Climate Science

Still No Global Warming June 2021

Posted on by Ron Clutz

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

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

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

 

gmt-warming-events

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

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

mc_wh_gas_web20210423124932

See Also Worst Threat: Greenhouse Gas or Quiet Sun?

June Update Ocean and Land Air Temps Continue Down

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With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with chilly temperatures setting in all regions.  Last month despite some warming in NH, temps in the Tropics and SH dropped sharply.

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

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

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

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

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

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

UAH Oceans 202106

Note 2020 was warmed mainly by a spike in February in all regions, and secondarily by an October spike in NH alone. End of 2020 November and December ocean temps plummeted in NH and the Tropics. In January SH dropped sharply, pulling the Global anomaly down despite an upward bump in NH. An additional drop in March has SH matching the coldest in this period. March drops in the Tropics and NH made those regions at their coldest since 01/2015.  In June 2021 despite an uptick in NH, the Global anomaly dropped back down due to a record low in SH along with a Tropical cooling.

Land Air Temperatures Tracking Downward in Seesaw Pattern

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

UAH Land 202106aHere we have fresh evidence of the greater volatility of the Land temperatures, along with an extraordinary departure by SH land.  Land temps are dominated by NH with a 2020 spike in February, followed by cooling down to July.  Then NH land warmed with a second spike in November.  Note the mid-year spikes in SH winter months.  In December all of that was wiped out.

Then January 2021 showed a sharp drop in SH, but a rise in NH more than offset, pulling the Global anomaly upward.  In February NH and the Tropics cooled further, pulling down the Global anomaly, despite slight SH land warming.  March continued to show all regions roughly comparable to early 2015, prior to the 2016 El Nino.  Then in April NH land dropped sharply along with the Tropics, bringing Global Land anomaly down by nearly 0.2C.  Now a remarkable divergence with NH rising in May and June, while SH drops sharply to a new low, along with Tropical cooling. With NH having most of the land mass, the Global land anomaly ticked upward.

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202106

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

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

June 2021 N. Atlantic Finally Cooling?

Posted on by Ron Clutz

RAPID Array measuring North Atlantic SSTs.

For the last few years, observers have been speculating about when the North Atlantic will start the next phase shift from warm to cold.

Source: Energy and Education Canada

An example is this report in May 2015 The Atlantic is entering a cool phase that will change the world’s weather by Gerald McCarthy and Evan Haigh of the RAPID Atlantic monitoring project. Excerpts in italics with my bolds.

This is known as the Atlantic Multidecadal Oscillation (AMO), and the transition between its positive and negative phases can be very rapid. For example, Atlantic temperatures declined by 0.1ºC per decade from the 1940s to the 1970s. By comparison, global surface warming is estimated at 0.5ºC per century – a rate twice as slow.

In many parts of the world, the AMO has been linked with decade-long temperature and rainfall trends. Certainly – and perhaps obviously – the mean temperature of islands downwind of the Atlantic such as Britain and Ireland show almost exactly the same temperature fluctuations as the AMO.

Atlantic oscillations are associated with the frequency of hurricanes and droughts. When the AMO is in the warm phase, there are more hurricanes in the Atlantic and droughts in the US Midwest tend to be more frequent and prolonged. In the Pacific Northwest, a positive AMO leads to more rainfall.

A negative AMO (cooler ocean) is associated with reduced rainfall in the vulnerable Sahel region of Africa. The prolonged negative AMO was associated with the infamous Ethiopian famine in the mid-1980s. In the UK it tends to mean reduced summer rainfall – the mythical “barbeque summer”.Our results show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres – the intergyre region. This a major influence on the wind patterns and the heat transferred between the atmosphere and ocean.

The observations that we do have of the Atlantic overturning circulation over the past ten years show that it is declining. As a result, we expect the AMO is moving to a negative (colder surface waters) phase. This is consistent with observations of temperature in the North Atlantic.

Cold “blobs” in North Atlantic have been reported, but they are usually a winter phenomena. For example in April 2016, the sst anomalies looked like this

But by September, the picture changed to this

And we know from Kaplan AMO dataset, that 2016 summer SSTs were right up there with 1998 and 2010 as the highest recorded.

As the graph above suggests, this body of water is also important for tropical cyclones, since warmer water provides more energy.  But those are annual averages, and I am interested in the summer pulses of warm water into the Arctic. As I have noted in my monthly HadSST3 reports, most summers since 2003 there have been warm pulses in the north atlantic.

AMO June 2021
The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N.  The graph shows warming began after 1970s up to 1998, with a series of matching years since.  Since 2016, June SSTs have backed down despite an upward bump in 2020. Because McCarthy refers to hints of cooling to come in the N. Atlantic, let’s take a closer look at some AMO years in the last 2 decades.

AMO decade 062021

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.  Note that 2020 tracked the 2016 highs, even exceeding those temps the first 4 months.  Now 2021 is starting tracking the much cooler 2018.

With all the talk of AMOC slowing down and a phase shift in the North Atlantic, we await SST measurements for July, August and September to confirm if cooling is starting to set in.

July 2021 Heat Records Silly Season Again

Posted on by Ron Clutz

Photo illustration by Slate. Photos by Thinkstock.

A glance at the news aggregator shows the silly season is in full swing.  A partial listing of headlines today proclaiming the hottest whatever.

  • Last Month Was the Hottest June in North America in Recent Recorded History TIME
  • Global Warming Is Increasing the Likelihood of Frost Damage in Vineyards Martha Stewart
  • Heat records smashed in Moscow and Helsinki CGTN
  • Alberta glacial melt about 3 times higher than average during heat wave: expert The Weather Network
  • US and Canada heatwave ‘impossible’ without climate change, analysis shows Sky News
  • Heat waves caused warmest June ever in North America The Independent
  • Glacial melt: the European Alps New Age
  • The North American heatwave shows we need to know how climate change will change our weather Cyprus Mail
  • Global evidence links rise in extreme precipitation to human-driven climate change Phys.org
  • Drought-Stricken Western Districts Plan New Ways to Store Water Bloomberg
  • Amid record heat, Equilibrium Capital raises $1 billion for second greenhouse fund ImpactAlpha
  • Last Month Was Hottest June on Record in North America MTV Lebanon
  • Superior National Forest could provide refuge to wildlife as the climate warms Yale Climate Connections
  • How climate change is exacerbating record heatwaves The Telegraph
  • Lapland records hottest day for more than a century as heatwave grips region Sky News
  • Heatwave stokes North America’s warmest June on record The Raw Story

Time for some Clear Thinking about Heat Records (Previous Post)

Here is an analysis using critical intelligence to interpret media reports about temperature records this summer. Daniel Engber writes in Slate Crazy From the Heat

The subtitle is Climate change is real. Record-high temperatures everywhere are fake.  As we shall see from the excerpts below, The first sentence is a statement of faith, since as Engber demonstrates, the notion does not follow from the temperature evidence. Excerpts in italics with my bolds.

It’s been really, really hot this summer. How hot? Last Friday, the Washington Post put out a series of maps and charts to illustrate the “record-crushing heat.” All-time temperature highs have been measured in “scores of locations on every continent north of the equator,” the article said, while the lower 48 states endured the hottest-ever stretch of temperatures from May until July.

These were not the only records to be set in 2018. Historic heat waves have been crashing all around the world, with records getting shattered in Japan, broken on the eastern coast of Canada, smashed in California, and rewritten in the Upper Midwest. A city in Algeria suffered through the highest high temperature ever recorded in Africa. A village in Oman set a new world record for the highest-ever low temperature. At the end of July, the New York Times ran a feature on how this year’s “record heat wreaked havoc on four continents.” USA Today reported that more than 1,900 heat records had been tied or beaten in just the last few days of May.

While the odds that any given record will be broken may be very, very small, the total number of potential records is mind-blowingly enormous.

There were lots of other records, too, lots and lots and lots—but I think it’s best for me to stop right here. In fact, I think it’s best for all of us to stop reporting on these misleading, imbecilic stats. “Record-setting heat,” as it’s presented in news reports, isn’t really scientific, and it’s almost always insignificant. And yet, every summer seems to bring a flood of new superlatives that pump us full of dread about the changing climate. We’d all be better off without this phony grandiosity, which makes it seem like every hot and humid August is unparalleled in human history. It’s not. Reports that tell us otherwise should be banished from the news.

It’s true the Earth is warming overall, and the record-breaking heat that matters most—the kind we’d be crazy to ignore—is measured on a global scale. The average temperature across the surface of the planet in 2017 was 58.51 degrees, one-and-a-half degrees above the mean for the 20th century. These records matter: 17 of the 18 hottest years on planet Earth have occurred since 2001, and the four hottest-ever years were 2014, 2015, 2016, and 2017. It also matters that this changing climate will result in huge numbers of heat-related deaths. Please pay attention to these terrifying and important facts. Please ignore every other story about record-breaking heat.

You’ll often hear that these two phenomena are related, that local heat records reflect—and therefore illustrate—the global trend. Writing in Slate this past July, Irineo Cabreros explained that climate change does indeed increase the odds of extreme events, making record-breaking heat more likely. News reports often make this point, linking probabilities of rare events to the broader warming pattern. “Scientists say there’s little doubt that the ratcheting up of global greenhouse gases makes heat waves more frequent and more intense,” noted the Times in its piece on record temperatures in Algeria, Hong Kong, Pakistan, and Norway.

Yet this lesson is subtler than it seems. The rash of “record-crushing heat” reports suggest we’re living through a spreading plague of new extremes—that the rate at which we’re reaching highest highs and highest lows is speeding up. When the Post reports that heat records have been set “at scores of locations on every continent,” it makes us think this is unexpected. It suggests that as the Earth gets ever warmer, and the weather less predictable, such records will be broken far more often than they ever have before.

But that’s just not the case. In 2009, climatologist Gerald Meehl and several colleagues published an analysis of records drawn from roughly 2,000 weather stations in the U.S. between 1950 and 2006. There were tens of millions of data points in all—temperature highs and lows from every station, taken every day for more than a half-century. Meehl searched these numbers for the record-setting values—i.e., the days on which a given weather station saw its highest-ever high or lowest-ever low up until that point. When he plotted these by year, they fell along a downward-curving line. Around 50,000 new heat records were being set every year during the 1960s; then that number dropped to roughly 20,000 in the 1980s, and to 15,000 by the turn of the millennium.

From Meehl et al 2009.

This shouldn’t be surprising. As a rule, weather records will be set less frequently as time goes by. The first measurement of temperature that’s ever taken at a given weather station will be its highest (and lowest) of all time, by definition. There’s a good chance that the same station’s reading on Day 2 will be a record, too, since it only needs to beat the temperature recorded on Day 1. But as the weeks and months go by, this record-setting contest gets increasingly competitive: Each new daily temperature must now outdo every single one that came before. If the weather were completely random, we might peg the chances of a record being set at any time as 1/n, where n is the number of days recorded to that point. In other words, one week into your record-keeping, you’d have a 1 in 7 chance of landing on an all-time high. On the 100th day, your odds would have dropped to 1 percent. After 56 years, your chances would be very, very slim.

The weather isn’t random, though; we know it’s warming overall, from one decade to the next. That’s what Meehl et al. were looking at: They figured that a changing climate would tweak those probabilities, goosing the rate of record-breaking highs and tamping down the rate of record-breaking lows. This wouldn’t change the fundamental fact that records get broken much less often as the years go by. (Even though the world is warming, you’d still expect fewer heat records to be set in 2000 than in 1965.) Still, one might guess that climate change would affect the rate, so that more heat records would be set than we’d otherwise expect.

That’s not what Meehl found. Between 1950 and 2006, the rate of record-breaking heat seemed unaffected by large-scale changes to the climate: The number of new records set every year went down from one decade to the next, at a rate that matched up pretty well with what you’d see if the odds were always 1/n. The study did find something more important, though: Record-breaking lows were showing up much less often than expected. From one decade to the next, fewer records of any kind were being set, but the ratio of record lows to record highs was getting smaller over time. By the 2000s, it had fallen to about 0.5, meaning that the U.S. was seeing half as many record-breaking lows as record-breaking highs. (Meehl has since extended this analysis using data going back to 1930 and up through 2015. The results came out the same.)

What does all this mean? On one hand, it’s very good evidence that climate change has tweaked the odds for record-breaking weather, at least when it comes to record lows. (Other studies have come to the same conclusion.) On the other hand, it tells us that in the U.S., at least, we’re not hitting record highs more often than we were before, and that the rate isn’t higher than what you’d expect if there weren’t any global warming. In fact, just the opposite is true: As one might expect, heat records are getting broken less often over time, and it’s likely there will be fewer during the 2010s than at any point since people started keeping track.

This may be hard to fathom, given how much coverage has been devoted to the latest bouts of record-setting heat. These extreme events are more unusual, in absolute terms, than they’ve ever been before, yet they’re always in the news. How could that be happening?

While the odds that any given record will be broken may be very, very small, the total number of potential records that could be broken—and then reported in the newspaper—is mind-blowingly enormous. To get a sense of how big this number really is, consider that the National Oceanic and Atmospheric Administration keeps a database of daily records from every U.S. weather station with at least 30 years of data, and that its website lets you search for how many all-time records have been set in any given stretch of time. For instance, the database indicates that during the seven-day period ending on Aug. 17—the date when the Washington Post published its series of “record-crushing heat” infographics—154 heat records were broken.

 

That may sound like a lot—154 record-high temperatures in the span of just one week. But the NOAA website also indicates how many potential records could have been achieved during that time: 18,953. In actuality, less than one percent of these were broken. You can also pull data on daily maximum temperatures for an entire month: I tried that with August 2017, and then again for months of August at 10-year intervals going back to the 1950s. Each time the query returned at least about 130,000 potential records, of which one or two thousand seemed to be getting broken every year. (There was no apparent trend toward more records being broken over time.)

Now let’s say there are 130,000 high-temperature records to be broken every month in the U.S. That’s only half the pool of heat-related records, since the database also lets you search for all-time highest low temperatures. You can also check whether any given highest high or highest low happens to be a record for the entire month in that location, or whether it’s a record when compared across all the weather stations everywhere on that particular day.

Add all of these together and the pool of potential heat records tracked by NOAA appears to number in the millions annually, of which tens of thousands may be broken. Even this vastly underestimates the number of potential records available for media concern. As they’re reported in the news, all-time weather records aren’t limited to just the highest highs or highest lows for a given day in one location. Take, for example, the first heat record mentioned in this column, reported in the Post: The U.S. has just endured the hottest May, June, and July of all time. The existence of that record presupposes many others: What about the hottest April, May and June, or the hottest March, April, and May? What about all the other ways that one might subdivide the calendar?

Geography provides another endless well of flexibility. Remember that the all-time record for the hottest May, June, and July applied only to the lower 48 states. Might a different set of records have been broken if we’d considered Hawaii and Alaska? And what about the records spanning smaller portions of the country, like the Midwest, or the Upper Midwest, or just the state of Minnesota, or just the Twin Cities? And what about the all-time records overseas, describing unprecedented heat in other countries or on other continents?

Even if we did limit ourselves to weather records from a single place measured over a common timescale, it would still be possible to parse out record-breaking heat in a thousand different ways. News reports give separate records, as we’ve seen, for the highest daily high and the highest daily low, but they also tell us when we’ve hit the highest average temperature over several days or several weeks or several months. The Post describes a recent record-breaking streak of days in San Diego with highs of at least 83 degrees. (You’ll find stories touting streaks of daily highs above almost any arbitrary threshold: 90 degrees, 77 degrees, 60 degrees, et cetera.) Records also needn’t focus on the temperature at all: There’s been lots of news in recent weeks about the fact that the U.K. has just endured its driest-ever early summer.

“Record-breaking” summer weather, then, can apply to pretty much any geographical location, over pretty much any span of time. It doesn’t even have to be a record—there’s an endless stream of stories on “near-record heat” in one place or another, or the “fifth-hottest” whatever to happen in wherever, or the fact that it’s been “one of the hottest” yadda-yaddas that yadda-yadda has ever seen. In the most perverse, insane extension of this genre, news outlets sometimes even highlight when a given record isn’t being set.

Loose reports of “record-breaking heat” only serve to puff up muggy weather and make it seem important. (The sham inflations of the wind chill factor do the same for winter months.) So don’t be fooled or flattered by this record-setting hype. Your summer misery is nothing special.

Summary

This article helps people not to confuse weather events with climate.  My disappointment is with the phrase, “Climate Change is Real,” since it is subject to misdirection.  Engber uses that phrase referring to rising average world temperatures, without explaining that such estimates are computer processed reconstructions since the earth has no “average temperature.”  More importantly the undefined “climate change” is a blank slate to which a number of meanings can be attached.

Some take it to mean: It is real that rising CO2 concentrations cause rising global warming.  Yet that is not supported by temperature records.
Others think it means: It is real that using fossil fuels causes global warming.  This too lacks persuasive evidence.
WFFC and Hadcrut 2018Over the last five decades the increase in fossil fuel consumption is dramatic and monotonic, steadily increasing by 234% from 3.5B to 11.7B oil equivalent tons. Meanwhile the GMT record from Hadcrut shows multiple ups and downs with an accumulated rise of 0.74C over 53 years, 5% of the starting value.

Others know that Global Mean Temperature is a slippery calculation subject to the selection of stations.

Graph showing the correlation between Global Mean Temperature (Average T) and the number of stations included in the global database. Source: Ross McKitrick, U of Guelph

Global warming estimates combine results from adjusted records.
Conclusion

The pattern of high and low records discussed above is consistent with natural variability rather than rising CO2 or fossil fuel consumption. Those of us not alarmed about the reported warming understand that “climate change” is something nature does all the time, and that the future is likely to include periods both cooler and warmer than now.

Background Reading:

The Climate Story (Illustrated)

2020 Update: Fossil Fuels ≠ Global Warming

Man Made Warming from Adjusting Data

What is Global Temperature? Is it warming or cooling?

NOAA US temp 2019 2021

Tropics Lead Ocean Temps Return to Mean

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;
  • A major El Nino was the dominant climate feature in recent years.

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

The Current Context

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

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

Hadsst052021

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

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

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

And as before, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.  Note the May warming was strongest in the Tropics, though the anomaly is quite cool compared to 2016.

A longer view of SSTs

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

Hadsst1995to 0520211995 is a reasonable (ENSO neutral) starting point prior to the first El Nino.  The sharp Tropical rise peaking in 1998 is dominant in the record, starting Jan. ’97 to pull up SSTs uniformly before returning to the same level Jan. ’99.  For the next 2 years, the Tropics stayed down, and the world’s oceans held steady around 0.2C above 1961 to 1990 average.

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

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

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

The highest summer NH peaks came in 2019 and 2020, only this time the Tropics and SH are 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, and now all regions are rising to bring the global anomaly above the mean since 1995.

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

But the peaks coming nearly every summer in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.
AMO Aug and Dec 2021The AMO Index is from from Kaplan SST v2, the unaltered and not detrended dataset. By definition, the data are monthly average SSTs interpolated to a 5×5 grid over the North Atlantic basically 0 to 70N. The graph shows August warming began after 1992 up to 1998, with a series of matching years since, including 2020.  Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
AMO decade 052021This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The black line shows that 2020 began slightly warm, then set records for 3 months. then dropped below 2016 and 2017, peaked in August ending below 2016. Now in 2021, AMO is tracking the coldest years.

Summary

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

Footnote: Why Rely on HadSST3

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

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

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

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

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

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

 

 

Solar Cycles Chaotic

Posted on by Ron Clutz

screenshot-2020-02-25-at-08.38.39-6a4eb07-e1582620697162

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

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

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

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

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

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

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

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

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

Planets as a metronome

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

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

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

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

solar-cycle-25-nasa-full

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

Background from previous post Climate Chaos

Foucault’s pendulum in the Panthéon, Paris

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

The Pendulum is Settled Science

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

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

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

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

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

What About the Double Pendulum?

Trajectories of a double pendulum

Just today a comment by tom0mason at alerted me to the science demonstrated by the double compound pendulum, that is, a second pendulum attached to the ball of the first one. It consists entirely of two simple objects functioning as pendulums, only now each is influenced by the behavior of the other.

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

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

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

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

And What about the Climate?

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

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

What happens in a complex system of 10 double pendulums?

Summary

To quote the IPCC:

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

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

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

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

Update May 2

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

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

Flow Diagram for Climate Modeling, Showing Feedback Loops

May 2021 Slight Warming of Land and Sea

Posted on by Ron Clutz

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With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast the cooling has set in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated after all regions headed down, now reversing slightly.

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

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

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

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

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

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

UAH Oceans 202105

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

Land Air Temperatures Tracking Downward in Seesaw Pattern

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

UAH Land 202105

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

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202105

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

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

April Oceans Temper Cold 2021 Start

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;
  • A major El Nino was the dominant climate feature in recent years.

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

The Current Context

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

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

Hadsst4 202104

 

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

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

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

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

A longer view of SSTs

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

Hadsst1995to 042021

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

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

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

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

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

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

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

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

AMO decade 042021

 

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

Summary

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

Footnote: Why Rely on HadSST3

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

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

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

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

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

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

Adios, Global Warming

Posted on by Ron Clutz

a62edf0f39de560a219b7262163b0d45

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

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 ~55 ppm, a 15% increase.

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

gmt-warming-events

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

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

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?

April Update Ocean and Land Air Temps Continue Down

banner-blog

With apologies to Paul Revere, this post is on the lookout for cooler weather with an eye on both the Land and the Sea.  While you will hear a lot about 2020 temperatures matching 2016 as the highest ever, that spin ignores how fast is the cooling setting in.  The UAH data analyzed below shows that warming from the last El Nino is now fully dissipated with chilly temperatures setting in all regions.  Last month it was the ocean cooling off dramatically.

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

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

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

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

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

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

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

 

Land Air Temperatures Tracking Downward in Seesaw Pattern

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

UAH Land 202104

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

The Bigger Picture UAH Global Since 1995

UAH Global 1995to202104

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

TLTs include mixing above the oceans and probably some influence from nearby more volatile land temps.  Clearly NH and Global land temps have been dropping in a seesaw pattern, more than 1C lower than the 2016 peak.  Since the ocean has 1000 times the heat capacity as the atmosphere, that cooling is a significant driving force.  TLT measures started the recent cooling later than SSTs from HadSST3, but are now showing the same pattern.  It seems obvious that despite the three El Ninos, their warming has not persisted, and without them it would probably have cooled since 1995.  Of course, the future has not yet been written.

 

Two Views of Oceans SST End of April 2021

Posted on by Ron Clutz

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

Overview

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

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

The Current Context

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

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

Hadsst4 202103

 

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

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

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

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

ERSST202103rev

 

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

A longer view of SSTs

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

ERSST95to2103rev

 

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

Hadsst4 1995to 202103

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

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

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

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

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

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

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

AMO decade 032021

 

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

Summary

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

Footnote: Why Rely on HadSST3

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

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

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

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

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

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean

 

Oceans SST Update April 2021

Posted on by Ron Clutz

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

Overview

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

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

The Current Context

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

ERSST202103

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

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

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

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

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

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

A longer view of SSTs

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

ERSST95to0321

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

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

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

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

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

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

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

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

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

AMO decade 022021

 

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

Summary

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

Footnote: Why Rely on HadSST3

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

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

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

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

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

USS Pearl Harbor deploys Global Drifter Buoys in Pacific Ocean