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This study presents estimates of the maximum temperature in Bangladesh for the 21st century for the pre-monsoon season (March–May), the hottest season in Bangladesh. The maximum temperature is important as indicator of the frequency and severity of heatwaves. Several emission scenarios were considered assuming different developments in the emission of greenhouse gases. Results show that there will likely be a heating of at least 1 to 2 degrees Celsius.

Correct estimates of wind speed between 60 and 200 m above ground are of great interest for the renewable energy sector. Observed wind speeds are compared to three different reanalyses. ERA5 and COSMO-REA6 outperform MERRA-2 at offshore, flat and hilly sites. Over land, ERA5 models nighttime wind speed better than COSMO-REA6 due to better representation of the low level jet through higher vertical resolution, a more comprehensive data assimilation scheme, and/or the more recent model version.

Each building has to withstand a certain mass of snow. In the Alps, snow load standards are coarse, and inconsistencies at national borders are common. A new methodology to derive a snow load map for Austria is presented. It consists of modeling and spatially interpolating snow loads with modern extreme value statistics. The new approach is much more accurate than the currently used Austrian snow load map and provides a reproducible base for other countries.

Wind speed forecasts have many potential users that could benefit from skilful forecasts. We validated weekly mean speed forecasts for Finland using forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). We concentrate on winter (November, December and January) forecasts. The forecasts proved to be skilful until the third week, but the longest skilful lead time depends on how the skill is calculated and what is used as the reference.

Convection-permitting models allow for prediction of rainfall events with increasing levels of detail. However, this increased resolution can create problems such as the so-called double penalty problem when attempting to verify model forecast accuracy. This problem is amplified when trying to maximise the value of a convection-permitting ensemble prediction system (EPS). Post-processing of the EPS can help to overcome these issues. In this spirit, two new up-scaling algorithms based on Machine

10-year long sensitivity study on domain size was perform with REMO regional climate model. We can conclude, that the selection of domain size has larger impact on the simulation of precipitation, and in case of the seasonal mean of the precipitation indices, the differences amongst the results obtained on each model domain exceed 10%. In general, the smallest biases were obtained on the largest domain, therefore further long term simulations are being achieved on this.

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.

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.

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.

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".