Climate Science

UAH January 2024: Ocean Warm, Land Cooling

Posted on by Ron Clutz

The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots.  It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition.  Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.  

As an overview consider how recent rapid cooling  completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016).  The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022  At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Now we have an usual El Nino warming spike of uncertain cause, but unrelated to steadily rising CO2.

For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa.  While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions, with some cooling the last two months. 

Update August 3, 2021

Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT

image-8

 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

January 2024 El Nino Spikes Higher While Land Cools 

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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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in.  The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995.  Spring and Summer 2023 saw a series of warmings, continuing into October, but with cooling since. 

UAH has updated their tlt (temperatures in lower troposphere) dataset for January 2024. Posts on their reading of ocean air temps this month preceded updated records from HadSST4.  I last posted on SSTs using HadSST4 Ocean Warming Spike Recedes December 2023.  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.

Sometimes air temps over land diverge from ocean air changes.  November 2023 was notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions.  As a result the Global Ocean and Land anomaly result remained little changed. Now again in January 2024, ocean temps went higher driven by El Nino and NH, while all land regions cooled except for Tropics.

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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4.  For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for January.  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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October.  That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June.  After an upward spike in July, ocean air everywhere cooled in August and also in September.   

After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.7C, with the largest increases in April to July, and continuing through adding to a new high January 2024. NH also spiked upward to a new high, while Global ocean rise was more modest due to slight SH cooling.  

Land Air Temperatures Tracking 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 December is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land.  Land temps are dominated by NH with a 2021 spike in January,  then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere.  After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH. 

Remarkably, in 2023, SH land air anomaly shot up 2.1C, from  -0.6C in January to +1.5 in September, then dropped sharply, now down to 0.6 in January 2024.  NH land temps have also dropped 0.3C down to 1.0C, resulting in Global land temps cooling to 0.9C, matching the peak in Feb. 2016. Land in the Tropics was unchanged in January, down slightly from its October peak.

The Bigger Picture UAH Global Since 1980

The chart shows monthly Global anomalies starting 01/1980 to present.  The average monthly anomaly is -0.05, for this period of more than four decades.  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.   An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022.  March and April brought warmer Global temps, later reversed

With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016.  December and January are down slightly, but where it goes from here, up or down further, remains to be seen.

The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.

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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

Ocean Warming Spike Recedes December 2023

Posted on by Ron Clutz

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;
  • Major El Ninos have been 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. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through December 2023.  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 in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  

Then in 2022, another strong NH summer spike peaked in August, but this time both the Tropic and SH were countervailing, resulting in only slight Global warming, later receding to the mean.   Oct./Nov. temps dropped  in NH and the Tropics took the Global anomaly below the average for this period. After an uptick in December, temps in January 2023 dropped everywhere, strongest in NH, with the Global anomaly further below the mean since 2015.

Then came El Nino as shown by the upward spike in the Tropics since January, the anomaly nearly tripling from 0.38C to 1.09C.  In September 2023, all regions rose, especially NH up from 0.70C to 1.41C, pulling up the global anomaly to a new high for this period. But then in October anomalies in all regions started dropping down bringing down the Global anomaly.  In December, NH cooled to 1.1C and the Global anomaly down to 0.94C from its peak of 1.10C, despite slight warming in SH and Tropics.

Comment:

The climatists have seized on this unusual warming as proof of their Zero Carbon agenda, without addressing how impossible it would be for CO2 warming the air to raise ocean temperatures.  It is the ocean that warms the air, not the other way around.  Recently Steven Koonin had this to say about the phonomenon confirmed in the graph above:

El Nino is a phenomenon in the climate system that happens once every four or five years.  Heat builds up in the equatorial Pacific to the west of Indonesia and so on.  Then when enough of it builds up it surges across the Pacific and changes the currents and the winds.  As it surges toward South America it was discovered and named in the 19th century  It is well understood at this point that the phenomenon has nothing to do with CO2.

Now people talk about changes in that phenomena as a result of CO2 but it’s there in the climate system already and when it happens it influences weather all over the world.   We feel it when it gets rainier in Southern California for example.  So for the last 3 years we have been in the opposite of an El Nino, a La Nina, part of the reason people think the West Coast has been in drought.

It has now shifted in the last months to an El Nino condition that warms the globe and is thought to contribute to this Spike we have seen. But there are other contributions as well.  One of the most surprising ones is that back in January of 2022 an enormous underwater volcano went off in Tonga and it put up a lot of water vapor into the upper atmosphere. It increased the upper atmosphere of water vapor by about 10 percent, and that’s a warming effect, and it may be that is contributing to why the spike is so high.

A longer view of SSTs

Open image in a new tab to enlarge.

The graph above 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. 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. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled 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 peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  In 2021-22 there were again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, then in October to January 2023 by deeper cooling in NH and Tropics.  

Now in 2023 the Tropics flipped from below to well above average, while NH has produced a summer peak extending into September higher than any previous year. In fact, October and now November are showing that this number is likely the crest, despite El Nino driving the Tropics anomaly close to 1998 and 2015 peaks.

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.

Contemporary AMO Observations

Through January 2023 I depended on the Kaplan AMO Index (not smoothed, not detrended) for N. Atlantic observations. But it is no longer being updated, and NOAA says they don’t know its future.  So I find that ERSSTv5 AMO dataset has data through October.  It differs from Kaplan, which reported average absolute temps measured in N. Atlantic.  “ERSST5 AMO  follows Trenberth and Shea (2006) proposal to use the NA region EQ-60°N, 0°-80°W and subtract the global rise of SST 60°S-60°N to obtain a measure of the internal variability, arguing that the effect of external forcing on the North Atlantic should be similar to the effect on the other oceans.”  So the values represent sst anomaly differences between the N. Atlantic and the Global ocean.

The chart above confirms what Kaplan also showed.  As August is the hottest month for the N. Atlantic, its varibility, high and low, drives the annual results for this basin.  Note also the peaks in 2010, lows after 2014, and a rise in 2021. Now in 2023 the peak was holding at 1.4C before decling.  An annual chart below is informative:

 

Note the difference between blue/green years, beige/brown, and purple/red years.  2010, 2021, 2022 all peaked strongly in August or September.  1998 and 2007 were mildly warm.  2016 and 2018 were matching or cooler than the global average.  2023 started out slightly warm, then rose steadily to an  extraordinary peak in July.  August to October were only slightly lower, but by December cooled by ~0.4C.

The pattern suggests the ocean may be demonstrating a stairstep pattern like that we have also seen in HadCRUT4. 

The purple line is the average anomaly 1980-1996 inclusive, value 0.18.  The orange line the average 1980-202306, value 0.38, also for the period 1997-2012. The red line is 2013-202306, value 0.64. As noted above, these rising stages are driven by the combined warming in the Tropics and NH, including both Pacific and Atlantic basins.

Curiosity:  Solar Coincidence?

The news about our current solar cycle 25 is that the solar activity is hitting peak numbers now and higher  than expected 1-2 years in the future.  As livescience put it:  Solar maximum could hit us harder and sooner than we thought. How dangerous will the sun’s chaotic peak be?  Some charts from spaceweatherlive look familar to these sea surface temperature charts.

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? And is the sun adding forcing to this process?

Space weather impacts the ionosphere in this animation. Credits: NASA/GSFC/CIL/Krystofer Kim

Footnote: Why Rely on HadSST4

HadSST 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.

HadSST4 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

 

 

UAH December 2023: Cooling Despite El Nino Spike

Posted on by Ron Clutz

The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots.  It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition.  Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.  

As an overview consider how recent rapid cooling  completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016).  The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022  At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020). Now we have an usual El Nino warming spike of uncertain cause, but unrelated to steadily rising CO2.

For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa.  While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions, with some cooling the last two months. 

Update August 3, 2021

Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT

image-8

 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

December 2023 Cooling Despite El Nino Spike

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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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in.  The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995.  Spring and Summer 2023 saw a series of warmings, continuing into October, but with cooling since. 

UAH has updated their tlt (temperatures in lower troposphere) dataset for December 2023. Posts on their reading of ocean air temps this month preceded updated records from HadSST4.  I last posted on SSTs using HadSST4 November 2023 Ocean Warmth Persists Due to Tropics 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.

Sometimes air temps over land diverge from ocean air changes.  November 2023 was notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions.  As a result the Global Ocean and Land anomaly result remained little changed. Now in December, all regions cooled except for Tropics.

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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4.  For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for December.  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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October.  That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June.  After an upward spike in July, ocean air everywhere cooled in August and also in September.   

After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.5C, with the largest increases in April to July, and continuing through to December 2023.  But now both SH and NH have dropped in December, pulling the global average back down despite the El Nino spike in the Tropics.

Land Air Temperatures Tracking 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 December is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land.  Land temps are dominated by NH with a 2021 spike in January,  then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere.  After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH. 

Remarkably, in 2023, SH land air anomaly shot up 2.1C, from  -0.6C in January to +1.5 in October, then dropped to 0.7 in November, 0.76 in December.  Tropical land temps are up 1.6 since January and NH Land air temps rose 0.9, mostly since May.  Now in December SH land air temps are little changed while the drop in NH brought the Global anomaly down despite another uptick in Tropical land temps. 

The Bigger Picture UAH Global Since 1980

The chart shows monthly Global anomalies starting 01/1980 to present.  The average monthly anomaly is -0.05, for this period of more than four decades.  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.   An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022.  March and April brought warmer Global temps, later reversed

With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October/November peak exceeded the sharp April peak of the El Nino 1998 event. It also surpassed the February peak in 2016.  December is down slightly, but where it goes from here, up or down further, remains to be seen.

The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.

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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

2024 Oceanic Climate Warming At Work

Posted on by Ron Clutz

David Wojick describes how ocean cycles create warming blips in global temperature records in his concise, plain language CFACT article Big temperature spike may lead to small temperature rise.  Excerpts in italics with my bolds and added images.

The recent big temperature spike has the climate alarmists all excited, pulling out all the hyperbolic stops as it were. The warming is huge they say. Their favorite descriptor — unprecedented — appears frequently.

Which makes it all very funny, since we had exactly this same situation not that long ago. What is most interesting is what happened next back then, because in my view it is likely to happen again. Let me explain.

For what follows you need to be looking at the UAH temperature record, which is here:

First of all compare the ongoing spike now with the 1998 spike. They are virtually identical as far as the short term temperature increase is concerned, roughly 1.0 degrees C. So as spikes go there is nothing unprecedented.

Yes the tip of the now spike is at a higher temperature that the 1998 spike and this is where is gets very interesting. The base of the now spike is warmer than the base was in 1998. This is because there has been a little bit of warming since then.

But all of that warming has occurred in two specific steps up, each following a super El Niño. After the 1998 spike the temperature oscillated around a constant value that was warmer than before the spike but there was no additional warming until the 2016 super El Niño spike came along. Then after that spike it was again warmer but with no warming.

All the warming in the entire record occurs in just two steps with no warming in between. For the record I first pointed out this step pattern six years ago, when there was just one clear step, the 1998. See No CO2 warming for the last 40 years

At the time we were wondering if this step pattern would repeat with the 2016 super El Niño and by golly it did.

So now the question is will we get another little step up in average temperature from the ongoing spike? My bet is it will so, Of course I am prepared to be wrong but it is still very likely.  But the basic point from six years ago remains.

There is no evidence of any warming due to the ongoing steady CO2
increase in this entire 45 year record. None whatsoever as it is
all clearly to do with the periodic occurrence of super El Niños.

The likely explanation also seems pretty simple. There is residual energy in the atmosphere left over from each spike. So the total energy goes up with each step.

Note that the energy in the spike does not come from the El Niño. An El Niño is simply a lack of cold water upwelling. Without that cold water the ocean surface layer gets a lot warmer from the incoming solar energy. Some of that energy goes into the atmosphere creating the big spike. That some of it would then hang around does not seem surprising. There is no reason why the La Niña that follows each super El Niño should remove all recently added energy.

Here is my conclusion from six years ago: “But in no case is there any evidence of CO2 induced warming here, nor of any human-caused warming for that matter. These causes would produce a relatively steady warming over time, not the single episodic warming that we clearly see here. In particular, to my knowledge there is no known way that the gradual CO2 increase could have caused this giant El Nino-La Nina cycle.

Thus the little warming that there is in the last 40 years appears to be more or less entirely natural. In any normal science this result would be sufficient to invalidate the hypothesis that the increasing CO2 concentration is causing global warming.”

Nothing has changed. The hypothesis of anthropogenic global warming
is falsified by simple observation. Science is like that, or should be.

Addendum:

The stairstep warming also appears in HadSST4 global ocean temperature dataset, with the suggestion that a new plateau may be in place.

Since Hadcrut4 (ocean + land) goes back early in the 20th century, we can see the same pattern from an earlier analysis updated to today. 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.

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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions.

Footnote:

As David stated and diagramed so well, ENSO (El Nino Southern Oscillation) ocean cycle has driven this contemporary warming of atmospheric temperatures.  But we should also note how the Northern Atlantic has contributed to this effect, both in 2016 and currently.

To enlarge open image in new tab.

Note that in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  Then in 2023 we see the Tropical peaking from El Nino at the same time as the remarkable NH spike, raising the Global ocean anomaly to a new high.

Additional evidence for North Atlantic warming comes from the AMO index (Atlantic Multi-decadal Oscillation).  ERSSTv5 AMO dataset uses the NA region EQ-60°N, 0°-80°W and subtracts the global rise of SST 60°S-60°N to obtain a measure of the internal variability of NA. So the values represent SST anomaly differences between the N. Atlantic and the Global ocean.

The chart shows the outlier 2023 spike peaking in the North Atlantic in July, persisting through October, before dropping November and December. Note how much higher are these anomalies compared to 2016 in purple.  Note also that August typically has the highest NA ocean temperatures, so these anomalies are on top of the highest actual temperatures recorded.

It remains to be seen how long this warming will persist, and what will be the longer term effect, but as David explained, it all has nothing to do with CO2.

Temps Cause CO2 Changes, Not the Reverse. 2024 Update

Posted on by Ron Clutz

This post is about proving that CO2 changes in response to temperature changes, not the other way around, as is often claimed.  In order to do  that we need two datasets: one for measurements of changes in atmospheric CO2 concentrations over time and one for estimates of Global Mean Temperature changes over time.

Climate science is unsettling because past data are not fixed, but change later on.  I ran into this previously and now again in 2021 and 2022 when I set out to update an analysis done in 2014 by Jeremy Shiers (discussed in a previous post reprinted at the end).  Jeremy provided a spreadsheet in his essay Murray Salby Showed CO2 Follows Temperature Now You Can Too posted in January 2014. I downloaded his spreadsheet intending to bring the analysis up to the present to see if the results hold up.  The two sources of data were:

Temperature anomalies from RSS here:  http://www.remss.com/missions/amsu

CO2 monthly levels from NOAA (Mauna Loa): https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html

Changes in CO2 (ΔCO2)

Uploading the CO2 dataset showed that many numbers had changed (why?).

The blue line shows annual observed differences in monthly values year over year, e.g. June 2020 minus June 2019 etc.  The first 12 months (1979) provide the observed starting values from which differentials are calculated.  The orange line shows those CO2 values changed slightly in the 2020 dataset vs. the 2014 dataset, on average +0.035 ppm.  But there is no pattern or trend added, and deviations vary randomly between + and -.  So last year I took the 2020 dataset to replace the older one for updating the analysis.

Now I find the NOAA dataset starting in 2021 has almost completely new values due to a method shift in February 2021, requiring a recalibration of all previous measurements.  The new picture of ΔCO2 is graphed below.

The method shift is reported at a NOAA Global Monitoring Laboratory webpage, Carbon Dioxide (CO2) WMO Scale, with a justification for the difference between X2007 results and the new results from X2019 now in force.  The orange line shows that the shift has resulted in higher values, especially early on and a general slightly increasing trend over time.  However, these are small variations at the decimal level on values 340 and above.  Further, the graph shows that yearly differentials month by month are virtually the same as before.  Thus I redid the analysis with the new values.

Global Temperature Anomalies (ΔTemp)

The other time series was the record of global temperature anomalies according to RSS. The current RSS dataset is not at all the same as the past.

Here we see some seriously unsettling science at work.  The purple line is RSS in 2014, and the blue is RSS as of 2020.  Some further increases appear in the gold 2022 rss dataset. The red line shows alterations from the old to the new.  There is a slight cooling of the data in the beginning years, then the three versions mostly match until 1997, when systematic warming enters the record.  From 1997/5 to 2003/12 the average anomaly increases by 0.04C.  After 2004/1 to 2012/8 the average increase is 0.15C.  At the end from 2012/9 to 2013/12, the average anomaly was higher by 0.21. The 2022 version added slight warming over 2020 values.

RSS continues that accelerated warming to the present, but it cannot be trusted.  And who knows what the numbers will be a few years down the line?  As Dr. Ole Humlum said some years ago (regarding Gistemp): “It should however be noted, that a temperature record which keeps on changing the past hardly can qualify as being correct.”

Given the above manipulations, I went instead to the other satellite dataset UAH version 6. UAH has also made a shift by changing its baseline from 1981-2010 to 1991-2020.  This resulted in systematically reducing the anomaly values, but did not alter the pattern of variation over time.  For comparison, here are the two records with measurements through December 2023.

Comparing UAH temperature anomalies to NOAA CO2 changes.

Here are UAH temperature anomalies compared to CO2 monthly changes year over year.

Changes in monthly CO2 synchronize with temperature fluctuations, which for UAH are anomalies now referenced to the 1991-2020 period.  As stated above, CO2 differentials are calculated for the present month by subtracting the value for the same month in the previous year (for example June 2022 minus June 2021).   Temp anomalies are calculated by comparing the present month with the baseline month.

The final proof that CO2 follows temperature due to stimulation of natural CO2 reservoirs is demonstrated by the ability to calculate CO2 levels since 1979 with a simple mathematical formula:

For each subsequent year, the co2 level for each month was generated

CO2  this month this year = a + b × Temp this month this year  + CO2 this month last year

Jeremy used Python to estimate a and b, but I used his spreadsheet to guess values that place for comparison the observed and calculated CO2 levels on top of each other.

In the chart calculated CO2 levels correlate with observed CO2 levels at 0.9986 out of 1.0000.  This mathematical generation of CO2 atmospheric levels is only possible if they are driven by temperature-dependent natural sources, and not by human emissions which are small in comparison, rise steadily and monotonically.

Comment:  UAH dataset reported a sharp warming spike starting mid year, with causes speculated but not proven.  In any case, that surprising peak has not yet driven CO2 higher, though it might,  but only if it persists despite the likely cooling already under way.

Previous Post:  What Causes Rising Atmospheric CO2?

nasa_carbon_cycle_2008-1

This post is prompted by a recent exchange with those reasserting the “consensus” view attributing all additional atmospheric CO2 to humans burning fossil fuels.

The IPCC doctrine which has long been promoted goes as follows. We have a number over here for monthly fossil fuel CO2 emissions, and a number over there for monthly atmospheric CO2. We don’t have good numbers for the rest of it-oceans, soils, biosphere–though rough estimates are orders of magnitude higher, dwarfing human CO2.  So we ignore nature and assume it is always a sink, explaining the difference between the two numbers we do have. Easy peasy, science settled.

What about the fact that nature continues to absorb about half of human emissions, even while FF CO2 increased by 60% over the last 2 decades? What about the fact that in 2020 FF CO2 declined significantly with no discernable impact on rising atmospheric CO2?

These and other issues are raised by Murray Salby and others who conclude that it is not that simple, and the science is not settled. And so these dissenters must be cancelled lest the narrative be weakened.

The non-IPCC paradigm is that atmospheric CO2 levels are a function of two very different fluxes. FF CO2 changes rapidly and increases steadily, while Natural CO2 changes slowly over time, and fluctuates up and down from temperature changes. The implications are that human CO2 is a simple addition, while natural CO2 comes from the integral of previous fluctuations.  Jeremy Shiers has a series of posts at his blog clarifying this paradigm. See Increasing CO2 Raises Global Temperature Or Does Increasing Temperature Raise CO2 Excerpts in italics with my bolds.

The following graph which shows the change in CO2 levels (rather than the levels directly) makes this much clearer.

Note the vertical scale refers to the first differential of the CO2 level not the level itself. The graph depicts that change rate in ppm per year.

There are big swings in the amount of CO2 emitted. Taking the mean as 1.6 ppmv/year (at a guess) there are +/- swings of around 1.2 nearly +/- 100%.

And, surprise surprise, the change in net emissions of CO2 is very strongly correlated with changes in global temperature.

This clearly indicates the net amount of CO2 emitted in any one year is directly linked to global mean temperature in that year.

For any given year the amount of CO2 in the atmosphere will be the sum of

  • all the net annual emissions of CO2
  • in all previous years.

For each year the net annual emission of CO2 is proportional to the annual global mean temperature.

This means the amount of CO2 in the atmosphere will be related to the sum of temperatures in previous years.

So CO2 levels are not directly related to the current temperature but the integral of temperature over previous years.

The following graph again shows observed levels of CO2 and global temperatures but also has calculated levels of CO2 based on sum of previous years temperatures (dotted blue line).

Summary:

The massive fluxes from natural sources dominate the flow of CO2 through the atmosphere.  Human CO2 from burning fossil fuels is around 4% of the annual addition from all sources. Even if rising CO2 could cause rising temperatures (no evidence, only claims), reducing our emissions would have little impact.

Addendum:

Roland Van den Broek made the valid point in his comments below that any two data sets generally trending positive will show a high degree of correlation, not proving any causation.  Certainly, UAH reports rising GMA (Global Mean Anomalies) and MLO reports rising CO2.  Note however that Δ GMA predicts Δ CO2 with a correlation of 0.9986.  For comparison, I generated GMA from CO2 differentials, resulting in a lower correlation of 0.6030.  I conclude that Δ CO2 ⇒ Δ GMA is spurious, while Δ GMA ⇒ Δ CO2 is real.

Resources
For a possible explanation of natural warming and CO2 emissions see Little Ice Age Warming Recovery May be Over
Resources:

CO2 Fluxes, Sources and Sinks

Who to Blame for Rising CO2?

Fearless Physics from Dr. Salby

In this video presentation, Dr. Salby provides the evidence, math and charts supporting the non-IPCC paradigm.

Footnote:  As CO2 concentrations rose, BP shows Fossil Fuel consumption slumped in 2020, Then Recovered

See also 2022 Update: Fossil Fuels ≠ Global Warming

November 2023 Ocean Warmth Persists Due to Tropics

Posted on by Ron Clutz

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;
  • Major El Ninos have been 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. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through November 2023.  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 in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean.

Then in 2022, another strong NH summer spike peaked in August, but this time both the Tropic and SH were countervailing, resulting in only slight Global warming, later receding to the mean.   Oct./Nov. temps dropped  in NH and the Tropics took the Global anomaly below the average for this period. After an uptick in December, temps in January 2023 dropped everywhere, strongest in NH, with the Global anomaly further below the mean since 2015.

Now comes El Nino as shown by the upward spike in the Tropics since January, the anomaly nearly tripling from 0.38C to 1.07C.  In August 2023, all regions rose, especially NH up from 0.70C to 1.37C, pulling up the global anomaly to a new high for this period. September showed a new peak for NH at 1.41, but then in October anomalies in all regions have dropped down 0.1C bringing down the Global anomaly.  In November, NH added cooling, offset by slight warming in SH.  Tropical ocean temps rose to nearly match 2015 in November, but the Global anomaly changed little and remained lower than the September peak.

Comment:

The climatists have seized on this unusual warming as proof of their Zero Carbon agenda, without addressing how impossible it would be for CO2 warming the air to raise ocean temperatures.  It is the ocean that warms the air, not the other way around.  Recently Steven Koonin had this to say about the phonomenon confirmed in the graph above:

El Nino is a phenomenon in the climate system that happens once every four or five years.  Heat builds up in the equatorial Pacific to the west of Indonesia and so on.  Then when enough of it builds up it surges across the Pacific and changes the currents and the winds.  As it surges toward South America it was discovered and named in the 19th century  It is well understood at this point that the phenomenon has nothing to do with CO2.

Now people talk about changes in that phenomena as a result of CO2 but it’s there in the climate system already and when it happens it influences weather all over the world.   We feel it when it gets rainier in Southern California for example.  So for the last 3 years we have been in the opposite of an El Nino, a La Nina, part of the reason people think the West Coast has been in drought.

It has now shifted in the last months to an El Nino condition that warms the globe and is thought to contribute to this Spike we have seen. But there are other contributions as well.  One of the most surprising ones is that back in January of 2022 an enormous underwater volcano went off in Tonga and it put up a lot of water vapor into the upper atmosphere. It increased the upper atmosphere of water vapor by about 10 percent, and that’s a warming effect, and it may be that is contributing to why the spike is so high.

A longer view of SSTs

To enlarge, open image in new tab.

The graph above 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. 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. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled 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 peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  In 2021-22 there were again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, then in October to January 2023 by deeper cooling in NH and Tropics.  

Now in 2023 the Tropics flipped from below to well above average, while NH has produced a summer peak extending into September higher than any previous year. In fact, October and now November are showing that this number is likely the crest, despite El Nino driving the Tropics anomaly close to 1998 and 2015 peaks.

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.

Contemporary AMO Observations

Through January 2023 I depended on the Kaplan AMO Index (not smoothed, not detrended) for N. Atlantic observations. But it is no longer being updated, and NOAA says they don’t know its future.  So I find that ERSSTv5 AMO dataset has data through October.  It differs from Kaplan, which reported average absolute temps measured in N. Atlantic.  “ERSST5 AMO  follows Trenberth and Shea (2006) proposal to use the NA region EQ-60°N, 0°-80°W and subtract the global rise of SST 60°S-60°N to obtain a measure of the internal variability, arguing that the effect of external forcing on the North Atlantic should be similar to the effect on the other oceans.”  So the values represent sst anomaly differences between the N. Atlantic and the Global ocean.

The chart above confirms what Kaplan also showed.  As August is the hottest month for the N. Atlantic, its varibility, high and low, drives the annual results for this basin.  Note also the peaks in 2010, lows after 2014, and a rise in 2021. Now in 2023 the peak is holding at 1.4C.  An annual chart below is informative:

Note the difference between blue/green years, beige/brown, and purple/red years.  2010, 2021, 2022 all peaked strongly in August or September.  1998 and 2007 were mildly warm.  2016 and 2018 were matching or cooler than the global average.  2023 started out slightly warm, then rose steadily to an  extraordinary peak in July.  August to October were only slightly lower, but now November cooled by ~0.3C.

The pattern suggests the ocean may be demonstrating a stairstep pattern like that we have also seen in HadCRUT4. 

The purple line is the average anomaly 1980-1996 inclusive, value 0.18.  The orange line the average 1980-202306, value 0.38, also for the period 1997-2012. The red line is 2013-202306, value 0.64. As noted above, these rising stages are driven by the combined warming in the Tropics and NH, including both Pacific and Atlantic basins.

Curiosity:  Solar Coincidence?

The news about our current solar cycle 25 is that the solar activity is hitting peak numbers now and higher  than expected 1-2 years in the future.  As livescience put it:  Solar maximum could hit us harder and sooner than we thought. How dangerous will the sun’s chaotic peak be?  Some charts from spaceweatherlive look familar to these sea surface temperature charts.

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? And is the sun adding forcing to this process?

Space weather impacts the ionosphere in this animation. Credits: NASA/GSFC/CIL/Krystofer Kim

Footnote: Why Rely on HadSST4

HadSST 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.

HadSST4 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

 

 

Gross Errors in Textbook Climate Science

Posted on by Ron Clutz

Dr. Paul Pettré provides a damning critque of textbook climate science taught to impressionable students.

Paul Pettré is Honorary Chief Meteorological Engineer. His scientific training took place at the Pierre and Marie Curie University (Paris VI) where he obtained a PhD in geophysics with Professor Paul Queney. His career developed at Météo-France by analyzing aerological campaigns on local winds and air pollution problems. At the end of his career, Paul Pettré turned to the study of atmospheric circulation and climate in Antarctica, where he carried out seven missions. Paul Pettré has published numerous articles in high-level peer-reviewed journals internationally and has established collaborations with several international research teams.

His article in French is at the blog Association des climato-réalistes Critique objective du concept d’effet de serre (Objective Critique of Greenhouse Gas Effect).  The paper in French is here as a Word Document. Below is an English translation I produced using an online translator (any mistakes you can attribute to Mr. Google).  Later on I post some insightful comments with responses from the author, which really served as a tutorial on earth’s climate system and its thermodynamics.   Dr. Pettré’s summary comment in that thread serves as an overview to the paper and discussion. (bolds are mine along with some images).

Plain Language Overview

In this paper, we discuss the radiation budget observed by satellite over an annual cycle. In this radiation budget, only two fluxes are measured: the incoming flux of 340 W and the flux emitted by the surface of the Earth + Oceans system of 240 W. All other terms of the Earth’s energy balance are estimates. The IPCC says that the Earth is in thermal equilibrium, implying that the energy emitted to the cosmos is 340 W to balance the incoming energy.

The IPCC says that the Earth + Ocean system emits to the atmosphere all the energy received from the sun estimated at 240 W, implying that the Earth + Ocean system is a black body. What physics says is that the thermodynamic system Earth + Oceans + Atmosphere is not in thermal equilibrium and that it has entropy. Physics also says that the Earth + Oceans thermodynamic system is not a black body and therefore the energy emitted from the surface of the system to the atmosphere is not equal to the energy received.

The IPCC’s energy balance is therefore wrong for these two reasons, which are purely a matter of thermodynamics. In this false assessment, a certain amount of energy is missing, which comes from hazardous estimates attributed to what the IPCC calls the “greenhouse effect”. This missing energy, estimated at 155 W, was calculated according to the “Earth’s energy budget” proposed by NASA/NOAA, which is agreed upon by the IPCC.

Objective Criticism of the Greenhouse Effect Concept

The scientific consensus introduced by the IPCC several years ago is that the Climatic warming observed since the mid-19th century would be the consequence of the increase in the concentration of “greenhouse gases” (GHGs) resulting from the concomitant increase in the industrial activities that consume the fossil fuels such as coal and oil.

For example, the chemistry textbook for university students (Th.L.Brown, H.E. LeMay, Jr. a.o. Chemistry. The Central Science. Pearson Education. 2009. ISBN 978-0-13-235-848-4. 1117 pp.) says on page 761 [1, p 761]:

“In addition to protecting us from harmful short-wavelength radiation, the atmosphere is essentially at a reasonably uniform and moderate temperature at the Earth’s surface. The Earth is in global thermal equilibrium with its environment. That means that the planet is emitting energy into space at a rate equal to the rate at which it absorbs energy from the sun. (…)

A portion of the infrared radiation that covers the surface of the the Earth is absorbed by water vapor and carbon dioxide from the atmosphere. In Absorbing this radiation, these two atmospheric gases help to maintain a uniform and livable temperature at the surface by retaining, so to speak, infrared radiation, which we feel as heat. The influence of H2O, CO2 and certain other atmospheric gases on the temperature of the Earth is called the “greenhouse effect” because, by trapping infrared radiation, these gases act like the glass in a greenhouse. The gases themselves are called “greenhouse gases” (GHG).”

This definition corresponds to the current scientific consensus of what is known as the “greenhouse effect” advocated by the IPCC and supported by most of the national scientific institutes such as NOAA in the United States or CNRS in France.

However, this definition lacks scientific rigour due to approximations or
neglect and ignorance of the physical laws that govern general circulation
of the atmosphere at the origin of what is known as the climate.

The first three sentences of the first paragraph of this definition are erroneous from a scientific point of view:

1. The atmosphere does not maintain a uniform and moderate temperature at the surface of the Earth.

The atmosphere of planet Earth is the gaseous fluid that surrounds its surface. This gas is held together by gravitational attraction and is set in motion by the unequal heating of its surface (thermodynamics) and by the rotation of the planet (force of of Coriolis).

The general circulation of the atmosphere is characterized by a very strong predominance of horizontal displacements, which are themselves generated by the predominance of meridional temperature or pressure gradients. On a global scale, it is considered that there is a close correlation between the distribution of the wind and pressure, and therefore also temperature by virtue of the hydrostatic equation.

It is therefore necessary to consider seasonal mean meridional distribution of temperature, pressure, and meridional component of the wind. In the troposphere, the average temperature decreases upwards at an average rate of 6 to 7°C per km, and horizontally towards the pole in each of the temperate zones, maximum amplitude in winter and minimum amplitude in summer. Horizontal meridional gradients are especially important in temperate zones and very low in all seasons in the equatorial zone.

As a result, the Earth’s global atmospheric circulation has bands alternating zonal circulation resulting from meridional temperature gradients, separated by areas of convergence and divergence of winds, which result from the Coriolis force generated by the rotation of the Earth on the herself. It is not scientifically possible to separate the global atmospheric circulation climate.

As a result, the control of climate models cannot be based on a criterion
that has no physical link with the overall atmospheric circulation.

Control of climate models based on an average surface temperature should, in order to be scientifically credible, be based on five meridian zones: -90° at -60°, -60° to -30°, -30° to +30°, +30° to +60° and +60° to +90°, where the – and + signs denote the southern and northern hemispheres.

2. The Earth is not in thermal equilibrium with its environment.

According to William Lowrie, the Earth’s internal heat is its greatest source of energy. It feeds into global geological processes such as the tectonics of the plates and the generation of the geomagnetic field. The Earth’s Internal Heat comes from two sources: the decay of radioactive isotopes present in rocks of the crust and mantle, and the primordial heat from the formation of the of the planet. Internal heat must find a way to remove itself from the Earth. The three main forms of heat transfer are radiation, conduction, and convection. Heat is also transferred during the transitions of composition and phase. Heat transport by conduction is the most important in solid regions of the Earth, while thermal convection occurs in the viscous mantle and the molten outer core.

According to the KamLAND collaboration, the Earth has cooled since its formation, but the decay of radiogenic isotopes, in particular uranium, thorium and potassium, in the interior of the planet, are a source of permanent heat. The current total heat flux from Earth to space is 44.2±1.0 TW, but the contribution from the primary waste heat and the radiogenic decay remains uncertain. However, the disintegration of radiogenic radiation can be estimated by the flux of geoneutrinos, electrically neutral emissions that are emitted during radio decay and that can cross the Earth practically unaffected. Here we combine precise measurements of the geoneutrino flux made by the antineutrino detector Kamioka, Japan, with existing detector measurements Borexino, Italy.

We find that the decay of uranium-238 and of Thorium-232 both contribute to the Earth’s heat flow. Neutrinos emitted by the decay of potassium 40 are below the detection limits of our experiences, but they are known to contribute 4 TW. Overall, our Observations indicate that the heat from the radioactive decay contributes to about half of the Earth’s total heat flux. We therefore conclude that the primordial heat of the Earth is not yet exhausted.

3.  The Earth emits more energy into space than it receives from the sun

The sun is not the Earth’s only source of heat. The sun provides the Earth a net solar radiation of 235 W/m2. In order for the Earth to be in thermal equilibrium, it would have to move into space as soon as possible 244 W/m2. In this case, the Earth would behave like a black body and there would be neither global warming nor cooling of the surface. For an emission of 235 W/m2 from Earth to space, that is, if the Earth were a black body, corresponds, by applying the Stefan-Boltzmann law with an albedo of 1, an average Earth’s surface temperature of -19°C.

But the Earth emits 390 W/m2 to space. So the Earth is not a black body since it emits 155 W/m2 more than it receives. For an emission of 390 W/m2, corresponds, applying the Stefan-Boltzmann law with an average albedo of 0.3, an average surface temperature of the Earth of 15°C. The mere fact that the Earth is not a black body, but a body with an average albedo has been estimated at 0.3 results in a warming of the average temperature Earth’s global surface temperature of about 30°C.

The CNRS in an article written by Marie-Antoine Mélières explains what warming by the “greenhouse effect” would provide the 155 W/m2 required for emission from the Earth’s surface of 390 W/m2. This theory assumes that the Earth and its atmosphere are two separate bodies, each in thermal equilibrium, and that all the energy received independently by one and the other is fully reissued by each one. This concept is demonstrably false since it would require that the Earth and the atmosphere be black bodies.

The Earth cannot be a black body because: on the one hand, it has an average albedo estimated at 0.3, which means that it does not re-emit all the energy received. And on the other hand that its core is made of molten material that radiates heat to the surface that it warms up. The volcanic regions are a clear proof of this. Similarly, there is no physical evidence that the atmosphere is a black body. It could not be since you can’t define its upper limit: it has no surface area above a given temperature.

As a result, it must be noted that the definition of the “greenhouse effect”
that is proposed by the IPCC and generally supported by scientific
institutions is a concept that cannot be not be scientifically proven.

We have seen that in the radiative balance of the Earth the 155 W/m2 that are emitted into the atmosphere can not be attributed to the “greenhouse effect. “That assumes the Earth behaves in a way like a black body, which it clearly is not, since it is scientifically accepted that it has a mean albedo different from 1 (O,3). And at least one can observe and evaluate locally, the heating of the surface by the Earth’s internal heat.

The CNRS statement (cited above) states: “The global effect of the greenhouse effect (is estimated): 155 watts per m2 surface heating (of which approximately 100 Watts related to the role of water vapour and 50 watts to CO2, all other remaining greenhouse gases constant”. That statement is therefore not physically demonstrated, nor is there any evidence of the effects claimed for the doubling of the concentration of CO2 in the atmosphere.

Comment Thread at Association des climato-réalistes

Various commenters participated, a few quite adversarial, and many inquisitive, with several responses provided by the author Dr.Paul Pettré.  Not surprising was the dismissing of earth internal heat as a climate factor.  The author responded accordingly.

Contrary to what you say, I do not give in my article the value of 44 TW for “the terrestrial heat flux”, but for one of the two terrestrial fluxes identified in the article cited in reference and estimated at 155 W per m2. Meteorology and climate are not exact sciences, but the mechanisms that govern them must always be able to be explained by physics. This requires working with proven scientific methods and some approximations or assumptions are permitted, but a responsible scientist must always keep in mind the assumptions on which he or she has based his or her study and be willing to examine contradictions if they arise.

Pettré provides a context regarding Earth internal heat:

Any thermodynamic system that is not in equilibrium, i.e. if a temperature gradient and/or movement is observed within the system, will necessarily tend for physical reasons to eventually reach a state of equilibrium. The Earth is no exception to this rule: it consumes energy that is not renewable and it is inexorably cooling. The problem is therefore to assess the entropy of the Earth and, knowing its energy reserve, to estimate its lifetime.

The loss of energy by radiation is not the only one to be taken into account because there is also the friction due to its rotation on itself and its displacement in the cosmos which is not empty. There may be others that I don’t know about, but I guess the energy lost through radiation is the most important. What is shocking about the very low value in mW/m2 that is proposed to us is that it leads to the Earth being almost eternal, which is probably not consistent with generally accepted astronomical theories.

I believe that the Earth’s energy reserve is evaluated on the basis of the mass of iron that constitutes the core of the Earth and its temperature, which has recently been re-evaluated, to the order of 6250°C, close to that of the surface of the sun. The objective of the referenced article was to assess the Earth’s life reserve. The authors’ conclusion is that there was no need to worry about this.

The problem we are interested in is whether the heat transfer from the centre of the Earth to the cosmos is the one identified so far of 44 TW or whether there could be another one of unidentified electromagnetic origin. The referenced article identified such a source of electromagnetic radiation measurable by complex methods and gave an approximate estimate of 155 W/m2, but this assessment was not the objective of the study and is given as a guideline. Nevertheless, it is of great value to us because it is a new result for the Earth’s energy balance.

To answer your question, we need to take into account the functioning of the Earth’s core and the influence of solar radiation on it. These questions are the subject of arduous discussions among astronomers which I cannot go into. Basically, in the center of the Earth, there is a core made of iron at a temperature of 6250°C. The energy source is nuclear fission. Around this core there is magma at a temperature between 680°C and 1200°C. Around the magma there is the Earth’s crust formed by tectonic plates.

Magma is in motion because the Earth rotates and it is subject, like the atmosphere, to the Coriolis force which varies with latitude, zero at the poles, maximum at the equator and combines with centrifugal force. It is this movement of the plasma that explains why there is a certain thrust on the Earth’s crust that displaces the tectonic plates. Over a very long period of time, on the order of billions of years, this force moves continents and modifies the climate.

Some authors believe that magma is isothermal and therefore not a source of electromagnetic radiation. Other authors consider the fact that the earth is in the atmosphere of the sun and subject to solar electromagnetic radiation which would have an effect on the magma which would be anisotropic from a magnetic point of view with an outward orientation. This electromagnetic anisotropy of the magma would explain the electromagnetic radiation observed by the authors.

Solar electromagnetic disturbances have a known period of 11 years. We are currently at the maximum of these disturbances, which may explain the increase in the frequency of some of the events currently observed. I can mention the auroras because the connection is obvious. To conclude, I would say that the discussion around these 155 W/m2 can take place, but it is not possible to dismiss this observation without serious argumentation.

Background Post Overview: Seafloor Eruptions and Ocean Warming

 

 

 

 

UAH November 2023: Ocean Stays Warm, Land Cools

Posted on by Ron Clutz

The post below updates the UAH record of air temperatures over land and ocean. Each month and year exposes again the growing disconnect between the real world and the Zero Carbon zealots.  It is as though the anti-hydrocarbon band wagon hopes to drown out the data contradicting their justification for the Great Energy Transition.  Yes, there has been warming from an El Nino buildup coincidental with North Atlantic warming, but no basis to blame it on CO2.  

As an overview consider how recent rapid cooling  completely overcame the warming from the last 3 El Ninos (1998, 2010 and 2016).  The UAH record shows that the effects of the last one were gone as of April 2021, again in November 2021, and in February and June 2022  At year end 2022 and continuing into 2023 global temp anomaly matched or went lower than average since 1995, an ENSO neutral year. (UAH baseline is now 1991-2020).

For reference I added an overlay of CO2 annual concentrations as measured at Mauna Loa.  While temperatures fluctuated up and down ending flat, CO2 went up steadily by ~60 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. And now in 2023 we are seeing an amazing episode with a temperature spike driven by ocean air warming in all regions. 

Update August 3, 2021

Chris Schoeneveld has produced a similar graph to the animation above, with a temperature series combining HadCRUT4 and UAH6. H/T WUWT

image-8

 

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

November 2023 Ocean Stays Warm, Land Cools

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 2020-21 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling set in.  The UAH data analyzed below shows that warming from the last El Nino had fully dissipated with chilly temperatures in all regions. After a warming blip in 2022, land and ocean temps dropped again with 2023 starting below the mean since 1995.  Spring and Summer 2023 saw a series of warmings.  Now in November the high persisted due to another rise in ocean air temps in all regions, while land air temps cooled everywhere, most strongly in SH.

UAH has updated their tlt (temperatures in lower troposphere) dataset for November 2023. Posts on their reading of ocean air temps this month preceded updated records from HadSST4.  I last posted on SSTs using HadSST4 October 2023 Ocean Cooling Off.  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.

Sometimes air temps over land diverge from ocean air changes.  November 2023 is notable for a dichotomy between Ocean and Land air temperatures in UAH dataset. Remarkably a new high for Ocean air temps appeared with warming in all regions, while Land air temps dropped with cooling in all regions.  As a result the Global Ocean and Land anomaly result remained little changed.

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 cooling oceans 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 change in priorities, updates are now exclusive to HadSST4.  For comparison we can also look at lower troposphere temperatures (TLT) from UAHv6 which are now posted for November.  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 revised 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 air 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. In 2021, SH and the Tropics both pulled the Global anomaly down to a new low in April. Then SH and Tropics upward spikes, along with NH warming brought Global temps to a peak in October.  That warmth was gone as November 2021 ocean temps plummeted everywhere. After an upward bump 01/2022 temps reversed and plunged downward in June.  After an upward spike in July, ocean air everywhere cooled in August and also in September.   

After sharp cooling everywhere in January 2023, all regions were into negative territory. Note the Tropics matched the lowest value, but since have spiked sharply upward +1.4C, with the largest increases in April to July, and continuing in Autumn 2023.  NH also warmed to 0.83C in the last 9 months, while SH ocean air rose about the same. Global Ocean air November 2023 now exceeds the 2016 peak by 0.2C, the main difference being the much higher rise in SH anomalies since June.  The strength of the El Nino will determine the pattern in coming months.

Land Air Temperatures Tracking 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 November is below.

Here we have fresh evidence of the greater volatility of the Land temperatures, along with extraordinary departures by SH land.  Land temps are dominated by NH with a 2021 spike in January,  then dropping before rising in the summer to peak in October 2021. As with the ocean air temps, all that was erased in November with a sharp cooling everywhere.  After a summer 2022 NH spike, land temps dropped everywhere, and in January, further cooling in SH and Tropics offset by an uptick in NH. 

Remarkably, in 2023, SH land air anomaly shot up 1.6C, from  -0.56C in January to +1.03 in October, then dropped to 0.7 in November.  Tropical land temps are up 1.6 since January and NH Land air temps rose 0.9, mostly since May.  Now in November NH land air temps are little changed and Tropical land temps down nearly 0.2C.

The Bigger Picture UAH Global Since 1980

The chart shows monthly Global anomalies starting 01/1980 to present.  The average monthly anomaly is -0.05, for this period of more than four decades.  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.   An upward bump in 2021 was reversed with temps having returned close to the mean as of 2/2022.  March and April brought warmer Global temps, later reversed.

With the sharp drops in Nov., Dec. and January 2023 temps, there was no increase over 1980. Now in 2023 the buildup to the October/November peak exceeds the sharp April peak of the El Nino 1998 event. It also surpasses the February peak in 2016.  Where it goes from here, up or down, remains to be seen.

The graph reminds of another chart showing the abrupt ejection of humid air from Hunga Tonga eruption.

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, nearly 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. Despite the three El Ninos, their warming has not persisted prior to 2023, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

October 2023 Ocean Cooling Off

Posted on by Ron Clutz

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;
  • Major El Ninos have been 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. Previously I used HadSST3 for these reports, but Hadley Centre has made HadSST4 the priority, and v.3 will no longer be updated.  HadSST4 is the same as v.3, except that the older data from ship water intake was re-estimated to be generally lower temperatures than shown in v.3.  The effect is that v.4 has lower average anomalies for the baseline period 1961-1990, thereby showing higher current anomalies than v.3. This analysis concerns more recent time periods and depends on very similar differentials as those from v.3 despite higher absolute anomaly values in v.4.  More on what distinguishes HadSST3 and 4 from other SST products at the end. The user guide for HadSST4 is here.

The Current Context

The chart below shows SST monthly anomalies as reported in HadSST4 starting in 2015 through October 2023.  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 in 2015-2016 the Tropics and SH peaked in between two summer NH spikes.  That pattern repeated in 2019-2020 with a lesser Tropics peak and SH bump, but with higher NH spikes. By end of 2020, cooler SSTs in all regions took the Global anomaly well below the mean for this period.  In 2021 the summer NH summer spike was joined by warming in the Tropics but offset by a drop in SH SSTs, which raised the Global anomaly slightly over the mean.

Then in 2022, another strong NH summer spike peaked in August, but this time both the Tropic and SH were countervailing, resulting in only slight Global warming, later receding to the mean.   Oct./Nov. temps dropped  in NH and the Tropics took the Global anomaly below the average for this period. After an uptick in December, temps in January 2023 dropped everywhere, strongest in NH, with the Global anomaly further below the mean since 2015.

Now comes El Nino as shown by the upward spike in the Tropics since January, the anomaly nearly tripling from 0.38C to 1.07C.  In August 2023, all regions rose, especially NH up from 0.70C to 1.37C, pulling up the global anomaly to a new high for this period. September showed a new peak for NH at 1.41, but now in October anomalies in all regions have dropped down 0.1C to bring the Global anomaly back down.

Comment:

The climatists have seized on this unusual warming as proof of their Zero Carbon agenda, without addressing how impossible it would be for CO2 warming the air to raise ocean temperatures.  It is the ocean that warms the air, not the other way around.  Recently Steven Koonin had this to say about the phonomenon confirmed in the graph above:

El Nino is a phenomenon in the climate system that happens once every four or five years.  Heat builds up in the equatorial Pacific to the west of Indonesia and so on.  Then when enough of it builds up it surges across the Pacific and changes the currents and the winds.  As it surges toward South America it was discovered and named in the 19th century  It is well understood at this point that the phenomenon has nothing to do with CO2.

Now people talk about changes in that phenomena as a result of CO2 but it’s there in the climate system already and when it happens it influences weather all over the world.   We feel it when it gets rainier in Southern California for example.  So for the last 3 years we have been in the opposite of an El Nino, a La Nina, part of the reason people think the West Coast has been in drought.

It has now shifted in the last months to an El Nino condition that warms the globe and is thought to contribute to this Spike we have seen. But there are other contributions as well.  One of the most surprising ones is that back in January of 2022 an enormous underwater volcano went off in Tonga and it put up a lot of water vapor into the upper atmosphere. It increased the upper atmosphere of water vapor by about 10 percent, and that’s a warming effect, and it may be that is contributing to why the spike is so high.

A longer view of SSTs

To enlarge, open image in new tab.

The graph above 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.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. There were strong cool periods before and after the 1998 El Nino event. Then SSTs in all regions returned to the mean in 2001-2. 

SSTS fluctuate around the mean until 2007, when another, smaller ENSO event occurs. There is cooling 2007-8,  a lower peak warming in 2009-10, following by cooling in 2011-12.  Again SSTs are average 2013-14.

Now a different pattern appears.  The Tropics cooled 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 peaks came in 2019 and 2020, only this time the Tropics and SH were offsetting rather adding to the warming. (Note: these are high anomalies on top of the highest absolute temps in the NH.)  Since 2014 SH has played a moderating role, offsetting the NH warming pulses. After September 2020 temps dropped off down until February 2021.  In 2021-22 there were again summer NH spikes, but in 2022 moderated first by cooling Tropics and SH SSTs, then in October to January 2023 by deeper cooling in NH and Tropics.  

Now in 2023 the Tropics flipped from below to well above average, while NH has produced a summer peak extending into September higher than any previous year. In fact, October is now showing that this number is likely the crest.

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.

Contemporary AMO Observations

Through January 2023 I depended on the Kaplan AMO Index (not smoothed, not detrended) for N. Atlantic observations. But it is no longer being updated, and NOAA says they don’t know its future.  So I find that ERSSTv5 AMO dataset has data through October.  It differs from Kaplan, which reported average absolute temps measured in N. Atlantic.  “ERSST5 AMO  follows Trenberth and Shea (2006) proposal to use the NA region EQ-60°N, 0°-80°W and subtract the global rise of SST 60°S-60°N to obtain a measure of the internal variability, arguing that the effect of external forcing on the North Atlantic should be similar to the effect on the other oceans.”  So the values represent sst anomaly differences between the N. Atlantic and the Global ocean.

The chart above confirms what Kaplan also showed.  As August is the hottest month for the N. Atlantic, its varibility, high and low, drives the annual results for this basin.  Note also the peaks in 2010, lows after 2014, and a rise in 2021. Now in 2023 the peak is holding at 1.4C.  An annual chart below is informative:

 

Note the difference between blue/green years, beige/brown, and purple/red years.  2010, 2021, 2022 all peaked strongly in August or September.  1998 and 2007 were mildly warm.  2016 and 2018 were matching or cooler than the global average.  2023 started out slightly warm, then in May and June spiked to match 2010. Now there is an  extraordinary peak in July, with August to October only slightly lower.

The pattern suggests the ocean may be demonstrating a stairstep pattern like that we have also seen in HadCRUT4. 

The purple line is the average anomaly 1980-1996 inclusive, value 0.18.  The orange line the average 1980-202306, value 0.38, also for the period 1997-2012. The red line is 2013-202306, value 0.64. As noted above, these rising stages are driven by the combined warming in the Tropics and NH, including both Pacific and Atlantic basins.

Curiosity:  Solar Coincidence?

The news about our current solar cycle 25 is that the solar activity is hitting peak numbers now and higher  than expected 1-2 years in the future.  As livescience put it:  Solar maximum could hit us harder and sooner than we thought. How dangerous will the sun’s chaotic peak be?  Some charts from spaceweatherlive look familar to these sea surface temperature charts.

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? And is the sun adding forcing to this process?

Space weather impacts the ionosphere in this animation. Credits: NASA/GSFC/CIL/Krystofer Kim

Footnote: Why Rely on HadSST4

HadSST 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.

HadSST4 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

 

 

Assessing Risk and Climate Science (Quora Discussion)

Posted on by Ron Clutz

Excerpted below is a Quora discussion with illuminating commentary from  Aaron Brown, former asset risk manager. AB responds to Topic Question and related comments, text in italics with my bolds and added images.

Quora? What will make conservatives accept climate change as real science?

AB: There are scientists who study cloud formation, ocean currents, rainfall patterns and other aspects of climate. Some are good, some not so much. Most people, liberal or conservative, accept that much of this is science.

Then there are scientists who build climate models and make predictions about things like global average temperature from 2081 to 2100 under different assumptions about human emissions and other factors. The people doing this work are considered scientists, but the conclusions are not science in the sense of empirically verifiable facts or consensus theories with strong empirical confirmation.

It’s a semantic game whether you call the conclusions “science” or not, but either way they are not as certain as scientific laws about gravity or momentum. People who like the predictions will embrace them, people who don’t like the predictions will resist them.

Liberals tend to be open to new ideas, conservatives tend to be more skeptical. That means many liberals are more willing to take strong action based on model predictions than are most conservatives. Skeptics tend to accept models if they make useful, non-obvious predictions that turn out to be true. Unfortunately it will take at least a century to gather that kind of evidence for climate models.

One possible breakthrough would be improvements in forecasting weather. You can prove a weather model in months rather than decades or centuries. But the fundamental claim of climate science is that it’s easier to predict global decadal averages in fifty years than next month’s weather in New York’s Central Park. That kind of claim—”I can’t predict the stuff you can check but trust me on stuff you can’t check”—makes skeptics skeptical.

A more likely breakthrough would be the the people making climate predictions proving their modeling ability by making useful, non-obvious predictions in other fields that can be validated. So far we have not seen this—successful modelers in other fields moving to climate science, or climate modelers proving success in other fields. This is a major point of skepticism for skeptics.

Finally, many conservatives are skeptical due to the big money involved in climate change combined with intense government interest and possibilities for vast wealth from subsidies and other programs. This is called Big Science and it’s often been dead wrong in the past, not to mention occasionally threatening all life on Earth. There are some successes of Big Science as well but skeptics will note the temptation to skew climate science for money or to push policies the advocates wanted before any climate support showed up.

None of this is relevant for policy decisions. If we somehow knew for certain today what the global mean temperature would be from 2081 – 2100, it wouldn’t tell us whether it was a good idea to ban coal or impose a carbon tax today. Conservatives are apt to assume any legislation will be written by lobbyists paid by cronies and empire-building bureaucrats rather than any kind of scientist. The laws will have unintended consequences, and send the economy and technology down unpredictable novel paths. We can’t estimate the effect on the human environmental footprint, we have only limited ability to relate the human environmental footprint to climate, and even less to relate climate to human welfare.

In such circumstances, the conservative inclination is to wait until you’re sure you’re helping things before spending a lot of money and writing a bunch of rules. The liberal tendency is to use your best judgement today, and expand the stuff that works tomorrow, while fixing or abandoning the stuff that doesn’t. This choice has nothing to do with climate science.

Comment: A model is just a theory put into numbers.

AB: Agreed, but the problem is lack of data. You can’t check 80 year in the future predictions with 30 years of data; and the global climate is so complex you need far more data even than we have with current measurements.

The data from more than 150 years or so is local data averaged over centuries or longer, useless for predicting global shorter-term data. Prior to 1990 we have very noisy data that is broader and available daily or sometimes even more often, but only since 1990 do we have anything like reliable, consistent global data.

People do calibrate their models to be consistent with the past, sometimes with more success than others. But there are so many parameters to global climate that this is not a useful check.

Comment: The required accuracy of your data and models grows exponentially with the amount of time you are predicting. It’s practically impossible to improve weather models beyond a certain point, so it’s not fair to consider this a failing of climate science.

AB: This is the central claim of climate science, but it remains unproven. Chaotic systems are not inherently unpredictable—for example the multibody solar system—and three or more bodies under gravity are chaotic—appears to have remained stable and pretty easy to predict for billions of years.

Attempts to predict weather in the most straightforward way, breaking the atmosphere down into small parts and applying rules of physics, have not succeeded in precise or long-range predictions—but there clearly are weather patterns that repeat often enough they must have some explanation. Modern weather prediction relies mainly on observed regularities without firm theoretic explanations.

You may be right that weather prediction will always be intractable, but perhaps some out-of-the-box idea will change that. If it did, we’d probably understand a lot more about climate.

It’s not obvious that long-term averages are more stable and predictable than shorter-term ones. In the stock market, for example, prices are pretty close to a random walk and uncertainty increases pretty steadily with the square root of time interval.

If you look at actual temperature measurements over local areas or global, over time scales from days to millions of years, uncertainty seems to increase with time, but slower than the square root. The unit of most certainty seems to be a year—predicting the average temperature over the next year has less uncertainty than predicting tomorrow’s temperature, but also less uncertainty than predicting the average temperature over the next decade or century.

Trajectories of a double pendulum. The simple predictable behavior of a pendulum appears chaotic when a second pendulum is attached. How many factors interact in our climate system?

This is a pure statistical observation, ignoring all climate science. The claim of climate science is models that incorporate things like solar variation, volcanoes, human emissions and so forth can make long-range averages less uncertain than annual averages. But we’ll need a lot of examples of long-range predictions—centuries of data—to confirm that directly, without resorting to climate theory; meaning that’s unlikely to convince skeptics in this century.

Of course you’re right that there seem to be physical limits that cause climate to move in cycles rather than drifting off to entirely new regimes—but regimes do change, and on planets other than Earth perhaps to extremes like losing the atmosphere.

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

But conservation of energy, for example, does not necessarily impose a constraint. There are many ways for energy to be removed from or added to global temperatures. It’s not necessarily true that, say, reducing incoming solar radiation cools the planet. In a simple system, reducing heat input lowers temperature. But in a complex system you could touch off any number of positive and negative feedback effects that could lead to any outcome.

Comment: I think this group is under valuing the large amount of research that has been predicting increases in global temperatures and the effects it will cause. There is ample data on the rate of increase in green house gases [CO2 and Methane] caused by humans lately.

AB: Are you saying that the predictions will convince skeptics? I disagree for several reasons.

1. There have been many predictions, many of which were spectacularly wrong, none of which were spectacularly right. The more catastrophic the prediction, the more often it turned out to be spectacularly wrong. Now you can go back after-the-fact and say the people making the worst predictions were nuts and other people made predictions that were not spectacularly wrong, but skeptics will find this unconvincing—like someone sifting through horoscope predictions to find some that seemed to come true.

2. The more sober predictions have merely been extrapolations of the recent past, too obvious to convince skeptics. Every time anything happens lots of people claim to have predicted it, and that it will continue in the future until disaster. Skeptics think that if temperatures started falling tomorrow, the predictions would quickly shift to predicting global cooling.

3.  Yes, atmospheric CO2 levels have gone up, and those could cause temperature increases, and humans are emitting CO2, and there’s no other obvious explanation for the increases in CO2. But those are simple observations. To convince skeptics of your explanations and predictions, you have to do more. If temperature increases tracked CO2 increases—rather than CO2 going up steadily and temperature bouncing up and down with more down months than up months—but an overall increase, the connection is not obvious.

4. Videos like the one you posted that tell us what things will be like decades in the future, something we cannot check, will not convince skeptics.

I think I outlined the main things likely to convince skeptics in my answer.

Comment: Many of the inter related factors determining climate have non linear relationships so modeling is extremely challenging and in order to produce sensible sounding outputs, tuning software is used to produce an answer deemed politically correct. If funding agencies would ban the use of tuning software the model funding would soon stop because of the self evident garbage answers.

AB: I agree and would go even further. I think climate is chaotic, and cannot be usefully modeled.

Everyone agrees that weather is chaotic, so only tentative short-term predictions are useful. But the defining claim of climate science is that if you average parameters like temperature over the entire globe over 20-year periods, it becomes predictable.

But if you check that assumption by comparing the standard deviation of temperature changes over larger regions and longer periods, you see it hits a minimum at single locations over one year. You can predict the average temperature in Central Park over the next year more accurately than tomorrow’s average temperature over New York State, or 20-years’ average temperature in Central Park.

It’s possible that casual models driven entirely by physics could surmount that issue, but so far these have been entirely unsuccessful without statistical tuning—tuning that does not improve ability for future predictions. Moreover you would expect such a model to predict weather better than climate, and no models can do that—they can only claim successful predictions over periods too long for practical testing.

That doesn’t mean climate models are worthless, but they are less reliable than weather reports, not more reliable.

Comment: In the case of climate, it’s the case that a large chunk of conservatives are still conservationists, who don’t get counted as environmentalists because of the heavy left (Marxist, even) bent of the green movement over the last several decades. Why not appeal to this perspective?

AB: I think you’re focusing on the wrong issue. You don’t have to convince anyone that protecting the environment is important, you have to convince them you have a plan that will do more good than harm.

Nuclear power is a great example. It reduces CO2, but also other forms of pollution. It doesn’t require decades and trillions of dollars to build a new power-grid infrastructure, it’s plug-and-play with the existing system (almost, anyway). The technology is well-understood, safe and efficient. You won’t find opposition from conservatives, only from some liberals.

Several MEPs (mainly Greens) hold up anti-nuclear posters at the debate.

But other tactics will require more argument. A carbon tax, for example, would send technology and the economy down an entirely new path, with entirely unpredictable consequences. It would seem to increase uncertainty about future climate rather than decrease it. It has other issues as well. To gain support for one from skeptics, you’ll have to convince them that you can predict the effects of such a tax on human welfare in 2100 well enough to make it a good bet.

Geoengineering is the cheapest and surest way to reduce global temperatures, but it controversial on both left and right for its possible unintended consequences. Here you have to convince people the gain is worth the risk.

The single best no-brainer solution is to work for world peace and cooperation. War is the biggest threat to the environment and climate. Solutions to climate change and dozens of equally consequential global issues will require cooperation—or at least less conflict—among nations. Redirecting military spending to climate research and mitigation would do tremendous good. Best of all, world peace and global cooperation have many direct advantages, not just vastly improving our ability to respond rationally to issues like climate change.