Flaws of scale-aware techniques in convective parameterizations, as discovered in NOAA’s operational convection-allowing modeling systems: an attempt to improve them.

Significant problems in numerical weather prediction modeling systems appear when the horizontal grid-spacing is between 20 km and 1 km and when deep convection is important. These scales are usually termed “Gray Scales”.  Techniques have been developed so that the behavior of the convective parameterization changes with the horizontal grid spacing of the model; such parameterizations are said to become “scale-aware”. Commonly used techniques involve applying a scaling approach to smoothly transition from parameterized to resolved convection. These are similar to an elegantly simple mathematical method originally developed by Arakawa et al. (2011), which scales the convective tendencies in dependence on the convective area fraction. Here we show that the scaling approaches are flawed, since they fail to consider the fact that the impacts of deep convection on those scales are not limited to one grid box, and usually – because of the scaling -- leads to light precipitation covering too much area, as we have previously shown in HRRR simulations. Any scaling approach is especially flawed in areas of light forcing (such as daytime heating) and in the tropics, when the explicit microphysics parameterization is not yet producing precipitation. We will show examples of these problems and discuss possible solutions as applied to NOAA’s new RRFS storm-scale modeling system.