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In this work, machine learning techniques, satellite data and land-cover data were used to produce a land-cover map for Ireland that shows greater accuracy and resolution than an altered version of the standard land-cover map (ECOCLIMAP-SG) used for numerical weather prediction. This method offers a way to universally improve meteorological land-cover maps across jurisdictions, while also offering a method of updating the map regularly to account for seasonal changes in surface land-covers.

Persistent warm urban temperature anomalies – urban heat islands – significantly enhance already amplified climate warming in the Arctic. This study presents the surface urban heat islands in all circum-Arctic settlements with more than 3000 inhabitants. It reveals strong and persistent urban temperature anomalies during both summer and winter seasons that vary in different cities from 0.5 °C to more than 6.0 °C.

We have developed a tool to visualize rainfall observations, based on a combination of meteorological stations and weather radars, over Sweden in near real-time. By accumulating the rainfall in time (1–12 h) and space (hydrological basins), the tool is designed mainly for hydrological applications, e.g. to support flood forecasters and to facilitate post-event analyses. Despite evident uncertainties, different users have confirmed an added value of the tool in case studies.

Based on the LES model data, a very strong correlation was found not only between the condensation, but also evaporation rate and upward mass flux. While good correlation between the upward mass flux and condensation is not surprising, the very high correlation coefficient (R = 0.99), as well as the role of the upward mass flux in determining the evaporation rate, is remarkable and may be important for future latent heat parameterization development.

The Pūre orchard is one of the biggest and oldest apple orchards in the Baltic. We have digitized the full flowering phenological data of apple trees over the period of 1959 to 2019. Described changes in full-flowering time: apple trees all 17 varieties have begun to flower earlier. We tested three sets of meteorological data in phenological model to develop better-quality phenological predictions. As ongoing and predicted climate change has had and will have a significant impact on agriculture

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.