- climate forecasting has to focus on the slow evolution of the circulation in the world ocean and slow changes in land use and natural vegetation...
- it is not a little bit alarming that the current generation of climate models cannot simulate such fundamental phenomena as the Pacific Decadal Oscillation. I will not trust any climate model until and unless it can accurately represent the PDO and other slow features of the world ocean circulation. Even then, I would remain skeptical about thepotential predictive skill of such a model many tens of years into the future.
- If I were still young, I would attempt to build a conceptual climate model based on a deterministic representation of the world ocean and a stochastic representation of synoptic activity in the atmosphere.
- From my background in turbulence I look forward with grim anticipation to the day that climate models will run with a horizontal resolution of less than a kilometer. The horrible predictability problems of turbulent flows then will descend on climate science with a vengeance.
Tennekes scepticism as to the predictive capability of current climate models seems to be well founded, but his prediction of the "horrible predictability problems of turbulent flow", may well be too pessimistic
Our experience of computing turbulent flow indicates that a global adaptive grid of say 1000 x 1000 x 100 = 100 million mesh points could capture long-time turbulent motion of a coupled ocean-atmosphere system modeled by the full 3d Navier-Stokes equations, and thus potentially could offer some prediction capability. At least it seems worthwhile to try, and the core of the computational technology is available in FEniCS/Unicorn.
Tennekes also discusses the need of giving not only forecasts but also forecasts of forecast skills. This couples to the automatic posteriori error estimation in FEniCS/Unicorn based on computing output sensitivities by solving associated dual linearized problems.
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