Abstract:
Cloud Resolving Models use microphysics parameterisation schemes for the simulation
of clouds. The thesis reports on the introduction of two single-moment
Bulk Microphysics Parameterisation (BMP) schemes in the Nonhydrostatic -
coordinate Model (NSM). The rst BMP is known as the PURDUE-LIN scheme,
and can be used with ve (excluding graupel) or six (including graupel) classes
of the water substance. The second scheme was developed using the PURDUELIN
scheme as a starting point, and is known as SBU-YLIN. Graupel and snow
share a category and processes in the latter scheme. Simulations of two hours
in length are made, with convection initiated through inserting a warm thermal
into a cooler environment, using a six-class and ve-class PURDUE-LIN and the
SBU-YLIN BMPs. The simulations are performed at various horizontal resolutions
of 500 m, 1 km and 2 km. The six-class PURDUE-LIN scheme simulates
more rainfall than the ve-class PURDUE-LIN and the SBU-YLIN schemes.
The SBU-YLIN scheme generally rains the least, looses the least water vapour
to hydrometeors and warms up the least. The PURDUE-LIN schemes simulate
two convective cells in a no shear environment. The maximum updrafts
associated with the rst cell (triggered by the warm perturbation) are similar
in all the simulations. The second cell is triggered by a cold pool. While the cold pool is stronger in the six-class PURDUE-LIN scheme simulations, the updrafts
in the second cell are stronger in the ve-class PURDUE-LIN simulation.
The SBU-YLIN scheme generally simulates just one cell because of a weak cold
pool. Simulations were also made for three di erent periods dominated by suppressed
convection with deep convection at the beginning and end of the three
periods, forced with large scale tendencies observed during the Tropical Ocean
Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA
COARE). The NSM is able to capture di erences in the suppressed and deep
convection periods. Qualitatively, the simulations provide new insight into the
interplay between cloud microphysics and cloud dynamics, and points out the
potential for better describing the uncertainty range associated with projections
of future climate change, through the improvement and stochastic application
of cloud microphysics schemes.
