1Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
2Meteorology Department, University of Reading, Reading, UK
3Division of Atmospheric Sciences, Department of Physics, University of Helsinki, Helsinki, Finland
Received: 02 Mar 2011 – Published in Atmos. Chem. Phys. Discuss.: 22 Mar 2011
Abstract. The statistics of cloud base vertical velocity simulated by the non-hydrostatic mesoscale model AROME are compared with Cloudnet remote sensing observations at two locations: the ARM SGP site in central Oklahoma, and the DWD observatory at Lindenberg, Germany. The results show that AROME significantly underestimates the variability of vertical velocity at cloud base compared to observations at their nominal resolution; the standard deviation of vertical velocity in the model is typically 4–8 times smaller than observed, and even more during the winter at Lindenberg. Averaging the observations to the horizontal scale corresponding to the physical grid spacing of AROME (2.5 km) explains 70–80 % of the underestimation by the model. Further averaging of the observations in the horizontal is required to match the model values for the standard deviation in vertical velocity. This indicates an effective horizontal resolution for the AROME model of at least 10 km in the presented case. Adding a TKE-term on the resolved grid-point vertical velocity can compensate for the underestimation, but only for altitudes below approximately the boundary layer top height. The results illustrate the need for a careful consideration of the scales the model is able to accurately resolve, as well as for a special treatment of sub-grid scale variability of vertical velocities in kilometer-scale atmospheric models, if processes such as aerosol-cloud interactions are to be included in the future.
Revised: 26 Aug 2011 – Accepted: 30 Aug 2011 – Published: 07 Sep 2011
Tonttila, J., O'Connor, E. J., Niemelä, S., Räisänen, P., and Järvinen, H.: Cloud base vertical velocity statistics: a comparison between an atmospheric mesoscale model and remote sensing observations, Atmos. Chem. Phys., 11, 9207-9218, doi:10.5194/acp-11-9207-2011, 2011.