Conducting volcanic ash cloud exercises: practising forecast evaluation procedures and the pull-through of scientific advice to the London VAAC

The London Volcanic Ash Advisory Centre (VAAC) provides forecasts on the expected presence of volcanic ash in the atmosphere to mitigate the risk to aviation. It is fundamentally important that operational capability is regularly tested through exercises, to guarantee an effective response to an event. We have developed exercises which practise the pull-through of scientific advice into the London VAAC, the forecast evaluation process, and the decision-making procedures and discussions needed for generating the best possible forecasts under real-time conditions. London VAAC dispersion model forecasts are evaluated against observations. To test this capability in an exercise, we must create observation data for a hypothetical event. We have developed new methodologies for generating and using simulated satellite and lidar retrievals. These simulated observations enable us to practise our ability to interpret, compare, and evaluate model output and observation data under real-time conditions. Forecast evaluation can benefit from an understanding of how different choices of model setup (input parameters), model physics, and driving meteorological data impact the predicted extent and concentration of ash. Through our exercises, we have practised comparing output from model simulations generated using different models, model setups, and meteorological data, supplied by different institutions. Our exercises also practise the communication and interaction between Met Office (UK) scientists supporting the London VAAC and external experts, enabling knowledge exchange and discussions on the interpretation of model output and observations, as we strive to deliver the best response capability for the aviation industry and stakeholders. In this paper, we outline our exercise methodology, including the use of simulated satellite and lidar observations, and the development of the strategy to compare output generated from different modelling systems. We outline the lessons learnt, including the benefits and challenges of conducting exercises which practise our ability to provide scientific advice for an operational response at the London VAAC

Forewarned is forearmed: understanding multihazard risk assessment methods for disaster risk reduction and for increasing disaster preparedness

Recent years have demonstrated that changing climate is likely to increase the frequency and impacts of complex multihazard events. There is therefore a pressing need to develop methodologies to comprehensively assess the interactions between hazard, exposure and vulnerability that create multihazard risk assessments. Due to the character of many natural hazard events and the paucity of data in inventories, purely quantitative (statistically driven) methods can be challenging to support consequently many multihazard risk approaches have been more qualitative in nature. We present an overview of a new open-source python toolbox that can generate a compounding multi-hazard risk assessment at national scale in a semi-quantitative manner. The toolbox works by: 1) Creating an index value to allow for the combination of hazard footprints and impacts data for: Flood, Earthquake, Landslide and Volcanic eruptions, 2) Identifying the factors that affect the exposure and vulnerability of buildings to these specific hazards, 3) Calculating of the vulnerability of individual buildings within hazard zones, 4) Applying weights for each building type to express the potential vulnerability of individual buildings to a specific hazard to generate relative single hazard vulnerability maps and then 5) Combining these single hazard ‘relative vulnerability maps’ to generate a multi-hazard vulnerability map which is weighted to reflect single hazard frequencies. This toolbox and the methodologies that support it have been deployed in work the BGS has conducted in Nepal, Tanzania, Brazil and Colombia and is the basis of new collaborations with organizations in the Philippines and Indonesia. We will present an overview of selected use cases to demonstrate how these tools can support DRR and disaster preparedness. Keywords: Geoscience, SE Asia, CCOP, Thematic Sessio

metomi/isodatetime: isodatetime 2017.08.0

Release 8. See https://github.com/metomi/isodatetime/blob/master/CHANGES.md for detail

Geomorphometric delineation of floodplains and terraces from objectively defined topographic thresholds

Floodplain and terrace features can provide information about current and past fluvial processes, including channel response to varying discharge and sediment flux, sediment storage, and the climatic or tectonic history of a catchment. Previous methods of identifying floodplain and terraces from digital elevation models (DEMs) tend to be semi-automated, requiring the input of independent datasets or manual editing by the user. In this study we present a new method of identifying floodplain and terrace features based on two thresholds: local gradient, and elevation compared to the nearest channel. These thresholds are calculated statistically from the DEM using quantile–quantile plots and do not need to be set manually for each landscape in question. We test our method against field-mapped floodplain initiation points, published flood hazard maps, and digitised terrace surfaces from seven field sites from the US and one field site from the UK. For each site, we use high-resolution DEMs derived from light detection and ranging (lidar) where available, as well as coarser resolution national datasets to test the sensitivity of our method to grid resolution. We find that our method is successful in extracting floodplain and terrace features compared to the field-mapped data from the range of landscapes and grid resolutions tested. The method is most accurate in areas where there is a contrast in slope and elevation between the feature of interest and the surrounding landscape, such as confined valley settings. Our method provides a new tool for rapidly and objectively identifying floodplain and terrace features on a landscape scale, with applications including flood risk mapping, reconstruction of landscape evolution, and quantification of sediment storage and routing

LSDTopoTools

The LSDTopoTools code and documentation are available on GitHub, with archival copies on Zenodo.LSDTopoTools is a software package for analysing topography. Applications of these analyses span hydrology, geomorphology, soil science, ecology, and cognate fields. The software began within the Land Surface Dynamics group at the University of Edinburgh, and now has developers and users around the world

Conducting Multi-Agency Volcanic Ash Cloud Exercises: Practicing forecast evaluation procedures and the pull-through of scientific advice to the London VAAC

Practising and testing emergency procedures are fundamental for ensuring an effective operational response to a crisis. In this presentation we will introduce a new series of exercises which have been developed to test the multi-agency response needed to produce volcanic ash forecasts at the London Volcanic Ash Advisory Centre (VAAC). Our exercises have been specifically designed to practice our ability to interpret and evaluate model simulations and observations, the pull through of international scientific expertise into the London VAAC, and decision-making procedures under uncertainty. In this presentation we will describe our exercise methodology, this includes the development of simulated observations for exercise conditions, and a framework for comparing transport and dispersion simulations generated using different model setups (multi-model ensemble). We will also discuss how we practice the necessary interactions between scientists supporting the London VAAC and external collaborators, which may include experts at volcano observatories, national/state geological or geophysical institutions, and volcano research institutions. We will present case-studies of exercises for hypothetical events in Iceland and outline the lessons learnt. Our Exercises have not only improved our ability to respond to a volcanic ash cloud event but have also driven scientific and technical improvement of the forecasts, and strengthened the relationships between collaborators and responders, with the aim of providing the best possible advice to the London VAAC

cylc/cylc-flow: cylc-flow-8.2.3

<p>See <a href="https://github.com/cylc/cylc-flow/blob/master/CHANGES.md">CHANGES.md</a> for detail.</p> <p>Cylc 8 can be installed via pypi or Conda - you don't need to download this release directly. See the <a href="https://cylc.github.io/cylc-doc/latest/html/installation.html">installation</a> section of the documentation.</p&gt