Scare of the Day: Ocean Heat Content

What is Argo? Argo is a global array of 3,800 free-drifting profiling floats that measures thetemperature and salinity of the upper 2000 m of the ocean. This allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection. Positions of the floats that have delivered data within the last 30 days :

Scientists deploy an Argo float. For over a decade, more than 3000 floats have provided near-global data coverage for the upper 2000 m of the ocean.

Here is a sample of yesterday’s coordinated reports from CCN- Climate Crisis Network captured by my news aggregator, listed by the most recent first. Note the worldwide scope and editorial poetic license on the titles.

Ocean warming accelerating to record temperatures, scientists warn Engineering and Technology Magazine
Scalding seas? Oceans boil to hottest temp on record USA Today EU
World’s oceans heating up at quickening pace: study Egypt Independent
Ocean warming ‘accelerating’ The London Economic
Oceans warming faster than we thought: Study AniNews.in
Ocean temperatures rising faster than thought in ‘delayed response’ to global warming, scientists say The Japan Times
Oceans warming much faster than previously thought: Study The Hindu Business Line
The Oceans Are Warming Faster Than We Thought, a New Study Says TIME
Oceans Warming Even Faster Than Previously Thought Eurasia Review
The Ocean Is Warming Much Faster Than We Thought, According To A New Study BuzzFeed
Pacific: New research proves ocean warming is accelerating ABC Online – Radio Australia
We’re Boiling the Ocean Faster Than We Thought New York Magazine
Oceans warming faster than expected SBS
Ocean temperatures are rising far faster than previously thought, report says TVNZ
Ocean Temps Rising Faster Than Scientists Thought: Report HuffPost (US)
World’s oceans are heating up at a quickening pace Bangkok Post
The Warming of the World’s Oceans Is Set to Increase Dramatically Over the Next 60 Years Pacific Standard
New Climate Change Report Says Ocean Warming Is Far Worse Than Expected Fortune
Oceans Are Warming Faster Than Expected, Research Says Geek.com
World’s oceans are heating up at a quickening pace: study AFP
Oceans Warming Faster Than Predicted, Scientists Say gCaptain

So the message to the world is very clear: Ocean Heat Content is rising out of control, Be Very Afraid!
The trigger for all of this concern comes from this paper How fast are the oceans warming? by Lijing Cheng, John Abraham, Zeke Hausfather, Kevin E. Trenberth. Science 11 Jan 2019 Excerpts from paper in italics with my bolds.

Climate change from human activities mainly results from the energy imbalance in Earth’s climate system caused by rising concentrations of heat-trapping gases. About 93% of the energy imbalance accumulates in the ocean as increased ocean heat content (OHC). The ocean record of this imbalance is much less affected by internal variability and is thus better suited for detecting and attributing human influences (1) than more commonly used surface temperature records. Recent observation-based estimates show rapid warming of Earth’s oceans over the past few decades (see the figure) (1, 2). This warming has contributed to increases in rainfall intensity, rising sea levels, the destruction of coral reefs, declining ocean oxygen levels, and declines in ice sheets; glaciers; and ice caps in the polar regions (3, 4). Recent estimates of observed warming resemble those seen in models, indicating that models reliably project changes in OHC.

The Intergovernmental Panel on Climate Change’s Fifth Assessment Report (AR5), published in 2013 (4), featured five different time series of historical global OHC for the upper 700 m of the ocean. These time series are based on different choices for data processing (see the supplementary materials). Interpretation of the results is complicated by the fact that there are large differences among the series. Furthermore, the OHC changes that they showed were smaller than those projected by most climate models in the Coupled Model Intercomparison Project 5 (CMIP5) (5) over the period from 1971 to 2010 (see the figure).

Since then, the research community has made substantial progress in improving long-term OHC records and has identified several sources of uncertainty in prior measurements and analyses (2, 6–8). In AR5, all OHC time series were corrected for biases in expendable bathythermograph (XBT) data that had not been accounted for in the previous report (AR4). But these correction methods relied on very different assumptions of the error sources and led to substantial differences among correction schemes. Since AR5, the main factors influencing the errors have been identified (2), helping to better account for systematic errors in XBT data and their analysis.

Multiple lines of evidence from four independent groups thus now suggest a stronger observed OHC warming. Although climate model results (see the supplementary materials) have been criticized during debates about a “hiatus” or “slowdown” of global mean surface temperature, it is increasingly clear that the pause in surface warming was at least in part due to the redistribution of heat within the climate system from Earth surface into the ocean interiors (13). The recent OHC warming estimates (2, 6, 10, 11) are quite similar to the average of CMIP5 models, both for the late 1950s until present and during the 1971–2010 period highlighted in AR5 (see the figure). The ensemble average of the models has a linear ocean warming trend of 0.39 ± 0.07 W m−2 for the upper 2000 m from 1971–2010 compared with recent observations ranging from 0.36 to 0.39 W m−2 (see the figure).

MISSION ACCOMPLISHED: “The recent OHC warming estimates are quite similar to the average of CMIP5 models.”

What They are Not Telling You

The Sea Surface Temperature (SST) record is a mature dataset, not without issues from changing measurement technologies, but providing a lengthy set of observations making up 71% of the surface temperature history.  Sussing out temperatures at various depths in the ocean is a whole nother kettle of fish.

The Ocean Heat Content data is sparse, both in time and space.

The Ocean is vast, 360 million square kilometers with an average depth of 3700 meters, and we have 3900 Argo floats operating for 10 years. In addition we have some sensors arrayed at depths in the North Atlantic. As the text above admits, there are lots of holes in the data, and only a short history of the recently available reliable data. Other publications by some of the same authors admit: Large discrepancies are found in the percentage of basinal ocean heating related to the global ocean, with the largest differences in the Pacific and Southern Ocean. Meanwhile, we find a large discrepancy of ocean heat storage in different layers, especially within 300–700 m in the Pacific and Southern Oceans. Source: Consensuses and discrepancies of basin-scale ocean heat content changes in different ocean analyses, Gongjie Wang, Lijing Cheng, John Abraham.

Modelers Make OHC Reconstructions by Adding Guesstimates to Observations

Again climate science alarms are raised after “reanalysis” of the data. No one should be surprised that after computer manipulations and data processing, the “reanalyzed” data has changed and now favors warming and confirms the climate models. The Argo data record by itself is too short to make any such claim. In previous studies, scientists were more circumspect and refrained from “jumping the shark.” Apparently, with the Paris Accord on the ropes in 2019, caution and nuance has been thrown to the wind, as witnessed by the recent SR15 horror show, and now this.

Methodological Problems Bedevil These Reconstructions

One of the studies cited in support of revising OHC upward is the study Quantification of ocean heat uptake from changes in atmospheric O2 and CO2 composition, L. Resplandy et al. Published in Nature 31 October 2018.  From the Media Release:

The world’s oceans have absorbed far more heat than we realized, shortening our timeline to stop the causes of global warming, and foreboding some of the worst case scenarios put forth by climate experts, according to new findings.

A novel study by researchers from Scripps Institution of Oceanography at the University of California San Diego and Princeton University, published on Wednesday in Nature, implies that officials have underestimated the amount of heat retained by Earth’s oceans.

Between 1991 and 2016, oceans warmed an average 60 percent more than estimates by the Intergovernmental Panel on Climate Change (IPCC) originally calculated, the study claims. That amount equalled 13 zettajoules, or eight times the world’s annual energy consumption.

Something didn’t look right to climate statistician Nic Lewis so he deconstructed the study, finding several methodological mistakes along the way. He explained and communicated with the authors in a series of 4 posts at Climate Etc. Nov. 6 through 23, 2018.

Nic Lewis, Nov. 6 (here):

The findings of the Resplandy et al paper were peer reviewed and published in the world’s premier scientific journal and were given wide coverage in the English-speaking media. Despite this, a quick review of the first page of the paper was sufficient to raise doubts as to the accuracy of its results. Just a few hours of analysis and calculations, based only on published information, was sufficient to uncover apparently serious (but surely inadvertent) errors in the underlying calculations.

Moreover, even if the paper’s results had been correct, they would not have justified its findings regarding an increase to 2.0°C in the lower bound of the equilibrium climate sensitivity range and a 25% reduction in the carbon budget for 2°C global warming.

Because of the wide dissemination of the paper’s results, it is extremely important that these errors are acknowledged by the authors without delay and then corrected.

Authors Respond:

On November 14, 2018 this paper’s authors announced key errors to the two week-old study that made claims about the amount of heat that Earth’s oceans have absorbed. The errors stem from “incorrectly treating systematic errors in the O2 measurements and the use of a constant land O2:C exchange ratio of 1.1,” co-author Ralph Keeling said in an update from Scripps Institution of Oceanography, which is affiliated with the study. More simply, the team’s findings are too uncertain to conclusively support their statement that Earth’s oceans have absorbed 60 percent more heat than previously thought. Keeling claims the errors “do not invalidate the study’s methodology or the new insights into ocean biogeochemistry on which it is based.”

Subsequent posts by Lewis found other differences between the stated method and the analysis actually applied, adding to the uncertainty of the study and its finding. Lewis is not done yet, and the paper has not been reissued. Unfortunately, it has not been retracted and is still cited in reference to unsupported claims of runaway ocean heat content.

Meanwhile, other measurements, such as those in North Atlantic and Indian Ocean show slight cooling rather than warming, with researchers suspecting natural cyclical activity.

Summary

So anxious are alarmists/activists to cry wolf that they are running the computers flat out to manipulate and extrapolate from precious but incomplete limited data to confirm their suppositions.  All to keep alive a deflating narrative that the public increasingly finds offensive.

Footnote:

Oceanographers know that deep ocean temperatures can vary on centennial up to millennial time scales, so if some heat goes into the depths, it is not at all clear when it would come out.

Beware getting sucked into any model, climate or otherwise.

More at Putting Climate Models in Their Place

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Ocean SSTs Tepid in November

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 November 2018.

Hadsst112018

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 2 months.  The Tropics have risen steadily since July, and along with a bump in SH pulled the Global anomaly up slightly the last 2 months.

The November Global anomaly is higher than 2017 but still lower than 2015.  Similarly, NH, SH and the Tropics are all slightly higher than 2017, but still lower than 11/2015. The rise in the Tropics is likely due to the weak El Nino, maybe also affecting the SH.

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.

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.

Hadsst95to112018

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, with July 2017 only slightly lower.  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 untrended 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 102018

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 October 2018 is 0.29C lower than October 2016, and is the coolest October since 2011.

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

 

Ocean SSTs Keep Cool

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 October 2018.

Hadsst102018

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 may have peaked in September.  The Tropics have risen steadily since July, and along with a small bump in SH pulled the Global anomaly up slightly.

NH is now slightly higher than 2017, but is still nearly 0.2C lower than 10/2015. The rise in the Tropics is likely due to the weak El Nino, maybe also affecting the SH. Both are still much cooler than 2015 and 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.  Also, note that the global release of heat was not dramatic, due to the Southern Hemisphere offsetting the Northern one.

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.

Hadsst95to102018

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, with July 2017 only slightly lower.  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 untrended 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 102018

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 October 2018 is 0.29C lower than October 2016, and is the coolest October since 2011.

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

 

Ocean SSTs Slightly Cooler

globpop_countriesThe 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 2018

Hadsst092018

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. Since 4/2018 SH and Tropics cooled slightly in the Spring and NH dipped in July 2018.

In August all ocean regions bumped upward, and in September the Global average dipped slightly. Note that NH rose, unlike dips in the last two years, but is still 0.2C lower than 9/2015. The rise in the Tropics is likely due to the weak El Nino, since the SH dropped almost 0.1C, nearly matching the SH low for this period in 9/2017.  That SH cooling is offsetting the NH rise.

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

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.

Hadsst95to092018

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, with July 2017 only slightly lower.  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 untrended 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 092018

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 September 2018 is 0.29C lower than September 2016, and is the coolest September since 2011.

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

 

On the Motion of the Ocean

The image shows what is known about how ocean currents flow under the influence of the earth’s rotation. A recent article adds another level of complexity and insight by examining smaller scale effects. From the American Institute of Physics Researchers challenge our assumptions on the effects of planetary rotation Excerpts in italics with my bolds.

Coriolis effect can influence eddies in wakes as small as 10 meters

The Coriolis effect impacts global patterns and currents, and its magnitude, relative to the magnitude of inertial forces, is expressed by the Rossby number. For over 100 years, scientists have believed that the higher this number, the less likely Coriolis effect influences oceanic or atmospheric events. Recently, however, researchers found that smaller ocean disturbances with high Rossby numbers are influenced by the Coriolis effect. Their discovery challenges assumptions of theoretical oceanography and geophysical fluid dynamics.

A 2-D image of the velocity in an internal jet with the Rossby number of 100 that shows how planetary rotation leads to the destabilization and dispersion of an initially coherent flow pattern. Credit: Timour Radko and David Lorfeld

Earth’s rotation causes the Coriolis effect, which deflects massive air and water flows toward the right in the Northern Hemisphere and toward the left in the Southern Hemisphere. This phenomenon greatly impacts global wind patterns and ocean currents, and is only significant for large-scale and long-duration geophysical phenomena such as hurricanes. The magnitude of the Coriolis effect, relative to the magnitude of inertial forces, is expressed by the Rossby number. For over 100 years, scientists have believed that the higher this number, the less likely Coriolis effect influences oceanic or atmospheric events.

Recently, researchers at the Naval Postgraduate School in California found that even smaller ocean disturbances with high Rossby numbers, like vortices within submarine wakes, are influenced by the Coriolis effect. Their discovery challenges assumptions at the very foundation of theoretical oceanography and geophysical fluid dynamics. The team reports their findings in Physics of Fluids, from AIP Publishing.

“We have discovered some major — and largely overlooked — phenomena in fundamental fluid dynamics that pertain to the way the Earth’s rotation influences various geophysical flows,” Timour Radko, an oceanography professor and author on the paper, said.

Radko and Lt. Cmdr. David Lorfeld originally focused on developing novel submarine detection systems. They approached this issue by investigating pancake vortices, or flattened, elongated mini-eddies located in the wakes of submerged vehicles. Eddies are caused by swirling water and a reverse current from waterflow turbulence.

Last year, a team led by Radko published a paper in the same AIP journal on the rotational control of pancake vortices, the first paper that challenged the famous “Rossby rule.” In this most recent paper, the researchers showed, through numerical simulations, that internal jets of the wake can be directly controlled by rotation. They also demonstrated that the evolution of a disorganized fine-scale eddy field is determined by planetary rotation.

“Here is where our discovery could be critical,” Radko said. “We find that cyclones persist, but that anticyclones unravel relatively quickly. If the anticyclones in the wake are as strong as the cyclones, this means that the wake is fresh — the enemy passed through not too long ago. If the cyclones are much stronger than the anticyclones, then the sub is probably long gone.”

The algorithm that the researchers developed is based on the dissimilar evolution of cyclones and anticyclones, which is a consequence of planetary rotation. “Therefore,” Radko concluded, “such effects must be considered in the numerical and theoretical models of finescale oceanic processes in the range of 10-100 meters.”

The computer model is detailed enough to resolve eddies that are important for ocean circulation. The triangle-shaped island of Newfoundland, center, is at the eastern edge of the study area, the mouth of the Gulf of St. Lawrence. This graphic shows oxygen at the surface, where red shows more oxygen. Credit: Mariona Claret/University of Washington

Background:  Ocean Physics in a Cup of Coffee

 

Ocean SSTs Tepid in August

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 August 2018

Hadsst082018

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. Since 4/2018 SH and Tropics cooled slightly in the Spring and NH dipped in July 2018.  Now in August all ocean regions bumped upward.

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

2018 is the coolest August since 2013 Globally, in NH and the Tropics.  In the SH August 2018 is matching 2017. The biggest difference from August 2015 is the Tropics anomaly being 0.36C lower this year (half of 0.74C in 2015).

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.

Hadsst95to082018

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, with July 2017 only slightly lower.  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 untrended 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 082018

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 August 2018 is 0.34C lower than August 2016, and is the coolest August since 2007.

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?  Lower SSTs in July suggested climate change of the cooling variety, but August has offset that.  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

 

Ocean SSTs Lower in July

globpop_countriesThe 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 July 2018

.Hadsst072018

A global cooling pattern has persisted, seen clearly in the Tropics since its peak in 2016, joined by NH and SH dropping since last August. Upward bumps occurred last October, in January and again in March and April 2018.  2018 started with slight warming after the low point of December 2017, led by steadily rising NH. Since 4/2018 SH and Tropics cooled slightly while NH pulled the Global anomaly upwards. Now in July 2018  a drop in NH with flat temps in SH and Tropics continues global cooling.

2018 is the coolest July since 2012 Globally and in NH.   The Tropics were lower in 2013.

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

With ocean temps positioned lower than July three years ago, further cooling appears likely. As the analysis below shows, the North Atlantic has been the wild card bringing warming this decade, and cooling will depend upon a phase shift in that region.  2018 NH July peak is almost 0.4C lower than NH peak in 2015.

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.

Hadsst95to072018

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, with July 2017 only slightly lower.  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 July in the North Atlantic from the Kaplan dataset.
amo-july-20181

The AMO Index is from from Kaplan SST v2, the unaltered and untrended 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-0720181

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 July 2018 is 0.4C lower than July 2016, and is the coolest July since 2002.

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 lower SSTs in July is any indication, climate change of the cooling variety is looking more likely

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

 

June 2018 Ocean SSTs Resume Cooling

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 June 2018.

Hadsst062018

A global cooling pattern has persisted, seen clearly in the Tropics since its peak in 2016, joined by NH and SH dropping since last August. Upward bumps occurred last October, in January and again in March and April 2018.  Five months of 2018 now show slight warming since the low point of December 2017, led by steadily rising NH. Since 4/2018 SH and Tropics cooled slightly while NH pulled the Global anomaly upwards. Now in June 2018  lower temps in SH and Tropics more than offset NH warming.

2018 is the coolest June since 2013 in all regions: Global, NH, SH and Tropics.

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

With ocean temps positioned the same as three years ago, we can only wait and see whether the previous cycle will repeat or something different appears.  As the analysis belows shows, the North Atlantic has been the wild card bringing warming this decade, and cooling will depend upon a phase shift in that region.

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.

Hadsst1995to062018

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, with July 2017 only slightly lower.  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 as shown by this graph:

The data is annual averages of absolute SSTs measured in the North Atlantic.  The significance of the pulses for weather forecasting is discussed in AMO: Atlantic Climate Pulse

But the peaks coming nearly every July in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.Now the regime shift appears clearly. Starting with 2003, seven times the August average has exceeded 23.6C, a level that prior to ’98 registered only once before, in 1937.  And other recent years were all greater than 23.4C.

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?

To paraphrase the wheel of fortune carnival barker:  “Down and down she goes, where she stops nobody knows.”  As recent months show, nature moves in cycles, not straight lines, and human forecasts and projections are tenuous at best.

einsteinalbert-integratesempirically800px

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

 

Updated: Pacific Sea Level Data

 

PSLMPThis post is about the SEAFRAME network measuring sea levels in the Pacific, and about the difficulty to discern multi-decadal trends of rising or accelerating sea levels as evidence of climate change.

Update July 9, 2018

Asked a question today about sea levels and Pacific islands, I referred to this article.  Realizing it was posted 2 years ago, it seemed important to check the most recent project report.  Thus at the bottom there are now results through May 2018.

Update May 10 below, regarding recent Solomon Islands news

Pacific Sea Level Monitoring Network

The PSLM project was established in response to concerns voiced by Pacific Island countries about the potential effects of climate change. The project aims to provide an accurate long-term record of sea levels in the area for partner countries and the international scientific community, and enable the former to make informed decisions about managing their coastal environments and resources.

In 1991, the National Tidal Facility (NTF) of the Flinders University of South Australia was awarded the contract to undertake the management of the project.  Between July 1991 and December 2000 sea level and meteorological monitoring stations were installed at 11 sites. Between 2001 and 2005 another station was established in the Federated States of Micronesia and continuous global positioning systems (CGPS) were installed in numerous locations to monitor the islands’ vertical movements.

The 14 Pacific Island countries now participating in the project provide a wide coverage across the Pacific Basin: the Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Marshall Islands, Nauru, Niue, Palau, Papua New Guinea, Samoa, Solomon Islands, Tonga, Tuvalu and Vanuatu.

SPSLCM_2008_4_data_report_Image_11

Each of these SEA Level Fine Resolution Acoustic Measuring Equipment (SEAFRAME) stations in the Pacific region are continuously monitoring the Sea Level, Wind Speed and Direction, Wind Gust, Air and Water Temperatures and Atmospheric Pressure.

In addition to its system of tide gauge facilities, the Pacific Sea-Level Monitoring Network also includes a network of earth monitoring stations for geodetic observations, implemented and maintained by Geoscience Australia. The earth monitoring installations provide Global Navigation Satellite System (GNSS) measurements to allow absolute determination of the vertical height of the tide gauges that measure sea level.

Sea Level Datasets from PSLM

Data and reports are here.

Monthly reports are detailed and informative. At each station water levels are measured every six minutes in order to calculate daily maxs, mins and means, as a basis for monthly averages. So the daily mean sea level value is averaged from 240 readings, and the daily min and max are single readings taken from the 240.

 

untitled

A typical monthly graph appears above. It shows how tides for these stations range between 1 to 3 meters daily, as well variations during the month.

According to the calibrations, measurement errors are in the range of +/- 1 mm. Vertical movement of the land is monitored relative to a GPS benchmark. So far, land movement at these stations has also been within the +/- 1 mm range (with one exception related to an earthquake).

The PSLM Record

March SL range

In the Monthly reports are graphs showing results of six minute observations, indicating tidal movements daily over the course of a month.The chart above shows how sea level varied in each location during March 2016 compared to long term March results. Since many stations were installed in 1993, long term means about 22 years of history.

This dataset for Pacific Sea Level Monitoring provides a realistic context for interpreting studies claiming sea level trends and/or acceleration of such trends. Of course, one can draw a line through any scatter of datapoints and assert the existence of a trend. And the error ranges above allow for annual changes of a few mm to be meaningful. Here is a table produced in just that way.

Location Installation date Sea-level trend (mm/yr)
Cook Islands Feb 2003 +5.5
Federated States of Micronesia Dec 2001 +17.7
Fiji Oct 1992 +2.9
Kiribati Dec 1992 +2.9
Marshall Islands May 1993 +5.2
Nauru Jul 1993 +3.6
Papua New Guinea Sept 1994 +8.0
Samoa Feb 1993 +6.9
Solomon Islands Jul 1994 +7.7
Tonga Jan 1993 +8.6
Tuvalu Mar 1993 +4.1
Vanuatu Jan 1993 +5.3

The rising trends range from 2.9 to 8.6 mm/year (FSM is too short to be meaningful).

Looking into the details of the monthly anomalies, it is clear that sea level changes at the mm level are swamped by volatility of movements greater by orders of magnitude.  And there are obvious effects from ENSO events. The 1997-98 El Nino shows up in a dramatic fall of sea levels almost everywhere, and that event alone creates most of the rising trends in the table above.  The 2014-2016 El Nino is also causing sea levels to fall, but is too recent to affect the long term trend.

Picture17revUpdate July 9, 2018

Here are the sea level records updated to May 2018.

Pacific Sea Levels May 2018

The records are dominated by two Major El Nino events in 1997-8 and 2015-6.  When Westerly winds pick up, warm surface water is pushed from western (Asian) Pacific toward eastern (American) Pacific.  Thus sea levels decline temporarily during those periods, as seen in the blue deficits in the charts above.  Below the updated sea level trends.
Seaframe trends May 2018
Summary

Sea Level Rise is another metric for climate change that demonstrates the difficulty discerning a small change of a few millimeters in a dataset where tides vary thousands of millimeters every day. And the record is also subject to irregular fluctuations from storms, currents and oceanic oscillations, such as the ENSO.

On page 8 of its monthly reports (here), PSLM project provides this caution regarding the measurements:

The overall rates of movement are updated every month by calculating the linear slope during the tidal analysis of all the data available at individual stations. The rates are relative to the SEAFRAME sensor benchmark, whose movement relative to inland benchmarks is monitored by Geosciences Australia.
Please exercise caution in interpreting the overall rates of movement of sea level – the records are too short to be inferring long-term trends.

A longer record will bring more insight, but even then sea level trends are a very weak signal inside a noisy dataset. Even with state-of-the-art equipment, it is a fool’s errand to discern any acceleration in sea levels, in order to link it to CO2. Such changes are in fractions of millimeters when the measurement error is +/- 1 mm.

For more on the worldwide network of tidal gauges, as well as satellite systems attempting to measure sea level, sea Dave Burton’s excellent website.

May 10 update Regarding recent news about Solomon Islands.

As the charts above show, there is negligible sea level rise in the West Pacific, and receding a bit lately at Solomon Islands.  So it was curious that the media was declaring those islands inundating because of climate change.

Now the real story is coming out (but don’t wait for the retractions)

A new study published in Environmental Research Letters shows that some low-lying reef islands in the Solomon Islands are being gobbled up by “extreme events, seawalls and inappropriate development, rather than sea level rise alone.” Despite headlines claiming that man-made climate change has caused five Islands (out of nearly a thousand) to disappear from rising sea levels, a closer inspection of the study reveals the true cause is natural, and the report’s lead author says many of the headlines have been ‘exaggerated’ to ill-effect.

http://www.examiner.com/article/sinking-solomon-islands-and-climate-link-exaggerated-admits-study-s-author

 

 

 

May 2018 Ocean Cooling On Hold

globpop_countriesThe 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 2018.

Hadsst052018

Open image in new tab to enlarge.

A global cooling pattern has persisted, seen clearly in the Tropics since its peak in 2016, joined by NH and SH dropping since last August. Upward bumps occurred last October, in January and again in March and April 2018.  Five months of 2018 now show slight warming since the low point of December 2017, led by steadily rising NH. May 2018  temps in all regions are slightly lower than 5/2015, except for the Tropics being much lower. Since 4/2018 SH and Tropics cooled slightly while NH pulled the Global anomaly upwards.

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

With ocean temps positioned the same as three years ago, we can only wait and see whether the previous cycle will repeat or something different appears.  As the analysis belows shows, the North Atlantic has been the wild card bringing warming this decade, and cooling will depend upon a phase shift in that region.

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.

Hadsst1995to2018

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, with July 2017 only slightly lower.  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 as shown by this graph:

The data is annual averages of absolute SSTs measured in the North Atlantic.  The significance of the pulses for weather forecasting is discussed in AMO: Atlantic Climate Pulse

But the peaks coming nearly every July in HadSST require a different picture.  Let’s look at August, the hottest month in the North Atlantic from the Kaplan dataset.Now the regime shift appears clearly. Starting with 2003, seven times the August average has exceeded 23.6C, a level that prior to ’98 registered only once before, in 1937.  And other recent years were all greater than 23.4C.

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?

To paraphrase the wheel of fortune carnival barker:  “Down and down she goes, where she stops nobody knows.”  As this month shows, nature moves in cycles, not straight lines, and human forecasts and projections are tenuous at best.

einsteinalbert-integratesempirically800px

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