Determination of heat requirements in the first developing phases of plants has been expressed as Growing Degree Days (GDD) and is useful in order to understand the flowering season development in plant species, and forecast when flowering will occur. The study dealt with the estimation of GDD in Crete Island in Greece. Results indicated that in the future, GDD will be increased and the existing cultivations can reach maturity sooner. Neverthelless, rough topography will act as an inhibitor.

The solar hourly irradiation received at ground level estimated by the databases HelioClim-3v4, HelioClim-3v5 and Copernicus Atmosphere Monitoring Service (CAMS) Radiation Service are compared to measurements made in stations in Oman and Abu Dhabi. The correlation coefficients are greater than 0.97. The relative bias is less than 5%. Each database captures accurately the temporal and spatial variability of the irradiance field. The three databases are reliable sources to assess solar radiation.

Large scale atmospheric oscillations, such as the North Atlantic Oscillation are known to have an influence on waves in the North Atlantic. This study investigated the influence of the NAO on the present and future wind and wave climate in the Northeast Atlantic near Ireland.

This study investigates the characteristic time-scales of variability found in long-term time-series of daily means of surface solar irradiance (SSI). Estimates of SSI from satellite-derived HelioClim-3 and radiation products from ERA-Interim and MERRA-2 re-analyses are compared to WRDC measurements. It is found that HelioClim-3 renders a more accurate picture of the variability found in ground measurements, not only globally, but also with respect to individual characteristic time-scales.

This paper is a summary of a very high resolution climate reanalysis carried out for a domain covering Ireland, using the HARMONIE-AROME numerical weather prediction model. Details of the simulations and set-up as well as a preliminary analysis of the main output variables are included in the study.

Twitter has proved to be an important source of information during emergencies. In Twitter hashtags are used by users to improve information retrieval and coordinate conversations. A set of 20 hashtags to be used during weather warnings was proposed in Italy in 2014. This study presents a one-year monitoring of the Italian codified hashtags. Different regional contexts are presented and main findings are discussed. Institutions have a crucial role in the stable adoption of a codified hashtag.

Monthly frequencies of circulation types (derived by clustering fields of SLP, vertical wind and rel. humidity at 700 hPa and regional rainfall series) are used as predictors in regression models for monthly frequencies of regional precipitation extremes (> 95 % percentile). With predictor output from global climate models, changes in regional precipitation extremes for 2021–2050 and 2071–2100 are assessed, most distinctive in summer: increasing/decreasing extremes for the earlier/later period.

This study presents the sensitivity of an oceanic model of the Adriatic Sea to the horizontal resolution and to the meteorological forcing. The model is run with two different configurations and with two horizontal grids at 1 and 2 km resolution. To study the influence of the meteorological forcing, the two storms have been reproduced by running ROMS in ensemble mode. Possible optimizations of the model set-up are deduced by the comparison of the different run outputs.

The probabilistic evaluation of 2 m temperature forecast of about one year of monthly ensemble forecasts, issued on a monthly basis, is provided. The ranked probability skill score, averaged over all the available cases, shows that the system has a residual predictive skill beyond week 2 on some peculiar regions. Reliability diagrams show that, in general, the probability forecasts of above-normal observed temperature are more reliable than below-normal temperature.

Finnish Meteorological Institute and Helen Ltd examined the feasibility of long-range forecasts (longer than two weeks) of temperature for needs of the energy sector in Helsinki, Finland. In this study, we examined the quality of Heating degree day (HDD) forecasts. As the forecasts we used UK Met Office seasonal forecasts. The long-range forecasts of monthly HDD showed some skill in Helsinki in winter 2015–2016, up to two months, especially if the very cold January is excluded.

Exact description of cloud microphysical processes is essential for providing accurate weather forecasts. The paper evaluates errors of different methods to account for variability of cloud microphysical parameters, such as cloud water. rain water, and cloud drop concentration. It is found that neglecting cloud variability results in a substantial underestimate of rain development in the short run. Nevertheless the total effect on rain development in the long run may be uncertain due to the fac

This paper presents the educational activities on meteorology carried out by LaMMA Consortium, official weather service for Tuscany. Since 2011 every year more than 1200 students come to visit LaMMA to follow one of the proposed modules. Students have also the opportunity to visit the LaMMA weather operations room and meet the forecasters. Furthermore, an educational module on climate change based on a participatory approach was proposed to more than 500 teachers in the last two years.

Was the July 2015 heat wave that struck Western Europe predictable more than 10 days ahead and to what extent? This article addresses the question by assessing forecasts from the CNRM-CM sub-seasonal forecast system. It is found that a warm anomaly was anticipated up to one month ahead despite the limited skill of the forecast system at such lead-time. The possible causes for this relative success are then discussed.

The ensemble reforecasts of the CNR-ISAC and ECMWF forecasting systems, both participating to the S2S project, have been combined in a multimodel ensemble. Tercile probability predictions of wintertime 2 m temperature produced through logistic regression outperform the probability estimation based on the direct count of ensemble members, in terms of RPSS and reliability diagrams. Also, it is argued that the logistic regression would not yield further improvements if a larger dataset were used.

The paper investigates, for 28 years, the correlation between the longwave radiation to the surface (SDL) and the sea ice concentration (SIC) over the Arctic Ocean. One relevant result is the strong correlations of the SDL/SIC co-variability with some main NH climate oscillations patterns. This study can help to better understand the relationship between atmospheric and cryospheric variables. The paper is based on an intensive use of some climate data sets provided by EUMETSAT and NSIDC.

In this article the comparability of knowledge transfer activities is discussed by accounting for external impacts. It is shown that factors which are neither part of the knowledge transfer activity nor part of the participating institution may have significant impact on the potential usefulness of knowledge transfer activities. The results show that the comparability of knowledge transfer activities is limited and challenge the adequacy of quantitative measures in this context.

The representation of the atmospheric moisture distribution in weather and climate prediction models has been identified as a source of error in the representation of heavy precipitation events. This research work shows the relevance of overcoming deficiencies in the representation of the moisture content in the vertical direction, even after assimilating humidity data for a case study characteristic of the western Mediterranean by early autumn.

As one element of the SASSCAL initiative (a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany) networks of automatic weather stations have been installed or improved in Southern Africa. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. The best interpolation results have been achieved combining multiple linear regression with three dimensional inverse distance weighted interpolation.

This paper reflects on the challenges of using seasonal climate forecasts (SCF) in the farming sector in a region in the UK. The findings from the study point to the need to explore and develop (new) research methods capable of addressing the complexity of the decision-making processes, such as those identified in the farming sector and beyond. This paper contributes to ongoing discussions about how to assess the value of climate information, such as SCF, in decision-making in a meaningful way.

The article describes ability of the numerical atmospheric model WRF-Chem to predict concentrations of main gas pollutants over Europe. Model experiments showed that daily and annual cycles of ozone are well captured, but the model concentrations of nitride dioxide and sulfur dioxide are significantly lower than measured values. The differences between two chemical modules are significant in term of ozone daily cycle, not in the total amount of nitride and sulfur dioxide.

This study investigates the impact of using lightning data on the precipitation forecast at different forecast ranges (3–24 h). Twenty case studies, occurred over Italy in fall 2012, are selected to show the impact. Results show the important and positive impact of using lightning data to improve the precipitation forecast. The time range, however, is very important because the performance decreases steadily and substantially with forecasting time.

This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the NWP model, without compromising on computational efficiency. Fast physically based radiation parametrizations are also valuable for high-resolution ensemble forecasting.

This work presents an analysis of tweets related to heat waves occurred in Italy in summer 2015. Social media offer new opportunities to indirectly measure the impact of heat waves on society. Tweets related to heat conditions were retrieved and analysed for main features. The daily volume of users and messages was a valuable indicator of heat wave impact in urban areas. The volume of tweets in certain locations was used to estimate thresholds of local discomfort conditions.

The fused product of wind speed for the wind farm is designed through using wind speed products of ensemble prediction from European Centre for Medium-Range Weather Forecasts and professional numerical model products on wind power based on Mesoscale Model5 and Beijing Rapid Update Cycle, which is suitable for short-term wind power forecasting and electric dispatch. The result shows that the fusion forecast has made obvious improvement on the accuracy relative to the numerical forecasting.

A new national daily snowfall record was measured in Finland in January 2016 when it snowed 73 cm in less than a day at a small town on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and found that a weather prediction model worked quite well in simulating the snowbands.

To facilitate progress in adaptation policy and practice, it is important not only to ensure the production of accurate, comprehensive and relevant information, but also the easy, timely and affordable access to it. Web-based platforms can play an important role in the relevant efforts, providing a cost-effective and efficient way to reach out to a wide audience. Despite the progress that has been achieved in this area in recent years, certain challenges remain and need to be further explored.

Global Eta Framework (GEF) is run on a cubed-sphere grid topology. A nonhydrostatic version of this atmospheric model is under development at CPTEC, SP, Brazil. This note describes preliminary tests with the GEF in which model performance is evaluated in seasonal simulations at a horizontal resolution of 25 km, running in the hydrostatic mode. Comparison of these simulations with the ERA-Interim reanalyses shows the model is able to well capture the main seasonal climate characteristics.

There is still a large gap between climate research results and their use in climate impact research and policy advisory. One of the many approaches taken to reduce this gap was a midterm user workshop of the German project ReKliEs-De. The users were asked to guide the further project work towards their needs. Conclusions from the workshop included the need for more plain text guidance on climate model strengths and weaknesses as well as more research on climate impact system functioning.

This work aims to provide a comparison between three dimensional and four dimensional variational data assimilation methods (3D-Var and 4D-Var) for a heavy rainfall case in central Italy. Nine simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators. The assimilation of conventional observations with 4D-Var method improves the quantitative precipitation forecast (QPF) compared to 3D-Var.

In this study, categories, dimensions and criteria for evaluating regional climate services are derived by a participatory approach with potential service users at the German Baltic Sea coast. The results show that stakeholders do mainly address other components than those found in the literature. This might indicate that an evaluation, following solely literature-based (non-participative) components, is not sufficient to localize deficiencies or efficiencies within a regional climate service.

Weather, climate and climate change can cause significant risks to businesses and public administration. By asking Finnish organizations about their weather and climate risk perceptions and management, this study aims to improve ways climate services can support in adapting to current and future climate. The results indicate that climate risk management is often de-centralized and relies on expert networks but that practices differ between actors.

Climate services and other fields, that are used to integrate the users in research activities (co-creation), are pledging for existing evaluation methods to be widened up. The authors harmonize the different elements of evaluation in an evaluation cascade, scaling down from very general evaluation dimensions to tangible assessment methods and suggest how to proceed in developing evaluation criteria and indicators. Two examples demonstrate how co-creation of knowledge could be assessed.

Knowledge transfer and dialogue processes (KT) in the field of climate science have captured intensive attention. This paper aims to serve as an input to stimulate further reflection on the field of evaluation of KT in the context of climate sciences. We carry out an analysis of three example activities and derive a set of indicators for measuring the output/outcome by balancing the wide diversity and range of activity contents as well as the different tools to realize them.

The HARMONIE weather forecasting model is used successfully in Greenland, but there are some problems over the ice sheet due to the lack of realistic glacier surface characteristics. By introducing a correction to the model, preventing glacier surface temperatures over 0 °C, we improve both 2 m air temperature and the surface winds (both strength and direction) forecast by the model. We also identify other corrections needed before HARMONIE can be used for climate and ice sheet modelling.

Accessibility, availability, re-use and re-distribution of scientific data are prerequisites to build climate services across Europe. The proposed architecture uses open-source tools and interoperable standards to ensure sustainability in the development and deployment of Web applications. The availability of structured raw data as customized information paves the way for building climate service purveyors to support adaptation, mitigation and risk management at different scales.