Evaluation of cloud properties and precipitation for stratiform and convective simulations. It has been shown previously that simulations of frontal stratiform precipitation events are sensitive to the representation of snow in the cloud microphysics parameterization, while convective precipitation events are mainly sensitive to the representation of the largest rimed ice species (either graupel or hail). It is important to understand how model modifications designed to improve moist processes under certain synoptic conditions affect simulations during different conditions. DOE scientists at Brookhaven National Laboratory and collaborators performed microphysics sensitivity experiments of the representation of snow and the rimed ice species for two composites of 15 stratiform and 15 convective observed precipitation events. Cloud properties and surface precipitation characteristics of all events were rigorously evaluated against satellite- and radar-derived observations. Simulations that include graupel and a temperature-dependent snow intercept parameter during both convective and stratiform events yielded ISCCP-cloud classifications that consistently agreed better with satellite observations. The enhanced depositional growth rates in these experiments led to significantly improved cloud-top pressure distributions. Compared to previous idealized experiments, surface precipitation was less sensitive to whether graupel or hail was chosen as the rimed ice species. However, including graupel in convective and stratiform events consistently yielded better peak precipitation rates compared to observed precipitation rates from a radar-rain gauge combined product. Reference: K. Van Weverberg, N. van Lipzig, L. Delobbe, and A. Vogelmann, 2012: “The role of precipitation size distributions in km-scale NWP simulations of intense precipitation: evaluation of cloud properties and surface precipitation,” Q. J. Royal Meteor. Soc., in press.

Motivation ● Stratiform and convective precipitation are sensitive to, respectively, the snow and the rimed ice parameterizations. However, it is important to understand how model improvements, which are tailored to certain synoptic conditions, affect simulations during different conditions. Approach ● Microphysics sensitivity experiments were performed for composites of 15 convective and 15 stratiform intense precipitation events. A detailed evaluation was performed against radar and satellite observations. Result ● Simulations that included a temperature- dependent snow intercept parameter improved cloud-top pressure distribution in all events. Including graupel consistently improved the peak precipitation rates in all events, although sensitivity was smaller than for previous idealized simulations. The role of size distributions in km-scale NWP simulations of intense precipitation: evaluation of cloud properties and surface precipitation K. Van Weverberg, N. van Lipzig, L. Delobbe, and A. Vogelmann, 2012: “The role of precipitation size distributions in km-scale NWP simulations of intense precipitation: evaluation of cloud properties and surface precipitation,” Q. J. Royal Meteor. Soc., in press. Evaluation of the stratiform composite of 15 simulations using an ISCCP-like cloud classification, based on cloud optical thickness and cloud top pressure. The top left panel shows the area covered by each cloud class as observed by SEVIRI (in 10 3 km 2 ). The other panels show the difference in area between the simulations and SEVIRI. ExpH and ExpG are identical except that the rimed ice species is hail in ExpH and graupel in ExpG. ExpGS is identical to ExpG, except that the snow size distribution varies with temperature. Cloud classes are: cirrus (Ci), cirrostratus (Cs), cumulonimbus (Cb), altocumulus (Ac), altostratus (As), nimbostratus (Nb), cumulus (Cu), stratocumulus (Sc) and stratus (St). Numbers to the right and below each figure denote the row and column totals.