Deep in the interior of the Greenland ice sheet, ice flow is speeding up — but not due to recent changes in climate.
As we warm our planet, oceans expand, ice on land melts, and sea levels rise. On century time scales, we find that the sea level response to warming can be characterized by a single metric: the transient sea level sensitivity. Historical sea level exhibits substantially higher sensitivity than model-based estimates of future climates in authoritative climate assessments. Implying recent projections could well underestimate the likely sea level rise by the end of this century.
We present an approach to normalize hurricane damage, where damage is framed in terms of an equivalent area of total destruction. This has some advantages over customary normalization schemes, and we demonstrate that our record has reduced variance and correlates marginally better with wind speeds and pressure. That is, it allows us to better address climatic trends. We find that hurricanes are indeed becoming more damaging. The frequency of the very most damaging hurricanes has increased 3 times per century.
The planet is warming, and sea levels are rising as oceans expand and ice on land melts. The warmer the Earth gets, the faster the seas will rise. Projecting future sea level rise (SLR) using numerical models has proved extremely challenging and, as a consequence, estimates carry a large uncertainty. How good are the models of ocean expansion and mass loss from glaciers and ice sheets? We tackle this question by comparing how the models react to future warming with how sea level reacted in the past. The models for glaciers, Greenland, and the oceans are compatible with observations. For the largest ice mass on the planet, the Antarctic Ice Sheet, the models do not agree with the observations. As a result, projections of global SLR may be an underestimate.
The Bristol CMIP6 Data Hackathon formed part of the Met Office Climate Data Challenge Hackathon series during 2021, bringing together around 100 UK early career researchers from a wide range of environmental disciplines. The purpose was to interrogate the under-utilised but currently most advanced climate model inter-comparison project datasets to develop new research ideas, create new networks and outreach opportunities in the lead up to COP26. Experts in different science fields, supported by a core team of scientists and data specialists at Bristol, had the unique opportunity to explore together interdisciplinary environmental topics summarised in this article.
FEniCS is a really nice tool for finite element modelling in python. It is difficult to install FEniCS on windows. The official instructions use a docker image. which I think is a bit heavy handed. I therefore installed it in a WSL-Ubuntu (Windows Subsystem for Linux). My experience with that has been friction free, so here are some very brief notes of what I did. In windows Enable WSL2 and install a Ubuntu image.
The orientation of ice-crystal grains in glacier ice locally co-evolve with and can enhance the flow of ice. Inferring the grain orientation structure inside glaciers and ice-sheets is therefore essential for improving the accuracy and realism of ice-flow models, with implications for reducing the uncertainty of future sea-level rise projections. In this work, we introduce a new radio-wave model and use it to investigate the extent to which radar surveys over glaciers and ice sheets can reveal the orientation information necessary to improve such ice-flow models. We show that conventional polarimetric radar surveys, where transmitted radio waves are typically incident perpendicular to the surface, might be poorly suited for the task; a configuration that is effectively blind to a specific but important component of the grain orientation structure. We find, however, that radio waves transmitted at an oblique angle to the surface might instead overcome this crucial limitation and allow the sought-after grain orientation information to be inferred.