• Geoscientific Model Development
• DOI 10.5194/gmd-15-5127-2022
• 23 September 2022

Firedrake is a state-of-the-art system that automatically generates highly optimised code for simulating finite-element (FE) problems in geophysical fluid dynamics. It creates a separation of concerns between employing the FE method and implementing it. Here, we demonstrate the applicability and benefits of Firedrake for simulating geodynamical flows, with a focus on the slow creeping motion of Earth’s mantle over geological timescales, which is ultimately the engine driving our dynamic Earth.

Read more

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-22-2201-2022
• 19 September 2022

Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.

Read more

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-22-2031-2022
• 12 September 2022

A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.

Read more

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-22-1969-2022
• 26 August 2022

The worldwide challenge of the present as well as the future is to navigate the global community to a sustainable and secure future. Humanity is increasingly facing multiple risks under more challenging conditions. The continuation of climate change and the ever more frequent occurrence of extreme, multi-hazard, and cascading events are interacting with increasingly complex and interconnected societies.

Read more

• Geoscientific Model Development
• DOI 10.5194/gmd-15-3831-2022
• 8 August 2022

In this study, we present a novel formulation to build a dynamical combination of models, the so-called supermodel, which needs to be trained based on data. Previously, we assumed complete and noise-free observations. Here, we move towards a realistic scenario and develop adaptations to the training methods in order to cope with sparse and noisy observations. The results are very promising and shed light on how to apply the method with state of the art general circulation models.

Read more

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-22-1577-2022
• 29 July 2022

The impact of extreme events is increasing with global warming. Based on future scenario data and an improved quantitative assessment model of natural-disaster risk, this study analyses the spatial and temporal patterns of floods in China at 1.5 °C and 2 °C of global warming, quantitatively assesses the socioeconomic risks posed by floods, and determines the integrated risk levels. Global warming of 1.5 °C can effectively reduce the population affected and the economic risks of floods.

Read more

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-22-617-2022
• 18 May 2022

Volcanic eruptions can produce tsunamis through multiple mechanisms. We present validation cases for a numerical method used in simulating waves caused by submarine explosions: a laboratory flume experiment and waves generated by explosions at field scale. We then demonstrate the use of the scheme for simulating analogous volcanic eruptions, illustrating the resulting wavefield. We show that this scheme models such dispersive sources more proficiently than standard tsunami models.

Read more

• Geoscientific Model Development
• DOI 10.5194/gmd-15-1595-2022
• 13 May 2022

It can be challenging to understand why Earth system models (ESMs) produce specific results because one can arrive at the same result simply by changing the values of the parameters. In our paper, we demonstrate that it is possible to use machine learning to figure out how and why particular components of an ESM (such as biology or ocean circulations) affect the output. This work could be applied to observations to improve the accuracy of the formulations used in ESMs.

Read more

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-22-461-2022
• 2 May 2022

Local communities in northern Malawi have well-developed knowledge of the conditions leading to flash floods, spatially and temporally. Scientific analysis of catchment geomorphology and global reanalysis datasets corroborates this local knowledge, underlining the potential of these large-scale scientific datasets. Combining local knowledge with contemporary scientific datasets provides a common understanding of flash flood events, contributing to a more people-centred warning to flash floods.

Read more

• Geoscientific Model Development
• DOI 10.5194/gmd-15-617-2022
• 15 April 2022

Here we present an improved model of the Antarctic continental shelf ocean and demonstrate that it is capable of reproducing present-day conditions. The improvements are fundamental and regard the inclusion of tides and ocean eddies. We conclude that the model is well suited to gain new insights into processes that are important for Antarctic ice sheet retreat and global ocean changes. The model will ultimately help to improve projections of sea level rise and climate change.

Read more