Data Sciences for Climate and Environment
Organisers: Michel Tsamados (University College London); Chris Oates (Newcastle University), Richard Smith, (University of North Carolina), and Ruth Petrie, (Rutherford Appleton Laboratory)
Date: 26 March 2018
Venue: The Alan Turing Institute
Collectively, we are modelling and monitoring our planet better than we have ever done in our history, as a result of sustained efforts from the climate modelling community and space agencies and the private sector worldwide. Climate and weather models can now be run at finer spatial resolutions (10km or better), therefore enabling more realistic simulations of smaller and smaller scale processes (i.e. tropical cyclones in the atmosphere or eddies in the ocean) that can have severe impacts on our planet.
At the same time there is a rapid growth in the number of satellites orbiting the Earth (221 launched in 2015, around 5000 in total) with a significant fraction of these satellites dedicated to Earth Observation using a large variety of sensors working at different electromagnetic frequencies (optical, radar, infrared, etc.). Our ability to store, process and share efficiently the vast amounts of data that are produced (~Pb yearly) by the modelling and remote sensing communities is a pre-requisite for the good functioning of these often publicly funded large programmes.
In this one-day workshop our speakers will present on how the new tools developed in data sciences can be applied to questions relating to climate and the environment to help us address the great challenges that our society is facing in a rapidly changing planet. Our event will be structured around five keynote speakers highlighting five separate topics described below and followed by a panel dialogue between our experts and the audience on the topic of Data Sciences for the Climate and the Environment.
Director of Models and Data at the UK National Centre for Atmospheric Science, Professor of Weather and Climate Computing at the University of Reading, and the Director of the STFC Centre for Environmental Data Analysis (CEDA).
Jeremy joined the NERC-Met Office UKESM core group in 2014 as Scientific Systems Manager and is the Lead Computational Scientist for the UK Earth System Model (UKESM)
Director of the Institute for Mathematics Applied to Geosciences (IMAGe) at the US National Center for Atmospheric Research, and also a Senior Scientist in the Statistics and Data Sciences Section.
Climate scientist and deputy head of the Polar Oceans Team at the British Antarctic Survey. Emily also holds a number of positions at the University of Cambridge (fellow of Darwin College, fellow of the Cambridge Institute for Sustainability Leadership, associate fellow of the Centre for Science and Policy and member of the Faculty of Mathematics).
Leads the Data and Analytics Services team at the US National Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Lab
Principal Statistician at the NASA Jet Propulsion Laboratory, California Institute of Technology, working in the Multi-angle Imaging SpectroRadiometer (MISR) science team and the Atmospheric Infrared Sounder (AIRS) science development team.
This workshop is kindly supported by the Statistical and Applied Mathematical Sciences Institute (SAMSI) and The Alan-Turing Institute-Lloyd’s Register Foundation Programme on Data-Centric Engineering.