The UK Climate Predicition 2009 (UKCP09) Outputs and metadata specification - Release 1.1

The UK Climate Predicition 2009 (UKCP09) Project user interface (UI) documentation. The User Interface (UI) provides the access to project outputs. These outputs must also be consistent and well-described with an appropriate level of information (metadata) passed to users alongside the data. This document explains the output formats delivered by the UI. Particular attention is paid to the formatting of CSV outputs which are likely to be the most commonly accessed by users

NCAS Computing skills training

The introduction to scientific computing course covers the skills needed for managing and analysing data using Linux and Python

Technology to aid the analysis of large-volume multi-institute climate model output at a central analysis facility (PRIMAVERA Data Management Tool V2.10)

The PRIMAVERA project aimed to develop a new generation of advanced and well-evaluated high-resolution global climate models. As part of PRIMAVERA, seven different climate models were run in both standard and higher-resolution configurations, with common initial conditions and forcings to form a multi-model ensemble. The ensemble simulations were run on high-performance computers across Europe and generated approximately 1.6 PiB (pebibytes) of output. To allow the data from all models to be analysed at this scale, PRIMAVERA scientists were encouraged to bring their analysis to the data. All data were transferred to a central analysis facility (CAF), in this case the JASMIN super-data-cluster, where it was catalogued and details made available to users using the web interface of the PRIMAVERA Data Management Tool (DMT). Users from across the project were able to query the available data using the DMT and then access it at the CAF. Here we describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this multi-model dataset. We believe that PRIMAVERA's experience using a CAF demonstrates how similar, multi-institute, big-data projects can efficiently share, organise and analyse large volumes of data.</p

Characteristics of stable flows over Southern Greenland

The main characteristic features of stable atmospheric flows over a large mountain plateau are summarised and then compared with mesoscale and synoptic scale numerical simulation, meteorological analysis, satellite imagery, and surface observations for the cases of flows over Southern Greenland for four wind directions. The detailed features are identified using the concepts and scaling of stably stratified flow over large mountains with variations in surface roughness, elevation, and heating. For westerly and easterly winds detached jets form at the southern tip, where coastal jets converge, which propagate large distances across the ocean. Near coasts katabatic winds can combine with barrier jets and wake flows generated by synoptic winds. Note how the approach flow rises/falls over southern Greenland for easterly/westerly winds, leading in both cases to more cloud on the western side. Some conclusions are drawn about the large-scale influences of these flows; detached jets in the atmosphere; air-sea interaction; formation of low pressure systems. For accurate simulations of these flows, mesoscale models are necessary with resolutions of order of 20 km or less. © Birkhäuser Verlag, Basel, 2005

MOLES3: implementing an ISO standards driven data catalogue

ISO19156 Observations and Measurements (O&M) provides a standardised framework for organising information about the collection of information about the environment. Here we describe the implementation of a specialisation of O&M for environmental data, the Metadata Objects for Linking Environmental Sciences (MOLES3). MOLES3 provides support for organising information about data, and for user navigation around data holdings. The implementation described here, “CEDA-MOLES”, also supports data management functions for the Centre for Environmental Data Archival, CEDA. The previous iteration of MOLES (MOLES2) saw active use over five years, being replaced by CEDA-MOLES in late 2014. During that period important lessons were learnt both about the information needed, as well as how to design and maintain the necessary information systems. In this paper we review the problems encountered in MOLES2; how and why CEDA-MOLES was developed and engineered; the migration of information holdings from MOLES2 to CEDA-MOLES; and, finally, provide an early assessment of MOLES3 (as implemented in CEDA-MOLES) and its limitations. Key drivers for the MOLES3 development included the necessity for improved data provenance, for further structured information to support ISO19115 discovery metadata export (for EU INSPIRE compliance), and to provide appropriate fixed landing pages for Digital Object Identifiers (DOIs) in the presence of evolving datasets. Key lessons learned included the importance of minimising information structure in free text fields, and the necessity to support as much agility in the information infrastructure as possible without compromising on maintainability both by those using the systems internally and externally (e.g. citing in to the information infrastructure), and those responsible for the systems themselves. The migration itself needed to ensure continuity of service and traceability of archived assets

Developing an open data portal for the ESA climate change initiative

We introduce the rationale for, and architecture of, the European Space Agency Climate Change Initiative (CCI) Open Data Portal (http://cci.esa.int/data/). The Open Data Portal hosts a set of richly diverse datasets – 13 “Essential Climate Variables” – from the CCI programme in a consistent and harmonised form and to provides a single point of access for the (>100 TB) data for broad dissemination to an international user community. These data have been produced by a range of different institutions and vary across both scientific and spatio-temporal characteristics. This heterogeneity of the data together with the range of services to be supported presented significant technical challenges. An iterative development methodology was key to tackling these challenges: the system developed exploits a workflow which takes data that conforms to the CCI data specification, ingests it into a managed archive and uses both manual and automatically generated metadata to support data discovery, browse, and delivery services. It utilises both Earth System Grid Federation (ESGF) data nodes and the Open Geospatial Consortium Catalogue Service for the Web (OGC-CSW) interface, serving data into both the ESGF and the Global Earth Observation System of Systems (GEOSS). A key part of the system is a new vocabulary server, populated with CCI specific terms and relationships which integrates OGC-CSW and ESGF search services together, developed as part of a dialogue between domain scientists and linked data specialists. These services have enabled the development of a unified user interface for graphical search and visualisation – the CCI Open Data Portal Web Presence

Spatial imaging of the spin Hall effect and current-induced polarization in two-dimensional electron gases

Spin-orbit coupling in semiconductors relates the spin of an electron to its momentum and provides a pathway for electrically initializing and manipulating electron spins for applications in spintronics and spin-based quantum information processing. This coupling can be regulated with quantum confinement in semiconductor heterostructures through band structure engineering. Here we investigate the spin Hall effect and current-induced spin polarization in a two-dimensional electron gas confined in (110) AlGaAs quantum wells using Kerr rotation microscopy. In contrast to previous measurements, the spin Hall profile exhibits complex structure, and the current-induced spin polarization is out-of-plane. The experiments map the strong dependence of the current-induced spin polarization to the crystal axis along which the electric field is applied, reflecting the anisotropy of the spin-orbit interaction. These results reveal opportunities for tuning a spin source using quantum confinement and device engineering in non-magnetic materials.Comment: Accepted for publication (2005

Data integration with the Climate Science Modelling Language

The Climate Science Modelling Language (CSML) has been developed by the NERC DataGrid (NDG) project as a standards-based data model and XML markup for describing and constructing climate science datasets. It uses conceptual models from emerging standards in GIS to define a number of feature types, and adopts schemas of the Geography Markup Language (GML) where possible for encoding. A prototype deployment of CSML is being trialled across the curated archives of the British Atmospheric and Oceanographic Data Centres. These data include a wide range of data types – both observational and model – and heterogeneous file-based storage systems. CSML provides a semantic abstraction layer for data files, and is exposed through higher level data delivery services. In NDG these will include file instantiation services (for formats of choice) and the web services of the Open Geospatial Consortium (OGC)

Blind topological measurement-based quantum computation

Blind quantum computation is a novel secure quantum-computing protocol that enables Alice, who does not have sufficient quantum technology at her disposal, to delegate her quantum computation to Bob, who has a fully fledged quantum computer, in such a way that Bob cannot learn anything about Alice's input, output and algorithm. A recent proof-of-principle experiment demonstrating blind quantum computation in an optical system has raised new challenges regarding the scalability of blind quantum computation in realistic noisy conditions. Here we show that fault-tolerant blind quantum computation is possible in a topologically protected manner using the Raussendorf-Harrington-Goyal scheme. The error threshold of our scheme is 0.0043, which is comparable to that (0.0075) of non-blind topological quantum computation. As the error per gate of the order 0.001 was already achieved in some experimental systems, our result implies that secure cloud quantum computation is within reach.Comment: 17 pages, 5 figure