Seth Minor, Daniel A. Messenger, Vanja Dukic
et al.
The multiscale and turbulent nature of Earth's atmosphere has historically rendered accurate weather modeling a hard problem. Recently, there has been an explosion of interest surrounding data-driven approaches to weather modeling, which in many cases show improved forecasting accuracy and computational efficiency when compared to traditional methods. However, many of the current data-driven approaches employ highly parameterized neural networks, often resulting in uninterpretable models and limited gains in scientific understanding. In this work, we address the interpretability problem by explicitly discovering partial differential equations governing atmospheric phenomena, identifying symbolic mathematical models with direct physical interpretations. The purpose of this paper is to demonstrate that, in particular, the Weak form Sparse Identification of Nonlinear Dynamics (WSINDy) algorithm can learn effective atmospheric models from both simulated and assimilated data. Our approach adapts the standard WSINDy algorithm to work with high-dimensional fluid data of arbitrary spatial dimension.
Failure of earthen slopes is a very recurrent phenomenon, credited mainly due to the excess rainfall and application of surfeit surcharge. However, most of the analyses regarding slope stability were performed without considering the unsaturated state of the soil. The prime purpose of the present manuscript is to address the stability of unsaturated homogeneous slopes subjected to surcharge load and pseudo-static seismic forces under different climatic conditions. The upper bound limit analysis technique was used based on the log-spiral failure mechanism. The suction stress-based effective stress approach was used to capture the effect of the unsaturated zone of the slope. The suction stress is modelled using Gardner's one-parameter hydraulic conductivity function and van-Genuchten's soil water characteristics curve. An extensive parametric study is carried out to assess the combined effect of slope geometry, soil-strength parameters, hydro-mechanical parameters, depth of water table, various flow conditions, surcharge load, and seismic loading. A few stability charts are proposed to show the impact of surcharge load and seismic load separately on unsaturated homogeneous slopes subjected to various climatic conditions. The present computed solutions match quite well with the available solutions prescribed in the literature.
The C01 Earth orientation parameters (EOP) series provided by the International Earth Rotation and Reference Systems Service (IERS) is the longest reliable record of the Earth's rotation. In particular, the polar motion (PM) series beginning from 1846 provides a basis for investigation of the long-term PM variations. However, the pole coordinate $Y_p$ in the IERS C01 PM series has a 2-year gap, which makes this series not completely evenly spaced. This paper presents the results of the first attempt to overcome this problem and discusses some ways to fill this gap. Two novel approaches were considered for this purpose: parametric astronomical model consisting of the bias and the Chandler and annual wobbles with linearly changing amplitudes, and data-driven model based on Singular Spectrum Analysis (SSA). Both methods were tested with various options to ensure robust and reliable results. The results obtained by the two methods generally agree within the $Y_p$ errors in the IERS C01 series, but the results obtained by the SSA approach can be considered preferable because it is based on a more complete PM model.
Seyed Morteza Davarpanah, Peter Ván, Balázs Vásárhelyi
AbstractThe determination of deformation parameters of rock material is an essential part of any design in rock mechanics. The goal of this paper is to show, that there is a relationship between static and dynamic modulus of elasticity (E), modulus of rigidity (G) and bulk modulus (K). For this purpose, different data on igneous, sedimentary and metamorphic rocks, all of which are widely used as construction materials, were collected and analyzed from literature. New linear and nonlinear relationships have been proposed and results confirmed a strong correlation between static and dynamic moduli of rock species. According to rock types, for igneous rocks, the best correlation between static and dynamic modulus of elasticity (E) were nonlinear logarithmic and power ones; for sedimentary rocks were linear and for metamorphic rocks were nonlinear logarithmic and power correlation. Moreover, with respect to different published linear correlations between static modulus of elasticity (Estat) and dynamic modulus of elasticity (Edyn), an interesting correlation for rock material constants was established. It was found that the static modulus of elasticity depends on the dynamic modulus only with one parameter formula.
In contrast to the wet gets wetter and dry gets drier paradigm, here, using observations and climate model simulations, we show that the mean rainfall over the semi-arid northwest parts of India and Pakistan has increased by 10 to 50 percent during 1901 to 2015 and is expected to increase by 50 to 200 percent under moderate greenhouse gas (GHG) scenarios, e.g, SSP2 4.5. The GHG forcing primarily drives the westward expansion of the Indian summer monsoon (ISM) rainfall and is a result of a westward expansion of the inter-tropical convergence zone (ITCZ), facilitated by a westward expansion of the Indian Ocean warm pool. While an adaptation strategy to increased hydrological disasters is a must, harvesting the increased rainfall would lead to a significant increase in food productivity, bringing transformative changes in the socio-economic condition of people in the region.
Abrupt and irreversible winter Arctic sea-ice loss may occur under anthropogenic warming due to the collapse of a sea-ice equilibrium at a threshold value of CO$_2$, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in Arctic sea ice exists because fully-coupled climate models are too computationally expensive to run to equilibrium for many CO$_2$ values. Here, we explore the deviation of sea ice from its equilibrium state under realistic rates of CO$_2$ increase to demonstrate how a few time-dependent CO$_2$ experiments can be used to predict the existence and timing of sea-ice tipping points without running the model to steady-state. This study highlights the inefficacy of using a single experiment with slow-changing CO$_2$ to discover changes in the sea-ice steady-state, and provides an alternate method that can be developed for the identification of tipping points in realistic climate models.
Noctilucent or polar mesospheric clouds have become visually brighter and occurred more frequently during the recent years and decades. The study of possible reasons and relations with climate changes requires data on long-time trends of mean particle size and altitude. Extended worldwide observational data is a good tool for this, and it can be provided by simple RGB-photometry using widely distributed all-sky cameras. Based on observations of bright expanded clouds in summer 2020 and 2021, the method of mean particle size determination is developed, results are validated using the radiative transfer model. The procedure also allows finding the effective 'umbral' altitude of clouds. The correlation of size and altitude of particles is compared with existing lidar data and models of particle growth.
Io, the most volcanically active body in the solar system, loses heat through eruptions of hot lava. Heat is supplied by tidal heating and is thought to be transferred through the mantle by magmatic segregation, a mode of transport that sets it apart from convecting terrestrial planets. We present a model that couples magmatic transport of tidal heat to the volcanic system in the crust, in order to determine the controls on crustal thickness, magmatic intrusions, and eruption rates. We demonstrate that magmatic intrusions are a key component of Io's crustal heat balance; around 80% of the magma delivered to the base of the crust must be emplaced and frozen as plutons to match rough estimates of crustal thickness. As magma ascends from a partially molten mantle into the crust, a decompacting boundary layer forms, which can explain inferred observations of a high-melt-fraction region.
It is important to be able to calculate the moist-air entropy of the atmosphere with precision. A potential temperature has already been defined from the third law of thermodynamics for this purpose. However, a doubt remains as to whether this entropy potential temperature can be represented with simple but accurate first- or second-order approximate formulas. These approximations are rigorously defined in this paper using mathematical arguments and numerical adjustments to some datasets. The differentials of these approximations lead to simple but accurate formulations for tendencies, gradients and turbulent fluxes of the moist-air entropy. Several physical consequences based on these approximations are described and can serve to better understand moist-air processes (like turbulence or diabatic forcing) or properties of certain moist-air quantities (like the static energies).
The climate system is a forced, dissipative, nonlinear, complex and heterogeneous system that is out of thermodynamic equilibrium. The system exhibits natural variability on many scales of motion, in time as well as space, and it is subject to various external forcings, natural as well as anthropogenic. This paper reviews the observational evidence on climate phenomena and the governing equations of planetary-scale flow, as well as presenting the key concept of a hierarchy of models as used in the climate sciences. Recent advances in the application of dynamical systems theory, on the one hand, and of nonequilibrium statistical physics, on the other, are brought together for the first time and shown to complement each other in helping understand and predict the system's behavior. These complementary points of view permit a self-consistent handling of subgrid-scale phenomena as stochastic processes, as well as a unified handling of natural climate variability and forced climate change, along with a treatment of the crucial issues of climate sensitivity, response, and predictability.
Staggered grid finite difference scheme is widely used for the first order elastic wave equation, which constitutes the basis for least-squares reverse time migration and full waveform inversion. It is of great importance to improve the efficiency and accuracy of wave equation modeling. Usually the same staggered grid finite difference scheme is used for all the spatial derivatives in the first order elastic wave equation. In this paper, we propose a new staggered grid finite difference scheme which can improve the efficiency while preserving the same accuracy for the first order elastic wave equation simulation. It uses second order staggered grid finite difference scheme for some of the first order spatial derivatives while utilizing longer staggered grid finite difference operator for other first order spatial derivatives. We The staggered grid finite difference coefficients of the new finite difference scheme are determined in the space domain by a linear method. We demonstrate by dispersion analysis and numerical simulation the effectiveness of the proposed method.
A novel approach is presented for fast generation of synthetic seismograms due to microseismic events, using heterogeneous marine velocity models. The partial differential equations (PDEs) for the 3D elastic wave equation have been numerically solved using the Fourier domain pseudo-spectral method which is parallelizable on the graphics processing unit (GPU) cards, thus making it faster compared to traditional CPU based computing platforms. Due to computationally expensive forward simulation of large geological models, several combinations of individual synthetic seismic traces are used for specified microseismic event locations, in order to simulate the effect of realistic microseismic activity patterns in the subsurface. We here explore the patterns generated by few hundreds of microseismic events with different source mechanisms using various combinations, both in event amplitudes and origin times, using the simulated pressure and three component particle velocity fields via 1D, 2D and 3D seismic visualizations.
Marina Rosas-Carbajal, Kevin Jourde, Jacques Marteau
et al.
Muon imaging has recently emerged as a powerful method to complement standard geophysical tools in the understanding of the Earth's subsurface. Muon measurements can yield a radiography of the average density along the muon path, allowing to image large volumes of a geological body from a single observation point. Here we jointly invert muon data from three simultaneous telescope acquisitions together with gravity data to estimate the three-dimensional density structure of the La Soufrière de Guadeloupe lava Dome. Our unique dataset allows us to achieve an unprecedented spatial resolution with this novel technique. The retrieved density model reveals an extensive, low-density anomaly where the most active part of the volcanic hydrothermal system is located, supporting previous studies that indicate this region as the most likely to be involved in a partial edifice collapse.
Denys Schmitt, Philippe Cardin, Patrick La Rizza
et al.
The dynamics of fluctuations in a fast rotating spherical Couette flow experiment in the presence of a strong dipolar magnetic field is investigated in detail, through a thorough analysis of the experimental data as well as a numerical study. Fluctuations within the conducting fluid (liquid sodium) are characterized by the presence of several oscillation modes, identified as magneto-Coriolis (MC) modes, with definite symmetry and azimuthal number. A numerical simulation provides eigensolutions which exhibit oscillation frequencies and magnetic signature comparable to the observation. The main characteristics of these hydromagnetic modes is that the magnetic contribution has a fundamental influence on the dynamical properties through the Lorentz forces, although its importance remains weak in an energetical point of view. Another specificity is that the Lorentz forces are confined near the inner sphere where the dipolar magnetic field is the strongest, while the Coriolis forces are concentrated in the outer fluid volume close to the outer sphere.