Highlight articles

A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?

The ocean plays a vital role in mitigating climate change by taking up atmospheric carbon dioxide (CO₂). Historically sparse ship-based measurements of surface ocean CO₂make direct estimates of CO₂exchange changes unreliable. We introduce a machine-learning ensemble approach to fill these observational gaps. Our method performs incrementally better relative to past methods, leading to our hypothesis that we are perhaps reaching the limitation of machine-learning algorithms’ capability.

Natural Hazards and Earth System Sciences

First reported case of thunderstorm asthma in Israel

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-19-2715-2019
10 December 2019

During severe thunderstorms, cold outflows can eject pollen and dust particles from the surface, releasing allergens and causingthunderstorm asthmaepidemics in sensitive populations. We report the first case in Israel that occurred on 25 October 2015. The emergency room presentation records from three hospitals in central Israel showed a clear increase in patients with respiratory complaints immediately after the passage of a massive super-cell thunderstorm in the area.

The first version of the Pan-European Indoor Radon Map

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-19-2451-2019
15 November 2019

The first version of the Pan-European Indoor Radon Map is presented in this article. The map has been developed using summary statistics estimated from 1.2 million samples. It represents an average radon concentration per 10 km x 10 km grid cell under the assumption that there are dwellings in the grid cell. It is a major contribution to the understanding of the exposure to ionizing radiation of Europeans and a first step towards a European radon exposure and, in the future, radon dose map.

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description

Our paper describes the Ecosystem Demography model. This computer program calculates how plants and ground exchange heat, water, and carbon with the air, and how plants grow, reproduce and die in different climates. Most models simplify forests to an average big tree. We consider that tall, deep-rooted trees get more light and water than small plants, and that some plants can with shade and drought. This diversity helps us to better explain how plants live and interact with the atmosphere.

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America

The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.

Ensemble models from machine learning: an example of wave runup and coastal dune erosion

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-19-2295-2019
29 October 2019

Wave runup is important for characterizing coastal vulnerability to wave action; however, it is complex and uncertain to predict. We use machine learning with a high-resolution dataset of wave runup to develop an accurate runup predictor that includes prediction uncertainty. We show how uncertainty in wave runup predictions can be used practically in a model of dune erosion to make ensemble predictions that provide more information and greater predictive skill than a single deterministic model.

Geologic and geomorphic controls on rockfall hazard: how well do past rockfalls predict future distributions?

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-19-2249-2019
11 October 2019

Here we evaluate geologic, geomorphic, and anthropogenic controls on rockfall hazard and highlight the complexity of interpreting future rockfall hazard based on former boulder distributions. To evaluate how past rockfall deposits relate to contemporary rockfall hazard, we mapped then compared the locations, physical characteristics, and lithologies of rockfall boulders deposited during the 2010–2011 Canterbury earthquake sequence (n= 185) with their prehistoric counterparts (n= 1093).

Understanding the spatiotemporal development of human settlement in hurricane-prone areas on the US Atlantic and Gulf coasts using nighttime remote sensing

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-19-2141-2019
1 October 2019

This study examined the spatiotemporal dynamics of nighttime satellite-derived human settlement in response to different levels of hurricane proneness in a period from 1992 to 2013. It confirms theSnow Belt-to-Sun BeltUS population shift trend. The results also suggest that hurricane-exposed human settlement has grown in extent and area, as more hurricane exposure has experienced a larger increase rate in settlement intensity.

Improved methodologies for Earth system modelling of atmospheric soluble iron and observation comparisons using the Mechanism of Intermediate complexity for Modelling Iron (MIMI v1.0)

MIMI v1.0 was designed for use within Earth system models to simulate the 3-D emission, atmospheric processing, and deposition of iron and its soluble fraction. Understanding the iron cycle is important due to its role as an essential micronutrient for ocean phytoplankton; its supply limits primary productivity in many of the world’s oceans. Human activity has perturbed the iron cycle, and MIMI is capable of diagnosing many of these impacts; hence, it is important for future climate studies.

Load-resistance analysis: an alternative approach to tsunami damage assessment applied to the 2011 Great East Japan tsunami

Natural Hazards and Earth System Sciences
DOI 10.5194/nhess-19-1807-2019
20 August 2019

It is known that fragility functions reflect localities (building design standards and topography) and flow velocity is more important, as damage might occur before flow depth reaches its maximum value. This research demonstrates that it is possible to accurately predict building damage by considering related forces with high accuracy, including resistant force, based on building design standards. This method will be useful for damage assessment in areas that have no experience of tsunamis.

NH Natural Hazards Highlight articles

Highlight articles

A comparative assessment of the uncertainties of global surface ocean CO2 estimates using a machine-learning ensemble (CSIR-ML6 version 2019a) – have we hit the wall?

First reported case of thunderstorm asthma in Israel

The first version of the Pan-European Indoor Radon Map

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America

Ensemble models from machine learning: an example of wave runup and coastal dune erosion

Geologic and geomorphic controls on rockfall hazard: how well do past rockfalls predict future distributions?

Understanding the spatiotemporal development of human settlement in hurricane-prone areas on the US Atlantic and Gulf coasts using nighttime remote sensing

Improved methodologies for Earth system modelling of atmospheric soluble iron and observation comparisons using the Mechanism of Intermediate complexity for Modelling Iron (MIMI v1.0)

Load-resistance analysis: an alternative approach to tsunami damage assessment applied to the 2011 Great East Japan tsunami

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