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EOOffshore is a Sustainable Energy Authority of Ireland (SEAI) funded project, which commenced in June 2020 in the School of Physics in University College Dublin (UCD). It presents a case study that demonstrates the utility of the Pangeo software ecosystem in the development of offshore wind speed and power density estimates, increasing wind measurement coverage of offshore renewable energy assessment areas in the Irish Continental Shelf (ICS) region. It has involved the creation of a new wind data catalog for this region, consisting of a collection of analysis-ready, cloud-optimized (ARCO) datasets featuring up to 21 years of available in situ, reanalysis, and satellite observation wind data products. The Copernicus Marine Service (CMS), or Copernicus Marine Environment Monitoring Service (CMEMS), is the marine component of the European Union Copernicus Earth Observation (EO) programme. It provides free, regular and systematic ocean data products on a global and regional scale. The CMS Surface Wind Thematic Assembly Center (Wind TAC) is responsible for the collection, processing, qualification and distribution of surface winds data products derived from scatterometer satellite missions, including near-real time (NRT) and delayed mode (REP) processing of global wind observations. These catalog data sets contain CMS wind speed and direction data products generated using the Advanced SCATterometer (ASCAT) instruments deployed on the Metop satellites. eooffshore_ics_cmems_WIND_GLO_WIND_L3_REP_OBSERVATIONS_012_005_MetOp_ASCAT.zarr.tar.gz 2007-2021 data products from the Global Ocean Daily Gridded Reprocessed (REP) Level-3 Sea Surface Winds from Scatterometer data set. eooffshore_ics_cmems_WIND_GLO_WIND_L3_NRT_OBSERVATIONS_012_002_MetOp_ASCAT.zarr.tar.gz 2016-2021 data products from the Global Ocean Daily Gridded Near Real Time (NRT) Level-3 Sea Surface Winds from Scatterometer data set. The products feature 0.125 degree grids, based on 12.5 km scatterometer swath observations, for all combinations of Metop A/B (REP) and Metop A/B/C (NRT) satellites and ASCending, DEScending passes. These ASCAT data sets were used in the EOOffshore project outputs presented (Scalable Offshore Wind Analysis With Pangeo) at the Meeting Exascale Computing Challenges with Compression and Pangeo 2022 EGU General Assembly session. Description and example usage of the ASCAT data sets in EOOffshore: ASCAT Wind Data for Irish Continental Shelf region Offshore Wind in Irish Areas Of Interest Comparison of Offshore Wind Speed Extrapolation and Power Density Estimation As requested by the Copernicus Marine Service Service Commitments and Licence, these Zarr stores were: Generated using E.U. Copernicus Marine Service Information; https://doi.org/10.48670/moi-00182; https://doi.org/10.48670/moi-00183;

Central to our investigation is the Building Energy Rating (BER) dataset of Ireland, sourced from GeoDirectory data. This dataset provides a foundational resource, encompassing a comprehensive range of building-scale parameters such as detailed addresses, geocode data (latitude and longitude), area, height, number of floors, roof type, construction age, radon emission, HVAC system details, and bedroom and bathroom counts. To enrich this dataset, we incorporated additional features from the Digital Landscape Models (DLM) Core Data from Tailte Éireann Surveying (PRIME2 Dataset). These enhancements include metrics such as nearest neighbor buildings, the density of the built environment surrounding each building, and district attributes like the ratio of green area to non-green area in the urban vicinity.

Demand-Side Management systems aim to modulate energy consumption at the customer side of the meter using price incentives. Current incentive schemes allow consumers to reduce their costs, and from the point of view of the supplier play a role in load balancing, but do not lead to optimal demand patterns. In the context of charging fleets of electric vehicles, we propose a centralised method for setting overnight charging schedules. This method uses evolutionary algorithms to automatically search for optimal plans, representing both the charging schedule and the energy drawn from the grid at each time-step. In successive experiments, we optimise for increased state of charge, reduced peak demand, and reduced consumer costs. In simulations, the centralised method achieves improvements in performance relative to simple models of non-centralised consumer behaviour.

Climate change affects the timing of phenological events, such as the start, end, and length of the growing season of vegetation. A better understanding of how the phenology responded to climatic determinants is important in order to better anticipate future climate-ecosystem interactions. We examined the changes of three phenological events for the Mongolian Plateau and their climatic determinants. To do so, we derived three phenological metrics from remotely sensed vegetation indices and associated these with climate data for the period of 1982 to 2011. The results suggested that the start of the growing season advanced by 0.10 days yr-1, the end was delayed by 0.11 days yr-1, and the length of the growing season expanded by 6.3 days during the period from 1982 to 2011. The delayed end and extended length of the growing season were observed consistently in grassland, forest, and shrubland, while the earlier start was only observed in grassland. Partial correlation analysis between the phenological events and the climate variables revealed that higher temperature was associated with an earlier start of the growing season, and both temperature and precipitation contributed to the later ending. Overall, our findings suggest that climate change will substantially alter the vegetation phenology in the grasslands of the Mongolian Plateau, and likely also in biomes with similar environmental conditions, such as other semi-arid steppe regions.

Experimental data supporting the findings of the manuscript 'Phenotypic Variation from Waterlogging in Multiple Perennial Ryegrass Varieties under Climate Change Conditions'. This dataset will be made publicly available when the manuscript has been accepted for journal publication unless exceptional conditions become apparent.

EOOffshore is a Sustainable Energy Authority of Ireland (SEAI) funded project, which commenced in June 2020 in the School of Physics in University College Dublin (UCD). It presents a case study that demonstrates the utility of the Pangeo software ecosystem in the development of offshore wind speed and power density estimates, increasing wind measurement coverage of offshore renewable energy assessment areas in the Irish Continental Shelf (ICS) region. It has involved the creation of a new wind data catalog for this region, consisting of a collection of analysis-ready, cloud-optimized (ARCO) datasets featuring up to 21 years of available in situ, reanalysis, and satellite observation wind data products. ERA5 is the fifth generation global reanalysis data set produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). It is a component of the Copernicus Climate Change Service (C3S), where data products are publicly available in the C3S Climate Data Store. This particular catalog data set (eooffshore_ics_era5_single_level_hourly_wind.zarr.tar.gz) contains 2001-2021 products for the ICS region from the ERA5 hourly data on single levels from 1979 to present data set, which provides hourly data from 1979 to the present day, at single levels (atmospheric, ocean-wave and land surface quantities). Wind speed and direction have been calculated from the uX and vX variables, where X = 10 m and 100 m above sea level. This ERA5 data set was used in the EOOffshore project outputs presented (Scalable Offshore Wind Analysis With Pangeo) at the Meeting Exascale Computing Challenges with Compression and Pangeo 2022 EGU General Assembly session. Description and example usage of the ERA5 data set in EOOffshore: ERA5 Wind Data for Irish Continental Shelf region Offshore Wind in Irish Areas Of Interest Comparison of Offshore Wind Speed Extrapolation and Power Density Estimation As requested by the ECMWF - Licence to Use Copernicus Products, this Zarr store was: Generated using Copernicus Climate Change Service information [2001 - 2021]

EOOffshore is a Sustainable Energy Authority of Ireland (SEAI) funded project, which commenced in June 2020 in the School of Physics in University College Dublin (UCD). It presents a case study that demonstrates the utility of the Pangeo software ecosystem in the development of offshore wind speed and power density estimates, increasing wind measurement coverage of offshore renewable energy assessment areas in the Irish Continental Shelf (ICS) region. It has involved the creation of a new wind data catalog for this region, consisting of a collection of analysis-ready, cloud-optimized (ARCO) datasets featuring up to 21 years of available in situ, reanalysis, and satellite observation wind data products. The European Union Copernicus Earth Observation (EO) programme and services are based on data collected from EO satellites, in particular, the Sentinel satellite missions. This includes the Sentinel-1 mission, which consists of C-band Synthetic Aperture Radar (SAR) imaging satellites in polar orbit. One of its main objectives is the provision of ocean monitoring services, where its Level-2 Ocean (OCN) products include an Ocean WInd field (OWI) component. This provides gridded estimates of wind speed and direction at 10 m above the surface, with a typical spatial resolution of 1 km. This particular catalog data set (eooffshore_ics_level3_sentinel1_ocn.zarr.tar.gz) contains 2015-2021 OCN wind products for the ICS region, which were retrieved from the Copernicus Open Access Hub (COAH) and the Alaska Satellite Facility (ASF). The data set was used in the EOOffshore project outputs presented (Scalable Offshore Wind Analysis With Pangeo) at the Meeting Exascale Computing Challenges with Compression and Pangeo 2022 EGU General Assembly session. Description and example usage of the Sentinel-1 data set in EOOffshore: Sentinel-1 Wind Data for Irish Continental Shelf region Offshore Wind in Irish Areas Of Interest Comparison of Offshore Wind Speed Extrapolation and Power Density Estimation As requested by the Legal Notice on the use of Copernicus Sentinel Data and Service Information, this data set: Contains modified Copernicus Sentinel data [2015 - 2021]