Resolving the biases in century-scale sea surface temperature measurements reveals some interesting patterns

This new paper in GRL takes on the well-known buckets-vs-inlets issue (Steve McIntyre also visited the issue several times) related to ship based sea surface temperature measurements and as a result, produces an improved dataset. The results show a surprising period of warming, but not in the time period expected.  How would AGW advocates explain that most of the warming in the near surface layers of the ocean came well before Dr. Hansen’s supposed “safe” value of 350ppm of CO2 in Earth’s atmosphere. How would they account for the big rise before 1940?

Even more interesting, if you look at panel (b), (surface temperature in red) you see essentially no change from over 100 years ago. The shape and slope of Panel (a) looks much like the BEST and other surface data up until the mid twentieth century, then post WWII population growth set in. The differences between the two sets post 1980 (when we have the best measurements) is quite stark: 

Here’s the paper:

Consistent near-surface ocean warming since 1900 in two largely independent observing networks

Viktor Gouretski, John Kennedy, Tim Boyer, and Armin Köhl

We compare historical global temperature time series, based on bias-adjusted sea-surface temperatures with independent temperature time series, for the upper 20 meter layer

of the ocean based on the latest update of an historical hydrographic profile data set. Despite the two underlying data sets being different in number of data points, instrumentation and applied adjustments, both of the time series are consistent in showing an overall warming since 1900.

We also extend records of temperature change in the upper 400 m back to 1900. Noting that the geographic coverage is limited prior to 1950, the temperature change in the 0–400 m layer is characterized by two periods of temperature increase between 1900 and 1940–45 and between 1970 and 2003, separated by a period of little change. Citation: Gouretski, V., J. Kennedy, T. Boyer, and A. Köhl (2012), Consistent near-surface ocean

warming since 1900 in two largely independent observing networks,

Geophys. Res. Lett., 39, L19606, doi:10.1029/2012GL052975.

Introduction

Numerous studies have identified an overall rise of the surface temperature of the Earth since the nineteenth century [Smith et al., 2008; Hansen et al., 2010; Morice et al.,

2012]. The global-average surface temperature is estimated from a composite dataset that includes both land- and seasurface temperature (SST) observations. In addition to studies

analyzing surface temperature data, collections of historical hydrographic temperature profiles have been used to estimate the change in heat content of the global oceans

[Levitus et al., 2005, 2009, 2012; Gouretski and Koltermann, 2007].

Two main sources of uncertainty affect both the surface and subsurface time series based on in situ data. The first is related to insufficient data coverage both in space and time, with extremely irregular sampling in the earlier parts of the records. The second arises from instrumental biases which can be comparable in magnitude to real variability in the

climate. Jones and Wigley [2010] identified biases in SST measurements as the most important remaining uncertainty associated with estimating global average temperature change.

Prior to the 1980s, SST measurements were mostly made using buckets or in the engine rooms of ships. Folland and Parker [1995] described systematic errors in SST observations

associated with the use of uninsulated buckets for water sampling and developed adjustments. Uncompensated biases associated with a shift in the database from engine room measurements (relatively warm biased) to bucket measurements (relatively cold biased) occurred at the end of World War II and led to an apparent drop in observed SSTs in late 1945 [Thompson et al., 2008]. More recent studies [Kennedy et al., 2011a, 2011b] attempt to quantify SST biases and their associated uncertainties in the post war period.

However, Kennedy et al. [2011b] note that “Until multiple, independent estimates of SST biases exist, a significant contribution to the total uncertainty will remain unexplored. This remains a key weakness of historical SST analysis”.

Gouretski and Koltermann [2007] revealed significant biases both in the eXpendable BathyThermograph (XBT) and in the Mechanical BathyThermograph (MBT) data used

to measure subsurface ocean temperatures. The effect of this instrumentation problem appeared as an artificial pattern of ocean warming around 1975–1985 in the Levitus et al.

[2005] time series of ocean heat content within the upper 700 meters. Further studies have confirmed the general characteristics of the biases described by Gouretski and

Koltermann [2007] and correction schemes have been developed for both MBT and XBT data [Wijffels et al., 2008; Ishii and Kimoto, 2009; Levitus et al., 2009; Gouretski and

Reseghetti, 2010].

However, Lyman et al. [2010] showed that even in the recent record (1994–2008) the uncertainties of the bias adjustments applied to subsurface data were a major component of the total uncertainty in estimates of ocean heat content. It is often difficult to assess the effectiveness of bias adjustments in reducing the imprint of systematic errors in climate data because independent test data are rarely available. In this analysis an initial approach to resolve this uncertainty is made by comparing two independently derived estimates of near-surface ocean temperature. In addition, a time series of the mean temperature within the upper 400 meters of the world ocean is calculated back to 1900.

[…]

Conclusions

1. The time series of the temperature anomalies within the upper 20-meter and 400-meter layers were extended to the beginning of the twentieth century, although there are

gaps around the two world wars for the 0–400 m layer. Previous estimates started around 1950.

2. A good agreement is observed between the time series based on the sea surface and the near-surface data respectively, but differences suggest either residual uncertainty

of around 0.1C in the adjustments applied to minimize the effects of systematic errors, or actual differences between temperatures at the sea-surface and in the upper 20 meters.

3. The upper 400 meters of the ocean warmed by about 0.3–0.7C since 1910, with a central estimate around 0.5 to 0.6C. The temperature change is characterized by

two periods of stronger temperature increase between 1900 and 1940–45 and between 1970 and 2003, separated by a period of little change in the global average.

4. Decadal mean SST and 0–20 m layer anomalies calculated relative to the reference decade 2001–2010 give evidence of the general warming of the global ocean since

1900. However, large regions of the oceans have experienced cooling since the 1990s. Whereas cooling in the tropical Eastern Pacific ocean is associated with frequent La

Nina events in the past decade, the cause of the cooling within the Southern Ocean remains unknown.

h/t to Dr. Leif Svalgaard, who has a copy of the paper online here.

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Stephen Wilde
October 8, 2012 8:23 am

“Unfortunately, the hypothesis that solar activity “affects” “global” cloudiness, has no well defined empirical data for its support and no working proven physics to support it.”
Some pretty supportive observations though, unlike AGW theory.
It only needs a few more years to confirm or rebut but in the meantime I recommend it as an area of investigation.

Paul Vaughan
October 8, 2012 10:22 am

markx (October 8, 2012 at 2:07 am) suggested:
“Sidorenkov etal may be the only ones looking in the right direction…..”

In the long run, solar cycle frequency/length changes centrally-limit terrestrial Antarctic ice specific mass & geomagnetic field jerks:
http://i49.tinypic.com/wwdwy8.png
For many geophysical variables, Earth’s response to solar input is nonlinear due to the volume, distribution, and state of water at and near the surface.
NASA JPL is reorienting to follow the Russian lead on this file.
There’s also a very bright group in Paris.

P. Solar
October 8, 2012 11:29 am

Paul Vaughan says: In the long run, solar cycle frequency/length changes centrally-limit terrestrial Antarctic ice specific mass & geomagnetic field jerks:
http://i49.tinypic.com/wwdwy8.png
What is the origin of that graph? What is that “solar cycle deceleration”? Looks pretty similar to the variation in length of day.

P. Solar
October 8, 2012 11:31 am

vukcevic says: … links.
most of those links and more are at the end of article I linked to at Climate etc. 😉

October 8, 2012 1:06 pm

P. Solar says: October 8, 2012 at 11:31 am
……
For some reason my pc is ‘allergic’ to Climate etc, it takes forever to load, even cooling fan goes to extra power. I avoid following links to (or on) the JC’s blog, since takes too long to return back where I started from.

P. Solar
October 8, 2012 11:39 pm

“For some reason my pc is ‘allergic’ to Climate etc, ”
That’s unfortunate, I think you’d find the article interesting. It looks at how the adjustments affect the frequency spectrum of the data.
It’s very odd that you have problems there. It’s hosted on the same WP platform as WUWT , has a lot less links and peripheral content and no ads. As a quick test, I just reloaded the CE page in question and this page (which is much shorter in comments). CE took 6s this page took 8s.
I usually open links in a new browser tab rather than going directly. That means “coming back” just involves changing tab or shutting down a tab. Much quicker and I don’t loose my place in the referring page.
Trying to understand all the supposed bias corrections, and corrections to the corrections, applied to hadSST3 is quite a paper chase. How many of their guesses about the nature and timing of equipment and sampling changes hit the mark I don’t know. But a lot of fairly broad assumptions seem to be involved.

P. Solar
October 8, 2012 11:58 pm

Nick Stokes says: “Another give-away is the stated average temp – about 20°C…. In fact, since average global temp is about 14°C and 3/4 of that is SST, something is wrong. I think it is that they are (in 1b) trying to average absolute temperatures rather than anomalies.”
Good point. That means the whole data set has a fairly significant geographical bias even at the end. These are based on “available data” in each plot. There is some infilling and project involved in the creating the 5×5 gridded data but these graphs apparently don’t include projecting infilling of areas with no data.
More coverage of Southern Ocean in recent period may explain why temperature time series curve down slightly in recent decades.

Paul Vaughan
October 9, 2012 9:00 pm

P. Solar (October 8, 2012 at 11:29 am) asked about http://i49.tinypic.com/wwdwy8.png :
“What is that “solar cycle deceleration”?”

Solar Cycle Deceleration = Rate of Change of Solar Cycle Length
Rate of Change of Solar Cycle Deceleration = Rate of Change of Rate of Change of Solar Cycle Length (i.e. 2nd derivative)
In this case I measured from sunspot numbers, but you could use other solar variables.
Use a complex wavelet (e.g. Paul or Morlet) to measure the cycle length as a function of time and then take derivatives. Tune the grain to something near Schwabe (~11 years) and the extent to something near 64 years. (You’ll find the results are robust even if you don’t tune carefully.) Cautionary Tip: You need to use a very, very, very wide support span to get good estimates of higher cycle length derivatives.

phlogiston
October 10, 2012 1:25 am

These data appear to confirm that recent warming of the oceans (i.e. of the planet) stopped around 2003.