…A Reminder of How Horribly Climate Models Simulate the Surface Temperatures of Earth’s Oceans.
This post serves as the annual model-data comparison for sea surface temperatures.
INTRODUCTION
Oceans cover about 70% of the surface of the Earth, yet climate models are far from properly simulating the surface temperatures of those oceans on global, hemispheric and individual ocean-basin bases over the past 3 decades. In past annual model-data comparisons, we’ve used the multi-model mean of all of the climate models stored in the CMIP5 archive, but for this post we’re using only the average of the outputs of the 3 CMIP5-archived climate model simulations from the Goddard Institute of Space Studies (GISS) with the “Russell” ocean model. And in past model-data comparisons, we’ve used the NOAA’s original satellite-enhanced Reynolds OI.v2 sea surface temperature dataset, but for this one we’re using NOAA’s Extended Reconstructed Sea Surface Temperature version 4 (ERSST.v4) data.
Why the different models and data?
Both NASA GISS and NOAA NCEI use NOAA’s ERSST.v4 “pause buster” data for the ocean surface temperature components of their combined land-ocean surface temperature datasets, and, today, both agencies are holding a multi-agency press conference to announce their “warmest ever” 2016 global surface temperature findings. (Press conference starts at 11am Eastern.) And we’re using the GISS climate model outputs because GISS is part of that press conference and I suspect GISS is not to going to expose how horribly their climate models simulate this critical global-warming metric.
PRELIMINARY INFORMATION
The sea surface temperature dataset being used in this post is NOAA’s Extended Reconstructed Sea Surface Temperature dataset, version 4 (ERSST.v4), a.k.a. their “pause buster” data. As noted above, the ERSST.v4 data make up the ocean portion of the NOAA and GISS global land+ocean surface temperature products. The data presented in this post are from the KNMI Climate Explorer, where they can be found on the Monthly observations webpage under the heading of “SST”.
The GISS climate models presented are those stored in the Coupled Model Intercomparison Project, Phase 5 (CMIP5) archive. They are one of the latest generations of climate models from GISS and they were used by the IPCC for their 5th Assessment Report (AR5). The GISS climate model outputs of sea surface temperature are available through the KNMI Climate Explorer, specifically through their Monthly CMIP5 scenario runs webpage, under the heading of Ocean, ice and upper air variables. Sea surface temperature is identified as “TOS” (temperature ocean surface). I’m presenting the average of the GISS models identified as GISS-E2-R p1, GISS-E2-R p2 and GISS-E2-R p3, where the “R” stands for Russell ocean. (I’ll present the GISS models with HYCOM ocean model in an upcoming post.) The Historic/RCP8.5 scenarios are being used. The RCP8.5 scenario is the worst-case scenario used by the IPCC for their 5th Assessment Report. And once again we’re using the model mean because it represents the forced component of the climate models; that is, if the forcings used by the climate models were what caused the surfaces of the oceans to warm, the model mean best represents how the ocean surfaces would warm in response to those forcings. For a further discussion, see the post On the Use of the Multi-Model Mean, which includes a quote from Dr. Gavin Schmidt of GISS on the model mean.
The model-data comparisons are in absolute terms, not anomalies, so annual data are being presented. And the models and data stretch back in time for the past 30 years, 1987 to 2016.
The linear trends in the graphs are as calculated by EXCEL.
WHY ABSOLUTE SEA SURFACE TEMPERATURES INSTEAD OF ANOMALIES?
The climate science community tends to present their model-data comparisons using temperature anomalies, not absolute temperatures. Why? As Dr. Gavin Schmidt of GISS claims “…no particular absolute global temperature provides a risk to society, it is the change in temperature compared to what we’ve been used to that matters”. (See the post Interesting Post at RealClimate about Modeled Absolute Global Surface Temperatures.)
But as you’ll discover, globally, the GISS climate model simulations of sea surface temperatures are too warm. Now consider that the ocean surfaces are the primary sources of atmospheric water vapor, the most-prevalent natural greenhouse gas. If the models are properly simulating the relationship between sea surface temperatures and atmospheric water vapor, then the models have too much water vapor (natural greenhouse gas) in their atmospheres. That may help to explain why the GISS models simulate too much warming over the past 3 decades.
WHY THE PAST 3 DECADES?
The World Meteorological Organization’s (WMO) classic definition of climate is weather averaged over a 30-year period. On their Frequently Asked Questions webpage, the World Meteorological Organization asks and answers (My boldface):
What is Climate?
Climate, sometimes understood as the “average weather,” is defined as the measurement of the mean and variability of relevant quantities of certain variables (such as temperature, precipitation or wind) over a period of time, ranging from months to thousands or millions of years.
The classical period is 30 years, as defined by the World Meteorological Organization (WMO). Climate in a wider sense is the state, including a statistical description, of the climate system.
By presenting models and data for the past 3 decades, no one can claim I’ve cherry-picked the timeframe. We’re comparing models and data over the most recent climate-related period.
A NOTE ABOUT THE ABSOLUTE VALUES OF THE NOAA ERSST.v4 DATA
The revisions to NOAA’s long-term sea surface temperature datasets were presented in the Karl, et al. (2015) paper Possible artifacts of data biases in the recent global surface warming hiatus. There Tom Karl and others noted:
First, several studies have examined the differences between buoy- and ship-based data, noting that the ship data are systematically warmer than the buoy data (15–17). This is particularly important because much of the sea surface is now sampled by both observing systems, and surface-drifting and moored buoys have increased the overall global coverage by up to 15% (supplementary materials). These changes have resulted in a time-dependent bias in the global SST record, and various corrections have been developed to account for the bias (18). Recently, a new correction (13) was developed and applied in the Extended Reconstructed Sea Surface Temperature (ERSST) data set version 4, which we used in our analysis. In essence, the bias correction involved calculating the average difference between collocated buoy and ship SSTs. The average difference globally was −0.12°C, a correction that is applied to the buoy SSTs at every grid cell in ERSST version 4.
For model-data comparisons where anomalies are presented, shifting the more accurate buoy-based data up 0.12 deg C to match the ship-based data makes no difference to the comparison. This shortcut was a matter of convenience for NOAA since there are many more years of ship-based data than buoy-based data. However, when models and data are compared on an absolute basis, shifting the more accurate buoy-based data up 0.12 deg C to match the ship-based data makes a difference to the comparison. Because the model-simulated sea surface temperatures are too warm globally, this shortcut helps to better align the data with the models. And that sounds typical of climate science at NOAA.
In other words, the differences between models and data are likely greater than shown in all of the examples in this post where the modeled sea surface temperatures are warmer than observed…and vice versa when the models are too cool.
Enough of the preliminaries…
GLOBAL TIME-SERIES
Figure 1 presents two model-data comparisons for global sea surface temperatures, not anomalies, for the past 30-years. I’ve included a comparison for the global oceans (90S-90N) in the top graph and a comparison for the global oceans, excluding the polar oceans (60S-60N), in the bottom graph. Excluding the polar oceans doesn’t seem to make a significant difference. It’s obvious that global sea surfaces simulated by the GISS climate model were warmer than observed and that the GISS model warming rate is too high over the past 3 decades. The difference between modeled and observed warming rates is approximately 0.07 to 0.08 deg C/decade, more than 60% higher than the observed rate. And in both cases the 30-year average sea surface temperature as simulated by the GISS models is too high by about 0.6 deg C.
Figure 1 – Global Oceans
TIME SERIES – TROPICAL AND EXTRATROPICAL SEA SURFACE TEMPERATURES
In June of 2013, Roy Spencer presented model-data comparisons of the warming of the tropical mid-troposphere prepared by John Christy. See Roy’s posts EPIC FAIL: 73 Climate Models vs. Observations for Tropical Tropospheric Temperature and STILL Epic Fail: 73 Climate Models vs. Measurements, Running 5-Year Means. The models grossly overestimated the warming rates of the mid-troposphere in the tropics. So I thought it would be worthwhile, since the tropical oceans (24S-24N) cover 76% of the tropics and about 46% of the global oceans, to confirm that the models also grossly overestimate the warming of sea surface temperatures of the tropical oceans.
It should come as no surprise that the models did overestimate the warming of the sea surface temperatures of the tropical oceans over the past 30 years. See Figure 2. In fact, the models overestimated the warming by a wide margin. The data indicate the sea surface temperatures of the tropical oceans warmed at a not-very-alarming rate of 0.11 deg C/decade, while the models indicate that, if the surfaces of the tropical oceans were warmed by manmade greenhouse gases, they should have warmed at almost 2 times that rate, at 0.22 deg C/decade. For 46% of the surface of the global oceans (about 33% of the surface of the planet), the models doubled the observed warming rate.
Figure 2 – Tropical Oceans
And of course, for the tropical oceans, the model-simulated ocean surface temperatures are too warm by about 0.9 deg C.
For the extratropical oceans of the Southern Hemisphere (90S-24S), Figure 3, the observed warming rate is also extremely low at 0.06 deg C/decade. On the other hand, the climate models indicate that if manmade greenhouse gases were responsible for the warming of sea surface temperatures in this region, the oceans should have warmed at a rate of 0.14 deg C/decade, more than doubling that observed trend. The extratropical oceans of the Southern Hemisphere cover about 33% of the surface of the global oceans (about 23% of the surface of the planet) and the models double the rate of warming.
Figure 3 – Extratropical Southern Hemisphere
The models are too warm in the extratropical oceans of the Southern Hemisphere, by roughly 0.6 deg C.
And the climate models seem to get the warming rate of sea surface temperatures just right for the smallest portion of the global oceans, the extratropical Northern Hemisphere (24N-90N). See Figure 4. The extratropical oceans of the Northern Hemisphere cover only about 21% of the surface of the global oceans (about 15% of the surface of the Earth).
Figure 4 – Extratropical Northern Hemisphere
Curiously, the model-simulated surface temperatures are too cool in the extratropical oceans of the Northern Hemisphere. That won’t help their simulations of sea ice.
TIME SERIES – OCEAN BASINS
Figures 5 to 11 provide comparisons of modeled and observed sea surface temperatures for the individual ocean basins…without commentary. I’d take the comparisons of the Arctic and Southern Oceans (Figures 10 and 11) with a grain of salt…because the models and data may account for sea ice differently.
Figure 5 – North Atlantic
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Figure 6 – South Atlantic
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Figure 7 – North Pacific
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Figure 8 – South Pacific
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Figure 9 – Indian
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Figure 10 – Arctic
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Figure 11 – Southern
CLOSING
It would be nice to know what planet the climate models from GISS are simulating. It certainly isn’t the Earth.
We live on an ocean-covered planet, yet somehow the whens, there wheres, and the extents of the warming of the surfaces of our oceans seem to have eluded the climate modelers at GISS. In this post, we presented sea surface temperatures, not anomalies, for the past 3 decades and this has pointed to other climate model failings, which further suggest that simulations of basic ocean circulation processes in the models are flawed.
Depending on the ocean basin, there are large differences between the modeled and observed ocean surface temperatures. The actual ocean surface temperatures, along with numerous other factors, dictate how much moisture is evaporated from the ocean surfaces, and, in turn, how much moisture there is in the atmosphere…which impacts the moisture available (1) for precipitation, (2) for water vapor-related greenhouse effect, and (3) for the negative feedbacks from cloud cover. In other words, failing to properly simulate sea surface temperatures impacts the atmospheric component of the fatally flawed coupled ocean-atmosphere models from GISS.
PLUG FOR A FREE EBOOK
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