 ECMWF’s strategic goal is to improve its global prediction through an Earth system approach. Recent advances have included enhanced dynamic coupling between the ocean, sea-ice and the atmosphere

The cumulative effects of overheating are the most common cause of failure for these units. ‘Our analysis indicated that, for the LPT we selected, the expected changes in the occurrence of the damaging heat waves from (unimpeded) human-induced climate change increased the underlying threat of (incremental) damage by a factor of four by the middle of this century. If the world did everything it could to avoid the human-induced warming, we would still see an increase of a factor of two,’ noted Schlosser. There are a number of caveats to this

study, according to Schlosser. First, the pilot only investigated these effects on one LPT but there are thousands of such systems deployed across the US power grid. ‘We also need to understand better how an incremental damaging heat wave or event impacts the cumulative risk of a catastrophic or premature failure of the LPT,’ Schlosser added. This would allow more proactive action

to be taken to upgrade and replace such systems. ‘We are actively pursuing collaborations and research support to continue our research endeavours along these lines,’ Schlosser concluded.

 To obtain high-quality labelled images for ClimateNet from the climate science community, Berkeley Lab researchers have modified the ‘Label-Me’ tool developed at MIT and created a web interface called ClimateContours

changes in our climate system. Adam Schlosser, a senior research scientist at the Center for Global Change Science and deputy director of the MIT Joint Program on Science and Policy of Global Change, explained: ‘The challenge is that models of the climate system are unable to resolve the details of many of the extreme events that we consider a threat. They typically occur at very ‘local’ scales (i.e. town, city, county). We bridge this gap by taking advantage of ‘tell-tale’ signs in a number of characteristics in the atmosphere at the larger spatial scales – and we use observations and machine-learning methods to identify what is the ‘recipe’ of these conditions that have to come together to cause the event.’ Schlosser added: ‘We then apply

these associations to the climate models’ | @scwmagazine

“Data assimilation is one of the big challenges associated with a large initiative at NSSL called Warn-on-Forecast”

simulations to see how often they occur now, and how that will change going into the future. We then associate these changes in the occurrence of the large- scale ingredients (again – based on observational evidence) to the risk of change in the extreme event occurrence.’ The team recently conducted a pilot

study to investigate the potential impact of extreme heat events on large power transformers (LPTs) in the Northeast US.

Longer ranges When we move to longer-term forecasts, global weather prediction models are required, such as the Integrated Forecasting System (IFS) from the European Centre for Medium-range Weather Forecasts (ECMWF), which produces analyses and forecasts in the mid-term. Peter Bauer, deputy director of research at the ECMWF, said: ‘Any forecast beyond a few days requires global simulations, because all processes are interconnected. Short-range forecasting systems can be limited to regions and draw their boundary conditions from systems like ours.’ ‘They then use km-scale models

to resolve details of the orography and coastlines. Ideally, longer-range predictions are also run at high resolution, because small-scale processes affect large-scale phenomena and vice versa. However, due to computing limitations, such predictions are usually run at

April/May 2019 Scientific Computing World 25


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