Melt inclusion analysis used to constrain and compare parental melt compositions of the nakhlite and chassignite martian meteorites.

In central Europe, many geo-energy reservoirs have revealed to be hosted in transverse isotropic crystalline rock, where the rock’s mechanical and hydraulic transport properties are poorly constrained. Here, we performed triaxial experiments on Cresciano Gneiss samples under stress (25-40 MPa) and fluid pressure (5 MPa) conditions. We tested 5 different foliation orientations towards the major principal stress (0, 30, 45, 60, 90). During deformation, we measured the porosity evolution and acoustic emission activity of the samples. In addition, we measured the axial permeability and P-wave velocity of the samples both during isostatic confinement and after sample failure. Our results show that the mechanical and hydraulic transport properties of transverse isotropic tight crystalline rocks can be separated into two classes. First, the mechanical properties such as onset of dilatancy, yield stress, peak strength and residual strength, follow a ”U-type” anisotropy towards foliation angle, with maximum values at 0 and 90 and minima between 30 and 45. These properties, as well as the porosity variation during deformation which follows an inversed ”U-type” shape can be explained by anisotropic wing crack models. Second, the volumetric physical properties (permeability and P-wave velocity) follow a ”decreasing order” shape towards foliation angle, with maximum values at 0 decreasing to the minimum at 90. These properties show a high dependence on the stress state and the wave path. We discuss the implications of these results for deep geothermal energy prospection, and for reservoir stimulation and operation.

Motivated by recent advances in mapping mesoscale eddy tracer mixing in the ocean we evaluate the sensitivity of a coarse-resolution global ocean model to a spatially variable neutral diffusion coefficient $\kappa_n(x,y,z)$. We gradually introduce physically-motivated models for the horizontal (mixing length theory) and vertical (surface mode theory) structure of $\kappa_n$ along with suppression of mixing by mean flows. Each structural feature influences the ocean’s hydrography and circulation to varying extents, with the suppression of mixing by mean flows being the most important factor and the vertical structure being relatively unimportant. When utilizing the full theory (experiment “FULL’) the interhemispheric overturning cell is strengthened by $2$ Sv at $26^\circ$N (a $\sim20\%$ increase), bringing it into better agreement with observations. Zonal mean tracer biases are also reduced in FULL. Neutral diffusion impacts circulation through surface temperature-induced changes in surface buoyancy fluxes and non-linear equation of state effects. Surface buoyancy forcing anomalies are largest in the Southern Ocean where decreased neutral diffusion in FULL leads to surface cooling and enhanced dense-to-light surface watermass transformation, reinforced by reductions in cabbeling and thermobaricity. The increased watermass transformation leads to enhanced mid-latitude stratification and interhemispheric overturning. The spatial structure for $\kappa_n$ in FULL is important as it enhances the interhemispheric cell without degrading the Antarctic bottom water cell, unlike a spatially-uniform reduction in $\kappa_n$. These results highlight the sensitivity of modeled circulation to $\kappa_n$ and motivate the use of physics-based models for its structure.

In this study, 42 years of tidal records and landfall TC best tracks in Japan were used to demonstrate that TC pre-landfall forward speed is significantly correlated with maximum storm surge height. Coastal morphology was the determining factor for the correlation between storm surge and TC forward speed. Fast-moving TCs tended to amplify the storm surge along open coastlines (Pearson correlation coefficient, R = 0.62), but reduce it in semi-enclosed bays (R = -0.52). The negative correlation contrasts with the general perception that the coincidence of TC wind speed and forward speed vectors generates a larger storm surge. The influence of coastal morphology was most prominent for TCs with a central pressure lower than 956 hPa. Tropical cyclone (TC) operational forecasts are continuously improving; however, there is still scope to improve the precision of storm surge predictions. These findings could contribute to the improvement of storm surge forecasting and provide emergency management personnel with more precise early warnings of dangerous storm surges.

Sea ice formation processes occur on sub-grid scales and the detailed physics describing the processes are therefore not generally represented in climate models. One likely consequence of this is the premature closing of areas of open water in model simulations, which may result in a misrepresentation of heat and gas exchange between the ocean and atmosphere. This work demonstrates the implementation of a more realistic model of sea ice formation, introducing grease ice as a wind- and oceanic- stress-dependant intermediary state between water and new sea ice. We use the fully coupled land-atmosphere-ocean- sea ice model, HadGEM3-GC3.1 and perform a three member ensemble with the new grease ice scheme from 1964 to 2014. Comparing our sea ice results with the existing ensemble without grease ice formation shows an increase in sea ice thickness and volume in the Arctic. In the Antarctic, including grease ice processes results in large local changes to both simulated sea ice concentration and thickness, but no change to the total area or volume.

Warm frozen soil is very sensitive to temperature change in the near phase transition region, and the relationship between temperature and physical and mechanical properties can be expressed by constitutive model. Based on the strain equivalent theory of damage mechanics, the damage model of warm frozen soil structure under the coupling action of stress and temperature is established. Based on Mohr- Coulomb criterion, the nominal stress is used to represent the stress damage of frozen soil element, the initial elastic modulus is used to represent the temperature damage, and the composite damage factor is introduced to describe the coupling relationship between them. Two methods are used to obtain the shape parameters and scale parameters of the coupled damage model: method 1 is the full fitting method based on the experimental data; method 2 is the semi theoretical semi fitting method based on the characteristic points of the stress-strain curve. Through the triaxial compression test of frozen sand, it is proved that the simulation results of the stress-temperature coupled damage model are in good agreement with the experimental curves. Based on the experimental results, the results of the two methods are compared, and it is proved that method 2 is better than method 1 under the condition of strain softening. By comparing the predicted results of stress temperature coupled damage model and single stress damage model, it is shown that the former can effectively reduce the influence of parameter estimation error on the results and improve the stability of the model.

Accounting for uncertainty in statistical model parameters is an essential part of geostatiscal reservoir characterization. While parameter uncertainty may be assessed in its ergodic form; the non-ergodic is a better characterization of the variability in the random field. Assessing non-ergodic parameter uncertainty requires re-sampling (bootstrapping) techniques. Existing techniques for such non-ergodic re-sampling are plagued with some limitations/complications. This paper therefore presents a spatial bootstrap algorithm that overcomes the limitations/complication. For a discretized field, the algorithm implements simultaneous displacements (shiftings) of all sampling points through the same distance vector. The shiftings are done across the dimensions of the field subject to the dimensionality of the sampling. In each dimension, the sampling points are shifted successively through a distance equivalent to the gridblock length in that dimension. At each shifting, a shifted sampling grid, of similar configuration as the original sampling grid, is generated. Using the shifted sampling grid, the algorithm re-samples a full-grid simulated realization of the field. The assumption of second-order stationarity implies that a sample from a shifted sampling grid is considered a repeated sample of the original sample. The algorithm has been scripted in R statistical computing environment and applied to an irregularly-sampled 3-D field with satisfactory results.

High pressures, along with thermal processes and irradiation, have a measurable effect on carbonaceous compounds which are found throughout the solar system. High pressure environments, such as those generated by impacts, occur frequently during the evolution of the solar system, and the effects of pressure on the carbonaceous materials present can influence the subsequent chemistry of the body. In situ high pressure synchrotron source Fourier Transform Infrared (FTIR) spectroscopy coupled with computational models has been used to directly study the effects of pressure on carbonaceous materials. Our work using these techniques investigates the specific case of structural sugars, where ribose and deoxyribose have differing responses to high pressures. These particular carbonaceous materials play a key role in the prebiotic chemistry of the early Earth as constituents of the bioinformational molecules ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) respectively. Ribose is substantially less stable than deoxyribose at pressures exceeding 14 GPa and shows less recovery on decompression. Our results imply that the modest impacts experienced throughout the solar system could substantially alter the carbonaceous payload of many bodies, with consequences for any prebiotic chemistry.

This study was conducted to assess precipitation particle properties, including ice-nucleating particle (INP) concentration (L^-1 Air), in West Texas, where the semi-arid climate prevails and typically <40 inches of rainfall coincides per year. Further, the West Texas region is dominated by deep convective clouds, where INPs play a crucial role in hailstorm and thunderstorm processes (e.g., Li et al., 2017; Rosenfeld et al., 2008). In this study, we looked into major precipitation events observed throughout the year in 2018 and 2019 in the Texas Panhandle area. More specifically, to characterize immersion freezing efficiency (T > -25 degree C) of our precipitation samples, we used a cold-stage instrument called West Texas Cryogenic Refrigerator Applied to freezing Test (WT-CRAFT) system (Hiranuma et al., 2019). Additionally, a disdrometer is used to look into the relationship between INP concentration, intensity and size of precipitation particles. An indigenously developed Internet of Things (IoT) air quality sensors were also used to compare ambient air quality (i.e., particulate matter concentrations) and meteorological conditions to the measured INP concentrations. Overall, the study’s preliminary results show a reasonable correlation between INP concentration and precipitation properties (i.e., intensity). We also find a high ice nucleation efficiency at higher temperatures (i.e., T > -15 degree C), which can be attributed to the biological INPs from local agricultural sources. The results also suggest that INPs play an important role in the precipitation particle size. These findings may be important in artificially varying the severity of the precipitation by varying the INP concentration in the West Texas region.

A large-eddy simulation (LES) tool is developed for simulating the dynamics of atmospheric boundary layers using lattice Boltzmann method (LBM), which is an alternative approach for computational fluid dynamics and proved to be very well suited for the simulation of low-Mach flows. The equations of motion are coupled with the global complex physical models considering the coupling among several mechanisms, namely basic hydro-thermodynamics and body forces related to stratification, Coriolis force, canopy effects, humidity transport and condensation. Mass and momentum equations are recovered by an efficient streaming, collision and forcing process within the framework of LBM while the governing equations of temperature, liquid and vapor water fraction are solved using a finite volume method. The implementation of wall models for atmospheric boundary layer, subgrid models and interaction terms related to multiphysic phenomena (e.g. stratification, condensation) is described, implemented and assessed in this study. An Immersed Boundary approach is used to handle flows in complex configurations, with application to flows in realistic urban areas. Applications to both wind engineering and atmospheric pollutant dispersion are illustrated.

We present a 1:10M scale map of the Niobe Map Area (NMA) of Venus (0N-57N/60E-80E). Geologic mapping employed NASA Magellan synthetic aperture radar and altimetry data. The NMA geologic map, and its companion Aphrodite Map Area (AMA), cover ~25% of Venus’ surface, providing with an important and unique perspective to study global and regional geologic processes. Both areas display a regional coherence of preserved geologic patterns that record three sequential geologic eras: the ancient era, the Artemis superstructure era, and the youngest fracture zone era. The NMA preserves a limited record of the fracture zone era, contrary to the AMA. However, the NMA host a diverse and rich assemblage of material and structures of the ancient era, and structures that define the Artemis superstructure era, with a footprint covering more than 25 percent of the surface of Venus. These two eras likely overlap in time and account for the formation of basement materials and lower plain units. Impact craters formed throughout the NMA recorded history. Approximately 40% of the impact craters show interior flood deposits, indicating that a significant number of NMA impact craters experienced notable geological events after impact crater formation. This and other geologic relations record a geohistory inconsistent with postulated global catastrophic resurfacing. Together, the NMA and the AMA record a rich geologic history of the surface of Venus that provide a framework to formulate new working hypotheses of Venus evolution, an to plan future studies of the planet.

From extracting nutrients to releasing energy, biological metabolism plays an integral role in determining evolutionary patterns of organisms through geologic time. A previous study depicted a positive relationship between metabolic rate and extinction probability for Mollusca within the Neogene period. We hypothesized that this relationship extends to other metazoan phyla during the Cenozoic Era. Using specific respiration rates measured from living organisms and body size data for fossil taxa, we estimated metabolic rates of animals across different phyla: Arthropoda, Brachiopoda, Echinodermata, and Mollusca. This analysis was performed at the class level by using the classes with the most data available to represent each phylum: Malacostraca, Ostracoda, Cirripedia, Rhynchonellata, Echinoidea, Bivalvia, Cephalopoda, and Gastropoda. We then used logistic regression to estimate the relationship between the calculated metabolic rates and extinction probability during each epoch of the Cenozoic Era. Results indicate that while each individual phylum has a different extinction probability across each epoch, the regression coefficients for the combination of all studied phyla illustrate no relationship since there is not enough evidence to reject the null hypothesis of no relationship between metabolic rate and extinction probability. Although this means that there is no significant correlation for most of the phyla, there are some exceptions where metabolism does affect extinction probability. During the Oligocene epoch, animals within the Mollusca phylum portray a clear negative correlation between metabolic rate and extinction probability. A negative relationship is also observed for Echinoderms during the Eocene epoch. Despite the crucial role that metabolism plays in species survival, our results indicate that more information is needed regarding specific environmental conditions in order to accurately predict the factors that ultimately affect species survival across marine animals within the Cenozoic Era.

Exploration of SST-Streamflow connection unravels the large scale climate influences that have a potential role in modulating local hydrological components. Most studies exploring this relationship only focus on seasonal or annual scales however, various atmospheric and oceanic phenomena occur at different timescales, which need to be considered. This study investigates the influence of sea surface temperature (SST) on German streamflow, divided into Alpine, Atlantic and Continental streamflow regions, at timescales ranging from sub-seasonal to decadal by integrating wavelet transform and complex network techniques. Wavelet transform is used to decompose the time series into multiple frequency signals, and the spatial connections are identified based on these decomposed signals for the 99 percentile correlation coefficient value by applying network theory. The degree centrality metric is used to evaluate the characteristics of the spatially embedded networks. Our results re-establish known SST regions that have a potential connection with the various streamflow regions of Germany. Spatial patterns that resemble the North Atlantic SST tripole-like pattern is predominant for Alpine streamflow regions at lower timescale. Equatorial Atlantic Mode regions observed for Atlantic streamflow at inter-annual timescale and Vb weather system connected regions in the Mediterranean Sea have appeared for all the streamflow regions of Germany. Besides, continental streamflow regions exhibited combined characteristics of the Alpine and Atlantic streamflow spatial patterns. In addition to the above regions, we also identify the scale specific patterns in the Pacific, Indian and Southern Ocean regions at different timescales ranging from seasonal to decadal scale.

An autonomous mobile ground-control point (AMGCP) was redesigned and refined for improved collaborative operation with an unmanned aerial vehicle (UAV) to enable calibration of image mosaics from multispectral (MS) and thermal cameras. The AMGCP has built-in reflectance panels and electronically controlled thermal panels that provide high and low reflectance and temperature references that can be used for calibration of reflectance measurements in MS images and temperature measurements in thermal-infrared images. The AMGCP also has an onboard temperature sensor that enables image-based temperature measurements to be compared to ambient temperature so that canopy temperature depression (CTD) can be calculated. The collaborative robotic system consists of the AMGCP and a UAV that have real-time kinematic (RTK) geographic positioning system (GPS) receivers onboard so their precise position can be determined in real time. The system also includes wireless communication capability between the AMGCP and UAV so they can transmit their position and other data to each other during a mission, in which the AMGCP positions itself at multiple locations under the flight path of the UAV, providing multiple instances of reflectance and temperature references in image mosaics collected by the UAV. Testing has shown that reflectance measurements can be calibrated to less than 1% reflectance error, and canopy temperatures of crop plants can be calibrated to within 1.0 C, enabling consistently accurate measurements to be made efficiently and without human intervention in various fields and regions and at different times and dates. This system is also suited to accurate measurement of CTD to facilitate genetic selection relative to various stresses and resilience characteristics like drought tolerance.

The science linking anthropogenic greenhouse gas emissions with our changing climate, and the resulting impacts, has been well established for decades. During that time one of the focal points of international negotiations was to establish a common target for action to address climate change. These negotiations culminated in the Paris Agreement at COP21 in 2015 which seeks to limit the global mean surface temperature (GMST) rise to well below 2C above pre-industrial, and to pursue efforts to limit it to 1.5C. Our research seeks to assess the climate justice implications of using global mean surface temperature as a metric for climate action by combining data from ice sheet models and fully coupled global climate model simulations in conjunction with a literature review spanning fields including international relations, political economy, critical geography, and history. Considering the political and scientific history of the development of the temperature target alongside global impacts of climate change we gain a new understanding of spatial, temporal, and procedural aspects of climate justice.

Brinicles are self-assembling tubular ice membrane structures, centimeters to meters in length, formed by the downward migration of supercooled brine rejected from ice sheets, and found beneath sea ice in the polar regions of Earth.  They provide a plausible setting for geochemical gradients amenable to life at the ice-ocean interface, in some ways analogous to hydrothermal vents at the seafloor-ocean interface. Their occurrence in icy ocean worlds like Europa and Enceladus remains hypothetical. The context of brinicles on Earth includes influences from oceanic flow, which will differ in other worlds, and surficial inputs from the atmosphere that do not exist in oceans with kilometers-thick global coverings of ice formed from the underlying ocean. Thus, it is difficult to project the likely occurrence and role of brinicles based on field observations of their earthly analogues. We discuss brinicles as they are currently understood, including their electrochemical properties in connection with potential habitats at the ice-ocean interface on Europa and Enceladus. We employ a fluid mechanical model (Cardoso and Cartwright, 2017) to assess the properties of brinicles on other worlds and consider their longevity relative to potential brine outflows from the overlying ice. We demonstrate how brinicles may grow by thermal diffusion, and provide simple scaling for their growth and outflow rates. The specifics of the composition and dynamics of both the ice and the ocean in these worlds remain poorly constrained. We demonstrate through calculations using FREZCHEM that sulfate likely fractionates out of accreting ice in Europa and Enceladus, and thus that an exogenous origin of sulfate observed on Europa’s surface need not preclude additional endogenous sulfate in Europa’s ocean. We suggest that, like hydrothermal vents on Earth, brinicles in icy ocean worlds constitute ideal places where ecosystems of organisms might be found.

The conservation of natural ecosystems is an essential component for sustainable land use (LU). One of the challenges facing society worldwide is climate change, where reduce emissions, and sequestrate greenhouse gases from the atmosphere are fundamental to mitigate its effects. LU change plays a major role in the carbon (C) cycle, and understanding and quantifying its effects is one of the main challenges for effectively implementing climate change mitigation actions. Given this scenario, our objective was to calibrate the Daycent model to estimate the references equilibrium soil organic matter (SOM) for three important Brazilian biomes: Atlantic Forest (AF), Cerrado (CE), and Pampa (PA). Together, they represent 39% of native vegetation area, and over them are concentrated the majority of the agricultural production in Brazil. Estimating the equilibrium for major soil types in the three biomes is fundamental for evaluating C dynamics and the soil C loss regarding LU changes. Data from literature, including SOM, were collected for the three biomes: PA (29°30’S, 54°15’W; soil with sandy loam texture), CE (19°28’S, 44°15’W; very clayey texture) and AF (10°92’S, 37°19’W; sandy texture). Daycent parameters to represent the biomes biophysical properties were initially set up with values from local literature. Measured SOM was then employed during the calibration of the Daycent model. We ran the model for 6,000 years for the equilibrium simulations, obtaining the stabilization of the SOM compartments (active, slow, and passive). For the biomes’ biophysical properties the parameters for maximum potential production (PRDX) were adjusted for each biome, PA with 0.92 g C m-2 , AF with 1.5 g C m-2 and CE with 0.9 g C m-2 (default = 0.5 g C m-2). The relative error between measured and predicted total SOM was lower than 2% for all biomes, thus representing the equilibrium properly for the study conditions. The largest C compartment of the biomes (slow organic matter in the soil) had 71.7% for AF, 68.5% for PA, and 63.7% for CE of the total SOM. The highest SOM values were found in the CE, with 53 Mg C ha-1, followed by the PA with 37 Mg C ha-1, and in the AF with 35 Mg C ha-1. Eventual LU changes will impact the SOM equilibrium of these native vegetation, but sustainable practices must take place to avoid C losses as far as possible.

We present approach based on physically substantiated short-term precursor’s selection to provide the real-time multiparameter monitoring having as a purpose the short-term forecast of earthquakes. Three main principles should be fulfilled: 1. We register natural phenomena for which we have multi-year experience demonstrating their connection with the earthquake preparation process 2. All these phenomena have very high statistical confidence in relation to post-phenomena earthquake occurrence 3. We have the physical explanation of these anomalous phenomena generation and their interrelation within the framework of earthquake preparation process. It is important to note that precursors are registered in different geospheres (lithosphere, atmosphere, ionosphere and magnetosphere) what confirms the fact of geospheres coupling during the earthquake preparation period. For the first time we included in consideration the role of triggers and their relationship with precursors. One of the well confirmed triggers is the Space weather evens changing the global atmospheric circulation. The arising large-scale irregularities of atmospheric pressure may serve as earthquake triggers while their linear borders coincide with the active tectonic fault. Another recently revealed effect is existence of earthquake retarders when earthquake happens later (up to month) in comparison with our procedure of earthquake time determination. Complications created by triggers and retarders in developed procedure of short-term earthquake forecast should be resolved in future development of our research. All these ideas are presented in the book which just published by Institute of Physics (IOP) and has the same title as abstract. This work was supported by RSF (project No 18-12-00441)