At MET Norway, a small interdisciplinary team – the Sandbox – tries to improve the communication between the meteorologists and their audience. In 2021, we focused on the communication of forecast uncertainty. The Sandbox created, with input from internal and external experts, solutions for applying linguistic and visual tools for forecasters to communicate about uncertainty. In the article, we share our experiences and lessons learned.

Weather forecast refers to objective estimations of parameters such as temperature, wind, humidity etc. However, attempts have been made to communicate the weather forecast into a more subjective approach, such as the "feels like" temperature. We propose an architecture for an artificial intelligence-based system to provide a forecast that could be more meaningful and actionable for each individual person; a forecast much closer to the way that this person "lives" the weather conditions.

This work used machine learning to produce the first open source building height map of Ireland. This map is intended to more accurately determine Local Climate Zones for use in the underlying physiography dataset in the HARMONIE AROME numerical weather prediction model.

High resolution, probabilistic weather prediction systems are increasingly able to model lightning activity with unprecedented accuracy. Is the probabilistic approach skillful when applied to localized, deep convection? This work shows that the ensemble prediction system maintained by the German Weather Service is able to provide a useful forecast of lightning activity at a scale of around 200 km and that the probabilistic approach can anticipate possible lack of accuracy in both time and space.

Wildfire origins can be related to human activity or to natural phenomena, like lightning. Under favourable environmental conditions, lightning ignitions can develop into a fire. In the present study, we analyse the kind of weather that favours wildfires ignited by lightning in Catalonia. We have found that most fires occur under three types of weather. These results help to improve our understanding of lightning fires and are of great assistance to wildfire management agencies.

The main aspect of the paper is to obtain transferable principles for the development of digital knowledge transfer products. As such products are still unstandardised, the authors explored challenges and approaches for product developments. The authors report what they see as useful principles for developing digital knowledge transfer products, by describing the experience of developing the Net-Zero-2050 Web-Atlas and the "Bodenkohlenstoff-App".

Climate normals are used as reference for climate monitoring. When calculating precipitation normals for the period 1991–2020 a homogeneous reference dataset is needed. Norway's observation network has changed drastically in the last 30 years and may have introduced non-climatic changes to the time series. Homogeneity analysis of monthly precipitation series for the period 1961–2018 was performed which produced a homogenous dataset that was used to calculate the new climate normals in Norway.