Guest post by Bob Tisdale

THE INDIAN AND ATLANTIC OCEANS

INTRODUCTION

This post is a continuation of Part 1 – Satellite-Era Sea Surface Temperature Versus IPCC Hindcast/Projections. It examines the differences between multi-model mean of the IPCC 20C3M (Hindcast)/SRES A1B (Projection) for Sea Surface Temperatures and the observations using Reynolds OI.v2 Sea Surface Temperature (SST) anomalies, a satellite-based SST dataset. Part 1 covered the global oceans and the Pacific. This post discusses the Indian and Atlantic Oceans.

Note that Part 1 was updated with additional comparisons that started and ended during ENSO-neutral years. The update was added April 11, a day after the post was originally published. Refer to the discussion after Figure 17 in Part 1. The update also appeared in my April 11, 2011 at 5:48 pm comment in the cross post at Watt’s Up With That (Satellite-Era Sea Surface Temperature Versus IPCC Hindcast/Projections – Part 1). Using ENSO-neutral years for the start and end years did not have a major impact the divergence between the models and observations, so they won’t be considered in this post.

This post includes a discussion of the Atlantic Multidecadal Oscillation (AMO). If this topic is new to you, refer to An Introduction To ENSO, AMO, and PDO — Part 2

We’ll begin the post with the comparisons for the Indian Ocean. The Atlantic will then be discussed, with an emphasis on the North Atlantic.

INDIAN OCEAN

Like the Global Sea Surface Temperatures and those of the North and South Pacific basins, the linear trend of the IPCC Hindcast/Projection (multi-model mean) for the Indian Ocean Sea Surface Temperatures is significantly higher than the satellite-era observations. Refer to Figure 1. The model mean has a linear trend of approximately 1.6 deg C per Century, while the observations show a linear trend of only 0.9 deg C per Century.

Figure 1

We can separate the Indian Ocean data into east and west subsets, using 80E as the dividing longitude, then compare the trends on a latitudinal (zonal mean) basis. As discussed in Part 1, the zonal mean data in these posts are based on the SST anomalies for 5-degree latitude bands (80S to 75S, then 75S-70S, etc.), from pole to pole. The graphs present the linear trends of the SST data for those latitude bands in Deg C/Decade, with the data starting in January 1982 and ending in February 2011. Figure 2 shows how the model hindcasts/projections for the East and West Indian Ocean subsets both follow somewhat similar patterns, with higher linear trends in the tropics than at the high latitudes of the Southern Hemisphere.

Figure 2

But the trends of the observations show little similarities between the east and west portions of the Indian Ocean, Figure 3. South of 40S there are portions of the Indian Ocean that have cooled over this period, but the cooling was not forecast by the models. And note the warming in the East Indian Ocean between the latitudes of 60S and 45S. The model mean projections also failed to forecast it.

Figure 3

Figures 4 and 5 compare the observations and the model data for the West Indian and the East Indian subsets. They show how poorly the models hindcast/project the rise in Sea Surface Temperatures on a zonal-mean basis.

Figure 4

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Figure 5

In short, the model hindcast/projections of the rise in Indian Ocean Sea Surface Temperatures during the satellite era show no similarities to the observed rise.

ATLANTIC OCEAN

For the South Atlantic, the linear trend of the multi-model mean, Figure 6, is twice the observed linear trend. Note how the South Atlantic SST anomalies were basically flat from the late 1980s to 2008, yet the models show a nearly continuous rise. (Of course, that excludes the dips and rebounds in the early 1990s resulting from the eruption of Mount Pinatubo.)

Figure 6

The model hindcasts/projections for all of the basin subsets we’ve examined so far–the North and South Pacific, the Indian Ocean, and the South Atlantic–have all been significantly higher than the observed rise in Sea Surface Temperatures. The North Atlantic is the exception to this. Refer to Figure 7. The North Atlantic SST observations rose faster than the model mean. The models show a linear trend for the North Atlantic of approximately 1.6 deg C per Century, a trend that is similar to the other ocean basins. But the observed rise in the SST anomalies of the North Atlantic is approximately 2.5 deg C per Century.

Figure 7

And if we compare the trends for the models and observations on a zonal mean basis, the high latitudes of the North Atlantic have the greatest divergence.

Figure 8

The additional variability in the North Atlantic is not unusual. During the cooling period from 1944 to 1976, the mid-to-high latitudes of the North Atlantic showed the greatest cooling as well, Figure 9.

Figure 9

WHY ARE THE MODEL TRENDS FOR NORTH ATLANTIC LOWER THAN THE OBSERVATIONS DURING THE SATELLITE ERA?

The models do not consider the additional mode of natural variability in the North Atlantic known as the Atlantic Multidecadal Oscillation or AMO.

The AMO is typically illustrated with the North Atlantic SST anomalies detrended, but there are other ways to illustrate the additional variability. A simple way is to subtract Global SST anomalies from North Atlantic SST anomalies. Refer to Figure 10, which I’ve borrowed from the post An Introduction To ENSO, AMO, and PDO — Part 2″ href=”http://bobtisdale.wordpress.com/2010/08/16/an-introduction-to-enso-amo-and-pdo-part-2/”>An Introduction To ENSO, AMO, and PDO — Part 2. As illustrated, when smoothed with a 121-month running-average filter (commonly used for the AMO), the curve of the dataset that was created by subtracting the Global SST anomalies from the North Atlantic SST anomalies is very similar to the AMO data that’s calculated by detrending the North Atlantic SST anomalies. Note how both curves rose drastically from 1982 to present (the period illustrated in this post). The North Atlantic SST anomalies are responding to the additional natural mode of variability, and that additional variability is not included in the IPCC hindcasts/projections.

Figure 10

It is well known that the hindcasts/projections presented by the IPCC do not include the Atlantic Multidecadal Oscillation. Kevin Trenberth of the National Center for Atmospheric Research (NCAR) discussed this in his 2007 guest post at Nature.com, Climate Feedback: Predictions of climate. The third paragraph reads, “None of the models used by IPCC are initialized to the observed state and none of the climate states in the models correspond even remotely to the current observed climate. In particular, the state of the oceans, sea ice, and soil moisture has no relationship to the observed state at any recent time in any of the IPCC models. There is neither an El Niño sequence nor any Pacific Decadal Oscillation that replicates the recent past; yet these are critical modes of variability that affect Pacific rim countries and beyond. The Atlantic Multidecadal Oscillation, that may depend on the thermohaline circulation and thus ocean currents in the Atlantic, is not set up to match today’s state, but it is a critical component of the Atlantic hurricanes and it undoubtedly affects forecasts for the next decade from Brazil to Europe. Moreover, the starting climate state in several of the models may depart significantly from the real climate owing to model errors. I postulate that regional climate change is impossible to deal with properly unless the models are initialized.” [My caps]

The boldfaced sentence about the Atlantic Multidecadal Oscillation should also have included forecasts for Arctic Sea Ice, since Arctic Sea Ice is strongly impacted by the Sea Surface Temperatures of the North Atlantic.

LONG-TERM NORTH ATLANTIC SST OBSERVATIONS VERSUS INDIVIDUAL ENSEMBLE MEMBER HINDCAST/PROJECTIONS

The fact that the IPCC models are “not set up to match today’s state” of the Atlantic Multidecadal Oscillation has been known since 2007 when Nature published Kevin Trenberth’s guest post. The failure to properly model and present the AMO has impacted the differences between models and observations shown in Figures 7 and 8 and is likely the reason why the North Atlantic is the only ocean basin where the observed rise in SST anomalies exceeds the model projections. Refer to Table 1.

Table 1

I also wanted to see how the individual IPCC hindcasts/projections represented the AMO. Animation 1 is a .gif animation. It includes the HADISST-based Atlantic Multidecadal Oscillation, calculated as the North Atlantic SST anomalies minus Global SST anomalies. The 32 IPCC AR4 ensemble members that provided TOS (SST) data and that are available through the KNMI Climate Explorer are also presented, individually, in sequence. They are calculated the same way; that is, Global SST anomalies for each ensemble member are subtracted from their respective North Atlantic SST anomalies. (Note that I excluded ensemble member 18 since there was missing data and I did not want to track it down.) As you will note, some appear to create a multidecadal signal in the North Atlantic. Others do not. Some show the North Atlantic SST anomalies rising faster than Global SST anomalies, while in others it’s reversed, with Global SST anomalies rising faster than those of the North Atlantic. One thing is certain: There is little to no agreement among the climate models on the future state of the North Atlantic.

Animation 1

CLOSING

With the exception of the North Atlantic, the IPCC Sea Surface Temperature hindcasts/projections (multi-model mean) for the ocean basins have significantly higher linear trends than what has been observed during the satellite era. That is, since 1982, the Sea Surface Temperatures for the Indian, North and South Pacific, and South Atlantic have warmed much more slowly than projected by the models. The models have failed to capture the higher rise in North Atlantic SST anomalies because they do not include the additional natural variability that’s attributable to the Atlantic Multidecadal Oscillation.

The rises in the model-mean Sea Surface Temperatures also do not capture the observed changes on latitudinal (zonal mean) bases. This could strongly impact any regional forecasts made by the IPCC in AR4.

The failure of the model-mean hindcasts/projections to capture the observed rise, or lack thereof, in regional sea surface temperatures was also discussed in the post How Can Things So Obvious Be Overlooked By The Climate Science Community? It includes links to numerous posts that discuss the natural causes of the rise in Sea Surface Temperatures since 1982.

We often read statements by alarmists and climate scientists that “x” part of the globe is warming faster, or that some regional climate indicator is responding quicker, than projected by climate models. Looking back at the time-series and zonal-mean graphs presented in this series of posts, the model-mean sea surface temperature data does not come close to representing reality, so the inability of the models to project regional warming, or to project the correct timing of certain regional indicators, is not surprising and should be considered model failings, not signs of impending doom. Some might even view the facts that the models were not initialized to the observed state, that the models failed to replicate some ocean processes, and that other known ocean processes were intentionally excluded from the models as the means for the models to underestimate the impacts of those ocean states and processes on many regional climate indicators.

SOURCE

The data presented in this post is available through the KNMI Climate Explorer:

http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

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