Evaluating the Performance of Past Climate Model Predictions

[bdgwx]

A new study appeared yesterday evaluating the skill of past climate model simulations.

https://www.sciencemag.org/news/2019/12/even-50-year-old-climate-models-correctly-predicted-global-warming

The news article contains a link for free access to the publication. Here is the paywall link though.

https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019GL085378

And here is the materials available on github.

https://github.com/hausfath/OldModels

Abstract

Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyse the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally‐estimated forcings were taken into account.

Plain Language Summary

Climate models provide an important way to understand future changes in the Earth's climate. In this paper we undertake a thorough evaluation of the performance of various climate models published between the early 1970s and the late 2000s. Specifically, we look at how well models project global warming in the years after they were published by comparing them to observed temperature changes. Model projections rely on two things to accurately match observations: accurate modeling of climate physics, and accurate assumptions around future emissions of CO₂ and other factors affecting the climate. The best physics‐based model will still be inaccurate if it is driven by future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO₂ (and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO₂ and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts, and increases our confidence that models are accurately projecting global warming.

[bdgwx]

One model that gets a lot of attention is that done by Hansen and published in 1988. See H88 here.

He models three different scenarios: A, B, and C. A is a high emissions scenario, B is medium emission scenario, and C is a low emission scenario. Scenario A assumes exponential growth of GHG emissions plus hypothetical new emissions. B assumes modest GHG emissions most similar to what has been experienced so far. And C assumes drastic curtailment of all GHG emissions by 2000. Scenarios B and C inject volcanic eruptions in the years 1995 and 2015 similar in magnitude to El Chichon and Agung. Scenario A has no such volcanic eruptions injected. Scenario A is claimed to produce an equivalent forcing of 2xCO2 by 2030, B by 2060, and never for C. Scenario B was said to be most realistic and likely future trajectory.

The actual trajectory of forcing lies between B and C. The HDAS2019 publication referenced in this thread estimates B's forcing as 27% higher than what actually transpired. Today we know this is partially due to the Montreal Protocol and probably the somewhat higher volcanic aerosol forcing that occurred due to Pinatubo 1991 and several VEI 4+ eruptions in the early 2000s as well. Had H88 used correct inputs in a hypothetical scenario that closely matched reality then that scenario would have exhibited very high skill in predicting the global mean surface temperature. This tells us the problem was more with the assumed inputs than with the model physics.