What Are We Missing about Ice Crystal Growth in Numerical Models, and How Can New Single Particle Growth Measurements Help?

Numerical cloud model parameterizations of ice crystal growth have followed nearly the same methodology for over 40 years. While early parameterizations were often informed by laboratory measurements, later methods moved towards using methods informed primarily by in-situ measurements. These latter approaches are both useful and attractive because they constrain the particle masses and size to conform to observations in certain limits. However, the approach has limitations as well, such as: The time-scale connecting mass and size is unknown from observations, and thus estimates are required from theories that not well tested or constrained especially at low temperatures. Crystals are forced to conform to single power-law relationships among mass, size, area and fall-speed whereas real crystals contain a bewildering array of crystal types. This crystal diversity could be important for the microphysics and radiative properties of clouds, but even current Lagrangian microphysical methods cannot address this issue. We will show that new and emerging measurement approaches provide quantitative information to inform and potentially improve the representation of ice in numerical models. For instance, models often separate pristine and snow categories by a size boundary. Our measurements indicate that this boundary is better represented in terms of a relative supersaturation, and this can be incorporated into many models. Recent measurements show that crystal growth rates at low temperatures are statistically distributed, which may provide better parameterizations for bulk models and allows a representation of crystal diversity in Lagrangian microphysical schemes. Recent in-situ observations and lab measurements using new devices reveal the details of crystal complexity on small crystals and show how complexity can develop spontaneously on relatively flat faces. These measurements provide critical data that can be used to quantify the development of crystal complexity, and to rethink how ice growth processes should be represented in cloud models.