LFRic: meeting the challenges of scalability and performance portability in weather and climate models

This paper describes LFRic: the new weather and climate modelling system being developed by the UK Met Office to replace the existing Unified Model in preparation for exascale computing in the 2020s. LFRic uses the GungHo dynamical core and runs on a semi-structured cubed-sphere mesh. The design of the supporting infrastructure follows object-oriented principles to facilitate modularity and the use of external libraries where possible. In particular, a `separation of concerns' between the science code and parallel code is imposed to promote performance portability. An application called PSyclone, developed at the STFC Hartree centre, can generate the parallel code enabling deployment of a single source science code onto different machine architectures. This paper provides an overview of the scientific requirement, the design of the software infrastructure, and examples of PSyclone usage. Preliminary performance results show strong scaling and an indication that hybrid MPI/OpenMP performs better than pure MPI

Position sensitive detectors for hard X-ray and gamma-ray astronomy

SIGLEAvailable from British Library Document Supply Centre- DSC:DX181479 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Design for persistence: graph-based connectivity, habitat reserves and species persistence

Connectivity is widely thought to play a key role in the persistence of metapopulations. However, there is no generally accepted approach to measuring connectivity in landscapes. Current reserve selection algorithms tend to focus on clustering habitat sites as an approach to maximising connectivity. An alternative approach to understanding connectivity is, however, to focus on the spatial configuration of habitat patches in a landscape. In this study, graph methods are used to represent habitat networks and investigate the relationship between spatial configuration and the flow of species moving across the network. Betweenness Centrality, a graph metric designed to measure the proportion of traffic passing through any node in a network, is applied in modified form as a reserve selection algorithm. The performance of reserves selected using Betweenness Centrality is assessed against species persistence measures from the metapopulation model RAMAS and compared to equivalent reserve selections for other well known reserve selection algorithms. Within the limited set of cases considered, this study found that Betweenness Centrality has a high degree of success in designing reserves for species with high dispersal characteristics, but is unable to predict appropriate reserve sites for low or non-dispersing species. Further directions for research in the field are suggested, with an emphasis on rigorously validating this type of approach to understanding connectivity

No quick fix for Australia's future energy challenge

This report sets out the findings of the technology assessments and reviews the implications for government policy in terms of developing and deploying low emissions electricity technology. An accompanying publication: No easy choices: which way to Australia\u27s energy future – Technology Analysis, available on the Grattan Institute, website, assesses each of the seven low emissions technologies in detail. It also includes a review of the barriers that the transmission network can pose to large-scale deployment of low-emissions energy technologies. The grid is a special case, being monopoly infrastructure and essential to electricity supply

Assessing the impacts of biodiversity offset policies

In response to the increasing loss of native vegetation and biodiversity, a growing number of countries have adopted 'offsetting' policies that seek to balance local habitat destruction by restoring, enhancing and/or protecting similar but separate habitat. Although these policies often have a stated aim of producing a 'net gain' or 'no net loss' in environmental benefits, it is challenging to determine the potential impacts of a policy and if, or when, it will achieve its objectives. In this paper we address these questions with a general approach that uses predictive modelling under uncertainty to quantify the ecological impacts of different offset policies. This is demonstrated with a case study to the west of Melbourne, Australia where a proposed expansion of Melbourne's urban growth boundary would result in a loss of endangered native grassland, requiring offsets to be implemented as compensation. Three different offset policies were modelled: i) no restrictions on offset location, ii) offset locations spatially restricted to a strategically defined area and iii) offset locations spatially and temporally restricted, requiring all offsets to be implemented before commencing development. The ecological impact of the policies was determined with a system model that predicts future changes in the extent and condition of native grassland