Guest Post by Willis Eschenbach [see update at the end]

How much is a “Whole Little”? Well, it’s like a whole lot, only much, much smaller.

There’s a new paper out. As usual, it has a whole bunch of authors, fourteen to be precise. My rule of thumb is that “The quality of research varies inversely with the square of the number of authors” … but I digress.

In this case, they’re mostly Chinese, plus some familiar western hemisphere names like Kevin Trenberth and Michael Mann. Not sure why they’re along for the ride, but it’s all good. The paper is “Record-Setting Ocean Warmth Continued in 2019“. Here’s their money graph:

Figure 1. Original Caption: “Fig. 1. (a) Upper 2000 m OHC from 1955 through 2019. The histogram represents annual anomalies (units: ZJ), wherein positive anomalies relative to a 1981−2010 baseline are shown as red bars and negative anomalies as blue. The two black dashed lines are the linear trends over 1955–86 and 1987−2019, respectively.”

Now, that would be fairly informative … except that it’s in zettajoules. I renew my protest against the use of zettajoules for displaying or communicating this kind of ocean analysis. It’s not that they are not accurate, they are. It’s that nobody has any idea what that actually means.

So I went to get the data. In the paper, they say:

The data are available at http://159.226.119.60/cheng/ and www.mecp.org.cn/

The second link is in Chinese, and despite translating it, I couldn’t find the data. At the first link, Dr. Cheng’s web page, as far as I could see the data is not there either, but it says:

Climate Data Guide (UCAR) has a webpage hosting IAP gridded temperature data, OCEAN TEMPERATURE ANALYSIS AND HEAT CONTENT ESTIMATE FROM INSTITUTE OF ATMOSPHERIC PHYSICS

When I went to that link, it says “Get Data (external)” … which leads to another page, which in turn has a link … back to Dr. Cheng’s web page where I started.

Ouroborous wept.

At that point, I tossed up my hands and decided to just digitize Figure 1 above. The data may certainly be available somewhere between those three sites, but digitizing is incredibly accurate. Figure 2 below is my emulation of their Figure 1. However, I’ve converted it to degrees of temperature change, rather than zettajoules, because it’s a unit we’re all familiar with.

Figure 2. Cheng et al Figure 1 converted to degrees Celsius. The error bars (dark black lines) are also from Figure 1, although you’ll need a magnifying glass to read them in their figure.

So here’s the hot news. According to these folks, over the last sixty years, the ocean has warmed a little over a tenth of one measly degree … now you can understand why they put it in zettajoules—it’s far more alarming that way.

Next, I’m sorry, but the idea that we can measure the temperature of the top two kilometers of the ocean with an uncertainty of ±0.003°C (three-thousandths of one degree) is simply not believable. For a discussion of their uncertainty calculations, they refer us to an earlier paper here, which says:

When the global ocean is divided into a monthly 1°-by-1° grid, the monthly data coverage is <10% before 1960, <20% from 1960 to 2003, and <30% from 2004 to 2015 (see Materials and Methods for data information and Fig. 1). Coverage is still <30% during the Argo period for a 1°-by-1° grid because the original design specification of the Argo network was to achieve 3°-by-3° near-global coverage (42).

The “Argo” floating buoy system for measuring ocean temperatures was put into operation in 2005. It’s the most widespread and accurate source of ocean temperature data. The floats sleep for nine days down at 1,000 metres, and then wake up, sink down to 2,000 metres, float to the surface measuring temperature and salinity along the way, call home to report the data, and sink back down to 1,000 metres again. The cycle is shown below.

It’s a marvelous system, and there are currently just under 4,000 Argo floats actively measuring the ocean … but the ocean is huge beyond imagining, so despite the Argo floats, more than two-thirds of their global ocean gridded monthly data contains exactly zero observations.

And based on that scanty amount of data, which is missing two-thirds of the monthly temperature data from the surface down, we’re supposed to believe that they can measure the top 651,000,000,000,000,000 cubic metres of the ocean to within ±0.003°C … yeah, that’s totally legit.

Here’s one way to look at it. In general, if we increase the number of measurements we reduce the uncertainty of their average. But the reduction only goes by the square root of the number of measurements. This means that if we want to reduce our uncertainty by one decimal point, say from ±0.03°C to ±0.003°C, we need a hundred times the number of measurements.

And this works in reverse as well. If we have an uncertainty of ±0.003°C and we only want an uncertainty of ±0.03°C, we can use one-hundredth of the number of measurements.

This means that IF we can measure the ocean temperature with an uncertainty of ±0.003°C with 4,000 Argo floats, we could measure it to one decimal less uncertainty, ±0.03°C, with a hundredth of that number, forty floats.

Does anyone think that’s possible? Just forty Argo floats, that’s about one for each area the size of the United States … measuring the ocean temperature of that area down 2,000 metres to within plus or minus three-hundredths of one degree C? Really?

Heck, even with 4,000 floats, that’s one for each area the size of Portugal and two kilometers deep. And call me crazy, but I’m not seeing one thermometer in Portugal telling us a whole lot about the temperature of the entire country … and this is much more complex than just measuring the surface temperature, because the temperature varies vertically in an unpredictable manner as you go down into the ocean.

Perhaps there are some process engineers out there who’ve been tasked with keeping a large water bath at some given temperature, and how many thermometers it would take to measure the average bath temperature to ±0.03°C.

Let me close by saying that with a warming of a bit more than a tenth of a degree Celsius over sixty years it will take about five centuries to warm the upper ocean by one degree C …

Now to be conservative, we could note that the warming seems to have sped up since 1985. But even using that higher recent rate of warming, it will still take three centuries to warm the ocean by one degree Celsius.

So despite the alarmist study title about “RECORD-SETTING OCEAN WARMTH”, we can relax. Thermageddon isn’t around the corner.

Finally, to return to the theme of a “whole little”, I’ve written before about how to me, the amazing thing about the climate is not how much it changes. What has always impressed me is the amazing stability of the climate despite the huge annual energy flows. In this case, the ocean absorbs about 6,360 zettajoules (10^21 joules) of energy per year. That’s an almost unimaginably immense amount of energy—by comparison, the entire human energy usage from all sources, fossil and nuclear and hydro and all the rest, is about 0.6 zettajoules per year …

And of course, the ocean loses almost exactly that much energy as well—if it didn’t, soon we’d either boil or freeze.

So how large is the imbalance between the energy entering and leaving the ocean? Well, over the period of record, the average annual change in ocean heat content per Cheng et al. is 5.5 zettajoules per year … which is about one-tenth of one percent (0.1%) of the energy entering and leaving the ocean. As I said … amazing stability.

And as a result, the curiously hubristic claim that such a trivial imbalance somehow perforce has to be due to human activities, rather than being a tenth of a percent change due to variations in cloud numbers or timing, or in El Nino frequency, or in the number of thunderstorms, or a tiny change in anything else in the immensely complex climate system, simply cannot be sustained.

Regards to everyone,

w.

h/t to Steve Milloy for giving me a preprint embargoed copy of the paper.

PS: As is my habit, I politely ask that when you comment you quote the exact words you are discussing. Misunderstanding is easy on the intarwebs, but by being specific we can avoid much of it.

[UPDATE] An alert reader in the comments pointed out that the Cheng annual data is here, and the monthly data is here. This, inter alia, is why I do love writing for the web.

This has given me the opportunity to demonstrate how accurate hand digitization actually is. Here’s a scatterplot of the Cheng actual data versus my hand digitized version.

The RMS error of the hand digitized version is 1.13 ZJ, and the mean error is 0.1 ZJ.

Share this: Print

Email

Twitter

Facebook

Pinterest

LinkedIn

Reddit



Like this: Like Loading...