Evaluating solar radiation forecast uncertainty

The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar energy and UV radiation forecasts. Here we investigate how operational forecasts of low and mid-level clouds affect the accuracy of solar radiation forecasts. A total of 4 years of cloud and solar radiation observations from one site in Helsinki, Finland, are analysed. Cloud observations are obtained from a ceilometer and therefore we first develop algorithms to reliably detect cloud base, precipitation, and fog. These new algorithms are widely applicable for both operational use and research, such as in-cloud icing detection for the wind energy industry and for aviation. The cloud and radiation observations are compared to forecasts from the Integrated Forecast System (IFS) run operationally and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop methods to evaluate the skill of the cloud and radiation forecasts. These methods can potentially be extended to hundreds of sites globally. Over Helsinki, the measured global horizontal irradiance (GHI) is strongly influenced by its northerly location and the annual variation in cloudiness. Solar radiation forecast error is therefore larger in summer than in winter, but the relative error in the solar radiation forecast is more or less constant throughout the year. The mean overall bias in the GHI forecast is positive (8 W m(-2)). The observed and forecast distributions in cloud cover, at the spatial scales we are considering, are strongly skewed towards clear-sky and overcast situations. Cloud cover forecasts show more skill in winter when the cloud cover is predominantly overcast; in summer there are more clear-sky and broken cloud situations. A negative bias was found in forecast GHI for correctly forecast clear-sky cases and a positive bias in correctly forecast overcast cases. Temporal averaging improved the cloud cover forecast and hence decreased the solar radiation forecast error. The positive bias seen in overcast situations occurs when the model cloud has low values of liquid water path (LWP). We attribute this bias to the model having LWP values that are too low or the model optical properties for clouds with low LWP being incorrect.Peer reviewe

Intermolecular oxidative dehydrogenative 3,3 '-coupling of benzo[b]furans and benzo[b]thiophenes promoted by DDQ/H+ : total synthesis of shandougenine B

With an excess of a strong acid, 2,3-dichloro-5,6-dicyano-1,4-quinone (DDQ) is shown to promote metal-free intermolecular oxidative dehydrogenative (ODH) 3,3'-coupling of 2-aryl-benzo[b]furans and 2-aryl-benzo[b]thiophenes up to 92% yield as demonstrated with 9 substrates. Based on the analysis of oxidation potentials and molecular orbitals combined with EPR, NMR and UV-Vis observations, the studied reaction is initiated by a DDQ-substrate charge transfer complex and presumably proceeds via oxidation of the substrate into an electrophilic radical cation that further reacts with another molecule of a neutral substrate. The coupling reactivity can easily be predicted from the oxidation potential of the substrate and the morphology of its frontier molecular orbitals. The intermolecular ODH coupling reaction allowed a concise total synthesis of the natural product shandougenine B.Peer reviewe

Development and experimental validation of a real-time analytical model for different intelligent tyre concepts

In recent years, the ever-increasing interest in intelligent tyre technology has led to the formulation of different empirical models correlating deformation measurements provided by the sensors with tyre dynamics. In this paper, a real-time physical model, suitable for describing the dynamics of intelligent tyres based on measurements of strains and/or displacements of the tyre carcass, is presented. The proposed flexible ring model can reproduce the tyre dynamics for both concentrated and distributed forces by introducing a discrete approach that also allows to analyse the longitudinal dynamics of the tyre in real-time. The analytical description of the problem allows to obtain solutions in closed form and to quickly identify model parameters from experimental data. The comparison between the simulated results and the ones provided by indoor tests of two intelligent tyre concepts highlighted that the proposed tyre model can estimate with an acceptable precision both the carcass deformations and the forces acting on the tyre

Low-Level Jets over Utö, Finland, Based on Doppler Lidar Observations

Over two years of meteorological observations from Utö, a small island in the Finnish outer archipelago in the Baltic Sea, were used to investigate the occurrence and characteristics of low-level jets (LLJs) and the diurnal and seasonal variations in these properties. An objective LLJ identification algorithm that is suitable for high-temporal-and-vertical-resolution Doppler lidar data was created and applied to wind profiles obtained from a combination of Doppler lidar data and two-dimensional sonic anemometer observations. This algorithm was designed to identify coherent LLJ structures and requires that they persist for at least 1 h. The long-term mean LLJ frequency of occurrence at Utö was 12%, the mean LLJ wind speed was 11.6 m s−1, and the vast majority of identified LLJs occurred below 150 m above ground level. The LLJ frequency of occurrence was much higher during summer (21%) and spring (18%) than in autumn (8%) and winter (3%). During winter and spring, the LLJ frequency of occurrence is evenly distributed throughout the day. In contrast, the LLJ frequency of occurrence peaks at night (1900–0100 UTC) during summer and during the evening hours (1700–1900 UTC) in autumn. The highest and strongest LLJs come from the southwest, which is also the predominant LLJ direction in all seasons. LLJs below 100 m are common in spring and summer, are weaker, and do not show a strong directional dependence.Peer reviewe

Mono- and bis-imidazolidinium ethynyl cations and the reduction of the latter to give an extended bis-1,4-([3]cumulene)-p-carbo-quinoid system

Sherpa Romeo yellow journal. This is the peer reviewed version. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived VersionsAn extended π-system containing two [3]cumulene fragments separated by a p-carbo-quinoid and stabilized by two capping N-heterocyclic carbenes (NHCs) has been prepared. Mono- and bis-imidazolidinium ethynyl cations have also been synthesized from the reaction of an NHC with phenylethynyl bromide or 1,4bis(bromoethynyl)benzene. Cyclic voltammetry coupled with synthetic and structural studies showed that the dication is readily reduced to a neutral, singlet bis-1,4-([3]cumulene)-p-carbo-quinoid due to the πaccepting properties of the capping NHCsYe

Opportunities and Challenges in Using Learning Analytics in Learning Design

Educational institutions are designing, creating and evaluating courses to optimize learning outcomes for highly diverse student populations. Yet, most of the delivery is still monitored retrospectively with summative evaluation forms. Therefore, improvements to the course design are only implemented at the very end of a course, thus missing to benefit the current cohort. Teachers find it difficult to interpret and plan interventions just-in-time. In this context, Learning Analytics (LA) data streams gathered from ‘authentic’ student learning activities, may provide new opportunities to receive valuable information on the students' learning behaviors and could be utilised to adjust the learning design already "on the fly" during runtime. We presume that Learning Analytics applied within Learning Design (LD) and presented in a learning dashboard provide opportunities that can lead to more personalized learning experiences, if implemented thoughtfully. In this paper, we describe opportunities and challenges for using LA in LD. We identify three key opportunities for using LA in LD: (O1) using on demand indicators for evidence based decisions on learning design; (O2) intervening during the run-time of a course; and, (O3) increasing student learning outcomes and satisfaction. In order to benefit from these opportunities, several challenges have to be overcome. We mapped the identified opportunities and challenges in a conceptual model that considers the interaction of LA in LD.SURF Foundation & NRO under the REFLECTOR project grant