Flood basalts are some of the largest magmatic events in Earth history, with intrusion and eruption of millions of km$^3$ of basaltic magma over a short time period ($\sim$ 1-5 Ma). A typical continental flood basalt (CFB) is emplaced in hundreds of individual eruptive episodes lasting decades to centuries with lava flow volumes of 10$^3$- 10$^4$ km$^3$. These large volumes have logically led to CFB models invoking large magma reservoirs ($>$ 10$^5$-10$^6$ km$^3$) within the crust or at Moho depth. Since there are currently no active CFB provinces, we must rely on observations of past CFBs with varying degrees of surface exposure to develop and test models. In the last few decades, significant improvements in geochronological, geochemical, paleomagnetic, volcanological, and paleo-proxy measurements have provided high-resolution constraints on CFB eruptive tempo - the volume, duration, and frequency of individual eruptive episodes. Using the well-studied Deccan Traps as an archetype for CFB systems, we compile multiple lines of evidence - geochronology, eruption tempo, dike spatial distribution, intrusive-extrusive ratio, geochemical variations, and volcanological observations - to assess the viability of previous models. We find that the presence of just a few large crustal magma reservoirs is inconsistent with these constraints. Although observations from the Deccan Traps primarily motivate our model, we discuss constraints from other CFBs to illustrate that this conclusion may be broadly applicable, with important implications for interpreting CFB geochemical datasets as well as the timing and volumes of climate-altering volatile emissions associated with CFBs.

The spatiotemporal patterns of injection-induced seismicity (IIS) are commonly interpreted with the concept of a triggering front, which propagates in a diffusion-like manner with an associated diffusivity parameter. Here, we refer to this diffusivity as the “seismic diffusivity”. Several previous studies implicitly assume that seismic diffusivity is equivalent to the effective hydraulic diffusivity of the subsurface, which describes the behavior of the mean pressure field in heterogeneous porous media. Seismicity-based approaches for hydraulic characterization or simulations of IIS using domains of homogeneous equivalent porous media are implicitly based on this assumed equivalence. However, seismicity is expected to propagate with the threshold triggering pressure, and thus not be controlled by the evolution of the mean pressure field. We present numerical simulations of fluid injection to compare the seismic and effective hydraulic diffusivities in heterogeneous formations (including fractured rock). The numerical model combines uncoupled, linear pressure diffusion with the Mohr-Coulomb failure criterion to simulate IIS. We demonstrate that connected pathways of relatively high hydraulic diffusivity in heterogeneous media (particularly in fractured rock domains) allow the threshold triggering pressure to propagate more rapidly than predicted by the effective hydraulic diffusivity. As a result, the seismic diffusivity is greater than the effective hydraulic diffusivity in heterogeneous porous media, possibly by an order of magnitude or more. Additionally, we present a case study of IIS near Soultz-sous-Forêts where seismic diffusivity is found to be at least one order of magnitude larger than the effective hydraulic diffusivity.

Bifurcations and tipping points (TPs) are an important part of the Earth system’s behavior. These critical points represent thresholds at which small changes in the system’s parameters or in the forcing abruptly switch the system from one state or type of behavior to another. Current concern with TPs is largely due to the potential contribution of anthropogenic forcing to one or more climatic subsystems undergoing such abrupt, and possibly irreversible, transitions. Paleorecords of past climate have been shown to contain abrupt transitions, or “jumps,” which may represent former instances of tipping. Robustly identifying and describing such transitions is essential to properly understanding the underlying bifurcation mechanisms. Doing so may provide valuable information for identifying critical TPs in current and future climate evolution.Here we present a robust methodology for detecting abrupt transitions in proxy records that is applied to a set of ice core, speleothem, and marine sediment records of the last climate cycle and the Holocene. This methodology is based on the nonparametric Kolmogorov-Smirnov (KS) test for the equality, or not, of the probability distributions associated with two samples drawn from a time series, before and after any potential jump. The KS test is augmented by several other criteria and it is evaluated against other jump detection algorithms, aiming to establish a “gold standard” for abrupt-transition detection. This objective approach to identifying climate TPs will allow us to construct better nonlinear and stochastic models of bifurcations in the Earth’s climate and its interactions with ecosystems within the TiPES (Tipping Points in the Earth System) EU-funded project.

Two data sets (OTREC and PREDICT) and the European Center operational model are used to study convection. Vertically integrated moisture convergence is taken to be a proxy for convection. The interplay between the thermodynamic parameters is examined for weak and strong convection. It is found that for strong convection saturation fraction anti-correlates with instability index and DCIN in a similar manner for all analyzed regions of PREDICT and OTREC. The European Center model is used to look at the composite diurnal cycles of strong and weak convection. As convection increases, saturation fraction increases while instability index and DCIN decrease as in OTREC and PREDICT. The boundary layer and free troposphere thus both play an important role in convection development.

Finite-fault stochastic method was applied to simulate the Mw 6.9, 2008 Iwate-Miyagi earthquake at 44 selected Kik-net sites using EXSIM computer code. To investigate the effects of source characteristics on the simulated results, three models were considered: two models with prescribed slip distribution (Model 1 and Model 3) and a model with random slip distribution (Model 2). S-wave regional attenuation indicates obvious difference between fore-arc and back-arc regions which are formed by volcanic front. Site amplification was determined by corrected surface to borehole spectral ratio and Quarter wavelength methods. High frequency decay parameter (kappa) was estimated to be 0.0473 s. The value of 160 bars for stress drop was calculated by minimizing absolute residual of 5% damped pseudo spectral accelerations (PSA). Comparison of the observed and simulated peak ground accelerations and PSAs were performed to investigate the capability of our finite-fault models. The residual models represent that the simulated results by Model 2 are in good agreement with the observations in f < 3 Hz, while the other models can better simulate higher frequency motions. We also focused on the effects of slip patches sitting on the fault plane on near-field stations placed in the directions of slip propagation. For these stations, the simulated results by Model 1 and Model 3 were preferred over those of Model 2. Finite-fault models successfully interpreted the real forced motion to AKTH04 where the recorded peak values were abnormal for non-seismological reasons. Finally, the comparison of intensity measures with the GMPEs showed good agreement.

We demonstrate that long-term tidally-induced changes in extreme sea levels affect estimates of major flood hazard in a predictable way. Long-term variations in tides due to the nodal and perigean tidal cycles influence extreme sea levels at 234 global tide gauges out of a total of 344. Results show regions where the amplitudes of the modulations are particularly relevant in the 100-year return sea level; the eastern coast of China, the northwestern and northeastern coasts of Australia, the northeast coast of Pacific, and the eastern coast of Europe, reaching up to ~22 cm in western France. We identify locations that are currently in a positive phase of the modulation and therefore at a higher risk of flooding, as well as when (year) the next peak of the nodal/perigean modulations is expected to occur. The timing of the peak of the modulation is spatially coherent and influenced by the relative importance of each cycle (nodal or perigee) over the total amplitude. An evaluation of four locations suggests that the potentially flooded area in a 100-year event can vary up to ~45% (in Boston) as a result of the long-term tidal cycles; however, areal change is often smaller due to local topography and tidal characteristics (6-13%). We conclude that tidally-modulated changes in extreme sea levels can alter the potentially inundated area in a 100-year event and that the traditional, fixed 100-year floodplain is inadequate for describing coastal flood risk.

Large thermospheric neutral density enhancements in the cusp region have been examined for many years. The CHAMP satellite for example has enabled many observations of the perturbation, showing that it is mesoscale in size and exists on statistical timescales. Further studies examining the relationship with magnetospheric energy input have shown that fine-scale Poynting fluxes are associated with the density perturbations on a case-by-case basis, whilst others have found that mesoscale downward fluxes also exist in the cusp region statistically. In this study, we use nearly 8 years of the overlapping SuperDARN and AMPERE datasets to generate global-scale patterns of the high-latitude and height-integrated Poynting flux into the ionosphere, with a time resolution of two minutes. From these, average patterns are generated based on the IMF orientation. We show the cusp is indeed an important feature in the Poynting flux maps, but the magnitude does not correlate well with statistical neutral mass density perturbations observed by the CHAMP satellite on similar spatial scales. Mesoscale height-integrated Poynting fluxes thus cannot fully account for the cusp neutral mass density enhancement, meaning energy deposition in the F-region or on fine-scales, which is not captured by our analysis, could be the primary driver.

We performed a comprehensive study of the generation and transport mechanisms of a river plume flowing into a microtidal environment. First, we analysed images simultaneously acquired by both two shore-based stations and satellite and correlated the plume offshore extension with the estuarine forcing. Furthermore, we run numerical simulations to reproduce real-life events, characterized by a combination of forces, and to distinguish the role of each forcing. We identified the river discharge and the wind as the main generation and transport mechanisms, respectively. Moreover, waves were able to both generate and drag plumes. Results showed that a river discharge associated with a return period of 1 year produced a denser plume than 10-years return period waves. The transport mechanisms were responsible for the alongshore extension of the plume and consequent potential nourishment of the beaches. The tide, even if secondarily, could affect the plume evolution, depending on its phase shift with respect to the river discharge peak. Finally, we used Particle Tracking Velocimetry on videos acquired by a shore-based station to obtain the surface velocity field in the final river stretch. Such velocity was then modified to consider the effect of wind and waves, so that it could be correlated with the plume extension. The relation between the along-river component of the plume velocity and the plume extension followed a linear law with angular coefficient inversely proportional to the alongshore component of the plume velocity.

Traditionally, NOAA NESDIS has distributed GOES imagery as small sector images, usually a jpg or gif. With the launch of GOES-16, NESDIS has embraced a more modern approach to serving this imagery: NOAA Satellite Maps is a geospatial data Map Service to access imagery from the geostationary and polar satellites in our fleet. We support open information sharing and integration through this RESTful Service, which can be used by a multitude of GIS software packages and web map applications (both open and commercially licensed) for free. One of the most important features of the Satellite Maps layers service is the interoperable nature of its data. Users can combine georeferenced data layers from other datasets together with the Satellite Maps data, allowing infinite opportunities for providing meaning and value to NOAA data. For example, GOES East infrared Band 10 data can be combined with Doppler radar data and Lightning data to see how cloud cover and instances of rain align during a critical weather event. In this poster we will discuss the architecture and application development that were used to generate the image services and how the public is accessing and downloading GOES imagery.

Oxygen ions, O+, efficiently energized by weak fast shock in the mid-altitude cusp observed by Cluster on 7 November 2004 are investigated in this paper. An interplanetary fast shock hitting Earth magnetosphere was observed by Geotail at 1825 UT with a sharply increase in the solar wind dynamic pressure from 3nPa to 11nPa. There are significant fluctuations of solar wind dynamic pressure from 1930 UT to 2000 UT during this shock compressing Earth magnetosphere. During this pressure disturbance intervals Cluster 4 was located in the mid-altitude cusp, (0.43, -3.25, 3.07) RE_GSE. CODIF/Cluster 4 instrument detected O+ ions with tens keV energized by the weak fast shock with Mach number MA~1.2 in the perpendicular direction. Those energetic O+ ions have bunch or partial ring distributions in the mid-altitude cusp. Our observation results put forward confident evidences on the weak fast shock efficiently energizing heavy ions, especially, O+ ions in the cusp.

The Saharan Air Layer (SAL) has been shown to be an elevated, well-mixed, warm, dry, frequently dusty layer. The structure of the SAL plays an important role in regional climate and in long-range dust transport. A new analysis of aircraft observations shows that although increased dustiness in the SAL is associated with drier conditions in the lower-SAL as expected, dustiness is also associated with increased moisture in the upper-SAL. We assess the radiative effects of the observed dust and increased water vapor (WV) using a radiative transfer model. The observed WV in the upper-SAL affects the top-of-atmosphere (TOA) direct radiative effect (DRE), while lower-SAL WV affects the surface DRE and column atmospheric heating. TOA DRE is negative for dust-only, while including both the observed dust and WV reduces the magnitude of the negative TOA DRE by 11%. The observed WV structure increases the negative surface DRE from dust by 8% and increases atmospheric heating by 17%. These effects are driven by longwave (LW) radiation, whereby WV changes increase the positive TOA LW DRE by 30%, decrease the surface LW DRE by 52% and change the sign of LW atmospheric heating from negative to positive. The observed WV profile leads to enhanced cooling in the moist upper-SAL and heating in the dry lower-SAL under dustier conditions. Increased WV in the SAL is consistent with other studies demonstrating a trend of increased WV over the Sahara. This work demonstrates the importance of the upper-SAL WV profile in determining the radiative effect dust.

Offshore freshened groundwater reservoirs occur on continental shelves in several regions of the world. Their origins are an active area of research, however, models often rely on simplified geometrical representations of subsurface geology. The New Jersey shelf hosts an extensive multi-layered freshened groundwater system that previous paleo-reconstructions have not reproduced. In this numerical case-study, we aim to characterize the New Jersey shelf system in the context of a geologically representative heterogeneous model. Our model combines sequence stratigraphic interpretation of 2D depth migrated seismic lines and a stochastic facies distribution with petrophysical properties of four boreholes. We employ a stochastic approach to generate both high and low onshore-offshore connectivity scenarios. The study considers a 58 000-year recharge period for the subaerially exposed shelf transect, followed by the marine transgression from 12 000 years ago until today. The results show that the lowstand period drove sufficient freshwater emplacement that can explain most of the present-day observations. The highest rates of recharge occurred during the periods of most rapid sea-level fall. Simulated scenarios indicate that topographically driven flow of meteoric recharge via surface-connected pathways is the key emplacement mechanism. Surviving freshwater systems exhibit lateral variability in salinity due to downward fingering of saline pore fluid. Freshwater preserved from the Last Glacial Maximum may extend up to 100 km from the coastline. The results also suggest that cyclical flushing and re-salinization of shelf sediments during glacial-interglacial cycles is an asymmetrical process, promoting freshwater storage over geological time scales.

Machine learning (ML) parameterizations of subgrid physics is a growing research area. A key question is whether traditional ML methods such as feed-forward neural networks (FNNs) are better suited for representing only specific processes. Radiation schemes are an interesting example, because they compute radiative flows through the atmosphere using well-established physical equations. The sequential aspect of the problem implies that FNNs may not be well-suited for it. This study explores whether emulating the entire radiation scheme is more difficult than its components without vertical dependencies. FNNs were trained to replace a shortwave radiation scheme, its gas optics component, and its reflectance-transmittance computations. In addition, a novel recurrent NN (RNN) method was developed to structurally incorporate the vertical dependence and sequential nature of radiation computations. It is found that a bidirectional RNN with an order of magnitude fewer model parameters than FNN is considerably more accurate, while offering a smaller but still significant 4-fold speedup over the original code on CPUs, and a much greater speedup on GPUs. The RNN predicts fluxes with less than 1\% error, and heating rates computed from fluxes have a root-mean-square-error of 0.16 K day$^{-1}$ in offline tests using a year of global data. Finally, FNNs emulating gas optics are very accurate while being several times faster. As with RNNs emulating radiative transfer, the smaller dimensionality may be crucial for developing models that are general enough to be used as parameterizations.

The successful application of deep learning for seismic phase arrival time picking has increased the efficacy of earthquake catalog development workflows. Earthquake catalogs with lower magnitude of completeness and better locational precision than current standard practice can now be generated with very limited need for human review and without the need for earthquake templates, which are not always available. Here, we report on a ‘Deep Earthquake Catalog’ with over 300,000 events from a geographically extensive region spanning Oklahoma and Southern Kansas from January 2010 to December 2020 developed using a workflow that leverages deep learning for phase picking. The increased number of events and improved spatial resolution compared to the previous statewide catalogs reveals numerous discrete faults and both broad trends and localized patterns of seismicity. This rich dataset provides new opportunities for data-driven analyses of induced earthquakes.

Airflows over complex geometrical surfaces such as complex terrain and densely built urban districts are highly turbulent and sometimes become a threat under disturbed weather conditions. Among the meteorological disturbances, the landfalls of tropical cyclones cause strong winds and may lead to severe damages in populated urban areas and in mountainous areas. Because gusty winds are primarily a cause for damages, diagnosing and predicting quantitatively wind and turbulent characteristics are critically important. In order to assess strong wind hazards in complex urban areas, this study uses a large-eddy-simulation (LES) model with buildings and structures explicitly resolved at an O(1 m) grid spacing. With such a building-resolving LES model, we have analyzed turbulent airflows in urban districts of Japanese major cities and have found that the LES model is capable of estimating the magnitude of gusty winds and turbulent fluctuations. In order to improve the accuracy in representing the properties of airflows, we have developed a data assimilation method which incorporates observed turbulence. The proposed data assimilation method used a vibration equation which can incorporate turbulence winds toward target mean winds while maintaining small-scale turbulent fluctuations and was applied for airflows in actual urban districts of Kyoto City by incorporating data obtained from meteorological observations located in Kyoto. We have concluded that the data assimilation method using the vibration equation successfully nudges toward the target mean winds while maintaining small-scale turbulent fluctuations well. Our recent LES analyses of airflows in urban districts have been extended to studies related to the impact assessment of and the adaptation to climate change in urban areas. A building-resolving LES model has become a practical tool to more applied side of turbulent airflow analysis.

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.

While hydraulic groundwater theory has been understood as a viable approach for representing the role of the aquifer(s) in the surface-subsurface hydrologic cycle, the integrated modeling community still lacks a proper hydrologic structure to utilize the well-studied theory for large-scale hydrologic predictions. This study aims to present a novel hydrologic modeling framework that enables the Boussinesq equation-based depiction of hillslope-channel connectivity for applying hydraulic groundwater theory to large-scale model configurations. We integrated the BE3S’s [Hong et al., 2020] representation scheme of the catchment-scale Boussinesq aquifer into the National Water Model (NWM) and applied the NWM-BE3S model to three major basins in Texas (i.e., the Trinity, Brazos, and Colorado River basins). Since the NWM currently relies on a single reservoir model for baseflow estimation, theory-based evaluation was performed as the efficacies that the Boussinesq aquifer has relative to the single reservoir model should be consistent with hydraulic groundwater theory. We identified that the implemented Boussinesq aquifer(s) showed ‘more’ pronouced improvements in capturing streamflow dynamics than the original NWM as aquifers exhibited higher nonlinearities in the observed recessions. The varying degree of improvements in streamflow outputs according to the recession nonlinearities demonstrates (1) the applicability of the theory-based depiction of hillslope-channel connectivity and (2) the technical enhancement of model structure. We also examined the river states of all the reaches based on the represented bidirectional lateral hydraulic connections between the stream-aquifer and thus identified the dominant processes between the stream-aquifer (i.e., either river infiltration or baseflow) were spatially variable roughly following climatic gradients.

Earthquake stress drop is an important source parameter that directly links to strong ground motion and fundamental questions in earthquake physics. Stress drop estimations may contain significant uncertainties due to factors such as variations in material properties and data limitations, which limits the applications of stress drop interpretations. Using a high-resolution borehole network, we analyze 4537 earthquakes in the Parkfield area in Northern California between 2001 and 2016 with spectral decomposition and an improved stacking method. To evaluate the influence of spatiotemporal variations of material properties on stress drop estimations, we apply six different strategies to account for spatial variations of velocity and attenuation changes, and divide earthquakes into three separate time periods to correct temporal variations of attenuation. These results show that appropriate corrections can significantly reduce the scatter in stress drop estimations, and decrease apparent depth and magnitude dependence. We further investigate the influence of data limitations on stress drop estimations, and show that insufficient bandwidth may cause systematic underestimation and increased stress drop scatter. The stress drop measurements from the high-frequency borehole recordings exhibit complex stable spatial patterns with no clear correlation with the nature of fault slip, or the slip distribution of the 2004 M6 earthquake. In some regions with the largest numbers of earthquakes, we can resolve temporal variations that indicate stress drop decrease following the 2004 earthquake, and gradual recovery. These temporal variations do not affect the long-term stress drop spatial variations, suggesting local material properties may control the spatial heterogeneity of stress drop.