- I am now quite convinced that most, if not all, previous estimates of feedback from our satellite observations of natural climate variability are in error.
- Furthermore, this error is usually in the direction of positive feedback, which will then give the illusion of a ‘sensitive’ climate system.
- The goal seems simple enough: to measure cloud feedbacks, we need to determine how much clouds change in response to a temperature change.
- But most researchers do not realize that this is not possible without accounting for causation in the opposite direction, i.e., the extent to which temperature changes are a response to cloud changes.
- As a result, it is not possible with current methods to measure feedbacks in response to a radiative forcing event such as a change in cloud cover, or even a major volcanic eruption, such as that from the 1991 eruption of Mt. Pinatubo.
- The reason is that the size of the radiative forcing of a temperature change overwhelms the size of the radiative feedback upon that temperature change, and our satellite measurements can not tell the difference.
- If you have an accurate estimate of the radiative forcing of temperature change, accurate estimates of radiative feedback can be made. But we do not have good estimates of this forcing during natural climate variations.
- Only in climate model simulations where a known amount of radiative forcing is imposed upon the model can this be done.
måndag 7 december 2009
Climate Sensitivity and Feedback 2
I continue on my previous post On Feedbacks by Lindzen and Spencer stimulated by Spencer's Can Global Warming Predictions be Tested with Observations of the Real Climate System?:
Spencer's concerns can be illustrated in the simple model
dT/dt = Q + A T - B T,
where T is temperature, e.g. global ocean surface temperature, t is time, Q is radiative heat forcing, A T is feed-back heat forcing from e.g. water vapour and clouds and B T is feed-back into outgoing LW radiation, with B a positive constant and A positive for positive feed-back.
The central problem is to estimate A from measurements of T, dT/dt and BT, from which the crucial climate sensitivity can be determined. The difficulty is to single out AT from Q + AT = dT/dt + BT. If Q is constant in time, then the time variation of Q + AT might reveal A. But as Spencer points out, the Q behind climate variations is unknown and so the climate sensitivity may be impossible to determine from observed variations, at least using this simple model, connecting to the simple model used by Lindzen and Choi in Climate feed-backs computed from ERBE data.
It seems that the only possibility of determining climate sensitivity is through accurate climate models with resolution of the turbulent convective heat transfer from ocean to stratosphere. It is conceivable that this is possible using adaptive finite element methods, a possiblity we are now exploring.
Compare Spencer's upcoming talk: On the Diagnosis of Radiative Feedback in the Presence of Unknown Radiative Forcing.