The global temperature jigsaw

It is likely that all these factors indeed contributed to a slowing of the warming, and they are also additive – according to the IPCC report (Section 9.4) about half of the slowdown can be explained by a slower increase in radiative forcing. A problem is that the data on the net radiative forcing are too imprecise to better quantify its contribution. Which in turn is due to the short period considered, in which the changes are so small that data uncertainties play a big role, unlike for the long-term climate trends.

The latest data and findings on climate forcings are not included in the climate model runs because of the long lead time for planning and executing such supercomputer simulations. Therefore, the current CMIP5 simulations run from 2005 in scenario mode (see Figure 6) rather than being driven by observed forcings. They are therefore driven e.g. with an average solar cycle and know nothing of the particularly deep and prolonged solar minimum 2005-2010.

Internal variability: El Niño, PDO & co.

The strongest internal variability in the climate system on this time scale is the change from El Niño to La Niña – a natural, stochastic “seesaw” in the tropical Pacific called ENSO (El Niño Southern Oscillation).

The fact that El Niño is important for our purposes can already be seen by how much the trend changes if you leave out 1998 (see above): El Niño years are particularly warm (see chart), and 1998 was the strongest El Niño year since records began. Further evidence of the crucial importance of El Niño is that after correcting the global temperature data for the effect of ENSO and solar cycles by a simple correlation analysis, you get a steady warming trend without any recent slowdown (see next graph and Foster and Rahmstorf 2011). ENSO is responsible for two thirds of the correction. And if you nudge a climate model in the tropical Pacific to follow the observed sequence of El Niño and La Niña (rather than generating such events itself in random order), then the model reproduces the observed global temperature evolution including the “hiatus” (Kosaka and Xie 2013) .

One can also ask how the observed warming fits the earlier predictions of the IPCC . The result looks like this (Rahmstorf et al 2011):


Figure 3 Comparison of global temperature (average over 5 data sets, including 2 satellite series) with the projections from the 3rd and 4 IPCC reports. Pink: the measured values. Red: data after adjusting for ENSO, volcanoes and solar activity by a multivariate correlation analysis. The data are shown as a moving average over 12 months. From Rahmstorf et al. 2012.

And what about the ocean heat storage ? That is no additional effect, but part of the mechanism by which El Niño years are warm and La Niña years are cold at the Earth’s surface. During El Niño the ocean releases heat, during La Niña it stores more heat. The often-cited data on the heat storage in the ocean are therefore just further evidence that El Niño plays a crucial role for the “pause”.

Leading U.S. climatologist Kevin Trenberth has studied this for twenty years and has just published a detailed explanatory article. Trenberth emphasizes the role of long-term variations of ENSO, called pacific-decadal oscillation (PDO). Put simply: phases with more El Niño and phases with predominant La Niña conditions (as we’ve had recently) may persist for up to two decades in the tropical Pacific. The latter brings a somewhat slower warming at the surface of our planet, because more heat is stored deeper in the ocean. A central point here: even if the surface temperature stagnates our planet continues to take up heat. The increasing greenhouse effect leads to a radiation imbalance: we absorb more heat from the sun than we emit back into space. 90% of this heat ends up in the ocean due to the high heat capacity of water. The fact that the ocean continues to heat up, without pause, demonstrates that the greenhouse effect has not subsided, as we have discussed here.

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