>…And It Will Be Exploited By Those Who Fail To Understand The Reasons For The Rise
UPDATE (January 22, 2010): Corrected typo in paragraph after Figure 11. 1956 should have read 1856.
UPDATE (November 10, 2009): For those who prefer decades in terms of ordinal instead of cardinal year names, the only impact it has on this post is the average temperatures in Table 1:
Table 1 in that form may appear a bit premature, but with the El Nino this winter, I don’t believe the 2000s will be cooler than the 1990s.
The rest of the post is unaffected. There will be bloggers who, in the next few months, will jump all over the cardinal decade of 2000 to 2009 being warmer than 1990 to 1999. In fact, I’ve already seen evidence of it.
For some visitors to this blog, this post will be a merging and rehashing of a few of my earlier posts. But this post is different in a very important way. I have attempted to simplify the discussion of El Nino-caused step changes for those with less technical backgrounds.
The post does assume the reader knows of El Nino and La Nina events. If not, here are links to two NOAA El Nino Frequently Asked Question web pages:
The following narrated video “Visualizing El Nino” from the NASA/Goddard Space Flight Center Scientific Visualization Studio provides an excellent overview of the 1997/98 E; Nino, one of the El Nino events that created the aftereffects illustrated in this post.
I have provided links to the referenced studies and to the posts that provide more detailed explanations at the end of the following. They do not appear within the general discussion of this post.
Many of the illustrations in the following are .gif animations, with 5- to 10-second pauses between cells.
GLOBAL TEMPERATURES THIS DECADE WILL BE THE WARMEST ON RECORD
It became apparent a number of years ago that the current decade, the 2000s, would have the highest surface temperature since the start of the instrument temperature record. Prior to now, the record decade for Global Surface Temperature Anomalies, Global Lower Troposphere Temperature (TLT) Anomalies, and Global Sea Surface Temperature (SST) anomalies had been the 1990s. Table 1 shows the average 1990s and 2000s (to date) temperature anomalies furnished by different suppliers, and the difference between the two decades. And with the end of this decade drawing near, one should expect to hear of this new record time and time again. There are those who will exploit this in the next few months and in the years to come. Those parties will, of course, blame anthropogenic greenhouse gases for the rise.
THOSE WHO TRUMPET THE ELEVATED TEMPERATURES WILL FAIL TO ACKNOWLEDGE THE NON-LINEAR RELATIONSHIP BETWEEN THE EL NINO-SOUTHERN OSCILLATION (ENSO) AND GLOBAL TEMPERATURES
There have been a number of recent research papers that have illustrated a linear relationship between El Nino-Southern Oscillation (ENSO) and global temperature. These papers contradict what is clearly visible in the instrument temperature record, and that is, that the relationship between ENSO and global temperature is non-linear. In a comparison of global temperatures and natural variables, the researchers scale one of the ENSO indices, and after adjusting for other natural variables such as solar irradiance and volcanic aerosols, the researchers claim the difference between those natural variables and global temperatures must be caused by the increase in anthropogenic greenhouse gases. A simplified example of these comparisons is shown in Figure 1; it compares global SST anomalies and scaled NINO3.4 SST anomalies, one of the ENSO indices. It also shows their linear trends. I’ve excluded volcanic aerosol and solar adjustments to simplify the illustration. Note how the Global SST anomaly trend is increasing while the NINO3.4 SST anomaly trend is decreasing. As noted earlier, there are those who would like you to believe that the difference in those trends is caused by anthropogenic greenhouse gases.
MULTIYEAR AFTEREFFECTS OF ENSO ARE VISIBLE AS STEP CHANGES IN THE SST RECORDS
The first dataset to be discussed is the sea surface temperature (SST) anomalies of the East Indian and West Pacific Oceans. This dataset represents approximately 25% of the global ocean surface area between 60S and 65N. A sizeable area, as can be seen in Figure 2.
Figure 2 also shows the location of the NINO3.4 region of the equatorial Pacific. Its coordinates are 5S-5N, 170W-120W. Climate change researchers use this and other similar datasets when studying the magnitudes of El Nino and La Nina events and how often those events occur. Meteorologists also monitor NINO3.4 SST anomalies and other ENSO indexes to help them forecast the impacts of the current event on regional climate, hurricanes, etc. The SST anomalies of the NINO3.4 area of the Pacific correlate well with global temperature measurements. That is, when the SST anomalies of the NINO3.4 area rise during an El Nino event, global SST anomalies, and global TLT anomalies, and global surface temperature anomalies typically rise by lesser amounts. Researchers assume this relationship is constant, that it is linear, but as will be shown in the following, it is not linear. The global response to La Nina events is not the same as it is to El Nino events. This will be clearer as the discussion progresses.
Keep in mind that it is not only the SST anomalies of the NINO3.4 that rise and fall during El Nino and La Nina events. As can be seen in the video “Visualizing El Nino” above, the SST anomalies entire tropical Pacific are impacted.
Of the 9 official El Nino events since November 1981 (the start year of the SST dataset used to illustrate the effect), only two of these specific major traditional El Nino events occurred, one in 1986/87/88 and the other in 1997/98. See Figure 3, which is a .gif animation of the time-series graph of NINO3.4 SST anomalies. The other significant traditional El Nino in 1982/83 was counteracted by the volcanic eruption of El Chichon.
Links to the individual cells of Figure 3:
Link to Figure 3 Cell A:
Link to Figure 3 Cell B:
Link to Figure 3 Cell C:
Something very curious happens in the East Indian and West Pacific area of the global oceans shown in Figure 2. The SST anomalies of the East Indian and West Pacific Oceans rise in steps in response to specific El Nino events. These particular El Nino events are major events that are traditional in nature, as opposed to El Nino Modoki (pseudo El Nino events), and they are also El Nino events that have not been impacted by explosive volcanic eruptions, such as El Chichon in 1982 and Mount Pinatubo in 1991.
Figure 4 is a .gif animation of two datasets presented in different ways. Cell A is a graph that compares the SST anomalies of the NINO3.4 region of the equatorial Pacific to the SST anomalies of the East Indian and West Pacific Oceans. The NINO3.4 SST anomalies have been scaled (multiplied by a factor of 0.2 in this case) so that the changes in them during the El Nino events of 1986/87/88 and 1997/98 are approximately the same magnitude as the responses in the East Indian and West Pacific Oceans. Note how the SST anomalies of the East Indian and West Pacific Oceans had little response to the 1982/83 El Nino. As discussed earlier, that El Nino was counteracted by the sunlight-blocking volcanic aerosols of the explosive eruption of El Chichon. Note also that there is a dip in the East Indian and West Pacific SST anomalies in 1991 and a rebound a few years later. That dip and rebound is caused by the eruption of Mount Pinatubo. In Cell B, linear trend lines have been added to the same datasets to show the relationship presented by researchers who assume the relationship between ENSO and global temperature is linear. The linear trends skew perspective and hide the actual cause of the rise in SST anomalies of the East Indian and West Pacific Oceans. In Cell C, I’ve included the average East Indian and West Pacific SST anomalies for the period before the 1986/76/88 El Nino, the period between the 1986/76/88 and 1997/98 El Nino events, and the period after the 1997/98 El Nino. These averages highlight the step changes that occurred in this portion of the global ocean. Again, these step changes are aftereffects of the 1986/87/88 and 1997/98 El Nino events.
Links to the individual cells of Figure 4:
Link to Figure 4 Cell A:
Link to Figure 4 Cell B:
Link to Figure 4 Cell C:
As you will note, the multiyear aftereffects aren’t true step changes. The SST anomalies for the East Indian and West Pacific Oceans don’t remain at the new higher temperatures indefinitely. They do, however, remain at higher levels (failing to respond fully to the La Nina) until the next series of lesser El Nino events drive the temperatures back up again, helping to maintain the higher levels. (The effects are easier to describe as step changes, which is why I refer to them that way.)
It is important to notice that the response of the East Indian and West Pacific Oceans to 1998/99/00 La Nina was not the same as the response to the El Nino that came before it. The SST anomalies for this area of the global oceans rose as would be expected in response to the El Nino, but it did not respond fully to the La Nina phase. Global SST response to La Nina events is not always the same as it is to El Nino events. And this difference between how Global SST responds to El Nino and La Nina events causes Global SST to rise.
These step changes in the East Indian and West Pacific Ocean SST anomalies are important for a number of reasons. First, the oceans represent approximately 70% of the surface area of the globe, and SST anomalies are included in the calculation of global surface temperature by GISS, Hadley Centre, and NCDC. Refer again to Table 1. In fact, the NCDC’s Optimum Interpolation SST dataset (OI.V2) used in Figure 4 has been included by the Goddard Institute for Space Studies (GISS) in their GISTEMP product since 1982. Second, these step changes are not reproduced by climate models. They also are not acknowledged by the scientific community–if they were, the papers listed at the end of this post would not illustrate a linear relationship between ENSO and global temperature. I have searched but have been unable to find any scientific paper that discusses these step changes. Third, the step changes bias the global SST anomalies upward and give the impression of a gradual increase in SST anomalies. This can be seen in a comparison graph of the SST anomalies of the East Indian and West Pacific Oceans, the SST anomalies of the “Rest of the World” (East Pacific, Atlantic, and West Indian Oceans), and the combination of the two, Figure 5. The period since 1996 is unique in the last 40+ years. There haven’t been any major volcanic eruptions to add noise to the data. This is why the data in Figure 5 starts in 1996.
Figure 5 (Note: The time period listed in Figure 5 is wrong. The data in that graph does not start in November 1981. It runs from January 1996 to September 2009.)
Note how in Figure 5 the East Indian and West Pacific SST anomalies linger at the elevated levels while the SST anomalies for the “Rest of the World” are mimicking the variability of the NINO3.4 SST anomalies, shown in Figure 3. (That is, the SST anomalies for the “Rest of the World” are responding as researchers expect to both El Nino and La Nina events.) Over the next few years, ocean currents “mix” the elevated SST anomalies of the East Indian and West Pacific Oceans with the depressed SST anomalies of the “Rest of the World” oceans, dropping one and raising the other, until they intersect in 2003. This is more than 4 years after the end of the 1997/98 El Nino. Because the Global SST anomalies are a combination of the two, they are biased upward by the elevated East Indian-West Pacific SST anomalies and by the mixing with the waters of the “Rest of the World”. This gives the false impression of a gradual increase in global SST anomalies.
In other words, the effects of the major traditional El Nino events can linger for at least 4 years, causing gradual increases in global sea surface temperatures during that time. This gradual increase is incorrectly attributed to anthropogenic sources.
These effects are also discussed and illustrated in my video “The Lingering Effects of the 1997/98 El Nino”.
MULTIYEAR AFTEREFFECTS OF ENSO ARE ALSO VISIBLE AS STEP CHANGES IN THE TLT RECORDS
Since 1979, two groups have analyzed the satellite-based Microwave Sounding Unit (MSU) radiometer data to determine atmospheric temperatures at different levels. These groups are Remote Sensing Systems (RSS) and the University of Alabama in Huntsville (UAH). We’ll be using the data from RSS in this discussion. One dataset, the Lower Troposphere Temperature (TLT) anomalies, correlate well with the global surface temperature anomalies determined from direct land and sea surface temperature observations.
Lower Troposphere Temperature (TLT) anomalies also show upward step changes in response to the significant traditional 1986/87/88 and 1997/98 El Nino events. And similar to the discussion of sea surface temperatures above, only a portion of the global TLT anomalies show clear signs of these upward steps. In this case, it’s the latitude band of 20N to 82.5N or the Mid-To-High Latitudes of the Northern Hemisphere. Refer to Figure 6 for the area of the globe included within these latitudes. It represents in the neighborhood of 33% of the global surface area.
The graph in Figure 7 compares the NINO3.4 SST anomalies to the Lower Troposphere Temperature (TLT) anomalies of the Mid-To-High Latitudes of the Northern Hemisphere. The scaled NINO3.4 SST anomalies are used again as a reference for the timing and magnitude of significant traditional El Nino events. As you can see, the TLT anomaly data for this area of the globe is noisy, but it is obvious that the TLT anomalies rose since 1979, a rise that is normally attributed to manmade greenhouse gases.
A common technique used to reduce data noise is to smooth it by calculating the average of a number of months before and after a given month, and to calculate this average for each month for the entire length of the dataset. (The same technique was used in Figure 5.) The TLT anomaly data in Figure 8 has been smoothed with a 13-month running average filter. Note how, when compare to Figure 7, there is much less noise in the smoothed data. Figure 8 is another .gif animation. It illustrates the TLT anomaly data for the Mid-To-High Latitudes of the Northern Hemisphere and the scaled NINO3.4 SST anomalies from different points of view. Cell A illustrates the data without any comments. Depending on your perspective, you can see a gradual rise in the TLT anomaly dataset that’s disrupted by ENSO events and volcanic eruptions or you can see three periods of relatively flat TLT anomalies that are punctuated by ENSO and volcanic eruptions with two major step increases caused by the 1986/87/88 and 1997/98 El Nino events. In Cell B, the impacts of the two major volcanic eruptions are noted. These are the 1982 eruption of EL Chichon and the Mount Pinatubo eruption in 1991. As with the SST data, the El Chichon eruption counteracted the impact of the 1982/83 El Nino. But the lesser El Nino in 1991/92 was no match for the Mount Pinatubo eruption, and TLT anomalies made a substantial drop. The TLT anomalies rebounded a few years later as the volcanic aerosols in the stratosphere dissipated. Cell C shows the positive linear trend of the TLT anomalies for the Mid-To-High Latitudes of the Northern Hemisphere and it shows the negative trend in the SST anomalies of the NINO3.4 region of the equatorial Pacific. The difference between the two, as discussed earlier, is attributed by researchers to anthropogenic greenhouse gases. However, the attribution is unfounded when the global data is broken down into smaller subsets. The heat released by significant El Nino events can and do cause step changes in the TLT anomalies of the Mid-To-High Latitudes of the Northern Hemisphere. This is clearly visible when the average temperatures before and after those significant El Nino events are displayed on the graph, Cell D.
Links to the individual cells of Figure 8:
Link to Figure 8 Cell A:
Link to Figure 8 Cell B:
Link to Figure 8 Cell C:
Link to Figure 8 Cell D:
It is primarily those two shifts in the Mid-To-High Latitude TLT Anomalies of the Northern Hemisphere that cause the upward trend in Global TLT Anomalies.
DO ANTHROPOGENIC GREENHOUSE GASES FUEL EL NINO EVENTS?
The source of heat for El Nino events is the Tropical Pacific, and there is no evidence that greenhouse gases have a significant effect on the Ocean Heat Content (OHC) anomalies of the Tropical Pacific. Refer to Figure 9. It is also a .gif animation. Cell A shows the comparison graph of Tropical Pacific OHC, scaled NINO3.4 SST anomalies, and scaled Sato Index of Stratospheric Aerosol Optical Thickness. The Sato Index data is presented to illustrate the timing of explosive volcanic eruptions. Like the other comparisons in this post, the NINO3.4 SST anomalies are used to illustrate the timing and magnitude of El Nino and La Nina events. The OHC dataset was created by the National Oceanographic Data Center (NODC). It presents OHC to depths of 700 meters. This OHC data was introduced with the Levitus et al (2009) paper “Global Ocean Heat Content 1955-2008 in light of recently revealed instrumentation problems”. Cell B highlights the two decade-long declines in Tropical Pacific OHC. Cell C calls attention to the upward surges (steps) in Tropical Pacific OHC that occurred during the multiyear La Nina events that followed the 1972/73 and 1997/98 El Nino events. And Cell D highlights a curious rise in Tropical Pacific OHC that occurred in the few years leading up to the 1997/98 El Nino. I have searched for but have not found any scientific paper that discusses this sudden surge that fueled the 1997/98 El Nino.
Links to the individual cells of Figure 9:
Link to Figure 9 Cell A:
Link to Figure 9 Cell B:
Link to Figure 9 Cell C:
Link to Figure 9 Cell D:
An additional note about Figure 9: Note how the OHC dips during the El Nino events and rebounds during the La Nina events. The El Nino discharges heat from the Tropical Pacific, and the La Nina recharges the heat. This is accomplished by variations in total cloud amount. If the La Nina is not being impacted by volcanic aerosols and if the La Nina lasts for more than one year, ocean heat content rises above its previous level, creating the upward step.
The changes in Tropical Cloud Amount Percentage mimic NINO3.4 SST anomalies. Refer to Figure 10. That is, when NINO3.4 SST anomalies rise, Tropical Pacific Cloud Amount increases, and when NINO3.4 SST anomalies drop during the La Nina phase, Tropical Pacific Cloud Amount decreases. Less cloud cover means more downward shortwave radiation (visible sunlight) is able to warm the Tropical Pacific. In Cell C of Figure 10, the sudden drop in Tropical Pacific Cloud Amount in 1995 is highlighted. As noted above, it appears this decline in cloud amount fueled the 1997/98 El Nino.
Links to the individual cells of Figure 10:
Link to Figure 10 Cell A:
Link to Figure 10 Cell B:
Link to Figure 10 Cell C:
NATURAL VARIATIONS IN THE NORTH ATLANTIC SST ALSO CONTRIBUTED TO THE DIFFERENCE IN GLOBAL TEMPERATURE BETWEEN THE 1990s AND THE 2000s
The SST anomalies of the North Atlantic Ocean are also impacted by another natural variable, the Atlantic Multidecadal Oscillation or AMO. The AMO is a semi-periodic variation (50 to 80 years) in the SST anomalies of the North Atlantic that has its basis in Thermohaline Circulation (THC) or Atlantic Meridional Overturning Circulation (AMOC). These variations are visible in the reconstruction of North Atlantic SST from 1567 to 1990, Figure 11. This dataset was created by Gray et al (2004) “Atlantic Multidecadal Oscillation (AMO) Index Reconstruction”. (IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series #2004-062. NOAA/NGDC Paleoclimatology Program, Boulder CO, USA.)
For the period of the instrument temperature record, the AMO is presented as detrended North Atlantic SST anomalies. Refer to Figure 12, which is also a .gif animation. Cell A of Figure 12 illustrates the AMO data calculated by the NOAA Earth System Research Laboratory (ESRL) from January 1856 to March 2009. The data has been smoothed with a 37-month filter to remove the noise. Cell B notes that the AMO is a naturally occurring variation in the SST anomalies of the North Atlantic. And Cell C illustrates the average AMO SST values for the 1990s and the 2000s. The difference between these two averages represents the contribution of the AMO to the rise in North Atlantic SST Anomalies from the 1990s to the 2000s. Keep in mind that, while the North Atlantic covers only a surface area that is approximately 15% of the global oceans, the AMO is also known to also impact the surface temperatures of Europe and North America and the SST of the Eastern Tropical Pacific.
Links to the individual cells of Figure 12:
Link to Figure 12 Cell A:
Link to Figure 12 Cell B:
Link to Figure 12 Cell C:
There is little doubt that the decade of the 2000s will have higher land surface, sea surface, and lower troposphere temperature anomalies than the 1990s. There will be those who will wrongly attribute the rise from decade to decade to anthropogenic greenhouse gases, when it is very apparent that the actual cause is the lingering effects of the 1997/98 El Nino event. Attempts will be made to contradict the obvious by those who fail to acknowledge or comprehend the multiyear aftereffects of significant traditional El Nino events. They will present numerous unfounded arguments. Here are a few that have been tried.
Argument 1: The short-term global warming of El Nino events are countered by the short-term global cooling of the La Nina events that follow them.
What The Instrument Temperature Record Shows: That’s true for only parts of the globe and for some El Nino events. It is not true, however, for the SST anomalies of the East Indian and West Pacific Oceans and for the TLT anomalies of the Mid-To-High Latitudes of the Northern Hemisphere. Refer to Figures 4 and 8. The effects of the 1986/87/88 and the 1997/98 El Nino lingered through the La Nina events that followed them in those datasets. This created the appearance of gradual rises in global SST and TLT anomalies.
Argument 2: Global warming caused by anthropogenic greenhouse gases is responsible for the increase in the number of major El Nino events since 1975. (This argument is normally made by someone referring to an ENSO Index that starts in 1950.)
What The Instrument Temperature Record Shows: There are multidecadal variations in the frequency and magnitude of ENSO events. This can be seen by smoothing the NINO3.4 SST anomalies from 1870 to 2009 with a 121-month filter. Refer to Figure 13. During epochs when the frequency and magnitude of El Nino events outweigh the frequency and magnitude of La Nina events, global temperatures rise. And during epochs when the frequency and magnitude of La Nina events outweigh the frequency and magnitude of El Nino events, global temperatures drop.
Argument 3: El Nino events don’t create heat.
What The Instrument Temperature Record Shows: During El Nino events, warm water that had been stored below the surface of the western tropical Pacific (in the Pacific Warm Pool) sloshes to the east and rises to the surface. Tropical Pacific SST anomalies increase in response. In this way, more heat than normal is released from the tropical Pacific to the atmosphere. But El Nino events not only release heat into the atmosphere, they also shift atmospheric circulation patterns (Hadley and Walker Circulation, surface winds, cloud cover). These shifts in the circulation patterns and cloud cover cause surface temperatures and OHC outside of the tropical Pacific to rise.
It is important to note that the vast majority of the warm water that sloshes east during the El Nino had been stored below the surface before the El Nino. While below the surface (to depths of 300 meters) it was not included in the instrument temperature record. But during the El Nino, that warm water has been relocated to the surface and is included in the surface temperature record. So, El Nino events relocate warm water from an area that was not included in the calculation of global temperature to the surface where it is included.
Argument 4: Climate models used by the IPCC reproduce these El Nino-induced step changes.
What The Climate Models Show: Most of the climate models (GCMs) used by the IPCC in AR4 for hindcasting 20th Century climate do not bother to model ENSO. Those that make the effort do not model it well. The frequency, magnitudes, linear trends, and multiyear aftereffects of those models do not match the surface temperature record. The step changes that exist in the instrument temperature record, which are the bases for the much of the rises in global temperatures, do not exist in the model outputs of the 20th century.
If and when GCMs can reproduce the past frequency and magnitude of ENSO events, if and when GCMs can reproduce the multiyear aftereffects of ENSO events, which are these El Nino-induced step changes (including the ones that also appear in the OHC records), then GCMs may have some predictive value. At present they cannot reproduce ENSO or its multiyear aftereffects. At present they have no value.
This failure of GCMs to properly account for the multiyear impacts of major El Nino events (and other natural variables such as the North Atlantic Oscillation) can be seen in a graph of the actual rise in global OHC versus the projected rise forecast by GISS, Figure 14. The GCM used by GISS based its projection on the rise in Ocean Heat Content during the 1990s, assuming the trend would continue at that pace. But during the 1990s, the vast majority of the rise in OHC was caused by the combined effects of ENSO and the North Atlantic Oscillation, and these are natural variables that the GISS GCM did not model. Since 2003, Global Ocean Heat Content has been relatively flat, while the GISS projection reaches to unrealized levels.
LINKS TO MORE DETAILED DISCUSSIONS
The upward step changes in the SST anomalies of the East Indian and West Pacific Oceans were discussed in the following posts:
1.Can El Nino Events Explain All of the Global Warming Since 1976? – Part 1
2.Can El Nino Events Explain All of the Global Warming Since 1976? – Part 2
And I discussed the step changes in the Mid-To-High Latitudes of the Northern Hemisphere in the post RSS MSU TLT Time-Latitude Plots…Show Climate Responses That Cannot Be Easily Illustrated With Time-Series Graphs Alone.
The erroneous assumption that the relationship between ENSO and global temperatures is linear was discussed in the following posts:
1.Multiple Wrongs Don’t Make A Right, Especially When It Comes To Determining The Impacts Of ENSO
2.Regression Analyses Do Not Capture The Multiyear Aftereffects Of Significant El Nino Events
3.The Relationship Between ENSO And Global Surface Temperature Is Not Linear
This link discusses and illustrates that El Nino Events Are Not Getting Stronger.
The impacts of natural variables (ENSO and NAO) on Ocean Heat Content were discussed in the following posts:
1.ENSO Dominates NODC Ocean Heat Content (0-700 Meters) Data
2.North Atlantic Ocean Heat Content (0-700 Meters) Is Governed By Natural Variables
3.NODC Corrections to Ocean Heat Content (0-700m) Part 2
Refer also to La Nina Events Are Not The Opposite Of El Nino Events.
The curious drop in cloud amount in 1995 and its possible impact on the 1997/98 El Nino is discussed further in Did A Decrease In Total Cloud Amount Fuel The 1997/98 El Nino?
LINK TO LEVITUS ET AL (2009)
I referred to the Levitus et al (2009) paper “Global Ocean Heat Content 1955-2008 in light of recently revealed instrumentation problems”. Here’s a link to the paper:
PAPERS THAT PORTRAY A LINEAR RELATIONSHIP BETWEEN ENSO AND GLOBAL TEMPERATURES
In a good portion of this post, I’ve illustrated that the relationship between ENSO and global temperatures is not linear. The following is a list of papers that portray a linear relationship even though the instrument temperature record indicates otherwise. There are likely more of them in existence, and there will likely be more of them in the future.
Lean and Rind (2008), How Natural and Anthropogenic Influences Alter Global and Regional Surface Temperatures: 1889 to 2006
Lean and Rind (2009), How Will Earth’s Surface Temperature Change in Future Decades? http://pubs.giss.nasa.gov/docs/2009/2009_Lean_Rind.pdf
Santer, B.D., Wigley, T.M.L., Doutriaux, C., Boyle, J.S., Hansen, J.E., Jones, P.D., Meehl, G.A., Roeckner, E., Sengupta, S., and Taylor K.E. (2001), Accounting for the effects of volcanoes and ENSO in comparisons of modeled and observed temperature trends
Thompson, D. W. J., J. J. Kennedy, J. M. Wallace, and P. D. Jones (2008), A large discontinuity in the mid-twentieth century in observed global-mean surface temperature
Thompson et al (2009), Identifying signatures of natural climate variability in time series of global-mean surface temperature: Methodology and Insights
Trenberth, K.E., J.M.Caron, D.P.Stepaniak, and S.Worley, (2002), Evolution of El Nino-Southern Oscillation and global atmospheric surface temperatures
Wigley, T. M. L. (2000), ENSO, volcanoes, and record-breaking temperatures
OI.v2 SST data is available through the NOAA NOMADS website:
Sato Index data is available from GISS:http://data.giss.nasa.gov/modelforce/strataer/tau_line.txt
The AMO data is available through the NOAA ESRL website:
The RSS TLT data is available here:http://www.remss.com/data/msu/monthly_time_series/RSS_Monthly_MSU_AMSU_Channel_TLT_Anomalies_Land_and_Ocean_v03_2.txt
HADISST data (Used in Figure 13) NODC OHC data and ISCCP Total Cloud Amount data is available through the KNMI Climate Explorer website:
The data for the North Atlantic SST Reconstruction is available through the NCDC’s World Data Center for Paleoclimatology:
For those who want to verify the outputs of the GCMs used by the IPCC, refer to the KNMI Climate Explorer webpage here: