Comparison of model predicted cloud parameters and surface radiative fluxes with observations on the 100 km scale

Summary

Cloud parameters and surface radiative fluxes predicted by regional atmospheric models are directly compared with observations for a 10-day period in late summer 1995 characterized by predominantly large-scale synoptic conditions. Observations of total cloud cover and vertical cloud structure are inferred from measurements with a ground-based network of Lidar ceilometers and IR-radiometers and from satellite observations on a 100 kilometer scale. Ground-based observations show that at altitudes below 3 km, implying liquid water clouds, there is a considerable portion of optically non-opaque clouds. Vertical distributions of cloud temperatures simultaneously inferred from the ground-based infrared radiometer network and from satellite can only be reconciled if the occurrence of optically thin cloud structures at mid- and high tropospheric levels is assumed to be frequent. Results of three regional atmospheric models, i.e. the GKSS-REMO, SMHI-HIRLAM, and KNMI-RACMO, are quantitatively compared with the observations. The main finding is that all models predict too much cloud amount at low altitude below 900 hPa, which is then compensated by an underestimation of cloud amount around 800 hPa. This is likely to be related with the finding that all models tend to underestimate the planetary boundary layer height. All models overpredict the high-level cloud amount albeit it is difficult to quantify to what extent due to the frequent presence of optically thin clouds. Whereas reasonably alike in cloud parameters, the models differ considerably in radiative fluxes. One model links a well matching incoming solar radiation to a radiatively transparent atmosphere over a too cool surface, another model underpredicts incoming solar radiation at the surface due to a too strong cloud feedback to radiation, the last model represents all surface radiative fluxes quite well on average, but underestimates the sensitivity of atmospheric transmissivity to cloud amount.