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Data for: Bulk microphysics schemes may perform better with a unified cloud-rain category

Hu, Arthur Z.1; Igel, Adele L.1

Research facility: University of California, Davis
Published Mar 21, 2024 on Dryad. https://doi.org/10.5061/dryad.1g1jwsv48

Data files

Mar 21, 2024 version files 1.41 MB

Abstract

Bulk microphysics schemes continue to face challenges due in part to the necessary simplification of hydrometeor properties and processes that are inherent to any parameterization. In all operational bulk schemes, one such simplification is the division of liquid water into two subcategories (cloud and rain) when predicting the evolution of warm clouds. It was previously found that biases in collisional growth in a bulk scheme with these separate liquid water categories can be mitigated with a unified liquid water category in which cloud and rain are contained within the same category. In this study, we examine the effect of artificially separating the liquid water category on other microphysical processes and in more realistic settings. Both our idealized 1D and 3D results show that a unified category bulk scheme is fundamentally better at predicting the timing and intensity of rain from warm-phase cumulus clouds compared to a traditional (separate) category bulk scheme. This is because a unified category bulk scheme allows a bimodal distribution to exist within one traditional "rain" category, whereas separate category bulk schemes only have one mode per category. This advantage allows the unified bulk scheme to retain the information of the largest droplets even as they fall through a layer of small raindrops. A separate category bulk scheme fails to represent this bimodal feature in comparison.