Editing Openai/6938382f-f9e4-8003-a158-6d812c1bce84 (section)

===== 2.5 Where error types are conflated or double-counted =====

Some key conflations:
* Systematic vs random error - He correctly notes cloud errors are systematic. Propagation_of_Error_and_the_Re… - Then uses random-error propagation formulas (RSS over N steps) as if the ±4 W/m² were independent draws each year. This is inconsistent with his own diagnosis.
* Calibration RMSE vs “resolution limit” - A ±4 W/m² climatological LWCF RMSE does not mean the model “cannot resolve” smaller perturbations in forcing; it means its long-term cloud radiative effect has that level of bias/noise relative to a particular satellite product. In practice, differences between scenarios and temporal changes can be simulated with much higher precision than the bias vs observations.
* Spatial field error vs global-mean flux uncertainty - Lauer & Hamilton’s RMSE is over grid-point fields. Frank treats it as a global scalar flux uncertainty that must apply directly to the global-mean energy budget each year. That’s a strong and unjustified simplification.