At 3:36 AM on the 24th of August a magnitude 6.2 earthquake struck the Amatrice region. The shaking in this event caused nearly 300 deaths and significant damage to the villages distributed across the region. The earthquake ruptured across two faults, the Laga-Amatrice and Vettore faults, which were previously thought to be separate structures that could not rupture in a single event. Our team visited the region days after the event to begin scientific study of this earthquake, investigating the surface expression of the earthquake and installing GNSS equipment that will measure high-resolution motion of the ground continuously for weeks and months following the earthquake. Our team comprises UK and Italian scientists from the University of Leeds, University of Durham, Univeristy of London, Birkbeck University of London, University of Insurbia, the Italian Geological Survey (ISPRA), and Geospatial Research Ltd (Durham). Members of our team who are experts in using satellite data to investigate ground deformation (Durham) processed data in real-time to direct the initial field campaign. This project will aim to fully characterise the nature of the Amatrice earthquake in terms of what happened during and what is continuing to occur after the seismic event. We will use a variety of techniques including satellite radar measurements and modelling of co and post -seismic deformation, GNSS (Global Navigation Satellite System) measurements of ground deformation, photogrammetry and laser scanning to make high resolution measurements of the surface rupture, detailed field work in the region of the earthquake, and modelling techniques to determine how this earthquake affected stress on the surrounding faults. The work is urgent due to the need to document post-seismic deformation in the weeks and months following the earthquake, and the degrading nature of the surface rupture. This research will allow us to investigate fault connectivity and how linkage develops. We will test hypotheses regarding the role of postseismic deformation after an earthquake that links previously independent structures. Fault linkage typically happens over long geological timescales and has never before been captured before with such a high quality dataset. Our results will be important for incorporating multi-fault rupturing earthquakes into future hazard assessments made in central Italy and globally.

By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. Computer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients. The aim of this project is to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions. We will gather information on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites have been chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. Using 28 radiometers, and moving them several times during the course of each experiment, will allow us to measure the highly variable patterns of radiation at the snow surface in forests. Information from the field experiments will be used in developing and testing a range of models. To reach the scales of interest, we will begin with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective is a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. We will work in close consultation with project partners at climate modelling and forecasting centres to ensure that our activities are directed towards outcomes that will meet their requirements.