Abstract
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.
Highlights
The vertical component of atmospheric motions, typically on the order of 1–10 cm s−1, is generally much weaker than its horizontal counterpart, often by 2 orders of magnitude when examined at the synoptic scale
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 Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in central Oklahoma, and the Deutscher Wetterdienst (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
Summary
The vertical component of atmospheric motions, typically on the order of 1–10 cm s−1, is generally much weaker than its horizontal counterpart, often by 2 orders of magnitude when examined at the synoptic scale. Hydrostatic models assume hydrostatic balance, where the weight of an air parcel is balanced by the vertical pressure gradient force This is usually a good approximation at the synoptic scale, and is generally applied in global-scale climate and NWP models. The aircraft measurements are usually related to intensive field campaigns with limited spatial and temporal coverage, which restricts their usability Another measurement technique uses remote sensing by vertically pointing Doppler radars and lidars. We use ground-based vertically-pointing Doppler cloud radar measurements to evaluate the ability of the non-hydrostatic regional NWP model AROME (Seity et al, 2010) to simulate the vertical velocity fields. 3, we outline the pertinent features of the mesoscale model AROME Data from both sources require further processing to obtain suitable cloud base vertical velocities for comparison, and this important step is discussed in Sect.
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