While there’s news of ocean heat content in the Atlantic being pumped up by “leakage” from the Indian Ocean, and NOAA proclaims that La Niña is back, Bob Tisdale finds that the global ocean heat content trend since the turn of the 21st century is flat. Worse than that, it widely diverges from climate models predicting a continued rise in OHC.
2nd Quarter 2011 NODC Global OHC Anomalies
by Bob Tisdale
The NODC updated its Ocean Heat Content Anomaly data to include the 2nd quarter 2011 data. (And they also updated their Thermosteric Sea Level Anomaly data, which is not discussed in this post) I will provide a more detailed discussion as soon as the KNMI Climate Explorer is updated with the 2ndquarter 2011 Ocean Heat Content data, which should be later this month.
THE GRAPHS
Figure 1 is a time-series graph of the NODC Global Ocean Heat Content Anomalies from the start of the dataset (1st Quarter of 1955) to present (2nd Quarter of 2011). The quarterly data for the world oceans is available through the NODC in spreadsheet (.csv ) form (Right Click and Save As: Global OHC Data). While there was a significant increase in Global Ocean Heat Content over the term of the data, Global Ocean Heat Content has flattened in recent years.
Figure 1
And as many are aware, Climate Model Projections of Ocean Heat Content anomalies did not anticipate this flattening. Figure 2 compares the ARGO-era (2003 to present) NODC Global Ocean Heat Content anomalies to the GISS Model-E Projection of 0.7*10^22 Joules per year. The linear trend of the observations is approximately 7% of the trend projected by the model mean of the GISS Model-E.
Figure 2
The source of the 0.7*10^22 Joules per year GISS Model-E ensemble-mean trend was illustrated, clarified, and questioned in the post GISS OHC Model Trends: One Question Answered, Another Uncovered.
HOW MANY MORE YEARS UNTIL GISS MODEL-E CAN BE FOUND TO HAVE FAILED AS A PREDICTOR OF THE IMPACTS OF ANTHROPOGENIC GREENHOUSE GASES ON OCEAN HEAT CONTENT?
I asked the above question in Figure 2. It’s a rewording of the question asked by Roger Pielke Sr., in his post 2011 Update Of The Comparison Of Upper Ocean Heat Content Changes With The GISS Model Predictions. There he notes:
Joules resulting from a positive radiative imbalance must continue to be accumulated in order for global warming to occur. In the last 7 1/2 years there has been an absence of this heating. An important research question is how many more years of this lack of agreement with the GISS model (and other model) predictions must occur before there is wide recognition that the IPCC models have failed as skillful predictions of the effect of the radiative forcing of anthropogenic inputs of greenhouse gases and aerosols.
As far as I’m concerned, they have already failed for numerous reasons. I have illustrated and discussed in past posts how:
1. ENSO is responsible for much of the rise in Ocean Heat Content for many of the ocean basins,
And as far as I know, these are natural contributors to the rise that are overlooked by the GISS Model-E. This was further illustrated and discussed in Why Are OHC Observations (0-700m) Diverging From GISS Projections?
NOTES ABOUT THE ARGO-ERA GRAPH
There will be those who will attempt to dismiss the divergence between model projection and observations shown in Figure 2. Tamino tried to downplay the divergence in his post Favorite Denier Tricks, or How to Hide the Incline. I responded to Tamino with my post On Tamino’s Post “Favorite Denier Tricks Or How To Hide The Incline”. And there may be those who believe 2004 is a more appropriate year to use as the start of the ARGO-era OHC data, so for them, I illustrated how little difference it makes whether the ARGO-era starts in 2003 or 2004 in the post ARGO-Era Start Year: 2003 vs 2004. Note that there are two GISS Model-E projections illustrated in the sole graph in the post ARGO-Era Start Year: 2003 vs 2004. The one at 0.98*10^22 Joules per year, identified as Hansen/Pielke Sr., was found to be in error. This was discussed in the post GISS OHC Model Trends: One Question Answered, Another Uncovered.And of course, there is the fact that natural variables, which are not accounted for by the GISS Model-E, are major contributors to rise in Ocean Heat Content, as discussed in the four posts linked in the previous section.
DATASET INTRODUCTION
The NODC OHC dataset is based on the Levitus et al (2009) paper “Global ocean heat content(1955-2008) in light of recent instrumentation problems”, Geophysical Research Letters. Refer to Manuscript. It was revised in 2010 as noted in the October 18, 2010 post Update And Changes To NODC Ocean Heat Content Data. As described in the NODC’s explanation of ocean heat content (OHC) data changes, the changes result from “data additions and data quality control,” from a switch in base climatology, and from revised Expendable Bathythermograph (XBT) bias calculations.
AJ says: “If you look at my variance analysis, you will see that GISS-ER is arguably the worst performing model in terms of generating of reasonable likeness of the ARGO data.”
You’ve downloaded the GISS Model-ER ensemble members for OHC? If so, are they easy for you to work with? That is, can you look at only the top 700 or 750 meters? Can you easily create time series data on a monthly basis of individual ocean basins, or subsets of the ocean basins, similar to the ones used in the following post, for model-data comparisons?
http://bobtisdale.wordpress.com/2009/09/05/enso-dominates-nodc-ocean-heat-content-0-700-meters-data/
Bob T.,
Your criticism of the failure of model to predict short-term variability when it was at best designed to forecast long-term trends is at bit misplaced. It reminds me of those who were quick to jump on the bandwagon of claiming that 2007’s record low Arctic sea-ice minimum was an “outlier” event, as the supposed “recovery” in 2008 and 2009 proved. But, as this years proves, the longer-term trend always wins when it comes to climate. Come back in 20 years, and if OHC isn’t greater at that point than today, (and probably close to tracking the longer term models) then you might have something worth noting.
R. Gates says: “Your criticism of the failure of model to predict short-term variability when it was at best designed to forecast long-term trends is at bit misplaced.”
R. Gates, that was really creative. I don’t believe I’ve ever before seen an AGW proponent attempt to use that excuse. I commend you on your creativity. –But– Please advise what Hansen et al paper states that the GISS Model-ER for OHC was “designed to forecast long-term trends…” and not “predict short-term variability…” While you’re searching, you’ll likely come across Hansen et al (2005). I’ll save you some time. Here’s a link:
http://pubs.giss.nasa.gov/docs/2005/2005_Hansen_etal_1.pdf
Note the length of the comparison of OHC observations versus GISS Model-E ensemble members and model mean, Figure 2. It’s a whopping 11 years. The OHC model is, in reality, only hindcasting short-term [decadal plus] variability. And you’re criticizing me for only comparing 8 1/2 years? And while you’re on that page of the paper, examine Figure 3 closely. Notice how poorly the model ensemble member and model mean actually capture the zonal trends presented by the data during the decade-plus term used by Hansen et al (2005). Mysteriously, they make the following proclamation, “Yet the model runs contain essential features of observations…” Nonsense.
Last: if you haven’t noticed, most of my discussion of observations versus models in this post dealt with fact the natural variables have had a strong impact on OHC, yet GISS failed to include these variables in their models. I provided four links to past posts to illustrate this.
Bob… I downloaded 10 NetCDF files of model output of Potential Temperature. Each was from a separate model and was the first time series file for that model’s SRES A1B Scenario. At the time I was looking at seasonal signals in the data and wasn’t particularly interested in trend analysis, so I didn’t download additional time series. Besides, the files are huge, with a ten year series running about 1.5GB.
As for ease of use, that depends on what tools you use and if you know how to use them. I choose R, which I didn’t know a lick of when I first started looking at the data. So there was a learning curve. I ended up writing a function which returned a four dimensional array (longitude, latitude, depth, time) of temperature data. The parameters for this function included the east/west, north/south, upper/lower level, and start/end time bounds. So yes, what you are looking for is probably doable. Be aware though that the spatial resolution for each model is different, so if you want to compare apples to apples you will probably have to use an interpolation (spline) function.
BTW… thanks for answering my initial question.
Hello again Bob… I managed to post a few plots, which illustrate my initial comments about increased upwelling, heat pumps, etc. The trends are from 2005 to 2010.
http://sites.google.com/site/climateadj/argo-analysis
I don’t understand the technicalities of this so my question might be stupid.
I have a cousin who lives near Toronto on the shores of Lake Michigan. It was in summer and very warm. We went for a swim,
The top 5 feet of water were pleasantly warm. I was rash enough to go a little deeper and found the water unpleasantly cold.
Now there are no currents like the gulf stream in Lake Michigan so we are not talking oceans here.
But surely most of the heat in the oceans are in the top 100 meters or so?
Whu do the warmists want to go down to 700 or 1000 metres?
The question of “How many more years until GISS Model-E can be found to have failed as a predictor of the impacts of anthropogenic greenhouse gases on ocean heat content?” confuses the idea of a “prediction” with the idea of a “projection.” Though climatologists persistently confuse the two ideas, they are distinct. A “prediction” is an extrapolation to the outcome of a statistical event. A “projection” is a response function emanating from a model.
To maintain a distinction between the two ideas is crucial to assessment of the logic of an inquiry or lack of same. A prediction is an example of a proposition; as such it has a “truth-value,” that is, a variable that takes on the values “true” and “false.” A projection is not an example of a proposition and does not have a truth-value.
A model that makes predictions is falsifiable, thus lying in science. A model that makes only projections is not falsifiable, thus lying outside science. The fault of GISS Model-E is not that it has failed as a predictor, for it is not a predictor. Its fault is that it is not falsifiable, thus lying outside science.
Terry Oldberg says: “Though climatologists persistently confuse the two ideas,..”
AFAIC. Climate scientists can’t make the distinction and state the climate models are not falsifiable. To do so is to admit the models have little value.
Jim Petrie: There are subsurface ocean currents and there are ocean processes such as meridional overturning circulation and thermohaline circulation that carry surface waters to depth and back toward the surface again. The coupled ocean-atmosphere process of ENSO (El Nino-Southern Oscillation) also releases and recharges ocean heat content within the tropical Pacific, It distributes warm and cool anomalies from the tropical Pacific poleward to the extratropical North and South Pacific and into the tropical Indian Ocean. And through teleconnections, ENSO causes Ocean Heat Content to vary outside of the tropical Pacific.
Most of the variability in Ocean Heat Content takes place within the top 750 meters.
AJ, thanks.
No problem Bob… note that there was an issue in my trend plots where I interpolated past the North/South bounds of my sample. The trends at the latitudinal edges should be about half of what was plotted. I’ll fix that later.
Actually the trends were pretty well right after all. I removed the interpolation from my code so I won’t confuse myself again. It wasn’t needed anyway.
I knew Americans were geography-challenged, but this is ridiculous. Toronto is much of Lake Ontario, and all of Lake Erie, and then another 300-mile cross-country stroll, east of Lake Michigan. You’d have had a LOONNGG walk to get your swim.
The real “travesty” about all this is that people seem to have forgotten surface tension. the sea will not accept physical heat from the atmosphere at normal temperatures, only radiation. All the graphs back this up.