Solar Cycles Chaotic

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A recent study published at Science Daily The sun’s clock by Helmholtz-Zentrum Dresden-Rossendor Excerpts in italics with my bolds

Not only the 11-year cycle, but also all other periodic solar activity fluctuations can be clocked by planetary attractive forces. With new model calculations, they are proposing a comprehensive explanation of known sun cycles for the first time. They also reveal the longest fluctuations in activity over thousands of years as a chaotic process.

Not only the very concise 11-year cycle, but also all other periodic solar activity fluctuations can be clocked by planetary attractive forces. This is the conclusion drawn by Dr. Frank Stefani and his colleagues from the Institute of Fluid Dynamics at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and from the Institute of Continuous Media Mechanics in Perm, Russia. With new model calculations, they are proposing a comprehensive explanation of all important known sun cycles for the first time. They also reveal the longest fluctuations in activity over thousands of years as a chaotic process. Despite the planetary timing of short and medium cycles, long-term forecasts of solar activity thus become impossible, as the researchers in the scientific journal Solar Physics assert.

Solar physicists around the world have long been searching for satisfactory explanations for the sun’s many cyclical, overlapping activity fluctuations. In addition to the most famous, approximately 11-year “Schwabe cycle,” the sun also exhibits longer fluctuations, ranging from hundreds to thousands of years. It follows, for example, the “Gleissberg cycle” (about 85 years), the “Suess-de Vries cycle” (about 200 years) and the quasi-cycle of “Bond events” (about 1500 years), each named after their discoverers. It is undisputed that the solar magnetic field controls these activity fluctuations.

Explanations and models in expert circles partly diverge widely as to why the magnetic field changes at all. Is the sun controlled externally or does the reason for the many cycles lie in special peculiarities of the solar dynamo itself? HZDR researcher Frank Stefani and his colleagues have been searching for answers for years — mainly to the very controversial question as to whether the planets play a role in solar activity.

Rosette-shaped movement of the sun can produce a 193-year cycle

The researchers have most recently taken a closer look at the sun’s orbital movement. The sun does not remain fixed at the center of the solar system: It performs a kind of dance in the common gravitational field with the massive planets Jupiter and Saturn — at a rate of 19.86 years. We know from the Earth that spinning around in its orbit triggers small motions in the Earth’s liquid core. Something similar also occurs within the sun, but this has so far been neglected with regard to its magnetic field.

The researchers came up with the idea that part of the sun’s angular orbital momentum could be transferred to its rotation and thus affect the internal dynamo process that produces the solar magnetic field. Such coupling would be sufficient to change the extremely sensitive magnetic storage capacity of the tachocline, a transition region between different types of energy transport in the sun’s interior. “The coiled magnetic fields could then more easily snap to the sun’s surface,” says Stefani.

The researchers integrated one such rhythmic perturbation of the tachocline into their previous model calculations of a typical solar dynamo, and they were thus able to reproduce several cyclical phenomena that were known from observations. What was most remarkable was that, in addition to the 11.07-year Schwabe cycle they had already modeled in previous work, the strength of the magnetic field now also changed at a rate of 193 years — this could be the sun’s Suess-de Vries cycle, which from observations has been reported to be 180 to 230 years. Mathematically, the 193 years arise as what is known as a beat period between the 19.86-year cycle and the twofold Schwabe cycle, also called the Hale cycle. The Suess-de Vries cycle would thus be the result of a combination of two external “clocks”: the planets’ tidal forces and the sun’s own movement in the solar system’s gravitational field.

Planets as a metronome

For the 11.07-year cycle, Stefani and his researchers had previously found strong statistical evidence that it must follow an external clock. They linked this “clock” to the tidal forces of the planets Venus, Earth and Jupiter. Their effect is greatest when the planets are aligned: a constellation that occurs every 11.07 years. As for the 193-year cycle, a sensitive physical effect was also decisive here in order to trigger a sufficient effect of the weak tidal forces of the planets on the solar dynamo.

After initial skepticism toward the planetary hypothesis, Stefani now assumes that these connections are not coincidental. “If the sun was playing a trick on us here, then it would be with incredible perfection. Or, in fact, we have a first inkling of a complete picture of the short and long solar activity cycles.” In fact, the current results also retroactively reaffirm that the 11-year cycle must be a timed process. Otherwise, the occurrence of a beat period would be mathematically impossible.

Tipping into chaos: 1000-2000-year collapses are not more accurately predictable

In addition to the rather shorter activity cycles, the sun also exhibits long-term trends in the thousand-year range. These are characterized by prolonged drops in activity, known as “minima,” such as the most recent “Maunder Minimum,” which occurred between 1645 and 1715 during the “Little Ice Age.” By statistically analyzing the observed minima, the researchers could show that these are not cyclical processes, but that their occurrence at intervals of approximately one to two thousand years follows a mathematical random process.

solar-cycle-25-nasa-full

To verify this in a model, the researchers expanded their solar dynamo simulations to a longer period of 30,000 years. In fact, in addition to the shorter cycles, there were irregular, sudden drops in magnetic activity every 1000 to 2000 years. “We see in our simulations how a north-south asymmetry forms, which eventually becomes too strong and goes out of sync until everything collapses. The system tips into chaos and then takes a while to get back into sync again,” says Stefani. But this result also means that very long-term solar activity forecasts — for example, to determine influence on climate developments — are almost impossible.

Background from previous post Climate Chaos

Foucault’s pendulum in the Panthéon, Paris

h/t tom0mason for inspiring this post, including his comment below

The Pendulum is Settled Science

I attended North Phoenix High School (Go Mustangs!) where students took their required physics class from a wild and crazy guy. Decades later alumni who don’t remember his name still reminisce about “the crazy science teacher with the bowling ball.”

To demonstrate the law of conservation of energy, he required each and every student to stand on a ladder in one corner of the classroom. Attached to a hook in the center of the rather high ceiling was a rope with a bowling ball on the other end. The student held the ball to his/her nose and then released it, being careful to hold still afterwards.

The 16 pound ball traveled majestically diagonally across the room and equally impressively returned along the same path. The proof of concept was established when the ball stopped before hitting your nose (though not by much).  In those days we learned to trust science and didn’t need to go out marching to signal some abstract virtue.

The equations for pendulums are centuries old and can predict the position of the ball at any point in time based on the mass of the object, length of the rope and starting position.

Pictured above is the currently operating Foucault pendulum that exactly follows these equations. While it had long been known that the Earth rotates, the introduction of the Foucault pendulum in 1851 was the first simple proof of the rotation in an easy-to-see experiment. Today, Foucault pendulums are popular displays in science museums and universities.

What About the Double Pendulum?

Trajectories of a double pendulum

Just today a comment by tom0mason at 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 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

Long exposure of double pendulum exhibiting chaotic motion (tracked with an LED)

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.

And What about the Climate?

This is a simple example of chaotic motion and its unpredictability. How predictable is our climate with so many variables and feedbacks, some known some unknown? Consider that this planet’s weather/climate system is chaotic in nature with many thousands (millions?) of loosely coupled variables and dependencies, and many of these variables have very complex feedback features within them.

Hurricane Gladys, photographed from orbit by Apollo 7 in 1968 (Photo: NASA)

Summary

To quote the IPCC:

The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions.

A recent National Review article draws the implications:
The range of predicted future warming is enormous — apocalyptism is unwarranted.

But as the IPCC emphasizes, the range for future projections remains enormous. The central question is “climate sensitivity” — the amount of warming that accompanies a doubling of carbon dioxide in the atmosphere. As of its Fifth Assessment Report in 2013, the IPCC could estimate only that this sensitivity is somewhere between 1.5 and 4.5°C. Nor is science narrowing that range. The 2013 assessment actually widened it on the low end, from a 2.0–4.5°C range in the prior assessment. And remember, for any specific level of warming, forecasts vary widely on the subsequent environmental and economic implications.

For now, though, navigating the climate debate will require translating the phrase “climate denier” to mean “anyone unsympathetic to the most aggressive activists’ claims.” This apparently includes anyone who acknowledges meaningful uncertainty in climate models, adopts a less-than-catastrophic outlook about the consequences of future warming, or opposes any facet of the activist policy agenda. The activists will be identifiable as the small group continuing to shout “Denier!” The “deniers” will be identifiable as everyone else.

Update May 2

Esteemed climate scientist Richard Lindzen ends a very fine recent presentation (here) with this description of the climate system:

I haven’t spent much time on the details of the science, but there is one thing that should spark skepticism in any intelligent reader. The system we are looking at consists in two turbulent fluids interacting with each other. They are on a rotating planet that is differentially heated by the sun. A vital constituent of the atmospheric component is water in the liquid, solid and vapor phases, and the changes in phase have vast energetic ramifications. The energy budget of this system involves the absorption and reemission of about 200 watts per square meter. Doubling CO2 involves a 2% perturbation to this budget. So do minor changes in clouds and other features, and such changes are common. In this complex multifactor system, what is the likelihood of the climate (which, itself, consists in many variables and not just globally averaged temperature anomaly) is controlled by this 2% perturbation in a single variable? Believing this is pretty close to believing in magic. Instead, you are told that it is believing in ‘science.’ Such a claim should be a tip-off that something is amiss. After all, science is a mode of inquiry rather than a belief structure.

Flow Diagram for Climate Modeling, Showing Feedback Loops

May 2021 Slight Warming of Land and 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.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling has set in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated after all regions headed down, now reversing slightly.

UAH has updated their tlt (temperatures in lower troposphere) dataset for May.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years.

Note:  UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021.  In the charts below, the trends and fluctuations remain the same but the anomaly values change with the baseline reference shift.

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?

HadSST3 belatedly reported March along with the April updates, so hopefully May will appear later in June.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for May. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the new and current dataset.

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 202105

Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. End of 2020 November and December ocean temps plummeted in NH and the Tropics. In January SH dropped sharply, pulling the Global anomaly down despite an upward bump in NH.  A further drop in March brought new lows for this period.  April stayed cool, and now in May SH and the Tropics warmed to converge on the same anomaly as NH, ~0.07  All regions are showing temps comparable to to 2015 prior to the 2016 El Nino event.

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 sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for May is below.

UAH Land 202105

Here we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a 2020 spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months.  In December all of that was wiped out. Then January showed a sharp drop in SH, but a rise in NH more than offset, pulling the Global anomaly upward. Then in February to April NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  In May all regions warmed pulling up the Global anomaly from its lowest value since 2015. All regions are roughly comparable to early 2015, prior to the 2016 El Nino.

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202105

The chart shows monthly anomalies starting 01/1995 to present.  The average anomaly is 0.04, since this period is the same as the new baseline, lacking only the first 4 years.  1995 was chosen as an ENSO neutral year.  The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20, with temps now returning again to the mean.

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, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  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.

April Oceans Temper Cold 2021 Start


The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source, the latest version being HadSST3.  More on what distinguishes HadSST3 from other SST products at the end.

The Current Context

The year end report below showed 2020 rapidly cooling in all regions.  The anomalies have continued to drop sharply and are now well below the mean since 1995.  This Global Cooling was also evident in the UAH Land and Ocean air temperatures ( See March 2021 Ocean Chill Deepens) 

The chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through April 2021. After three straight Spring 2020 months of cooling led by the tropics and SH, NH spiked in the summer, along with smaller bumps elsewhere.  Then temps everywhere dropped the last six months, hitting bottom in February 2021.  All regions were well below the Global Mean since 2015, matching the cold of 2018, and lower than January 2015. Now the spring is bringing more temperate, still cold ocean SSTs.

Hadsst4 202104

 

A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  

Note that higher temps in 2015 and 2016 were first of all due to a sharp rise in Tropical SST, beginning in March 2015, peaking in January 2016, and steadily declining back below its beginning level. Secondly, the Northern Hemisphere added three bumps on the shoulders of Tropical warming, with peaks in August of each year.  A fourth NH bump was lower and peaked in September 2018.  As noted above, a fifth peak in August 2019 and a sixth August 2020 exceeded the four previous upward bumps in NH.

In 2019 all regions had been converging to reach nearly the same value in April.  Then  NH rose exceptionally by almost 0.5C over the four summer months, in August 2019 exceeding previous summer peaks in NH since 2015.  In the 4 succeeding months, that warm NH pulse reversed sharply. Then again NH temps warmed to a 2020 summer peak, matching 2019.  This has now been reversed with all regions pulling the Global anomaly downward sharply, tempered by slight warming in March and April

And as before, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.  The major difference between now and 2015-2016 is the absence of Tropical warming driving the SSTs, along with SH anomalies reaching nearly the lowest in this period. Presently both SH and the Tropics are quite cool, with NH coming off its summer peak.  Note the tropical temps descending into La Nina levels.  At this point, the 2016 El Nino and its NH after effects have dissipated completely.

A longer view of SSTs

The graph below  is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.

Hadsst1995to 042021

1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino.  The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99.  For the next 2 years, the Tropics stayed down, and the world’s oceans held steady around 0.2C above 1961 to 1990 average.

Then comes a steady rise over two years to a lesser peak Jan. 2003, but again uniformly pulling all oceans up around 0.4C.  Something changes at this point, with more hemispheric divergence than before. Over the 4 years until Jan 2007, the Tropics go through ups and downs, NH a series of ups and SH mostly downs.  As a result the Global average fluctuates around that same 0.4C, which also turns out to be the average for the entire record since 1995.

2007 stands out with a sharp drop in temperatures so that Jan.08 matches the low in Jan. ’99, but starting from a lower high. The oceans all decline as well, until temps build peaking in 2010.

Now again a different pattern appears.  The Tropics cool sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peak came in 2019, only this time the Tropics and SH are offsetting rather adding to the warming. Since 2014 SH has played a moderating role, offsetting the NH warming pulses. Now September 2020 is dropping off last summer’s unusually high NH SSTs. (Note: these are high anomalies on top of the highest absolute temps in the NH.)

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.

AMO Aug and Dec 2021
The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

AMO decade 042021

 

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The black line shows that 2020 began slightly warm, then set records for 3 months. then dropped below 2016 and 2017, peaked in August and is now below 2016. Now in 2021, AMO is tracking the coldest years.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies may rise slightly in coming months, but once again, ENSO which has weakened will probably determine the outcome.

Footnote: Why Rely on HadSST3

HadSST3 is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST3 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

Adios, Global Warming

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The post below updates the UAH record of air temperatures over land and ocean.  But as an overview consider how recent rapid cooling has now completely overcome the warming from the last 3 El Ninos (1998, 2010 and 2016).  The UAH record shows that the effects of the last one are now gone as of April 2021. (UAH baseline is now 1991-2020).

UAH Global 1995to202104 w co2 overlayFor reference I added an overlay of CO2 annual concentrations as measured at Moana Loa.  While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~55 ppm, a 15% increase.

Furthermore, going back to previous warmings prior to the satellite record shows that the entire rise of 0.8C since 1947 is due to oceanic, not human activity.

 

gmt-warming-events

The animation is an update of a previous analysis from Dr. Murry Salby.  These graphs use Hadcrut4 and include the 2016 El Nino warming event.  The exhibit shows since 1947 GMT warmed by 0.8 C, from 13.9 to 14.7, as estimated by Hadcrut4.  This resulted from three natural warming events involving ocean cycles. The most recent rise 2013-16 lifted temperatures by 0.2C.  Previously the 1997-98 El Nino produced a plateau increase of 0.4C.  Before that, a rise from 1977-81 added 0.2C to start the warming since 1947.

Importantly, the theory of human-caused global warming asserts that increasing CO2 in the atmosphere changes the baseline and causes systemic warming in our climate.  On the contrary, all of the warming since 1947 was episodic, coming from three brief events associated with oceanic cycles. 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

April Update Ocean and Land Air Temps Continue Down

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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.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with chilly temperatures setting in all regions.  Last month it was the ocean cooling off dramatically.

UAH has updated their tlt (temperatures in lower troposphere) dataset for April.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years. Unusually, last month showed air over land remained cool, while oceans dropped down further.

Note:  UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021.  In the charts below, the trends and fluctuations remain the same but the anomaly values change with the baseline reference shift.

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.  Thus the cooling oceans now portend cooling land air temperatures to follow.  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?

After a technical enhancement to HadSST3 delayed updates Spring 2020, May resumed a pattern of HadSST updates toward the following month end.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for April.  The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the new and current dataset.

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 202104Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. End of 2020 November and December ocean temps plummeted in NH and the Tropics. In January SH dropped sharply, pulling the Global anomaly down despite an upward bump in NH. An additional drop in March has SH matching the coldest in this period. March drops in the Tropics and NH make those regions at their coldest since 01/2015.  In April despite an uptick in NH, the Global anomaly dropped further.

 

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 sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for April is below.

UAH Land 202104

Here we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a 2020 spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months.  In December all of that was wiped out. Then January showed a sharp drop in SH, but a rise in NH more than offset, pulling the Global anomaly upward.  In February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  March continued to show all regions roughly comparable to early 2015, prior to the 2016 El Nino.  Then in April NH land dropped sharply along with the Tropics, bringing Global Land anomaly down by nearly 0.2C.  With NH having most of the land mass, it’s possible the additional Polar Vortex events drove air temps downward last month.

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202104

The chart shows monthly anomalies starting 01/1995 to present.  The average anomaly is 0.04, since this period is the same as the new baseline, lacking only the first 4 years.  1995 was chosen as an ENSO neutral year.  The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20, with temps now returning again to the mean.

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, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  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.

Two Views of Oceans SST End of April 2021

My preferred SST dataset has been HadSST3, for reasons noted at the end.  However, no new data has been provided for either February or March, so I have been looking at alternatives.  This post will feature ERSST5, with some comparisons with HadSST4 which has now been updated through March 2021.   First the usual contextual introduction.

Overview

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

The Current Context

The various ERSST sources and history are described at the home page NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5.  A major distinction is the practice of interpolation, which involves infilling 2° by 2° grid cells missing sufficient observations in a month.  The values are anomalies from average anomalies for the period 1971 to 2000.  HadSST3 reports only on 5° by 5° grid cells observed in a month, and compares to a baseline 1961 to 1990. HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperature than shown in v.3.  The effect is that v4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v3. Clive Best has a fuller analysis comparing HadSST3 and HadSST4 in this post HadSST4 and knock on effects.

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through March 2021. Though the anomaly values are higher than those reported in HadSST3, the patterns of sst changes remain the same. After three straight Spring 2020 months of cooling led by the tropics and SH, NH spiked in the summer, along with smaller bumps elsewhere.  Now temps everywhere are dropping the last six months, with all regions well below the Global Mean since 2015, matching the cold of 2018, and lower than January 2015. A small upward bump in March still leaves all regions the same as March 2015.

Hadsst4 202103

 

A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  In 2019 all regions had been converging to reach nearly the same value in April.

Then  NH rose exceptionally by almost 0.5C over the four summer months, in August 2019 exceeding previous summer peaks in NH since 2015.  In the 4 succeeding months, that warm NH pulse reversed sharply. Then again NH temps warmed to a 2020 summer peak, matching 2019.  This has now been reversed with all regions pulling the Global anomaly downward sharply.

Note that higher temps in 2015 and 2016 were first of all due to a sharp rise in Tropical SST, beginning in March 2015, peaking in January 2016, and steadily declining back below its beginning level. Secondly, the Northern Hemisphere added three bumps on the shoulders of Tropical warming, with peaks in August of each year.  A fourth NH bump was lower and peaked in September 2018.  As noted above, a fifth peak in August 2019 and a sixth August 2020 exceeded the four previous upward bumps in NH.

And as before, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.  The major difference between now and 2015-2016 is the absence of Tropical warming driving the SSTs, along with SH anomalies reaching nearly the lowest in this period. Presently both SH and the Tropics are quite cool, with NH coming off its summer peak.  Note the tropical temps descending into La Nina levels.  At this point, the 2016 El Nino and its NH after effects have dissipated completely.

ERSST202103rev

 

ERSST5 reports only Global SSTs, unlike HadSST4 which also shows results for NH, SH and the Tropics (latitudes 20N to 20S).  The graph shows in green ERSST5 anomalies are much more volatile with both higher and lower extremes, compared to the blue HadSST4.  NH is added since it appears to vary similarly to ERSST, with the notable contradiction in 2016.  Also, the 2019 peak is much higher than 2015-16 in ERSST, whereas HadSST Global shows them comparable.  Both datasets show SSTs dropping sharply since summer 2020, and now below the mean anomaly for the period (only ERSST mean is shown).

A longer view of SSTs

The graph below  is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.

ERSST95to2103rev

 

In the longer record the 1998 El Nino stands as one bookend and 2019 as the other.  Note that HadSST Global warming events appear more as extended periods of slightly higher anomalies, while ERSST events appear as sharp peaks and valleys.  Note also that present Global SSTs are matching the mean since 1995.

Hadsst4 1995to 202103

1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino.  The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99.  For the next 2 years, the Tropics stayed down, and the world’s oceans held steady around 0.2C above 1961 to 1990 average.

Then comes a steady rise over two years to a lesser peak Jan. 2003, but again uniformly pulling all oceans up around 0.4C.  Something changes at this point, with more hemispheric divergence than before. Over the 4 years until Jan 2007, the Tropics go through ups and downs, NH a series of ups and SH mostly downs.  As a result the Global average fluctuates around that same 0.4C, which also turns out to be the average for the entire record since 1995.

2007 stands out with a sharp drop in temperatures so that Jan.08 matches the low in Jan. ’99, but starting from a lower high. The oceans all decline as well, until temps build peaking in 2010.

Now again a different pattern appears.  The Tropics cool sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peak came in 2019, only this time the Tropics and SH are offsetting rather adding to the warming. Since 2014 SH has played a moderating role, offsetting the NH warming pulses. Now September 2020 is dropping off last summer’s unusually high NH SSTs. (Note: these are high anomalies on top of the highest absolute temps in the NH.)

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.
The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

AMO decade 032021

 

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The black line shows that 2020 began slightly warm, then set records for 3 months. then dropped below 2016 and 2017, peaked in August and is now below 2016. Note this year is starting out among the coolest analog years.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies may rise slightly in coming months, but once again, ENSO which has weakened will probably determine the outcome.

Footnote: Why Rely on HadSST3

HadSST3 is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST3 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

Oceans SST Update April 2021

My preferred SST dataset is HadSST3, for reasons noted at the end.  However, no new data has been provided for either February or March, so I have been looking at alternatives.  HadSST4 shows February, but nothing since.  So this post will feature ERSST5, with some comparisons with HadSST3 and notes on the differences.  First the usual contextual introduction.

Overview

The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:

  • The ocean covers 71% of the globe and drives average temperatures;
  • SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
  • A major El Nino was the dominant climate feature in recent years.

The Current Context

The various ERSST sources and history are described at the home page NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5.  A major distinction is the practice of interpolation, which involves infilling 2° by 2° grid cells missing sufficient observations in a month.  The values are anomalies from average anomalies for the period 1971 to 2000.  HadSST3 reports only on 5° by 5° grid cells observed in a month, and compares to a baseline 1961 to 1990. 

ERSST202103

ERSST5 reports only Global SSTs, unlike HadSST3 which also shows results for NH, SH and the Tropics (latitudes 20N to 20S).  The graph shows in green ERSST5 anomalies are much more volatile with both higher and lower extremes, compared to the blue HadSST3.  NH is added since it appears to vary similarly to ERSST, with the notable contradiction in 2016.  Also, the 2019 peak is much higher than 2015-16 in ERSST, whereas HADSST Global shows them comparable.  Both datasets show SSTs dropping sharply since summer 2020, and now below the mean anomaly for the period (only ERSST mean is shown).

The chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through January 2021. After three straight Spring 2020 months of cooling led by the tropics and SH, NH spiked in the summer, along with smaller bumps elsewhere.  Now temps everywhere are dropping the last six months, with all regions well below the Global Mean since 2015, matching the cold of 2018, and lower than January 2015. 

A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  In 2019 all regions had been converging to reach nearly the same value in April.

Then  NH rose exceptionally by almost 0.5C over the four summer months, in August 2019 exceeding previous summer peaks in NH since 2015.  In the 4 succeeding months, that warm NH pulse reversed sharply. Then again NH temps warmed to a 2020 summer peak, matching 2019.  This has now been reversed with all regions pulling the Global anomaly downward sharply.

Note that higher temps in 2015 and 2016 were first of all due to a sharp rise in Tropical SST, beginning in March 2015, peaking in January 2016, and steadily declining back below its beginning level. Secondly, the Northern Hemisphere added three bumps on the shoulders of Tropical warming, with peaks in August of each year.  A fourth NH bump was lower and peaked in September 2018.  As noted above, a fifth peak in August 2019 and a sixth August 2020 exceeded the four previous upward bumps in NH.

And as before, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.  The major difference between now and 2015-2016 is the absence of Tropical warming driving the SSTs, along with SH anomalies reaching nearly the lowest in this period. Presently both SH and the Tropics are quite cool, with NH coming off its summer peak.  Note the tropical temps descending into La Nina levels.  At this point, the 2016 El Nino and its NH after effects have dissipated completely.

A longer view of SSTs

The graph below  is noisy, but the density is needed to see the seasonal patterns in the oceanic fluctuations.  Previous posts focused on the rise and fall of the last El Nino starting in 2015.  This post adds a longer view, encompassing the significant 1998 El Nino and since.  The color schemes are retained for Global, Tropics, NH and SH anomalies.  Despite the longer time frame, I have kept the monthly data (rather than yearly averages) because of interesting shifts between January and July.

ERSST95to0321

In the longer record the 1998 El Nino stands as one bookend and 2019 as the other.  Note that HadSST Global warming events appear more as extended periods of slightly higher anomalies, while ERSST events appear as sharp peaks and valleys.  Note also that present Global SSTs are matching the mean since 1995.

To enlarge image, single-click or open in new tab.

1995 is a reasonable (ENSO neutral) starting point prior to the first El Nino.  The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99.  For the next 2 years, the Tropics stayed down, and the world’s oceans held steady around 0.2C above 1961 to 1990 average.

Then comes a steady rise over two years to a lesser peak Jan. 2003, but again uniformly pulling all oceans up around 0.4C.  Something changes at this point, with more hemispheric divergence than before. Over the 4 years until Jan 2007, the Tropics go through ups and downs, NH a series of ups and SH mostly downs.  As a result the Global average fluctuates around that same 0.4C, which also turns out to be the average for the entire record since 1995.

2007 stands out with a sharp drop in temperatures so that Jan.08 matches the low in Jan. ’99, but starting from a lower high. The oceans all decline as well, until temps build peaking in 2010.

Now again a different pattern appears.  The Tropics cool sharply to Jan 11, then rise steadily for 4 years to Jan 15, at which point the most recent major El Nino takes off.  But this time in contrast to ’97-’99, the Northern Hemisphere produces peaks every summer pulling up the Global average.  In fact, these NH peaks appear every July starting in 2003, growing stronger to produce 3 massive highs in 2014, 15 and 16.  NH July 2017 was only slightly lower, and a fifth NH peak still lower in Sept. 2018.

The highest summer NH peak came in 2019, only this time the Tropics and SH are offsetting rather adding to the warming. Since 2014 SH has played a moderating role, offsetting the NH warming pulses. Now September 2020 is dropping off last summer’s unusually high NH SSTs. (Note: these are high anomalies on top of the highest absolute temps in the NH.)

What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH.  The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before.  After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.
The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

AMO decade 022021

 

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The black line shows that 2020 began slightly warm, then set records for 3 months. then dropped below 2016 and 2017, peaked in August and is now below 2016. This year is starting out matching cooler analog years.

Summary

The oceans are driving the warming this century.  SSTs took a step up with the 1998 El Nino and have stayed there with help from the North Atlantic, and more recently the Pacific northern “Blob.”  The ocean surfaces are releasing a lot of energy, warming the air, but eventually will have a cooling effect.  The decline after 1937 was rapid by comparison, so one wonders: How long can the oceans keep this up? If the pattern of recent years continues, NH SST anomalies may rise slightly in coming months, but once again, ENSO which has weakened will probably determine the outcome.

Footnote: Why Rely on HadSST3

HadSST3 is distinguished from other SST products because HadCRU (Hadley Climatic Research Unit) does not engage in SST interpolation, i.e. infilling estimated anomalies into grid cells lacking sufficient sampling in a given month. From reading the documentation and from queries to Met Office, this is their procedure.

HadSST3 imports data from gridcells containing ocean, excluding land cells. From past records, they have calculated daily and monthly average readings for each grid cell for the period 1961 to 1990. Those temperatures form the baseline from which anomalies are calculated.

In a given month, each gridcell with sufficient sampling is averaged for the month and then the baseline value for that cell and that month is subtracted, resulting in the monthly anomaly for that cell. All cells with monthly anomalies are averaged to produce global, hemispheric and tropical anomalies for the month, based on the cells in those locations. For example, Tropics averages include ocean grid cells lying between latitudes 20N and 20S.

Gridcells lacking sufficient sampling that month are left out of the averaging, and the uncertainty from such missing data is estimated. IMO that is more reasonable than inventing data to infill. And it seems that the Global Drifter Array displayed in the top image is providing more uniform coverage of the oceans than in the past.

uss-pearl-harbor-deploys-global-drifter-buoys-in-pacific-ocean

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

Worst Threat: Greenhouse Gas or Quiet Sun?

Elite Consensus Opinion

Minority Contrary Opinion

Expect 1+C Warmer from now to 2050 Expect 1C Colder from now to 2050
Mitigate Warming by Stopping Fossil Fuels Adapt to Cooling from Quiet Sun
Goal is Net Zero CO2 Emissions by 2050 Goal Robust Energy supply and Infrastructure Now

At the American Thinker, Anony mee writes The Coming Modern Grand Solar Minimum.  Excerpts in italics with my bolds.

solar_cycle_25_nasa_full

I wrote last week about the coming Grand Solar Minimum, something that will have much more impact on the environment than anything we puny humans can do. It generated a lot of interest from all sides, so it’s time to delve deeper into what we can expect.

Starting with the hype: During the last grand solar minimum (GSM), the Maunder Minimum of 1645 to 1715, glaciers advanced, rivers froze, sea ice expanded — in short, the Little Ice Age. Is another one is almost upon us?

Probably not. Maunder occurred at the tail end of a bi-millennial cycle. These cycles range between 2,000 and 2,600 years in length and see the Earth first warm, then cool. Gradual cooling had been going on for hundreds of years. Maunder just capped it off. Today we are a few hundred years into the warming phase of the subsequent bi-millennial cycle. Different starting conditions yield different paths.

The progressives say that we’re so deep into anthropogenically accelerated climate change (AACC) that there’s almost no time left to turn things around. If we don’t act now, it will be too late.

Nope, sorry squad members. What we can predict, instead, is an overall temperature reduction of 1 degree Centigrade by the end of the GSM. Afterward, natural warming at the rate of around 0.5 C. every hundred years will continue for the next 600 years or so.

That gives us a good 35 to 50 years to hone the science and come up with the best ways to mitigate the impact of unstoppable global warming on humankind; until, that is, it naturally reverses. See suggestions below for better uses of funding currently earmarked to address the “climate crisis.”

Reasonably speaking: We’ve been warming, so the cooling of the GSM will just even us out for a while. Therefore, nothing to worry about, right?

Well, not quite. There are a few worries. Plants grow in response to warmth, moisture, nutrients, and most importantly sunlight. Even if the temperature does not plunge to glacial depths, some cooling will take place and clouds are expected to grow denser and cover much of the earth’s surface as this GSM bottoms out. If normally-correlating volcanism takes place, the additional material in the atmosphere will further darken the globe and provide even more opportunity for condensation and cloud formation.

Last year, Dr. Valentina Zharkova wrote “This global cooling during the upcoming grand solar minimum…would require inter-government efforts to tackle problems with heat and food supplies for the whole population of the Earth” (not to mention their livestock).

The pessimists ask, what else can go wrong? Well, cooling will increase the demand for heat, darker days will increase the demand for light, and unfavorable outside conditions will increase the demand for power for enclosed food production. With more power needed, the amount we currently rely on from solar installations will decrease as cloud cover limits their efficacy.

A decrease in solar ultraviolet radiation can be expected to slow the formation of ozone in the atmosphere, a lack of which tends to destabilize the jet stream, causing wilder weather. Wind generators turn off when the wind is excessively strong. As we now know, they are not immune from freezing in place. In the face of a greater demand for power, we will generate less.

Even worse is this: Historically, GSMs have been associated with extreme weather events. Floods, droughts, heavy snowfall, late springs, and early autumns have all resulted in famine. Famine during GSMs has led to starvation and societal upheaval. No one wants the former, and I think we’ve seen enough of the latter this past year or so to do for our lifetimes.

We’re about 16 months into this GSM, with 32 more years to go. Already 2019 and 2020 saw record low numbers of sunspots. We’ve had lower than expected crop harvests due to unseasonable rains both years. The April 2021 USDA World Agricultural Product report has articles detailing Taiwan’s expected 20% decrease in rice production this year over last, Cuba’s rice production 15% below its five-year average, Argentina’s corn, Australia’s cotton, Malaysia’s palm oil — all down, all due primarily to the weather. There are some expected bumper crops, all based on expanded acreage.

We’ve got seven years until we hit the trough. There’s no time to lose. Fortunately, We the People are amazing. We’re strong, courageous, resilient, smart, well-educated, and clever. We are capable of coming together for a common cause and working well together regardless of politics and other differences. We must pull together to make sure we all survive the coming tumult. Here’s what we do.

On the federal level, take the brakes off energy production. No more talk of closing power plants, especially coal-fired ones, or of removing hydroelectric dams. Reinstate the Keystone XL pipeline; we’re going to need that fuel available to us when the predictable contraction of the global fuel market occurs. Extend the tax credits for those who install solar power. Production may not be optimal during the GSM, but as much as can occur will take a load off commercial energy.

At the United Nations, Ambassador Thomas-Greenfield should prioritize preparations for the coming dark, cold years. It is in the world’s best interest that all nations cease aggressions, even if just for a decade or so, so that we all may turn our resources to securing the lives of our peoples.

The USDA should not just take the brakes off agricultural production; it should encourage all producers to ramp it up. We need to have enough on hand to address the expected shortfall between production and requirement for at least five years. All loans to all farmers should be forgiven if they will agree to get on board with maximizing production. Garden seed producers, along with all other producers and processors, should be given significant tax credits for ramping up their production too.

Commerce should support vastly expanded food processing for long-term storage. Congress should fund the acquisition and storage of surplus staples and other food commodities so that sufficient amounts are on hand to keep our markets, feeding programs, and food banks operating when crop after crop begins to fail. Stockpiling for our future should take precedence over exports.

The NSC should demand a reconstitution of our strategic grain reserve, and that we prepare not just for ourselves, but to be able to share with needy neighbors and allies to keep America secure.

State, local, and tribal governments should clear away barriers to gardening and small animal production, including not limiting water catchment for gardening. Everything folks can do for themselves will take pressure off public services and limited markets. Local Emergency Services operations should also look at acquiring stocks of staples to help support their residents, as was done in many places last year.

Individuals, as well as schools and other institutions, should begin to garden, even if it’s just pots in a window. It’s a skill that takes time to learn and practice. Everyone should begin to preserve food for the hard times coming – freezing, canning, drying, smoking, pickling. As much as we can do for ourselves, we won’t be looking for someone else to have done for us.

This is really most important. We need to act now while food production is still relatively normal. Later on, if there’s nothing to buy, it won’t matter how much money we have on hand, as individuals or as a nation.

228683_5_

Valentina Zharkova presents her analysis and findings in paper Modern Grand Solar Minimum will lead to terrestrial cooling.  Excerpts in italics with my bolds.

In this editorial I will demonstrate with newly discovered solar activity proxy-magnetic field that the Sun has entered into the modern Grand Solar Minimum (2020–2053) that will lead to a significant reduction of solar magnetic field and activity like during Maunder minimum leading to noticeable reduction of terrestrial temperature.

ktmp_a_1796243_f0001_oc

Figure 3 presents the summary curve calculated with the derived mathematical formulae forwards for 1200 years and backwards 800 years. This curve reveals appearance of Grand Solar Cycles of 350–400 years caused by the interference of two magnetic waves. These grand cycles are separated by the grand solar minima, or the periods of very low solar activity.

Currently, the Sun has completed solar cycle 24 – the weakest cycle of the past 100+ years – and in 2020, has started cycle 25. During the periods of low solar activity, such as the modern grand solar minimum, the Sun will often be devoid of sunspots. This is what is observed now at the start of this minimum, because in 2020 the Sun has seen, in total, 115 spotless days (or 78%), meaning 2020 is on track to surpass the space-age record of 281 spotless days (or 77%) observed in 2019. However, the cycle 25 start is still slow in firing active regions and flares, so with every extra day/week/month that passes, the null in solar activity is extended marking a start of grand solar minimum.

Similarly to the Maunder Minimum … the reduction of solar magnetic field will cause a decrease of solar irradiance by about 0.22% for a duration of three solar cycles (25-27).” Zharkova determines that this drop in TSI (in conjunction with the “often overlooked” role solar background magnetic field plays, as well as with cloud nucleating cosmic rays) will lead to “a drop of the terrestrial temperature by up to 1.0°C from the current temperature during the next three cycles (25-27) … to only 0.4°C higher than the temperature measured in 1710,” with the largest temperature drops arriving “during the local minima between cycles 25−26 and cycles 26-27.

The reduction of a terrestrial temperature during the next 30 years can have important implications for different parts of the planet on growing vegetation, agriculture, food supplies, and heating needs in both Northern and Southern hemispheres. This global cooling during the upcoming grand solar minimum (2020-2053) can offset for three decades any signs of global warming and would require inter-government efforts to tackle problems with heat and food supplies for the whole population of the Earth.

March 2021 Ocean Chill Deepens

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.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with chilly temperatures setting in all regions.  Last month it was the ocean cooling off dramatically.

UAH has updated their tlt (temperatures in lower troposphere) dataset for March.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years. Unusually, last month showed air over land remained cool, while oceans dropped down further.

Note:  UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021.  In the charts below, the trends and fluctuations remain the same but the anomaly values change with the baseline reference shift.

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.  Thus the cooling oceans now portend cooling land air temperatures to follow.  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?

After a technical enhancement to HadSST3 delayed updates Spring 2020, May resumed a pattern of HadSST updates toward the following month end.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for February. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the new and current dataset.

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 202103

Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. End of 2020 November and December ocean temps plummeted in NH and the Tropics. In January SH dropped sharply, pulling the Global anomaly down despite an upward bump in NH. An additional drop in March has SH matching the coldest in this period. March drops in the Tropics and NH make those regions at their coldest since 01/2015.

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 sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for March is below.

UAH Land 202103Here we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a 2020 spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months.  In December all of that was wiped out. Then January showed a sharp drop in SH, but a rise in NH more than offset, pulling the Global anomaly upward.  In February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  March continued to show all regions roughly comparable to early 2015, prior to the 2016 El Nino.  With NH having most of the land mass, it’s possible the February Polar Vortex event drove air temps downward last month.

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202103The chart shows monthly anomalies starting 01/1995 to present.  The average anomaly is 0.04, since this period is the same as the new baseline, lacking only the first 4 years.  1995 was chosen as an ENSO neutral year.  The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20, with temps now returning again to the mean.

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, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  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.

Mann vs. Steyn Update: Getting to the Truth

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Thanks to the Manhattan Contrarian for providing a March update on the eight-year long legal action conducted by M. Mann against M. Steyn.  His post is Update On Michael Mann v. Mark Steyn Litigation.  Excerpts in italics with my bolds and images.

Mann’s central allegation in his case against Steyn is that this passage is defamatory because the “hockey stick” graph is not “fraudulent”; and therefore Steyn’s statement that the graph is “fraudulent” is false.

Remarkably, eight and a half years into this case, only now is the truth or falsity of the claim that the “hockey stick” graph is fraudulent being addressed.

The issue was finally raised in a motion for summary judgement filed by Steyn on January 22 — although almost as an aside, in a motion dealing with many other issues; and then the issue was much more squarely addressed in a response by Steyn to a motion for summary judgment by Mann, filed by Steyn on March 3. I have been sent a copy of the March 3 filing, but I have not been able to find a link for it online.

The Steyn motion papers point to three ways in which the Hockey Stick graph is fraudulent.

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  1.  Mann Deleted Data Adverse to the “Hockey Stick” Shape

Of the three, the most compelling is the deletion by Mann of certain adverse data that would have destroyed the neat “hockey stick” shape of the graph. The graph shows a reconstruction of world atmospheric temperatures from about the year 1050 to 2000, where the first 900 years have temperatures flat or slightly declining, followed by a sharp upward move in the last 50 or so years. The 900 year flat period was derived from several collections of data from tree rings, one of which was provided by a Mann colleague named Keith Briffa. However, in the most recent years (post-1960) the Briffa series showed a decline in temperatures — an inconvenient fact that would have greatly undermined the intended visual impact of the graphic. Mann then decided simply to delete the portion of the Briffa data post-1960, while still using the rest. From the Steyn March 3 submission:

The [Hockey Stick graph as published in the IPCC’s Third Assessment Report in 2001, in a portion written by lead author Mann] omitted tree ring proxy data collected by climate scientist Keith Briffa that showed a decline in temperatures after 1960, a message inconsistent with the prized hockey stick shape. . . . The IPCC TAR did not disclose the deletion of this data. . . . As lead author, Mann decided to omit the Briffa data without the input of his other lead authors.. . . Mann’s own collaborators cautioned him against the deletion. IPCC TAR Coordinating Lead Author Chris Folland wrote to Mann that Briffa’s data “contradicts the multiproxy curve and dilutes the message rather significantly.”. . . Briffa himself urged Mann not to succumb to “pressure to present a nice tidy story” by “ignor[ing]” his post-1960 results. . . . Mann agreed with them on the merits but bemoaned the data’s political impact: “[I]f we show Keith’s series . . . skeptics [will] have a field day.” . . . To prevent a “skeptics’ field day,” he chose to delete the data.

One would think that this is about as clear a demonstration of scientific fraud as it is possible to have.

2.  Mann “Cherry-Picked” Data to Show Flat Temperature Trend

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3. Mann Showed One Record Upside Down to Support the Desired Shape

And as indicated, this is just one of three instances of fraud in the Hockey Stick graph that are set forth in detail in Steyn’s March 3 submission. The other two involve: (1) “cherry picking” of data, in the selection of proxy data series to show a flat-to-declining temperature trend from 1050 to 1950, by simply omitting to use any of the many available series that show the existence of a “medieval warm period” warmer than the present, and (2) misinterpreting one series to use the results upside down and then, when the error was pointed out, continuing to use the series in that way because it supported the desired visual presentation.

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The original MBH graph compared to a corrected version
produced by MacIntyre and McKitrick after undoing Mann’s errors.

Anyway, Mann gets to throw at least one more brief into this mix, and then we will await the court’s decision. As clear-cut as this may appear from the excerpt I provided, the court’s decision could well not come out until late in the year. If sumary judgment is denied, there will then be a trial. Another possibility is that the court grants summary judgment to Mann as plaintiff. I find that possibility almost too ridiculous to contemplate, but the fact is that when things get as politicized as the “climate change” thing has become, the human mind loses almost all rational capability.

Background: Rise and Fall of the Modern Warming Spike

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The first graph appeared in the IPCC 1990 First Assessment Report (FAR) credited to H.H.Lamb, first director of CRU-UEA. The second graph was featured in 2001 IPCC Third Assessment Report (TAR) the famous hockey stick credited to M. Mann.

Feb. 2021 Cooling Land, Warming 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.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with all regions heading down.

UAH has updated their tlt (temperatures in lower troposphere) dataset for February.  Previously I have done posts on their reading of ocean air temps as a prelude to updated records from HADSST3. This month also has a separate graph of land air temps because the comparisons and contrasts are interesting as we contemplate possible cooling in coming months and years. Unusually, last month showed air over land chilled (Polar Vortex?) while oceans warmed slightly.

Note:  UAH has shifted their baseline from 1981-2010 to 1991-2020 beginning with January 2021.  In the charts below, the trends and fluctuations remain the same but the anomaly values change with the baseline reference shift.

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?

After a technical enhancement to HadSST3 delayed March and April updates, May resumed a pattern of HadSST updates mid month.  For comparison we can look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for February. The temperature record is derived from microwave sounding units (MSU) on board satellites like the one pictured above. Recently there was a change in UAH processing of satellite drift corrections, including dropping one platform which can no longer be corrected. The graphs below are taken from the new and current dataset.

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.

Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. End of 2020 November and December ocean temps plummeted in NH and the Tropics. In January SH dropped sharply, pulling the Global anomaly down despite an upward bump in NH. Both SH and the Tropics are now as cold as any time in the last five years, and all regions are comparable to to 2015 prior to the 2016 El Nino event. In February the Tropics stayed cold, while both NH and SH rebounded with warming, pulling the Global anomaly up slightly.

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 sample air temps at 2 meters above ground.  UAH gives tlt anomalies for air over land separately from ocean air temps.  The graph updated for February is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a 2020 spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months.  In December all of that was wiped out. Then January showed a sharp drop in SH, but a rise in NH more than offset, pulling the Global anomaly upward. Now in February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  All regions are roughly comparable to early 2015, prior to the 2016 El Nino.  With NH having most of the land mass, it’s possible the February Polar Vortex event drove air temps downward last month.

The Bigger Picture UAH Global Since 1995

The chart shows monthly anomalies starting 01/1995 to present.  The average anomaly is 0.04, since this period is the same as the new baseline, lacking only the first 4 years.  1995 was chosen as an ENSO neutral year.  The graph shows the 1998 El Nino after which the mean resumed, and again after the smaller 2010 event. The 2016 El Nino matched 1998 peak and in addition NH after effects lasted longer, followed by the NH warming 2019-20, with temps now returning again to the mean.

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, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  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.