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Power generation from photovoltaic systems is highly variable due to its dependence on meteorological conditions. An efficient use of this fluctuating energy source requires reliable forecast information for management and operation strategies. Due to the strong increase of solar power generation the prediction of solar yields becomes more and more important. As a consequence, in the last years various research organisations and companies have developed different methods to forecast irradiance as a basis for respective power forecasts. For the end-users of these forecasts it is important that standardized methodology is used when presenting results on the accuracy of a prediction model in order to get a clear idea on the advantages of a specific approach. In this paper we introduce a benchmarking procedure to asses the accuracy of irradiance forecasts and compare different approaches of forecasting. The evaluation shows a strong dependence of the forecast accuracy on the climatic conditions. For Central European stations the relative rmse ranges from 40 % to 60 %, for Spanish stations relative rmse values are in the range of 20 % to 35 %. 24th European Photovoltaic Solar Energy Conference, 21-25 September 2009, Hamburg, Germany; 4199-4208

With the increase in energy of the Large Hadron Collider to a centre-of-mass energy of 13 TeV for Run 2, events with dense environments, such as in the cores of high-energy jets, became a focus for new physics searches as well as measurements of the Standard Model. These environments are characterized by charged-particle separations of the order of the tracking detectors sensor granularity. Basic track quantities are compared between 3.2 fb$^{-1}$ of data collected by the ATLAS experiment and simulation of proton-proton collisions producing high-transverse-momentum jets at a centre-of-mass energy of 13 TeV. The impact of charged-particle separations and multiplicities on the track reconstruction performance is discussed. The efficiency in the cores of jets with transverse momenta between 200 GeV and 1600 GeV is quantified using a novel, data-driven, method. The method uses the energy loss, dE/dx, to identify pixel clusters originating from two charged particles. Of the charged particles creating these clusters, the measured fraction that fail to be reconstructed is $0.061 \pm 0.006 \textrm{(stat.)} \pm 0.014 \textrm{(syst.)}$ and $0.093 \pm 0.017 \textrm{(stat.)}\pm 0.021 \textrm{(syst.)}$ for jet transverse momenta of 200-400 GeV and 1400-1600 GeV, respectively. The European physical journal / C 77(10), 673 (2017). doi:10.1140/epjc/s10052-017-5225-7 Published by Springer, Berlin

The study was conducted at the experimental field of the Department of Environmental Science, Bangladesh Agricultural University, Mymensingh (24' 27" N, 90,50" E, elevation 18 m) to determine the fundamental process and trend of radiation interception and biomass production by rainfed rice. Radiation interception varied in various stages of rice growth in relation with leaf area index (LAI) and light extinction coefficient (k). Higher radiation interception was observed at 276 days of the year (DOY) when LAI was 5.24 and k value was 0.35. Linear relationship was found between cumulative total dry matter and cumulative intercepted photosynthetically active radiation. The mean radiation use efficiency (RUE) was 2.54.

The battle against climate change is one of the key issues occupying the global agenda today. Adapting to and mitigating climate change are considered key in strategic plans to tackle climate change. In this context, adaptation refers to taking action to adjust and prepare for current and future impacts of climate change. Meanwhile, mitigation refers to preventing and reducing the emission of greenhouse gases. This dissertation posits that both terms complement each other as actions geared towards the improvement or deterioration of one strategy affect the other. Many adaptation strategies have been proposed and/or implemented as a means to cope with climate impact. These elements however ignore the component of rainwater as a crucial adaptation strategy which in this dissertation is known as the “Sponge city” concept. This study aims to analyse the effectiveness of Berlin's rainwater adaptation strategy in the face of the increasing threat of climate change. The methodological approach adopted is an analytical framework supported by data from public sources, government and private websites complemented with an interview from the Berlin government personnel Mr. Pearson. The results of this study depicts that Berlin's sponge city implementation is slow but can be improved taking into account the recommendations provided based on the limitations delaying Berlin’s transition. In the end, recommendations are offered on how Berlin could revamp its rainwater management strategies and knowledge shared in this dissertation can also be adapted to other cities. Treball guanyador del primer premi 2022. Premi Càtedra UNESCO de Cicle de Vida i Canvi Climàtic, ESCI-UPF i Barcelona School of Management - UPF, als millors treballs de fi de grau (TFG) sobre temes de Benestar Planetari. Bachelor's degree in Global Studies. Curs 2021-2022 Tutor: Antonio Luna Garcia

Introduction The Windbench portal has been developed together with the IEA-Wind Task 31 “Wakebench” Wind Energy Model Evaluation Protocol (WEMEP) to promote interdisciplinary research in the development of integrated design tools. Due to the high complexity of the multi-scale wind energy system, a building-block validation process is required to systematically test model adequacy based on fit-to-purpose metrics across a wide range of wind conditions. Value Proposition Windbench focuses primarily on model developer needs while also engaging with researchers involved in the design of experiments and generation of validation datasets. End-users from industry use Windbench to judge the adequacy of the models underlying their design tools. The value proposition for these users is: Validate your code together with your peers and share your data safely to contribute to a traceable international model evaluation framework for the development of trustful wind energy engineering tools. This is rolled out into the following features that lead the new design of Windbench: A community platform to map and document the development an international wind energy modeling and evaluation framework. A validation directed research program to establish high-level priorities for experimental analysis, model development and evaluation to meet the requirements of wind energy applications. A guide to adopt formal model evaluation procedures and data standards to improve the traceability and interoperability of the framework. A gateway to open-access resources for modeling, data analysis and validation. A forum to discuss industry challenges and scientific insights that help identify knowledge gaps. Solution Windbench will orchestrate general-purpose services around the SeaDataCloud virtual research environment (VRE), a data analytics platform that allows users to run benchmarking activities powered by the EUDAT Collaborative Data Infrastructure. Jupyter notebooks will be integrated in the WEMEP using sphinx-based documentation through Github repositories, published in Zenodo for version control. Benchmark data repositories will be shared and exploited through EUDAT data management services integrated with the SeaDataCloud to adopt policies and standards that promote data interoperability. Potential contributions to the WEMEP will be discussed online through The Wind Vane Blog, a publication hosted by Medium to promote the exchange of scientific insights and challenges between wind energy researchers and industry. Testing Plans Windbench is developed alongside the third phase of the IEA Wind Task 31 with support from the H2020-MARINET2 project (grant agreement number 73108). Over the next three years the integration of Windbench in the SeaDataCloud VRE will be enabled and tested with use cases from MARINET2 calls for access to e-infrastructures as well as other parallel projects under the umbrella of the IEA Wind. Solution testing with early adopters will focus on developing critical components that lead to adoption (communities engaged, benchmarks produced, users producing content, etc). This will ultimately depend on an actionable model evaluation protocol that promotes validation repositories that follow FAIR principles on data that are findable, accessible, interoperable and reusable. Summary We present a prototype for the new design of Windbench, a service to manage benchmarking activities for verification and validation of wind energy models. Windbench addresses model developers, experimentalists and end-users from industry through an actionable model evaluation protocol that promotes data sharing and trust. This will be powered by a virtual research environment built on the SeaDataCloud to provide data analytics around benchmark repositories managed in the EUDAT data management ecosystem. Key performance indicators will be based on quantifying user adoption as well as assessing the FAIRification of the data as outlined in the GO FAIR initiative.