Sbsp affirmative- arl lab- ndi 2011



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AT: Milankovitch Cycles

Human influence outweighs Milankovitch cycle – emissions reversed projected cooling



Biello, ‘9 – [David, 9/04/2009, Scientific American, “Global Warming Reverses Long-Term Arctic Cooling,” http://www.scientificamerican.com/article.cfm?id=global-warming-reverses-arctic-cooling, DS]
Based on its long-term orbit, Earth should be heading into an ice age. But instead of continuing to cool—as it had been for at least the past 2,000 years—the Arctic has started to warm. And the reason is humans’ impact on the composition of the atmosphere, new research suggests. To look at this trend, geologist Darrell Kaufman of Northern Arizona University and a consortium of colleagues reconstructed Arctic temperatures decade by decade over the past two millennia by pulling sediment cores from the bottoms of 14 Arctic lakes—backed up by records in tree rings and ice cores.  In warm summers, relatively more sediment is deposited thanks to more meltwater from the glaciers that create these lakes, and the abundance of algae in the sediment layers reveals the length of growing seasons. So, these sediment cores provide a picture of the climate that goes back millennia. The record they reveal is of a cooling pole. As the Earth has moved slightly further away from the sun due to vagaries in its orbit—it’s roughly 600,000 miles further away now than in 1 C.E.—some parts of the Arctic received as much as 6 watts per meter squared less sunlight than in 1 C.E. That, in turn, has led to a cooling rate of roughly 0.2 degrees Celsius per 1,000 years. But at some point in the 20th century, that trend stopped and reversed. “Orbitally driven summer insolation continued to decrease through the 20th century, implying that summer temperatures should have continued to cool,” the researchers wrote this week in the September 4 edition of Science. “Instead, the shift to higher temperatures during the 20th century reversed the millennial scale cooling trend.” In the past decade, summertime Arctic temperatures have been 1.4 degrees Celsius higher on average than would be expected and 1.2 degrees Celsius higher than in 1900. And the Arctic is merely the trendsetter—the northern-most latitudes are among the fastest-warming parts of the globe due to various feedbacks. For example, melting Arctic sea ice exposes more ocean, which in turn absorbs more of the sunlight’s warmth and further increases warming. A graph of the warming trend largely replicates the so-called “hockey stick,” a previous reconstruction that showed relatively stable temperatures suddenly spiking upward in recent history. It also accurately reveals the impact of historical climate events like the Little Ice Age, which took place from the 17th to 19th centuries. Without greenhouse gas emissions in the atmosphere, a true ice age might have been expected as a 21,000-year wobble in Earth’s tilt relative to the sun that shifts the intensity of sunlight. That cooling trend wouldn’t have reversed naturally for at least another 4,000 years. Yet, despite this decline, Arctic temperatures have soared and the most likely culprit is the build-up of greenhouse gases in the atmosphere from fossil fuel burning, forest clearing and other human activity, Kaufmann and his colleagues wrote. “The most recent 10-year interval (1999–2008) was the warmest of the past 200 decades,” they wrote. “Temperatures were about 1.4 degrees C higher than the projected values based on the linear cooling trend and were even more anomalous than previously documented.” Of course, summer temperatures when the warming portion of the wobble cycle peaked roughly 7,500 years ago were at least 0.8 degrees Celsius warmer than 20th-century average temperatures. Nonetheless, this current, countercyclical warming trend will likely continue—potentially exceeding that earlier warming—unlessgreenhouse gas levels begin to come back down. In the meantime, polar denizens adapted for the cooler climate can blame humanity for a balmier Arctic.


AT: El Nino

El Nino can’t explain warming – your authors misfiltered data



Cook, ’10 – Citing Penn State Metereology Professor, Professor of Environmental Science at Auckland University, and Climatic Researcher at University of East Anglia in UK [John, 3/18/2010, “A peer-reviewed response to McLean’s El Nino paper,” Skeptical Science, http://www.skepticalscience.com/peer-reviewed-response-to-mclean-el-nino-paper.html]
A paper published mid-2009 claimed a link between global warming and the El Nino Southern Oscillation (ENSO) (McLean et al 2009). According to one of its authors, Bob Carter, the paper found that the “close relationship between ENSO and global temperature, as described in the paper, leaves little room for any warming driven by human carbon dioxide emissions”. This result is in strong contrast with two decades of peer-reviewed research which find ENSO has little influence on long-term trends. Why the discrepancy? A response has now been accepted for publication in the Journal of Geophysical Research (Foster et al 2010) explaining why McLean 2009 differs from the body of peer-reviewed research. First, let’s examine how McLean et al arrived at their conclusion. They compared both weather balloon (RATPAC) and satellite (UAH) measurements of tropospheric temperature to El Niño activity (SOI). To remove short-term noise, they plotted a 12 month running average of Global Tropospheric Temperature Anomaly (GTTA, the light grey line) and the Southern Oscillation Index (SOI, the black line). Figure 1: Twelve-month running means of SOI (dark line) and MSU GTTA (light line) for the period 1980 to 2006 with major periods of volcanic activity indicated (McLean 2009). The Southern Oscillation Index shows no long term trend while the temperature record shows a long-term warming trend. Consequently, McLean et al found only a weak correlation between temperature and SOI. Next, they applied another filter to the data by subtracting the 12 month running average from the same average 1 year later. The comparison between the filtered data for El Nino and Temperature are as follows: Figure 2: Derivatives of SOI (dark line) and MSU GTTA (light line) for the period 1981–2007 after removing periods of volcanic influence (McLean 2009). From this close correlation, McLean et al argued that more than two thirds of interseasonal and long-term variability in temperature changes can be explained by the Southern Oscillation Index. This result contradicts virtually every other study into the connection between ENSO and temperature variability, particularly with regard to long-term warming trends. Past analyses have found ENSO was responsible for 15 to 30% of interseasonal variability but little of the global warming trend over the past half century (Jones 1989, Wigley 2000, Santer 2001, Trenberth 2002, Thompson 2008). Why does McLean come to a different result? This question is examined in Comment on “Influence of the Southern Oscillation on tropospheric temperature” by J. D. McLean, C. R. de Freitas, and R. M. Carter (Foster et al 2010). Foster et al examine the filtering process that McLean et al applied to the temperature and ENSO data. This filtering has two steps – they take 12-month moving averages then take the differences between those values which are 12 months apart. The first step filters the high-frequency variation from the time series while the second step filters low-frequency variation. The problem with the latter step is it removes any long-term trends from the original temperature data. The long-term warming trend in the temperature record is where the disagreement between temperature and ENSO is greatest. Why do McLean et al remove the long-term trend? They justify it by noting a lack of correlation between SOI and GTTA, speculating that the derivative filter might remove noise caused by volcanoes or wind. However, taking the derivative of a time series does not remove, or even reduce, short-term noise. It has the opposite effect, amplifying the noise while removing longer-term changes. To further illustrate how the filtering process increases the correlation between SOI and temperature, the authors construct an artificial “temperature” time series as -0.02 times the SOI time series. They then add white noise and a linear trend. This has the effect of creating a temperature time series with a long term warming trend. The correlation between the raw artificial temperature series and the SOI series is very low (R2 = 0.0161). However, when the McLean et al filters are applied to both time series, the correlation is now very high (R2 = 0.8295). This is because the filtering removes low frequency elements such as the long term warming trend. Figure 3: (a) Southern Oscillation Index (SOI) data (black) versus artificial data proportional to the SOI, and with normally-distributed white noise and a sinusoidal signal added (red). (b): Filtered versions (using the McLean et al procedure) of the series in (a). Despite the extreme distorting effect of their filter, McLean et al consistently refer to the correlations as between SOI and tropospheric temperature. They draw no attention to the fact that the correlations are between heavily filtered time series. This failure causes what is essentially a mistaken result to be misinterpreted as a direct relationship between important climate variables. Another interesting feature of McLean et al 2009 is a plot of unfiltered temperature data (GTTA) against the Southern Oscillation Index (SOI) to illustrate the quality of the match between them. However the temperature signal is a splice of weather balloon data (RATPAC-A) to the end of 1979 followed by satellite data (UAH TLT) since 1980. RATPAC-A data show a pronounced warming trend from 1960 to 2008 with the temperature line rising away from the SOI line. This warming trend is obscured by substituting the weather balloon data with satellite data after 1980. It is especially misleading because the mean values of RATPAC-A and UAH TLT data during their period of overlap differ by nearly 0.2 K. Splicing them together introduces an artificial 0.2-degree temperature drop at the boundary between the two. Unfortunately, the splicing is obscured by the fact that the graph is split into different panels precisely at the splicing boundary. This splicing + graph splitting technique is an effective way to “hide the incline” of the warming trend. Figure 4: Seven-month shifted SOI with (a) weather balloon RATPAC-A temperature data 1958–1979 and satellite UAH temperature data (b) 1980–1995. Dark line indicates SOI and light line indicates lower tropospheric temperature. Periods of volcanic activity are indicated. It has been well known for many years that ENSO is associated with significant variability in global temperatures on short timescales of several years. However, this relationship cannot explain temperature trends on decadal and longer time scales. McLean et al 2009 grossly overstates the influence of ENSO, primarily by filtering out any long-term trends.



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