There are a lot of ways physics can explain climate warming. But the best explanations are those that successfully backtest – where the physics can reliably hindcast the past from the present.
Two issues, in particular, plague the IPCC CMIPx model series: (1) cloud formation and (2) the role of el Nino and the Southern Oscillation (ENSO).
Dr. Roy Spencer: “Since El Nino produces global average warmth, and La Nina produces global average coolness, I have been using our 1D forcing feedback model of ocean temperatures (published by Spencer & Braswell, 2014) to examine how the historical record of ENSO variations can be included, by using the CERES satellite-observed co-variations of top-of-atmosphere (TOA) radiative flux with ENSO.”
Spencer’s one dimensional model of mid-latitude climate dynamics generates the requisite net radiative feedback parameter corresponding to an equilibrium climate sensitivity of 1.91 degree C, matches the sea surface temperature (SST) observations during 1979-2020, and corresponds to IPCC HadSST1 or HadSST4 data.
As Dr. Spencer explains:
“ENSO can then be turned off in the model to see how it affects our interpretation of (and causes of) temperature trends over various time periods. Or, one can examine the affect of assuming some level of non-equilibrium of the climate system at the model initialization time.
“If nothing else, the results in Fig. 3 might give us some idea of the ENSO-related SST variations for 300-400 years before anthropogenic forcings became significant, and how those variations affected temperature trends on various time scales. For if those naturally-induced temperature trend variations existed before, then they still exist today.”
So which is the dominant driver of climate – natural variation or anthropogenic GHG emissions?
Econophysics2020 