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Abstract

The interplay between seismic activity and fluid flow is essential during the evolution of hydrothermal systems. Although earthquakes can trigger transient fluid flow and phase changes in dilational jogs, the temporal scale and the geologic conditions that enhance such process are poorly quantified. Here, we use numerical simulations of deformation and fluid flow to constrain the conditions that maximize adiabatic boiling—referred to as flashing—and estimate the extent and duration of such process. We show that there is an optimal geometry for a dilational jog that maximizes co-seismic flashing within the jog. Fluid flow simulations indicate that the duration, intensity, and propagation of the flashing front are limited and highly dependent on the magnitude of the co-seismic slip and the initial pressure-enthalpy conditions. Our results are valuable to better understand the implications of pressure fluctuations during the seismogenic cycle, as well the mineralization processes in the Earth's crust.

Abstract

The overflow of cold water through the Faroe Bank Channel (FBC) is the densest water crossing the Greenland-Scotland Ridge and the densest source for the Atlantic Meridional Overturning Circulation (AMOC). Here, we show that the overflow volume transport remained stable from 1996 to 2022, but that the bottom water warmed at an average rate of 0.1°C per decade, mainly caused by warming of deep waters upstream. The salinity of the overflow water has increased as a lagged and reduced response to the salinity increase seen in the upper-layer source waters. Therefore, the potential density of the bottom water over the FBC sill shows no statistically significant trend. After entrainment of warmer ambient waters downstream of the FBC, the nonlinear density dependence upon temperature implies, however, that the overflow contributed water of reduced density to the local overturning and the deep limb of the AMOC.

Abstract

Observational and modeling studies have elucidated the influential role played by the southern and northern extratropical Pacific (SEP and NEP) forcing in shaping dynamics of tropical Pacific climate variability. However, the relative importance of the NEP and SEP and the timescale on which they impact the tropics remain unclear. Using a linear inverse model (LIM) that selectively incorporates or excludes tropical-extratropical coupling, we find a reduction in tropical interannual variability (∼40%) and low-frequency (sub-decadal to decadal) variability in the southeastern tropical Pacific region (∼70%) in the absence of SEP. Conversely, the absence of NEP yields no significant impact on tropical interannual variability but markedly diminishes low-frequency variability in the central tropical Pacific region (∼70%). LIM and statistic diagnostics on CMIP6 models show the low-frequency to total variability ratio in the tropical Pacific depending on their NEP and SEP representation. Models with more (less) low-frequency power tend to show stronger NEP (SEP) dynamics.

Abstract

We evaluate the skill and sources of skill in initialized seasonal climate forecasts of monthly global mean temperature from the North American Multi-Model Ensemble (NMME) during the period 1991–2024. The forecasts demonstrate skill in addition to that from the long-term trend, and that skill is primarily attributable to ENSO. However, the skill varies seasonally, with skill being lowest for target periods during Northern Hemisphere summer. Single model ensembles show underdispersion at short leads, while the multi-model ensemble is overdispersed, suggesting initial condition errors and highlighting the importance of model initialization for quantification of forecast uncertainty. Lead-time dependent errors in global mean temperature trends appear related to Pacific trend errors. The multi-model mean captured the overall trend but underestimated the record-breaking temperatures of 2023. Forecasts for the remainder of 2024 indicate cooling by the end of the year.

Excess carbon dioxide emitted by human activities—such as fossil fuel burning, land-use changes, and deforestation—is known as anthropogenic carbon dioxide. Approximately 30% of this anthropogenic carbon dioxide in the atmosphere is absorbed by the world's oceans. While this absorption helps mitigate global warming, it also has adverse effects on marine life, including fish and plants.

Abstract

We present the first global geospace simulation to reproduce auroral giant undulations (GUs). To identify their magnetospheric drivers, we employ the MAGE (Multiscale Atmosphere-Geospace Environment) model in a case study of a geomagnetic storm for which there were spacecraft- and ground-based observations of GUs. The model reproduces the spatial and temporal scales of the GUs as well as the presence of duskside subauroral polarization streams (SAPS) and plasmapause undulations. Based on our modeling, we are able to identify the magnetospheric drivers of GUs as mesoscale ring current injections which, after drifting westward, create inverted regions of flux-tube entropy (FTE) and subsequent interchange instability. Outward-protruding interchange fingers disrupt shielding of the inner magnetosphere, creating longitudinally localized ripples in magnetospheric convection equatorward of the magnetospheric instability, which structure the plasmapause and duskside diffuse precipitation. While not causal, SAPS and plasmapause undulations are a consequence of the unstable magnetospheric configuration.

Abstract

Roughly one-third of sudden stratospheric warming (SSW) events lack a strong canonical surface response, and this can lead to a forecast bust if a strong response was predicted. Hence, it is desirable to predict before SSW onset if an event will propagate downward. The predictability of the downward response of SSWs is considered in seven subseasonal-to-seasonal forecast models for 16 major SSWs between 1998 and 2022, a larger sample size than considered by previous works. The models successfully predict before SSW onset which SSWs have a stronger downward response to 100 hPa, however they struggle to predict which have a stronger tropospheric response. The downward response is stronger if the magnitude of the deceleration of the 10 hPa winds is more accurately predicted. Downward response is stronger for split and absorbing SSWs. In contrast, there is little relationship between SSWs whose onset can be predicted at earlier leads and the downward response.

The hottest warm period in the past million years is believed to have occurred about 400,000 years ago. During this time, the Northern Hemisphere had less ice than today, and sea levels were about 10 meters higher. Surprisingly, solar radiation, a key driver of warm periods, was weak during this time, and greenhouse gas levels were lower than today. This puzzling period, known as the MIS 11c paradox, has long baffled scientists.

Author(s): Matthew Schlitters, Matthew Miller, Ben Farley, and Scott D. Bergeson

Bronin et al. [Phys. Rev. E 108, 045209 (2023)] recently reported molecular-dynamics simulations of ultracold neutral plasmas expanding in a quadrupole magnetic field. While the main results are in agreement with prior experimental measurements, we present data showing oscillations not captured in t…

[Phys. Rev. E 110, 027201] Published Wed Aug 21, 2024

Author(s): S. Ya. Bronin, E. V. Vikhrov, B. B. Zelener, and B. V. Zelener

In this Reply, we respond to the Comment by Schlitters et al. on our recent work [Phys. Rev. E 108, 045209 (2023)], where we present simulation results of ultracold Sr plasma expansion in a quadrupole magnetic field using a molecular-dynamics method. In the Comment, Schlitters et al. present their e…

[Phys. Rev. E 110, 027202] Published Wed Aug 21, 2024

Pioneering research forecasts that worldwide flooding is likely to be significantly worse in future decades if countries fail to meet official pledges to cut carbon emissions.

Abstract

Regression models (LEEMYR: Low Energy Electron MLT geosYnchronous orbit Regression) predict hourly 4.1–30 keV electron flux at geostationary orbit (GOES-16) using solar wind, IMF, and geomagnetic index parameters. Multiplicative interaction and polynomial terms describe synergistic and nonlinear effects. We reduce predictors to an optimal set using stepwise regression, resulting in models with validation comparable to a neural network. Models predict 1, 3, 6, 12, and 24 hr into the future. Validation correlations are as high as 0.78 (4.1 and 11 keV, 1 hr prediction) and Heidke Skill scores (HSS) up to 0.66. A 3 hr ahead prediction is more practical, with slightly lower validation correlation (0.75) and HSS (0.61). The addition of location (MLT: magnetic local time) as a covariate, including multiplicative interaction terms, accounts for location-dependent flux differences and variation of parameter influence, and allows prediction over the full orbit. Adding a substorm index (SME) provides minimal increase in validation correlation (0.81) showing that other parameters are good proxies for an unavailable real time substorm index. Prediction intervals on individual values provide more accurate assessments of model quality than confidence intervals on the mean values. An inverse N-weighted least squares approach is impractical as it increases false positive warnings. Physical interpretations are not possible as spurious correlations due to common cycles are not removed. However, SME, Bz, Kp, and Dst are the highest correlates of electron flux, with solar wind velocity, density, and pressure, and IMF magnitude being less well correlated.

Abstract

Recent studies have shown that the measurements of Langmuir Probes (LPs) onboard ESA's Swarm mission overestimate ion densities on the nightside by up to 50%. The overestimation is due to the assumption of oxygen-only plasma for ion density calculations, which is often violated at mid-latitudes on the nightside. In this study, we present a calibration model that resolves the nighttime overestimation by Swarm LPs. Using observations by Swarm FacePlate (FP) as a reference, we develop a neural network (NN) model that adjusts LP data to the FP measurements. The model incorporates dependence on solar and geomagnetic conditions, parameterized by the P10.7 and Hp30 indices, location, day of the year and local time. Our model reveals a distinct double-crest pattern in nighttime density overestimation by LPs, centered at ∼30° quasi-dipole latitude in both hemispheres. This overestimation intensifies during low solar activity and shows strong seasonal dependence. During solstices, the crests are more pronounced in the local winter hemispheres, while during equinoxes the crests are weaker and exhibit hemispheric symmetry. This morphology aligns with the presence of light ions diffusing downward from the plasmasphere. Validating the LP data in conjunctions with Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) observations showed a much stronger agreement after applying the developed correction: for Swarm B, nighttime correlation with COSMIC increased from 0.74 to 0.93. The NN-calibrated LP data set has numerous applications in ionospheric research, and the developed model can provide useful insights into the ion composition in the topside ionosphere.

Abstract

Satellite phase center variations need to be pre-eliminated in GNSS precise point positioning to ensure the best positioning precision and efficiency. To address the missing satellite antenna phase center corrections of GPS BLOCK IIF L5 signal, this study implements the estimation of satellite antenna Phase Center Offset (PCO) and Phase Center Variation (PCV) of BLOCK IIF and BLOCK III. One year of daily PCO and PCV solutions are estimated based on 118 globally distributed GPS stations. The x-offset, y-offset and z-offset PCO estimates yield a mean standard deviation of 2.3, 2.1 and 19.5 mm respectively. The mean differences between BLOCK III L5 PCO estimates and ground-based calibrated corrections are 1.8, 0.9 and 9.9 mm on the three components. Nadir-dependent PCVs are calculated with a precision better than 1.2 mm. Utilizing the antenna center corrections determined in this study, the convergence time of triple-frequency GPS kinematic PPP-AR can be shortened by 13.3%. Dual-frequency L1/L5 static PPP-AR validations show that L5 PCO corrections have no significant contribution to the positioning while 70% of globally distributed stations show improvements on the up component after applying L5 PCV corrections. By introducing L5 PCO/PCV corrections, the positioning precision of L1/L5 static PPP-AR are improved from 6.1, 3.2, 9.6 mm for the east, north and up components, respectively, to 6.2, 3.2 and 8.2 mm. The improvements of positioning precision are mainly for the up component, reaching 15%.

Abstract

Over the past decades, various experimental and numerical model studies have indicated cooling trend in the mesosphere and lower thermosphere (MLT), while the magnitude of the trend varies noticeably. Previous studies using the lidar observations derived the temperature trends and solar responses solely from the traditional nocturnal measurements. While these archived results are more or less in agreement with modeling studies, one of the main uncertainties in these studies is the potential biases induced by the trends of the diurnal tide forced in the lower atmosphere, and that of the in situ exothermal reactions involving the photolysis. In the MLT, the diurnal tide has significant seasonal variations, considerable amplitude and is one of the dominant dynamic sources. However, its potential effects in the trend studies have rarely been discussed. In this paper, we present and compare the long-term temperature trends in the upper mesosphere utilizing the daily mean and nightly mean temperature profiles measured by a Sodium (Na) Doppler lidar at midlatitude. The system was operating routinely in full diurnal cycles between 2002 and 2017, obtaining a unique multi-year temperature data set. A customized multi-linear regression (MLR) model is applied to determine the linear trends and the other fitting parameters, such as ENSO and solar F10.7 responses in the upper mesosphere. This study indicates the daily mean cooling trend between 84 and 98 km is larger than that of nightly mean trend by ∼−1 K/decade, while differences in the solar response are within the fitting uncertainties.

Abstract

We use measurements of trace gases from the Microwave Limb Sounder and polar stratospheric clouds (PSCs) from the Cloud-Aerosol Lidar with Orthogonal Polarization to investigate how the extraordinary stratospheric water vapor enhancement from the 2022 Hunga eruption affected polar processing during the 2023 Antarctic winter. Although the dynamical characteristics of the vortex itself were generally unexceptional, the excess moisture initially raised PSC formation threshold temperatures above typical values. Cold conditions, especially in early July, prompted ice PSC formation and unusually severe irreversible dehydration at higher levels (500–700 K), while atypical hydration occurred at lower levels (380–460 K). Heterogeneous chemical processing was more extensive, both vertically (up to 750–800 K) and temporally (earlier in the season), than in prior Antarctic winters. The resultant HCl depletion and ClO enhancement redefined their previously observed ranges at and above 600 K. Albeit unmatched in the satellite record, the early-winter upper-level chlorine activation was insufficient to induce substantial ozone loss. Chlorine activation, denitrification, and dehydration processes ran to completion by July/August, with trace gas evolution mostly following the climatological mean thereafter, but with chlorine deactivation starting slightly later than usual. While cumulative ozone losses at 410–550 K were relatively large, probably because of the delayed chlorine deactivation, they were not unprecedented. Thus, ozone depletion was unremarkable throughout the lower stratosphere. Although Hunga enhanced PSC formation and chemical processing in early winter, saturation of lower stratospheric denitrification, dehydration, and chlorine activation (as is typical in the Antarctic) prevented an exceptionally severe ozone hole in 2023.

Abstract

Hydration of the stratosphere by tropopause-overshooting convection has received increasing interest due to the extreme concentrations of water vapor that can result and, ultimately, the climate warming potential such hydration provides. Previous work has recognized the importance of numerous dynamic and physical processes that control stratospheric water vapor delivery by convection. This study leverages recent comprehensive observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign to determine the frequency at which each process operates during real events. Specifically, a well-established analysis technique known as tracer-tracer correlation is applied to DCOTSS observations of ozone, water vapor, and potential temperature to identify the occurrence of known processes. It is found that approximately half of convectively-driven stratospheric hydration samples show no indication of significant air mass transport and mixing, emphasizing the importance of ice sublimation to stratospheric water vapor delivery. Furthermore, the temperature of the upper troposphere and lower stratosphere environment and/or overshoot appears to be a commonly active constraint, since the approximate maximum possible water vapor concentration that can be reached in an air mass is limited to the saturation mixing ratio when ice is present. Finally, little evidence of relationships between dynamic and physical processes and their spatial distribution was found, implying that stratospheric water vapor delivery by convection is likely facilitated by a complex collection of processes in each overshooting event.

Abstract

Methane (CH4) is the second most abundant greenhouse gas and affects the Earth's radiative balance. In some regions, the methane burden and budget are still not well understood due to the lack of in situ observations, especially vertical profile observations. Here, we present the first high-resolution aircraft-based tropospheric vertical profiles of CH4 across the Indian subcontinent. Observations show significant variability, with the largest variability seen in the Indo-Gangetic Plain (IGP) during post-monsoon (September). The IGP also shows the highest concentrations and a peak in the boundary layer. By contrast, observations over western India show lower variability, especially during the Asian Summer Monsoon (ASM) (July). During ASM, when CH4 emissions peak, the vertical updraft of CH4 and other tracers is observed, leading to a peak between 4 and 5 km. During winter, the peak occurs in the boundary layer, and a decrease with altitude is observed. Model simulations slightly overestimate CH4 at the surface during some seasons but underestimate it at higher altitudes during all seasons. Integrated over the observed column, model simulations slightly underpredict CH4 (0.5%–3.1%) during all seasons. Calculations made using the observed CO/CH4 enhancement ratios show that in addition to anthropogenic fossil fuel emissions, other sources, such as rice cultivation and wetlands, need to be considered to reproduce the observed CH4 concentrations.

Seismic isolation is crucial for safeguarding buildings from earthquake damage. While traditional systems are effective, they struggle with multidirectional forces and adequate damping. These challenges highlight the need for innovative solutions that provide enhanced protection against the complex dynamics of seismic activity. Addressing these issues necessitates in-depth research into advanced seismic isolation technologies.

Publication date: August 2024

Source: Journal of Atmospheric and Solar-Terrestrial Physics, Volume 261

Author(s):