Highlight articles

This page features highlight articles from EGU's open access journals Geoscientific Model Development and Natural Hazards and Earth System Sciences. These articles of particular interest are selected by journal editors.

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All Geoscientific Model Development (GMD) Natural Hazards and Earth System Sciences (NHESS)

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Snow avalanche detection and mapping in multitemporal and multiorbital radar images from TerraSAR-X and Sentinel-1

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-1783-2020
• 2 July 2020

To assess snow avalanche mapping with radar satellites in Switzerland, we compare 2 m resolution TerraSAR-X images, 10 m resolution Sentinel-1 images, and optical 1.5 m resolution SPOT-6 images. We found that radar satellites provide a valuable option to map at least larger avalanches, though avalanches are mapped only partially. By combining multiple orbits and polarizations from S1, we achieved mapping results of quality almost comparable to single high-resolution TerraSAR-X images.

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Towards an objective assessment of climate multi-model ensembles – a casestudy: the Senegalo-Mauritanian upwelling region

• Geoscientific Model Development
• DOI 10.5194/gmd-13-2723-2020
• 30 June 2020

The most robust representation of climate is usually obtained by averaging a large number of simulations, thereby cancelling individual model errors. Here, we work towards an objective way of selecting the least biased models over a certain region, based on physical parameters. This statistical method based on a neural classifier and multi-correspondence analysis is illustrated here for the Senegalo-Mauritanian region, but it could potentially be developed for any other region or process.

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RainNet v1.0: a convolutional neural network for radar-based precipitation nowcasting

• Geoscientific Model Development
• DOI 10.5194/gmd-13-2631-2020
• 23 June 2020

In this study, we present RainNet, a deep convolutional neural network for radar-based precipitation nowcasting, which was trained to predict continuous precipitation intensities at a lead time of 5 min. RainNet significantly outperformed the benchmark models at all lead times up to 60 min. Yet, an undesirable property of RainNet predictions is the level of spatial smoothing. Obviously, RainNet learned an optimal level of smoothing to produce a nowcast at 5 min lead time.

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Induced seismicity risk analysis of the hydraulic stimulation of a geothermal well on Geldinganes, Iceland

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-1573-2020
• 16 June 2020

This study presents a first-of-its-kind pre-drilling probabilistic induced seismic risk analysis for the Geldinganes (Iceland) deep-hydraulic stimulation. The results of the assessment indicate that the individual risk within a radius of 2 km around the injection point is below the safety limits. However, the analysis is affected by a large variability due to the presence of pre-drilling deep uncertainties. This suggests the need for online risk updating during the stimulation.

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Present and future changes in winter climate indices relevant for access disruptions in Troms, northern Norway

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-1847-2020
• 9 June 2020

We have studied changes in winter weather known to trigger road closures and isolation of small seaside communities in northern Norway. We find that snow amounts and heavy snowfall events have increased in the past, while future projections for 2040–2100 show a decrease in snow-related indices. Events of heavy water supply and zero crossings are expected to increase. Our results imply fewer dry-snow-related access disruptions in the future, while wet-snow avalanches and slushflows may increase.

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Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-1421-2020
• 4 June 2020

Natural hazards have an increasing impact on transportation networks. In order to analyze it we developed Network-risk – an open toolbox for ArcGIS. The toolbox links input data such as network datasets (also OpenStreetMap – OSM – data), traffic values or segments which can be affected, determining the difficulty to reach an area and enabling evaluation of socioeconomic implications. By testing Network-risk for Bucharest we show areas difficult to reach by emergency units in earthquakes.

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Run-up, inundation, and sediment characteristics of the 22 December 2018 Sunda Strait tsunami, Indonesia

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-933-2020
• 21 April 2020

This article reports the results of a field survey carried out in the disaster area of the December 2018 Sunda Strait tsunami, Indonesia. It provides data covering run-up heights, inundations, tsunami directions, and sediment characteristics. The data can be used for the validation of hydrodynamic models, and they contribute to a better understanding of the Sunda Strait tsunami caused by the Anak Krakatau volcano. In addition, they are important for spatial planning and mitigation efforts.

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Modelling global tropical cyclone wind footprints

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-567-2020
• 10 March 2020

Assessing tropical cyclone (TC) wind risk is challenging due to a lack of historical TC wind data. This paper presents a novel approach to simulating landfalling TC winds anywhere on Earth. It captures local features such as high winds over coastal hills and lulls over rough terrain. A dataset of over 700 global historical wind footprints has been generated to provide new views of historical events. This dataset can be used to advance our understanding of overland TC wind risk.

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Measuring compound flood potential from river discharge and storm surge extremes at the global scale

• Natural Hazards and Earth System Sciences
• DOI 10.5194/nhess-20-489-2020
• 3 March 2020

When a high river discharge coincides with a high storm surge level, this can exarcebate flood level, depth, and duration, resulting in a so-called compound flood event. These events are not currently included in global flood models. In this research, we analyse the timing and correlation between modelled discharge and storm surge level time series in deltas and estuaries. Our results provide a first indication of regions along the global coastline with a high compound flooding potential.

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TRAPPIST-1 Habitable Atmosphere Intercomparison (THAI):motivations and protocol version 1.0

• Geoscientific Model Development
• DOI 10.5194/gmd-13-707-2020
• 3 March 2020

Atmospheric characterization of rocky exoplanets orbiting within the habitable zone of nearby M dwarf stars is around the corner with the James Webb Space Telescope (JWST), expected to be launch in 2021.
Global climate models (GCMs) are powerful tools to model exoplanet atmospheres and to predict their habitability. However, intrinsic differences between the models can lead to various predictions. This paper presents an experiment protocol to evaluate these differences.

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