Global warming, climate change, all these things are just a dream come true for politicians. I deal with evidence and not with frightening computer models because the seeker after truth does not put his faith in any consensus. The road to the truth is long and hard, but this is the road we must follow. People who describe the unprecedented comfort and ease of modern life as a climate disaster, in my opinion have no idea what a real problem is.
Total storms: 9-13
Hurricanes: 3-5
Major Hurricanes: 1-2
Landfalling U.S. hurricanes: 1-2
Impact storms on the U.S. when at least a warning is issued: 3
ACE Index: 85-105
For anyone at the conference, if you run into me, I will be more than happy to answer any questions.
Major points:
The forecast numbers have been taken way down.
The Canadian model has been thrown out.
The European indicates a powerful El Niño and a negative AMO “look”.
The closest analog is 2015.
The impact forecast is a roll of the dice.
Impacts will likely be below normal and scattered.
There is always the threat of one (un)lucky punch.
Early-season Gulf or SE system is a concern
The Western Pacific will take up the Global slack.
Eastern Pacific Mexican higher impact season possible
The forecast numbers for the 2026 season
Total storms: 9-13 Hurricanes: 3-5 Major Hurricanes: 1-2 Landfalling U.S. hurricanes: 1-2 Impact storms on the U.S. when at least a warning is issued: 3 ACE Index: 85-105
The closest analog is 2015:
This El Niño means business:
Now that we have a good look at the Euro, its message is strongly bearish on the overall season and well below the averages since 2015.
SST forecasts
First of all, the 2023 hyper El Niño season had a nice warm stretch in the Atlantic. The SOI for that El Niño revealed a pattern that in the Pacific was unlike most El Niños, despite the warmth farther to the east and allowed the big numbers we had then.
So that analog has been taken out.
The hyper 2024 season, which we picked out in December before, had the ultimate presentation with a weak La Niña and a large area of warmer-than-average SSTs in the Main Development Region of the Atlantic.
This season is the antilog to that, with warm water split in the Atlantic and a stronger El Niño:
This is more like 2015:
So, I am jumping on that analog.
The Sea Level Pressure forecast is not favorable either, implying stronger than average low-level easterlies in the Main Development Region at the height of the season:
That would increase shear.
The CFSv2 shows lower shear to the north of the Main Development Region, which makes sense:
Again, it also sounds a bit of an alarm about in-close development, with a puncher’s chance of a major hit. There will be a tendency for development to the north of the Main Development Region, and that increases the chances for storms in the Atlantic to stay out there, unless it develops to the west of 70°W.
There is no stopping this El Niño event, as the cumulative buildup of heat has been held back by the La Niña.
However, it’s all there and has been waiting for a burst of low-level westerly winds. This should start as the SOI is reversing:
As far as landfalls, I have no strong opinion this year. I don’t think this is like the weak El Niño of 2004, which saw Florida get hit with multiple storms. The last El Niño produced a fake major landfall with Idalia, which fell apart completely with no verified wind gust over 90 mph over land. With the water so warm, any storm that develops in close can get in a slugger’s punch. So, we can’t rule out a major hurricane hitting. Overall, though, I believe it is going to be much more in line with scattershot seasons.
Remember though, three El Niño years, 1969, 1976, and 1991, had hits in the Northeast. You have to wonder how long their drought can go on, along with southeastern Florida (landfalls from the southeast).
Early on (before July 15), I am concerned about the Gulf states, including Florida. The Gulf is quite warm. While I am just speculating here, I am expecting higher than average pressures to stick their nose down the plains toward Mexico in May and June.
This would force convergence into the Gulf. So that is something to watch.
The Western Pacific Typhoon season has been remarkably quiet for the last few years, contributing to the overall downturn (slightly) of Global ACE. This is because the Western Pacific is home to close to 60% of the Northern Hemisphere’s normal ACE. There have been only two extremely active years since 2015, and the busiest was 2015, our analog.
Remember, normal there is around 300. So I would prepare for a lot of activity in the Western Pacific. The Eastern Pacific looks normal to a bit above normal, and there will likely be some late-season landfalls on the Mexican coast. Hawaii also has to be wary, as El Niño years have been known to bring problems there.
The Verdict
I have become more impressed with the El Niño forecast and what is going on in the Pacific. The burst of westerlies at 850 mb to the north of the tropics in the Pacific is the strongest on record so early, and the SOI is likely to tank. The very warm Gulf and the late May and June pattern have me concerned about early-season impacts. There have been El Niño years when the Northeast has been hit, but again, unlike other years, I have no strong feeling for where the storms will go. I do have a strong feeling about total numbers, which should be suppressed. Because of in-close development and the warm SSTs, there is a puncher’s chance of a major hurricane landfall.
Joe Bastardi is a pioneer in extreme weather and long-range forecasting. He is the author of “The Climate Chronicles: Inconvenient Revelations You Won’t Hear From Al Gore — and Others” which you can purchase at the CFACT bookstore. His new book The Weaponization of Weather in the Phony Climate war can be found here. phonyclimatewar.com
Let’s get something straight: this new study entitled Equatorial Atlantic mid-depth warming indicates Atlantic meridional overturning circulation slowdown, hot off the Nature presses and already getting the full catastrophe-trending treatment, claims that mysterious “mid-depth warming” in the equatorial Atlantic—between 1,000 and 2,000 meters down—is the long-sought “fingerprint” proving that the Atlantic Meridional Overturning Circulation (AMOC) has been slowing since the 1990s.
Let’s get something straight: this new study entitled Equatorial Atlantic mid-depth warming indicates Atlantic meridional overturning circulation slowdown,hot off the Nature presses and already getting the full catastrophe-trending treatment, claims that mysterious “mid-depth warming” in the equatorial Atlantic—between 1,000 and 2,000 meters down—is the long-sought “fingerprint” proving that the Atlantic Meridional Overturning Circulation (AMOC) has been slowing since the 1990s.
According to the authors, this subsurface warming is more “reliable” than surface measurements, cleaner than the noise-soaked sea surface temperatures everyone’s been arguing about for years, and—conveniently—it fits right into the climate alarm narrative that the AMOC is heading for catastrophic collapse. If you buy this story, you’re supposed to panic now, because the collapse might already be underway, the tipping point looms, and we’re all headed for Day After Tomorrow ice-age-in-a-week horror.
There’s just one problem: the whole edifice is built on model outputs, selective data interpretation, circular reasoning, and a studied refusal to acknowledge that the AMOC might be doing just fine.
Let’s start with the foundation. The authors run the MIT General Circulation Model (MITgcm) using forcing data pulled from CMIP6 climate model simulations under a quadrupled CO₂ scenario—because apparently we needed more hypotheticals stacked on hypotheticals. Of course, there’s not enough fossil fuels on the planet to lead to a quadrupled CO₂ level, but pay no attention to the man behind the curtain …
Then they impose abrupt changes in wind stress, sea surface temperature, and sea surface salinity, taken straight from models that already assume an AMOC slowdown, and—surprise!—the model dutifully spits out a slowdown and equatorial warming. It’s the scientific equivalent of asking a parrot to repeat what you just taught it, then claiming the parrot discovered language.
The “experiments” (BUOY, BUOY-NA, SSS-NA) are all variations on a theme: fiddle with surface forcing, watch the model respond in pre-cooked ways, then cherry-pick the results that support the thesis. Want mid-depth warming? Easy—force in North Atlantic freshening (which the CMIP6 models already baked in as part of their AMOC-weakening scenarios), sit back, and let “baroclinic Kelvin waves” do the propagation magic. It’s not an independent test of the hypothesis; it’s a self-fulfilling simulation.
The study’s logic runs in a perfect circle.
Step one: assume the CMIP6 models (which all project AMOC weakening under CO₂ forcing) are correct.
Step two: use those same models’ outputs as forcing for your ocean model.
Step three: when your ocean model shows equatorial warming, declare that this warming is the “fingerprint” of AMOC slowdown.
Step four: find warming in the observational data.
Step five: conclude the AMOC must be slowing because you found the “fingerprint.”
At no point do they test whether the warming could be driven by anything other than AMOC changes—such as, oh, I don’t know, local wind patterns, El Niño teleconnections, subsurface advection from other basins, or the natural variability that the equatorial Atlantic is famous for.
The authors triumphantly point to warming trends in gridded datasets (WOA, Argo, IAP, Ishii, EN4) showing 0.14°C of mid-depth warming from 1960 to 2020. Sounds impressive until you realize: (1) pre-1980 subsurface data in the equatorial Atlantic is sparse, riddled with gaps, and heavily interpolated; (2) Argo floats only started coverage in 2004, so the “robust” trend is mostly a post-millennial artifact; and (3) the “signal-to-noise” ratio they’re so proud of is high precisely because mid-depth waters have high thermal inertia—meaning the warming could be a slow, cumulative response to anything, not necessarily AMOC changes.
Moreover, the study conveniently ignores a major new findingpublished just this year in Nature: an independent reconstruction using air-sea heat flux data concluded that the AMOC has not declined over the past 60 years and is more stable than previously thought. That study, from Woods Hole, directly contradicts the premise here and suggests that relying on SST proxies (the very thing this new study is trying to replace) was always the problem—not because the AMOC is weakening, but because SSTs are lousy proxies in the first place.
Yes, baroclinic Kelvin waves are real, and yes, they can propagate warming signals from the subpolar North Atlantic down the western boundary and across the equator. The authors make a big deal about “rapid adjustment” and “dynamical signals,” invoking vertical mode decomposition and wave speeds to lend scientific gravitas. But here’s what they don’t tell you: the equatorial Atlantic is also subject to wind-driven upwelling, Atlantic Niño/Niña variability, off-equatorial Rossby wave adjustments from the northwestern tropical Atlantic (not the subpolar regions), and teleconnections from the Pacific. Multiple studies have shown that equatorial Atlantic warming is more consistently linked to local and regional processes—especially wind stress curl anomalies associated with the Atlantic Meridional Mode—than to remote AMOC forcing.
The fact that their passive tracer experiment (BUOY-NA-passive) shows minimal mid-depth warming from mean circulation alone doesn’t rule out these other mechanisms—it just means their model setup didn’t include them.
The authors claim the warming “emerged” from natural variability around 2001, with a signal-to-noise ratio exceeding their arbitrary threshold of 4 (99.9% confidence). But “time of emergence” is a model-dependent metric that depends entirely on how you define “signal” and “noise.” They define signal as the linear trend and noise as detrended variability—which guarantees that any long-term drift, regardless of cause, will eventually “emerge.” It’s a statistical trick that makes any monotonic change look significant if you wait long enough.
The study buries or ignores inconvenient facts. For instance:
The subpolar North Atlantic “cold blob” (the supposed surface fingerprint of AMOC slowdown) has been highly variable and even disappeared in recent years.
Direct AMOC measurements from the RAPID array show large interannual variability with no clear long-term trend since 2004.
Multiple lines of evidence (including paleo-proxies and modern reanalysis) suggest the AMOC has been relatively stable over the instrumental period, with most of the “weakening” claims based on noisy, short-term SST datasets.
This isn’t dispassionate science. It’s model-driven alarmism dressed up in the language of “fingerprints” and “dynamical mechanisms.” The authors want you to believe that a few tenths of a degree of subsurface warming—detectable only after heroic interpolation and smoothing of sparse data—is the smoking gun for an AMOC on the brink. They invoke “tipping points,” cite scary projections of 2 Sv decline since the 1950s, and darkly hint that we’re already past the point of no return.
But the data don’t support it, the models are unreliable, and the alternative explanations are everywhere if you’re willing to look. The equatorial Atlantic warms for lots of reasons—most of them having nothing to do with the AMOC. This study cherry-picks one mechanism, builds an entire edifice on model outputs that assume what they’re trying to prove, and then declares victory because gridded datasets (with all their uncertainties) show a trend.
If you want to monitor the AMOC, measure it directly. Don’t use proxy tea-leaves from a noisy, complex region, filtered through biased models, and call it a “superior fingerprint.” This is climate science at its worst: models all the way down, confirmation bias all the way up, and a conclusion tailor-made for the next round of climate crisis headlines. The AMOC is probably fine. The real collapse is in scientific skepticism.
Seems like as the climate alarmism grift collapses, the claims get more outrageous. Meanwhile, here’s the situation in the real world …
My very best to everyone,
w.
PS—As is my wont, I ask that when you comment you quote the EXACT WORDS you are discussing. I can defend my words. I can’t defend your interpretation of my words. Thanks.
The ocean covers 71% of the globe and drives average temperatures; The SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations and Major El Ninos have been the dominant climate feature in recent years.
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 August 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 1.06C. 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 shows a new peak for NH at 1.41, but both SH and the Tropics cooled enough 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
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 with August higher than any previous year. In fact, the summer warming peaks in NH have occurred in August or September, so 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 August. 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 a peak in July, with August and September 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.
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
The best context for understanding decadal temperature changes comes from the world’s sea surface temperatures (SST), for several reasons:
The ocean covers 71% of the globe and drives average temperatures;
SSTs have a constant water content, (unlike air temperatures), so give a better reading of heat content variations;
A major El Nino was the dominant climate feature in recent years.
HadSST is generally regarded as the best of the global SST data sets, and so the temperature story here comes from that source. 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 March 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.
In February Global SSTs stayed cool, but in March temps everywhere spiked upward. SH and the Tropics both showed anomalies 0.16C higher than February, pulling the Global anomaly up 0.12C. Both SH and NH are now close to the Global anomaly of 0.78C
A longer view of SSTs
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. Now in 2021-22 there are 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. The graph shows the warming spikes since 2015, including one last month, lifted the Global anomaly by about 0.2C above the mean since 1995 (an ENSO neutral year).
What to make of all this? The patterns suggest that in addition to El Ninos in the Pacific driving the Tropic SSTs, something else is going on in the NH. The obvious culprit is the North Atlantic, since I have seen this sort of pulsing before. After reading some papers by David Dilley, I confirmed his observation of Atlantic pulses into the Arctic every 8 to 10 years.
But the peaks coming nearly every summer in HadSST require a different picture. Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.
The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020, dropping down in 2021. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The heavy blue line shows that 2022 started warm, dropped to the bottom and stayed near the lower tracks. Note the strength of that summer’s warming pulse, in September peaking to nearly 24 Celsius, a new record for this dataset. January 2023 starts similar to 2022. (Note: No data updates for February or March so far.)
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?
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
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