45 research outputs found
Rediscover Climate Change during Global Warming Slowdown via Wasserstein Stability Analysis
Climate change is one of the key topics in climate science. However, previous
research has predominantly concentrated on changes in mean values, and few
research examines changes in Probability Distribution Function (PDF). In this
study, a novel method called Wasserstein Stability Analysis (WSA) is developed
to identify PDF changes, especially the extreme event shift and non-linear
physical value constraint variation in climate change. WSA is applied to
21st-century warming slowdown period and is compared with traditional
mean-value trend analysis. The result indicates that despite no significant
trend, the central-eastern Pacific experienced a decline in hot extremes and an
increase in cold extremes, indicating a La Nina-like temperature shift. Further
analysis at two Arctic locations suggests sea ice severely restricts the hot
extremes of surface air temperature. This impact is diminishing as sea ice
melts. Overall, based on detecting PDF changes, WSA is a useful method for
re-discovering climate change.Comment: 12 pages, 4 figures, and 1 Algorith
Quantifying and analyzing rock trait distributions of rocky fault scarps using deep learning approach
We apply a deep learning model to segment and identify rock characteristics
based on a Structure-from-Motion orthomap and digital elevation model of a
rocky fault scarp in the Volcanic Tablelands, eastern California. By
post-processing the deep learning results, we build a semantic rock map and
analyze rock trait distributions. The resulting semantic map contains nearly
230,000 rocks with effective diameters ranging from 2 cm to 250 cm. Rock trait
distributions provide a new perspective on rocky fault scarp development and
extend past research on scarp geometry including slope, height, and length.
Heatmaps indicate rock size spatial distributions on the fault scarp and
surrounding topographic flats. Median grain size changes perpendicular to the
fault scarp trace with the largest rocks exposed on and downslope from the
scarp footwall. Correlation analyses of the segmented fault scarp illustrate
the relationship between rock trait statistics and fault scarp geomorphology.
Local fault scarp height correlates with median grain size (R2 of 0.6), the
mean grain size of the largest rocks (R2 of 0.76), and the ratio of the number
of small to large rocks (R2 of 0.40). The positive correlation (R2 of 0.81)
between local fault scarp height and standard deviation of grain size suggests
that rocks on a higher fault scarp are less well sorted. The correlation
analysis between fault scarp height and rock orientation statistics supports a
particle transportation model in which locally higher fault scarps have
relatively more rocks with long axes parallel to fault scarp trace because
rocks have a larger distance to roll and orient the long axes. Our work
demonstrates a data-driven approach to geomorphology based on rock trait
distributions, promising a greater understanding of fault scarp formation, as
well as many other applications for which granulometry is an indicator of
process
Virtual Shake Robot: Simulating Dynamics of Precariously Balanced Rocks for Overturning and Large-displacement Processes
 Understanding the dynamics of precariously balanced rocks (PBRs) is important for seismic hazard analysis and rockfall prediction. Utilizing a physics engine and robotic tools, we develop a virtual shake robot (VSR) to simulate the dynamics of PBRs during overturning and large-displacement processes. We present the background of physics engines and technical details of the VSR, including software architecture, mechanical structure, control system, and implementation procedures. Validation experiments show the median fragility contour from VSR simulation is within the 95% prediction intervals from previous physical experiments, when PGV/PGA is greater than 0.08 s. Using a physical mini shake robot, we validate the qualitative consistency of fragility anisotropy between the VSR and physical experiments. By overturning cuboids on flat terrain, the VSR reveals the relationship between fragility and geometric dimensions (e.g., aspect and scaling ratios). The ground motion orientation and lateral pedestal support affect PBR fragility. Large-displacement experiments estimate rock trajectories for different ground motions, which is useful for understanding the fate of toppled PBRs. Ground motions positively correlate with large displacement statistics such as mean trajectory length, mean largest velocity, and mean terminal distance. The overturning and large displacement processes of PBRs provide complementary methods of ground motion estimation
Recommended from our members
Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response
Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs
Understanding and exploring the diversity of soil microorganisms in tea (Camellia sinensis) gardens: toward sustainable tea production
Leaves of Camellia sinensis plants are used to produce tea, one of the most consumed beverages worldwide, containing a wide variety of bioactive compounds that help to promote human health. Tea cultivation is economically important, and its sustainable production can have significant consequences in providing agricultural opportunities and lowering extreme poverty. Soil parameters are well known to affect the quality of the resultant leaves and consequently, the understanding of the diversity and functions of soil microorganisms in tea gardens will provide insight to harnessing soil microbial communities to improve tea yield and quality. Current analyses indicate that tea garden soils possess a rich composition of diverse microorganisms (bacteria and fungi) of which the bacterial Proteobacteria, Actinobacteria, Acidobacteria, Firmicutes and Chloroflexi and fungal Ascomycota, Basidiomycota, Glomeromycota are the prominent groups. When optimized, these microbes’ function in keeping garden soil ecosystems balanced by acting on nutrient cycling processes, biofertilizers, biocontrol of pests and pathogens, and bioremediation of persistent organic chemicals. Here, we summarize research on the activities of (tea garden) soil microorganisms as biofertilizers, biological control agents and as bioremediators to improve soil health and consequently, tea yield and quality, focusing mainly on bacterial and fungal members. Recent advances in molecular techniques that characterize the diverse microorganisms in tea gardens are examined. In terms of viruses there is a paucity of information regarding any beneficial functions of soil viruses in tea gardens, although in some instances insect pathogenic viruses have been used to control tea pests. The potential of soil microorganisms is reported here, as well as recent techniques used to study microbial diversity and their genetic manipulation, aimed at improving the yield and quality of tea plants for sustainable production
Virtual Shake Robot Software
<p>Understanding the dynamics of precariously balanced rocks (PBRs) is important for seismic hazard analysis and rockfall prediction. Using a physics engine and robotic tools, we develop a virtual shake robot (VSR) to simulate the dynamics of PBRs for overturning and large-displacement processes. We present the background of physics engines and technical details of the VSR, including software architecture, mechanical structure, control system, and implementation procedures. Validation experiments show the median fragility contour from VSR simulation is within the 95% prediction intervals from previous physical experiments, when PGV/PGA is greater than 0.08 g. Using a physical mini shake robot, we validate the qualitative consistency of fragility anisotropy between the VSR and physical experiments. By overturning cuboids on flat terrain, the VSR reveals the relationship between fragility and geometric dimensions (e.g., height-width and scaling ratios). The ground motion orientation and lateral pedestal support affect PBR fragility. Large-displacement experiments estimate rock trajectories for different ground motions, which is useful for understanding the fate of toppled PBRs. Ground motions positively correlate with large displacement statistics such as mean trajectory length, mean largest velocity, and mean terminal distance. The overturning and large displacement processes of PBRs provide complementary methods of ground motion estimation. VSR is available on Github: https://github.com/DREAMS-lab/pbr_gazebo</p>