Description

The forecast of precipitation type from operational numerical weather prediction models can have a substantial impact on downstream users, such as those concerned with air and ground transportation, and also for surface energy, and hydrology. Well before the introduction of mixed-phase microphysics schemes into numerical weather prediction models, successful diagnostic techniques were designed using implicit assumptions about microphysical processes to allow estimation of the precipitation type. Among several factors that control the precipitation type at the surface, the vertical profile of wet-bulb temperature $T_w$ plays a key role (Bourgouin(2000) [26]), and a number of algorithms have been devised to determine the precipitation type based on the $T_w$ profile or quantities derived from it (e.g., Ramer(1993) [146]; Baldwin et al. 1994 [12] ; Bourgouin(2000) [26]; Schuur et al. (2012) [154]). A description of Ramer's algorithm can be found in Bourgouin(2000) [26] and Wandishin et al.(2005) [172]. We will briefly review those methods.

Ramer's approach (calwxt_ramer()) uses temperature( $T$ ), relative humidity( $RH$ ), and wet-bulb temperature( $T_w$ ) on different pressure levels to diagnose precipitation types. This procedure performs two checks before doing a full calculation. First, if the surface $T_w$ is greater than $2^oC$ , liquid precipitation is diagnosed. Second, if $T_w$ remains below a specified value at all levels, solid precipitation is expected. A full calculation will be needed if neither condition is satisfied. The basic parameters( $T$ , $RH$ , $T_w$ ) are used to determine layers where precipitation is likely to be generated and also to determine the ice fraction. A generating layer exists if relative humidity exceeds a specified threshold value over a sufficiently thick layer. The generating level is defined as the top of the highest generating layer. The ice fraction is the basic quantity calculated for diagnosing the precipitation type. Precipitation at the generating level is assumed to be entirely liquid if the $T_w$ is above a specified value. Otherwise, it is considered fully frozen. If frozen precipitation is dianosed at the generating level and if the $T_w$ is below freezing for the entire sounding below the generating layer, solid precipitation is assumed. As precipitation falls, the ice fraction value changes according to the vertical distribution of $T_w$ and relative humidity. The precipitation type is determined by the values of the ice fraction and the $T_w$ at the surface. If the ice fraction is greater than a specified threshold (e.g.,0.85), solid precipitation (i.e., snow or ice pellets) will be diagnosed. If the ice fraction is lower than another threshold (0.04), liquid precipitation (i.e., freezing precipitation or rain) is expected.

The Baldwin et al. algorithms (calwxt() and calwxt_revised()) also considers the vertical profile of the $T_w$ below saturated layers where precipitation is presumed to form. If this precipitation is presumed frozen, the precipitation type at the surface is obtained by using the vertically integrated departure of the $T_w$ from $0^oC$ in various layers and the temperature in the lowest model layer. A more complete description can be found in Bourgouin(2000) [26] and Wandishin et al.(2005) [172] .

Conceptually similar to the Baldwin algorithm, the Bourgouin method (calwxt_bourg()) computes the melting and freezing energies of warm and cold layers from a standard tephigram. The final precipitation type is determined by comparing the melting and freezing energies.

If the Zhao-Carr MP scheme is called, calwxt_dominant() takes the precipitation type solution from different algorithms (calwxt(), calwxt_ramer(), calwxt_revised(), and calwxt_bourg())and uses them up to output a dominant type.

GFDL MP scheme permits the prognostic surface precipitation to simultaneously consist of ice, snow and graupel at the same location. Hence if the GFDL MP scheme is called, the precipitation type at the surface is directly diagnosed from the explicit surface precipitation (i.e. ice, snow and graupel) predicted by the scheme and convective rainfall predicted by the cumulus scheme if surface temperature is below $0^oC$ .

Intraphysics Communication

Argument Table

General Algorithm

GFS MP Generic Post General Algorithm