Quantitative comparison of presumed-number-density and quadrature moment methods for the parameterisation of drop sedimentation

In numerical weather prediction models, parameterisations are used as an alternative to spectral modelling. One type of parameterisations are the so-called methods of moments. In the present study, two different methods of moments, a presumed-number-density-function method with finite upper integration limit and a quadrature method, are applied to a one-dimensional test case (‘rainshaft’) for drop sedimentation. The results are compared with those of a reference spectral model. An error norm is introduced, which is based on several characteristic properties of the drop ensemble relevant to the cloud microphysics context. This error norm makes it possible to carry out a quantitative comparison between the two methods. It turns out that the two moment methods presented constitute an improvement regarding two-moment presumed-number-density-function methods from literature for a variety of initial conditions. However, they are excelled by a traditional three-moment presumed-number-density-function method which requires less computational effort. Comparisons of error scores and moment profiles reveal that error scores alone should not be taken for a comparison of parameterisations, since moment profile characteristics can be lost in the integral value of the error norm

Modelling of the Population Dynamics of Sedimenting Hydrometeors with Moment Methods

For the treament of clouds and precipitation in weatherforecast or climate models, a direct spectral representation of the microphysical processes is computationally infeasible. Therefore, their effects have to be considered in an approximative, parameterised way. It is then possible that the model results are not sensible in a cloud microphysics context. In order to avoid this, in this dissertation a new parameterisation of sedimentation (two moment method) is developed and tested in a 1D model. The parameterisation is based on a hydrometeor distribution with bounded domain and is implemented in two ways: 1) truncated Gamma-distribution: compared to already existing parameterisations, the model results are considerably improved (for drops as well as for ice crystals). Investigations include the computation time, the sensitivity of the results on the upper hydrometeor size limit and an optimisation concerning this limit. The development of a rain cloud is simulated by adding drop collisions to the test case. 2) Beta-distribution: It contains an additional free parameter. Its diagnostic relationship has a strong impact on the results

Modellierung des Ensembleverhaltens von sedimentierenden Hydrometeoren mittels Momentenverfahren

For the treament of clouds and precipitation in weatherforecast or climate models, a direct spectral representation of the microphysical processes is computationally infeasible. Therefore, their effects have to be considered in an approximative, parameterised way. It is then possible that the model results are not sensible in a cloud microphysics context. In order to avoid this, in this dissertation a new parameterisation of sedimentation (two moment method) is developed and tested in a 1D model. The parameterisation is based on a hydrometeor distribution with bounded domain and is implemented in two ways: 1) truncated Gamma-distribution: compared to already existing parameterisations, the model results are considerably improved (for drops as well as for ice crystals). Investigations include the computation time, the sensitivity of the results on the upper hydrometeor size limit and an optimisation concerning this limit. The development of a rain cloud is simulated by adding drop collisions to the test case. 2) Beta-distribution: It contains an additional free parameter. Its diagnostic relationship has a strong impact on the results

A comparative study of WRF model simulations and aircraft observations in the Canadian Tundra

We present a case study of the formation of a small-scale vortex, which has been observed by the aircraft campaign AIRMETH2 in the delta of the Mackenzie River, Canada. AIRMETH2 was carried out in July 2012 with the purpose to measure methane concentrations over arctic wetlands, thereby also providing a high-resolution data set of meteorological quantities in the lower troposphere. While the observed vortex of about 50 km horizontal scale is not resolved in the ERA-Interim data, high-resolution WRF simulations with a mesh size of about 2 km can indeed model its formation. The aircraft observations are then used to validate the model results in the lower troposphere. It turns out that the position of the vortex in the model is somewhat shifted in comparison to the observed vortex. Other meteorological quantities are also compared. For example, we find deviations in the structure of vertical temperature profiles