High-Resolution COSMO-CLM Modeling and an Assessment of Mesoscale Features Caused by Coastal Parameters at Near-Shore Arctic Zones (Kara Sea)

Characterization of the skill of the CORDEX-Africa regional climate models to simulate regional climate setting in the East African Transboundary Omo Gibe River Basin, Ethiopia

Regional climate models (RCMs) that produce good outputs in one region or for specific variables may underperform for others. Thereby, assessing the performance of various model simulations and their corresponding mean ensemble is critical in identifying the most suitable models. In this regard, a study was conducted to evaluate the performance of ten RCMs against observations from multiple ground-based stations in the East African Transboundary Omo Gibe River Basin, Ethiopia, during the baseline period of 1986-2005. The study evaluated the models' ability to replicate various aspects of climatic variables and their corresponding statistical indicators. The results confirmed that RCMs have varying abilities to reproduce climatic conditions across the basin. The ensembles and RACMO22T (EC-EARTH) were better at replicating the average annual precipitation distribution. Meanwhile, the CCLM4-8-17 (MPI) together with the ensembles better captured the measured precipitation annually, despite the discrepancies in the actual magnitudes. All RCMs were able to simulate the seasonal precipitation patterns effectively, with RACMO22T (EC-EARTH), CCLM4-8-17 (CNRM), RCA4 (CNRM), CCLM4-8-17 (MPI), and REMO2009 (MPI) models captured superior, excluding the maximum value. Interannual and seasonal rainfall pattern variations were more significant than variations in air temperature. Additionally, a better correlation was observed between actual and simulated precipitation at multiple separate monitoring places. The RCA4 (MPI) and CCLM4-8-17 (MPI) demonstrated reasonable minimum and maximum temperatures. The RCA4 (MIROC5) model was more effective in reproducing extreme precipitation events. However, all RCMs and their ensembles tended to overestimate the return periods of these events. In general, the research highlights the importance of selecting reliable RCMs that better replicate observed climatic settings and employing the ensemble mean of top-performing models following systematic bias adjustment for a specific application.

A Three-Year Climatology of the Wind Field Structure at Cape Baranova (Severnaya Zemlya, Siberia) from SODAR Observations and High-Resolution Regional Climate Model Simulations during YOPP

Measurements of the atmospheric boundary layer (ABL) structure were performed for three years (October 2017–August 2020) at the Russian observatory “Ice Base Cape Baranova” (79.280° N, 101.620° E) using SODAR (Sound Detection And Ranging). These measurements were part of the YOPP (Year of Polar Prediction) project “Boundary layer measurements in the high Arctic” (CATS_BL) within the scope of a joint German–Russian project. In addition to SODAR-derived vertical profiles of wind speed and direction, a suite of complementary measurements at the observatory was available. ABL measurements were used for verification of the regional climate model COSMO-CLM (CCLM) with a 5 km resolution for 2017–2020. The CCLM was run with nesting in ERA5 data in a forecast mode for the measurement period. SODAR measurements were mostly limited to wind speeds <12 m/s since the signal was often lost for higher winds. The SODAR data showed a topographical channeling effect for the wind field in the lowest 100 m and some low-level jets (LLJs). The verification of the CCLM with near-surface data of the observatory showed good agreement for the wind and a negative bias for the 2 m temperature. The comparison with SODAR data showed a positive bias for the wind speed of about 1 m/s below 100 m, which increased to 1.5 m/s for higher levels. In contrast to the SODAR data, the CCLM data showed the frequent presence of LLJs associated with the topographic channeling in Shokalsky Strait. Although SODAR wind profiles are limited in range and have a lot of gaps, they represent a valuable data set for model verification. However, a full picture of the ABL structure and the climatology of channeling events could be obtained only with the model data. The climatological evaluation showed that the wind field at Cape Baranova was not only influenced by direct topographic channeling under conditions of southerly winds through the Shokalsky Strait but also by channeling through a mountain gap for westerly winds. LLJs were detected in 37% of all profiles and most LLJs were associated with channeling, particularly LLJs with a jet speed ≥ 15 m/s (which were 29% of all LLJs). The analysis of the simulated 10 m wind field showed that the 99%-tile of the wind speed reached 18 m/s and clearly showed a dipole structure of channeled wind at both exits of Shokalsky Strait. The climatology of channeling events showed that this dipole structure was caused by the frequent occurrence of channeling at both exits. Channeling events lasting at least 12 h occurred on about 62 days per year at both exits of Shokalsky Strait.

Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.