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Sunday, November 30, 2008

Recharging The Pacific Warm Pool

I’ve moved to WordPress.  This post can now be found at Recharging The Pacific Warm Pool
Note: This is my first attempt at uploading or linking a video I created, so things might get interesting.


In prior posts, I’ve noted that the heat upwelled during El Nino events isn’t all released into the atmosphere, that much of it is returned to the West Pacific and the Pacific Warm Pool where it awaits the next El Nino event. This video of the 1997/98 El Nino and the years that followed should help illustrate the process. I’ve interrupted the flow of the SSH video from JPL to narrate as needed. I also took the opportunity to illustrate and reinforce the lingering effects of the 1997/98 El Nino.

YouTube Link:

Sorry, no audio.


Sea Surface Height videos are available from NASA’s Jet Propulsion website:
The video used in the preceding is a much edited version of:

Optimally Interpolated Sea Surface Temperature Data (OISST) are available through the NOAA National Operational Model Archive & Distribution System (NOMADS).

Saturday, November 29, 2008

Dip and Rebound

I’ve moved to WordPress.  This post can now be found at Dip and Rebound

More than two decades ago, the hypothesis of Anthropogenic Global Warming (AGW) seemed logical to me. I bit into it hook, line, and sinker. (See following note) Until recent times, most articles and papers presented both sides of the AGW debate. The one sentence used by skeptical authors or resources back then that always seemed like a way to avoid a concrete data-based statement was something to the effect of “The change in global temperature is well within the realm of Natural Variability.” I have mixed feelings about the term “Natural Variability” even to this day, yet I will conclude this post with it.

Note: My understanding of and position on AGW changed more than 10 years ago. I would now be classified as a full-fledged, bona fide, card-carrying AGW skeptic. Well, I’d have a card if one was available.


Figure 1 illustrates Global SST anomalies from Jan 1854 to October 2008. The data is raw and smoothed with an 11-year (133-month) filter. (The reason for the 11-year filter: I was plotting Monthly Sunspot Numbers for an upcoming post and I liked the way it smoothed global SST anomaly data. No other reason.) I’ve also circled the period from 1870 to 1940, during which SST anomalies dipped and rebounded.
Figure 1

As shown in Figure 2, which isolates the data over the period of January 1870 to December 1939, the variation is more than 0.3 deg C. I have yet to find an explanation for the dip and rebound in any IPCC or CCSP report. Are the IPCC and CCSP taking advantage of a natural decline in Global SST anomaly to reinforce or amplify their claims of an unprecedented rise in 20th Century Global Temperatures caused by anthropogenic forcings? Of course, they are.
Figure 2

Figure 3 contains the same data as Figure 2, except the data has been inverted. It’s supplied simply as a reference for the next illustration.
Figure 3

In Figure 4, I took the inverted 1870-to-1939 data and shifted it 90 years. I also shifted the temperature range a few tenths of a degree (I did not scale it) so that there was agreement in the starting points of the rises in the two curves after 1960. Note how the two curves have very similar trends from 1960 to 2000.

Note: I do not intend the broken extension of the red curve from present to the year 2030 as a prediction of future events. It simply seemed appropriate to include it. We’ll just have to wait and see what the future holds.
Figure 4


Using the unexplained 1870 to 1939 dip and rebound as reference, as of now, the rise in Global SST over the term of the instrument temperature record is well within the range of Natural Variability.


Sea Surface Temperature Data is Smith and Reynolds Extended Reconstructed SST (ERSST.v2) available through the NOAA National Operational Model Archive & Distribution System (NOMADS).

Thursday, November 27, 2008

Estimated Number of Major Atlantic Hurricanes and Vertical Windshear

I’ve moved to WordPress.  This post can now be found at Estimated Number of Major Atlantic Hurricanes and Vertical Windshear
And to those of you who are not celebrating the holiday, Happy Thursday.

With the 2008 Hurricane Season coming to a close, it seemed appropriate to resurrect the paleoclimatological reconstruction of the estimated number of major Atlantic hurricanes created by Nyberg et al in 2007. The data source is here:
I wrote resurrect above because I know I’d read this abstract before, but googling the title in quotes revealed only 6 references, all of them NASA or NCDC websites. Regardless, here’s the graph of the Estimated Number of Hurricanes. I haven’t graphed the windshear. The data was smoothed by the authors, not by me. The graph is created by the raw data.

Nyberg, J., et al. 2007.Estimated Number of Major Atlantic Hurricanes and Vertical Windshear.IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2007-056.NOAA/NCDC Paleoclimatology Program, Boulder CO, USA.

This file contains estimated number of major hurricanes and vertical windshear (five-year running averages). Back propagation artificial neural networks were used to estimate past number of major hurricanes and vertical windshear. The relationships between combined input (independent) proxy records and the two output (dependent) instrumental records of number of major hurricanes and vertical windshear were determined unconnectedly.

Hurricane activity in the North Atlantic Ocean has increased significantly since 1995. This trend has been attributed to both anthropogenically induced climate change and natural variability, but the primary cause remains uncertain. Changes in the frequency and intensity of hurricanes in the past can provide insights into the factors that influence hurricane activity, but reliable observations of hurricane activity in the North Atlantic only cover the past few decades. Here we construct a record of the frequency of major Atlantic hurricanes over the past 270 years using proxy records of vertical wind shear and sea surface temperature (the main controls on the formation of major hurricanes in this region) from corals and a marine sediment core. The record indicates that the average frequency of major hurricanes decreased gradually from the 1760s until the early 1990s, reaching anomalously low values during the 1970s and 1980s. Furthermore, the phase of enhanced hurricane activity since 1995 is not unusual compared to other periods of high hurricane activity in the record and thus appears to represent a recovery to normal hurricane activity, rather than a direct response to increasing sea surface temperature. Comparison of the record with a reconstruction of vertical wind shear indicates that variability in this parameter primarily controlled the frequency of major hurricanes in the Atlantic over the past 270 years, suggesting that changes in the magnitude of vertical wind shear will have a significant influence on future hurricane activity.

Tuesday, November 25, 2008

Another Global Temperature Blunder? Or RealClimate Confusion

I’ve moved to WordPress.  This post can now be found at Another Global Temperature Blunder? Or RealClimate Confusion
On the recent RealClimate thread Mind the Gap!, Rasmus discussed the confusion over global temperature trends. Maybe if he had checked his graphics before he posted them, he might have helped his cause. The mistake:

The second graphic on the RealClimate thread is shown in Figure 1.
Figure 1

The end of the RealClimate caption for that figure reads: “(click on figures for PDF-version)”. I clicked and was presented with the graphic shown in Figure 2. The link:

Figure 2

Notice a difference? In Figure 3, I’ve shown the two time-series graphs. They are NOT the same.
Figure 3

In Figure 4, I’ve shown the two pairs of coverage maps. They are NOT the same.
Figure 4

I discovered the error at 4:31PM on November 25, 2008, then checked to see if any of the 270+ comments made to that time had mentioned it. (No, I didn’t read all the comments; I simply let Internet Explorer search for “pdf”.) In comment 254, blogger Glen Fergus noted the error at 12:14AM on November 25, 2008, but as of the time I found it, they had not corrected it, obviously.

An Interesting Correlation with North Atlantic Subpolar Gyre SST

I’ve moved to WordPress.  This post can now be found at An Interesting Correlation with North Atlantic Subpolar Gyre SST

While I was investigating North Atlantic Meridional Overturning Circulation, an area of the North Atlantic kept coming up in papers: the North Atlantic Subpolar Gyre. Refer to Figure 1. The red box (the borders for the data used in the following graphs) picks up the center of the “heart-shaped” gyre that’s located south of Greenland. The North Atlantic Subpolar Gyre includes the North Atlantic Drift, and the Irminger, Greenland and Labrador Currents. (The Irminger Current is not identified on the map, but it’s south and west of Iceland.)
Figure 1

There’s an interesting correlation between the cycles of the North Atlantic Gyre SST anomalies and those of another data set. I believe the explanation of this would have to come under the all-encompassing heading of teleconnections. But first let’s take a look at the…


Figure 2 illustrates the North Atlantic Subpolar Gyre [45N-60N, 60W-30W] SST anomaly data from January 1854 to October 2008 that’s been smoothed with a 12-month running-average filter. The cycle is the first thing to catch the eye. The second: If trend lines were to be drawn from peak-to-peak and from trough-to-trough, they would be relatively flat. That is, there does not appear to be a significant, if any, underlying “global warming” trend. The curve almost appears to be a residual like the Atlantic Multidecadal Oscillation (AMO).
Figure 2

Figures 3 and 4 illustrate the North Atlantic Subpolar Gyre SST anomaly data smoothed with 37- and 85-month filters, to help minimize the noise.
Figure 3
Figure 4

In case someone was interested, in Figure 5, I’ve illustrated the short-term data (November 1981 to October 2008) as a comparative graph between ERSST.v2 data (used for the long term graphs) and OI.v2 SST data.
Figure 5


Keep in mind that in the following two graphs, SST data is being compared to scaled residual data.

The first thing one would think of when they see a cycle in any North Atlantic SST anomaly data would be the AMO. In looking at a comparative graph of the AMO (scaled) and the North Atlantic Subpolar Gyre SST anomalies, Figure 6, the cycles do compare well after the early 1900s. But they are out of synch before then.
Figure 6

To my eye, and seeming to be counterintuitive, the timing of the cycles in the North Pacific Residual agree with those of the North Atlantic Subpolar Gyre SST anomalies. Refer to Figure 7, which compares the North Pacific Residual (scaled) with the North Atlantic Subpolar Gyre SST anomalies.
Figure 7

Or maybe the North Atlantic Subpolar Gyre SST anomalies have been impacted by both over the term of the data. Could the dominant influence change with time?


Smith and Reynolds Extended Reconstructed SST Sea Surface Temperature Data (ERSST.v2) and the Optimally Interpolated Sea Surface Temperature Data (OISST) are available through the NOAA National Operational Model Archive & Distribution System (NOMADS).

Sunday, November 23, 2008

Atlantic Meridional Overturning Circulation Data

I’ve moved to WordPress.  This post can now be found at Atlantic Meridional Overturning Circulation Data

I believe this is the paper that describes the data set:


In their Climate Indices webpage, the Royal Netherlands Meteorological Institute (KNMI) has an interesting historical data set available for downloading: Atlantic Meridional Overturning Circulation (AMOC).

KNMI website:
Climate Indices webpage:
ORA-S3, MOC [Sv] Meridional Overturning Circulation at 26N webpage:
MOC Data in text form:

The monthly data set begins in January 1961 and ends in December 2005. The units are Sverdrup (Sv), where 1 Sv is equal to a volume flow rate of 10^6 cubic meters per second. The notation “ORA-S3” at the top of the data page indicates the source, which is the European Centre for Medium-Range Weather Forecasts (ECMRF). Their webpage:
Chasing the data set farther, the ECMRF’s ORA-S3 System is described beginning on page 9 of their Autumn 2007 newsletter:

Enough with the background.


Figures 1 and 2 illustrate the Atlantic Meridional Overturning Circulation (AMOC) Data from January 1961 to December 2005. In Figure 1, the data is raw. The data has been smoothed with a 12-month running average filter in Figure 2 to remove the monthly noise. At first glance, the graph of the data set doesn’t appear similar to any other data I’ve run across to date, and the 1972 spike does not to correlate with any of the usual suspects: volcanic aerosols or ENSO.

Figure 1
Figure 2

The representation of AMOC bears no resemblance to the AMO. Refer to Figure 3.
Figure 3

The AMOC curve does not appear to have a basis in the High Latitude North Atlantic SST anomalies, Figure 4. Since that’s the area of AMOC subsidence, it seemed possible there might be a correlation. There’s not.
Figure 4

Maybe we need to change the appearance.


In Figure 5, the AMOC data has been inverted (multiplying it by -1). There are times when the inverted AMOC data may correlate with ENSO.
Figure 5

Figure 6 is a comparative graph of Inverted AMOC and NINO3.4 SST anomalies. I have not scaled the NINO3.4 data. I simply shifted it, changing its temperature range. Prior to 1977, there seems to be no correlation between NINO3.4 and Inverted AMOC. But, from the early 1977 to present, they correlate very well, with the exceptions of in-phase then out-of-phase response to the 1997/98 El Nino. What took place just before 1977? The Great Pacific Climate Shift of 1976.

Keep in mind that the AMOC data has been inverted in Figure 6 and that it illustrates that an increase in NINO3.4 SST anomaly causes a decrease in AMOC flow during most ENSO events from 1977 to present.
Figure 6


The source of the AMOC data is discussed in the Introduction of this post.

The Smith and Reynolds Extended Reconstructed SST (ERSST.v2) data is available through the NOAA National Operational Model Archive & Distribution System (NOMADS).http://nomads.ncdc.noaa.gov/#climatencdc

Thursday, November 20, 2008

NINO3.4 Data Comparison – HADSST and ERSST.v2


In a previous post “Standardized versus Raw (Not Standardized) NINO3.4 SST Anomaly Data” (11/13/08), which I have removed, I mistakenly attributed the differences between the two data sets to standardization. The standardized NINO3.4 SST anomaly data that I used in that post was prepared by Trenberth and Stepaniak. Trenberth and Stepaniak discuss their NINO3.4 index and its recipe here:
Their updated 1871 to 2007 NINO3.4 data is here:
Investigating the source of the Trenberth and Stepaniak NINO3.4 SST data further, it’s based on Hadley Centre HADSST data, which is available through the NCDC:
The reference to HADSST is at the bottom of that webpage. The HADSST source is confirmed by the NCDC discussion page:

With the background of this post complete, there are underlying differences between the HADSST and ERSST.v2 NINO3.4 SST data, with the most significant differences occurring before the mid-20th Century.

There are also small and subtle differences depending on whether the NINO3.4 anomaly data has been standardized or left in its raw state. For this reason, I’ve illustrated it both ways in the following. But first, there’s the…


Figure 1 compares the HADSST and ERSST.v2 versions of NINO3.4 SST (not anomaly) data. The two track well from the mid-1950s to present. Prior to that, they diverge and the differences can be substantial.

Figure 1

Figure 2 illustrates the difference between the ERSST.v2 and HADSST versions of NINO3.4 SST, where the ERSST.v2 data was subtracted from the HADSST data. The difference indicates there is an underlying trend in the SST data of the ERSST.v2 version that doesn’t appear in the HADSST data.
Figure 2


Figures 3 and 4 provide comparisons that are similar to the above, but in these graphs, SST anomaly data are compared. The same base years were used for both data sets, 1950 to 1979, which are those used in the referenced Trenberth and Stepaniak data. The comparisons of SSTs and SST anomalies are very similar.
Figure 3

Figure 4


In Figures 5 and 6, I took the process one step farther and compared standardized versions of the ERSST.v2 and HADSST NINO3.4 data. There are subtle differences between the raw and standardized data sets, though you’d have to flip between the images to see them. The most obvious is that the variations have been exaggerated by the standardization process. This can be seen by comparing the temperature scales and the peaks of the major El Nino events.

A note about the standardization used: I followed the recipe given by Trenberth and Stepaniak in the first link above, with the following exception: I did NOT smooth the data with a 5-month filter prior to normalization.
Figure 5

Figure 6


In the earlier post that I’ve just deleted, I had included graphs of the Trenberth and Stepaniak NINO3.4 data for use as references. The following are those graphs. The data in Figure 7 has not been filtered by me. Figures 8 and 9 have been smoothed, with 12- and 25-month filters.
Figure 7

Figure 8

Figure 9


The source of the HADSST data is discussed in the introduction, above.

The Smith and Reynolds Extended Reconstructed SST (ERSST.v2) data is available through the NOAA National Operational Model Archive & Distribution System (NOMADS).http://nomads.ncdc.noaa.gov/#climatencdc

The reasons for smoothing ENSO-related data with a 25-month filter are discussed here:

Wednesday, November 19, 2008

For Example, Bob Tisdale Commented...

UPDATE (2-19-09): And yet another website attributing this comment to me. MacCompanion:

Being misquoted is one thing, having a thoughtful comment by another blogger attributed to me is another.

I discovered on a number of blogs that I was said to have made the following comment:
"If the Antarctic is getting warmer, as claimed, than (sic) why has the ice cover there increased by far more than that 'lost' at the arctic? 

If the arctic is loosing (sic) ice at an 'increasing rate', than why has this year seen record early ice formation and record extent? 

If the earth is getting warmer, than why have record low temperatures and record early snowfalls been occurring across the Northern hemisphere this year (and temperatures becoming lower for the last 5 years)?"

An example from the Pure Energy Systems (PesWiki) site:

I haven’t taken the time to track down who made the error first, but the above quote is part of comment made by Abigail at the Telegraph.co.UK website on their thread titled “Man is to blame for Antarctic temperature rise”.

My comment was immediately before hers and it read:

Here are two graphs of temperature data that contradict the claims made in the article. The first is a graph of global, Northern Hemisphere, and Arctic land and sea surface temperature anomalies. Note how the Arctic temperature diverges from the global and Northern Hemisphere data after the 97/98 El Nino. Arctic temperatures then remain at the elevated level due to the influence of the subsequent El Nino events that occurred in 2002/03, 2004/05, and 2006/07. Arctic warming in response to El Nino events is consistent with the projections of coupled GCMs.

The second graph is of the Sea Surface Temperature (SST) anomalies for the Southern Ocean, which is the ocean that surrounds the Antarctic. I fail to find an anthropogenic warming signal in that data. In fact, Southern Ocean SST anomalies have been decreasing since the 1980s. How does that agree with the claims made in the article?



Have a nice day.


To those who made the mistake: please correct your attribution.

Sorry to steal your thunder, Abigail. I hope this corrects the problem.


Tuesday, November 18, 2008

The 2007 Spike in Arctic Ocean SST


The reasons for the drastic decline in Arctic Sea ice during 2007 include the reversal of Arctic Ocean currents, polar amplification exacerbated by of a string of El Nino events (2002/03, 2004/05, 2006/07) with no La Ninas to counteract them, the Arctic Oscillation, and others. Emphasizing the magnitude of that decline, the Arctic Ocean SST anomaly graph in my post Optimally Interpolated SST (OI.v2 SST) versus Extended Reconstructed SST (ERSST.v2) Data showed a significant spike in Arctic Ocean SST in 2007. To save you a click, the following is a graph of OI.v2 SST anomaly data for the Arctic Ocean [65N-90N] from November 1981 to October 2008. It clearly shows the anomalous 2007 rise in SST.
Figure 1

The majority of the unusual sea ice loss in 2007 took place in and north of (moving west to east from Siberia to the Alaska-Canada border) the Laptev Sea, the East Siberian Sea, the Chukchi Sea, and the Beaufort Sea. Refer to the following video (MOV format, 5.66MB) of the 2007 Arctic melt season.


Figures 2 and 3 illustrate how I divided the Arctic Ocean SST anomaly data into quadrants. The coordinates I used isolate most of the affected area.
Figure 2
Figure 3

Figure 4 shows the Arctic SST anomaly data (OI.v2 SST) from November 1981 to October 2008, with the data divided into the quadrants shown above. Sorry about the weight of the curves, but if they were heavier, the forward curves would hide those behind. The 2007 spike in SST anomaly took place in the area identified as “Siberia-Alaska”, the purple curve, confirming that the spike in SST simply reflects the unusual ice loss north of Eastern Russia and Alaska.
Figure 4

But the 2008 Arctic sea ice loss was nearly the same as 2007, yet in 2008, Arctic SST in that area did not climb to the 2007 temperature. The sea ice loss in 2008 appears to have been more evenly distributed than it was in 2007. Refer to Figure 5, which are comparative sea ice maps near the peaks of the melt season, September 15, 2007 and 2008.
Figure 5


Comparative sea ice maps are available from Cryosphere Today:

Optimally Interpolated Sea Surface Temperature Data (OI.v2 SST) is available through the NOAA National Operational Model Archive & Distribution System (NOMADS).

Monday, November 17, 2008

Optimally Interpolated SST (OI.v2 SST) versus Extended Reconstructed SST (ERSST.v2) Data


I would prefer to use ERSST.v3 in all posts since it’s the most up-to-date version of SST data, but I have yet to find a simple way to download time-series data for it. For short-term data, however, monthly Optimally Interpolated SST (OI.v2 SST) data is available from NOMADS from November 1981 to present. The OI.v2 SST data provides better resolution than ERSST.v2, but it’s obviously not a long-term data set. The improvements are discussed in the Reynolds et al paper (2002) “An Improved In Situ and Satellite SST Analysis for Climate”, Journal of Climate, 15, 1609-1625.

This post provides a visual comparison of OI.v2 SST and ERSST.v2 SST data for the period that the two data sets overlap, November 1981 to present. As you will note, the OI.v2 SST data illustrates more detail for the Southern Hemisphere and the extreme high latitudes. For this reason, I’ve elected to use it as the source for future monthly SST updates.


As noted above, the differences between OI.v2 and ERSST.v2 SST data for the Arctic and the Southern Ocean are significant. They are illustrated in the following two graphs. Note the spike in the 2007 Arctic Ocean SST anomalies. I’ll do a follow-up post on that blip to illustrate its primary location.
Arctic Ocean SST Anomalies (65 to 90N)
Southern Ocean SST Anomalies (60 to 90S)


There are no major differences between the two data sets for NINO3.4 SST anomalies.
NINO3.4 SST Anomalies (5S to 5N, 170W to 120W)


There is little difference between the two data sets for the Northern Hemisphere, but there are significant changes in the Southern Hemisphere data. These changes to the Southern Hemisphere are then reflected in the Global SST anomaly data.
Northern Hemisphere SST Anomalies
Southern Hemisphere SST Anomalies
Global SST Anomalies


The following graphs compare SST anomalies for the Indian Ocean as a whole and for the North and South Atlantic and Pacific Oceans. As noted previously, the Southern Hemisphere data sets have the greater differences.
North Atlantic SST Anomalies (0 to 75N, 78W to 10E)
South Atlantic SST Anomalies (0 to 60S, 70W to 20E)
North Pacific SST Anomalies (0 to 65N, 90 to 180W) & (0 to 65N, 100 to 180E)
South Pacific SST Anomalies (0 to 60S, 70 to 180W) & (0 to 60S, 145 to 180E)
Indian Ocean SST Anomalies (30N to 60S, 20 to 145E)


Smith and Reynolds Extended Reconstructed SST Sea Surface Temperature Data (ERSST.v2) and the Optimally Interpolated Sea Surface Temperature Data (OISST) are available through the NOAA National Operational Model Archive & Distribution System (NOMADS).

Sunday, November 16, 2008

Revised Ocean Heat Content

In my post The Ishii and Kimoto Proposed Update to Ocean Heat Content, I provided a link to the November 5, 2008, NASA Earth Observatory article “Correcting Ocean Cooling”. http://earthobservatory.nasa.gov/Features/OceanCooling/
Figure 1 is a copy of the graph of the Ocean Heat Content from page 4 of the article. It compares the original OHC data to the newly revised data. Unfortunately, they failed to document the depths for the data. If they did, I couldn’t find it in the article.

Figure 1

Using the coordinate capabilities of MS Paint, I “duplicated” the graph in Figure 2 so that I could run a few quick comparisons.
Figure 2

In Figure 3, the last few years of revised data have been deleted to make the time spans equal. Linear trends were then added. Note the minor decrease in trend between the original and the revised OHC data.
Figure 3

Figure 4 is a comparative graph of OHC and the Multivariate ENSO Index (MEI). Regrettably, there was no simple way to scale the MEI data to make it easier to compare to OHC, so I simply left it as raw annual data. There does not appear to be a consistent reaction of OHC to ENSO events. Note how, counter-intuitively, the OHC rises and falls in synch with SST during the 1997/98 El Nino. One would expect the OHC to decrease during that El Nino since the tropical east Pacific discharged so much heat into the atmosphere, but the OHC rose. Then the variation in OHC opposes the La Nina that follows, as expected. That specific period was selected because it is not influenced by volcanic aerosols.
Figure 4

The influence of stratospheric aerosols ejected from explosive volcanic eruptions can be seen in Figure 5. It‘s impossible, unfortunately, to draw any conclusions about the relationship between volcanic aerosols and OHC solely on this graph because volcanic aerosols are not the only significant natural variable capable of altering the amount of solar irradiance reaching the surface of the oceans.
Figure 5

More unfortunate is the lack of long-term cloud cover data. The only cloud cover data sets I’ve found begin in 1980 or thereabouts. Refer to Figure 6, which shows a decrease (about 4 to 5%) in global Total Cloud Amount from 1986 to 2000, then an increase (about 2 to 3%) from 2000 to 2005.
Figure 6

In Figure 7 I’ve compared OHC with annual scaled and ranged ERSST.v3 global SST data. Both display increasing trends, but the annual variability of SST far exceeds that of OHC.
Figure 7

Figure 8 illustrates the annual change in OHC. The period of sustained volcanic aerosols from 1960 to the early 1970s clearly suppressed annual variations in OHC.
Figure 8


At the end of my November 11, 2008 post about the Ishii and Kimoto proposed changes to OHC (linked above and below), I commented about the curious coincidence between the number of global ocean data profiles and the rise and fall in ocean heat content. It would be inappropriate for me to make the observation in that post but not in this, so I’ve repeated it here. While the revised OHC data in this post does not have the "hump" in the 1970s, OHC appears to have accelerated since the early 1990s. Oddly, this seems to coincide, though not perfectly in synch, with the surge in the number of readings.


From The Ishii and Kimoto Proposed Update to Ocean Heat Content:

UPDATE (November 14, 2008): Please note that I am not implying any wrongdoing on the parts of those who calculate Ocean Heat Content. I simply found the following to be an odd coincidence, one that should be discussed.

The following is a graph of the number of global ocean data profiles accumulated monthly from 1979 to 2006 by the NCEP Global Ocean Data Assimilation System for a depth of 0-250 Meters from 90S to 90N. It’s odd that in recent years the Ocean Heat Content rises above its previous high in the 1970s, while at the same time the number of subsurface ocean temperature readings increases drastically. Then the Ocean Heat Content peak and decline about the same time as the number of readings.
Number of Global Ocean Data Profiles

The Climate Prediction Center NCEP Global Ocean Data Assimilation System: Monthly Products webpage is here:


The Ocean Heat Content data was extracted from the graph in the above-linked NASA Earth Observatory article.

SATO Index data is available from GISS:

Multivariate ENSO Index data is available from the NOAA Earth System Research Laboratory:

Cloud Amount Graph is part of Figure 1 from Palle et al (2006)“Can Earth’s Albedo and Surface Temperatures Increase Together?” EOS Vol. 87, No. 4, 24 January 2006


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Blog Archive

Comment Policy, SST Posts, and Notes

Comments that are political in nature or that have nothing to do with the post will be deleted.
The Smith and Reynolds SST Posts DOES NOT LIST ALL SST POSTS. I stopped using ERSST.v2 data for SST when NOAA deleted it from NOMADS early in 2009.

Please use the search feature in the upper left-hand corner of the page for posts on specific subjects.
NOTE: I’ve discovered that some of the links to older posts provide blank pages. While it’s possible to access that post by scrolling through the history, that’s time consuming. There’s a quick fix for the problem, so if you run into an absent post, please advise me. Thanks.
If you use the graphs, please cite or link to the address of the blog post or this website.