Going out on a limb and sawing it off

Dr Kevin Trenberth lead author of “Observations: Surface and Atmospheric Climate Change” in the 2007 IPCC report is reported to have emailed colleagues to say (my italics):

1.  ‘The fact is we can’t account for the lack of warming at the moment and it is a travesty that we can’t.’

2. ‘How come you do not agree with a statement that says we are no where close to knowing where energy is going or whether clouds are changing to make the planet brighter. We are not close to balancing the energy budget. The fact that we can not account for what is happening in the climate system makes any consideration of geoengineering quite hopeless as we will never be able to tell if it is successful or not! It is a travesty!’

Kevin Trenberth and the UNIPCC have enthusiastically promoted the notion of impending climate disaster. But when Kevin Trenberth admits to colleagues that he can’t explain what is going on, we should thank him for his candor, put aside the message, defer planned legislation, cancel attendance at international meetings and take a good hard look at the possible causes of climate change.

The ‘Anthropogenic Global Warming’ mechanism is plainly in trouble. What else is at hand?

Atmospheric shifts
Trends in tropical and global temperature are dictated by change in the electromagnetic forces governing the distribution of the atmosphere.  The atmosphere can shift from high to low latitudes or vice versa over any time interval. Atmospheric pressure governs the strength of polar vortex activity. Vortex activity determines the flow of nitrous oxides from the mesosphere that govern the concentration of ozone and therefore the temperature of the upper atmosphere. When the temperature of the upper atmosphere changes, so does the concentration of reflective ice crystals, so changing the porosity of the atmospheric filter that determines how much sunlight reaches the surface.

Change in the distribution of the atmosphere is continuous. Such a change initiated the celebrated climate shift of 1978 that was followed by thirty years of warming. But a mini-shift occurs once or twice each year, whenever the polar atmosphere warms in the middle of the polar night. Regardless of the time scale, the result is the same. The warming of the polar stratosphere initiates a period when more sunlight gets through the atmospheric medium to warm the surface of the planet.

Regulation of stratospheric ozone

A low pressure regime at the pole weakens the polar vortex. A high pressure regime strengthens the vortex. If the vortex weakens, ozone levels increase and the air warms. This is a direct consequence of a slower flow of nitrous oxides from the mesosphere. These compounds are hungry for oxygen.

Surface temperature follows that of the upper atmosphere

The ozone content of the upper atmosphere determines its temperature. Ozone absorbs UVB from the sun and Infrared from the Earth. The stratosphere represents the temperature inversion to top all temperature inversions. This is a classic greenhouse gas warming scenario. But the mechanism whereby temperature increases aloft to cause temperature to increase below has nothing to do with back radiation. That simply doesn’t work against the countervailing force of convection. No, it’s to do with ice cloud. Ice cloud density changes when the temperature of the upper atmosphere changes. This is very likely the factor that modulates the flow of solar radiation to the surface of the earth.  Manifestly, surface temperature closely follows that of the upper atmosphere as is clearly evident in figure 1. We don’t have to know how it works to appreciate the dependence of surface temperature on the temperature of the upper atmosphere. We jump in the car, move the lever to ‘first gear’, let out the ‘clutch’ and off we go. Indeed, it’s a big surprise when it doesn’t happen that way. Driving a motor car is an act of faith. We can understand the climate system and predict the near future on the basis of the linkages described above .

Inspecting figure 1, we can see that, patently, 200hpa temperature (about 10km in elevation) varies much more than surface temperature. About 1978 the temperature of the air at 200hpa stepped up to a new plateau in the space of just a few years. Since that time, 200hpa temperature has been in slow decline while sea surface temperature has continued to exceed the period mean. It hasn’t risen much but nor has it fallen by very much. Short term variation in surface temperature is a much dampened version of temperature gyrations in the upper atmosphere with change initiated from above rather than below. Change in the temperature of the upper atmosphere leads the surface.

The ice cloud region stretches from a few kilometers to 20 or more in altitude. It is therefore far more extensive and it seems, more influential, than the near Earth cloud zone that is composed of water droplets. Unlike water droplets, microscopic ice crystals are near invisible and very hard to detect from satellites or from the surface. But the evidence of changing sea surface temperature tells us what we need to know.

Figure 1

Source: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

Pressure and temperature are intimately related

When air pressure drops at the pole it increases at low latitudes. Figure 2 shows that there is a strong relationship between surface pressure at the equator and sea surface temperature. Pressure is plainly the independent, more volatile, variable and there is frequently a short lag in the temperature response. The climate shift of 1978 that initiated strong warming is apparent in both series. The cooling process that set in after 1998 is plainly associated with declining atmospheric pressure at the equator.

Figure 2

Source: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

Effect of an atmospheric shift on the temperature of the tropical upper atmosphere

A major stratospheric warming in the Arctic in January-February 2009, as seen in figure 3, is associated with a simultaneous fall in the temperature of the tropical (25N to 25S) stratosphere, as seen in figure 5. I suggest that the fall in the temperature of the tropical stratosphere is associated with the outward movement of the zone of direct heating of the atmosphere by incoming short wave radiation as atmospheric pressure rises at the equator.

A sudden stratospheric warming at the winter pole influences month to month weather elsewhere because it is related to an increase in ozone content.  See figures 7-14 at http://climatechange1.wordpress.com/2009/03/08/the-atmosphere-dancing-in-the-solar-wind-el-nino-shows-his-face/, where the increase in ozone is carefully documented.

Episodic sudden stratospheric warming does not change climate. It is the change in the distribution of the atmosphere that persists over longer time periods that changes the climate.

Figure 3 shows that after 1979, the Arctic stratosphere has shown marked variability in temperature between October and April (black lines).  While the lower bounds of the temperature curve show a positive anomaly in December and January this curve is otherwise about where we would expect it to be. It is dictated by the tilt of the Earths axis and its rotation about the sun.  However, the upper boundary of the thermal range shows marked anomalous warming between November and March including a dramatic increase in December. This is in the middle of the polar night.

Figure 3

Source: http://www.cpc.ncep.noaa.gov/products/stratosphere/temperature/

Figure 4 shows evidence of enhanced variability in the temperature of the southern vortex between April and February with peak anomalies centered in August and September (black lines). By contrast, the range is very restricted in the late summer and autumn months February, March and April.

Figure 4

Source: http://www.cpc.ncep.noaa.gov/products/stratosphere/temperature/

Figure 5 shows that cooling of the tropical stratosphere occurs between November and March with the most intense cooling in November and December. The Earth is closest to the sun in January and this is when temperature at 1hPa should be warmest. A decline in temperature at 1hpa between November and March is anachronistic. It can only be due to a shift in the atmosphere.

Figure 5

Source: http://www.cpc.ncep.noaa.gov/products/stratosphere/temperature/

My last post ‘The climate Engine’ showed that the difference between the pre 1978 cooling mode and the post 1978 warming mode was a marked increase in the temperature of the stratosphere peaking in September in Antarctica and February in the Arctic. See figures 6 and 7 as re-numbered for this post. How do I reconcile the fact that the evidence in figure 5 suggests that the peak period for the gain in atmospheric pressure in the tropics lies, not in September or February, but midway between the two in November and December.  Naturally, if the poles are suffering a simultaneous depletion, as they do when surface pressure drops simultaneously at both poles the atmosphere can pile up only in the tropics. There is nowhere else for it to go.

The upshot of this analysis is that shifts in the atmosphere are responsible for an increase in the temperature of the upper atmosphere with peak warming occurring between August and February. This feeds through to sea surface temperature. The southern hemisphere experiences a warmer spring and summer in consequence. The vast expanse of the southern ocean absorbs the energy. In the cooling scenario it is the southern oceans that suffer a depletion in energy supply. That is simply a function of the time of year when the polar stratosphere warms. This is consistent with earlier bud burst and ripening in grapevines in the last forty years. Its a plant that leafs out in spring and matures its fruit in Autumn.

Figure 6

Data Source: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

Figure 7

Data Source: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

El Nino Southern Oscillation: Climate change on all time scales

The ENSO phenomenon is intimately related to atmospheric shifts. Figure 8 shows the relationship between the Southern Oscillation Index and sea surface pressure in the Indonesian region. In figure 8 the SOI index is inverted by changing its sign. Warming is indicated by a rising index which is more intuitive. Plainly, there is a very close association between the SOI and pressure over Indonesia.

Figure 8

Data Source: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

ftp://ftp.bom.gov.au/anon/home/ncc/www/sco/soi/soiplaintext.html

The SOI index is based on the relationship between atmospheric pressure in Tahiti and Darwin. A falling SOI is accompanied by a slackening of the Trade winds and rising sea surface temperature at the equator while a rising SOI is accompanied by intensification of the trades and a cooling sea. The Southern oscillation Index, and change in the Nino 3.4 region in mid Pacific are monitored because change in this region is associated with changing climate phenomena world-wide. Global temperature follows tropical sea surface temperature with a lag of a few months. Billions of dollars of research funds have been dedicated to studying temperature change in the Pacific Ocean. In spite of this investment, the dynamics of atmospheric change that drive the change in the temperature of the sea remain unknown, mysterious and controversial. Some birds, when faced with a threat to their existence will bury their head in the sand. Anthropogenic Global Warming theorists are not immune.

It is patently obvious that the El Nino Southern Oscillation phenomenon (ENSO) is the manifestation of ‘climate change in action’ both in the short and the long term. However, this interpretation is very much at odds with the version of climate science expressed by the U.N.I.P.C.C. where it is assumed that ENSO is internally generated and temperature neutral. Nothing could be further from the truth. This organization prefers its own highly speculative view of climate change in preference to that which is observed. This apparently ‘orthodox view’ is mistaken. Like many other supposed ‘pollutants’, carbon dioxide is just ‘plant food’. Like many other plant foods, it is in short supply. Many farmers who work with controlled atmospheres purchase carbon dioxide to supplement the natural supply. The atmosphere and the UNIPCC, ‘climate models’, have very little in common.  Kevin Trenberth has implicitly admitted this.

Figure 9 shows the relationship between surface pressure in Indonesian waters and the global tropics as represented by the latitude band 10N to 10S. It is apparent that pressure in Indonesia is an amplified version of pressure in the entire tropics, perhaps reflecting the movement in the zone of convection across the Indo-Pacific oceans.  The dramatic change in surface pressure in the El Nino of 1997-8 establishes this as the most powerful El Nino event of the last half of the century with the event of 1982-3 second in apparent intensity. From 1978 to the present time, surface pressure at the equator has been greater than the period average whereas prior to 1978 it was less than the period average. The globe cooled in the nineteen seventies, warmed between 1978 and 1998 and has since cooled. Periods of cooling are denied in ‘U.N.I.P.C.C.’ climate science. It appears that data is massaged to remove them. That is not science. It’s spin.

In problem solving activity, science can be of no utility unless some ground rules are adhered to. One must call a spade, a spade and cooling is cooling.

Figure 9

Data Source: http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl

Since tropical sea surface atmospheric pressure is such a good guide to surface temperature it occurred to me to look for a time series going back further in time. The virtue of barometric pressure is that it is not subject to urbanization effects, changes in land use and does not suffer from discontinuities due to relocation of the recording site, all problems that bedevil the temperature record.

Evangelista Torricelli, working with Galileo, became the first scientist to create a sustained vacuum and to discover the principle of a barometer. Torricelli realized that the variation of the height of the mercury from day to day was caused by changes in the atmospheric pressure. Torricelli built the first mercury barometer around 1644. In 1843, the French scientist Lucien Vidie invented the aneroid barometer and this was soon linked to a recording device.

Understandably, barometric pressure records before 1850 are scarce. The Hadley Centre produces a gridded series of barometric pressure for the globe that can be accessed at http://climexp.knmi.nl

The period from 1922 through to 1978 is characterized by low barometric pressure in the tropics whereas the period after 1978 is characterized by very high barometric pressure. In this graph we see the origins of the global cooling scare of the seventies and the warming scare of recent times.

Figure 10

Conclusion

Recent change in global temperature is explicable in terms of atmospheric dynamics that depend upon the influence of the sun. There is no need to invoke an anthropogenic influence.

There have been episodes of very high barometric pressure in the past, just as extreme as those of recent years. One can confidently assert that the pressure record is an accurate reflection of thermal conditions and is probably better than the temperature record itself. The period since 1978 is therefore warm only in the context of the cool period that immediately preceded it.

Reality check

Good science requires accurate measurement and careful extrapolation where no data is available. In that context consider the difference between HadAT2 and NCEP /NCAR Reanalysis versions of atmospheric pressure near the equator as represented in figure 11. Do these two series reflect national differences in demeanor? Is British ‘reserve’ and American ‘exuberance’ coming through? Where oh where does reality lie? Are scientists kidding us when they maintain that they have a handle on measurement? When they say they have confidence one way or the other, do they really expect us to believe them?

Figure 11

When I was just a lad my mother read me the story ‘The Boy Who Cried Wolf”. I guess we are just coming to terms with the refinements of what is conveyed by the term ‘Expert’ and the term ‘Scientist’. But, to be humane about it, all so called ‘knowledge’ is speculation anyway. We ‘choose’ what to believe on the basis of very limited evidence and most of the time it doesn’t worry us at all.

Note on the dominant data source:

NCEP/NCAR data is described in Kalnay, E. and Coauthors, 1996: The NCEP/NCAR Reanalysis 40-year Project. Bull. Amer. Meteor. Soc., 77, 437-471.

From http://www.esrl.noaa.gov/psd/data/gridded/reanalysis/ we have this description:

Physical Sciences Division  maintains a collection of reanalysis datasets for use in climate diagnostics and attribution. Reanalysis datasets are created by assimilating (“inputting”) climate observations using the same climate model throughout the entire reanalysis period in order to reduce the affects of modeling changes on climate statistics. Observations are from many different sources including ships, satellites, ground stations, RAOBS, and radar. Currently, PSD makes available these reanalysis datasets to the public in our standard netCDF format:

• NCEP/NCAR Reanalysis I (1948-present)

  This reanalysis was the first of it’s kind. NCEP used the same climate model that were initialized with a wide variety of weather observations: ships, planes, RAOBS, station data, satellite observations and many more. By using the same model, scientists can examine climate/weather statistics and dynamic processes without the complication that model changes can cause. The dataset is kept current using near real-time observatons.

I’m sure most of you are familiar with these images that have been circulating the blogosphere:

First, let me point out that Al Gore has failed at proving that Global Warming exists. That’s like trying to prove that Santa exists. Sure, wouldn’t it be dandy? But facts are facts and fiction is fiction. So, what does a has-been politician do when his life’s work has been proven time and time again to be a fraud? Well, if this has-been politician is Al Gore; he resorts to Photoshopping “evidence”. I mean, Photoshop trumps science, right? Wrong. Sorry, Al. It doesn’t. Just like whining about pregnant chads doesn’t win an election. YES, we all remember your whiny ass complaining about pregnant chads and dimples on ballots.

In the images above you can clearly see that several massive hurricanes have been Photoshopped. It’s been proven that hurricanes are at a 30 year low. Here are some graphs I found at Watts Up With That:

Both Northern Hemisphere and South Hemisphere AND therefore overall Global hurricane activity has continued to sink to levels not seen since the 1970s. Even more astounding, when the Southern Hemisphere hurricane data is analyzed to create a global value, we see that Global Hurricane Energy has sunk to 30-year lows, at the least. Since hurricane intensity and detection data is problematic as one goes back in time, when reporting and observing practices were different than today, it is possible that we underestimated global hurricane energy during the 1970s.

Using a well-accepted metric called the Accumulated Cyclone Energy index or ACE for short (Bell and Chelliah 2006), which has been used by Klotzbach (2006) and Emanuel (2005) (PDI is analogous to ACE), and most recently by myself in Maue (2009) , simple analysis shows that 24-month running sums of global ACE or hurricane energy have plummeted to levels not seen in 30 years.

Why use 24-month running sums instead of simply yearly values? Since a primary driver of the Earth’s climate from year to year is the El Nino Southern Oscillation (ENSO) acts on time scales on the order of 2-7 years, and the fact that the bulk of the Southern Hemisphere hurricane season occurs from October – March, a reasonable interpretation of global hurricane activity requires a better metric than simply calendar year totals. The 24-month running sums is analogous to the idea of “what have you done for me lately”. During the past 6 months, extending back to October of 2008 when the Southern Hemisphere tropical season was gearing up, global ACE had crashed due to two consecutive years of well-below average Northern Hemisphere hurricane activity. To avoid confusion, I am not specifically addressing the North Atlantic, which was above normal in 2008 (in terms of ACE), but the hemisphere (and or globe) as a whole. The North Atlantic only represents a 1/10 to 1/8 of global hurricane energy output on average but deservedly so demands disproportionate media attention due to the devastating societal impacts of recent major hurricane landfalls.

Interesting, indeed. Visit Watts Up With That for more information. Unless you’re a liberal. From what I understand; you liberals aren’t all that interested in facts and information. But, it’s there if you ever decide to quit being morons.

If you look at the second image I posted; the one with the faux-hurricanes… you’ll notice that the Arctic has magically disappeared! Funny, since the Arctic ice is currently at the SAME levels as 1979. The good people at Daily Tech pointed this out.

(click to enlarge)

Rapid growth spurt leaves amount of ice at levels seen 29 years ago.

Thanks to a rapid rebound in recent months, global sea ice levels now equal those seen 29 years ago, when the year 1979 also drew to a close.

Visit Daily Tech for more information.

Also, NASA points out that the average temperature of the water near the top of the Earth’s oceans has significantly cooled since 2003. CLICK FOR NASA ARTICLE

BBC has found that we have not observed any increase in global temperatures for the last 11 years. Yes, that’s over ONE DECADE. CLICK FOR BBC ARTICLE

So… tell me… Why does Florida appear to be dissolving in Al Gore’s lame Photoshopped images? What the hell happened to CUBA? Last time I checked; Cuba still exists. Also; look at the SIZE of those faux-hurricanes. Anyone who actually believes this Global Warming bullshit simply WANTS to. There is no other conclusion.

Here’s something fun:
Letting Al Gore know we aren’t falling for his junk science, Portland, Oregon 11/18/09

Wake up, people. He’s cashing in and making BILLIONS off of easily influenced MORONS.

enso…

A todos nos sorprende el efecto mariposa en la predicción meteorológica, pero a los expertos les sorprende más que el fenómeno de la Oscilación del Sur de El Niño (ENSO) no se limite a la capa inferior de la atmósfera (troposfera) sino que esté conectado con la estratosfera y a través de ella con toda la atmósfera terrestre en su conjunto. Una influencia que parece muy remota pero que ha sido evidenciada gracias a la correlación entre las fluctuaciones de la capa de ozono y las variaciones de temperatura en el Oceáno Pacífico asociadas a ENSO por el Dr. Randel y sus colegas. Los óvalos naranjas corresponden a anomalías positivas y los azules a valores negativos. Estas anomalías no sólo están concentradas en los trópicos y latitudes medias, sino que se extienden hasta las regiones árticas durante el invierno. Las flechas azules representan ondas térmicas que desde la troposfera alcanzan la estratosfera produciendo un proceso de ruptura (similar a la ola que rompe en la playa) que es un motor fundamental en la circulación térmica en toda la estratosfera. Nos lo cuenta Elisa Manzini, “Atmospheric science: ENSO and the stratosphere,” Nature Geoscience 2: 749-750, 2009, quien se hace eco del artículo técnico de William J. Randel, Rolando R. Garcia, Natalia Calvo, Dan Marsh, “ENSO influence on zonal mean temperature and ozone in the tropical lower stratosphere,” Geophys. Res. Lett. 36: L15822, 2009 [versión gratis en la web del primer autor].

El estudio de Randel et al. se ha beneficiado de que estudios anteriores no encontraran ninguna asociación entre ENSO y la estratosfera debido a que las erupciones volcánicas de El Chichón (1982) y el Pinatubo (1991), que ocurrieron durante la fase caliente de ENSO, enmascararon sus efectos sobre la troposfera. Los datos más recientes muestra claramente la correlación entre la temperatura troposférica debida a ENSO y la concentración de ozono estratosférica. Los autores han utilizado el modelo por ordenador de la química del ozono y los gases de efecto invernadero acoplados a la atmósfera global llamado WACCM (Whole Atmosphere Community Climate Model) desarrollado por la NCAR. Con dicho programa han analizado la dinámica de la atmósfera entre 0 y 140 km de altitud forzada con la variabilidad de temperaturas superficiales debidas a ENSO. Los resultados muestran una clara correlación entre ambos mediada por la tropopausa, la capa que separa troposfera y estratosfera.

From the “WUWT never reports on anything warm department”, JPL reports El Niño looks like it is on schedule to make a Christmas appearance as “The Boy”. The good news is that it will likely help California’s water situation this year.

Click for large image - This image was created with data collected by the U.S./French satellite during a 10-day period centered on November 1, 2009. It shows a red and white area in the central and eastern equatorial Pacific that is about 10 to 18 centimeters (4 to 7 inches) above normal. Image credit: NASA/JPL Ocean Surface Topography Team

From NASA Jet Propulsion Laboratory

El Niño is experiencing a late-fall resurgence. Recent sea-level height data from the NASA/French Space Agency Ocean Surface Topography Mission/Jason-2 oceanography satellite show that a large-scale, sustained weakening of trade winds in the western and central equatorial Pacific during October has triggered a strong, eastward-moving wave of warm water, known as a Kelvin wave. In the central and eastern equatorial Pacific, this warm wave appears as the large area of higher-than-normal sea surface heights (warmer-than-normal sea surface temperatures) between 170 degrees east and 100 degrees west longitude. A series of similar, weaker events that began in June 2009 initially triggered and has sustained the present El Niño condition.

This image was created with data collected by the U.S./French satellite during a 10-day period centered on November 1, 2009. It shows a red and white area in the central and eastern equatorial Pacific that is about 10 to 18 centimeters (4 to 7 inches) above normal. These regions contrast with the western equatorial Pacific, where lower-than-normal sea levels (blue and purple areas) are between 8 to 15 centimeters (3 and 6 inches) below normal. Along the equator, the red and white colors depict areas where sea surface temperatures are more than one to two degrees Celsius above normal (two to four degrees Fahrenheit).

“In the American west, where we are struggling under serious drought conditions, this late-fall charge by El Niño is a pleasant surprise, upping the odds for much-needed rain and an above-normal winter snowpack,” said JPL oceanographer Bill Patzert.

For more information on NASA’s ocean surface topography missions, see http://sealevel.jpl.nasa.gov/ ; or to view the latest Jason data, see http://sealevel.jpl.nasa.gov/science/jason1-quick-look/.

Global Temperatures This Decade Will Be The Warmest On Record…

…And It Will Be Exploited By Those Who Fail To Understand The Reasons For The Rise

Guest post by Bob Tisdale

INITIAL NOTES

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:
http://www.aoml.noaa.gov/general/enso_faq/
http://faculty.washington.edu/kessler/occasionally-asked-questions.html

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.

YouTube Link:
http://www.youtube.com/watch?v=DbNzw1CCKHo

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.

http://i33.tinypic.com/2i7mj4i.png
Table 1

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.

http://i34.tinypic.com/3589pj9.png
Figure 1

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.

http://i34.tinypic.com/iwrz39.png
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.

http://i37.tinypic.com/2la6640.gif
Figure 3
Links to the individual cells of Figure 3:
Link to Figure 3 Cell A:
http://i33.tinypic.com/9pw0no.png
Link to Figure 3 Cell B:
http://i36.tinypic.com/apigjq.png
Link to Figure 3 Cell C:
http://i35.tinypic.com/2yorexg.png

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.

http://i37.tinypic.com/smrt44.gif
Figure 4
Links to the individual cells of Figure 4:
Link to Figure 4 Cell A:
http://i33.tinypic.com/2cparf4.png
Link to Figure 4 Cell B:
http://i38.tinypic.com/dz5go.png
Link to Figure 4 Cell C:
http://i33.tinypic.com/14wu8pk.png

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.

http://i38.tinypic.com/2ezjk9s.png
Figure 5

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”.

YouTube Link:
http://www.youtube.com/watch?v=4uv4Xc4D0Dk

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.

http://i34.tinypic.com/id7h4k.png
Figure 6

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.

http://i35.tinypic.com/2coiln8.png
Figure 7

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.

http://i35.tinypic.com/j0f89k.gif
Figure 8
Links to the individual cells of Figure 8:
Link to Figure 8 Cell A:
http://i37.tinypic.com/30rraky.png
Link to Figure 8 Cell B:
http://i37.tinypic.com/2yjocr9.png
Link to Figure 8 Cell C:
http://i38.tinypic.com/2jcdc13.png
Link to Figure 8 Cell D:
http://i37.tinypic.com/2ue1jz8.png

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.

http://i36.tinypic.com/dpzu6h.gif
Figure 9
Links to the individual cells of Figure 9:
Link to Figure 9 Cell A:
http://i33.tinypic.com/2gwys1t.png
Link to Figure 9 Cell B:
http://i37.tinypic.com/kamom.png
Link to Figure 9 Cell C:
http://i35.tinypic.com/w075g6.png
Link to Figure 9 Cell D:
http://i34.tinypic.com/10e28ic.png

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.

http://i37.tinypic.com/24wztqe.gif
Figure 10
Links to the individual cells of Figure 10:
Link to Figure 10 Cell A:
http://i35.tinypic.com/4rxele.jpg
Link to Figure 10 Cell B:
http://i36.tinypic.com/2z4d6hc.jpg
Link to Figure 10 Cell C:
http://i36.tinypic.com/34obno7.jpg

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.)
http://i36.tinypic.com/wld5kl.jpg
Figure 11

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 1956 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.

http://i38.tinypic.com/oj4bqg.gif
Figure 12
Links to the individual cells of Figure 12:
Link to Figure 12 Cell A:
http://i37.tinypic.com/mwqeqh.jpg
Link to Figure 12 Cell B:
http://i34.tinypic.com/kaqtjq.jpg
Link to Figure 12 Cell C:
http://i35.tinypic.com/2gtddn7.jpg

CLOSING

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.

http://i43.tinypic.com/33agh3c.jpg
Figure 13

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.

http://i37.tinypic.com/i6xtnl.png
Figure 14

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:
ftp://ftp.nodc.noaa.gov/pub/data.nodc/woa/PUBLICATIONS/grlheat08.pdf

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
http://pubs.giss.nasa.gov/docs/2008/2008_Lean_Rind.pdf

Lean and Rind (2009), How Will Earth’s Surface Temperature Change in Future Decades? http://pubs.giss.nasa.gov/docs/2009/2009_Lean_Rind.pdfSanter, 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
http://pubs.giss.nasa.gov/docs/2001/2001_Santer_etal.pdfThompson, 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
http://www.nature.com/nature/journal/v453/n7195/abs/nature06982.html
Thompson et al (2009), Identifying signatures of natural climate variability in time series of global-mean surface temperature: Methodology and Insights
http://ams.allenpress.com/perlserv/?request=get-abstract&doi=10.1175%2F2009JCLI3089.1
Preprint Version:http://www.atmos.colostate.edu/ao/ThompsonPapers/TWJK_JClimate2009_revised.pdf
Trenberth, K.E., J.M.Caron, D.P.Stepaniak, and S.Worley, (2002), Evolution of El Nino-Southern Oscillation and global atmospheric surface temperatures
http://www.cgd.ucar.edu/cas/papers/2000JD000298.pdfWigley, T. M. L. (2000), ENSO, volcanoes, and record-breaking temperatures
http://www.agu.org/pubs/crossref/2000/2000GL012159.shtml

SOURCES

OI.v2 SST data is available through the NOAA NOMADS website:
http://nomad3.ncep.noaa.gov/cgi-bin/pdisp_sst.sh?lite=

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:
http://www.cdc.noaa.gov/data/correlation/amon.us.long.data

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

The data for the North Atlantic SST Reconstruction is available through the NCDC’s World Data Center for Paleoclimatology:
ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/reconstructions/amo-gray2004.txt

For those who want to verify the outputs of the GCMs used by the IPCC, refer to the KNMI Climate Explorer webpage here:
http://climexp.knmi.nl/selectfield_co2.cgi?someone@somewhere

Wiele wskazuje na to, że po dłuższym okresie “niezdecydowania” El Nino zaczęło przybierać na sile. Dla przypomnienia dodam, że według prognozy NOAA tegoroczne El Nino ma być wyjątkowo silne; z anomalią sięgającą nawet do ok. +2 oC. Szczyt anomalii powinien przypaść na przełom roku 2009/10.

Zdjęcia: NOAA

Poniżej link do ciekawej animacji przedstawiającej “rozwój” anomalii od 25. maja do 9 listopada. Dane NOAA:

LINK

We hear so much about El Niño, and a little bit about La Niña… but what does it all really mean? Is climate change involved in all this…. and why do they keep predicting it and it never comes!!!

Although there is a consensus since 2005 amongst North American countries over an operational index and definition for El Niño events, the reality does not always follow the science. Every day definitions for an El Niño event vary from one place to another based on the observed occurrence of catastrophic events and their economic and social impacts. Peruvian fisherman may consider a given year to be an El Niño year because of the low fish stock while no torrential rains hit Galapagos. Or Galapagos may be facing El Niño conditions while the fisheries off Peru are sustained. What is certain, is that the last two very strong El Niño events, 1982-1983 and 1997-1998, had Pacific wide consequences, from Indonesia and Australia to North America and down to Peru.

The Galapagos Archipelago and its relationship to El Niño Southern Oscillation is unique, because it sits right on the Equator, in the center of the El Niño mayhem! The operational index proposed by NOAA (National Oceanic and Atmospheric Administration) to describe an El Niño event is:

A three-month average of sea surface temperature departures from normal for a critical region of the equatorial Pacific (Niño 3.4 region; 120W-170W, 5N-5S).

This region is just west of Galapagos! which straddles the Niño 1+2 region and the Niño 3 region.

Galapagos straddles Niño 1+2 and Niño 3 regions

So why am I talking about all this now??? Well, there’s been talk about El Niño event occurring this year. Everyone’s reaction is that they heard the same thing last year… So I thought I’d share some real information about what’s happening.

Southern Oscillation Index and Sea Surface Temperature anomaly from 1980 to current.

A month ago, it was a mess. Warm waters where occurring north of the Equator, and a cold water anomaly was persisting between Galapagos and mainland Ecuador. The tradewinds were still blowing strong yet we had quite a fair bit of early morning rain. The Southern Oscillation Index (SOI): difference in atmospheric pressure difference between Tahiti and Darwin, Australia, was neutral.

Over the last week, something suddenly changed. The recent SOI data are showing a clear negative index, although not yet as strong as in 1982-1983 and 1997-1998.

So, I went back to look at where the winds were at.

Maps showing Sea Surface Temperature (SST), Winds, and anomalies in SST and Winds as of November 4th 2009

From the data display of the Tropical Atmosphere Ocean (TAO) project, have a look at what’s happening below the surface!

Maps showing depth profiles across the Equatorial Pacific from moored buoys.

It will be fascinating to see what happens over the next couple of weeks, and whether this Niño is to be or not to be.

All images presented here are from National Oceanic and Atmospheric Administration webpage and Tropical Atmosphere Ocean Project webpage

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Guest Post by Bob Tisdale:

Why Are OHC Observations (0-700m) Diverging From GISS Projections?

INTRODUCTION

My post “NODC Corrections to Ocean Heat Content (0-700m) Part 2” illustrated the divergence between observed Global Ocean Heat Content (OHC) and the GISS projected rise. Figure 1 shows that GISS models projected a rise of 0.98*10^22 Joules per year, but, since 2003, global OHC has only been rising at 0.079*10^22 Joules per year. How could there be such a significant difference between the projection and the observed OHC data?

http://i36.tinypic.com/5dscxg.png
Figure 1

GISS FAILS TO MODEL ENSO

Roger Pielke Sr discussed the disagreement between the GISS OHC projections and observations in his February 9, 2009 post ‘Update On A Comparison Of Upper Ocean Heat Content Changes With The GISS Model Predictions’. There he refers to a communication from James Hansen of GISS, a response to Pielke Sr and Christy, in which Mr. Hansen offers the GISS OHC projection. Refer to the linked response from Hansen here:
http://www.climatesci.org/publications/pdf/1116592Hansen.pdf

NOTE: In his response to Pielke Sr and Christy, Hansen writes, “Contrary to the claim of Pielke and Christy, our simulated ocean heat storage (Hansen et al., 2005) agrees closely with the observational analysis of Willis et al. (2004). All matters raised by Pielke and Christy were considered in our analysis and none of them alters our conclusions.” The Hansen et al (2005) paper is “Earth’s energy imbalance: Confirmation and implications.“ And the Willis et al (2004) paper is “Interannual Variability in Upper Ocean Heat Content, Temperature, and Thermosteric Expansion on Global Scales.” Link to abstract:
http://www.agu.org/pubs/crossref/2004/2003JC002260.shtml

Back to the topic of this post…

In his response to Pielke Sr and Christy, Hansen acknowledges that GISS does not account for ENSO in its models. He writes, “We note the absence of ENSO variability in our coarse resolution ocean model and Willis et al. note that a 10-year change in the tropics is badly aliased by ENSO variability.”

What Mr. Hansen fails to acknowledge is that ENSO also has significant impacts outside of the tropics.

SIGNIFICANT TRADITIONAL ENSO EVENTS CAUSE UPWARD STEP CHANGES IN OHC OF OCEAN BASINS

In my post “ENSO Dominates NODC Ocean Heat Content (0-700 Meters) Data”, I illustrated the upward step changes in OHC anomalies caused by significant traditional ENSO events such as those in 1972/73 and in 1997/98. This was done through simple comparison graphs of NINO3.4 SST anomalies, Sato Index data to illustrate the timing of explosive volcanic eruptions, and NODC (Levitus et al 2009) OHC anomaly data for individual ocean basins. Figures 2 through 4 are examples. In them, I’ve also highlighted the period GISS elected to model. Hansen explains the selection of those years in the response to Pielke and Christy linked above, “Our analysis focused on the past decade because: (1) this is the period when it was predicted that, in the absence of a large volcanic eruption, the increasing greenhouse effect would cause the planetary energy imbalance and ocean heat storage to rise above the level of natural variability (Hansen et al., 1997), and (2) improved ocean temperature measurements and precise satellite altimetry yield an uncertainty in the ocean heat storage, ~15% of the observed value, smaller than that of earlier times when unsampled regions of the ocean created larger uncertainty.”

But examination of the data illustrates variations that are caused primarily by natural variation, and much of these variations are apparent responses to ENSO, a variable that GISS does not model.

Figure 2 illustrates the monthly Tropical Indian and Pacific Ocean OHC anomaly data from January 1955 to June 2009. Note how the Tropical Indian and Pacific Ocean OHC anomaly data declines from the early-to-mid 1960s to 1973, then rises during the extended La Nina of 1973/74/75/76. And even though greenhouse gases (not illustrated) are rising from the late 1970s to 1999, there is a gradual decline in Tropical Indian and Pacific Ocean OHC anomalies. Some of this decline may be caused by the eruptions of El Chichon in 1982 and Mount Pinatubo in 1991, but their impacts are difficult to determine with the ENSO-related variability of the data. Then in 1998, Tropical Indian and Pacific Ocean OHC anomalies rise again during the multiyear La Nina that followed the significant 1997/98 El Nino. So regardless of the impacts of the El Chichon and Mount Pinatubo eruptions, the largest rises in OHC occurred during the two multiyear La Nina events associated with the El Nino events of 1972/73 and 1997/98. Also note that the period GISS elected to model captures one of these natural ENSO-induced upward step changes.
http://i35.tinypic.com/2j5tl4.png
Figure 2

Figure 3 illustrates the long-term OHC anomaly data for the South Pacific. The South Pacific OHC anomalies oscillate at or near 0 GJ/sq meter from 1971 to 1996 even though greenhouse gas emissions are increasing. The dip between the late 1960s and 1970 could be related to the volcanic eruption in 1963. If so, then the period of relatively flat OHC anomalies could be extended further back in time. What is certain is that there was a shift in South Pacific OHC anomalies, an upward step, in response to the 1997/98 El Nino. This happened, of course, during the period modeled by GISS.
http://i36.tinypic.com/2us7kvn.png
Figure 3

Like the Tropical Indian and Pacific Ocean OHC anomalies, the South Indian Ocean OHC anomalies decrease until the early 1970s, then rise in two steps in response to the La Nina events associated with the El Nino events of 1972/73 and 1997/98. Note the response of the South Indian Ocean OHC anomalies to the 1991 Mount Pinatubo eruption. Without that decline, the South Indian Ocean OHC anomalies are relatively flat though greenhouses gases are rising, similar to the South Pacific OHC data. And once more, the period GISS modeled captures the ENSO-induced rise associated with the 1997/98 El Nino.
http://i37.tinypic.com/2aetled.png
Figure 4

BUT ENSO RELEASES HEAT FROM THE TROPICAL PACIFIC

If ENSO events release heat from the tropical Pacific to the atmosphere, how then could they cause upward step changes in the OHC of other ocean basins?

During El Nino events, warm waters in the Pacific Warm Pool shift eastward to release heat that has been stored since the last La Nina event. Some of this warm water returns to the Pacific Warm Pool during the subsequent La Nina; some of it is transported to nearby ocean basins. This transport of warm water causes the OHC in those nearby oceans to rise. ENSO events also cause changes in Hadley and Walker circulation, changes in wind stress, and changes in cloud cover outside of the tropical Pacific. GCMs that do not model ENSO cannot account for these changes and cannot estimate their impacts on SST and OHC.

NORTH ATLANTIC OHC IS ALSO GOVERNED BY NATURAL VARIABLES

Over the past 50+ years, North Atlantic OHC anomalies rose at a rate that almost tripled the rise in global OHC anomalies. Refer to Figure 5. I discussed and illustrated the natural factors that impact the long-term North Atlantic OHC anomaly trends in the post “North Atlantic Ocean Heat Content (0-700 Meters) Is Governed By Natural Variables”. These natural variables include ENSO, the North Atlantic Oscillation (NAO), and Atlantic Meridional Overturning Circulation (AMOC). Unfortunately, the NODC OHC data only extends back to 1955. It is therefore impossible to determine how much of the excessive rise in the North Atlantic is related to AMOC.
http://i37.tinypic.com/34fche9.png
Figure 5

The Tropical North Atlantic OHC anomalies, Figure 6, show responses to ENSO events that are similar to the Tropical Indian and Pacific Ocean OHC data, Figure 2, except the tropical North Atlantic variations are imposed on what appears to be an AMOC-related positive trend. The period modeled by GISS included the response of the Tropical North Atlantic OHC anomalies to the 1997/98 El Nino.
http://i37.tinypic.com/292mwsy.png
Figure 6

Also discussed and illustrated in my post “North Atlantic Ocean Heat Content (0-700 Meters) Is Governed By Natural Variables”, Lozier et al (2008) in “The Spatial Pattern and Mechanisms of Heat-Content Change in the North Atlantic” identifies the North Atlantic Oscillation as the driver of decadal OHC variability in the high latitudes of the North Atlantic. Link:
http://www.sciencemag.org/cgi/content/abstract/319/5864/800?rss=1

The decadal variations in the NAO (inverted and scaled) do appear to agree with the High-Latitude North Atlantic OHC anomalies, Figure 7, until the aftermath of the 1997/98 El Nino. Note again that the period that GISS elected to model captures this NAO-related rise in High-Latitude North Atlantic OHC anomalies. Did the GISS model include the NAO in its analysis of OHC? I can find no mention of it in Hansen et al (2005) “Earth’s energy imbalance: Confirmation and implications.“

http://i38.tinypic.com/2rdf3ao.png
Figure 7

It appears that the North Atlantic OHC anomalies peaked in 2005. Are they on a multidecadal decline now? If the North Atlantic OHC is, in fact, governed by the same processes that cause the multidecadal variations in North Atlantic SST anomalies known as the Atlantic Multidecadal Oscillation (AMO), this would have a major impact on the GISS projections. Did GISS include this natural variability in its model? I can find no reference to it in Hansen et al (2005) “Earth’s energy imbalance: Confirmation and implications.“

IN SUMMARY

It appears the reason OHC observations are diverging from the GISS projection is GISS failed to recognize the impact of natural variables such as AMOC, the NAO, and ENSO on OHC. GISS assumed the rise in OHC from 1993 to 2003 was caused by anthropogenic forcings, when, in fact, there is little evidence to support this in the OHC data of the individual ocean basins. In order for OHC anomalies to rise in agreement with the GISS projection, there would have had to have been another significant traditional El Nino followed by a multiyear La Nina, and there would have had to have been another shift in the NAO, and there would have had to have been a continued rise in North Atlantic OHC anomalies. Unfortunately for GISS (and for the IPCC who relies on GCMs that fail to model natural variables properly), these natural variables have not cooperated.

A CLOSING NOTE ABOUT THE IMPACTS OF ANTHROPOGENIC GREENHOUSE GASES ON OHC

I was once asked by a blogger at another website, “What is the source of the energy necessary to raise SSTs?” I have revised my response to include OHC.

The ultimate source of energy necessary to raise SSTs would be an increase in solar irradiance, regardless of whether the increase in solar irradiance resulted from variations in the solar cycle, or from changes in cloud cover, or from a reduction in stratospheric volcanic aerosols. The impact of shortwave radiation (visible light) on SST depends on factors such as the turbidity of the water and sea surface albedo, which in turn depend on other variables including wind speed and chlorophyll concentration. Downwelling shortwave radiation reaches ocean depths of a few hundred meters. Therefore, changes in downwelling shortwave radiation would have a significant impact on OHC.

An increase in downward longwave (infrared) radiation caused by anthropogenic greenhouse gas emissions, on the other hand, can only warm the top few centimeters of the oceans. So an increase in downward longwave (infrared) radiation only warms the top few centimeters while downwelling shortwave radiation (visible light) warms the top few hundred meters.

However, it has been argued by AGW proponents that through mixing caused by waves and wind stress turbulence, the downward longwave (infrared) radiation would warm the mixed layer of the ocean. This in turn would affect the temperature gradient between the mixed layer and skin, dampening the outward flow of heat from the ocean to the atmosphere. The end result: OHC would rise due to an increase in downward longwave (infrared) radiation caused by increases in greenhouse gas emissions.

The OHC data illustrated in this post provide little support for the argument that downward longwave (infrared) radiation causes OHC to rise. OHC anomalies for the Tropical Indian and Pacific Oceans and for the South Indian and South Pacific Oceans show little upward trend from the early 1970s to the late 1990s. The only significant rises in OHC for those datasets occur in response to significant traditional ENSO events.

To emphasize this, the North Pacific OHC anomaly graph, Figure 8, illustrates a long-term decline in OHC from the late 1950s to the late 1980s, followed by a sudden upward shift. This long-term decline does not appear to be consistent with arguments that accelerating greenhouse gas emissions cause OHC to rise. The upward shift in the late 1980s appears to be associated with the 1986/87/88 El Nino. This El Nino is one of the two El Nino events since 1976 that caused upward step changes in SST anomalies of the East Indian and West Pacific Oceans and in the TLT anomalies of the Mid-To-High Latitudes of the Northern Hemisphere–the second being the 1997/98 El Nino. Why did the 1986/87/88 ENSO event cause the upward step in North Pacific OHC anomalies? Or was it caused by a shift in some other natural variable?
http://i35.tinypic.com/2czvw5l.png
Figure 8

As illustrated in this post, the impacts of natural variables such as ENSO, NAO, and AMOC dominate short-term and long-term OHC variability. ENSO events also cause upward step changes in SST and TLT anomalies, as noted above. These impacts on SST and TLT anomalies were discussed and illustrated in my 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
3.RSS MSU TLT Time-Latitude Plots…Show Climate Responses That Cannot Be Easily Illustrated With Time-Series Graphs Alone

If and when GCMs like those used by GISS, and in turn by the IPCC, are capable of reproducing ENSO events and their multiyear aftereffects on SST, TLT, and OHC anomalies, they may be capable of determining “Earth’s energy imbalance: Confirmation and implications.“ At present, they are not.

SOURCES

The NINO3.4 SST anomaly data is based on HADISST data available through the KNMI Climate Explorer. The NODC OHC data is also available through Climate Explorer:
http://climexp.knmi.nl/selectfield_obs.cgi?someone@somewhere

Sato Index data is available through GISS:
http://data.giss.nasa.gov/modelforce/strataer/
Specifically:
http://data.giss.nasa.gov/modelforce/strataer/tau_line.txt

Don’t miss out on this PING PONG BATTLE ROYALE! We’ll have a ping pong table set up in the middle room, nuff rackets and 1.000.000 balls, so you won’t have to bring your own.

Special guest: 3 x China DMC champion WORDY from Beijing:

Download his latest mixtape here:

DJ Wordy – No Escape Mix

A new paper in Geophysical Research Letters was brought to my attention by Dr. Leif  Svalgaard.

Tropical origins of North and South Pacific decadal variability by Jeremy D. Shakun and Jeffrey Shaman makes some very interesting findings suggesting that both the northern and southern Pacific Ocean has evidence of the Pacific Decadal Variation PDV being driven by ENSO variations. They produced a model, which when run correlates reasonably well with observations.

Fig 4. Observed (red line with circles) and modeled (blue line with slashes) PC1s for the (top) North and (bottom) South Pacific. The model is of an AR-1 process forced by ENSO, see the paper for details - click for a larger image

Abstract:

The origin of the Pacific Decadal Oscillation (PDO), the leading mode of sea surface temperature variability for the North Pacific, is a matter of considerable debate. One paradigm views the PDO as an independent mode centered in the North Pacific, while another regards it as a largely reddened response to El Nin˜o-Southern Oscillation (ENSO) forcing from the tropics. We calculate the Southern Hemisphere equivalent of the PDO index based on the leading mode of sea surface temperature variability for the South Pacific and find that it adequately explains the spatial structure of the PDO in the North Pacific. A first-order autoregressive model forced by ENSO is used to reproduce the observed PDO indices in the North and South Pacific. These results highlight the strong similarity in Pacific decadal variability on either side of the equator and suggest it may best be viewed as a reddened response to ENSO.

They write about the graph above:

…we model PDV as a first-order autoregressive process driven by ENSO as done by Newman et al. [2003]. This AR-1 model is applied to the North and South Pacific separately.

The modeled PDO index at year n is a function of the modeled PDO index at n – 1 and the observed ENSO index (Nino 3.4) at n. These annually-averaged indices are centered on boreal winter (Jul–Jun) for the North Pacific and austral winter (Jan–Dec) for the South Pacific. Per Newman et al. [2003], the coefficients β and α are parameters derived, respectively, by regression of the PDO index on the ENSO index, then autoregression of the residual time series with a lag of one year. h is an uncorrelated noise term not used in our analysis but shown for completeness. a and b are 0.51 and 0.56 for North Pacific PC1 and 0.62 and 0.71 for South Pacific PC1. While Newman et al. [2003] found this simple model did a remarkable job reproducing the observed 20th century PDO index in the North Pacific (r = 0.63 in our study), it yields an even stronger fit to our Southern Hemisphere PDO index (r = 0.71) (Figure 4).

The greater success of the model in the South Pacific may be a function of its larger α and β terms, which indicate that the persistence of SST anomalies and ENSO forcing are more important. The stronger ENSO signal in the South Pacific may derive from the equatorial asymmetry of ENSO SST anomalies in the eastern tropical Pacific, which extend considerably farther to the south than to the north. One implication of this finding is that the South Pacific may be a better place to develop paleo-ENSO records as it appears to contain a ‘cleaner’ ENSO signal.

Conclusion

Deriving a Southern Hemisphere equivalent of the PDO index shows that the spatial signature of the PDO can be well explained by the leading mode of SST variability for the South Pacific. Thus, PDV appears to be a basin-wide phenomenon most likely driven from the tropics. Moreover, while it was already known PDV north of the equator could be adequately modeled as a reddened response to ENSO, our results indicate this is true to an even greater extent in the South Pacific.

Leif has a copy of the paper on his website that you can read here

Citation:

Shakun, J. D., and J. Shaman (2009), Tropical origins of North and South Pacific decadal variability, Geophys. Res. Lett., 36, L19711, doi:10.1029/2009GL040313.

Lemme bless you with my 5th and last US tour ‘09 related bloggery! From Albuquerque, I flew down to Los Angeles to meet Enso at the LAX airport. I’ve never been to LA before, and Enso’s last stay was like 78 years ago, so we’ve been pretty much drifting aimlessly in the city of angels, which made a GPS-equipped rental whip essential. Peep the lovely blood stains on the ceiling. Welcome to LA!

After struggling with configurating the world’s worst GPS system, we hit the highway

to Beverly Hills for a top secret bizness meeting. I sorta only knew valet-parking from movies and such. Hello surrealism! Speaking of which, after the meeting, I insisted on a cruise over Mulholland Drive to get my David Lynch on. By one of the highest vista points, we pulled off the road and hopped over fences to sneak a peek of this picturesque LA panorama by night.

We checked out Hollywood’s clubs for a bit and impatiently hit the highway 101 San Francisco bound on the same night to avoid LA’s daytime traffic. We decided for a sleepover in Santa Barbara, and switched from 101 to the Pacific Coast Highway 1; probably the most amazing drive I ever did in my life. The 1 constantly runs along the coast, stunning ocean views and winding mountain roads included.

The sky was as blue as it can get, our iPods were loaded with jams and the whip was more than decent.

Next up, while my co-driver took a roadnap, I stopped at Piedras Blancas to eyeball a bunch of elephant seals sloshing around at the beach,

and treat starving squirrels with peanuts.

After a long day of cruising, we arrived late in San Francisco to fulfill our duties.

Cali, what’s up with your clubs shutting down at 2AM? It just doesn’t compute.

MP3:

Dead Kennedys – California Über Alles