Evaluation and Sensitivity of Arctic clouds simulated by the single-column climate model HIRHAM5-SCM

• Main Authors: Klaus, Daniel, Dethloff, Klaus, Dorn, Wolfgang, Rinke, Annette, Mielke, Moritz
• Format: Conference Object
• Language: unknown
• Published: 2012
• Subjects: Arctic; North Pole
• Online Access: https://epic.awi.de/id/eprint/31066/; https://epic.awi.de/id/eprint/31066/1/Poster_ICCP-2012_No290_dklaus.pdf; https://hdl.handle.net/10013/epic.39951; https://hdl.handle.net/10013/epic.39951.d001

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 (RH-Scheme) and a prognostic statistical (PS-Scheme) cloud 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). In addition, 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 matches the observations better than the RH-Scheme. Nevertheless, the model overestimates the monthly averaged total cloud cover in the Arctic systematically almost throughout the year. Thus, sensitivity experiments were conducted to assess the effect of changing model adjustment parameters. Two tunable parameters of the PS-Scheme and several tuning parameters contained in the cloud microphysics were analyzed. Both the PS-Scheme adjustment parameter q_0, which defines the shape of the symmetric beta distribution (applied probability density function), and the minimum cloud water content CW_min are potentially able to reduce the overestimation of Arctic cloud cover in the model. Furthermore, the cloud ice threshold g_thr, which controls the Bergeron-Findeisen process, could correct the overestimation/underestimation of liquid/ice water content.