scholarly journals Performance analysis of 300 GHz backhaul links using historic weather data

2021 ◽  
Vol 19 ◽  
pp. 153-163
Author(s):  
Bo Kum Jung ◽  
Thomas Kürner
Keyword(s):  
Weather Conditions ◽  
Weather Data ◽  
Climate Data ◽  
Propagation Models ◽  
Horizon 2020 ◽  
Ieee Standard ◽  
Backhaul Links ◽  
Outage Probabilities ◽  
Ray Tracing Simulation ◽  
The Eu

Abstract. According to the recently published IEEE standard 802.15.3d (2017), THz links operating at 300 GHz are viable to achieve more than 100 Gbit s−1 of data rate. This feature can support a transition of the future backhaul connectivity from the underground fibre connection to the wireless, where fibre links are not available or too costly to install. The EU-Japan Horizon 2020 project “ThoR” is working towards the demonstration of such links. A detailed investigation on the influence of weather conditions will help to derive planning guidelines of 300 GHz backhaul links for forthcoming applications. This paper focuses on the dependency of the THz link on the general weather by using ray-tracing simulation. Simulation is conducted combining ITU-R propagation models for atmospheric attenuation (water vapour and oxygen content of air, droplets of rains, liquid content of clouds or fog), a wind-depending swaying model for the antenna poles, and historical measured climate data for the deployment scenarios considered in the ThoR project. As a result, this research will show the feasibility of THz link in outdoor applications under general weather conditions, defines weather-dependent outage probabilities, and allows us to derive planning guidelines of THz links at a frequency of 300 GHz.

Polytope: Serving ECMWFs Big Weather Data

2020 ◽  
Author(s):  
James Hawkes ◽  
Nicolau Manubens ◽  
Emanuele Danovaro ◽  
John Hanley ◽  
Stephan Siemen ◽  
...  
Keyword(s):  
Spatial Data ◽  
High Performance ◽  
Large Scale ◽  
Data Extraction ◽  
Weather Data ◽  
Primary Data ◽  
Climate Data ◽  
Raw Data ◽  
Horizon 2020 ◽  
Weather And Climate

<div>Every day, ECMWF produces ~120TiB of raw weather data, represented as a six-dimensional dataset. This data is used to produce approximately 30TiB of user-defined products, which are disseminated worldwide. The raw data is also stored in the world's largest meteorological archive (MARS), currently holding over 300 PiB of primary data -- which is also served around the world on demand. As the resolution of ECMWFs global weather models increase over the next few years, the amount of raw data produced per day will increase into the petabytes, and the distribution of products and archived data becomes impossible. In-situ, on-the-fly data extraction and processing are required to sustain and increase the accessibility of ECMWFs big weather data.</div><div> </div><div>To meet these requirements, ECMWF is developing Polytope -- an open-source service which allows users to request arbitrary n-dimensional stencils ("polytopes") of data from highly-structured n-dimensional datasets. The data extraction is performed server-side (collocated with the data), allowing for large data reduction prior to transmission and less complexity for the user. For example, a user could request a polytope describing a flight path -- simultaneously crossing temporal and spatial axes. Polytope will return just a few bytes of data rather than large structured arrays of geo-spatial data which must be further post-processed by the user.</div><div> </div><div>Polytope is being partly developed under LEXIS, an EU-funded Horizon 2020 project which focuses on large-scale HPC & cloud workflows. The emphasis of LEXIS is on how HPC and cloud systems interact; how they can share data; and methods to compose workflows of tasks running on both cloud and HPC systems. Polytope will be used to provide a cross-centre weather and climate data API which connects to multiple high-performance data sources across Europe, and serves multiple cloud environments with this data.</div><div> </div><div>This poster will present the early developments and future vision of Polytope. It will also illustrate how it is used within the LEXIS project to enable complex weather and climate workflows, involving global forecasts, regional forecasts and cloud-based simulations.</div>

scholarly journals Generation of a Test Reference Year for Alūksne, Latvia

2015 ◽  
Vol 33 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Mārtiņš Ruduks ◽  
Arturs Lešinskis
Keyword(s):  
Selection Process ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Building Energy ◽  
Weather Data ◽  
Building Performance ◽  
Climate Data ◽  
Meteorological Observations ◽  
Energy Simulations

Abstract Precise and reliable meteorological data are necessary for building performance analysis. Since meteorological conditions vary significantly from year to year, there is a need to create a test reference year (TRY), to represent the long-term weather conditions over a year. In this paper two different TRY data models were generated and compared: TRY and TRY-2. Both models where created by analysing every 3-hour weather data for a 30-year period (1984–2013) in Alūksne, Latvia, provided by the Latvian Environment Geology and Meteorology Centre (LEGMC). TRY model was generated according to standard LVS EN ISO 15927-4, but to create second model - TRY-2, 30 year average data were applied. The generated TRY contains typical months from a number of different years. The data gathered from TRY and TRY-2 models where compared with the climate data from the Latvian Cabinet of Ministers regulation No. 379, Regulations Regarding Latvian Building Code LBN 003-01. Average monthly temperature values in LBN 003-01 were lower than the TRY and TRY-2 values. The results of this study may be used in building energy simulations and heating-cooling load calculations for selected region. TRY selection process should include the most recent meteorological observations and should be periodically renewed to reflect the long-term climate change.

scholarly journals Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3030
Author(s):  
Simon Liebermann ◽  
Jung-Sup Um ◽  
YoungSeok Hwang ◽  
Stephan Schlüter
Keyword(s):  
Neural Network ◽  
Goodness Of Fit ◽  
Renewable Energy Sources ◽  
Weather Conditions ◽  
Solar Irradiation ◽  
Weather Data ◽  
Short Term ◽  
Climate Conditions ◽  
Lstm Network ◽  
The Time Domain

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models’ performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations it shows that combining an LSTM network with a CNN yields the best performance. However, regarding the chosen GoF measures, differences to the alternative approaches are fairly small. The hybrid model’s advantage lies not in the improved GoF but in its versatility: contrary to an LSTM or a CNN, it produces good results under all tested weather conditions.

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

scholarly journals Advanced Flight Planning and the Benefit of In-Flight Aircraft Trajectory Optimization

2021 ◽  
Vol 13 (3) ◽  
pp. 1383
Author(s):  
Judith Rosenow ◽  
Martin Lindner ◽  
Joachim Scheiderer
Keyword(s):  
New York ◽  
Traffic Control ◽  
Traffic Management ◽  
Trajectory Optimization ◽  
Service Providers ◽  
Weather Conditions ◽  
Air Traffic ◽  
Weather Data ◽  
Weather Forecasts ◽  
Aircraft Trajectory

The implementation of Trajectory-Based Operations, invented by the Single European Sky Air Traffic Management Research program SESAR, enables airlines to fly along optimized waypoint-less trajectories and accordingly to significantly increase the sustainability of the air transport system in a business with increasing environmental awareness. However, unsteady weather conditions and uncertain weather forecasts might induce the necessity to re-optimize the trajectory during the flight. By considering a re-optimization of the trajectory during the flight they further support air traffic control towards achieving precise air traffic flow management and, in consequence, an increase in airspace and airport capacity. However, the re-optimization leads to an increase in the operator and controller’s task loads which must be balanced with the benefit of the re-optimization. From this follows that operators need a decision support under which circumstances and how often a trajectory re-optimization should be carried out. Local numerical weather service providers issue hourly weather forecasts for the coming hour. Such weather data sets covering three months were used to re-optimize a daily A320 flight from Seattle to New York every hour and to calculate the effects of this re-optimization on fuel consumption and deviation from the filed path. Therefore, a simulation-based trajectory optimization tool was used. Fuel savings between 0.5% and 7% per flight were achieved despite minor differences in wind speed between two consecutive weather forecasts in the order of 0.5 m s−1. The calculated lateral deviations from the filed path within 1 nautical mile were always very small. Thus, the method could be easily implemented in current flight operations. The developed performance indicators could help operators to evaluate the re-optimization and to initiate its activation as a new flight plan accordingly.

scholarly journals Urban soundscape maps modelled with geo-referenced data

Noise Mapping ◽  
2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Catherine Lavandier ◽  
Pierre Aumond ◽  
Saul Gomez ◽  
Catherine Dominguès
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Public Space ◽  
Road Traffic ◽  
Sound Quality ◽  
Acoustic Measurements ◽  
Propagation Models ◽  
Urban Public Space ◽  
Eu Directive ◽  
The Eu

AbstractThe noise maps that are currently proposed as part of the EU Directive are based on the calculation of the Lday, Levening and Lnight. These levels are calculated from emission and propagation models that are expensive in time. These noise maps are criticized for being distant from the perception of city users. Thus, calculation models of sound quality have been proposed, for being closer to city users’ perception. They are either based on perceptual variables, or on acoustic measurements, or on georeferenced data, the latter being often already integrated into the Geographic Information Systems of most French metropolises. Considering 89 Parisian situations, this article proposes to compare the sound quality really perceived, with those from models using geo-referenced data. It also looks at the modeling of perceptual variables that influence the sound quality, such as perceived loudness, the perceived time ratio of traffic, voices and birds. To do this, such geo-referenced data as road traffic, the presence of gardens, food shops, restaurants, bars, schools, markets, are transformed into core densities. Being quick and easy to calculate, these densities predict effectively sound quality in the urban public space. Visualization of urban soundscape maps are proposed in this paper.

New Scientific Information Can Help to Inform the Evaluation of EU Deep-sea Fisheries Regulations

2021 ◽  
pp. 1-20
Author(s):  
Phillip J Turner ◽  
Matthew Gianni ◽  
Ellen Kenchington ◽  
Sebastian Valanko ◽  
David E Johnson
Keyword(s):  
Deep Sea ◽  
Scientific Information ◽  
Fish Population ◽  
Molecular Techniques ◽  
Fish Stocks ◽  
Horizon 2020 ◽  
Management Measures ◽  
Sea Fish ◽  
The Eu ◽  
Fish Population Structure

Abstract The European Union’s deep-sea fisheries regulations (Regulation (EU) No. 2016/2336) established obligations to manage deep-sea fisheries and to protect vulnerable marine ecosystems (VMEs). The European Commission is scheduled to complete a review of the regulations in 2021, providing an opportunity for new scientific information to be incorporated into the implementation of the regulations. Here, we summarise research outputs from the EU-funded Horizon 2020 ATLAS Project and explain their relevance to the regulation of deep-sea fisheries in EU waters. ATLAS research has increased our understanding of the distribution of VMEs and their importance in terms of ecosystem functioning. ATLAS research has also highlighted the utility of molecular techniques to understand fish population structure and the potential for habitat suitability models to help incorporate climate change into decision-making. Building on these scientific advances, we provide recommendations to help increase the effectiveness of management measures to conserve deep-sea fish stocks and protect VMEs.

Advances in the data rescue and digitization of historical wind speed observations in Sweden: the WINDGUST project

2021 ◽  
Author(s):  
Erik Engström ◽  
Cesar Azorin-Molina ◽  
Lennart Wern ◽  
Sverker Hellström ◽  
Christophe Sturm ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Global Climate ◽  
Current Status ◽  
Weather Data ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
Staff Members ◽  
The 1960S

<p>Here we present the progress of the first work package (WP1) of the project “Assessing centennial wind speed variability from a historical weather data rescue project in Sweden” (WINDGUST), funded by FORMAS – A Swedish Research Council for Sustainable Development (ref. 2019-00509); previously introduced in EGU2019-17792-1 and EGU2020-3491. In a global climate change, one of the major uncertainties on the causes driving the climate variability of winds (i.e., the “stilling” phenomenon and the recent “recovery” since the 2010s) is mainly due to short availability (i.e., since the 1960s) and low quality of observed wind records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC).</p><p>The WINDGUST is a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI) and the University of Gothenburg aimed at filling the key gap of short availability and low quality of wind datasets, and improve the limited knowledge on the causes driving wind speed variability in a changing climate across Sweden.</p><p>During 2020, we worked in WP1 to rescue historical wind speed series available in the old weather archives at SMHI for the 1920s-1930s. In the process we followed the “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization. Our protocol consisted on: (i) designing a template for digitization; (ii) digitizing papers by an imaging process based on scanning and photographs; and (iii) typing numbers of wind speed data into the template. We will report the advances and current status, challenges and experiences learned during the development of WP1. Until new year 2020/2021 eight out of thirteen selected stations spanning over the years 1925 to 1948 have been scanned and digitized by three staff members of SMHI during 1,660 manhours.</p>

scholarly journals The Influence of the European H2020 Program on the Development of Regions: The Multiplier Impact of EU Funding in the Regions under Horizon 2020 in NUT III - North

2019 ◽  
Vol 17 (3) ◽  
pp. 853-871
Author(s):  
Natacha Jesus Silva ◽  
Diamantino Ribeiro
Keyword(s):  
Regional Economy ◽  
Community Support ◽  
Northern Region ◽  
The European Union ◽  
Final Phase ◽  
Investment Funds ◽  
Horizon 2020 ◽  
Regional Investment ◽  
Partnership Agreement ◽  
The Eu

The partnership agreement between the European Union and the Member States for the implementation of the European Structural and Investment Funds for the period 2014 to 2020 is in its final phase. This study analyzes the multiplier impact on regional investment of the European funds made available to the northern region of Portugal - NUTS III, until September 2018 and intends to answer the following questions: What is the amount invested in the regional economy for each euro of support allocated by the EU through the H2020 program, and what is the percentage distribution of community support versus investment per area of intervention?

scholarly journals Review of Weather Forecast Services for Ship Routing Purposes

2019 ◽  
Vol 26 (4) ◽  
pp. 80-89
Author(s):  
Marcin Życzkowski ◽  
Joanna Szłapczyńska ◽  
Rafał Szłapczyński
Keyword(s):  
Collision Avoidance ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Weather Data ◽  
Ocean Engineering ◽  
Ship Routing ◽  
Engineering Research ◽  
Fishing Vessels ◽  
Analysis Of Stability

Abstract Weather data is nowadays used in a variety of navigational and ocean engineering research problems: from the obvious ones like voyage planning and routing of sea-going vessels, through the analysis of stability-related phenomena, to detailed modelling of ships’ manoeuvrability for collision avoidance purposes. Apart from that, weather forecasts are essential for passenger cruises and fishing vessels that want to avoid the risk associated with severe hydro-meteorological conditions. Currently, there is a wide array of services that offer weather predictions. These services include the original sources – services that make use of their own infrastructure and research models – as well as those that further postprocess the data obtained from the original sources. The existing services also differ in their update frequency, area coverage, geographical resolution, natural phenomena taken into account and finally – output file formats. In the course of the ROUTING project, primarily addressing ship weather routing accounting for changeable weather conditions, the necessity arose to prepare a report on the state-of-the-art in numerical weather prediction (NWP) modelling. Based on the report, this paper offers a thorough review of the existing weather services and detailed information on how to access the data offered by these services. While this review has been done with transoceanic ship routing in mind, hopefully it will also be useful for a number of other applications, including the already mentioned collision avoidance solutions.

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