Obtaining realistic land-surface states for initial and boundary conditions is important for the numerical weather prediction of many atmospheric phenomena. Here we investigate model sensitivity to land use and snow cover for a persistent wintertime cold-air pool in northern Utah during 1–8 January 2011. A Weather Research and Forecast model simulation using the 1993 United States Geological Survey land-use and North American Mesoscale model reanalysis snow-cover datasets is compared to an improved configuration using the modified 2011 National Land Cover Database and a more realistic representation of snow cover. The improved surface specification results in an increase (decrease) in urban land cover (Great Salt Lake surface area), and changes to the snow-cover initialization, depth, extent, and albedo. The results obtained from the model simulations are compared to observations collected during the Persistent Cold-Air Pool Study. The changes in land use and snow cover and the resulting impacts on the surface albedo and surface heat fluxes contributed to near-surface air temperature increases of 1–\(2\,^{\circ }\hbox {C}\) in urban areas and decreases of 2–\(4\,^{\circ }\hbox {C}\) in areas surrounding the Great Salt Lake. Although wind speeds in the boundary layer were overestimated in both simulations, shallow thermally-driven and terrain-forced flows were generally lessened in intensity and breadth in response to the decreased areal extent of the Great Salt Lake and increases in the urban footprint. 相似文献
How societies organize themselves to respond to cascading impacts exacerbated by climate change will help define the future of disaster planning, mitigation, response, and recovery. Current emergency management risk analyses focus on identifying a broad array of threats and hazards that may affect an area. However, there is limited attention and understanding of the totality of hazard impacts, the relationship of consequences across disasters, and the dangers of not addressing critical capabilities necessary to rapidly managing consequences—including the potential to create new incidents within incidents. Through a focused review of the related literature and guiding policy documents, this study aims to provide a cascading consequence-based framework that can support emergency managers in the analysis of their jurisdictional risks, development of emergency operations plans, and decision-making. Results include the identification of an alternative framework to identify cascading networks, the creation of a supplementary model for downstream risk assessment, and refined Threat and Hazard Identification and Risk Analysis (THIRA) outputs for improved grant allocation. The proposed framework has the potential to help organizations factor both conspicuous and downstream consequences into their Emergency Operations Plans in the planning and mitigations phases. This proposed refinement, which looks deeper into the progression of a disaster, has both national and international implications.
The Afar Depression offers a rare opportunity to study the geodynamic evolution of a rift system from continental rifting
to sea floor spreading. This study presents geochemical data for crustal and mantle xenoliths and their alkaline host basalts
from the region. The basalts have enriched REE patterns, OIB-like trace element characteristics, and a limited range in isotopic
composition (87Sr/86Sr = 0.70336–0.70356, εNd = +6.6 to +7.0, and εHf = +10.0 to +10.7). In terms of trace elements and Sr–Nd isotopes, they are similar to basalts from the Hanish and Zubair
islands in the southern Red Sea and are thus interpreted to be melts from the Afar mantle. The gabbroic crustal xenoliths
vary widely in isotope composition (87Sr/86Sr = 0.70437–0.70791, εNd = −8.1 to +2.5, and εHf = −10.5 to +4.9), and their trace element characteristics match those of Neoproterozoic rocks from the Arabian–Nubian Shield
and modern arc rocks, suggesting that the lower crust beneath the Afar Depression contains Neoproterozoic mafic igneous rocks.
Ultramafic mantle xenoliths from Assab contain primary assemblages of fresh ol + opx + cpx + sp ± pl, with no alteration or
hydrous minerals. They equilibrated at 870–1,040°C and follow a steep geothermal gradient consistent with the tectonic environment
of the Afar Depression. The systematic variations in major and trace elements among the Assab mantle xenoliths together with
their isotopic compositions suggest that these rocks are not mantle residues but rather series of layered cumulate sills that
crystallized from a relatively enriched picritic melt related to the Afar plume that was emplaced before the eruption of the
host basalts. 相似文献
Cracks are accounted as the most destructive discontinuity in rock, soil, and concrete. Enhancing our knowledge from their properties such as crack distribution, density, and/or aspect ratio is crucial in geo-systems. The most well-known mechanical parameter for such an evaluation is wave velocity through which one can qualitatively or quantitatively characterize the porous media. In small scales, such information is obtained using the ultrasonic pulse velocity(UPV) technique as a non-destructive test. In large-scale geo-systems, however, it is inverted from seismic data. In this paper, we take advantage of the recent advancements in machine learning(ML) for analyzing wave signals and predict rock properties such as crack density(CD) – the number of cracks per unit volume. To this end, we designed numerical models with different CDs and, using the rotated staggered finite-difference grid(RSG) technique, simulated wave propagation. Two ML networks, namely Convolutional Neural Networks(CNN) and Long Short-Term Memory(LSTM), are then used to predict CD values. Results show that, by selecting an optimum value for wavelength to crack length ratio, the accuracy of predictions of test data can reach R2> 96% with mean square error(MSE) < 25e-4(normalized values). Overall, we found that:(i) performance of both CNN and LSTM is highly promising,(ii) accuracy of the transmitted signals is slightly higher than the reflected signals,(iii) accuracy of 2D signals is marginally higher than 1D signals,(iv)accuracy of horizontal and vertical component signals are comparable,(v) accuracy of coda signals is less when the whole signals are used. Our results, thus, reveal that the ML methods can provide rapid solutions and estimations for crack density, without the necessity of further modeling. 相似文献
Human-induced afforestation has been one of the main policies for environmental management of farmland abandonment in Mediterranean areas. Over the last decades, several studies have reviewed the impact of afforestation activities on geomorphological and hydrological responses and soil properties, although few studies have evaluated the effects on water table dynamics. In parallel to human-induced afforestation activities, natural revegetation occurred in abandoned fields and in fields where the intensity of human activity declined, driving the expansion of shrubs. This research addresses the spatial and temporal variability of water table dynamics in a small afforested sub-catchment located in the Central Spanish Pyrenees. Differences between afforestation (Pinus nigra and Pinus sylvestris) and natural plant colonization (shrubs, mainly Genista scorpius, Buxus sempervirens, and Juniperus communis) and early abandoned meadows (G. scorpius), are analysed in terms of runoff generation and seasonal water table depth dynamics. Precipitation, runoff and water table datasets recorded for the 2014–2019 period are used. Results show a high temporal and spatial variability with large fluctuations in discharge and water table. Groundwater dynamics varied markedly over the year, identifying a wet and dry period with different responses suggesting different runoff generation processes (Hortonian flow during dry and wet periods, and saturation excess runoff during wet conditions). Furthermore, important differences are noted among the various land cover types: (i) in the natural revegetation area (shrubland and meadows) a marked seasonal cycle was observed with short saturation periods during winter and spring; and (ii) in the afforestation areas, the water table dynamics showed a seasonal cycle with a high variability, with fast responses and rapid oscillations. Likewise, the relationship between the depth of water table and hydrological variables was not straightforward, suggesting complex hydrological behaviour. 相似文献