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The 2016 Antarctic sea ice extent (SIE) drop was a rapid decrease that led to persistent low sea ice conditions. The event was triggered by atmospheric anomalies, but the potential preconditioning role of the ocean is unsettled. Here, we use sensitivity experiments with a fully-coupled regional climate model to elucidate the impact of the ocean conditions on the drop and on the persistence of the negative SIE anomalies during 2017. In particular, we re-initialize the model in January 2016 using different ocean and sea ice conditions, keeping lateral boundary forcings in the atmosphere and ocean unchanged. We find that the state of the Southern Ocean in early 2016 does not determine whether the drop occurs or not, but indeed has an impact on its amplitude and regional characteristics. Our results also indicate that the ocean initialization affects the sea ice recovery after the drop in the short term (one year), especially in the Weddell sector. The ocean’s influence appears not to be linked to the ocean surface and sea-ice initialization, but rather to the sub-surface conditions (between 50 m and 150 m) and heat exchange fluctuations at the regional scale, while the atmospheric forcing triggering the drop is driven by the large-scale circulation.

The CORDEX.be project created the foundations for Belgian climate services by producing high-resolution Belgian climate information that (a) incorporates the expertise of the different Belgian climate modeling groups and that (b) is consistent with the outcomes of the international CORDEX (“COordinated Regional Climate Downscaling Experiment”) project. The key practical tasks for the project were the coordination of activities among different Belgian climate groups, fostering the links to specific international initiatives and the creation of a stakeholder dialogue. Scientifically, the CORDEX.be project contributed to the EURO-CORDEX project, created a small ensemble of High-Resolution (H-Res) future projections over Belgium at convection-permitting resolutions and coupled these to seven Local Impact Models. Several impact studies have been carried out. The project also addressed some aspects of climate change uncertainties. The interactions and feedback from the stakeholder dialogue led to different practical applications at the Belgian national level. Keywords: Regional downscaling, Climate impact modeling, Statistical downscaling, Dynamical downscaling, Local Impact Models, Climate change, EURO-CORDEX, Uncertainty estimation, Regional Climate Model, Climate Belgium, Water vapour observations

Data of two years of observations (2007-2008) from the General Observation Period (GOP) are used to evaluate forecasts of the operational COSMO model applications (COSMO-DE and COSMO-EU) of the German Weather Service (DWD). As part of the German Priority Programme on Quantitative Precipitation Forecasting (PQP), the GOP gathered a comprehensive data set from existing instrumentation not used in routine verification and corresponding model output. In this paper we focus on the water cycle variables: integrated water vapor (IWV), cloud base height (CBH) and precipitation. In addition brightness temperatures (BT) from satellite observations are included. The biases in IWV and BT 6.2 μm data are small for COSMODE and COSMO-EU. CBH data show a larger bias with a maximum in the summer season. The largest biases have been found in the precipitation and BT 10.8 μm data. The latter can probably be explained by deficiencies in modelled clouds in the upper troposphere. A classification into different weather condition types gives some additional insight into model deficits. For northerly/north-westerly (maritime) flows model forecasts are too dry (cold) and for southerly (continental) flows too humid (warm).

The exact forecast of precipitation is a challenge. New microphysics formulations were introduced recently into the COSMO model in order to improve the precipitation forecast. An important modification was the change from the autoconversion and accretion scheme following the Kessler (1969) formulation to the Seifert and Beheng (2001) scheme. The other main modification was implemented in the snow parameterisation by replacing the constant intercept parameter to a temperature dependent intercept parameter. These microphysics modifications are evaluated in detail in three case studies (one stratiform and two convective cases) by comparing the modelled and observed reflectivity and precipitation data. Comparisons to weather radar reflectivity data show that especially light to moderate precipitation forecast (< 20 dB) is improved. For the evaluation of the modelled precipitation, weather radar and rain gauge data are combined in order to get spatially high resolution data of high accuracy. For the quality analysis, the new error measure SAL (analysis of structure, amplitude and location) is used. The results show that the new microphysics formulations improve the precipitation amplitude forecast of up to 50% for the convective cases while the forecast for the stratiform case is not improved.