Simulations of cloud radiative properties for climate modeling and remote sensing rely on accurate knowledge of the complex refractive index (CRI) of water.  Although conventional algorithms assume the CRI is temperature independent, recent infrared measurements of supercooled water at low temperatures have demonstrated that the CRI becomes increasingly ice-like at lower temperatures. In situ measurements were made of a supercooled liquid cloud at 241 K at the South Pole; corresponding downwelling infrared spectra agree well with simulated spectra only when the temperature dependence of the CRI is included. Here, we assess biases that result from ignoring the temperature dependence.  Based on simulations of pure, supercooled clouds, this leads to cloud retrievals with spurious ice components. Or, if the cloud is assumed to be liquid-only, the cloud thickness and droplet size are underestimated. TIA-based downwelling radiative fluxes are lower than those for the temperature-dependent CRI by as much as 1.7 W/m 2 (in cold regions), while top-of-atmosphere fluxes are higher by as much as 3.4 W/m 2 (in warm regions). Proper accounting of the temperature dependence of the CRI, therefore, leads to significantly greater local greenhouse warming due to supercooled clouds than previously predicted.