First some background graphics before we demonstrate the cherry pick.
We’ll start with the IPCC graphic from the AR5 draft.
Then we’ll look at Christy and Spencer’s recent graph.
Now let’s look at what Marlo Lewis brought to our attention at globalwarming.org. He writes:
Seeing is believing, but things are not always what they seem. Skeptical Science, a Web site devoted to “debunking” global warming skepticism, asserts that Spencer’s claim about recent warming being only 50% of what the model consensus projects is “flat-out ridiculously wrong” (original emphasis). Observed warming has been “spot on consistent with climate model projections,” Skeptical Science contends. The evidence, supposedly, is in the graph below (click on it to activate the presentation if it doesn’t animate).
Figure explanation: This animation compares the observed global temperature change since 1990 (black curve) to projections of global temperature change from the first four Intergovernmental Panel on Climate Change (IPCC) reports (red, pink, orange, green) and from various “climate contrarians” (blue, purple, green, gray dashed). The observations are given by the average of 3 primary global temperature datasets (NASA GISS, NOAA NCDC, and HadCRUT4). All of the IPCC projections have proven to be quite accurate, suggesting high reliability. The contrarian projections all underestimate the global warming substantially, and in fact they erroneously predict global cooling and are quite unreliable.
So who’s right: Spencer and Christy or Skeptical Science (SS)? The SS graph and commentary are misleading in two ways.
The period covered in the SS graph is a decade shorter than that covered by the Spencer-Christy graph and looks suspiciously like cherry-picking. By starting their graph in 1990, SS can use the Mt. Pinatubo-induced cold period of 1992-93 to tilt the trend to be more positive. The Spencer-Christy graph begins at the start of the satellite record — 1979 — providing a longer and more representative period.
More importantly, SS uses global surface temperature datasets, which do not accurately represent heat content in the bulk atmosphere. In contrast, Spencer and Christy use temperature data from the tropical troposphere — the place where the models project the strongest, least ambiguous, greenhouse warming signal.
As Christy explained in testimony last August, the popular surface datasets often touted as evidence of model validity are not reliable indicators of the greenhouse effect. Land use changes (urbanization, farming, deforestation) “disrupt the normal formation of the shallow, surface layer of cooler air during the night when TMin [daily low temperature] is measured.” Over time, TMin gets warmer, producing a trend easily mistaken for a global atmospheric phenomenon.