Abstract. The nonhydrostatic regional climate model CCLM was used for a long-term hindcast run (2002–2016) for the Weddell Sea region with resolutions of 15 and 5 km and two different turbulence parametrizations. CCLM was nested in ERA-Interim data and used in forecast mode (suite of consecutive 30 h long simulations with 6 h spin-up). We prescribed the sea ice concentration from satellite data and used a thermodynamic sea ice model. The performance of the model was evaluated in terms of temperature and wind using data from Antarctic stations, automatic weather stations (AWSs), an operational forecast model and reanalyses data, and lidar wind profiles. For the reference run we found a warm bias for the near-surface temperature over the Antarctic Plateau. This bias was removed in the second run by adjusting the turbulence parametrization, which results in a more realistic representation of the surface inversion over the plateau but resulted in a negative bias for some coastal regions. A comparison with measurements over the sea ice of the Weddell Sea by three AWS buoys for 1 year showed small biases for temperature around ±1 K and for wind speed of 1 m s−1. Comparisons of radio soundings showed a model bias around 0 and a RMSE of 1–2 K for temperature and 3–4 m s−1 for wind speed. The comparison of CCLM simulations at resolutions down to 1 km with wind data from Doppler lidar measurements during December 2015 and January 2016 yielded almost no bias in wind speed and a RMSE of ca. 2 m s−1. Overall CCLM shows a good representation of temperature and wind for the Weddell Sea region. Based on these encouraging results, CCLM at high resolution will be used for the investigation of the regional climate in the Antarctic and atmosphere–ice–ocean interactions processes in a forthcoming study.

Abstract. In the present study a non-motion-stabilized scanning Doppler lidar was operated on board of RV Polarstern in the Arctic (June 2014) and Antarctic (December 2015–January 2016). This is the first time that such a system measured on an icebreaker in the Antarctic. A method for a motion correction of the data in the post-processing is presented. The wind calculation is based on vertical azimuth display (VAD) scans with eight directions that pass a quality control. Additionally a method for an empirical signal-to-noise ratio (SNR) threshold is presented, which can be calculated for individual measurement set-ups. Lidar wind profiles are compared to total of about 120 radiosonde profiles and also to wind measurements of the ship. The performance of the lidar measurements in comparison with radio soundings generally shows small root mean square deviation (bias) for wind speed of around 1 m s−1 (0.1 m s−1) and for wind direction of around 10∘ (1∘). The post-processing of the non-motion-stabilized data shows a comparably high quality to studies with motion-stabilized systems. Two case studies show that a flexible change in SNR threshold can be beneficial for special situations. Further the studies reveal that short-lived low-level jets in the atmospheric boundary layer can be captured by lidar measurements with a high temporal resolution in contrast to routine radio soundings. The present study shows that a non-motion-stabilized Doppler lidar can be operated successfully on an icebreaker. It presents a processing chain including quality control tests and error quantification, which is useful for further measurement campaigns.

Low-level jets (LLJs) are climatological features in polar regions. It is well known that katabatic winds over the slopes of the Antarctic ice sheet are associated with strong LLJs. Barrier winds occurring, e.g., along the Antarctic Peninsula may also show LLJ structures. A few observational studies show that LLJs occur over sea ice regions. We present a model-based climatology of the wind field, of low-level inversions and of LLJs in the Weddell Sea region of the Antarctic for the period 2002–2016. The sensitivity of the LLJ detection on the selection of the wind speed maximum is investigated. The common criterion of an anomaly of at least 2 m/s is extended to a relative criterion of wind speed decrease above and below the LLJ. The frequencies of LLJs are sensitive to the choice of the relative criterion, i.e., if the value for the relative decrease exceeds 15%. The LLJs are evaluated with respect to the frequency distributions of height, speed, directional shear and stability for different regions. LLJs are most frequent in the katabatic wind regime over the ice sheet and in barrier wind regions. During winter, katabatic LLJs occur with frequencies of more than 70% in many areas. Katabatic LLJs show a narrow range of heights (mostly below 200 m) and speeds (typically 10–20 m/s), while LLJs over the sea ice cover a broad range of speeds and heights. LLJs are associated with surface inversions or low-level lifted inversions. LLJs in the katabatic wind and barrier wind regions can last several days during winter. The duration of LLJs is sensitive to the LLJ definition criteria. We propose to use only the absolute criterion for model studies.

Spectra of wind, kinetic energy, and temperature are investigated for a dataset of 10 years of regional climate simulations for mid-Europe. The nonhydrostatic Consortium for Small-Scale Modeling (COSMO) model in Climate Mode [COSMO-CLM (CCLM)] climate model is used in a hindcast mode for 1991–2000. The three-step nesting chain starts with a CCLM run with 18-km resolution covering all of Europe nested in ERA-40 reanalyses and then a run with a resolution of 4.4 km is performed for mid-Europe. Finally, the 1.3-km run focuses on the region of mid-Germany and Luxembourg. In the present study, only results for the 4.4- and 1.3-km runs are shown. Different methods based on the Fourier and cosine transformations for the computation of the spectra are evaluated. The kinetic energy spectra show the expected slope in the mesoscale (up to the effective resolution), while the spectrum of the vertical wind shows a zero-slope behavior. The spectra of the horizontal wind components and temperature compare well to the observations. The effective model resolution was found to be about 7–10 (5–7) times the horizontal grid spacing for the one-dimensional (two-dimensional) spectral methods. A comparison between the different model resolutions shows a benefit of the 1.3-km simulations for the boundary layer for horizontal scales up to 25 km. The multiyear time-scale simulations allow for a climatological study of the seasonal cycle. The kinetic energy spectrum is found to have the largest values in summer.

Abstract. The non-hydrostatic regional climate model CCLM was used for a long-term hindcast run (2002–2016) for the Weddell Sea region with resolutions of 15 and 5 km and two different turbulence parametrizations. CCLM was nested in ERA-Interim data. We prescribed sea-ice concentration from satellite data, and used a thermodynamic sea-ice model. The performance of the model was evaluated in terms of temperature and wind using data from Antarctic stations, AWS over land and sea ice, operational forecast model and reanalyses data, and lidar wind profiles. For the reference run we found a warm bias for the near-surface temperature over the Antarctic plateau. This bias was removed in the second run by adjusting the turbulence parametrization, which results in a more realistic representation of the surface inversion over the plateau. Differences in other regions were small. A comparison with measurements over the sea ice of the Weddell Sea by three AWS buoys for one year showed small biases for temperature around 1 K and for wind speed of 1 m s−1. Comparisons of radio soundings showed a model bias around zero and a RMSE of 1–2 K for temperature and of 3–4 m s−1 for wind speed. The comparison of CCLM simulations at resolutions down to 1 km with wind data from Doppler Lidar measurements during December 2015 and January 2016 yielded almost no bias in wind speed and RMSE of ca. 2 m s−1. Overall CCLM shows a good representation of temperature and wind for the Weddell Sea region. These results encourage for further studies using CCLM data for the regional climate in the Antarctic at high resolutions and the study of atmosphere-ice-ocean interactions processes.