A Quick Look at the HADGEM2-ES Simulations of Sea Surface Temperatures

There’s been an online disagreement between skeptics and the UKMO in recent days.  See Bishop Hill’s post here, and Nic Lewis’s full discussion here.  Nic’s discussion was also referenced in David Rose’s article in the Mail on Sunday.  The UKMO’s response to David’s article is here.

I was asked to take a look at how well (better written: how poorly) the HADGEM2-ES simulates sea surface temperatures.

For the first few comparisons, we’ll be examining the Reynolds OI.v2 sea surface temperature data (anomalies) and model mean of the HADGEM2-ES’s 3 ensemble members for the satellite era; i.e., the period of January, 1982 to August, 2013.  During this period, the model outputs include historic simulations (hindcasts) through 2005 and projections from 2006 to 2013. I’ve used the RCP6.0 scenario for projections because it’s close to the A1B scenario that was popular in past IPCC reports.

Let’s start with Global sea surface temperature data and the model simulations of it.

GLOBAL

The model mean of the HADGEM2-ES more than doubles the warming rate of the observed global sea surface temperatures from January, 1982 to August, 2013.  See Figure 1.

Figure 1

Figure 1

PACIFIC OCEAN

For the model-data comparison of the Pacific (60S-65N, 120E-80W), see Figure 2.  The HADGEM2-ES simulated a warming rate of about 0.19 deg C/ decade for the sea surface temperature of the Pacific from January, 1982 to August, 2013, but the observed Pacific sea surface temperatures warmed at a rate that was less than 1/3 of the rate guesstimated by the UKMO’s HADGEM2-ES.

Figure 2

Figure 2

Also, apparently the UKMO didn’t get the memo that the sea surface temperatures of the Pacific Ocean stopped warming 2 decades ago. See Figure 3.

Figure 3

Figure 3

The Pacific Ocean covers more of the surface of the Earth than all of the continental land masses combined.  When you look at a globe or a global map, it’s the big blue thing (see Figure 4) that stretches almost half way around the globe at the equator.  It’s difficult to miss. Maybe the UKMO is simulating the Pacific Ocean on some other planet, where sea surface temperatures are warmed by manmade greenhouse gases.

Figure 4 pacific_ocean

Figure 4

The map of the Pacific Ocean is available from mapsof.net.

MULTIDECADAL VARIABILITY

We examined the multidecadal variations in the sea surface temperature anomalies of the North Atlantic and North Pacific in a recent post: Multidecadal Variations and Sea Surface Temperature Reconstructions.

In the following graphs, we’re presenting the UKMO’s new and improved HADSST3 data and the HADGEM2-ES simulations of sea surface temperatures for the Northern Hemisphere.  In the graphs, the models and data have been detrended over the period of January 1870 to June 2013.  The data and models have been smoothed with 61-month filters to reduce the large variations caused by El Niño and La Niña events.

In Figure 5, it’s very obvious that the HADGEM2-ES model mean does not fully capture the cooling that took place from the late 1870s to 1910, and, as a result, they underestimate the warming that occurred from 1910 to the early 1940s.  Over the second “cycle”, the HADGEM2-ES model mean cools and rebounds about a decade earlier than the observations.  All in all, the HADGEM2-ES does show multidecadal variability, though it’s out of synch with the real world.

Note also that the data appears as though it may have peaked about 2004/05, while the models continue warming on their merry ways.

Figure 5

Figure 5

Do the models continue to show multidecadal variations into the future?  Nope.  See Figure 6.

Figure 6

Figure 6

And for those concerned that the model mean presents an average and therefore doesn’t fully capture the multidecadal variations of the individual ensemble members, see Figure 7, 8, and 9.

Figure 7

Figure 7

# # #

Figure 8

Figure 8

# # #

Figure 9

Figure 9

The individual simulations are poor representations of the sea surface temperatures, and as a result, so is the model mean.  The average of bad simulations is not going to be a good simulation—no matter how hard the climate science community believes an average will be a good representation.  The average simply smooths out the inherent internal noises within the models—noises that are not true representations of coupled ocean-atmosphere processes.

SOURCE

The data and model outputs are available through the KNMI Climate Explorer.

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About Bob Tisdale

Research interest: the long-term aftereffects of El Niño and La Nina events on global sea surface temperature and ocean heat content. Author of the ebook Who Turned on the Heat? and regular contributor at WattsUpWithThat.
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