January Cooling by Land, A Surprise by Sea

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With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for January.   Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month I will add a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The January update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for January. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

UAH Oceans 201901The anomalies over the entire ocean dropped to the same value, 0.12C  in August (Tropics were 0.13C).  Warming in previous months was erased, and September added very little warming back. In October and November NH and the Tropics rose, joined by SH.  In December 2018 all regions cooled resulting in a global drop of nearly 0.1C. Now in January an upward jump in SH overcame slight cooling in NH and the Tropics, pulling up the Global anomaly as well.  While the trajectory is not yet set, it is the highest ocean air January since 2016.

Land Air Temperatures Tracking Downward in Seesaw Pattern

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations record air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for January is below.UAH Land 201901

The greater volatility of the Land temperatures is evident, and also the dominance of NH, which has twice as much land area as SH.  Note how global peaks mirror NH peaks.  In December air over Tropics fell sharply, SH slightly, while the NH land surfaces rose, pulling up the Global anomaly for the month.  In January  both NH and SH cooled slightly, pulling the Global anomaly down despite some Tropical warming. Presently, air temps over land were the lowest January since 2014 both Globally and for the NH, despite warmer temps over SH and Tropical land areas.

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, now more than 1C lower than the peak in 2016.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

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Sciencing Vs. Scientism

 

What is Scientific Truth? Previous posts here have discussed the difference between science as a process of discovery (“sciencing” if you will), and science as a catalog of answers to how the world works (“scientism” in this sense). On this issue, I am following Richard Feynman, and also Arthur Eddington, who is quoted at the end.

This post dives into the struggle over truth and science in contemporary society. It also discusses some underlying philosophical confusions leading to distortions of scientific processes and discoveries. Michela Massimi is Professor of Philosophy of Science at the University of Edinburgh in Scotland. She works in history and philosophy of science and was the recipient of the 2017 Wilkins-Bernal-Medawar Medal by the Royal Society, London, UK. Her article recently published at Aeron is entitled Getting it right. Excerpts in italics with my bolds and images. My takeaway: Science matters only because Truth matters. But do read her entire essay for your own edification. Title is link to essay.

Truth is neither absolute nor timeless. But the pursuit of truth remains at the heart of the scientific endeavour

Think of the number of scenarios in which truth matters in science. We care to know whether increased CO2 emission levels cause climate change, and how fast. We care to know whether smoking tobacco increases the risk of lung cancer. We care to know whether poor diet exposes children to the risk of developing obesity, or whether forecasts of economic growth are correct. Truth in science is not esoteric dilly-dallying. It shapes climate science, medicine, public health, the economy and many other worldly endeavours.

That truth matters to science is hardly news. For a long time, people have looked to science for truths about the world. The Scientific Revolution was nothing if not the triumph of Galileo’s scientific truth – hard-won through his telescopic observations – over centuries of dogma about the geocentric system. With its system of epicycles and deferents, Ptolemaic astronomy was at once sophisticated and false. It served to, at best, ‘save the appearances’ about how planets seemed to move in the sky. It did not tell the truth about planetary motion until the discovery of the Copernican explanation. Or consider the Chemical Revolution at the end of the 18th century. We no longer, after all, believe in phlogiston – the fictional imponderable fluid that Georg Ernst Stahl, Joseph Priestley and other natural philosophers at the time believed to be at work in combustion and calcination phenomena. Antoine Lavoisier’s scientific truth about oxygen prevailed over false beliefs about phlogiston.

The main actors of these scientific revolutions often fostered this way of thinking about science as an enquiry leading to the inevitable triumph of truth over past errors. Two centuries after Galileo’s successful defence of the heliocentric system, this idea of the course of scientific truth continued to inspire philosophers. In his Cours de philosophie positive (1830-42), Auguste Comte saw the evolution of human knowledge in three main stages: ‘the Theological, or fictitious; the Metaphysical, or abstract; and the Scientific, or positive’. In the ‘positive’, the third and last stage, ‘an explanation of facts is simply the establishment of a connection between single phenomena and some general facts, the number of which continually diminishes with the progress of science’.

In some scientific quarters, this Comtean notion of how science evolves and progresses remains common currency. But philosophers of science, over the past half-century, have turned against the representation of science as a ceaseless forward march toward truth. It is just not how science works, how it moves through history. It flies in the face of the wonderful and subtle historical nuances of how scientific revolutions have in fact occurred. It does not accommodate how some of the greatest scientific minds held dearly to some false beliefs. It wilfully ignores the many voices, disagreements and controversies through which scientific knowledge has often advanced and progressed over time.

However, many (and legitimate in their own right) criticisms against this naive view of science have committed a similar mistake. They have offered a portrait of science purged of any commitment to truth. They see truth as an inconvenient and disposable feature of science. Fraught as the ideal and pursuit of truth is with tendencies to petty doctrinairism, it is nonetheless a mistake to try to purge it. The fallacy of positivist philosophy was to think of science as coming in stages of some sort, or following a particular path, or historical cycles. The anti-truth trend in the philosophy of science has often ended up repeating this same misstep. It is important to move beyond the sterile dichotomy between the old (quasi-positivist) view of truth in science and the rival anti-truth trend of recent decades.

Let us start with some genuine philosophical questions about truth in science. Here are three: 1) Does science aim at truth? 2) Does science tell us the truth? 3) Should we expect science to tell us the truth?

In each of these questions, ‘science’ is a generic placeholder for whichever scientific discipline we are interested in questioning. Question one might strike us as otiose but, in fact, it triggered one of the liveliest debates of the past 40 years. Bas van Fraassen launched this debate as to whether science aims at truth with his pioneering book The Scientific Image (1980). Does science aim to tell us a true story about nature? Or does it aim only at saving the observable phenomena (namely, providing an account that makes sense of what we can observe, without expecting it to be the true account about nature)?

There are philosophers today who embrace the view that science does not need to be true in order to be good. They argue that asking for truth is risky because it commits one to believing in things (be it epicycles, phlogiston, ether or something else) that might prove false in the future. In their view, ‘empirically adequate’ theories, theories that ‘save the observable phenomena’, are good enough for science. For example, one might take the Standard Model in high-energy physics not as aiming at the truth about whether the world is really carved up into quarks, leptons and force carriers; whether these entities really have the properties that the Standard Model says they have; and so on.

When it comes to the second question – does science tell us the truth? – scientific realists and anti-realists of various stripes have debated it. Leaving aside the aim of science, let us concentrate on its track record instead. Has science told us the truth? Looking at the history of science, does it amount to a persuasive story of truth accumulated over the centuries? Philosophers, historians, sociologists and science-studies scholars have all challenged a simple affirmative answer to this question.

This decades-long, multi-pronged, disenchantment-with-truth trend in philosophy of science starts by rejecting the idea that there are facts about nature that make our scientific claims true or false. Fact-constructivism is only one aspect of this multi-pronged disenchantment-with-truth trend. Outlandish as this might sound, its defenders claim that there is not a single, objective way that the world is; there are rather many different and ‘equally true descriptions of the world, and their truth is the only standard of their faithfulness’, in the words of the philosopher Nelson Goodman. For example, he claimed that we do make facts, but not like, say, a baker makes bread, or a sculptor makes a statue. In Goodman’s view, we make facts any time we construct what he called a ‘version’ of the world (via works of art, of music, of poetry, or of science).

We do this all the time, for example, with stars and constellations. As the philosopher Hilary Putnam expresses it: ‘Nowadays, there is a Big Dipper up there in the sky, and we, so to speak, “put” a Big Dipper up there in the sky by constructing that version.’ Goodman’s world-making view has severe implications for truth in science. ‘Truth,’ he wrote, ‘far from being a solemn and severe master, is a docile and obedient servant. The scientist who supposes that he is single-mindedly dedicated to the search for truth deceives himself … He as much decrees as discovers the laws he sets forth, as much designs as discerns the patterns he delineates.’

Fact-constructivism sounds too radical to many philosophers, and alienating to most scientists. So here is another approach against factual truth, well-known among philosophers of science. Over the past 40 years, they have produced an extraordinary amount of work on models in science. The role of abstractions and idealisations in scientific models, they maintain, is to select and to distort aspects of the relevant target system. The billiard-ball model of Brownian motion, for example, represents the motion of molecules by idealising them as perfectly spherical billiard balls. Moreover, the model abstracts, or removes, molecules from their actual environment, which is of course where collisions among molecules take place.

Studying modelling practices in science has led some to argue that science does not tell the truth but it does provide important non-factive understanding. Consider, for instance, Boyle’s gas law, which captures the relation between pressure p and volume v in an ideal gas at constant temperature. At best, Boyle’s law is true ceteris paribus (ie, all else being equal) in highly idealised and contrived circumstances. There simply is no ideal gas with perfectly spherical molecules displaying ‘atomic facts’ (in a quasi-Wittgensteinian sense) that make Boyle’s law true. Despite being true of nothing real, the billiard-ball model of Brownian motion and Boyle’s ideal gas law do nonetheless provide important non-factual understanding of the behaviour of real gases. For they allow scientists to understand the relation between decreasing volume and increasing pressure in any gas, even if there are no atomic facts in nature about perfectly spherical molecules corresponding to such idealisations.

Anti-dogmatic and anti-monist approaches to science have also questioned the value, as well as the facticity, of truth. From the 1960s, science-studies scholars began to see the word ‘truth’ as evoking unpalatable petty doctrinairism and intracultural battles in the wake of the Vietnamese war, postmodernism and, later on, what became known as the ‘science wars’. Many saw the physicist Thomas Kuhn as the forefather of a new historicist trend that dismantled what they perceived as the naive view that science aims at or tracks truth. Kuhn saw himself as ‘a fact lover and a truth seeker’. Yet in the final remarks to his classic The Structure of Scientific Revolutions (1962), he made a prescient, almost ominous, warning:

Does it really help to imagine that there is some one full, objective, true account of nature and that the proper measure of scientific achievement is the extent to which it brings us closer to the ultimate goal? … Successive stages in that developmental process are marked by an increase in articulation and specialisation. And the entire process might have occurred, as we now suppose biological evolution did, without benefit of a set goal, a permanent fixed scientific truth, of which each stage in the development of scientific knowledge is a better exemplar.

For Kuhn, truth is not an overarching aim of science across scientific revolutions. Nor do scientific revolutions (eg, from Ptolemaic to Copernican astronomy) track truth either. What they do, at best, is to increase our ability to solve anomalies that beset the previous paradigm (as when we eventually discovered that retrograde motion was only an illusion, and not something that needed epicycles and deferents to be explained).

We see the spirit of Kuhn’s warning in discussions today. Truth itself is not enough to settle or even guide debates about expertise, trust, consensus and dissent in science. The philosophers of science Inmaculada de Melo-Martín and Kristen Intemann have described the matter well in their book The Fight Against Doubt (2018). When it comes to the role of science in policymaking, the key is ‘engaging in discussions with all relevant parties about the values at stake, rather than the truth of particular scientific claims’. Policymaking involves politics and values, and ‘disagreement about values cannot, and should not, be decided by scientists alone’ or by just scientific evidence.

The third question is whether we should expect science to tell us the truth, or is truth (or at least the notion of factual truth) not best left to logicians and metaphysicians?

While critical analyses of factual truth are indeed best left to logicians and metaphysicians, philosophers of science should not abdicate their responsibility to talk about truth in science. The quasi-Wittgensteinian myth of atomic facts as the truth-makers of scientific claims has proved inadequate to even scratch the surface of very complex practices in science. But that is not a good reason (or pretext) for forgoing truth altogether. Nor is it a reason for concluding that science should not be expected to tell us the truth.

But whose truth? By whose lights? Some might be tempted at this point by a Jamesian pragmatist theory of truth. American pragmatism has traditionally provided an alternative way of thinking about truth, which some philosophers of science see as more congenial to capturing the complex nuances and the power structure of scientific practice.

In James’s words: ‘“The true” … is only the expedient in the way of our thinking, just as “the right” is only the expedient in the way of our behaving.’ Stripped of its rhetorical flourishes, for James to be true is (to a good approximation) to work successfully. A scientific model is true – on a loosely Jamesian view – if it successfully facilitates and enables activities (be they epistemic or not). If the billiard-ball model of Brownian motion helps scientists to predict the behaviour of gas molecules, for example, the model is (pragmatically) true. The falseness of the presumption of perfectly spherical molecules does not matter.

The risk with a James-inspired conception of truth, as I see it, is that it is too malleable to resist the tides of time and the stresses of social forces endlessly at work in science. A James-inspired view of truth abdicates the expectation that science tells us the truth in the name of a non-better-qualified kind of success of a scientific practice. But how to tell apart cases where success does indeed track truth from cases where it does not? More to the point, when it comes to matters such as climate change, the benefit of vaccinating children, or economic forecasts, we seem to need more than a malleable Jamesian conception of truth for the sake of scientifically informed decisions that do not bow to pressure from powerful lobbies and political agendas (in the name of what ‘might work’). But, someone might reply, how can truth and pluralism go hand in hand if not by opting for a Jamesian conception of truth (if we really care about truth at all)?

There is another way of thinking about how truth and pluralism might go hand in hand, without reducing matters of truth to calculations of what is pragmatically good to individuals or communities sharing a scientific perspective at some point in time. First, it is necessary to understand the key term ‘scientific perspective’ and how it impinges on scientific pluralism. In its original use by the philosopher Ronald Giere in 2006, ‘scientific perspective’ is akin to Kuhn’s disciplinary matrix: a set of scientific models (including the relevant experimental instruments to gather data). In broader terms, scientific perspective is the disciplinary practice of a real scientific community at any given historical time. It includes the knowledge they produce, and the theoretical, technological and experimental resources they use, or that guide their work.

The time for a defence of truth in science has come. It begins with a commitment to get things right, which is at the heart of the realist programme, despite mounting Kuhnian challenges from the history of science, considerations about modelling, and values in contemporary scientific practice. In the simple-minded sense, getting things right means that things are as the relevant scientific theory says that they are. Climate science is true if what it says about CO2 emissions (and their effects on climate change) corresponds to the way that things are in nature. For the sake of powerful economic interests, sociopolitical consequences or simply different economic principles, one can try to discount, mitigate, compensate for, disregard or ignore altogether the way that things are. But doing so is to forgo the normative nature of the realist commitment in science. The scientific world, we have seen, is too complex and messy to be represented by any quasi-Wittgensteinian picture of atomic facts. Nor can the naive image of Comte’s positive science render justice to it. But acknowledging complexity and historical nuances gives no reason (or justification) for forgoing truth altogether; much less for concluding that science trades in falsehoods of some kind. It is part of our social responsibility as philosophers of science to set the record straight on such matters.

We should expect science to tell us the truth because, by realist lights, this is what science ought to do. Truth – understood as getting things right – is not the aim of science, because it is not what science (or, better, scientists) should aspire to (assuming one has realist leanings). Instead, it is what science ought to do by realist lights. Thus, to judge a scientific theory or model as true is to judge it as one that ‘commands our assent’. Truth, ultimately, is not an aspiration; a desirable (but maybe unachievable) goal; a figment in the mind of the working scientist; or, worse, an insupportable and dispensable burden in scientific research. Truth is a normative commitment inherent in scientific knowledge.

Constructive empiricists, instrumentalists, Jamesian pragmatists, relativists and constructivists do not share the same commitment. They do not share with the realist a suitable notion of ‘rightness’. As an example, compare the normative commitment to get things right with the view of the philosopher Richard Rorty, in whose hands Putnam’s truth as ‘idealised warranted assertibility’ reduces to what is acceptable to ‘us as we should like to be … us educated, sophisticated, tolerant, wet liberals, the people who are always willing to hear the other side, to think out all the implications’.

Getting things right is not a norm about us at our best, ‘educated, sophisticated, tolerant, wet liberals’. It is a norm inherent in scientific knowledge. To claim to know something in science (or about a scientific topic or domain) is to claim for the truth of the relevant beliefs about that topic or domain.

Thinking of truth as a normative commitment inherent in the very notion of scientific knowledge brings some benefits. It overcomes a false dichotomy between atomic facts and non-factive, non-truth-conducive inferences. And it makes realism compatible with perspectivism. Scientific communities that endorse historically and culturally situated scientific perspectives (either across the history of science or in contemporary science, across different fields or different scientific programmes) share (and indeed ought to) a normative commitment to get things right. That is a minimum requirement to pass the bar of what we count as ‘scientific knowledge’.

Getting the evidence right, in the first instance – via accurate measurements, sound non-ad-hoc procedures, and robust inferential strategies – defines any research programme that is worth being called ‘scientific’. The realist commitment to get things right must begin with getting the evidence right. No perspective worthy of being called ‘scientific’ survives fudging the evidence, massaging or altering the data or discarding evidence.

Scientists ought to share rules for cross-perspectival assessment. That our knowledge is situated and perspectival does not make scientific truths relativised to perspectives. Often enough, scientific perspectives themselves provide the rules for cross-perspectival assessment. Those rules can be as simple as translating the 10 degree Celsius temperature in Edinburgh today into the 50 degree equivalent on the Fahrenheit scale. Or they can be as complex as retrieving the viscosity of a fluid in statistical mechanics, where fluids are treated as statistical ensembles of a large number of discrete molecules.

Let there be no doubt: scientific knowledge is the product of our getting it right across our perspectival multicultural scientific history. Scientific knowledge is not a prerogative of our Western cultural perspective (and its discipline-specific scientific perspectives) but the outcome of a plurality of historically and culturally situated scientific perspectives that, over millennia, have reliably produced knowledge with the tools, resources and concepts respectively available to each and every one of them.

Scientific truths are the resilient and robust outcome of a plurality of scientific perspectives that, over time, have meshed with one another in their (tacit, implicit and often survival-adaptive) normative commitment to reliably produce scientific knowledge for us as humankind. That is why, far from being an insufferable hindrance to scientific pluralism, truth is in fact its best safeguard in tolerant, open and democratic societies that are genuinely committed to the advancement of scientific knowledge in the very many faces it comes with.

Footnote: 

Religious creeds are a great obstacle to any full sympathy between the outlook of the scientist and the outlook which religion is so often supposed to require … The spirit of seeking which animates us refuses to regard any kind of creed as its goal. It would be a shock to come across a university where it was the practice of the students to recite adherence to Newton’s laws of motion, to Maxwell’s equations and to the electromagnetic theory of light. We should not deplore it the less if our own pet theory happened to be included, or if the list were brought up to date every few years. We should say that the students cannot possibly realise the intention of scientific training if they are taught to look on these results as things to be recited and subscribed to. Science may fall short of its ideal, and although the peril scarcely takes this extreme form, it is not always easy, particularly in popular science, to maintain our stand against creed and dogma.
― Arthur Stanley Eddington

See Also: 

Data, Facts and Information

Three Wise Men Talking Climate

Head, Heart and Science

Post-Truth Climatism

How Science Is Losing Its Humanity

 

Climate Models Cover Up

Making Climate Models Look Good

Clive Best dove into climate models temperature projections and discovered how the data can be manipulated to make model projections look closer to measurements than they really are. His first post was A comparison of CMIP5 Climate Models with HadCRUT4.6 January 21, 2019. Excerpts in italics with my bolds.

Overview: Figure 1. shows a comparison of the latest HadCRUT4.6 temperatures with CMIP5 models for Representative Concentration Pathways (RCPs). The temperature data lies significantly below all RCPs, which themselves only diverge after ~2025.

Modern Climate models originate from Global Circulation models which are used for weather forecasting. These simulate the 3D hydrodynamic flow of the atmosphere and ocean on earth as it rotates daily on its tilted axis, and while orbiting the sun annually. The meridional flow of energy from the tropics to the poles generates convective cells, prevailing winds, ocean currents and weather systems. Energy must be balanced at the top of the atmosphere between incoming solar energy and out going infra-red energy. This depends on changes in the solar heating, water vapour, clouds , CO2, Ozone etc. This energy balance determines the surface temperature.

Weather forecasting models use live data assimilation to fix the state of the atmosphere in time and then extrapolate forward one or more days up to a maximum of a week or so. Climate models however run autonomously from some initial state, stepping far into the future assuming that they correctly simulate a changing climate due to CO2 levels, incident solar energy, aerosols, volcanoes etc. These models predict past and future surface temperatures, regional climates, rainfall, ice cover etc. So how well are they doing?

Fig 2. Global Surface temperatures from 12 different CMIP5 models run with RCP8.5

The disagreement on the global average surface temperature is huge – a spread of 4C. This implies that there must still be a problem relating to achieving overall energy balance at the TOA. Wikipedia tells us that the average temperature should be about 288K or 15C. Despite this discrepancy in reproducing net surface temperature the model trends in warming for RCP8.5 are similar.

Likewise weather station measurements of temperature have changed with time and place, so they too do not yield a consistent absolute temperature average. The ‘solution’ to this problem is to use temperature ‘anomalies’ instead, relative to some fixed normal monthly period (baseline). I always use the same baseline as CRU 1961-1990. Global warming is then measured by the change in such global average temperature anomalies. The implicit assumption of this is that nearby weather station and/or ocean measurements warm or cool coherently, such that the changes in temperature relative to the baseline can all be spatially averaged together. The usual example of this is that two nearby stations with different altitudes will have different temperatures but produce the similar ‘anomalies’. A similar procedure is used on the model results to produce temperature anomalies. So how do they compare to the data?

Fig 4. Model comparisons to data 1950-2050

Figure 4 shows a close up detail from 1950-2050. This shows how there is a large spread in model trends even within each RCP ensemble. The data falls below the bulk of model runs after 2005 except briefly during the recent el Nino peak in 2016.  Figure 4. shows that the data are now lower than the mean of every RCP, furthermore we won’t be able to distinguish between RCPs until after ~2030.

Zeke Hausfather’s Tricks to Make the Models Look Good

Clive’s second post is Zeke’s Wonder Plot January 25,2019. Excerpts in italics with my bolds.

Zeke Hausfather who works for Carbon Brief and Berkeley Earth has produced a plot which shows almost perfect agreement between CMIP5 model projections and global temperature data. This is based on RCP4.5 models and a baseline of 1981-2010. First here is his original plot.

I have reproduced his plot and  essentially agree that it is correct. However, I also found some interesting quirks.

The apples to apples comparison (model SSTs blended with model land 2m temperatures) reduces the model mean by about 0.06C. Zeke has also smoothed out the temperature data by using a 12 month running average. This has the effect of exaggerating peak values as compared to using the annual averages.

Effect of changing normalisation period. Cowtan & Way uses kriging to interpolate Hadcrut4.6 coverage into the Arctic and elsewhere.

Shown above is the result for a normalisation from 1961-1990. Firstly look how the lowest 2 model projections now drop further down while the data seemingly now lies below both the blended (thick black) and the original CMIP average (thin black). HadCRUT4 2016 is now below the blended value.

This improved model agreement has nothing to do with the data itself but instead is due to a reduction in warming predicted by the models. So what exactly is meant by ‘blending’?

Measurements of global average temperature anomalies use weather stations on land and sea surface temperatures (SST) over oceans. The land measurements are “surface air temperatures”(SAT) defined as the temperature 2m above ground level. The CMIP5 simulations however used SAT everywhere. The blended model projections use simulated SAT over land and TOS (temperature at surface) over oceans. This reduces all model predictions slightly, thereby marginally improving agreement with data. See also Climate-lab-book

The detailed blending calculations were done by Kevin Cowtan using a land mask and ice mask to define where TOS and SAT should be used in forming the global average. I downloaded his python scripts and checked all the algorithm, and they look good to me. His results are based on the RCP8.5 ensemble

The solid blue curve is the CMIP5 RCP4.6 ensemble average after blending. The dashed curve is the original. Click to expand.

Again the models mostly lie above the data after 1999.

This post is intended to demonstrate just how careful you must be when interpreting plots that seemingly demonstrate either full agreement of climate models with data, or else total disagreement.

In summary, Zeke Hausfather writing for Carbon Brief 1) used a clever choice of baseline, 2) of RCP for blended models and 3) by using a 12 month running average, was able to show an almost perfect agreement between data and models. His plot is 100% correct. However exactly the same data plotted with a different baseline and using annual values (exactly like those in the models), instead of 12 monthly running averages shows instead that the models are still lying consistently above the data. I know which one I think best represents reality.

Moral to the Story:
There are lots of ways to make computer models look good.Try not to be distracted.

Update Jan.22: Hot Ocean False Alarm

What is Argo? Argo is a global array of 3,800 free-drifting profiling floats that measures thetemperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection. Positions of the floats that have delivered data within the last 30 days :

Scientists deploy an Argo float. For over a decade, more than 3000 floats have provided near-global data coverage for the upper 2000 m of the ocean.

Update January 22, 2019

In a post at GWPF Nic Lewis critiques the Cheng et al. study and points in detail to the errors and misleading findings.  His short analysis: Is ocean warming accelerating faster than thought? – An analysis of Cheng et al (2019), Science . Excerpt in italics with my bolds.

Contrary to what the paper indicates:
Contemporary estimates of the trend in 0–2000 m depth ocean heat content over 1971–2010 are closely in line with that assessed in the IPCC AR5 report five years ago
Contemporary estimates of the trend in 0–2000 m depth ocean heat content over 2005–2017 are significantly (> 95% probability) smaller than the mean CMIP5 model simulation trend.

lewis fig.1

Figure 1: Updated 0–2000 m OHC linear trend estimates compared with AR5 and the CMIP5 mean. Error bars are 90% confidence intervals; black lines are means. Units relate to the Earth’s entire surface area.

falsealarm02

Previous Post:  Scare of the Day:  Ocean Heat Content (January 11, 2019)

Here is a sample of yesterday’s coordinated reports from CCN- Climate Crisis Network captured by my news aggregator, listed by the most recent first. Note the worldwide scope and editorial poetic license on the titles.

Ocean warming accelerating to record temperatures, scientists warn Engineering and Technology Magazine
Scalding seas? Oceans boil to hottest temp on record USA Today EU
World’s oceans heating up at quickening pace: study Egypt Independent
Ocean warming ‘accelerating’ The London Economic
Oceans warming faster than we thought: Study AniNews.in
Ocean temperatures rising faster than thought in ‘delayed response’ to global warming, scientists say The Japan Times
Oceans warming much faster than previously thought: Study The Hindu Business Line
The Oceans Are Warming Faster Than We Thought, a New Study Says TIME
Oceans Warming Even Faster Than Previously Thought Eurasia Review
The Ocean Is Warming Much Faster Than We Thought, According To A New Study BuzzFeed
Pacific: New research proves ocean warming is accelerating ABC Online – Radio Australia
We’re Boiling the Ocean Faster Than We Thought New York Magazine
Oceans warming faster than expected SBS
Ocean temperatures are rising far faster than previously thought, report says TVNZ
Ocean Temps Rising Faster Than Scientists Thought: Report HuffPost (US)
World’s oceans are heating up at a quickening pace Bangkok Post
The Warming of the World’s Oceans Is Set to Increase Dramatically Over the Next 60 Years Pacific Standard
New Climate Change Report Says Ocean Warming Is Far Worse Than Expected Fortune
Oceans Are Warming Faster Than Expected, Research Says Geek.com
World’s oceans are heating up at a quickening pace: study AFP
Oceans Warming Faster Than Predicted, Scientists Say gCaptain

So the message to the world is very clear: Ocean Heat Content is rising out of control, Be Very Afraid!
The trigger for all of this concern comes from this paper How fast are the oceans warming? by Lijing Cheng, John Abraham, Zeke Hausfather, Kevin E. Trenberth. Science 11 Jan 2019 Excerpts from paper in italics with my bolds.

Climate change from human activities mainly results from the energy imbalance in Earth’s climate system caused by rising concentrations of heat-trapping gases. About 93% of the energy imbalance accumulates in the ocean as increased ocean heat content (OHC). The ocean record of this imbalance is much less affected by internal variability and is thus better suited for detecting and attributing human influences (1) than more commonly used surface temperature records. Recent observation-based estimates show rapid warming of Earth’s oceans over the past few decades (see the figure) (1, 2). This warming has contributed to increases in rainfall intensity, rising sea levels, the destruction of coral reefs, declining ocean oxygen levels, and declines in ice sheets; glaciers; and ice caps in the polar regions (3, 4). Recent estimates of observed warming resemble those seen in models, indicating that models reliably project changes in OHC.

The Intergovernmental Panel on Climate Change’s Fifth Assessment Report (AR5), published in 2013 (4), featured five different time series of historical global OHC for the upper 700 m of the ocean. These time series are based on different choices for data processing (see the supplementary materials). Interpretation of the results is complicated by the fact that there are large differences among the series. Furthermore, the OHC changes that they showed were smaller than those projected by most climate models in the Coupled Model Intercomparison Project 5 (CMIP5) (5) over the period from 1971 to 2010 (see the figure).

Since then, the research community has made substantial progress in improving long-term OHC records and has identified several sources of uncertainty in prior measurements and analyses (2, 6–8). In AR5, all OHC time series were corrected for biases in expendable bathythermograph (XBT) data that had not been accounted for in the previous report (AR4). But these correction methods relied on very different assumptions of the error sources and led to substantial differences among correction schemes. Since AR5, the main factors influencing the errors have been identified (2), helping to better account for systematic errors in XBT data and their analysis.

Multiple lines of evidence from four independent groups thus now suggest a stronger observed OHC warming. Although climate model results (see the supplementary materials) have been criticized during debates about a “hiatus” or “slowdown” of global mean surface temperature, it is increasingly clear that the pause in surface warming was at least in part due to the redistribution of heat within the climate system from Earth surface into the ocean interiors (13). The recent OHC warming estimates (2, 6, 10, 11) are quite similar to the average of CMIP5 models, both for the late 1950s until present and during the 1971–2010 period highlighted in AR5 (see the figure). The ensemble average of the models has a linear ocean warming trend of 0.39 ± 0.07 W m−2 for the upper 2000 m from 1971–2010 compared with recent observations ranging from 0.36 to 0.39 W m−2 (see the figure).

MISSION ACCOMPLISHED: “The recent OHC warming estimates are quite similar to the average of CMIP5 models.”

What They are Not Telling You

The Sea Surface Temperature (SST) record is a mature dataset, not without issues from changing measurement technologies, but providing a lengthy set of observations making up 71% of the surface temperature history.  Sussing out temperatures at various depths in the ocean is a whole nother kettle of fish.

The Ocean Heat Content data is sparse, both in time and space.

The Ocean is vast, 360 million square kilometers with an average depth of 3700 meters, and we have 3900 Argo floats operating for 10 years. In addition we have some sensors arrayed at depths in the North Atlantic. As the text above admits, there are lots of holes in the data, and only a short history of the recently available reliable data. Other publications by some of the same authors admit: Large discrepancies are found in the percentage of basinal ocean heating related to the global ocean, with the largest differences in the Pacific and Southern Ocean. Meanwhile, we find a large discrepancy of ocean heat storage in different layers, especially within 300–700 m in the Pacific and Southern Oceans. Source: Consensuses and discrepancies of basin-scale ocean heat content changes in different ocean analyses, Gongjie Wang, Lijing Cheng, John Abraham.

Modelers Make OHC Reconstructions by Adding Guesstimates to Observations

Again climate science alarms are raised after “reanalysis” of the data. No one should be surprised that after computer manipulations and data processing, the “reanalyzed” data has changed and now favors warming and confirms the climate models. The Argo data record by itself is too short to make any such claim. In previous studies, scientists were more circumspect and refrained from “jumping the shark.” Apparently, with the Paris Accord on the ropes in 2019, caution and nuance has been thrown to the wind, as witnessed by the recent SR15 horror show, and now this.

Methodological Problems Bedevil These Reconstructions

One of the studies cited in support of revising OHC upward is the study Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition, L. Resplandy et al. Published in Nature 31 October 2018.  From the Media Release:

The world’s oceans have absorbed far more heat than we realized, shortening our timeline to stop the causes of global warming, and foreboding some of the worst case scenarios put forth by climate experts, according to new findings.

A novel study by researchers from Scripps Institution of Oceanography at the University of California San Diego and Princeton University, published on Wednesday in Nature, implies that officials have underestimated the amount of heat retained by Earth’s oceans.

Between 1991 and 2016, oceans warmed an average 60 percent more than estimates by the Intergovernmental Panel on Climate Change (IPCC) originally calculated, the study claims. That amount equalled 13 zettajoules, or eight times the world’s annual energy consumption.

Something didn’t look right to climate statistician Nic Lewis so he deconstructed the study, finding several methodological mistakes along the way. He explained and communicated with the authors in a series of 4 posts at Climate Etc. Nov. 6 through 23, 2018.

Nic Lewis, Nov. 6 (here):

The findings of the Resplandy et al paper were peer reviewed and published in the world’s premier scientific journal and were given wide coverage in the English-speaking media. Despite this, a quick review of the first page of the paper was sufficient to raise doubts as to the accuracy of its results. Just a few hours of analysis and calculations, based only on published information, was sufficient to uncover apparently serious (but surely inadvertent) errors in the underlying calculations.

Moreover, even if the paper’s results had been correct, they would not have justified its findings regarding an increase to 2.0°C in the lower bound of the equilibrium climate sensitivity range and a 25% reduction in the carbon budget for 2°C global warming.

Because of the wide dissemination of the paper’s results, it is extremely important that these errors are acknowledged by the authors without delay and then corrected.

Authors Respond:

On November 14, 2018 this paper’s authors announced key errors to the two week-old study that made claims about the amount of heat that Earth’s oceans have absorbed. The errors stem from “incorrectly treating systematic errors in the O2 measurements and the use of a constant land O2:C exchange ratio of 1.1,” co-author Ralph Keeling said in an update from Scripps Institution of Oceanography, which is affiliated with the study. More simply, the team’s findings are too uncertain to conclusively support their statement that Earth’s oceans have absorbed 60 percent more heat than previously thought. Keeling claims the errors “do not invalidate the study’s methodology or the new insights into ocean biogeochemistry on which it is based.”

Subsequent posts by Lewis found other differences between the stated method and the analysis actually applied, adding to the uncertainty of the study and its finding. Lewis is not done yet, and the paper has not been reissued. Unfortunately, it has not been retracted and is still cited in reference to unsupported claims of runaway ocean heat content.

Meanwhile, other measurements, such as those in North Atlantic and Indian Ocean show slight cooling rather than warming, with researchers suspecting natural cyclical activity.

Summary

So anxious are alarmists/activists to cry wolf that they are running the computers flat out to manipulate and extrapolate from precious but incomplete limited data to confirm their suppositions.  All to keep alive a deflating narrative that the public increasingly finds offensive.

Footnote:

Oceanographers know that deep ocean temperatures can vary on centennial up to millennial time scales, so if some heat goes into the depths, it is not at all clear when it would come out.

Beware getting sucked into any model, climate or otherwise.

More at Putting Climate Models in Their Place

Scare of the Day: Ocean Heat Content

What is Argo? Argo is a global array of 3,800 free-drifting profiling floats that measures thetemperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection. Positions of the floats that have delivered data within the last 30 days :

Scientists deploy an Argo float. For over a decade, more than 3000 floats have provided near-global data coverage for the upper 2000 m of the ocean.

Here is a sample of yesterday’s coordinated reports from CCN- Climate Crisis Network captured by my news aggregator, listed by the most recent first. Note the worldwide scope and editorial poetic license on the titles.

Ocean warming accelerating to record temperatures, scientists warn Engineering and Technology Magazine
Scalding seas? Oceans boil to hottest temp on record USA Today EU
World’s oceans heating up at quickening pace: study Egypt Independent
Ocean warming ‘accelerating’ The London Economic
Oceans warming faster than we thought: Study AniNews.in
Ocean temperatures rising faster than thought in ‘delayed response’ to global warming, scientists say The Japan Times
Oceans warming much faster than previously thought: Study The Hindu Business Line
The Oceans Are Warming Faster Than We Thought, a New Study Says TIME
Oceans Warming Even Faster Than Previously Thought Eurasia Review
The Ocean Is Warming Much Faster Than We Thought, According To A New Study BuzzFeed
Pacific: New research proves ocean warming is accelerating ABC Online – Radio Australia
We’re Boiling the Ocean Faster Than We Thought New York Magazine
Oceans warming faster than expected SBS
Ocean temperatures are rising far faster than previously thought, report says TVNZ
Ocean Temps Rising Faster Than Scientists Thought: Report HuffPost (US)
World’s oceans are heating up at a quickening pace Bangkok Post
The Warming of the World’s Oceans Is Set to Increase Dramatically Over the Next 60 Years Pacific Standard
New Climate Change Report Says Ocean Warming Is Far Worse Than Expected Fortune
Oceans Are Warming Faster Than Expected, Research Says Geek.com
World’s oceans are heating up at a quickening pace: study AFP
Oceans Warming Faster Than Predicted, Scientists Say gCaptain

So the message to the world is very clear: Ocean Heat Content is rising out of control, Be Very Afraid!
The trigger for all of this concern comes from this paper How fast are the oceans warming? by Lijing Cheng, John Abraham, Zeke Hausfather, Kevin E. Trenberth. Science 11 Jan 2019 Excerpts from paper in italics with my bolds.

Climate change from human activities mainly results from the energy imbalance in Earth’s climate system caused by rising concentrations of heat-trapping gases. About 93% of the energy imbalance accumulates in the ocean as increased ocean heat content (OHC). The ocean record of this imbalance is much less affected by internal variability and is thus better suited for detecting and attributing human influences (1) than more commonly used surface temperature records. Recent observation-based estimates show rapid warming of Earth’s oceans over the past few decades (see the figure) (1, 2). This warming has contributed to increases in rainfall intensity, rising sea levels, the destruction of coral reefs, declining ocean oxygen levels, and declines in ice sheets; glaciers; and ice caps in the polar regions (3, 4). Recent estimates of observed warming resemble those seen in models, indicating that models reliably project changes in OHC.

The Intergovernmental Panel on Climate Change’s Fifth Assessment Report (AR5), published in 2013 (4), featured five different time series of historical global OHC for the upper 700 m of the ocean. These time series are based on different choices for data processing (see the supplementary materials). Interpretation of the results is complicated by the fact that there are large differences among the series. Furthermore, the OHC changes that they showed were smaller than those projected by most climate models in the Coupled Model Intercomparison Project 5 (CMIP5) (5) over the period from 1971 to 2010 (see the figure).

Since then, the research community has made substantial progress in improving long-term OHC records and has identified several sources of uncertainty in prior measurements and analyses (2, 6–8). In AR5, all OHC time series were corrected for biases in expendable bathythermograph (XBT) data that had not been accounted for in the previous report (AR4). But these correction methods relied on very different assumptions of the error sources and led to substantial differences among correction schemes. Since AR5, the main factors influencing the errors have been identified (2), helping to better account for systematic errors in XBT data and their analysis.

Multiple lines of evidence from four independent groups thus now suggest a stronger observed OHC warming. Although climate model results (see the supplementary materials) have been criticized during debates about a “hiatus” or “slowdown” of global mean surface temperature, it is increasingly clear that the pause in surface warming was at least in part due to the redistribution of heat within the climate system from Earth surface into the ocean interiors (13). The recent OHC warming estimates (2, 6, 10, 11) are quite similar to the average of CMIP5 models, both for the late 1950s until present and during the 1971–2010 period highlighted in AR5 (see the figure). The ensemble average of the models has a linear ocean warming trend of 0.39 ± 0.07 W m−2 for the upper 2000 m from 1971–2010 compared with recent observations ranging from 0.36 to 0.39 W m−2 (see the figure).

MISSION ACCOMPLISHED: “The recent OHC warming estimates are quite similar to the average of CMIP5 models.”

What They are Not Telling You

The Sea Surface Temperature (SST) record is a mature dataset, not without issues from changing measurement technologies, but providing a lengthy set of observations making up 71% of the surface temperature history.  Sussing out temperatures at various depths in the ocean is a whole nother kettle of fish.

The Ocean Heat Content data is sparse, both in time and space.

The Ocean is vast, 360 million square kilometers with an average depth of 3700 meters, and we have 3900 Argo floats operating for 10 years. In addition we have some sensors arrayed at depths in the North Atlantic. As the text above admits, there are lots of holes in the data, and only a short history of the recently available reliable data. Other publications by some of the same authors admit: Large discrepancies are found in the percentage of basinal ocean heating related to the global ocean, with the largest differences in the Pacific and Southern Ocean. Meanwhile, we find a large discrepancy of ocean heat storage in different layers, especially within 300–700 m in the Pacific and Southern Oceans. Source: Consensuses and discrepancies of basin-scale ocean heat content changes in different ocean analyses, Gongjie Wang, Lijing Cheng, John Abraham.

Modelers Make OHC Reconstructions by Adding Guesstimates to Observations

Again climate science alarms are raised after “reanalysis” of the data. No one should be surprised that after computer manipulations and data processing, the “reanalyzed” data has changed and now favors warming and confirms the climate models. The Argo data record by itself is too short to make any such claim. In previous studies, scientists were more circumspect and refrained from “jumping the shark.” Apparently, with the Paris Accord on the ropes in 2019, caution and nuance has been thrown to the wind, as witnessed by the recent SR15 horror show, and now this.

Methodological Problems Bedevil These Reconstructions

One of the studies cited in support of revising OHC upward is the study Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition, L. Resplandy et al. Published in Nature 31 October 2018.  From the Media Release:

The world’s oceans have absorbed far more heat than we realized, shortening our timeline to stop the causes of global warming, and foreboding some of the worst case scenarios put forth by climate experts, according to new findings.

A novel study by researchers from Scripps Institution of Oceanography at the University of California San Diego and Princeton University, published on Wednesday in Nature, implies that officials have underestimated the amount of heat retained by Earth’s oceans.

Between 1991 and 2016, oceans warmed an average 60 percent more than estimates by the Intergovernmental Panel on Climate Change (IPCC) originally calculated, the study claims. That amount equalled 13 zettajoules, or eight times the world’s annual energy consumption.

Something didn’t look right to climate statistician Nic Lewis so he deconstructed the study, finding several methodological mistakes along the way. He explained and communicated with the authors in a series of 4 posts at Climate Etc. Nov. 6 through 23, 2018.

Nic Lewis, Nov. 6 (here):

The findings of the Resplandy et al paper were peer reviewed and published in the world’s premier scientific journal and were given wide coverage in the English-speaking media. Despite this, a quick review of the first page of the paper was sufficient to raise doubts as to the accuracy of its results. Just a few hours of analysis and calculations, based only on published information, was sufficient to uncover apparently serious (but surely inadvertent) errors in the underlying calculations.

Moreover, even if the paper’s results had been correct, they would not have justified its findings regarding an increase to 2.0°C in the lower bound of the equilibrium climate sensitivity range and a 25% reduction in the carbon budget for 2°C global warming.

Because of the wide dissemination of the paper’s results, it is extremely important that these errors are acknowledged by the authors without delay and then corrected.

Authors Respond:

On November 14, 2018 this paper’s authors announced key errors to the two week-old study that made claims about the amount of heat that Earth’s oceans have absorbed. The errors stem from “incorrectly treating systematic errors in the O2 measurements and the use of a constant land O2:C exchange ratio of 1.1,” co-author Ralph Keeling said in an update from Scripps Institution of Oceanography, which is affiliated with the study. More simply, the team’s findings are too uncertain to conclusively support their statement that Earth’s oceans have absorbed 60 percent more heat than previously thought. Keeling claims the errors “do not invalidate the study’s methodology or the new insights into ocean biogeochemistry on which it is based.”

Subsequent posts by Lewis found other differences between the stated method and the analysis actually applied, adding to the uncertainty of the study and its finding. Lewis is not done yet, and the paper has not been reissued. Unfortunately, it has not been retracted and is still cited in reference to unsupported claims of runaway ocean heat content.

Meanwhile, other measurements, such as those in North Atlantic and Indian Ocean show slight cooling rather than warming, with researchers suspecting natural cyclical activity.

Summary

So anxious are alarmists/activists to cry wolf that they are running the computers flat out to manipulate and extrapolate from precious but incomplete limited data to confirm their suppositions.  All to keep alive a deflating narrative that the public increasingly finds offensive.

Footnote:

Oceanographers know that deep ocean temperatures can vary on centennial up to millennial time scales, so if some heat goes into the depths, it is not at all clear when it would come out.

Beware getting sucked into any model, climate or otherwise.

More at Putting Climate Models in Their Place

December Cooling by Sea, More than by Land

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for December.   Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month I will add a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The December update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for December. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

uah oceans 201812The anomalies over the entire ocean dropped to the same value, 0.12C  in August (Tropics were 0.13C).  Warming in previous months was erased, and September added very little warming back. In October and November NH and the Tropics rose, joined by SH last month.,  In December 2018 all regions cooled resulting in a global drop of nearly 0.1C.

Taking a longer view, we can look at the record since 1995, that year being an ENSO neutral year and thus a reasonable starting point for considering the past two decades.  On that basis we can see the plateau in ocean temps is persisting. Global ocean temps are the lowest December since 2014.  It also appears that the NH Autumn upward bump is over and temps will likely trend downward.

Land Air Temperatures Plunged in September, then Rose in October

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations record air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for December is below.uah land 201812

The greater volatility of the Land temperatures is evident, and also the dominance of NH, which has twice as much land area as SH.  Note how global peaks mirror NH peaks.  In December air over Tropics fell sharply, SH slightly, while the NH land surfaces rose, pulling up the Global anomaly for the month.  Despite the warming, air temps over land were the lowest December since 2013 both Globally and for the Tropics.  And all regions are cooler than December 2015 when the El Nino was starting in earnest.

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  It is striking to now see NH and Global land temps dropping rapidly.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

November Cooling by Land, or Cooling by Sea?

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for November.   Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month I will add a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The November update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for November. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

UAH Oceans 201811

Open image in new tab to enlarge.

The anomalies over the entire ocean dropped to the same value, 0.12C  in August (Tropics were 0.13C).  Warming in previous months was erased, and September added very little warming back. In October and November, NH and the Tropics rose, joined by SH last month, resulting in a warming bump.

As of November 2018, NH ocean air temps are matching all Novembers since 2013.  Global and SH this year are the lowest November since 2015.  OTOH ocean air temps in the Tropics are the highest November since 2015.

Land Air Temperatures Plunged in September, Rose in October, Then Plunged Again

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations record air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for November is below.UAH Land 201811

The greater volatility of the Land temperatures is evident, and also the dominance of NH, which has twice as much land area as SH.  Note how global peaks mirror NH peaks.  In November air over SH and the Tropical land surfaces rose, while NH fell sharply pulling the global anomaly down.  For the moment, UAH shows ocean and land temps moving in opposite directions, though still well below the peaks in 2015 and 2016.

Postscript:  NH Continents Drive  Variability in Temperature Anomalies

Clive Best provides this animation of recent monthly temperature anomalies which demonstrates how most variability in anomalies occur over northern continents.

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  It is striking to now see NH and Global land temps dropping in a mixed fashion.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

October Cooling by Land, or Cooling by Sea?

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for October.   Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month I will add a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The October update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for October. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

UAH Oceans 201810

Open image in new tab to enlarge.

The anomalies over the entire ocean dropped to the same value, 0.12C  in August (Tropics were 0.13C).  Warming in previous months was erased, and September added very little warming back. In October, NH and the Tropics rose, while SH cooled, resulting in slight warming.

Taking a longer view, we can look at the record since 1995, that year being an ENSO neutral year and thus a reasonable starting point for considering the past two decades.  On that basis we can see the plateau in ocean temps is persisting. Since last October all oceans have cooled, with offsetting bumps up and down.

UAHv6 TLT 
Monthly Ocean
Anomalies
Average Since 1995 Ocean 10/2018
Global 0.13 0.17
NH 0.16 0.30
SH 0.11 0.08
Tropics 0.12 0.32

As of October 2018, NH ocean air temps as well as the Tropics are twice the long term average, SH is slightly cooler, and the Global anomaly slightly warmer.   In the Tropics and SH, 2018 is the coolest October since 2014. The Global and NH ocean air temps are the coolest October since 2013.

Land Air Temperatures Plunged in September, then Rose in October

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations record air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for October is below.UAH Land 201810

The greater volatility of the Land temperatures is evident, and also the dominance of NH, which has twice as much land area as SH.  Note how global peaks mirror NH peaks.  In October air over NH and the Tropical land surfaces rose, and SH followed suit.  A table for Land temperatures is below, comparable to the one for Oceans.

UAHv6 TLT 
Monthly Land
Anomalies
Average Since 1995 Land 10/2018
Global 0.21 0.33
NH 0.23 0.33
SH 0.19 0.33
Tropics 0.18 0.39

In September land air temps were below the average since 1995.  As the table shows, in October the land air anomalies jumped up well above average, demonstrating the higher volatility of these measures.  Still last month was much cooler than October 2017 in all regions.

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  It is striking to now see NH and Global land temps dropping rapidly.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

Cooling by Land, or Cooling by Sea?

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  UAH has updated their tlt (temperatures in lower troposphere) dataset for September.   Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month I will add a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The August update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for August. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

UAH Oceans 201809The anomalies over the entire ocean dropped to the same value, 0.12C  in August (Tropics were 0.13C).  Warming in previous months was erased, and September added very little warming back.

Taking a longer view, we can look at the record since 1995, that year being an ENSO neutral year and thus a reasonable starting point for considering the past two decades.  On that basis we can see the plateau in ocean temps is persisting. Since last October all oceans have cooled, with offsetting bumps up and down.

UAHv6 TLT 
Monthly Ocean
Anomalies
Average Since 1995 Ocean 9/2018
Global 0.13 0.15
NH 0.16 0.18
SH 0.11 0.13
Tropics 0.12 0.22

As of September 2018, Global ocean air temps as well as SH and SH are nearly the average since 1995.  The Tropics bumped upward last month. Globally,  in NH and the Tropics, 2018 is the coolest September since 2014. The SH ocean air temps are the coolest September since 2013

Land Air Temperatures Plunged in September.

We sometimes overlook that in climate temperature records, while the oceans are measured directly with SSTs, land temps are measured only indirectly.  The land temperature records at surface stations record air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for September is below.
UAH Land 201809

The greater volatility of the Land temperatures is evident, and also the dominance of NH, which has twice as much land area as SH.  Note how global peaks mirror NH peaks.  Thus the importance of the recent drops in NH and SH driving global land temps downward.  A table for Land temperatures is below, comparable to the one for Oceans.

UAHv6 TLT 
Monthly Land
Anomalies
Average Since 1995 Land 9/2018
Global 0.21 0.13
NH 0.23 0.10
SH 0.12 0.14
Tropics 0.14 0.24

In the longer term since 1995, Globally and in NH land temps are well below the average anomalies, while SH is nearly average, and the Tropics above average (though comprising limited surface area).

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  It is striking to now see NH and Global land temps dropping rapidly.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

Ocean Air Temps Drop in August

Presently sea surface temperatures (SST) are the best available indicator of heat content gained or lost from earth’s climate system.  Enthalpy is the thermodynamic term for total heat content in a system, and humidity differences in air parcels affect enthalpy.  Measuring water temperature directly avoids distorted impressions from air measurements.  In addition, ocean covers 71% of the planet surface and thus dominates surface temperature estimates.  Eventually we will likely have reliable means of recording water temperatures at depth.

Recently, Dr. Ole Humlum reported from his research that air temperatures lag 2-3 months behind changes in SST.  He also observed that changes in CO2 atmospheric concentrations lag behind SST by 11-12 months.  This latter point is addressed in a previous post Who to Blame for Rising CO2?

The August update to HadSST3 will appear later this month, but in the meantime we can look at lower troposphere temperatures (TLT) from UAHv6 which are already posted for August. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above.

The UAH dataset includes temperature results for air above the oceans, and thus should be most comparable to the SSTs. There is the additional feature that ocean air temps avoid Urban Heat Islands (UHI).  The graph below shows monthly anomalies for ocean temps since January 2015.

UAH Oceans 201808

Open image in new tab to enlarge.

Remarkably, the anomalies over the entire ocean dropped to the same value, 0.12C (Tropics are 0.13C).  In previous months both the Tropics and SH rose, while NH rose very slightly, resulting in a small increase in the Global average temp of air over oceans. Now that warming is gone in NH and Globally.

Taking a longer view, we can look at the record since 1995, that year being an ENSO neutral year and thus a reasonable starting point for considering the past two decades.  On that basis we can see the plateau in ocean temps is persisting. Since last October all oceans have cooled, with offsetting bumps up and down.

UAHv6 TLT 
Monthly Ocean
Anomalies
Average Since 1995 Ocean 8/2018
Global 0.13 0.12
NH 0.16 0.12
SH 0.11 0.12
Tropics 0.12 0.13

As of August 2018, Global ocean air temps as well as SH and Tropics are matching the average since 1995.  NH is now cooler than the average.  Globally,  2018 is the coolest August since 2013. NH, SH and the Tropics are the coolest August since 2014.

The details of UAH ocean temps are provided below.  The monthly data make for a noisy picture, but seasonal fluxes between January and July are important.

The greater volatility of the Tropics is evident, leading the oceans through three major El Nino events during this period.  Note also the flat period between 7/1999 and 7/2009.  The 2010 El Nino was erased by La Nina in 2011 and 2012.  Then the record shows a fairly steady rise peaking in 2016, with strong support from warmer NH anomalies, before returning to the 22-year average.

Summary

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  They started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.