Abstract
Based on the atmospheric regional climate model HIRHAM5, the single-column model version HIRHAM5-SCM was developed and applied to investigate the performance of a relative humidity based (RH-Scheme) and a prognostic statistical cloud scheme (PS-Scheme) in the central Arctic. The surface pressure as well as dynamical tendencies of temperature, specific humidity, and horizontal wind were prescribed from the ERA-Interim data set to enable the simulation of a realistic annual cycle. Both modeled temperature and relative humidity profiles were validated against radio soundings carried out on the 35th North Pole drifting station (NP-35). Simulated total cloud cover was evaluated with NP-35 and satellite-based ISCCP-D2 and MODIS observations. The more sophisticated PS-Scheme was found to perform more realistically and matched the observations better. Nevertheless, the model systematically overestimated the monthly averaged total cloud cover. Sensitivity studies were conducted to assess the effect of modified “tuning” parameters on cloud-related model variables. Two tunable parameters of the PS-Scheme and six tuning parameters contained in the cloud microphysics were analyzed. Lower values of the PS-Scheme adjustment parameter q0, which defines the shape of the symmetric beta distribution (acting as probability density function), as well as higher values of the cloud water threshold CWmin or autoconversion rate γ1 are able to reduce the overestimation of Arctic clouds. Furthermore, a lower cloud ice threshold γthr, which controls the Bergeron–Findeisen process, improves model cloudiness and the ratio of liquid to solid water content.
Highlights
Clouds play a central role in the Arctic climate system
To evaluate the performance of HIRHAM5-single-column climate model (SCM), a series of case studies was conducted, and model results were compared with NP-35 measurements carried out from middle of October 2007 to the beginning of April 2008
On the other hand, modeled and observed total cloud cover C tot were compared, where the latter was available from 6-hourly NP-35 weather reports
Summary
Clouds play a central role in the Arctic climate system. On the one hand, they reflect solar radiation cooling the Earth’s surface (cloud albedo effect), on the other hand, they absorb and (re-)emit terrestrial radiation warming the Earth’s surface (cloud greenhouse effect). Arctic air masses are normally cold, comparably dry and unpolluted [12], high-latitudes are mainly characterized by the occurrence of so-called boundary layer clouds (BLCs, [13,14,15]). These BLCs show large seasonal and interannual variability, which is reversely related to Arctic sea-ice variability [16,17]. The motivation to this study was to evaluate and possibly adapt the subgrid-scale parameterization of Arctic clouds in the single-column climate model (SCM) HIRHAM5-SCM.
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