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Who Really Warms the Planet: The Information Trail of Climate Drivers ✎

Original: "Quantitative assessment of drivers of recent climate variability: An information theoretic approach"
· Ankush Bhaskar, Durbha Sai Ramesh, Geeta Vichare, Triven Koganti, S. Gurubaran
arXiv:1607.01529 · 2016-07-06 · arXiv non-exclusive · independent analysis · 2 min
Atmospheric and Oceanic Physics
Entropy transfer showed that CO₂, methane, and volcanic aerosols almost equally drove global temperature in 1984–2005.

In a climate trial, the judge doesn't listen to who shouts loudest. He watches who whispers to whom. Nine witnesses, from carbon dioxide to cosmic rays, testified from 1984 to 2005. Their statements were recorded every month. The judge doesn't trust mere coincidences, because two witnesses might echo each other without knowing who started first. He looks for a one-way flow of information.

Entropy transfer is a way to measure how much information about the future of one series is contained in the past of another series, beyond what is already known from its own past. If one series 'whispers' to another, it is a driver.

The records were cleaned of slow trends, leaving fast fluctuations. Then, for each pair of 'suspect and temperature,' they calculated who whispers to whom, with delays from zero to ten months. To filter out random coincidences, the records were shuffled one hundred times to see if the signal persisted. If the whisper disappeared after shuffling, then in the real data it was genuine.

The judge delivered a verdict: carbon dioxide, methane, and volcanic aerosols whispered to temperature almost equally, accounting for 24%, 19%, and 23% of the total information flow. Ultraviolet radiation and El Niño also whispered, but more weakly. Cosmic rays, nitrous oxide, and total solar radiation remained silent.

Previously, correlations could not distinguish cause from effect: a warm ocean also releases more CO₂. The judge hears the direction of the whisper. It turned out that volcanic aerosols from the El Chichón eruption in 1982 and Pinatubo in 1991 left a clear mark in the records. Nitrous oxide, despite being a potent greenhouse gas that stays in the atmosphere for about 120 years, barely whispered because of its low concentration.

This method requires no model assumptions, so it can serve as an independent check for climate models. The judge doesn't know the physics but sees who controls whom. His verdict does not negate anthropogenic warming; rather, it clarifies that natural variability contributed comparably to short-term temperature fluctuations during those years. Now the judge is ready for new cases: longer records, paleoclimate reconstructions, and other witnesses.

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Nitrous oxide (N₂O) has a strong radiative effect per molecule and stays in the atmosphere for about 120 years, yet its contribution turned out to be marginal due to low concentration. Volcanic aerosols from the 1982 El Chichón and 1991 Pinatubo eruptions produced an optical depth spike that the method confidently identified as a temperature driver.

In Kim Stanley Robinson's novel The Ministry for the Future, climatologists try to separate natural fluctuations from the anthropogenic signal to justify geoengineering measures. The entropy transfer method from this paper resembles their tool for identifying causal links in climate data.

TE_{x\to y}(\tau) = \sum P(y(t+\tau), y(t), x(t)) \log_2 \left( \frac{P(y(t+\tau), y(t), x(t)) P(y(t))}{P(x(t), y(t)) P(y(t+\tau), y(t))} \right)
The amount of information about the future of y provided by knowing the past of x, beyond what is already known from the past of y.
NTE_{x\to y}(\tau) = \frac{TE_{x\to y}(\tau)}{\sqrt{H_x H_{y+\tau}}}
Entropy transfer divided by the geometric mean of the entropies of x and y, allowing comparison across different variable pairs.
D_{x\to y}(\tau) = NTE_{x\to y}(\tau) - NTE_{y\to x}(\tau)
The difference in normalized information flows; a positive value indicates that x is a driver of y.
Concepts
natural variability North Atlantic Oscillation interannual variability seasonal cycle ENSO NOAA CPC Multivariate ENSO Index climate Jin-Timmermann model El Niño-Southern Oscillation ERSST spring predictability barrier TAO/TRITON moorings climate model UAH satellite record information theory El Niño index Teleconnection granger causality IRI