Ocean Oxygen Misdirection

Warmists consistently do recycling, especially alarming stories coming back for encore media appearances.  This week it’s the suffocating ocean meme, which taps into our caring about the seas, but conflates impacts from human maritime activities with subtle temperature changes, i.e climate change (AKA emergency, chaos, crisis etc.).  Of course COP 25 is the trigger for this.  I won’t list the alarming headlines since they are little different from last time, covered in a previous post reprinted below.  Below are two typical recent quotes showing how an actual ocean concern is exploited for fossil fuel activism.

“A healthy ocean with abundant wildlife is capable of slowing the rate of climate breakdown substantially,” said Dr Monica Verbeek, the executive director of the group Seas at Risk. “To date, the most profound impact on the marine environment has come from fishing. Ending overfishing is a quick, deliverable action which will restore fish populations, create more resilient ocean ecosystems, decrease CO2 pollution and increase carbon capture, and deliver more profitable fisheries and thriving coastal communities.”

“Ending overfishing would strengthen the ocean, making it more capable of withstanding climate change and restoring marine ecosystems – and it can be done now,” explained Rashid Sumaila, professor and director of the fisheries economics research unit at the University of British Columbia. “The crisis in our fisheries and in our oceans and climate are not mutually exclusive problems to be addressed separately – it is imperative that we move forward with comprehensive solutions to address them.”

Previous post from last year

The climate scare machine is promoting again the fear of suffocating oceans. For example, an article this week by Chris Mooney in Washington Post, It’s Official, the Oceans are Losing Oxygen.

A large research synthesis, published in one of the world’s most influential scientific journals, has detected a decline in the amount of dissolved oxygen in oceans around the world — a long-predicted result of climate change that could have severe consequences for marine organisms if it continues.

The paper, published Wednesday in the journal Nature by oceanographer Sunke Schmidtko and two colleagues from the GEOMAR Helmholtz Centre for Ocean Research in Kiel, Germany, found a decline of more than 2 percent in ocean oxygen content worldwide between 1960 and 2010.

Climate change models predict the oceans will lose oxygen because of several factors. Most obvious is simply that warmer water holds less dissolved gases, including oxygen. “It’s the same reason we keep our sparkling drinks pretty cold,” Schmidtko said.

But another factor is the growing stratification of ocean waters. Oxygen enters the ocean at its surface, from the atmosphere and from the photosynthetic activity of marine microorganisms. But as that upper layer warms up, the oxygen-rich waters are less likely to mix down into cooler layers of the ocean because the warm waters are less dense and do not sink as readily.

And of course, other journalists pile on with ever more catchy headlines.

The World’s Oceans Are Losing Oxygen Due to Climate Change

How Climate Change Is Suffocating The Oceans

Overview of Oceanic Oxygen

Once again climate alarmists/activists have seized upon an actual environmental issue, but misdirect the public toward their CO2 obsession, and away from practical efforts to address a real concern. Some excerpts from scientific studies serve to put things in perspective.

k2_g_sauerstoffmischung_meer_2_e_en

2.14 > Oxygen from the atmosphere enters the near-surface waters of the ocean. This upper layer is well mixed, and is thus in chemical equilibrium with the atmosphere and rich in O2. It ends abruptly at the pyncnocline, which acts like a barrier. The oxygenrich water in the surface zone does not mix readily with deeper water layers. Oxygen essentially only enters the deeper ocean by the motion of water currents, especially with the formation of deep and intermediate waters in the polarregions. In the inner ocean, marine organisms consume oxygen. This creates a very sensitive equilibrium.

How the Ocean Breathes

Variability in oxygen and nutrients in South Pacific Antarctic Intermediate Water by J. L. Russell and A. G. Dickson

The Southern Ocean acts as the lungs of the ocean; drawing in oxygen and exchanging carbon dioxide. A quantitative understanding of the processes regulating the ventilation of the Southern Ocean today is vital to assessments of the geochemical significance of potential circulation reorganizations in the Southern Hemisphere, both during glacial-interglacial transitions and into the future.

Traditionally, the change in the concentration of oxygen along an isopycnal due to remineralization of organic material, known as the apparent oxygen utilization (AOU), has been used by physical oceanographers as a proxy for the time elapsed since the water mass was last exposed to the atmosphere. The concept of AOU requires that newly subducted water be saturated with respect to oxygen and is calculated from the difference between the measured oxygen concentration and the saturated concentration at the sample temperature.

ocean oxygen

This study has shown that the ratio of oxygen to nutrients can vary with time. Since Antarctic Intermediate Water provides a necessary component to the Pacific equatorial biological regime, this relatively high-nutrient, high-oxygen input to the Equatorial Undercurrent in the Western Pacific plays an important role in driving high rates of primary productivity on the equator, while limiting the extent of denitrifying bacteria in the eastern portion of the basin. 

Uncertain Measures of O2 Variability and Linkage to Climate Change

A conceptual model for the temporal spectrum of oceanic oxygen variability by Taka Ito and Curtis Deutsch

Changes in dissolved O2 observed across the world oceans in recent decades have been interpreted as a response of marine biogeochemistry to climate change. Little is known however about the spectrum of oceanic O2 variability. Using an idealized model, we illustrate how fluctuations in ocean circulation and biological respiration lead to low-frequency variability of thermocline oxygen.

Because the ventilation of the thermocline naturally integrates the effects of anomalous respiration and advection over decadal timescales, shortlived O2 perturbations are strongly damped, producing a red spectrum, even in a randomly varying oceanic environment. This background red spectrum of O2 suggests a new interpretation of the ubiquitous strength of decadal oxygen variability and provides a null hypothesis for the detection of climate change influence on oceanic oxygen. We find a statistically significant spectral peak at a 15–20 year timescale in the subpolar North Pacific, but the mechanisms connecting to climate variability remain uncertain.

The spectral power of oxygen variability increases from inter-annual to decadal frequencies, which can be explained using a simple conceptual model of an ocean thermocline exposed to random climate fluctuations. The theory predicts that the bias toward low-frequency variability is expected to level off as the forcing timescales become comparable to that of ocean ventilation. On time scales exceeding that of thermocline renewal, O2 variance may actually decrease due to the coupling between physical O2 supply and biological respiration [Deutsch et al., 2006], since the latter is typically limited by the physical nutrient supply.

k2_wk_sauerstoffmangel_e_en

2.15 > Marine regions with oxygen deficiencies are completely natural. These zones are mainly located in the mid-latitudes on the west sides of the continents. There is very little mixing here of the warm surface waters with the cold deep waters, so not much oxygen penetrates to greater depths. In addition, high bioproductivity and the resulting large amounts of sinking biomass here lead to strong oxygen consumption at depth, ­especially between 100 and 1000 metres.

Climate Model Projections are Confounded by Natural Variability

Natural variability and anthropogenic trends in oceanic oxygen in a coupled carbon cycle–climate model ensemble by T. L. Frolicher et al.

Internal and externally forced variability in oceanic oxygen (O2) are investigated on different spatiotemporal scales using a six-member ensemble from the National Center for Atmospheric Research CSM1.4-carbon coupled climate model. The oceanic O2 inventory is projected to decrease significantly in global warming simulations of the 20th and 21st centuries.

The anthropogenically forced O2 decrease is partly compensated by volcanic eruptions, which cause considerable interannual to decadal variability. Volcanic perturbations in oceanic oxygen concentrations gradually penetrate the ocean’s top 500 m and persist for several years. While well identified on global scales, the detection and attribution of local O2 changes to volcanic forcing is difficult because of unforced variability.

Internal climate modes can substantially contribute to surface and subsurface O2 variability. Variability in the North Atlantic and North Pacific are associated with changes in the North Atlantic Oscillation and Pacific Decadal Oscillation indexes. Simulated decadal variability compares well with observed O2 changes in the North Atlantic, suggesting that the model captures key mechanisms of late 20th century O2 variability, but the model appears to underestimate variability in the North Pacific.

Our results suggest that large interannual to decadal variations and limited data availability make the detection of human-induced O2 changes currently challenging.

The concentration of dissolved oxygen in the thermocline and the deep ocean is a particularly sensitive indicator of change in ocean transport and biology [Joos et al., 2003]. Less than a percent of the combined atmosphere and ocean O2 inventory is found in the ocean. The O2 concentration in the ocean interior reflects the balance between O2 supply from the surface through physical transport and O2 consumption by respiration of organic material.

Our modeling study suggests that over recent decades internal natural variability tends to mask simulated century-scale trends in dissolved oxygen from anthropogenic forcing in the North Atlantic and Pacific. Observed changes in oxygen are similar or even smaller in magnitude than the spread of the ensemble simulation. The observed decreasing trend in dissolved oxygen in the Indian Ocean thermocline and the boundary region between the subtropical and subpolar gyres in the North Pacific has reversed in recent years [McDonagh et al., 2005; Mecking et al., 2008], implicitly supporting this conclusion.

The presence of large-scale propagating O2 anomalies, linked with major climate modes, complicates the detection of long-term trends in oceanic O2 associated with anthropogenic climate change. In particular, we find a statistically significant link between O2 and the dominant climate modes (NAO and PDO) in the North Atlantic and North Pacific surface and subsurface waters, which are causing more than 50% of the total internal variability of O2 in these regions.

To date, the ability to detect and interpret observed changes is still limited by lack of data. Additional biogeo-chemical data from time series and profiling floats, such as the Argo array (http://www.argo.ucsd.edu) are needed to improve the detection of ocean oxygen and carbon system changes and our understanding of climate change.

The Real Issue is Ocean Dead Zones, Both Natural and Man-made

Since 1994, he and the World Resources Institute (report here) in Washington,D.C., have identified and mapped 479 dead zones around the world. That’s more than nine times as many as scientists knew about 50 years ago.

What triggers the loss of oxygen in ocean water is the explosive growth of sea life fueled by the release of too many nutrients. As they grow, these crowds can simply use up too much of the available oxygen.

Many nutrients entering the water — such as nitrogen and phosphorus — come from meeting the daily needs of some seven billion people around the world, Diaz says. Crop fertilizers, manure, sewage and exhaust spewed by cars and power plants all end up in waterways that flow into the ocean. Each can contribute to the creation of dead zones.

Ordinarily, when bacteria steal oxygen from one patch of water, more will arrive as waves and ocean currents bring new water in. Waves also can grab oxygen from the atmosphere.

Dead zones develop when this ocean mixing stops.

Rivers running into the sea dump freshwater into the salty ocean. The sun heats up the freshwater on the sea surface. This water is lighter than cold saltier water, so it floats atop it. When there are not enough storms (including hurricanes) and strong ocean currents to churn the water, the cold water can get trapped below the fresh water for long periods.

Dead zones are seasonal events. They typically last for weeks or months. Then they’ll disappear as the weather changes and ocean mixing resumes.

Solutions are Available and do not Involve CO2 Emissions

Helping dead zones recover

The Black Sea is bordered by Europe and Asia. Dead zones used to develop here that covered an area as large as Switzerland. Fertilizers running off of vast agricultural fields and animal feedlots in the former Soviet Union were a primary cause. Then, in 1989, parts of the Soviet Union began revolting. Two years later, this massive nation broke apart into 15 separate countries.

The political instability hurt farm activity. In short order, use of nitrogen and phosphorus fertilizers by area farmers declined. Almost at once, the size of the Black Sea’s dead zone shrunk dramatically. Now if a dead zone forms there it’s small, Rabalais says. Some years there is none.

Chesapeake Bay, the United State’s largest estuary, has its own dead zone. And the area affected has expanded over the past 50 years due to pollution. But since the 1980s, farmers, landowners and government agencies have worked to reduce the nutrients flowing into the bay.

Farmers now plant cover crops, such as oats or barley, that use up fertilizer that once washed away into rivers. Growers have also established land buffers to absorb nutrient runoff and to keep animal waste out of streams. People have even started to use laundry detergents made without phosphorus.

In 2011, scientists reported that these efforts had achieved some success in shrinking the size of the bay’s late-summer dead zones.

The World Resources Institute lists 55 dead zones as improving. “The bottom line is if we take a look at what is causing a dead zone and fix it, then the dead zone goes away,” says Diaz. “It’s not something that has to be permanent.”

Summary

Alarmists/activists are again confusing the public with their simplistic solution for a complex situation. And actual remedies are available, just not the agenda preferred by climatists.


Waste Management Saves the Ocean

 

SSTs NH Cooling in October

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through October 2019.
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 in the over four summer months, in August exceeding previous summer peaks in NH since 2015.  Now that warm NH pulse is reversing.  Meanwhile the SH and Tropics cooled with an upward bump in October.  Despite the rise in SH, the global anomaly changed little due to NH cooling.

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 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.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

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. (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 warming began after 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler, then tracked 2018, then rose to match previous summer pulses, before dropping down in September.

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

SSTs Cooling in September

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through September 2019.
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 in the previous three months, exceeding previous summer peaks in NH since 2015.  Now that warm NH pulse has started to reverse.  Meanwhile the SH continues to cool sharply, and the Tropics are cooling gradually.  Despite the sharp jump in NH, the global anomaly dropped in September by almost 0.1C

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, July 2019 is matching the first of these upward bumps.

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.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 warming began after 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler, then tracked 2018, then rose to match previous summer pulses, before dropping down in September.

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

August SSTs Offset NH Warming

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through August 2019.

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.

Now something exceptional is happening in NH rising almost 0.5C in the last three months, now exceeding previous summer peaks in NH since 2015.  Meanwhile the SH remains relatively cooler, and the Tropics not changing much.  Despite the sharp jump in NH, the global anomaly rose only slightly.

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, July 2019 is matching the first of these upward bumps.

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.

Note: The NH spike is unexpected since UAH ocean air tempts dropped sharply in July 2019 and remained cooler in August.  The discrpency between the two datasets is surprising since previously they were quite similar.

 

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 warming began after 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler, then tracked 2018, but has now risen to match previous summer pulses.

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

July SSTs NH Anomaly

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through June 2019.

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.

Now something exceptional is happening in NH rising 0.4C in the last two months, matching the 2015 summer peak.  Meanwhile the SH remains relatively cooler, and the Tropics not changing much.  Despite the sharp jump in NH, the global anomaly rose only slightly.

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, July 2019 is matching the first of these upward bumps.

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.

Note: The NH spike is unexpected since UAH ocean air tempts dropped sharply in July 2019.  The discrpency between the two datasets is surprising since previously they were quite similar.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 August 2018

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 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler, then tracked 2018, but has now risen to match previous summer pulses.

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

Ocean SSTs Mixed in June

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through June 2019.
A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  2018 started with slow warming after the low point of December 2017, led by steadily rising NH, which peaked in September and cooled since.  The Tropics rose steadily until November, then cooled before returning to the same level.

In 2019 all regions had been converging to reach nearly the same value in April.  Now in June, NH rose sharply, while SH dropped by the same amount while the Tropics SSTs are holding steady.  As a result the Global average anomaly is up 0.04 to an anomaly of 0.56C  All regions are about the same as 05/2017 which led to a cooling period despite NH warming at the time

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.  Also, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Hadsst1995 to 062019Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 August 2018

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 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler and is now tracking last year closely.

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.

Postscript:

In the most recent GWPF 2017 State of the Climate report, Dr. Humlum made this observation:

“It is instructive to consider the variation of the annual change rate of atmospheric CO2 together with the annual change rates for the global air temperature and global sea surface temperature (Figure 16). All three change rates clearly vary in concert, but with sea surface temperature rates leading the global temperature rates by a few months and atmospheric CO2 rates lagging 11–12 months behind the sea surface temperature rates.”

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

Ocean SSTs Cooled in May

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through May 2019.
A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  2018 started with slow warming after the low point of December 2017, led by steadily rising NH, which peaked in September and cooled since.  The Tropics rose steadily until November, and are now cooling as well.

In 2019 all regions have been converging to reach nearly the same value in April.  Now in May, NH rose very slightly, while SH dropped 0.1C and the Tropics SSTs are down 0.07C. As a result the Global average anomaly in down 0.05 to an anomaly of 0.52C  All regions are about the same as 05/2017 which led to a cooling period despite NH warming at the time

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.  Also, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 August 2018

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 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.
This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler and is now tracking last year closely.

 

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.

Postscript:

In the most recent GWPF 2017 State of the Climate report, Dr. Humlum made this observation:

“It is instructive to consider the variation of the annual change rate of atmospheric CO2 together with the annual change rates for the global air temperature and global sea surface temperature (Figure 16). All three change rates clearly vary in concert, but with sea surface temperature rates leading the global temperature rates by a few months and atmospheric CO2 rates lagging 11–12 months behind the sea surface temperature rates.”

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

 

April Ocean SSTs Hold Steady

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through April 2019. Hadley Centre did some technical upgrades and only now published results for March and April

 

A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  2018 started with slow warming after the low point of December 2017, led by steadily rising NH, which peaked in September and cooled since.  The Tropics rose steadily until November, and are now cooling as well.

In 2019 we can see that NH is flat, the Tropics are up and down, and SH gently rising.  As a result, all regions are converging on the Global average anomaly of 0.57C  All regions are about the same as 2017 and 2015, but much cooler than 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.  Also, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 August 2018

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 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler than January 2018,  and in February matched the low SST of the previous year.

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 will likely cool in coming months.  Once again, ENSO will probably determine the outcome.

Postscript:

In the most recent GWPF 2017 State of the Climate report, Dr. Humlum made this observation:

“It is instructive to consider the variation of the annual change rate of atmospheric CO2 together with the annual change rates for the global air temperature and global sea surface temperature (Figure 16). All three change rates clearly vary in concert, but with sea surface temperature rates leading the global temperature rates by a few months and atmospheric CO2 rates lagging 11–12 months behind the sea surface temperature rates.”

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

 

De Nada Ocean SSTs in February

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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through February 2019. For some reason, it took almost a whole month to publish the updated dataset.

A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  2018 started with slow warming after the low point of December 2017, led by steadily rising NH, which peaked in September and cooled since.  The Tropics rose steadily until November, and are now cooling as well.  With a little warming in SH, the Global anomaly is virtually unchanged last month.

All regions are about the same as 02/2017 and 02/2015, but much cooler than 02/2016.  The February Global anomaly is 0.09 lower than 2016;  NH is 0.06 lower, SH is 0.09 lower and the Tropics  are down 0.43, or 50% from 02/2016. The rise in the Tropics had suggested a possible El Nino, but is now cooling down and better described as De Nada.

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.  Also, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 August 2018

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 1992 up to 1998, with a series of matching years since. Because the N. Atlantic has partnered with the Pacific ENSO recently, let’s take a closer look at some AMO years in the last 2 decades.

This graph shows monthly AMO temps for some important years. The Peak years were 1998, 2010 and 2016, with the latter emphasized as the most recent. The other years show lesser warming, with 2007 emphasized as the coolest in the last 20 years. Note the red 2018 line is at the bottom of all these tracks. The short black line shows that 2019 began slightly cooler than January 2018,  and in February matched the low SST of the previous year.

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 will likely cool in coming months.  Once again, ENSO will probably determine the outcome.

Postscript:

In the most recent GWPF 2017 State of the Climate report, Dr. Humlum made this observation:

“It is instructive to consider the variation of the annual change rate of atmospheric CO2 together with the annual change rates for the global air temperature and global sea surface temperature (Figure 16). All three change rates clearly vary in concert, but with sea surface temperature rates leading the global temperature rates by a few months and atmospheric CO2 rates lagging 11–12 months behind the sea surface temperature rates.”

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

 

January Ocean SSTs Cooling

volvo_globpopThe 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 chart below shows SST monthly anomalies as reported in HadSST3 starting in 2015 through January 2019.

Hadsst012019

A global cooling pattern is seen clearly in the Tropics since its peak in 2016, joined by NH and SH cycling downward since 2016.  2018 started with slow warming after the low point of December 2017, led by steadily rising NH, which peaked in September and cooled the last 4 months.  The Tropics rose steadily until November, and are now cooling as well.  With little change in SH, the Global anomaly cooled further.

All regions are slightly warmer than 01/2015, but much cooler than 01/2016.  The January Global anomaly is 0.2 lower than 2016;  NH is 0.22 lower, SH is 0.16 lower and the Tropics  are down 0.52 from 01/2016. The rise in the Tropics had suggested a possible El Nino, but is now cooling down.

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.  Also, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.

The annual SSTs for the last five years are as follows:

Annual SSTs Global NH SH  Tropics
2014 0.477 0.617 0.335 0.451
2015 0.592 0.737 0.425 0.717
2016 0.613 0.746 0.486 0.708
2017 0.505 0.650 0.385 0.424
2018 0.480 0.620 0.362 0.369

2018 annual average SSTs across the regions are close to 2014, slightly higher in SH and much lower in the Tropics.  The SST rise from the global ocean was remarkable, peaking in 2016, higher than 2011 by 0.32C.

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.

Hadsst1995 to 012019

Open image in new tab to enlarge.

1995 is a reasonable 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.  Note also that starting in 2014 SH plays a moderating role, offsetting the NH warming pulses. (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 August 2018

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 1992 up to 1998, with a series of matching years since. 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-122018

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. Most recently December 2018 is 0.4C lower than December 2016, and is the coolest December since 2000.

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 will likely cool in coming months.  Once again, ENSO will probably determine the outcome.

Postscript:

In the most recent GWPF 2017 State of the Climate report, Dr. Humlum made this observation:

“It is instructive to consider the variation of the annual change rate of atmospheric CO2 together with the annual change rates for the global air temperature and global sea surface temperature (Figure 16). All three change rates clearly vary in concert, but with sea surface temperature rates leading the global temperature rates by a few months and atmospheric CO2 rates lagging 11–12 months behind the sea surface temperature rates.”

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