Evaluation of Microphysical Parameterizations


Investigators: 

J. M. Straka, M. S. Gilmore, K. Kanak, and E. N. Rasmussen


Equations that will represent the Gamma drop spectrum distribution changes more physically are being derived, by allowing certain parameters to vary which have formerly been assumed to be constant.  We are working on a set of equations and their theoretical solutions that will allow the distribution spectrum to vary with diffusional (e.g., evaporation/condensation), collection and other growth processes in a more realistic manner.  We will also develop discretized forms of these equations to be incorporated in numerical models.

The equations that represent two microphysical processes, for which total number concentration (Nt) should be conserved, are integrated over sizes of hydrometeor diameters (D) for one- and two moment methods. The gamma distribution function is assumed and incorporates total mixing ratio q, Nt, and mean diameter, Dn, (inverse of the distribution slope λ). In all of the methods, the slope intercept (no), is diagnosed or specified but not predicted. The moment methods explored include:

• The one-moment method where q is predicted, no is specified, and Nt and Dn are diagnosed,
• The one-moment method where q is predicted, Dn is specified, and Nt and no are diagnosed,
• The two-moment method where q and Nt are predicted, and no and Dn are diagnosed, and
• The two-moment method where q and Dn are predicted, and Nt and no are diagnosed.

To more easily discern the strengths and weaknesses of each moment-method, two processes are considered: vapor diffusional growth and continuous collection growth, and in both cases there is no introduction of new particles (dNt/Dt = 0). It is demonstrated for the processes examined that all of the schemes fail to conserve Nt and have other unphysical attributes, except the two-moment method where q and Nt are predicted.


Publications on this topic:

This research is supported by  the National Science Foundation (NSF) Grants ATM-0340639, ATM-0339519, ATM-9986672, ATM- 0003869, and ATM-0119398. Partial funding for this research was provided by the National Severe Storms Laboratory under NOAA–OU Cooperative Agreement NA17RJ1227. K. Kanak is supported by the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) under Award NA17RJ1227 from the NOAA, U.S. Department of Commerce, and NSF ATM-0135510.


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 and do not necessarily reflect the views of the National Science Foundation.