The EGU General Assembly最新文献

Through advanced statistical investigation and evaluation of solar wind plasma and magnetic field data, we investigate the statistical relation between the magnetic field B_z component, measured at L1, and Earth’s thermospheric neutral density. We will present preliminary results of the time series analyzes using in-situ plasma and magnetic field measurements from different spacecraft in near Earth space (e.g., ACE, Wind, DSCOVR) and relate those to derived thermospheric densities from various satellites (e.g., GRACE, CHAMP). The long and short term variations and dependencies in the solar wind data are related to variations in the neutral density of the thermosphere and geomagnetic indices. Special focus is put on the specific signatures that stem from coronal mass ejections and stream or corotating interaction regions.  The results are used to develop a novel short-term forecasting model called SODA (Satellite Orbit DecAy). This is a joint study between TU Graz and University of Graz funded by the FFG Austria (project “SWEETS”).

Within the project SWEETS (funded by the FFG Austria) it is intended to develop a forecasting model, to predict the expected impact of solar events, like coronal mass ejections (CMEs), on satellites at different altitudes between 300-800 km. For the realization, scientific data, such as kinematic orbit information and accelerometer measurements, from a wide variety of satellites are incorporated. Based on the evaluation of the impact of several hundred solar events on the thermosphere the forecasting will be realized through a joint analysis and evaluation of solar wind plasma and magnetic field data observed at the Lagrange point L1.
In this contribution we show first preliminary results of thermospheric densities estimates based on kinematic orbit information for different satellite missions (e.g., TerraSAR-X, TanDEM-X, Swarm A-C, GRACE, GRACE-FO, CHAMP). To validate the outcome, we compare the results with state-of-the-art thermospheric models as well as with densities estimated from accelerometer measurements if available. Finally, for some specific CME events we will perform a comparison between the post-processed density estimates and results from our preliminary forecasting tool.

Blasting operations in quarries are accompanied by ground vibrations which can endanger buildings nearby. A production blast is made of several holes with a small distance to each other, which are blasted with a time delay, for the purpose of production and to reduce the ground vibrations. These production blasts produce a specific radiation pattern. It would be favorable to focus the ground vibrations to a less sensitive direction or area. We want to be able to predict the ground vibrations for a realistic inhomogeneous case at an area around the iron ore mine at mount Erzberg in Austria. Therefore a numerical forward modeling on a 3D model of the iron ore mine and its surrounding area was performed with a 3D elastic code with topography. The 3D model itself is the result of a tomographic travel time inversion. One problem is that the spectral response of a single blast is unknown and therefore we had to find a transfer function which transfers the numeric spectral response to the observed spectral response. After applying the transfer function the amplitude spectra of the numerical solution show a good match to the amplitude spectra of the observed production blasts. In this study, we investigate, if a reduction of ground vibrations can be achieved by blasting simultaneously two arrays with optimized time delays. To achieve that optimized time delays we developed a global search algorithm, based on Markov chain Monte Carlo method which finds potential blast configurations, with minimum impact to critical locations near the quarry. This study is part of the EU-funded project SLIM (Sustainable Low Impact Mining, www.slim-project.eu).

High mountain environments are among the most sensitive on Earth. Due to anthropogenic disturbances and climate change, rates of regolith mobilization due to for example landsliding have been accelerating recently. As a result, soils degrade, geohazards occur and flash floods have negative consequences in downstream areas. The restoration of soils in high mountain environments and an improved understanding of nature-based solutions to land degradation is, therefore, urgent. As finding the origin of erosion sources is a first step to improve mitigation strategies and guide the implementation of effective soil restoration measures, we discuss sediment source fingerprinting research in the context of soil restoration in high mountain environments. A literature review was done based on articles that apply sediment source fingerprinting in high mountain environments and additional articles on land use-based markers and soil restoration were used to develop an outlook for future research. The application of sediment provenance studies in high mountains environments has been limited so far. While some studies yield a rough distinction between sediment sources based on environmental radionuclides or elemental geochemistry, they cannot reflect multiple semi-natural vegetation types which are relevant source types that should be discriminated in high mountain environments. Therefore, we explore emerging techniques such as eDNA tracing that could potentially refine the information on the provenance of sediment based on land use and cover sources. Then, we will address the challenging hydro-geomorphic environment of high mountains and the implications for designing properly a sediment tracing study in such a context. We will conclude by presenting an outlook to guide future applications of sediment source fingerprinting in high mountain environments, where geohazards are imminent and soil restoration is urgent.

Key words: alpine, environmental DNA, erosion, landslide, vegetation

Colombia is an equatorial country located in the northwestern corner of South America with characteristic and complex climatic and geologic settings, which contribute to a great diversity of landforms in the Colombian Andes. 65% of the Colombian population is concentrated in this mountainous terrain, where landslides and torrential flows are common. These natural hazards led to several tragic events over time. Their occurrence is favored by a very dynamic landscape made up of weak and highly weathered materials and affected by tectonic stress. In this study, we aim to gain a better understanding of morphometric control on the occurrence of landslides and torrential flows through process geomorphology and information derived from Digital Elevation Models (DEMs). Several morphometric indices related to drainage network, basin geometry, drainage texture, relief characteristics, asymmetry factor and others were calculated over 168 drainage basins in the northern Colombian Andes. We used quantitative geomorphology to find patterns of anomalies associated with landscape evolution and the occurrence of landslides and torrential flows. Understanding morphodynamics from morphogenesis is important to assess landslide and torrential flow hazard conditions in relation to landscape characteristics and evolution, to support hazard assessment, and consequently to reduce human and economic losses.
Keywords: Landslide, torrential flow, morphometric indices, mountainous terrains.

The wintertime Arctic is influenced by air pollution transported from mid-latitudes, leading to formation of Arctic Haze, as well as local emissions such as combustion for heating and power production in very cold winter conditions. This contributes to severe air pollution episodes, with enhanced aerosol concentrations, inter-dispersed with cleaner periods. However, the formation of secondary aerosol particles (sulphate, organics, nitrate) in cold/dark wintertime Arctic conditions, which could contribute to these pollution episodes, is poorly understood.

In this study, which contributes to the Air Pollution in the Arctic: Climate, Environment and Societies - Alaskan Layered Pollution and Arctic Chemical Analysis (PACES-ALPACA) initiative, the Weather Research Forecasting Model with chemistry (WRF-Chem) is used to investigate wintertime pollution over central Alaska focusing on the Fairbanks region, during the pre-ALPACA campaign in winter 2019-2020. Fairbanks is the most polluted city in the United States during wintertime, due to high local emissions and the occurrence of strong surface temperature inversions trapping pollutants near the surface.

Firstly, different WRF meteorological and surface schemes were tested over Alaska with a particular focus on improving simulations of the wintertime boundary layer structure including temperature inversions. An optimal WRF set-up, with increased vertical resolution below 2km, was selected based on evaluation against available data.

Secondly, a quasi-hemispheric WRF-Chem simulation, using the improved WRF setup, was used to assess large-scale synoptic conditions and to evaluate background aerosols originating from remote anthropogenic and natural sources affecting central Alaska during the campaign. The model was run with Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants (ECLIPSE) v6b anthropogenic emissions and improved sea-spray aerosol emissions. Discrepancies in modelled aerosols compared available data are being investigated (e.g. missing dark formation mechanisms, treatment of removal processes).

Thirdly, fine resolution simulations, using high resolution emissions (e.g. 2019 CAMS inventory), including local point sources, over the Fairbanks region, were used to investigate chemical and dynamical processes influencing aerosols under different meteorological conditions observed during the field campaign including a cold stable episode and a period with possible mixing of air masses from aloft. The model was evaluated against available aerosol, oxidant (ozone) and aerosol precursor data from surface monitoring sites and collected during the pre-campaign, including vertical profile data collected in the lowest 20m. The sensitivity of modelled aerosols to meteorological factors, such as relative humidity, temperature gradients and vertical mixing under winter conditions are investigated.