Climate feedbacks determine how much surface temperatures will eventually warm to balance anthropogenic radiative forcing, but remain difficult to constrain. The climate feedback due to some process X is defined as the partial derivative of outgoing radiation at the top of the atmosphere with respect to surface temperature following a change in X, λX=-∂Rout/TS|X, with total climate feedback a summation from all processes, λtotal=∑λX. Standard approaches evaluate climate feedbacks from finite temporal changes in surface temperatures and outgoing radiation, following observed or simulated perturbations to climate state. However, this introduces significant linear combination error (λtotal≠∑λX) when the applied perturbation is large enough to achieve a good signal-to-noise ratio. This study presents a new semi-empirical evaluation of non-cloud climate feedbacks, constrained instead by spatial variation in outgoing radiation and climate state. First, we observationally constrain functional relations for outgoing radiation over ocean and land in terms of surface temperature, pressure, relative humidity, the height of the tropopause, fractional clound amount and latitude. Then, these functional relations are differentiated with respect to surface temperature to calculate the climate feedbacks for infinitesimal perturbation, eliminating linear combination error at high signal-to-noise ratio. We find, when combined with a recent cloud feedback estimate, a present-day total climate feedback of -0.99 (-0.75 to -1.22 at 66% range) Wm-2K-1. Our method is independent of temporal variation approaches to evaluate climate feedback allowing Bayesian combination to further reduce uncertainty.