In this study, a novel optics scheme for cloud and precipitation modeling is introduced. Based on the Mie theory and existing datasets on ice crystals, the scheme offers an open-source package for generating data for user-defined gas bands, particle size distributions, and crystal habits. This approach ensures continuity across wide spectral bands and from small particle sizes (i.e., clouds) to large particle sizes (i.e., precipitation). It overcomes biases in existing schemes caused by numerical accuracy and inconsistency. Results are evaluated using an offline version of radiation codes used in a global circulation model. Using the flexible new scheme, it is found that cloud radiative effects are sensitive to microphysics variables such as particle size and habit distribution, which have an impact on effective radius. Systematic biases in radiation fluxes may occur if the effective radius is not fully predicted in microphysics processes due to predefined size and habit distributions. We show that when models assume spherical ice crystals, they dramatically underestimate radiative effects in ice clouds. The biases can be addressed by improving the effective radius approximation with a volume-to-radius ratio calculated from in-situ measurements. Combining these findings, we propose that numerical models can use a set of optics parameterizations for each type of hydrometer while accurately accounting for radiation effects caused by variations in size and habit distributions. Uncertainties due to this simplification are evaluated. This study offers a pathway towards a simple, consistent, and physical representation of radiative processes of clouds and precipitation in weather and climate simulations.