Climate services comprise of climate model or observational data that is provided by scientists or authorities to stakeholders who use them in decision-making processes. However, providers and users typically have diverging expectations regarding the data. We here describe various aspects of the gap between needs and offers that were identified in two workshops in the Main River catchment (central Germany). To bridge the gap, we propose a framework that can guide future stakeholder dialogues.

We looked into how a numerical experiment represents the interactions between the air and the sea at scales of about 100–1000 km. We found that slight changes in sea surface temperature (SST) drive dramatic modifications in evaporation rates from the sea surface. Cold sea patches tend to cool down the air and to keep moisture trapped within the lower atmospheric layers. Warmer SST, instead, makes them more buoyant and inflate with drier air, thus diluting moisture over thicker air layers.

Long-term series of precipitation data are important for e.g. the precise quantification of climate change.

Such time series should be consistent, but changes in the measurement conditions can't always be avoided. Parallel measurements are carried out at German climate reference stations in order to analyse the effects of changes in the measuring systems, e.g. when switching the device to another.

In this study, the influence of funnel heating on precipitation measurement  was analysed.

The question of how to best evaluate and communicate the value of weather warnings was addressed by a survey. This included questions with respect to the relevance of various aspects of a warning, the potential benefit of providing information on warning quality, the type of useful information and suitable ways of providing such information. Apart from the core information of warnings (time, place and severity) impact information and behavioural advice are seen to add value to a warning.

In this study, the quality of 10 and 100 m wind speeds from three different reanalyses (global and regional) are evaluated along the different coasts of France. The evaluation show that Copernicus Regional Reanalysis for Europe (CERRA) has a high skill for surface wind speed on the three French seafronts, as well as for offshore wind speed at 100 m. Thus, CERRA appears to be the optimal reanalysis to use as a reference for offshore wind studies over the French maritime zone.

To better predict offshore wind energy in Belgium, we improved the Royal Meteorological Institute (RMI) weather model by directly incorporating the effects of wind turbines. We also used AI to account for wind farm wake effects, where turbines slow down wind for other turbines. By combining physics-based models with a neural network trained on observations from the Belgian Offshore Zone, we achieved more accurate forecasts. This helps ensure a stable power grid and supports the growing role of offshore wind in our energy mix.