Toward Transparency and Consistency: An Open‐Source Optics Parameterization for Clouds and Precipitation

Abstract In this study, a new open‐source package for cloud and precipitation modeling is introduced. Based on Mie theory and existing ice crystal data sets, the scheme generates optical properties for user‐defined gas bands, particle size distribution, and crystal habits, ensuring continuity across wide spectral bands and from small particles (clouds) to large particles (precipitation). Compared with existing schemes in GFDL's AM4‐MG2, it reduces shortwave reflection of liquid clouds at the top of the atmosphere (TOA) by 1.50 Wm −2 and increases that of ice clouds by 1.62 Wm −2 , based on offline radiative calculations. Using the new scheme, we find that cloud radiative effects are sensitive to microphysics variables such as particle size and habit, which affect the effective radius. Systematic flux biases may arise if the effective radius is not fully predicted in microphysics due to predefined size and habit distributions. We show that assuming spherical ice crystals underestimates ice‐cloud radiative effects by 3.20 Wm −2 in the longwave TOA and 2.76 Wm −2 in the shortwave TOA. These biases can be addressed by improving the effective radius approximation with a volume‐to‐radius ratio derived from in‐situ measurements. Combining these findings, we propose that climate models use a set of optics parameterizations for each hydrometeor type while adequently accounting for radiation effects caused by size and habit distributions. Uncertainties due to this simplification are evaluated. This study offers a consistent and physically based representation of radiative processes of clouds and precipitation in weather and climate simulations.