The power output of solar photovoltaic (PV) modules depends largely upon incident solar radiation as well as PV module temperature. Although irradiance can fluctuate rapidly under broken cloud conditions, module temperature is subject to latency due to the solar panel's heat capacity. In order to reconcile this difference a simple four-parameter model is successfully employed to describe the dynamics of PV module temperature as a function of atmospheric conditions.

We present the open source project Titan for automatic quality control of meteorological in-situ observations. The quality control strategy adopted is a sequence of tests, where several of them utilize the expected spatial consistency between nearby observations. Titan serves real-time operational applications that process massive amounts of observations measured by networks of automatic weather stations. Further developments include transforming Titan into a more flexible library of functions.

The present work deals with the spatial consistency of two well-known databases of solar radiation received at ground level: the CAMS Radiation Service database version 3.2, abbreviated as CAMS-Rad and the HelioClim-3 database version 5, abbreviated as HC3v5. Both databases are derived from satellite images. For both databases, there is no noticeable spatial trend in the standard deviation.

A common framework for early action to cope with complex disasters can make it easier for authorities and populations at risk, to understand the full spectrum of impacts and thus where to focus preparedness efforts, and how best to provide more targeted warnings and early actions. There are useful lessons from Multi-Hazard Impact-based Early Warning Systems for the COVID-19 pandemic, and some valuable insight to be gained in risk communication, analysis and monitoring methodologies.

Reanalyses are long-term meteorological datasets that are based on numerical weather prediction models and the assimilation of historic observations. The regional model COSMO of Germany’s national meteorological service (Deutscher Wetterdienst) has been used to develop regional reanalyses with spatial resolution of up to 2 km. In this paper, we provide an overview of evaluation results and application examples at the European and national German level with a focus on renewable energy.

In this study we look for a new knowledge of the costal boundary layer processes through analysis of extreme phenomena which include the verification of numerical modeling data outputs from the WRF mesometological model for selected period with high availability of extreme wind profiles by acoustic sounding of the atmosphere. The work is within the frame of research projects REPLICA (extReme Events and wind ProfiLe In a Coastal Area) – DM 14/1 26 May 2020.

In the case of coastal wind farms, the wind that produces power simultaneously contributes to the cooling of high-voltage overhead conductors. Ideally this would allow for increased power transmission or decreased dimensions and cost of the conductor wires. In this study we investigate how well the wind speed in coastal wind farms is correlated with wind along a 75 km long 330 kW power line towards inland.

Statistics of the frequency and intensity of snow bands affecting the Finnish coast during years 2000–2010 was conducted. A set of criteria for meteorological variables favoring the formation of the snow bands were applied to regional climate model (RCA4) data. We found on average three days per year with favorable conditions for coastal sea-effect snowfall. The heaviest convective snowfall events were detected most frequently over the southern coastline.

High-resolution precipitation observation based on signal attenuation in a Commercial Microwave Link (CML) network is an emerging technique that is becoming more and more used. Here a pragmatic method for estimating the optimal resolution is presented. The method is demonstrated using a CML network and a representative precpitation pattern in Stockholm, Sweden. One application would be feasibility investigations in cities considering starting CML-based precipitation observations.

Wind speeds at turbine hub heights are scarcely measured and often replaced by numerical datasets when simulating wind power time series for various impact studies. Can we trust these modelled wind speeds? This work investigates five wind-speed datasets, comparing them to actual wind-speed and wind-power observations in France. They show various skills in terms of bias and hourly variability, leading to more or less realistic wind-power simulations at the local scale.

Recently an objective method was suggested to translate realistic vegetation characteristics into spatially varying values of effective roughness. This parameter allows prediction of wind flow over vegetation using models, without incorporating local drag forces in each grid volume of a three-dimensional model domain. Results of the flow simulations over different forested sites show that an approach based on a roughness representation of forest is appropriate only for the flat terrain.

This paper describes the approach and the process used for the development of TOPaCS, a contribution of RTC Italy to the WMO Global Campus initiative for ongoing continuous professional development in Meteorological and Climate Services. TOPaCS is open access and created under a Creative Commons licence, facilitating knowledge sharing and dissemination. TOPaCS is now available to the community of Climate Services through the platform www.climateservices.it.

Ensemble forecasting has gained popularity as a means of handling the limitations inherent to predicting the behavior of high dimensional systems with strong sensitivity to initial conditions. Initial conditions are sampled and propagated through the model equations, leading to a set of predictions. So far, this set has been interpreted in a probabilistic way. Here, we question this choice and show that possibility theory may be a sounder approach, especially in the case of extreme events.

European NMHSs are progressing towards impact-oriented and impact-based warnings. This publication gives an overview of warning implementation as surveyed at 32 of the 37 NMHSs participating in the EUMETNET Meteoalarm project. Topics adressed include warning format, legislation and production process of warnings, dissemination and verification of warnings, impact databases, warning strategy and cooperation and cross-border collaboration. Obstacles are identified and trends are discussed.

The monthly mean soil moisture forecasts for forestry are been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts help in timber harvesting planning, and forecasts could large economic value. Therefore the skillfulness of forecasts was measured. Throughout the year the first month was skillful, and after that it can be hard to say if the forecasts are better than the normal conditions. Winter forecasts are a bit better than summer forecasts.