend, as presented in NASA graphs, suggests a temperature plateau from 1950 to 1970 and little or no cooling. So, are these contrasting trends the result of an increased urban warming effect offsetting natural cooling?
After decades of cooling, tree ring data recorded a global warming trend but with temperatures just now reaching a warmth that approaches the 1930s and 40s. In contrast, instrumental data suggests global temperatures have risen by more than 1°F above the 1940s. Some suggest tree rings have suddenly become insensitive to recent warmth? But the different warming trends are again better explained by a growing loss of vegetation and increasing areas covered by asphalt affecting temperatures measured by thermometers compared with temperatures determined from tree ring data in natural habitats.
Humans are increasingly inhabiting urban environments with 66% of humans projected to inhabit urban areas by 2030. High population densities typically reduce cooling vegetation, reduce wetlands and soil moisture, and increase landscape areas covered by heat retaining pavements. Thus, we should expect trends biased from urbanized landscapes to continue to rise. But there is a real solution to this “urban climate crisis.” It requires increasing vegetation, creating more parks and greenbelts, restoring wetlands and streams, and reducing heat absorbing pavements and roofs. Reducing CO2 concentrations will not reduce stifling urban temperatures.
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.
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.
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
In a GWPF video released today, Dr. Susan Crockford, a Canadian wildlife…
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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):
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):
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.
Reblogged from Watts Up With That:
Antarctica consisted of a large Eastern ice sheet, a smaller Western ice sheet and the Antarctic peninsula. The Eastern ice sheet has been slightly gaining ice from 1992, but the Western ice sheet mass trend is more uncertain.
A new paper published in Geophysical Research: Atmospheres, presents a reconstruction of the surface mass balance (SMB) over the West Antarctic Ice Sheet (WAIS) spanning 1800-2010. The study is based on ice core records combined with a European reanalysis model and a regional climate model.
The results show a significant negative trend of -1.9 ± 2.2 Gt/yr over the WAIS during the 19th century but a significant positive trend of 5.4 ± 2.9 Gt/yr between 1900 and 2010. In contrast, the Antarctic Peninsula (AP) shows opposite SMB trends to the WAIS trends with different signs in the 19th and 20th centuries. The study compared the trends to large-scale atmospheric oscillations. The SMB in the AP and WAIS are significantly correlated with the Southern Annular Mode (the north–south movement of the westerly wind belt that circles Antarctica), but the correlations are unstable.
High‐spatial resolution surface mass balance (SMB) over the West Antarctic Ice Sheet (WAIS) spanning 1800‐2010 is reconstructed by means of ice core records combined with the outputs of the European Centre for Medium‐range Weather Forecasts “Interim” reanalysis (ERA‐Interim) and the latest polar version of the Regional Atmospheric Climate Model (RACMO2.3p2). The reconstruction reveals a significant negative trend (‐1.9 ± 2.2 Gt yr‐1 decade‐1) in the SMB over the entire WAIS during the 19th century, but a statistically significant positive trend of 5.4 ± 2.9 Gt yr‐1 decade‐1 between 1900 and 2010, in contrast to insignificant WAIS SMB changes during the 20th century reported earlier. At regional scales, the Antarctic Peninsula (AP) and western WAIS show opposite SMB trends, with different signs in the 19th and 20th centuries. The annual resolution reconstruction allows us to examine the relationships between SMB and large‐scale atmospheric oscillations. Although SMB over the AP and western WAIS correlates significantly with the Southern Annular Mode (SAM) due to the influence of the Amundsen Sea Low (ASL) and El Niño/Southern Oscillation (ENSO) during 1800‐2010, the significant correlations are temporally unstable, associated with the phase of SAM, ENSO and the Pacific decadal oscillation (PDO). In addition, the two climate modes seem to contribute little to variability in SMB over the whole WAIS on decadal‐centennial time scales. This new reconstruction also serves to identify unreliable precipitation trends in ERA‐Interim, and thus has potential for assessing the skill of other reanalyses or climate models to capture precipitation trends and variability.
Reblogged from Watts Up With That:
May 6, 2019 By jennifer
THE First Finding handed down by Judge Salvador Vasta in the Peter Ridd court case concerned Bramston reef off Bowen and a photograph taken in 1994 that Terry Hughes from James Cook University has been claiming proves Acropora corals that were alive in 1890 are now all dead – the fringing reef reduced to mudflat.
Meanwhile, Peter Ridd from the same university, had photographs taken in 2015 showing live Acropora and the need for quality assurance of Hughes’ claims.
Both sides were preparing evidence for over a year – with the lawyers apparently pocketing in excess of one million dollars – yet there was no interest in an independent assessment of the state of Bramston reef.
It more than once crossed my mind, that with all the money floating around for reef research and lawyers … there could perhaps be some mapping, or just one transect, at this most contentious of locations supposedly indicative of the state of the Great Barrier Reef more generally.
In his judgment Judge Salvadore Vasta was left to simply conclude that it was unclear whether there was now mudflat or coral reef where an extensive area of Acropora coral had been photographed back in 1890, but that Peter Ridd nevertheless had the right to ask the question.
Indeed, the court case and the appeal which must be lodged by tomorrow (Tuesday 7th May), is apparently all about ‘academic freedom’ and ‘employment law’, while the average Australian would perhaps be more likely to care if they got to see some coral and some fish – dead or alive.
I visited Bramston Reef over Easter because I couldn’t wait any longer to know if the corals in Peter Ridd’s 2015 photographs had been smashed by Cyclone Debbie that hovered over Bowen two years later, in April 2017.
As I drove into Bowen, I took a detour towards Edgecombe Bay, but I didn’t stop and explore – because I saw the signage warning of crocodiles.
Peter Ridd had told me that his technicians had approached from the south south-east in a rubber dinghy to get their photographs. The day I arrived (April 18, 2019), and the next, there was a strong south south-easterly wind blowing, and no-one prepared to launch a boat to take me out.
On the afternoon of Easter Friday – ignoring the signage warning of crocodiles – I walked through the mangroves to the water’s edge. I found the mudflat which Terry Hughes had claimed now covers once healthy Acropora coral and walked across it. The other side of the mudflat there was reef flat with beds of healthy Halimeda. This area of reef flat over sand extended for nearly one kilometre – before it gave way to hectares of Acropora coral.
Professor Hughes had just not walked far enough.
When, with much excitement, I showed my photographs of all the Acropora to a Bowen local. He described them as, “rubbish corals”. He seemed ashamed that the corals I had photographed at Bramston reef were not colourful.
For a coral to make the front cover of National Geographic it does need to be exceptionally colourful. Indeed, for a woman model to make the cover of Vogue magazine she needs to be exceptionally thin. But neither thin, nor colourful, is necessarily healthy. Indeed, Acropora corals are generally tan or brown in colour when they have masses of zooxanthellae and are thus growing quickly – and are healthy.
White corals have no zooxanthellae and are often dead, because they have been exposed to temperatures that are too high. Colourful corals, like thin women, are more nutrient starved and often exist in environments of intense illumination – existing near the limits of what might be considered healthy.
Such basic facts are not well understood. Instead there is an obsession with saving the Great Barrier Reef from imminent catastrophe while we are either shown pictures of bleached white dead coral, or spectacularly colourful corals from outer reefs in nutrient-starved waters … while thousands of square kilometres of healthy brown coral is ignored.
Peter Ridd did win his high-profile court case for the right to suggest there is a need for some quality assurance of the research – but I can’t see anyone getting on with this. The Science Show on our National Broadcaster, hosted by a most acclaimed scientist journalist, has reported on the case just this last weekend. Rather than launching a dinghy and having a look at Bramston Reef, Robyn Williams has replayed part of a 2008 interview with Peter Ridd, and let it be concluded that because Peter Ridd holds a minority view he is likely wrong.
Understanding the real state of the Great Barrier Reef is not a trivial question: it has implications for tourism, and the allocation of billions of dollars of public monies … with most currently allocated to those properly networked – but not necessarily knowledgeable or prepared to walk beyond a mudflat to find the corals.
To be sure to know when I post pictures at this blog, and to get the latest news regarding the Peter Ridd court case including the possible appeal by James Cook University, subscribe for my irregular email updates.
Reblogged from Watts Up With That:
Guest Post by Willis Eschenbach
I got to thinking about the relationship between the Equatorial Pacific, where we find the El Nino/La Nina phenomenon, and the rest of the world. I’ve seen various claims about what happens to the temperature in various places at various lag-times after the Nino/Nina changes. So I decided to take a look.
To do that, I’ve gotten the temperature of the NINO34 region of the Equatorial Pacific. The NINO34 region stretches from 90°W, near South America, out to 170° West in the mid-Pacific, and from 5° North to 5° South of the Equator. I’ve calculated how well correlated that temperature is with the temperatures in the whole world, at various time lags.
To start with, here’s the correlation of what the temperature of the NINO34 region is doing with what the rest of the world is doing, with no time lag. Figure 1 shows which areas of the planet move in step with or in opposition to the NINO34 region with no lag.
Now, perfect correlation is where two variables move in total lockstep. It has a value of 1.0. And if there is perfect anti-correlation, meaning whenever one variable moves up the other moves down, that has a value of minus 1.0.
There are a couple of interesting points about that first look, showing correlations with no lag. The Indian Ocean moves very strongly in harmony with the NINO34 region (red). Hmmm. However, the Atlantic doesn’t do that. Again hmmm. Also, on average northern hemisphere land is positively correlated with the NINO34 region (orange), and southern hemisphere land is the opposite, negatively correlated (blue).
Next, with a one-month lag to give the Nino/Nina effects time to start spreading around the planet, we see the following:
Here, after a month, the North Pacific and the North Atlantic both start to feel the effects. Their correlation switches from negative (blues and greens) to positive (red-orange). Next, here’s the situation after a two-month lag.
I found this result most surprising. Two months after a Nino/Nina change, the entire Northern Hemisphere strongly tends to move in the same direction as the NINO34 region moved two months earlier … and at the same time, the entire Southern Hemisphere moves in opposition to what the NINO34 region did two months earlier.
And here’s the three-month lag:
An interesting feature of the above figure is that the good correlation of the north-eastern Pacific Ocean off the west coast of North America does not extend over the continent itself.
Finally, after four months, the hemispherical pattern begins to fall apart.
Even at five months, curious patterns remain. In the northern hemisphere, the land is all negatively correlated with NINO34, and the ocean is positively correlated. But in the southern hemisphere, the land is all positively correlated and the ocean negative.
Note that this hemispheric land-ocean difference with a five-month lag is the exact opposite of the land-ocean difference with no lag shown in Figure 1.
Now … what do I make of all this?
The first thing that it brings up for me is the astounding complexity of the climate system. I mean, who would have guessed that the two hemispheres would have totally opposite strong responses to the Nino/Nina phenomenon? And who would have predicted that the land and the ocean would react in opposite directions to the Nino/Nina changes right up to the very coastlines?
Second, it would seem to offer some ability to improve long-range forecasting for certain specific areas. Positive correlation with Hawaii, North Australia, Southern Africa, and Brazil is good up to four-five months out.
Finally, it strikes me that I can run this in reverse. By that, I mean I can find all areas of the planet that are able to predict the future temperature at some pre-selected location. Like, say, what areas of the globe correlate well with whatever the UK will be doing two months from now?
Hmmm indeed …
Warmest regards to all, the mysteries of this wondrous world are endless.
Reblogged from Watts Up With That:
Institute of Atmospheric Physics, Chinese Academy of Sciences
IMAGE: Deployment of an APEX float from a German research ship.
The global ocean represents the most important component of the Earth climate system. The oceans accumulate heat energy and transport heat from the tropics to higher latitudes, responding very slowly to changes in the atmosphere. Digital gridded climatologies of the global ocean provide helpful background information for many oceanographic, geochemical and biological applications. Because both the global ocean and the observational basis are changing, periodic updates of ocean climatologies are needed, which is in line with the World Meteorological Organization’s recommendations to provide decadal updates of atmospheric climatologies.
“Constructing ocean climatologies consists of several steps, including data quality control, adjustments for instrumental biases, and filling the data gaps by means of a suitable interpolation method”, says Professor Viktor Gouretski of the University of Hamburg and a scholarship holder of the Chinese Academy of Sciences’ President’s International Fellowship Initiative (PIFI) at the Institute of Atmospheric Physics, Chinese Academy of Sciences, and the author of a report recently published in Atmospheric and Oceanic Science Letters.
“Sea water is essentially a two-component system, with a nonlinear dependency of density on temperature and salinity, with the mixing in the ocean interior taking place predominantly along isopycnal surfaces. Therefore, interpolation of oceanic parameters should be performed on isopycnals rather than on isobaric levels, to minimize production of artificial water masses. The differences between these two methods of data interpolation are most pronounced in the high-gradient regions like the Gulf Stream, Kuroshio, and Antarctic Circumpolar Current,” continues Professor Gouretski.
In his recent report, Professor Gouretski presents a new World Ocean Circulation Experiment/ARGO Global Hydrographic Climatology (WAGHC), with temperature and salinity averaged on local isopycnal surfaces. Based on high-quality ship-board data and temperature and salinity profiles from ARGO floats, the new climatology has a monthly resolution and is available on a 1/4° latitude-longitude grid.
“We have compared the WAGHC climatology with NOAA’s WOA13 gridded climatology. These climatologies represent alternative digital products, but the WAGHC has benefited from the addition of new ARGO float data and hydrographic data from the North Polar regions”, says Professor Gourteski. “The two climatologies characterize mean ocean states that are 25 years apart, and the zonally averaged section of the WAGHC-minus-WOA13 temperature difference clearly shows the ocean warming signal, with a mean temperature increase of 0.05°C for the upper 1500-m layer since 1984”.