Atmospheric & Solar Oscillations With Linkage To The Earth’s Mean Temperature Trend: An Assessment In The Context Of Global Warming Debate
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- INTRODUCTION
- WALKER AND THE FIRST RECOGNITION OF LARGE SCALE OSCILLATIONS
- THE SOUTHERN OSCILLATION INDEX (SOI)
- NINO 3.4 ANOMALIES
- MULTIVARIATE ENSO INDEX (MEI)
| Atmospheric & Solar Oscillations With Linkage To The Earth’s Mean Temperature Trend: An Assessment In The Context Of Global Warming Debate
By Joseph D’Aleo, CCM, AMS Fellow ABSTRACT The IPCC in its 2007 Fourth Assessment Summary for Policy Makers (SPM) has proclaimed that “warming of the climate system is unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice and rising global average sea level”. It concluded that “Most of the observed increase in global average temperatures since the mid-20th century is very likely (>90% probability by IPCC definition) due to the observed increase in anthropogenic greenhouse gas (GHG) concentrations.” In the document they showed that using their assessment of solar forcing, that natural factors (solar and volcanic) could not account for recent observed changes. In this paper, we will provide evidence that the observed changes CAN be explained by natural factors including secular changes in overall solar activity and multidecadal cycles in the oceans. We will show why the correlation of two decades of climate changes in the 1980s and 1990s to GHGs is likely to be coincidental as 5 of the last 7 decades since the beginning of the post World War II boom have actually cooled as CO2 increased. We will show how multidecadal cycles in the ocean correlate with the frequency and strength of the shorter term El Nino Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) phases and through them the United States temperatures. Total solar irradiance is shown to vary with both these multidecadal ocean cycles and thus the temperatures suggesting the sun as the ultimate driver. A plausible hypothesis is that the sun is the primary driver through alterations of the radiation and galactic cosmic rays entering the atmosphere. The differences in energy entering the world’s oceans, which cover 2/3rds of the earth surface is especially important. Given their huge heat capacity, the oceans likely act as the flywheel of the climate system, providing the mechanisms to bring about the changes by altering the atmosphere’s controlling circulations. For example, when too much heat builds in the tropical oceans as solar activity increases, the Pacific appear to flip into its warm mode, which is the positive phase of the Pacific Decadal Oscillation (PDO) favoring more El Ninos, which act to transport excess heat poleward. The Atlantic thermohaline circulation gradually strengthens and transports warm water to the higher latitudes and the arctic (eventually transitions to the warm phase of the Atlantic Multidecadal Oscillation or AMO). This sequence happened in the 1930s and 1940s and again the 1980s into the early 2000s. Global temperatures responded upwards. Conversely when the solar activity diminishes as it did last in the late 1950s to the 1970s, the tropical oceans cool and the Pacific Decadal Oscillation flips into its negative cold mode. The global temperatures begin to cool and then accelerate as the Atlantic thermohaline slows and the ocean begins a cooling and the Atlantic Multidecadal Oscillation turns negative. Global temperatures decline. Since that same sequence is now repeating, cooling is more likely than warming in the decades ahead. INTRODUCTION The sun and ocean undergo regular changes on regular and predictable time frames. Temperatures likewise have exhibited changes that are cyclical. This paper will compare the cycles in temperatures with the cycles on the sun and in the oceans. The ocean and solar influences on climate were discussed at some length in the scientific back-up to the IPCC AR4 2007 Summary for Policy Makers (SPM). IPCC chapter 3 (Observations: Surface and Atmospheric Climate Change) defined the circulation indices including the short term and decadal scale oscillations in the Pacific, and Atlantic and attributed their origin as natural. It noted that the decadal variability in the Pacific (the Pacific Decadal Oscillation or PDO) is likely due to oceanic processes. “Extratropical ocean influences are likely to play a role as changes in the ocean gyre evolve and heat anomalies are subducted and reemerge”. (3.6.3) The Atlantic Multidecadal Oscillation (AMO) is thought to be due to changes in the strength of the thermohaline circulation. Ultimately IPCC fails to suggest a connection between these cyclical oceanic changes and the observed global cyclical temperature changes. They only go as far as making a possible connection to regional variances. “Understanding the nature of teleconnections and changes in their behavior is central to understanding regional climate variability and change. (3.6.1) In chapter 2, the AR4 discussed at length the varied research on the solar changes and possible direct and indirect influences on climate. In chapter 2, the AR4 discussed at length the varied research on the direct solar irradiance variance and the uncertainties related to indirect solar influences through variance through the solar cycles of ultraviolet and solar wind/geomagnetic activity. They admit that ultraviolet radiation by warming through ozone chemistry and geomagnetic activity through the reduction of cosmic rays and through that low clouds could have an effect on climate but in the end chose to ignore the indirect effect. They stated: “Since TAR, new studies have confirmed and advanced the plausibility of indirect effects involving the modification of the stratosphere by solar UV irradiance variations (and possibly by solar-induced variations in the overlying mesosphere and lower thermosphere), with subsequent dynamical and radiative coupling to the troposphere. Whether solar wind fluctuations (Boberg and Lundstedt, 2002) or solar-induced heliospheric modulation of galactic cosmic rays (Marsh and Svensmark, 2000b) also contribute indirect forcings remains ambiguous.” (2.7.1.3) For the total solar forcing, in the end the AR4 chose to ignore the considerable recent peer review in favor of Wang et al. (2005) who used an untested flux transport model with variable meridional flow hypothesis and reduced the net long term variance of direct solar irradiance since the mini-ice age around 1750 by up to a factor of 7. This may ultimately prove to be AR4’s version of the AR3’s “hockey stick” debacle. This paper will examine ocean-based teleconnections and solar variances and temperatures and describe how various cycles interrelate with each other and correlate with temperatures. A team of mathematicians in 2007 produced a model that supports this theory. Developed by a team led by Dr. Anastasios Tsonis, the model suggests that known cycles of the Earth’s oceans-the Pacific Decadal Oscillation, the North Atlantic Oscillation, El Nino (Southern Oscillation) and the North Pacific Oscillation - all tend to synchronize with each other. The theory is based on a branch of mathematics known as Sychronized Chaos. The model predicts the degree of coupling to increase over time, causing the solution to “bifurcate,” or split. Then, the synchronization vanishes. The result is a climate shift. Eventually the cycles begin to synchronize again, causing a repeating pattern of warming and cooling, along with sudden changes in the frequency and strength of El Nino events. They show how this has explained the major shifts that have occurred including 1913, 1942 and 1978. These may be in the process of synchronizing once again with is likely impact on climate very different from what has been observed over the last several decades. WALKER AND THE FIRST RECOGNITION OF LARGE SCALE OSCILLATIONS Sir Gilbert Walker was generally recognized as the first to find large scale oscillations in atmospheric variables. As early as 1908, while on a mission to try and explain why the Indian monsoon sometimes failed, he assembled global surface data and did a thorough correlation analysis. On purely statistical grounds through careful interpretation, Walker was able to identify three pressure oscillations: a flip flop on a big scale between the Pacific Ocean and the Indian Ocean which he called the Southern Oscillation (SO); a second oscillation, on a much smaller scale, between the Azores and Iceland, which he named the North Atlantic Oscillation; and a third, between the areas of high and low pressure in the North Pacific, which Walker called the North Pacific Oscillation. Walker further asserted that the SO is the predominant oscillation, and had a tendency to persist for at least one to two seasons. He went so far in 1924 as to suggest the SOI had global weather impacts and might be useful in predicting the world’s weather. He was ridiculed by the scientific community at the time for these statements. Not until four decades later was the Southern Oscillation was recognized as a coupled atmosphere pressure and ocean temperature phenomena (Bjerknes 1969) and more than two decades further before it was shown to have statistically significant global impacts and could be used to predict global weather/climate at times many seasons in advance. Walker was clearly a man ahead of his time. THE SOUTHERN OSCILLATION INDEX (SOI) The Southern Oscillation Index (SOI) is the oldest measure of the large-scale fluctuations in air pressure occurring between the western and eastern tropical Pacific (i.e., the state of the Southern Oscillation) during El Niño and La Niña episodes (Walker et al.1932). Traditionally, this index has been calculated based on the differences in air pressure anomaly between Tahiti and Darwin, Australia. In general, smoothed time series of the SOI correspond very well with changes in ocean temperatures across the eastern tropical Pacific. The negative phase of the SOI represents below-normal air pressure at Tahiti and above-normal air pressure at Darwin. Prolonged periods of negative SOI values coincide with abnormally warm ocean waters across the eastern tropical Pacific typical of El Niño episodes. Prolonged periods of positive SOI values coincide with abnormally cold ocean waters across the eastern tropical Pacific typical of La Niña episodes. As an atmospheric observation-based measure, SOI is subject not only to underlying ocean temperature anomalies in the Pacific but also the intraseasonal oscillations like the Madden-Julian Oscillation (MJO). The SOI often shows month-to-month swings even if the ocean temperatures remain steady due to these atmospheric waves. This is especially true in weaker El Nino or La Nina events as well as La Nadas (neutral ENSO) conditions. Indeed, even the changes week-to-week can be significant. For that reason, other measures are often preferred. NINO 3.4 ANOMALIES On February 23, 2005, NOAA announced that the NOAA National Weather Service, the Meteorological Service of Canada and the National Meteorological Service of Mexico reached a consensus on an index and definitions for El Niño and La Niña events (also referred to as the El Niño Southern Oscillation or ENSO). Canada, Mexico and the United States all experience impacts from El Niño and La Niña.
The index was called the ONI and is defined as 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 of the tropical Pacific contains what scientists call the "equatorial cold tongue," a band of cool water that extends along the equator from the coast of South America to the central Pacific Ocean. North America's operational definitions for El Niño and La Niña, based on the index, are: El Niño: A phenomenon in the equatorial Pacific Ocean characterized by a positive sea surface temperature departure from normal (for the 1971-2000 base period) in the Niño 3.4 region greater than or equal in magnitude to 0.5 degrees C (0.9 degrees Fahrenheit), averaged over three consecutive months.
The MEI is calculated as the first unrotated Principal Component (PC) of all six observed fields combined. This is accomplished by normalizing the total variance of each field first, and then performing the extraction of the first PC on the co-variance matrix of the combined fields (Wolter and Timlin, 1993). In order to keep the MEI comparable, all seasonal values are standardized with respect to each season and to the 1950-93 reference period. Negative values of the MEI represent the cold ENSO phase, (La Niña), while positive MEI values represent the warm ENSO phase (El Niño). Here is a plot of the three indices since 2000. (Wolter and Timlin, 1993)
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