A Semi-Lagrangian Advection Algorithm for Falling Raindrops in aTwo-Moment Microphysics Schemes
- 1NOAA/ESRL/PSL, Boulder, Colorado, United States of America (songyouhong@gmail.com)
- 2NOAA/ESRL/GSL, Boulder, Colorado, United States of Americ
- 3University of Colorado/CIRES, Boulder, Colorado, United States of America
- 4NOAA/NCEP/EMC, College Park, Maryland, United States of America
A semi-Lagrangian algorithm (SLA) is implemented in NOAA's Global Forecast System (GFS) for
simulating raindrop sedimentation in a double-moment microphysics schemes. This SLA includes
a significant improvement to its predecessor for single-moment raindrop sedimentation. It is
numerically stable and mass-conserving when used to sediment raindrops in double-moment
microphysics schemes. Numerical results from an idealized single-column model show that the
SLA overcomes an issue of mass accumulation at the cloud bottom in the case of the Eulerian
algorithm for raindrop sedimentation, which is due to the assumption of constant terminal
velocity within a time step of sedimentation. The results from the single-column model also show
that the time step in the SLA can be 10 times greater than that in the Eulerian algorithm for
sedimentation. Further numerical experiments using NOAA's GFS show that using the SLA
mitigates the numerical instability problem associated with a newly-implemented double-moment
microphysics scheme in the GFS.
How to cite: Hong, S., Li, H., Bao, J.-W., Grell, G., and Sun, R.: A Semi-Lagrangian Advection Algorithm for Falling Raindrops in aTwo-Moment Microphysics Schemes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8984, https://doi.org/10.5194/egusphere-egu22-8984, 2022.
