ALBERT

Description: This paper analyses the temporal and spatial variability of droughts in Romania, over the last five decades, based on a high-resolution data set developed at country level, namely ROCADA. Droughts are analyzed by means of the Standardized Precipitation Index (SPI) for 3-, 6- and 12-month time scales. The time period 1979–1995 was identified as the period with the highest number of months affected by moderate, severe as well as extreme drought conditions. The 2000–2001 episode was identified as the major drought event, concerning the severity and the spatial extent, with an area of 60 % of the country affected by extreme drought for more than 10 consecutive months. The results of the trend analysis emphasize an inhomogeneous spatial aspect of the dryness/wetness trends. Statistically significant positive trends (wetter conditions) over small areas distributed inhomogeneous around the country like the southernmost corner as well as the northeastern part and some small areas in the western part of the country have been identified. Statistically significant negative (drier conditions) trends have been obtained over the southwestern part of the country and over the eastern part. In general, the SPI trends follow the observed trends in the monthly precipitation totals, at country level. The results indicate that there is no spatial consistency in the occurrence of droughts at country level and the SPI at different time scales may vary in its usefulness in drought monitoring, due to the fact that in the case of shorter time scales the SPI values have the tendency to fluctuate frequently above and below the zero line, while for longer time scales there are well-defined dry and wet cycles.

Description: The relationships between the dominant modes of interannual variability of Diurnal Temperature Range (DTR) over Europe and large-scale atmospheric circulation and sea surface temperature anomaly fields are investigated through statistical analysis of observed and reanalysis data. It is shown that the dominant DTR modes as well as their relationship with large-scale atmospheric circulation and sea surface temperature anomaly fields are specific for each season. During winter the first and second modes of interannual DTR variability are strongly related with the North Atlantic Oscillation and the Scandinavian pattern, while the third mode is related with the Atlantic Multidecadal Oscillation. Strong influence of the Atlantic Multidecadal Oscillation and the Arctic Oscillation on spring DTR modes of variability was also detected. During summer the DTR variability is influenced mostly by a blocking-like pattern over Europe, while the autumn DTR variability is associated with a wave-train like pattern, which develops over the Atlantic Ocean and extends up to Siberia. It is also found that the response of DTR to global sea surface temperature is much weaker in spring and summer comparing to winter and autumn. A correlation analysis reveals a strong relationship between DTR modes of variability and the Cloud Cover anomalies during all seasons. The influence of the potential evapotranspiration and precipitation anomalies on DTR modes of variability is strongest during summer, but it is significant also in spring and autumn. It is suggested that a large part of interannual to decadal DTR variability over Europe is induced by the large-scale climate anomaly patterns via modulation of cloud cover, precipitation and potential evapotranspiration anomaly fields.

Description: 〈jats:p〉Abstract. Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense. The method is described as applied to the discretization of the Finite volumE Sea ice – Ocean Model (FESOM2) on triangular meshes. It, however, is generalizable to colocated vertex-based discretization on triangular meshes and to both triangular and hexagonal C-grid discretizations. 〈/jats:p〉

Description: 〈jats:p〉Abstract. We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice–Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25–125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model. 〈/jats:p〉

Description: 〈jats:p〉Abstract. This study evaluates the impact of increasing resolution on Arctic Ocean simulations using five pairs of matched low- and high-resolution models within the OMIP-2 (Ocean Model Intercomparison Project phase 2) framework. The primary objective is to assess whether a higher resolution can mitigate typical biases in low-resolution models and improve the representation of key climate-relevant variables. We reveal that increasing the horizontal resolution contributes to a reduction in biases in mean temperature and salinity and improves the simulation of the Atlantic water layer and its decadal warming events. A higher resolution also leads to better agreement with observed surface mixed-layer depth, cold halocline base depth and Arctic gateway transports in the Fram and Davis straits. However, the simulation of the mean state and temporal changes in Arctic freshwater content does not show improvement with increased resolution. Not all models achieve improvements for all analyzed ocean variables when spatial resolution is increased so it is crucial to recognize that model numerics and parameterizations also play an important role in faithful simulations. Overall, a higher resolution shows promise in improving the simulation of key Arctic Ocean features and processes, but efforts in model development are required to achieve more accurate representations across all climate-relevant variables. 〈/jats:p〉