One of the main sources of seismic noise below 0.05 Hz is the atmospheric pressure variation, especially when surface pressure variations are large. The amount of ground deformation under surface pressure variations reflects the characteristics of shallow elastic structure. When a surface broadband seismic stations is equipped with a pressure sensor, we can estimate near-surface shear-modulus structure using an inversion method. In the inversion method, we have the surface observable η(f)=Sz/Sp, where f is a frequency between 0.01 and 0.05 Hz, and Sz and Sp are the power spectral densities of vertical seismic data and of surface pressure data. We derive depth sensitivity kernels for η(f) with which we invert for elastic moduli of the shallow structure. Between 0.01 and 0.05 Hz, sensitivity kernels typically have peaks at depths within the uppermost 100 meters. Based on vertically heterogeneous 1-D structures, we estimate Vs30 at 744 USArray Transportable Array stations. Vs30 is the time-averaged shear-wave velocity from the surface to the 30-meters depth. We compare our results with various surficial geology maps. Although Vs30 has high horizontal variability over a short distance on the scale of hundreds of meters, we find correlations between Vs30 and large-scale geological structures, such as mapped units and surficial materials. We find good agreement between estimated Vs30 and mapped Quaternary sediment depths, where stations with thicker underlying sediment tend to have slower Vs30.

The surface of ice in contact with water contains sites that undergo deprotonation 6 and protonation, and can act as adsorption sites for aqueous ions. Therefore, an electrical double layer should form at this interface, and existing models for describing the electrical double layer at metal oxide-water interfaces should be able to be modified to describe the surface charge, surface potential, and ionic occupancy at the ice-water interface. I used a surface complexation model along with literature measurements of zeta potential of ice in brines of various strength and pH to constrain equilibrium constants. I then made predictions of ion site occupancy, surface charge density, and partitioning of counterions between the Stern and diffuse layers. The equilibrium constant for cation adsorption is more than 5 orders of magnitude larger than the others constants, indicating that this reaction dominates even at low salinity. Deprotonated OH sites are predicted to be slightly more abundant than dangling O sites, consistent with previous work. Surface charge densities are on the order of ±0.001 C/m^2 and are always negative at the moderate pH values of interest to atmospheric and geophysical applications (6-9). In this pH range, over 99% of the counterions are contained in the Stern layer. This suggests that diffuse layer polarization will not occur because the ionic concentrations in the diffuse layer are nearly identical to those in the bulk electrolyte, and that electrical conduction and polarization in the Stern layer will be negligible due to reduced ion mobility.

Reasonable classification of aurora is of great significance to the study of the generation mechanism of aurora and the dynamic process of the magnetosphere boundary layer. Previous aurora classification studies, both manual and automatic, rely on experts’ visual inspection and manual labeling of part or all of the data. However, there is currently no consensus on aurora classification schemes. In this paper, an auroral image clustering network (AICNet) is proposed to unsupervised classification of all-sky images for the first time by grouping observations according to their morphological similarities. Auroral features are first extracted by deep convolutional auto-encoder, and the images with similar features are automatically clustered into one group. AICNet is fully automatic and requires no human supervision to tell the classification scheme or manually label samples. In the experiments, 4000 dayside all-sky auroral images captured at the Chinese Yellow River Station during 2003-2008 were considered. The images were clustered into two classes. The occurrence time of auroras illustrates that images in one cluster appear a double-peak occurrence distribution and mostly occur in the afternoon, while images in the other cluster mostly occur before and at noon. Auroral displays in the two clusters exhibit high intra-cluster similarity and low inter-cluster similarity in terms of the overall intensity and morphological structures. Experimental results demonstrate that the proposed method can discover the internal structures of auroras and would enable automatic classification of unprecedented scope without any human supervision.

A document by Hao Zhou. Click on the document to view its contents.

Inter-annual sea-level variations of up to 20 mm are superimposed upon the global average sea-level rise (~3 mm/yr) from human-caused global warming. These variations affect the degree of coastal flooding, and related damage, during the highest annual tides. Along the Atlantic coast of the United States, such inter-annual sea-level variations have been attributed to several atmospheric and oceanographic processes. In the present analysis, detrended tide gauge data isolate inter-annual interannual variations that can be reconstructed using Fourier analysis of a limited number of coefficients based on frequencies of lunar orbit ( and precessions) combined with . Although a causal relationship between such forcings and extreme sea levels remains elusive, the reconstructions may provide an effective method for projections of occurrence of extreme sea levels. Two reconstructions project that anomalously high sea levels may occur in the late 2020s, mid 2050s, early 2060s, early 2070s and late 2090s.

We examine characteristics of the boundaries of 11 Kelvin-Helmholtz vortex crossings observed by MMS on September 23, 2017 under southward IMF conditions. At both the leading and trailing edges, boundary regions of mixed plasma are observed together with lower-hybrid wave activity. We found that thicker boundary regions feature a higher number of sub-ion scale current sheets, of which only one shows clear reconnection signatures. Moreover, the lower-hybrid waves along the vortex spine region are identified as an effective mechanism for plasma transport with an estimated diffusion coefficient of D ≈ 109 m2/s. Comparisons with 3D simulations performed under the same conditions as the MMS event suggest that the extension of the boundary regions as well as the number of current sheets are related to different evolutionary stages of the vortices. Such observations can be explained by changes in the upstream magnetic field conditions.

Surface waves modify upper ocean dynamics through Stokes drift related processes. Representation of these processes at either resolved or parameterized scales in an ocean model depends on accurate estimation of Stokes drift profiles. Stokes drift estimated from a discrete wave spectrum is compared to Stokes drift approximations as a monochromatic profile based on bulk surface wave parameters, and to two additional super-exponential functional forms. The impact of these different methods on resolved-scale ocean processes is examined in the context of two test-bed cases of a wave-current coupled system: (1) a shallow water inlet test case and (2) an idealized deep water hurricane case. In case (1), tidal currents can modify the waves and significantly affect Stokes drift computed from the wave spectrum. In both cases, large deviations in ocean current response are produced when the Stokes drift is approximated monochromatically from bulk wave parameters, rather than from integration over the wave spectra. Deep water simulations using the two super-exponential approximations are in better agreement with those estimated from wave spectra than are those using the monochromatic, exponential profile based on bulk wave parameters. In order to represent the impact of Stokes drift at resolved scales, we recommend that for studies of nearshore processes and brief deep water events, like wave-current interactions under storms, the Stokes drift should be calculated from full wave spectra. For long simulations of open ocean dynamics, methods using super-exponential profiles to represent equilibrium wind seas might be sufficient, but appear to be marginally more computationally efficient.

This study presents an information content analysis of the retrieval of global carbon monoxide (CO) from the 2 nd generation of Hyperspectral Infrared Atmospheric Sounder on board Fengyun-3E (FY-3E/HIRAS-II), which is the world's first dawn-dusk orbiting meteorological satellite for civilian use with equatorial overpass times at about 5:30 am/pm. Using the distinctive absorption features of CO around 2145 cm-1 in the infrared band, a retrieval algorithm based on optimal estimation is first developed to retrieve the CO profiles from FY-3E/HIRAS-II. The thermal contrast, defined as the temperature difference between the surface and the lower atmosphere, is then examined for the FY-3E/HIRAS-II observations to investigate the potential sensitivity of the observations. Retrievals of CO columns on four representative days over four seasons reveal strong enhancements from global wildfire emissions. Furthermore, the information content from the spectra, quantified by the degree of freedom for signal (DOFS), is assessed using the retrievals. The retrievals are compared with model simulations, which show good agreement. Finally, synthetic experiments are performed to investigate the impacts of thermal contrast and the vertical structure of wildfire-induced CO enhancement on the observational sensitivity. The result highlights the effectiveness of observing wildfire-induced CO enhancement during the dawn and dusk hours, even thermal contrast conditions are not favorable. This study demonstrates the capability of FY-3E/HIRAS-II to monitor global CO, which sheds light on the potential benefits of adding dawn-dusk orbit observations to the current global air quality observations from mid-morning and early-afternoon orbit constellations.

Changes in atmospheric pressure continuously ventilate soils and snowpacks. This physical process, known as pressure pumping, is a major factor in the exchange fluxes of H2O, CO2 and other trace gases between the soil and atmosphere. Thus models of pressure pumping are relevant to many areas of critical importance. This study compares the three principal models used to describe pressure pumping. Beginning with the fundamental physical principles and whether the flow field is compressible or incompressible, these models are categorized as linear parabolic (one model – compressible) or nonlinear hyperbolic (two models – incompressible). Using observed soil surface pressure data, measured vertical profiles of soil permeability and standard linear analysis and numerical methods, this study shows that nonlinear models produce advective velocities that are one to two orders of magnitude greater than those associated with the linear model. Incorporating soil temperature and moisture dynamics made very little difference to the linear model, but a significant difference in the nonlinear models suggesting that advective velocities induced by pressure changes associated with soil heating and moisture dynamics may not always be small enough to ignore. All numerical results are sensitive to the frequency of the pressure forcing, which was band-pass filtered into low, mid and high frequencies with the greatest model differences at low frequencies. Partitioning the pressure forcing and model responses helped to establish that mid-frequency weather-related phenomena (empirically identified as inertia gravity waves and solitons) are important drivers of gas exchange between the soil and the atmosphere.

Realistic representation of detailed rainfall characteristics on local scale by current state-of-the-art climate models remains a key challenge, especially on sub-daily timescales. In this research, the convection-permitting Weather Research and Forecasting (WRF) model configured with 1.5 km grid spacing is used to simulate precipitation on sub-daily timescales over the Yangtze River Delta Region of China for continuous 10 years (2005–2014). The simulations are compared to rain gauge observations, reanalysis data, and the simulations of a lower resolution WRF with 9 km grid spacing that has a parameterization of convection. The results show that precipitation over the region can be well captured by using the convection-permitting model (CPM). Furthermore, the intensity, duration and coverage of these precipitation events can be more accurately described by the CPM. On the convection timescales of 1–4 hours, especially for heavy rainfall events, the CPM is more accurate than the convection-parameterized model in capturing the short-duration events, which may be related to its better account of physical processes related with the convection on the convection-permitting scale. In addition, the extreme events which are more localized and with short-duration can be represented better by the CPM while the convection-parameterized model tends to produce widespread precipitation events covering more grid cells than observed. Biases of the simulation by the 9-km mesh convection-parameterized mode appear to be related to the deficiencies in the representation of convections.

Incoherent scatter radars (ISR) estimate the electron and ion temperatures in the ionosphere by fitting measured spectra of ion-acoustic waves to forward models. For radars looking at aspect angles within 5° of perpendicular to the Earth’s magnetic field, the magnetic field constrains electron movement and Coulomb collisions add an additional source of damping that narrows the spectra. Fitting the collisionally narrowed spectra to collisionless forward models leads to errors or underestimates of the plasma temperatures. This paper presents the first fully kinetic particle-in-cell simulations of ISR spectra with collisional damping by velocity dependent electron-electron and electron-ion collisions. For aspect angles between 0.5° and 2° off perpendicular, the damping effects of electron-ion and electron-electron collisions are the same and the resulting spectra are narrower than what current theories predict. For aspect angles larger than 3° away from perpendicular, the simulations with electron-ion collisions match collisionless ISR theory well, but spectra with electron-electron collisions are narrower than theory predicts at aspect angles as large as 5° away from perpendicular. At all aspect angles the particle-in-cell simulations produce narrower spectra than previous simulations using single particle displacement statistics. The narrowing of spectra by electron-electron collisions between 3° and 5° away from perpendicular is currently neglected when fitting measured spectra from the Jicamarca and Millstone Hill radars, leading to underestimates of electron temperatures by as much as 50% at these radars.

Key questions remain about the atmospheric response to variability in the oceanic western boundary currents (WBCs). Here we exploit a unique high-resolution slab-ocean coupled climate model to investigate how ocean heat transport (OHT) anomalies in the major WBCs of both hemispheres affect the atmospheric circulation. In both hemispheres, prescribed OHT anomalies lead to robust changes in convective precipitation anomalies equatorward of the maximum surface warming. The response is deepest and most pronounced over the Northern Hemisphere (NH) WBCs, where it is associated with significant changes in upper tropospheric vertical motion, condensational heating and geopotential heights. The response is relatively shallow over the Southern Hemisphere (SH) WBCs. The findings reveal the robustness of the atmospheric response to OHT anomalies and highlight key hemispheric differences: in the NH, realistic OHT anomalies are balanced by deep atmospheric vertical motion; in the SH, they are balanced primarily by shallow horizontal temperature advection.

Vegetation patterns often affected by the soil pH, soil compaction and human mediated disturbance. Several studies have explored how pH, compaction and human disturbance have altered the ecosystem patterns, functioning and services. These studies about semi-arid drylands, explain how lifeforms and productivity resulting from soil acidity, hardness and human disturbance in arid-land. To further enhance the understanding of this correlation, we have surveyed five different eco-system within Yookamurra Sanctuary (Murray lands of South Australia), which is protecting over 5000 hectares of epidemic vegetation and wildlife species. Data has been collected by random sampling method with 150 quadrate samples for soil pH, soil compaction, litter depth, disturbance (Animal or Human) and lifeforms within Yookamurra region. Results suggest that the impacts of pH and compaction are varying across five different ecosystems. Moreover, vehicle disturbance has greater consequences at Roadside ecosystem. These findings amend our understanding of the interaction of soil characteristics with the vegetation patterns, especially in semi-arid region, such as Yookamurra wildlife sanctuary.

Understanding the spatiotemporal characteristics of terrestrial water storage (TWS) variation is crucial for evaluating climate change and promoting sustainable water resource management. Numerical hydrological models and satellite data, particularly information obtained from gravity variations through the Gravity Recovery and Climate Experiment (GRACE) mission, are widely utilized for the analysis of TWS fluctuations. Even though GRACE holds excellent promise for large-scale exploration, these measurements are too coarse for localized quantification. Therefore, enhancing the resolution of GRACE measurements holds significant potential for application at the local to regional scale. The objective of this study is to produce higher-resolution images capable of depicting the local-scale TWS anomalies (TWSA) in the South America continent using a modified version of the Generative Adversarial Network (GAN). Our results demonstrate that the conditional WGAN-GP model can effectively replicate the structures of the TWSA signals with a reasonably close resemblance. This indicates that the model can successfully execute the downscaling task and harness high-resolution spatiotemporal structures within the low-resolution satellite observation for unseen temporal data.

This study explores the structures of the correlations between infrared (IR) brightness temperatures (BTs) from the three water vapor channels of the Advanced Baseline Imager (ABI) onboard the GOES-16 satellite and the atmospheric state. Ensemble-based data assimilation techniques such as the ensemble Kalman filter (EnKF) rely on correlations to propagate innovations of BTs to increments of model state variables. Because the three water vapor channels are sensitive to moisture in different layers of the troposphere, the heights of the strongest correlations between these channels and moisture in clear-sky regions are closely related to the peaks of their respective weighting functions. In cloudy regions, the strongest correlations appear at the cloud tops of deep clouds, and ice hydrometeors generally have stronger correlations with BT than liquid hydrometeors. The magnitudes of the correlations decrease from the peak value in a column with both vertical and horizontal distance. Just how the correlations decrease depend on both the cloud scenes and the cloud structures, as well as the model variables. Horizontal correlations between BTs and moisture, as well as hydrometeors, in fully cloudy regions decrease to almost 0 at about 30 km. The horizontal correlations with atmospheric state variables in clear-sky regions are broader, maintaining non-zero values out to ~100 km. The results in this study provide information on the proper choice of cutoff radii in horizontal and vertical localization schemes for the assimilation of BTs. They also provide insights on the most efficient and effective use of the different water vapor channels.

Solute transport in unsaturated porous media is of interest in many engineering and environmental applications. The interplay between small-scale, local forces and the porous microstructure exerts a strong control on the transport of fluids and solutes at the larger, macroscopic scales. Heterogeneity in pore geometry is intrinsic to natural materials across a large range of scales. This multiscale nature, and the intricate links between two-phase flow and solute transport, remain far from well understood, by and large. Here, we use high-resolution direct simulation to quantify solute mixing and dispersion behavior within correlated porous media during drainage under an unfavorable viscosity ratio. Through analysis of flow and transport at multiple realizations, we find that increasing spatial correlations in pore sizes increase the size of the required Representative Elementary Volume (REV). We show that increasing the correlation length enhances solute dispersivity through its impact on the spatial distribution of low-velocity (diffusion-dominated) and high-velocity (advection-dominated) regions. Fluid saturation is shown to directly affect diffusive mass flux among high-and low-velocity zones. Another indirect effect of correlated heterogeneity on solute transport is through its control of the drainage patterns via repeated alteration in the connectivity of flowing pathways. Our findings improve quantitative understanding of solute mixing and dispersion under two-phase conditions, highly relevant to some of our most urgent environmental problems.

This study investigates the influence of the phase of quasi-biennial oscillation (QBO) and the 11-year solar cycle on the Arctic spring ozone, using satellite observations, reanalysis data, and outputs of a chemistry climate model (CCM) during the period of 1979–2011. For this duration, we found that the composite mean of the Northern Hemisphere high-latitude total ozone in the QBO-westerly (QBO-W)/solar minimum (S) phase indicates a large negative anomaly for the climatology in February–March. An analysis of the passive ozone tracer defined at the pressure levels between 220 hPa and 12 hPa in the CCM simulation indicates that this negative anomaly is primarily caused by transport. The negative anomaly is consistent with a weakening of the residual mean downward motion in the polar lower stratosphere. The contribution of chemical processes estimated using the total ozone difference between the chemically active ozone runs and the passive tracer simulations is less than 6% of the total anomaly in February and between 10–20% in March. The lower ozone levels in the Arctic spring during the QBO-W/Syears are associated with a stronger Arctic polar vortex from late winter to early spring, which is linked to the reduced occurrence of sudden stratospheric warming in the winter during the QBO-W/Syears.

Jupiter’s giant magnetosphere is a complex system seldom in a configuration approximating steady state, and a clear picture of its governing dynamics remains elusive. Crucial to understanding how the magnetosphere behaves on a large scale are disturbances to the system on length-scales comparable to the cavity, which are communicated by magnetohydrodynamic waves in the ultra-low-frequency band (≤ 1 mHz). In this study we used magnetometer data from multiple spacecraft to perform the first global heritage survey of these waves in the magnetosphere. To map the equatorial region, we relied on the large local-time coverage provided by the Galileo spacecraft. Flyby encounters performed by Voyager 1 and 2, Pioneer 10 and 11, and Ulysses provided local-time coverage of the dawn sector. We found several hundred events where significant wave power was present, with periods spanning ~5-60 min. The majority of events consisted of multiple superposed discrete periods. Periods at ~15, ~30 and ~40 min dominated the event-averaged spectrum, consistent with the spectra of quasi-periodic pulsations often reported in the literature. Most events were clustered in the outer magnetosphere close to the magnetopause at noon and dusk, suggesting that an external driving mechanism may dominate. The most energetic events occurred close to the planet, though more sporadically, indicating an accumulation of wave energy in the inner magnetosphere or infrequent impulsive drivers in the region. Our findings suggest that dynamics of the system at large scales is modulated by this diverse population of waves, which permeate the magnetosphere through several cavities and waveguides.