A5019061680- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Distributed and Parallel Computing Systems
- Astro and Planetary Science
- Energy Load and Power Forecasting
- Water Quality and Pollution Assessment
- Geophysics and Gravity Measurements
- Methane Hydrates and Related Phenomena
- Advanced Data Storage Technologies
- Scientific Computing and Data Management
- Peer-to-Peer Network Technologies
- Marine and coastal ecosystems
- Stellar, planetary, and galactic studies
- Infrared Target Detection Methodologies
- Atmospheric aerosols and clouds
- Advanced Image Processing Techniques
- Marine and coastal plant biology
- Research Data Management Practices
- Isotope Analysis in Ecology
- Hydrology and Watershed Management Studies
- Gene expression and cancer classification
- SARS-CoV-2 detection and testing
- Coastal wetland ecosystem dynamics
- Wind and Air Flow Studies
- Oceanographic and Atmospheric Processes
Irish Centre for High-End Computing
2011-2024
Ollscoil na Gaillimhe – University of Galway
2010-2022
Abstract. In the simulation of complex multi-scale flows arising in weather and climate modelling, one biggest challenges is to satisfy strict service requirements terms time solution budgetary constraints energy solution, without compromising accuracy stability application. These simulations require algorithms that minimise footprint along with required produce a maintain physically level accuracy, are numerically stable, resilient case hardware failure. The European Centre for Medium-Range...
Graphical Abstract Overall research workflow showing data types, study area, model development and biomass results.
Abstract. Data augmentation is a well known technique that frequently used in machine learning tasks to increase the number of training instances and hence decrease model over-fitting. In this paper we propose data can further boost performance satellite image super resolution tasks. A super-resolution convolutional neural network (SRCNN) was adopted as state-of-the-art deep test proposed technique. Different techniques were studied investigate their relative importance accuracy gains. We...
Abstract. In the simulation of complex multi-scale flow problems, such as those arising in weather and climate modelling, one biggest challenges is to satisfy operational requirements terms time-to-solution energy-to-solution yet without compromising accuracy stability calculation. These competing factors require development state-of-the-art algorithms that can optimally exploit targeted underlying hardware efficiently deliver extreme computational capabilities typically required forecast...
Wind-speed forecasts for a wind-farm in southwest Ireland were made over one year using the operational HARMONIE mesoscale weather forecast model, and Bayes Model Averaging (BMA) statistical post-processing to remove systematic local bias. The deterministic alone generated mean absolute errors of 1.7−2.0 ms −1 out 24 hrs, when interpolated location met-mast. Application BMA reduced these by about 15%, 1.5−1.6 -1 , on average. Forecast do not degrade significantly as lead-time increases, at...
As the market environment for farming has become more complicated, need farmer engagement in financial management increased. However, decisions to consider individual farm environmental conditions. This paper discusses design of a new big-data based analytical solution low management—a Farm Financial Information System (FARMFIS). Using pastoral livestock system as case study, methodology required develop this predictive is described. Building upon real-time weather, satellite grass growth...
  Access to climate data is essential if we are better understand the of past, present and future. Climate scientists require reconstruct past extreme weather events, create seasonal forecasts produce projections. Various private public sector actors also as part their climate-related decision-making planning. Historical can assist insurance by providing information on events. Farmers how future will impact output. The help populations who live along coastlines changing nature storm...
<p>Through Remote Sensing of Irish Surface Water (INFER) project, we are validating the algorithms to measure  water quality using Sentinel 2 imagery, which comprises two European Space Agency (ESA) terrestrial satellites with combined temporal resolution 5 days. The project is focused on selection optimal that will be applicable in context relation high cloud cover and relatively small sizes water bodies. current procedure entails collection reflectance data from...
<p>The ESA-funded AIREO project [1] sets out to produce AI-ready training dataset specifications and best practices support the development of machine learning models on Earth Observation (EO) data. While quality quantity EO data has increased drastically over past decades, availability for applications is considered a major bottleneck. The goal move towards implementing FAIR principles in EO, enhancing especially finability, interoperability reusability aspects. ...
is Coordinator of a project established to develop world-class, extreme-scale computing capabilities for numerical weather prediction and future climate models.Below, he discusses the challenges seeks address, coordination complex research initiatives, upcoming dissemination events Impact Objective• Develop European operational models
This document is one of the deliverable reports created for ESCAPE project. stands Energy-efficient Scalable Algorithms Weather Prediction at Exascale. The project develops world-class, extreme-scale computing capabilities European operational numerical weather prediction and future climate models. done by identifying & Climate dwarfs which are key patterns in terms computation communication (in spirit Berkeley dwarfs). These then optimised different hardware architectures (single...