Ocean Climate Flywheel Science (Updated)

A continuing theme at this blog has been our planetary fact that Oceans Make Climate.  The initial inspiration came from Dr. Arnd Bernaerts’ insightful phrase:  “Climate is the continuation of ocean by other means.”

Posts on this topic can be accessed by the category link Ocean Climate Science.

An early post provides relevant background to today’s discussion:  The Climate Water Wheel

6m (20ft) flywheel, weighs 15 tonnes. Used at Gepps Cross, Adelaide, South Australia Meatworks

The image at the top is the cover of a fresh presentation of the ocean flywheel paradigm written by William Kininmonth, and posted at GWPF Rethinking the Greenhouse Effect.

Dr. Ralph Alexander summarized the paper in his article Ocean Currents More Important than the Greenhouse Effect.   Excerpts in italics with my bolds and added images.

A rather different challenge to the CO2 global warming hypothesis from the challenges discussed in my previous posts postulates that human emissions of CO2 into the atmosphere have only a minimal impact on the earth’s temperature. Instead, it is proposed that current global warming comes from a slowdown in ocean currents.

The daring challenge has been made in a recent paper by retired Australian meteorologist William Kininmonth, who was head of his country’s National Climate Centre from 1986 to 1998. Kininmonth rejects the claim of the IPCC (Intergovernmental Panel on Climate Change) that greenhouse gases have caused the bulk of modern global warming. The IPCC’s claim is based on the hypothesis that the intensity of cooling longwave radiation to space has been considerably reduced by the increased atmospheric concentration of gases such as CO2.

But, he says, the IPCC glosses over the fact that the earth is spherical,
so what happens near the equator is very different from what happens at the poles.

Most absorption of incoming shortwave solar radiation occurs over the tropics, where the incident radiation is nearly perpendicular to the surface. Yet the emission of outgoing longwave radiation takes place mostly at higher latitudes. Nowhere is there local radiation balance.

ERBE measurements of radiative imbalance.

In an effort by the climate system to achieve balance, atmospheric winds and ocean currents constantly transport heat from the tropics toward the poles. Kininmonth argues, however, that radiation balance can’t exist globally, simply because the earth’s average surface temperature is not constant, with an annual range exceeding 2.5 degrees Celsius (4.5 degrees Fahrenheit). This shows that the global emission of longwave radiation to space varies seasonally, so radiation to space can’t define Earth’s temperature, either locally or globally.

In warm tropical oceans, the temperature is governed by absorption of solar shortwave radiation, together with absorption of longwave radiation radiated downward by greenhouse gases; heat carried away by ocean currents; and heat (including latent heat) lost to the atmosphere. Over the last 40 years, the tropical ocean surface has warmed by about 0.4 degrees Celsius (0.7 degrees Fahrenheit).

But the warming can’t be explained by rising CO2 that went up from 341 ppm in 1982 to 417 ppm in 2022. This rise boosts the absorption of longwave radiation at the tropical surface by only 0.3 watts per square meter, according to the University of Chicago’s MODTRAN model, which simulates the emission and absorption of infrared radiation in the atmosphere. The calculation assumes clear sky conditions and tropical atmosphere profiles of temperature and relative humidity.

The 0.3 watts per square meter is too little to account for the increase in ocean surface temperature of 0.4 degrees Celsius (0.7 degrees Fahrenheit), which in turn increases the loss of latent and “sensible” (conductive) heat from the surface by about 3.5 watts per square meter, as estimated by Kininmonth.

So twelve times as much heat escapes from the tropical ocean to the atmosphere as the amount of heat entering the ocean due to the increase in CO2 level. The absorption of additional radiation energy due to extra CO2 is not enough to compensate for the loss of latent and sensible heat from the increase in ocean temperature.

The minimal contribution of CO2 is evident from the following table, which shows how the amount of longwave radiation from greenhouse gases absorbed at the tropical surface goes up only marginally as the CO2 concentration increases. The dominant greenhouse gas is water vapor, which produces 361.4 watts per square meter of radiation at the surface in the absence of CO2; its value in the table (surface radiation) is the average global tropical value.

You can see that the increase in greenhouse gas absorption from preindustrial times to the present, corresponding roughly to the CO2 increase from 300 ppm to 400 ppm, is 0.62 watts per square meter. According to the MODTRAN model, this is almost the same as the increase of 0.63 watts per square meter that occurred as the CO2 level rose from 200 ppm to 280 ppm at the end of the last ice age – but which resulted in tropical warming of about 6 degrees Celsius (11 degrees Fahrenheit), compared with warming of only 0.4 degrees Celsius (0.7 degrees Fahrenheit) during the past 40 years.

Therefore, says Kininmonth, the only plausible explanation left for warming of the tropical ocean is a slowdown in ocean currents, those unseen arteries carrying the earth’s lifeblood of warmth away from the tropics. His suggested slowing mechanism is natural oscillations of the oceans, which he describes as the inertial and thermal flywheels of the climate system.

Kininmonth observes that the overturning time of the deep-ocean thermohaline circulation is about 1,000 years. Oscillations of the thermohaline circulation would cause a periodic variation in the upwelling of cold seawater to the tropical surface layer warmed by solar absorption; reduced upwelling would lead to further heating of the tropical ocean, while enhanced upwelling would result in cooling.

Such a pattern is consistent with the approximately 1,000-year interval between the Roman and Medieval Warm Periods, and again to current global warming.

See also About Meridional Cooling and Climate Change

Arctic “Amplification” Not What You Think

Climate Dissonance: Ocean Warming or Cooling?

Climatists are manifesting cognitive dissonance, or maybe factional conflict.  They simultaneously claim the ocean current warming the North Atlantic is slowing down bringing colder weather, while also claiming the increasing ocean heat content is warming the ocean faster than ever.  The cooling alarm was noted and rebutted in a recent No Tricks Zone article 3 New Studies Show Atlantic Tipping Point Unrealistic…”Muted Response”…”Changes To Be Viewed With Caution”.

My own critique of the alarm was this post: The Cooling Also Not Our Fault

Turning Attention from the Freezing to the Overheating Ocean

The Ocean Heat scare was included in the recent UN Climate report, alongside four other claims I rebutted in the post UN False Alarms from Key Climate Indicators.The Ocean Heat Content is more complex, requiring this post of its own. The key message was this:

Ocean heat was record high. The upper 2000m depth of the ocean continued to warm in 2021 and it is expected that it will continue to warm in the future – a change which is irreversible on centennial to millennial time scales. All data sets agree that ocean warming rates show a particularly strong increase in the past two decades. The warmth is penetrating to ever deeper levels. Much of the ocean experienced at least one ‘strong’ marine heatwave at some point in 2021.

Figure 4. 1960–2021 ensemble mean time series and ensemble standard deviation (2 standard deviations, shaded) of global OHC anomalies relative to the 2005–2017 average for the 0–300 m (grey), 0–700 m (blue), 0–2 000 m (yellow) and 700–2 000 m (green) depth layers. The ensemble mean is an update of the outcome of a concerted international data and analysis effort.

Context and Background Information

Media alarms are rampant relying mostly on a publication Record-Setting Ocean Warmth Continued in 2019 in Advances in Atmospheric Sciences
Authors: Lijing Cheng, John Abraham, Jiang Zhu, Kevin E. Trenberth, John Fasullo, Tim Boyer, Ricardo Locarnini, Bin Zhang, Fujiang Yu, Liying Wan, Xingrong Chen, Xiangzhou Song, Yulong Liu, Michael E. Mann.

Reasons for doubting the paper and its claims go well beyond the listing of so many names, including several of the usual suspects. No, this publication is tarnished by its implausible provenance. It rests upon and repeats analytical mistakes that have been pointed out, but true believers carry on without batting an eye.

It started with Resplandy et al in 2018 who became an overnight sensation with their paper Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition in Nature October 2018, leading to media reports of extreme ocean heating. Nic Lewis published a series of articles at his own site and at Climate Etc. in November 2018, leading to the paper being withdrawn and eventually retracted. Those authors acknowledged the errors and did the honorable thing at the time, resulting the paper’s retraction 25 September 2019.

Then a revised version of the paper was published 27 December 2019 with the same title and stands today.  The 2019 abstract is exactly the same as the 2018 abstract (retracted), except for one sentence.

♦  2018:  We show that the ocean gained 1.33 ± 0.20 × 10^22 joules of heat per year between 1991 and 2016, equivalent to a planetary energy imbalance of 0.83 ± 0.11 watts per square metre of Earth’s surface.

♦  2019:  We show that the ocean gained 1.29 ± 0.79 × 10^22 Joules of heat per year between 1991 and 2016, equivalent to a planetary energy imbalance of 0.80 ± 0.49 W watts per square metre of Earth’s surface.

Figure 1. Argo float operation. There are about 3,500 floats in the ocean, and a total of ~10,000 floats have been used over the period of operation.

In the discussion and graphs, readers should note that 1 Zettajoule (ZJ) = 1 x 10^21 joules, and that these are energy units, not temperatures. Willis Eschenbach did a fine analysis of this OHC issue, since it depends mostly upon ARGO float measurements. From that essay:

The first thing that I wanted to do was to look at the data using more familiar units. I mean, nobody knows what 10^22 joules means in the top two kilometres of the ocean. So I converted the data from joules to degrees C. The conversion is that it takes 4 joules to heat a gram of seawater by 1°C (or 4 megajoules per tonne per degree). The other information needed is that there are 0.65 billion cubic kilometres of ocean above 2,000 metres of depth, and that seawater weighs about 1.033 tonnes per cubic metre.

The first thing is to note that 3500 floats are sampling 0.65 billion cubic km of the ocean, and the record began in 2005. The next thing is to appreciate the impact of increasing energy upon the ocean temperature.

Yes, those are ocean warming increments of a few 1/100ths of a degree kelvin.  Applying the math to Resplandy et al., we should also note the ranges of uncertainty in these estimates (ocean temps to 1/100 of a degree, really?)

Resplandy 2018: Claim 103 to 153 ZJ/decade, or warming between 0.03 to 0.05 C/decade.

Resplandy 2019:  Claim  50 to 208 ZJ/decade, or warming between 0.02 to 0.07 c/decade

And the Climate Show Goes On

Benny Peiser of GWPF objected in writing to IPCC, saying inter alia:

Your report (SROCC, p. 5-14) concludes that
” The rate of heat uptake in the upper ocean (0-700m) is very likely higher in the 1993-2017 (or .2005-2017) period compared with the 1969-1993 period (see Table 5.1).”

We would like to point out that this conclusion is based to a significant degree on a paper
by Cheng et al. (2019) which itself relies on a flawed estimate by Resplandy et al. (2018).
An authors’ correction to this paper and its ocean heat uptake (OHU) estimate was under
review for nearly a year, but in the end Nature requested that the paper be retracted
(Retraction Note, 2019).

That was not the only objection. Nic Lewis examined Cheng et al. 2019 and found it wanting. That discussion is also at Climate Etc. Is ocean warming accelerating faster than thought? The authors replied to Lewis’ critique but did not refute or correct the identified errors.

Now in 2022 the same people have processed another year of data in the same manner and then proclaim the same result. The only differences are the addition of several high profile alarmists and the subtraction of Resplandy et al. from the References.  It looks like the group is emulating MIchael Mann’s blueprint:  The Show Must Go On.  The Noble cause justifies any and all means.

Show no weaknesses, admit no mistakes, correct nothing, sue if you have to.

Footnote: Q: Is the Ocean Warming or Cooling?  A: Nobody Knows.

To enlarge, open image in new tab.




The Cooling Also Not Our Fault

With the lack of global warming and the steep decline of surface temperatures the last 6 to 8 months, climatists are pivoting to the notion invented by the infamous M. Mann, AKA Mr. Hockey Stick (aiming to erase the Medieval warming period).  The reasoning is convoluted, as you might expect given the intent to blame cold weather on global warming.  The claim is that burning fossil fuels causes the North Atlantic Current to slow down and bring cold temperatures to the Northern Hemisphere.  The video below is an excellent PR piece promoting this science fiction as though it were fact.


The link below allows you to view it in its natural habitat (USA Today)


Science Facts to Counter Science Fiction

Natural variability has dominated Atlantic Meridional Overturning Circulation since 1900
Mojib Latif et al. published April 2022 Nature Climate Change.  Excerpts in italics with my bolds.


There is debate about slowing of the Atlantic Meridional Overturning Circulation (AMOC), a key component of the global climate system. Some focus is on the sea surface temperature (SST) slightly cooling in parts of the subpolar North Atlantic despite widespread ocean warming. Atlantic SST is influenced by the AMOC, especially on decadal timescales and beyond. The local cooling could thus reflect AMOC slowing and diminishing heat transport, consistent with climate model responses to rising atmospheric greenhouse gas concentrations.

Here we show from Atlantic SST the prevalence of natural AMOC variability since 1900. This is consistent with historical climate model simulations for 1900–2014 predicting on average AMOC slowing of about 1 Sv at 30° N after 1980, which is within the range of internal multidecadal variability derived from the models’ preindustrial control runs. These results highlight the importance of systematic and sustained in-situ monitoring systems that can detect and attribute with high confidence an anthropogenic AMOC signal.


Global surface warming (global warming hereafter) since the beginning of the twentieth century is unequivocal, and humans are the main cause through the emission of vast amounts of greenhouse gases (GHGs), especially carbon dioxide (CO2)1,2,3. The oceans have stored more than 90% of the heat trapped in the climate system caused by the accumulation of GHGs in the atmosphere, thereby contributing to sea-level rise and leading to more frequent and longer lasting marine heat waves4. Moreover, the oceans have taken up about one third of the total anthropogenic CO2 emissions since the start of industrialization, causing ocean acidification5. Both ocean warming and acidification already have adverse consequences for marine ecosystems6. Some of the global warming impacts, however, unfold slowly in the ocean due to its large thermal and dynamical inertia. Examples are sea-level rise and the response of the Atlantic Meridional Overturning Circulation (AMOC), a three-dimensional system of currents in the Atlantic Ocean with global climatic relevance7,8,9,10.

[Comment: The paragraph above is the obligatory statement of fidelity to the Climatist Creed. All the foundational claims are affirmed with references to prove the authors above reproach, and not to be dismissed as denialists.  As further evidence of their embrace of IPCC consensus science, consider the diagrams below.

a, The NAWH SST index (°C), defined as the annual SST anomalies averaged over the region 46° N–62° N and 46° W–20° W. Observations for 1900–2019 from ERSSTv.5 (orange) and Kaplan SST v.2 (yellow), and ensemble-mean SST for 1900–2014 (dark blue line) from the historical simulations with the CMIP6 models and the individual historical simulations (thin grey lines) are shown. b, Same as a but for the NA-SST index (°C), defined as the annual SST anomalies averaged over the region 40° N–60° N and 80° W–0° E. c, Same as a but for the AMO/V (°C) index, defined as the 11-year running mean of the annual SST anomalies averaged over the region 0° N–65° N and 80° W–0° E. The SST indices in a–c are calculated as area-weighted means. d, NAO index (dimensionless) for 1900–2019 (red), defined as the difference in the normalized winter (December–March) sea-level pressure between Lisbon (Portugal) and Stykkisholmur/Reykjavik (Iceland). The blue curve indicates the equivalent CO2 radiative forcing (W m−2) for 1900–2019, which is taken from the Representative Concentration Pathway (RCP) SSP5-8.5 after 2014.

Chart d shows the NAO fluxes compared to a CO2 forcing curve based upon the much criticized RCP 8.5 scenario, which is not “business-as-usual” but rather “business-impossible.” Using it shows the authors bending over backwards to give every chance for confirming the alarming slowdown narrative.  The next paragraph gives the entire game away]

Climate models predict substantial AMOC slowing if atmospheric GHG concentrations continue to rise unabatedly1,11,12,13,14. Substantial AMOC slowing would drive major climatic impacts such as shifting rainfall patterns on land15, accelerating regional sea-level rise16,17 and reducing oceanic CO2 uptake. However, it is still unclear as to whether sustained AMOC slowing is underway18,19,20,21,22. Direct ocean-circulation observation in the North Atlantic (NA) is limited9,23,24,25,26,27. Inferences drawn about the AMOC’s history from proxy data28 or indices derived from other variables, which may provide information about the circulation’s variability (for example, sea surface temperature (SST)21,29,30, salinity31 or Labrador Sea convection32), are subject to large uncertainties.


Observed SSTs and a large ensemble of historical simulations with state-of-the-art climate models suggest the prevalence of internal AMOC variability since the beginning of the twentieth century. Observations and individual model runs show comparable SST variability in the NAWH region. However, the models’ ensemble-mean signal is much smaller, indicative of the prevalence of internal variability. Further, most of the SST cooling in the subpolar NA, which has been attributed to anthropogenic AMOC slowing21, occurred during 1930–1970, when the radiative forcing did not exhibit a major upward trend. We conclude that the anthropogenic signal in the AMOC cannot be reliably estimated from observed SST. A linear and direct relationship between radiative forcing and AMOC may not exist. Further, the relevant physical processes could be shared across EOF modes, or a mode could represent more than one process.

A relatively stable AMOC and associated northward heat transport during the past decades is also supported by ocean syntheses combining ocean general circulation models and data76,77, hindcasts with ocean general circulation models forced by observed atmospheric boundary conditions78 and instrumental measurements of key AMOC components9,22,79,80,81.

Neither of these datasets suggest major AMOC slowing since 1980, and neither of the AMOC indices from Rahmstorf et al.20 or Caesar et al.21 show an overall AMOC decline since 1980.

Contextual Background

From the Energy MIx Changes in Atlantic Current May Fall Within Natural Variability.  

In the February, 2022, edition of the journal Nature Geoscience, researchers at the University of Maryland Center for Environmental Science urged more detailed study of the notoriously complex Atlantic Meridional Overturning Circulation (AMOC). Now, oceanographer Mojib Latif and his team from the GEOMAR Helmholtz Centre for Ocean Research in Kiel, Germany are repeating that call in a paper just published in the journal Nature Climate Change.

The latest study describes the AMOC as a “three-dimensional system of current in the Atlantic Ocean with global climatic relevance.”

The February study responded to an August 2021 warning from the Potsdam Institute
that the AMOC has become wildly unstable and dangerously weak
due to global warming caused by human activity.

The authors of the latest study affirm that the Earth’s oceans have taken up more than 90% of the accumulated heat and roughly a third of all CO2 emissions since the dawn of the industrial age, leading to clearly measurable and devastating impacts like marine heat waves, sea level rise, and ocean acidification.

But it isn’t easy to confirm that the Atlantic circulation is actually slowing, partly because the ocean possesses such “large thermal and dynamical inertia.”

It is also extremely difficult to directly observe ocean circulation patterns in the North Atlantic, and proxies like sea surface temperature are “subject to large uncertainties,” the scientists say. Based on the available data, the GEOMAR study attributes localized sea surface cooling in the North Atlantic since 1900 to natural AMOC variability—not, as had been hypothesized, to a global heating-induced breakdown in the AMOC’s capacity to transfer heat.


See also from Science Norway Researchers and the media need to stop crying ‘wolf’ about the Gulf Stream


Why Ocean Keeps Its Cool at 4 Celsius

Water (H2O) has magical properties that make our planet suitable for us.  The video explains why most of the ocean water is about 4 degrees Celsius.  A transcript from another presentation draws the implications. Excerpts in italics with my bolds.

At the surface, ocean water can vary wildly in temperature – the water at the equator is around 30 degrees Celsius and the water at the poles is, well, freezing.  But surface waters are only a small fraction of the total water in the ocean.  Dive a little deeper, and you’ll find that a whopping 75 percent of the ocean’s water is all at the same temperature…and we’re not talking averages or anything – the vast majority of ocean water is 4 degrees Celsius.  And that’s not just a coincidence – it’s because water is weird.

As a liquid cools, its molecules slow down and the liquid generally gets denser and denser.  That’s how molten metals, wax, nacho cheese, and basically everything else behaves – except water.  Water does become denser as it cools though, but only up to a point.  Then it reverses course and actually gets less dense.

This happens because once water molecules slow down enough, intermolecular forces due to the water molecule’s unique shape start pushing the molecules apart until – at zero degrees and below – they form a lattice-like structure.  That’s why ice is less dense than water.

But the magic temperature where water is actually densest is 4 degrees Celsius. This weird maximum density is what causes the vast majority of the ocean to be stuck at the same temperature.

By about 1000 meters down, water has cooled to around four degrees. Any water here, or below, that happens to warm up – say, via heat from a hydrothermal vent or underwater volcano – will get a little less dense and float upwards, as less-dense things tend to do – out of this 4-degree zone.  Strangely, water cooler than 4 degrees will behave the same way; any water that loses a little bit of heat will also become a little less dense and balloon upwards.

As a result, all the ocean water below 1000 meters or so is about 4 degrees. 
Well, almost all the water. 

The very deepest parts of the ocean can get just a tiny bit colder, because of salt.  When salt ions are stuck to water molecules, they weigh them down, making saltier water a little denser than less salty water.  So when polar ice forms, salt gets pushed into the surrounding water, making it super-salty.  This super-salty water is most dense slightly below 4 degrees, in addition to being a little denser than less salty water, so, it has the tendency to plummet straight to the seafloor.

This heavier, colder water makes the deepest depths of the ocean slightly colder and denser than the water above.  Expeditions to the deepest parts of the ocean, like the Challenger Deep of Mariana’s Trench have recorded temperatures of 1 degree.  However, the same rules apply down there as they do in the rest of the water column – any water that warms or cools, even a bit, will become less dense and float away into the higher, less dense layers above.

If these weird water density rules didn’t apply – if water behaved like, say, nacho cheese – ocean water would just solidify from the bottom up as it’s cooled, and we wouldn’t have liquid oceans at all.



Why Climate Models Fail to Replicate the North Atlantic


A recent paper employed expert statistical analysis to prove that currently climate models fail to reproduce fluctuations of sea surface temperatures in the North Atlantic, a key region affecting global weather and climate.  H/T to David Whitehouse at GWPF for posting a revew of the paper.  I agree with him that the analysis looks solid and the findings robust.  However, as I will show below, neither Whitehouse nor the paper explicitly drew the most important implication.

At GWPF, Whitehouse writes Climate models fail in key test region (in italics with my bolds):

A new paper by Timothy DelSole of George Mason University and Michael Tippett of Columbia University looks into this by attempting to quantify the consistency between climate models and observations using a novel statistical approach. It involves using a multivariate statistical framework whose usefulness has been demonstrated in other fields such as economics and statistics. Technically, they are asking if two time series such as observations and climate model output come from the same statistical source.

To do this they looked at the surface temperature of the North Atlantic which is variable over decadal timescales. The reason for this variability is disputed, it could be related to human-induced climate change or natural variability. If it is internal variability but falsely accredited to human influences then it could lead over estimates of climate sensitivity. There is also the view that the variability is due to anthropogenic aerosols with internal variability playing a weak role but it has been found that models that use external forcing produce inconsistencies in such things as the pattern of temperature and ocean salinity. These things considered it’s important to investigate if climate models are doing well in accounting for variability in the region as the North Atlantic is often used as a test of a climate model’s capability.

The researchers found that when compared to observations, almost every CMIP5 model fails, no matter whether the multidecadal variability is assumed to be forced or internal. They also found institutional bias in that output from the same model, or from models from the same institution, tended to be clustered together, and in many cases differ significantly from other clusters produced by other institutions. Overall only a few climate models out of three dozen considered were found to be consistent with the observations.

The paper is Comparing Climate Time Series. Part II: A Multivariate Test by DelSole and Tippett.  Excerpts in italics with my bolds.

We now apply our test to compare North Atlantic sea surface temperature (NASST) variability between models and observations. In particular, we focus on comparing multi-year internal variability. The question arises as to how to extract internal variability from observations. There is considerable debate about the magnitude of forced variability in this region, particularly the contribution due to anthropogenic aerosols (Booth et al., 2012; Zhang et al., 2013). Accordingly, we consider two possibilities: that the forced response is well represented by (1) a second-order polynomial or (2) a ninth-order polynomial over 1854-2018. These two assumptions will be justified shortly.

If NASST were represented on a typical 1◦ × 1◦ grid, then the number of grid cells would far exceed the available sample size. Accordingly, some form of dimension reduction is necessary. Given our focus on multi-year predictability, we consider only large-scale patterns. Accordingly, we project annual-mean NASST onto the leading eigenvectors of the Laplacian over the Atlantic between 0 0 60◦N. These eigenvectors form an orthogonal set of patterns that can be ordered by a measure of length  scale from largest to smallest.

DelSole Tippett fig1

Figure 1. Laplacian eigenvectors 1,2,3,4,5,6 over the North Atlantic between the equator and 60◦N,  where dark red and dark blue indicate extreme positive and negative values, respectively

The first six Laplacian eigenvectors are shown in fig. 1 (these were computed by the method of DelSole and Tippett, 2015). The first eigenvector is spatially uniform. Projecting data onto the first Laplacian eigenvector is equivalent to taking the area-weighted average in the basin. In the case of SST, the time series for the first Laplacian eigenvector is merely an AMV index (AMV stands for “Atlantic Multidecadal Variability”). The second and third eigenvectors are dipoles that measure the large-scale gradient across the basin. Subsequent eigenvectors capture smaller scale patterns.  For model data, we use pre-industrial control simulations of SST from phase 5 of the Coupled Model Intercomparison Project (CMIP5 Taylor et al., 2012). Control simulations use forcings that repeat year after year. As a result, interannual variability in control simulations come from internal dynamical mechanisms, not from external forcing.

DelSole Tippett fig2Figure 2. AMV index from ERSSTv5 (thin grey), and polynomial fits to a second-order (thick black) and ninth-order (red) polynomial.

For observational data, we use version 5 of the Extended Reconstructed SST dataset (ERSSTv5 Huang et al., 2017). We consider only the 165-year period 1854-2018. We first focus on time series for the first Laplacian eigenvector, which we call the AMV index. The corresponding least squares fit to second- and ninth-order polynomials in time are shown in fig. 2. The second-order polynomial captures the secular trend toward warmer temperatures but otherwise has weak multidecadal variability. In contrast, the ninth-order polynomial captures both the secular trend and multidecadal variability. There is no consensus as to whether this multidecadal variability is internal or forced. 

DelSole Tippett fig4

Figure 4. Deviance between ERSSTv5 1854-1935 and 82-year segments from 36 CMIP5 pre-industrial control simulations. Also shown is the deviance between ERSSTv5 1854-1935 and ERSSTv5 1937-2018 (first item on x-axis). The black and red curves show, respectively, results after removing a second- and ninth-order polynomial in time over 1854-2018 before evaluating the deviance. The models have been ordered on the x-axis from smallest to largest deviance after removing a second-order polynomial in time.


The test was illustrated by using it to compare annual mean North Atlantic SST variability in models and observations. When compared to observations, almost every CMIP5 model differs significantly from ERSST. This conclusion holds regardless of whether a second- or ninth-order polynomial in time is regressed out. Thus, our conclusion does not depend on whether multidecadal NASST variability is assumed to be forced or internal. By applying a hierarchical clustering technique, we showed that time series from the same model, or from models from the same institution, tend to be clustered together, and in many cases differ significantly from other clusters. Our results are consistent with previous claims (Pennell and Reichler, 2011; Knutti et al., 2013) that the effective number of independent models is smaller than the actual number of models in a multi-model ensemble.

The Elephant in the Room

Now let’s consider the interpretation reached by model builders after failing to match observations of Atlantic Multidecadal Variability.  As an example consider INMCM4, whose results deviated greatly from the ERSST5 dataset.  In 2018, Evgeny Volodin and Andrey Gritsun published Simulation of observed climate changes in 1850–2014 with climate model INM-CM5.   Included in those simulations is a report of their attempts to replicate North Atlantic SSTs.  Excerpts in italics with my bolds.


Figure 4 The 5-year mean AMO index (K) for ERSSTv4 data (thick solid black); model mean (thick solid red). Dashed thin lines represent data from individual model runs. Colors correspond to individual runs as in Fig. 1.

Keeping in mind the argument that the GMST slowdown in the beginning of the 21st century could be due to the internal variability of the climate system, let us look at the behavior of the AMO and PDO climate indices. Here we calculated the AMO index in the usual way, as the SST anomaly in the Atlantic at latitudinal band 0–60∘ N minus the anomaly of the GMST. The model and observed 5-year mean AMO index time series are presented in Fig. 4. The well-known oscillation with a period of 60–70 years can be clearly seen in the observations. Among the model runs, only one (dashed purple line) shows oscillation with a period of about 70 years, but without significant maximum near year 2000. In other model runs there is no distinct oscillation with a period of 60–70 years but a period of 20–40 years prevails. As a result none of the seven model trajectories reproduces the behavior of the observed AMO index after year 1950 (including its warm phase at the turn of the 20th and 21st centuries).

One can conclude that anthropogenic forcing is unable to produce any significant impact on the AMO dynamics as its index averaged over seven realization stays around zero within one sigma interval (0.08). Consequently, the AMO dynamics are controlled by the internal variability of the climate system and cannot be predicted in historic experiments. On the other hand, the model can correctly predict GMST changes in 1980–2014 having the wrong phase of the AMO (blue, yellow, orange lines in Figs. 1 and 4).


Figure 1 The 5-year mean GMST (K) anomaly with respect to 1850–1899 for HadCRUTv4 (thick solid black); model mean (thick solid red). Dashed thin lines represent data from individual model runs: 1 – purple, 2 – dark blue, 3 – blue, 4 – green, 5 – yellow, 6 – orange, 7 – magenta. In this and the next figures numbers on the time axis indicate the first year of the 5-year mean.

The Bottom Line

Since the models incorporate AGW in the form of CO2 sensitivity, they are unable to replicate Atlantic Multidecadal Variability.  Thus, the logical conclusion is that variability of North Atlantic SSTs is an internal, natural climate factor.


How Water Warms Our Planet

The hydrological cycle. Estimates of the observed main water reservoirs (black numbers in 10^3 km3 ) and the flow of moisture through the system (red numbers, in 10^3 km3 yr À1 ). Adjusted from Trenberth et al. [2007a] for the period 2002-2008 as in Trenberth et al. [2011].

This site has long asserted that “Oceans Make Climate”. Now a recent study reveals the dynamics by which water influences temperatures over land as well. The paper is Testing the hypothesis that variations in atmospheric water vapour are the main cause of fluctuations in global temperature by Ivan R. Kennedy and Migdat Hodzic, published in Periodicals of Engineering and Natural Sciences, August 2019.  Excerpts in italics with my bolds. H/T Notrickszone.


Global warming issues have caused intensive research work in related areas, from land use, to urban environment to data science use in order to understand its effects better [25], [26], [27]. In this paper we focus on water related effects on global warming. Although water is recognised as the main cause of the greenhouse effect warming the Earth 33 oC above its black body temperature, water vapour is usually given a secondary role in global models, as a positive feedback from warming by all other causes. Despite its dominant effect in generating the weather, changes related to water are not seen as having a primary role in climate change, the focus being primarily on CO2. With positive feedback from primary warming, the effect of increasing CO2 is trebled [15] by water vapour increase. This conclusion is based on the perception that there are no significant trends in the hydrological cycle that could cause climate forcing. But this overlooks the effect of more than 3500 km3 of extra surface and ground water used annually in irrigation [17] to grow food for the human population. This quantity of extra water increases steadily year by year, well correlated with increasing atmospheric CO2, growing about 60% of world food requirements. Even so, the amount used in irrigation probably only adds about 3% to the annual hydrological cycle [9] of 113,000 km3. Is this sufficient to exert a significant extra greenhouse effect? Here we advance the hypothesis that it does and should be included in climate models.

A critical assumption of the IPCC consensus of global warming is that an increasing concentration of CO2 causes more retention of radiant heat near the top of the atmosphere, largely as a result of reduced emission of its spectral wavelengths centred on 15 microns. The radiative-convective model assumes that the lowered emissions at reduced pressure, number density and higher, colder altitudes from this GHG now provides an independent and sustained forcing exceeding 1-2 W per m2. It is assumed that once this reduction in OLR in the air column from increasing CO2 has occurred it must be compensated by increased OLR at different wavelengths elsewhere, maintaining balance with incoming radiation.

This critical assumption still lacks empirical confirmation.

Water Drives Atmospheric Warming

The importance of water in helping to keep the Earth’s atmosphere warm in the short term is beyond dispute. Table 1 summarises previously estimated rates for thermal energy flows into and out of the atmosphere [23]. As shown in the table, more than 80% of the power by which the temperature of air is maintained above the Earth’s black body temperature of -18 C is facilitated by water. Most significant of these air warming inputs from water is the greenhouse effect by which water vapour absorbs longwave radiation emitted from the surface, retaining more energy in air. However, warming from absorption of specific quanta by water vapour of incoming short wave solar radiation (ISR) and the latent heat of condensation of water vapour, exceeding the cooling effect of vertical convection, also contribute to warming of air.

Thus, the greenhouse gas (GHG) content of the atmosphere effectively provides resistance to heat flow to space increasing the transient storage of solar energy, with a warming effect analogous to resistances in an electrical circuit. By comparison to water, other polyatomic greenhouse gases like CO2 play a minor role in this process, totalling less than 20% of warming. Furthermore, the fact that the minor GHGs are relatively well-mixed by the turbulence in the troposphere, unlike water, means that we cannot expect to observe spatial variations in their effects. Furthermore, the heat capacity of non-greenhouse gases provides some 99% of the thermal inertia of the troposphere, although only greenhouse gases capable of longwave radiation by vibrational and rotational quanta can contribute to cooling by radiation through the top of the atmosphere as OLR. Figure 1 contrasts schematically the typical variation of outgoing longwave radiation (OLR) over marine and terrestrial environments.

On well-watered land such as southern China much less direct emission of OLR to space occurs, in contrast to Quetta, Pakistan, on the same latitude with similar incoming shortwave radiation (ISR). In contrast to humid atmospheres on land and tropical seas, relatively arid regions such as the Sahara, the Middle East and Australia provide heat vents effectively cooling the Earth, solely as a result of the radiant emissions from GHGs as OLR. The varying global emissions of OLR estimated for typical marine and terrestrial regions shown in Figure 2 mirror this scheme.

Clearly, water vapour is the most critical factor in the mechanism by which the air column of the lower troposphere is charged with heat energy. It is of interest from this figure and in Table 1 that the exact sum of the effects of all greenhouse gases in directly warming air, including conduction from the surface, charges the lower atmosphere with sufficient heat to generate the downwelling radiation from greenhouse gases directed towards the surface [12]. Water is the main source of this back radiation [18], well understood to be responsible for keeping the surface air warmer in humid atmospheres, thus raising the minimum temperature.

None of the variation in OLR in Figure 1 can be attributed to the well-mixed GHGs such as CO2.

Furthermore, unlike the greenhouse effect of CO2, which is regarded as increasing only in in a logarithmic manner as its concentration rises, the greenhouse effect of water on retaining heat in the atmosphere should vary more linearly, even in the case of absorption of surface radiation, as its vapour spreads into dryer atmospheres; this potential is illustrated in Fig.1 in the descending zones of Hadley cells at sub-tropical latitudes.

Fig. 1 Global values of mean OLR from 2003-2011 (downloaded August 2, 2017, AIRS OLR 2003-2011 average htpp://mirador.gsfc.nasa.gov/ estimated by Giorgio, G.P., June 24, 2014). The russet areas show regions of greater OLR, with outgoing radiation above the average of ca. 240 W per m2, thus tending to cool the Earth. Note how the upper troposphere above arid continental regions provides a vent for the greatest rate of cooling.

Thermal Effects from Water are Direct and Linear

An approximately linear response in increasing air temperature to changes in atmospheric water content is reasonable. Unlike the well-mixed CO2, there are marked spatial and temporal variations in atmospheric water content, with much of the Earth’s surface in significant deficit, particularly in the sub-tropical zone subject to Hadley cell recycling, emphasised over semi-arid land. To the extent that additional water vapour spills over into these dryer regions on land the greater the area of the Earth that is subject to the greenhouse effect. This response can be contrasted to the effect of increasing CO2, which has a logarithmic relationship between climate forcing and concentration in the atmosphere [14], [15], each doubling causing a similar increase in temperature. Because there is no obvious regional effect of CO2 on the weather or regional climate, the effect of any increases in its concentration can only be theoretically inferred. If additional heat is retained in the atmosphere by increasing greenhouse effects from CO2 or water, the air temperature near the surface is expected to increase to keep global values of ISR and OLR in balance. A critical assumption of the IPCC consensus for climate change is that increasing CO2 causes more retention of heat in air near the top of the troposphere, largely as reduced emission from the edges of its spectral peak centred on 15 microns. This edge effect is predicted to be visible from space as a cooling of its spectrum, providing a negative forcing of 1-2 W per m2. It is assumed that this forcing must be compensated by increased OLR at different wavelengths as a result of the increased temperature.

Fig. 3 Satellite measurements of global-zonal OLR (http://www.cpc.ncep.noaa.gov/data/indices/olr NOAA website, downloaded August 20, 2017). The 1998-2000 El Nino peaked at about 1.03 C above the minimum temperature in the preceding La Nina, with zonal OLR varying approximately 4 W/m2; see also (8)

This is regarded as a result of convective elevation of the maritime atmosphere, reducing the outgoing longwave radiation (OLR) about 100 W/m2 locally and 4 W/m2 globally from an increase in global water vapour of about 4%. This suggests a linear response from greenhouse warming to increased water vapour content of the atmosphere. Note that the extra heat in the atmosphere during an El Nino is controlled by all these sources of warming, as shown in Figure 2. Whatever the source of extra heat in the ocean, by moving extra water into the atmosphere as vapour it warms the atmosphere by the resultant greenhouse effect, reducing OLR, as well as direct warming by sunlight in the air column. In Table 4, another estimate of the possible effect of irrigation on global warming by comparison with the El Nino-La Nina cycle [22] is made. Consistent with the irrigation water hypothesis the El Nino has been long known to significantly reduce the OLR over the Pacific Ocean up to 25% [3], recognised as a result of elevation of emission of the OLR from water being elevated and therefore a colder altitude. Assuming 60% of irrigation water becomes vapour in the troposphere and a longer rain-out time of 15 days in dry regions compared to less than a week over the oceans with a global average of 8.5 days [19], a steady state of about 100 km3 of extra water vapour results from irrigation.

This estimate also suggests an increase in temperature near 0.2C from 0.84 W/m2 of forcing based on the data given in Figure 3. This is consistent with the total effect of water vapour on global warming exceeding 25 C.

It should be noted that this dynamic effect of water on warming air includes heat pumping by evapotranspiration as well as significant warming by direct absorption of short wave solar radiation (see Fig. 2), also contributing to a more linear effect by water on warming. Since this increase estimates a primary forcing effect of new water, a positive feedback is also anticipated from increased evaporation of the ocean, suggesting that the total increase from irrigation could be of the order of 0.5 oC in the 20th century.

These global results may have more accuracy than the results obtained from the numerous grid points in global circulation models, given the additivity of errors.

Empirical Proof Comparing Dry and Irrigated Land

In Figure 4, using the same modelling as in Figure 2, the predicted steady state greenhouse effect of adding irrigation water in a comparison between dryland and irrigated land. In fact the effect of water on heat transfer to the atmospheric column is not only a result of the greenhouse effect given in the equation in the figure but also from direct absorption by water of short wave ISR and evapotranspiration, similar in total magnitude. These latter effects will be a linear function of the water vapour involved. The evaporative effect cools the surface but must transfer a similar amount of heat to the atmosphere as infrared radiation (ca. 6 microns) associated with condensation of water vapour into droplets under convective cooling as in [21]. Paradoxically, the modelling paper in [6] failed to account for any of these effects, specifically dismissing significant transfer of water vapour into the atmosphere from growth of irrigated crop growth as noted above. This provides a clue to the possible flaw in their models. Except for environments already very humid where evapotranspiration is limited, this cannot be true.

Fig. 4 Comparison of dryland and irrigated land for effect of water on heat retention in the atmosphere as an enhanced greenhouse effect. The El Nino condition of enhanced evaporation from the ocean known to strongly reduce OLR In [3] is shown as an analogue.

NCEP/ NCAR Reanalyses Coincident with the Periodic Flooding of Lake Eyre

Fig. 5 Variation in OLR from flooding of lake Eyre using NCEP-NCAR reanalysis datasets. a.Difference in OLR values between 1978 and 1974, dry and wet years. b. Difference in OLR values between 1978 and 1973, two dry years.

Rarely, during the La Nina phase of the climate cycle, the dry interior of northern Australia overlying the Great Artesian Basin may flood. Lacking riverine exits to the ocean, the massive runoff caused flows southwards, mainly accumulating in the depression below sea level in central South Australia known as Lake Eyre. In late January and February in the early months of 1974 Lake Eyre filled to a depth of six metres, its surface only returning to its hot, dry state three years later in 1977-78. This was the greatest flood ever recorded. The hypothesis in [4] suggests that this flooding should also lead to persistent elevated water vapour content of the atmosphere, predominantly downwind from the Lake Eyre basin. Using the NCEP-NCAR reanalysis datasets, which are informed by Nimbus and other satellite observations since 1970, the OLR emissions to space and the variation in humidity from this region comparing 12 months of 1974 with the same period in 1978 by subtraction of one year from the other. A significant elevation of OLR when the lake was dry by more than 10 W/m2 was observed for the 12-month period (Figure 5). This result is accompanied by increases in specific humidity consistent with an elevated greenhouse effect such as would be experienced in semi-arid areas when irrigated. The area affected downwind also showing elevated humidity is estimated as 35 times the flooded area, showing that the magnitude of this regional greenhouse effect was indeed significant.

Conclusion:  Thankfully, A Wet World is a Warm World

The neglect of the possible effect of irrigation as a significant source of anthropogenic climate change may have been a result of reluctance to consider the relatively small amount of irrigation in the hydrological cycle. Because water has been considered as providing positive feedback to warming primarily from CO2 its possible forcing effect has been overlooked. But as shown here by several different means, the more potent effect of applying water previously in the ocean or deep in the ground to dry surfaces with air in strong water deficit can be sufficient to affect global temperature. Clearly, the water vapour content of the troposphere is the major cause of the natural greenhouse effect, contributing up to two-thirds of the 33 oC warming.

Spatial and temporal variations in soil moisture and relative humidity of the atmosphere are the main factors controlling the regional outgoing longwave radiation (OLR), in contrast to the more even effects from well-mixed greenhouse gases such as CO2.

This is well illustrated in the 4-6 year El Nino cycles, resulting in a global mean temperature variation approaching 1 oC compared with La Nina years. Longer term, the proposed Milankovitch glaciations of paleoclimates result in declines of atmospheric temperature around 10 oC, consistent with the major reduction in tropospheric water vapour approaching 50%. Weather conditions and climate as illustrated in the greenhouse effect are clearly demonstrated in the distribution of water, particularly on land. The apparently linear relationship between the water content of the atmosphere is direct verification of the greenhouse warming effect of this greenhouse gas. By contrast, other than by correlation, there is no such direct verification possible for the greenhouse effect of CO2. We rely on the forcing equation of 5.3ln[(CO2)t /(CO2)o] to estimate the climate sensitivity with respect to varying concentration (ppmv) of this greenhouse gas. Early hopes that a clear spectral signal was available showing significantly reduced OLR from increasing CO2, proving the hypothesis of climate forcing by permanent GHGs, have not been realised [5]. A focus using new satellites on the longer wavelength OLR associated with rotations of water might help resolve this question. Up till now, OLR is estimated for this region based on shorter wavelengths. The natural experiment provided by the flooding of Lake Eyre of the greenhouse effect by significantly reducing the OLR provides confirmation that irrigation water typically applied to dry land will have a measurable greenhouse effect.

One year time lapse of precipitable water (amount of water in the atmosphere) from Jan 1, 2016 to Dec 31, 2016, as modeled by the GFS. The Pacific ocean rotates into view just as the tropical cyclone season picks up steam.

H20 the Gorilla Climate Molecule

In climate discussions, someone is bound to say: Climate is a lot more than temperatures. And of course, they are right. So let’s consider the other major determinant of climate, precipitation.

The chart above is actually a screen capture of real-time measurements of precipitable water in the atmosphere.  The 24-hour animation can be accessed at MIMIC-TPW ver.2 .  H/T Ireneusz Palmowski, who commented:  “I do not understand why scientists deal with anthropogenic CO2, although the entire convection in the troposphere is driven by water vapor (and ozone in high latitudes).”

These images show that H2O is driving the heat engine through its phase changes (liquid to vapor to liquid (and sometimes ice crystals as well).  And as far as radiative heat transfer is concerned, 95% of it is done by water molecules.  Below is an essay going into the dynamics of precipitation, its variability over the earth’s surface, and its role in determining regional, and even microclimates.  The post was originally titled “Here Comes the Rain Again, inspired by the Eurythmics classic song

The global story on rain is straightforward:

“Precipitation is a major component of the water cycle, and is responsible for depositing the fresh water on the planet. Approximately 505,000 cubic kilometres (121,000 cu mi) of water falls as precipitation each year; 398,000 cubic kilometres (95,000 cu mi) of it over the oceans. Given the Earth’s surface area, that means the globally averaged annual precipitation is 990 millimetres (39 in). Climate classification systems such as the Köppen climate classification system use average annual rainfall to help differentiate between differing climate regimes.


Globally, average precipitation can vary from +/-5% yearly, but there is no particular trend in the history of observations. But rain is one of those things where averages don’t tell you much. For starters, look at where it’s coming down:

So about 1 meter a year is the nominal average of all rain over all surfaces. Some places get up to 10 meters of rain (about 400 inches ) and others get near none. 47% of the earth is considered dryland, defined as anyplace where the rate of evaporation/transpiration exceeds the rate of precipitation. A desert is defined as a dryland with less than 25 cm of precipitation. In the image above, polar deserts are remarkably defined. It just does not have much hope of precipitation as there is little heat to move the water. More heat in, more water movement. Less heat in, less water movement.

Then there’s the seasonal patterns. The band of maximum rains moves with the sun: More north in June, more south in December. More sun, more heating, more rain. Movement in sync with the sun, little time delay. Equatorial max solar heat has max rains. Polar zones minimal heating, minimal precipitation. It’s a very tightly coupled system with low time lags.

The other obvious thing is how central land areas get dry desert conditions if they are not in the equatorial band nor near a warm water current. Brazil, in particular, benefits from warm coastal waters and near equatorial rains. The Gulf Stream rescues Europe from a much drier climate, but I fear the Gulf Stream shifting of zones also puts parts of Saharan Africa out of the equatorial wet. (In some times during history it DOES get a load of water, though…)
From E.M. Smith

How do Oceans Make Rain

Here I am taking direction from A. M Makarieva and her colleagues. She explains:

“Water vapor originating by evaporation sustained by solar radiation represents a source of ordered potential energy that is available for generation of atmospheric circulation, including the biotic pump. We will further consider details of this process.

As we can see, early in its life the cloud expands in all directions, meanwhile the air continues to converge towards the (growing) condensation area. This process is at the core of condensation-induced dynamics: as condensation occurs and local pressure drops, this initiates convergence and ascent. They, in their turn, feedback positively on condensation intensity, such that the air pressure lowers further, convergence becomes more extensive and so on — as long as there is enough water vapor around to feed the process.

And where does the water vapor come from? Ocean evaporation, 87%, Plant transpiration 10% , Other evaporation, lakes, rivers, etc. 3%.

Air circulation without condensation (A) and with condensation (B). Gray squares are the air volumes, which in case (B) contain water vapor shown by small blue squares inside gray ones. White squares indicate those air volumes that have lost their water vapor owing to condensation. Blue arrows at the Earth’s surface represent evaporation that replenishes the store of water vapor in the circulating air.

On Fig. B we can see a circulation accompanied by water vapor condensation (water vapor is shown by blue squares). At a certain height water vapor condenses leaving the gaseous phase, while the remaining air continues to circulate deprived of water vapor (this depletion is shown by empty white squares): it first rises and then descends. As one can see, in such a circulation total mass of the rising air would be larger than total mass of the descending air (cf. an escalator transporting people up). The motor driving such a circulation would not only have to compensate the friction losses, but also have to work against gravity that is acting on the ascending air.

One can see from Fig. B that the difference between the cumulative masses of the ascending and descending air parcels grows with increasing height where condensation occurs. This difference also grows with increasing amount of water vapor in the air (i.e. with increasing size of the blue squares). The dynamic power of condensation, on the other hand, is also proportional to the amount of water vapor, but it is practically independent of condensation height.

Condensation height (a proxy for precipitation pathlength) grows with increasing temperature of the Earth’s surface. It is shown in the paper that power losses associated with precipitation of condensate particles become equal to the total dynamic power of condensation at surface temperatures around 50 degrees Celsius. Since the observed power of condensation-driven winds is equal to the total dynamic power of condensation (the “motor”) minus the power spent on compensating precipitation, at such temperatures the observed circulation power becomes zero and the circulation must stop. For commonly observed values of surface temperature these losses do no exceed 40% of condensation power and cannot arrest the condensation-induced circulation. Over 60% of condensation power is spent on friction at the Earth’s surface.

Why Some Places Get More Rain Than Others

This figure shows the “tug-of-war” between the forest and the ocean for the right to become a predominant condensation zone. In Fig. a: on average the Amazon and Congo forests win this war: annual precipitation over forests is two to three times larger than the precipitation over the Atlantic Ocean at the same latitude. Note the logarithmic scale on the vertical axis: “1” means that the land/ocean precipitation ratio is equal to e = 2.718, “2” means it is equal to e2 ≈ 7.4; “0” means that this ratio is unity (equal precipitation on land and the ocean); “-1” means this ratio is 1/e ≈ 0.4; and so on.

In Fig. b: the Eurasian biotic pump. In winter the forest sleeps, so the ocean wins, and all moisture remains over the ocean and precipitates there. In summer, when trees are active, moisture is taken from the ocean and distributed regularly over seven thousand kilometers. The forest wins! (compare the red and black lines) As a result, precipitation over the ocean in summer is lower than it is in winter, despite the temperature in summer is higher.

Finally, in panel (c): an unforested Australia. One can often hear that Australia is so dry because it is situated in the descending branch of the Hadley cell. But this figure shows that such an interpretation does not hold. Both in wet and dry seasons precipitation over Australia is four to six times lower than over the ocean. There is no biotic pump there. Being unforested, oceanic moisture cannot penetrate to the Australian continent irrespective of how much moisture there is over the ocean; during the wet season it precipitates in the coastal zones causing floods. Gradually restoring natural forests in Australia from coast to interior will recover the hydrological cycle on the continent.


biotic pump

The Biotic Pump A. M Makarieva et al

Water cycle on land owes itself to the atmospheric moisture transport from the ocean. Properties of the aerial rivers that ensure the “run-in” of water vapor inland to compensate for the gravitational “run-off” of liquid water from land to the ocean are of direct relevance for the regional water availability. The biotic pump concept clarifies why the moist aerial rivers flow readily from ocean to land when the latter gives home to a large forest — and why they are reluctant to do so when the forest is absent.

While it is increasingly common to blame global change for any regional water cycle disruption, the biotic pump evidence suggests that the burden of responsibility rather rests with the regional land use practices. On large areas on both sides of the Atlantic Ocean, temperate and boreal forests are intensely harvested for timber and biofuel. These forests are artificially maintained in the early successional stages and are never allowed to recover to the natural climax state. The water regulation potential of such forests is low, while their susceptibility to fires and pests is high.



So the oceans make rain, and together with the forests the land receives its necessary fresh water. There is a threat from human activity, but it has nothing to do with CO2. Land use practices leading to deforestation have the potential to disrupt this process. Without trees attracting the moist air from the ocean there is desert.

Ironically, modern societies burn fossil fuels instead of burning the forests as in the past.

For more on climate science related to H2O, see Bill Gray: H20 is Climate Control Knob, not CO2

AMOC Update: Not Showing Climate Threat

The RAPID moorings being deployed. Credit: National Oceanography Centre.

The AMOC is back in the news following a recent Ocean Sciences meeting.  This update adds to the theme Oceans Make Climate. Background links are at the end, including one where chief alarmist M. Mann claims fossil fuel use will stop the ocean conveyor belt and bring a new ice age.  Actual scientists are working away methodically on this part of the climate system, and are more level-headed.  H/T GWPF for noticing the recent article in Science Ocean array alters view of Atlantic ‘conveyor belt’  By Katherine Kornei Feb. 17, 2018 . Excerpts with my bolds.

The powerful currents in the Atlantic, formally known as the Atlantic meridional overturning circulation (AMOC), are a major engine in Earth’s climate. The AMOC’s shallower limbs—which include the Gulf Stream—transport warm water from the tropics northward, warming Western Europe. In the north, the waters cool and sink, forming deeper limbs that transport the cold water back south—and sequester anthropogenic carbon in the process. This overturning is why the AMOC is sometimes called the Atlantic conveyor belt.

Fig. 1. Schematic of the major warm (red to yellow) and cold (blue to purple) water pathways in the NASPG (North Atlantic subpolar gyre ) credit: H. Furey, Woods Hole Oceanographic Institution): Denmark Strait (DS), Faroe Bank Channel (FBC), East and West Greenland Currents (EGC and WGC, respectively), NAC, DSO, and ISO.

Last week, at the American Geophysical Union’s (AGU’s) Ocean Sciences meeting here, scientists presented the first data from an array of instruments moored in the subpolar North Atlantic. The observations reveal unexpected eddies and strong variability in the AMOC currents. They also show that the currents east of Greenland contribute the most to the total AMOC flow. Climate models, on the other hand, have emphasized the currents west of Greenland in the Labrador Sea. “We’re showing the shortcomings of climate models,” says Susan Lozier, a physical oceanographer at Duke University in Durham, North Carolina, who leads the $35-million, seven-nation project known as the Overturning in the Subpolar North Atlantic Program (OSNAP).

Fig. 2. Schematic of the OSNAP array. The vertical black lines denote the OSNAP moorings with the red dots denoting instrumentation at depth. The thin gray lines indicate the glider survey. The red arrows show pathways for the warm and salty waters of subtropical origin; the light blue arrows show the pathways for the fresh and cold surface waters of polar origin; and the dark blue arrows show the pathways at depth for waters that originate in the high-latitude North Atlantic and Arctic.

The research and analysis is presented by Dr. Lozier et al. in this publication Overturning in the Subpolar North Atlantic Program: A New International Ocean Observing System Images above and text excerpted below with my bolds.

For decades oceanographers have assumed the AMOC to be highly susceptible to changes in the production of deep waters at high latitudes in the North Atlantic. A new ocean observing system is now in place that will test that assumption. Early results from the OSNAP observational program reveal the complexity of the velocity field across the section and the dramatic increase in convective activity during the 2014/15 winter. Early results from the gliders that survey the eastern portion of the OSNAP line have illustrated the importance of these measurements for estimating meridional heat fluxes and for studying the evolution of Subpolar Mode Waters. Finally, numerical modeling data have been used to demonstrate the efficacy of a proxy AMOC measure based on a broader set of observational data, and an adjoint modeling approach has shown that measurements in the OSNAP region will aid our mechanistic understanding of the low-frequency variability of the AMOC in the subtropical North Atlantic.

Fig. 7. (a) Winter [Dec–Mar (DJFM)] mean NAO index. Time series of temperature from the (b) K1 and (c) K9 moorings.

Finally, we note that while a primary motivation for studying AMOC variability comes from its potential impact on the climate system, as mentioned above, additional motivation for the measure of the heat, mass, and freshwater fluxes in the subpolar North Atlantic arises from their potential impact on marine biogeochemistry and the cryosphere. Thus, we hope that this observing system can serve the interests of the broader climate community.

Fig. 10. Linear sensitivity of the AMOC at (d),(e) 25°N and (b),(c) 50°N in Jan to surface heat flux anomalies per unit area. Positive sensitivity indicates that ocean cooling leads to an increased AMOC—e.g., in the upper panels, a unit increase in heat flux out of the ocean at a given location will change the AMOC at (d) 25°N or (e) 50°N 3 yr later by the amount shown in the color bar. The contour intervals are logarithmic. (a) The time series show linear sensitivity of the AMOC at 25°N (blue) and 50°N (green) to heat fluxes integrated over the subpolar gyre (black box with surface area of ∼6.7 × 10 m2) as a function of forcing lead time. The reader is referred to Pillar et al. (2016) for model details and to Heimbach et al. (2011) and Pillar et al. (2016) for a full description of the methodology and discussion relating to the dynamical interpretation of the sensitivity distributions.

In summary, while modeling studies have suggested a linkage between deep-water mass formation and AMOC variability, observations to date have been spatially or temporally compromised and therefore insufficient either to support or to rule out this connection.

Current observational efforts to assess AMOC variability in the North Atlantic.

The U.K.–U.S. Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array (RAPID–MOCHA) program at 26°N successfully measures the AMOC in the subtropical North Atlantic via a transbasin observing system (Cunningham et al. 2007; Kanzow et al. 2007; McCarthy et al. 2015). While this array has fundamentally altered the community’s view of the AMOC, modeling studies over the past few years have suggested that AMOC fluctuations on interannual time scales are coherent only over limited meridional distances. In particular, a break point in coherence may occur at the subpolar–subtropical gyre boundary in the North Atlantic (Bingham et al. 2007; Baehr et al. 2009). Furthermore, a recent modeling study has suggested that the low-frequency variability of the RAPID–MOCHA appears to be an integrated response to buoyancy forcing over the subpolar gyre (Pillar et al. 2016). Thus, a measure of the overturning in the subpolar basin contemporaneous with a measure of the buoyancy forcing in that basin likely offers the best possibility of understanding the mechanisms that underpin AMOC variability. Finally, though it might be expected that the plethora of measurements from the North Atlantic would be sufficient to constrain a measure of the AMOC within the context of an ocean general circulation model, recent studies (Cunningham and Marsh 2010; Karspeck et al. 2015) reveal that there is currently no consensus on the strength or variability of the AMOC in assimilation/reanalysis products.

Atlantic Meridional Overturning Circulation (AMOC). Red colours indicate warm, shallow currents and blue colours indicate cold, deep return flows. Modified from Church, 2007, A change in circulation? Science, 317(5840), 908–909. doi:10.1126/science.1147796

In addition we have a recent report from the United Kingdom Marine Climate Change Impacts Partnership (MCCIP) lead author G.D. McCarthy Atlantic Meridional Overturning Circulation (AMOC) 2017.

12-hourly, 10-day low pass filtered transport timeseries from April 2nd 2004 to February 2017.

Figure 1: Ten-day (colours) and three month (black) low-pass filtered timeseries of Florida Straits transport (blue), Ekman transport (green), upper mid-ocean transport (magenta), and overturning transport (red) for the period 2nd April 2004 to end- February 2017. Florida Straits transport is based on electromagnetic cable measurements; Ekman transport is based on ERA winds. The upper mid-ocean transport, based on the RAPID mooring data, is the vertical integral of the transport per unit depth down to the deepest northward velocity (~1100 m) on each day. Overturning transport is then the sum of the Florida Straits, Ekman, and upper mid-ocean transports and represents the maximum northward transport of upper-layer waters on each day. Positive transports correspond to northward flow.

The RAPID/MOCHA/WBTS array (hereinafter referred to as the RAPID array) has revolutionized basin scale oceanography by supplying continuous estimates of the meridional overturning transport (McCarthy et al., 2015), and the associated basin-wide transports of heat (Johns et al., 2011) and freshwater (McDonagh et al., 2015) at 10-day temporal resolution. These estimates have been used in a wide variety of studies characterizing temporal variability of the North Atlantic Ocean, for instance establishing a decline in the AMOC between 2004 and 2013.

Summary from RAPID data analysis

MCCIP reported in 2006 that:

  • a 30% decline in the AMOC has been observed since the early 1990s based on a limited number of observations. There is a lack of certainty and consensus concerning the trend;
  • most climate models anticipate some reduction in strength of the AMOC over the 21st century due to increased freshwater influence in high latitudes. The IPCC project a slowdown in the overturning circulation rather than a dramatic collapse.And in 2017 that:
  • a substantial increase in the observations available to estimate the strength of the AMOC indicate, with greater certainty, a decline since the mid 2000s;
  • the AMOC is still expected to decline throughout the 21st century in response to a changing climate. If and when a collapse in the AMOC is possible is still open to debate, but it is not thought likely to happen this century.

And also that:

  • a high level of variability in the AMOC strength has been observed, and short term fluctuations have had unexpected impacts, including severe winters and abrupt sea-level rise;
  • recent changes in the AMOC may be driving the cooling of Atlantic ocean surface waters which could lead to drier summers in the UK.


  • The AMOC is key to maintaining the mild climate of the UK and Europe.
  • The AMOC is predicted to decline in the 21st century in response to a changing climate.
  • Past abrupt changes in the AMOC have had dramatic climate consequences.
  • There is growing evidence that the AMOC has been declining for at least a decade, pushing the Atlantic Multidecadal Variability into a cool phase.
  • Short term fluctuations in the AMOC have proved to have unexpected impacts, including being linked
    with severe winters and abrupt sea-level rise.


Climate Pacemaker: The AMOC

Evidence is Mounting: Oceans Make Climate

Mann-made Global Cooling



Oceans Make Climate: SST, SSS and Precipitation Linked


Satellite image of sea surface temperature in the Gulf Stream.

Climates are locally defined according to their weather patterns combining temperature and precipitation. Those two variables determine the flora and fauna to survive and flourish in any locale. A number of posts here support the theme that Oceans Govern Climate, and this is another one, summarizing the findings from a new paper published in Nature Communications Pronounced centennial-scale Atlantic Ocean climate variability correlated with Western Hemisphere hydroclimate by Thirumalai et al. 2018. Below is an overview from Science Daily followed by excerpts from the paper with my bolds. (Note:  SST refers to sea surface temperatures, SSS refers to sea surface salinity, and GOM means Gulf of Mexico.)

Science Daily Rainfall and ocean circulation linked in past and present

Research conducted at The University of Texas at Austin has found that changes in ocean currents in the Atlantic Ocean influence rainfall in the Western Hemisphere, and that these two systems have been linked for thousands of years.

The findings, published on Jan. 26 in Nature Communications, are important because the detailed look into Earth’s past climate and the factors that influenced it could help scientists understand how these same factors may influence our climate today and in the future.

“The mechanisms that seem to be driving this correlation [in the past] are the same that are at play in modern data as well,” said lead author Kaustubh Thirumalai, postdoctoral researcher at Brown University who conducted the research while earning his Ph.D. at the UT Austin Jackson School of Geosciences. “The Atlantic Ocean surface circulation, and however that changes, has implications for how the rainfall changes on continents.”


Open image in new tab if animation is not working.

Thirumalai et al. 2018 Abstract:

Surface-ocean circulation in the northern Atlantic Ocean influences Northern Hemisphere climate. Century-scale circulation variability in the Atlantic Ocean, however, is poorly constrained due to insufficiently-resolved paleoceanographic records.

Here we present a replicated reconstruction of sea-surface temperature and salinity from a site sensitive to North Atlantic circulation in the Gulf of Mexico which reveals pronounced centennial-scale variability over the late Holocene. We find significant correlations on these timescales between salinity changes in the Atlantic, a diagnostic parameter of circulation, and widespread precipitation anomalies using three approaches: multiproxy synthesis, observational datasets, and a transient simulation.

Our results demonstrate links between centennial changes in northern Atlantic surface-circulation and hydroclimate changes in the adjacent continents over the late Holocene. Notably, our findings reveal that weakened surface-circulation in the Atlantic Ocean was concomitant with well-documented rainfall anomalies in the Western Hemisphere during the Little Ice Age.

Here we address this shortfall and reconstruct SST and SSS variability over the last 4,400 years using foraminiferal geochemistry in marine sediments cored from the Garrison Basin (26°40.19′N,93°55.22′W, (purple circle in diagrams above), northern GOM. We make inferences about past changes in Loop Current strength by identifying time periods in our reconstruction where synchronous decreases in SST and SSS are interpreted as periods with a weaker Loop Current due to reduced eddy penetration over that period and vice versa. Thus, we assess the spatial heterogeneity of the putative reduction of Atlantic surface-ocean circulation and furthermore, with multiproxy synthesis, correlation analysis, and model-data comparison, we document linkages between changes in Atlantic surface-circulation and Western Hemisphere hydroclimate anomalies. Our findings reveal that regardless of whether changes in the AMOC and deepwater formation occurred or not, weakened surface-circulation prevailed in the northern Atlantic basin during the Little Ice Age and was concomitant with widespread and well-documented precipitation anomalies over the adjacent continents.

Figure 2. Garrison Basin multicore reconstructions and corresponding stacked records. Individual core Mg/Ca (mmol/mol) and δ18Oc data (‰, VPDB), and δ18Osw (‰, VSMOW) and SST (°C) reconstructions (blue–MCA, red- MCB, yellow–MCC) plotted with median and 68% uncertainty envelope incorporating age, analytical, calibration, and sampling errors (a-d) along with corresponding median stacked records with 68% and 95% confidence bounds (e-h). Diamonds in a and e indicate stratigraphic points sampled for radiocarbon. Gray histogram in g is the probability distribution for a changepoint in the δ18Osw time series. Orange circle in g is the mean of available δ18Osw measurements in the GOM and orange line in h is observed monthly mean SST with uncertainty envelope calculated using a Monte Carlo procedure that simulates foraminiferal sampling protocol. Purple line in h is the 100-year running correlation between SST and δ18Osw with corresponding uncertainty with shaded boxes indicating correlations with r > 0.7 (p < 0.001), which is the basis for identifying time periods where Loop Current and associated processes are relevant.

Loop Current control on regional SST and SSS variability

We analyzed long-term (~multidecadal) observations in instrumental datasets to place our reconstructions into a global climatic context. The HadISST data set22 documents 0.4–0.7 °C of multidecadal SST variability in the northern GOM over the last century. On these multidecadal timescales, SSTs in the northern GOM correlate highly with SST in the Loop Current region. In particular, long-term SST variability here is impacted by the Loop Current through its eddy shedding processes which are coupled to the strength of transport from the Yucatan Straits through the Florida Straits: if Loop Current transport is anomalously low, then northern GOM SSTs are anomalously cooler due to decreased eddy penetration and the opposite is the case when Loop Current transport is anomalously higher, i.e., northern GOM experiences anomalously warmer conditions. Furthermore, the Loop Current, sitting upstream of where the Gulf Stream originates, correlates highly with SST associated with regions encompassing downstream currents.

In summary, correlation analysis using SSS datasets provides a blueprint for investigating circulation variability and transport into the North Atlantic Ocean.

We also examine long-term correlations between SSS in the northern GOM and mean annual rainfall in the continents adjacent to the Atlantic Basin using rain-gauge precipitation datasets (Fig. 1). Most notably, GOM SSS is anticorrelated with southern North American rainfall (i.e., fresher GOM with wetter southern North America) and is positively correlated with rainfall in West Africa, northern South America, and the southeast United States (|r| > 0.6, p < 0.01). These inferences demonstrate a correspondence between Western Hemisphere hydroclimate and Atlantic Ocean circulation on multidecadal timescales.

Approach to understanding past circulation and hydroclimate

Taken together, we interpret past periods in the Garrison Basin reconstructions when both SST and δ18Osw variability were positively correlated (salty/warm or fresh/cool) as periods during which Loop Current strength fluctuated. We hypothesize that during these periods, increased Loop Current penetration led to increased SST as well as increased advection of more enriched δ18Osw (or more saline waters) into the northern GOM. Using the correlation analysis as a blueprint28, we can pinpoint whether these past fluctuations in the northern GOM δ18Osw record (such as during the LIA) were concomitant with changes in pan-Atlantic SSS records that would implicate circulation changes in the northern Atlantic Ocean. Finally, the long-term correlations with precipitation allow us to contextualize periods where surface-ocean circulation and continental rainfall anomalies were linked, which can then be placed within a multiproxy framework.

In comparing available reconstructions of precipitation during the LIA with our correlation map (Fig. 1), we find remarkable agreement with the proxy record: tree-ring-based PDSI reconstructions in southern North America, and stalagmites from southern Mexico43 and Peru44 capture a wetter LIA compared to modern times whereas a lake record from southern Ghana, titanium percent in Cariaco Basin sediments, and reconstructed PDSI in the southeast U. S. indicate dry LIA conditions. Additional proxy records appear to corroborate this observation as well (brown and green squares in Fig. 1; Supplementary Table 1). These mean state changes during the LIA all appear to be coeval with an anomalously fresher northern Atlantic Ocean, indicative of weakened Gulf Stream strength and reduced surface-ocean circulation.

Figure 5. Simulated correlations between sea-surface salinity and rainfall over last millennium. Correlation map between northern Gulf of Mexico SSS (dashed red box) and global oceanic SSS (red-blue scale) as well as continental precipitation (brown-green scale) from the MPI-ESM transient simulation of the last millennium along with locations of proxy records used in the study. Proxy markers are filled as in Fig. 1. Correlations were performed with 50–150 year bandpass filters to isolate centennial scale variability, where black stippling indicates significance at the 5% confidence level

The transient simulation indicates that a weaker gyre, increased sea-ice cover, and reduced interhemispheric heat transport causes the ITCZ to shift southward and produces anomalous rainfall over the Americas.

This state of weakened AMOC, observed in millennial-scale and glacial paleo-studies, with cool and fresh north Atlantic anomalies and a southward ITCZ, can induce increased rainfall over the southwest US via atmospheric teleconnections associated with the North Atlantic subtropical high overlying the gyre. Despite this southward shift, positive SSS anomalies can occur in the tropical Atlantic (and negative anomalies in the northern Atlantic) due to reduced freshwater input resulting from decreased rainfall in the Amazon and West African regions. Eventually, the tropical positive salinity anomaly in the southern Atlantic propagates northward, thereby strengthening meridional oceanic transport and providing the delayed negative feedback.

Though the length of the instrumental record limits us from directly analyzing centennial-scale correlations, there is theoretical and modeling evidence to implicate similar ocean-atmosphere processes on multidecadal and centennial timescales. Both model and observational analyses reveal a dipolar structure in Atlantic Ocean SSS that is consistent with the LIA proxies and thereby supports our hypothesis linking meridional salt transport and tropical rainfall. Both analyses also display similarities in continental precipitation patterns over western Africa, northern South America, and the southwestern United States, which are also consistent with the LIA hydroclimate proxies.


The broad agreement between the analyses supports similar ocean-atmosphere processes on multidecadal-to-centennial timescales, and provides additional evidence of a robust century-scale link between circulation changes in the Atlantic basin and precipitation in the adjacent continents.

Regardless of the specific physical mechanism concerning the onset of the LIA, and whether AMOC changes were linked with circulation changes in the surface ocean, we hypothesize that the reported oscillatory feedback on centennial-time scales involving the surface-circulation in the Atlantic Ocean and Western Hemisphere hydroclimate played an important role in last millennium climate variability and perhaps, over the late Holocene.








Natural Climate Cycles: Fresh Insights

Multiple aspects of nature cycle and interact over various time scales, frustrating attempts to discern human influence upon the climate. To demonstrate the challenge, consider one simple physical example: The compound pendulum shown in operation below:

Recently a comment (H/T tom0mason) alerted me to the science demonstrated by the double compound pendulum, that is, a second pendulum attached to the ball of the first one. It consists entirely of two simple, well understood objects functioning as pendulums, only now each is influenced by the behavior of the other.

Lo and behold, you observe that a double pendulum in motion produces chaotic behavior. In a remarkable achievement, complex equations have been developed that can and do predict the positions of the two balls over time, so in fact the movements are not truly chaotic, but with considerable effort can be determined. The equations and descriptions are at Wikipedia Double Pendulum.

But here is the kicker, as described in tomomason’s comment:

If you arrive to observe the double pendulum at an arbitrary time after the motion has started from an unknown condition (unknown height, initial force, etc) you will be very taxed mathematically to predict where in space the pendulum will move to next, on a second to second basis. Indeed it would take considerable time and many iterative calculations (preferably on a super-computer) to be able to perform this feat. And all this on a very basic system of known elementary mechanics.  More at Climate Chaos


Fresh Study of Antarctic Oscillation

Many of the cycles driving the climate system are circulations with the ocean and air interacting. A 2018 study looks in more detail at one of the more important ones: The Antarctic Oscillation (AAO), also known as Southern Annular Mode (SAM).  The Antarctic Centennial Oscillation: A Natural Paleoclimate Cycle in the Southern Hemisphere That Influences Global Temperature  W. Jackson Davis, Peter J. Taylor and W. Barton Davis, Santa Cruz USA Published: 8 January 2018
H/T Kenneth Richard NoTricksZone.  Excerpts from paper in italics with added images and bolds.

We report a previously-unexplored natural temperature cycle recorded in ice cores from Antarctica—the Antarctic Centennial Oscillation (ACO)—that has oscillated for at least the last 226 millennia. Here we document the properties of the ACO and provide an initial assessment of its role in global climate. We analyzed open-source databases of stable isotopes of oxygen and hydrogen as proxies for paleo-temperatures. We find that centennial-scale spectral peaks from temperature-proxy records at Vostok over the last 10,000 years occur at the same frequencies (±2.4%) in three other paleoclimate records from drill sites distributed widely across the East Antarctic Plateau (EAP), and >98% of individual ACOs evaluated at Vostok match 1:1 with homologous cycles at the other three EAP drill sites and conversely.

Superimposed upon these multi-millennial climate cycles are numerous shorter global and regional climate cycles ranging in period from several millennia down to a few weeks. Included among these faster oscillations are millennial-scale cycles, particularly the Bond cycle and centennial-scale cycles, notably the Antarctic Oscillation (AAO) known also as the Southern Annular Mode (SAM) and tracked quantitatively by means of the Southern Oscillation Index (SOI). These interdependent Southern Hemisphere (SH) temperature-proxy oscillations exhibit both centennial and decadal frequency components. Similar periodicity appears in independent reconstructions of more contemporary temperature proxies from James Ross Island and snow accumulation in stacked records from snowpits at Vostok.
Figure 3. Spectral power density periodogram of temperature-proxy records from Vostok over the Holocene. Arrows and associated numerals designate spectral peaks at the indicated periods in years (y) that are discernible within the indicated confidence limits. Discernible peaks at p < 0.005 are labeled 1–6 for reference to the same peaks portrayed in subsequent figures. The confidence limits are represented by best-fit exponential curves fitted to stepwise forward regression data over the whole frequency spectrum represented in the periodogram (Methods and SM). Fisher’s Kappa and the corresponding probability that the periodogram results from white noise are 17.34 and p < 8.7 × 10−7, respectively.

Periodograms of the remaining three AICC2012 climate records during the Holocene are similar to the periodogram of the Vostok record (Figure 4). All are bounded near the low end by a peak corresponding approximately to the mean period of the TOC350V cycles and near the high end by a peak corresponding to the Bond cycle in the NH and ranging from 825 to 1027 years. Between these extremes lie at least four additional centennial-scale peaks in all AICC2012 climate records evaluated.

Interannually the AAO shifts between phases, designated here as positive and normal (or negative.)

The null hypothesis that TOC350V cycles comprise random variation in cycle structure was tested by means of cyclic autocorrelation coefficients. We find that autocorrelation coefficients alternate between positive and negative at the same periodicity as the corresponding TOC350V cycle frequency (Figure 5). Near peaks and troughs, nearly all of these autocorrelation coefficients are discernibly different from zero at low alpha levels (at least at p < 0.05). These autocorrelation results supplement and extend spectral periodograms to confirm that TOC350V cycles comprise nonrandom periodic sequences. Such positive autocorrelation results would not be possible unless the short time series evaluated represent relatively stationary time series over the time periods evaluated.

Modern measures of AAO showing the positive anomalies compared to slightly negative normally in this time frame.

Discussion and Conclusions
Centennial-scale climate cycles reported previously by several investigators and in this paper are significant in at least three contexts.

First, centennial-scale climate cycles demonstrate “an important role of natural multicentennial variability that is likely to continue”. When both the mean and variance of any centennial-scale climate cycle are known, as is the case for the TOC350V cycles documented here (Table 1), then the future behavior of such cycles can be projected within well-defined confidence limits. Understanding centennial-scale temperature cycles can therefore contribute to precise climate projections over timelines that are most pertinent to human and civilizational life cycles, decades to centuries. This approach to the projection of future climate change has been pioneered by Liu and colleagues based on analysis of tree ring data from the Tibetan Plateau. From past centennial-scale temperature oscillations, they project a steep decline of temperature on the Tibetan Plateau of ~3 °C between 2006 and 2068, followed by a weaker warming trend and continuing on a cyclic basis into the future.

JMA refers to Japan El Nino index. The graph shows that often a peak in one index coincides with a valley in the other one. This suggests a teleconnection between AAO and ENSO cycles.

Second, centennial-scale paleoclimate cycles comprise a “natural” source of temperature forcing, i.e., one that is free from anthropogenic influences. Human impact on global climate from agriculture and land clearing may have begun as early as the mid-Holocene, but earlier climate change was presumably devoid of anthropogenic influences. Characterizing past cycles of temperature fluctuation can therefore help inform the distinction between natural (non-anthropogenic) and anthropogenic forcing of climate in the present, as discussed further below.

Emperor penguins  in Antarctica.

Third, Antarctic temperature fluctuations on several time scales are reflected worldwide and in the NH after a delay of 0.5 to 3.0 millennia. These delays were measured for older time periods, however, generally before the LGT, and may be shorter for more recent climate events in a warmer environment (see below). Given the close association between AIMs (Antarctic Isotope Maxima) in the Antarctic and D-O events in the NH, as demonstrated repeatedly by previous investigators, the discovery here that AIMs are composed of summated TOC350V cycles constitutes strong evidence that ACOs manifest globally. The centennial-scale climate cycles identified in the NH may be northerly manifestations of the Antarctic TOC350V climate cycle documented here, a hypothesis that remains to be tested. In the meantime, the present findings demonstrate that the ACO and its potential modern counterpart (the AAO; see below) influence the temperature of the NH. This finding suggests a potentially-fruitful research direction aimed at assessing the impact of the contemporary AAO on global climate and weather. Our study raises the possibility that the ACO/AAO entrains global temperature and serves as the primary pacemaker of centennial fluctuations in temperature in both hemispheres while simultaneously modulating shorter cycles.