Prior work suggests drought exacerbates U.S. air quality by increasing surface ozone concentrations. We analyze 2005-2015 tropospheric column concentrations of two trace gases that serve as proxies for surface ozone precursors retrieved from the OMI/Aura satellite: nitrogen dioxide (ΩNO2; NOx proxy) and formaldehyde (ΩHCHO; VOC proxy). We find 3.5% and 7.7% summer drought enhancements for ΩNO2 and ΩHCHO, respectively, corroborating signals previously extracted from ground-level observations. When we subset by land cover type (using MCD12Q1) and isolate the influences of precipitation and temperature on drought, we find the strongest ΩHCHO drought enhancement (10%) in the woody savannas of the Southeast US. This increase likely reflects biogenic VOC emissions and occurs independently with both high temperature and low precipitation. The strongest ΩNO2 drought enhancement (6.0%) occurs over Midwest US croplands and grasslands, which we infer to reflect the sensitivity of soil NOx emissions to temperature.

Carbonate mineral precipitation via capture of atmospheric CO2 by alkaline-hyperalkaline waters offers a potential strategy-referred to as carbon capture and storage-to mitigate anthropogenic CO2 emissions. Oman ophiolite produces high-pH waters characterized by continuous sequestration of atmospheric CO2. The geochemical and isotopic data of carbonates are utilized to assess the CO2 stored in dolomite-calcite assemblage of the Barzaman Formation. PAAS-normalized REE+Y patterns display increasing LREE, flat HREE, and a positive Eu-anomaly, identical to those of the bulk ocean crust and lower crust. Further, La(+), Ce(-), and Y(+) anomalies in studied samples are missing in the ocean crust, however, present in local groundwater and modern seawater. Carbon and oxygen isotopes show two distinct end-members, heavier dolomite than calcite. The estimated carbonate growth temperatures (18℃ to 65℃) are indistinguishable from literature values. The C-O isotope model of dolomite-calcite assemblage, water, and atmospheric CO2 demonstrates that the C-budget of ophiolite-derived carbonates represent an unequivocal contribution from the latter. Meanwhile, the remaining contributors may include dissolved inorganic carbon (DIC) in waters closely associated with travertines and ophiolite-derived soil exhibiting large variations in their C-O isotope compositions caused by kinetic fractionation leading to isotopic disequilibrium. Taken together, REE+Y patterns and isotopic compositions verify that the carbonates were formed under oxic conditions through alterations triggered by the reaction between ophiolite and meteoric water. A detailed groundwater study is recommended to assess the contribution of atmospheric CO2 in DIC for a thorough estimation of the amount of CO2 sequestered by carbonates of the Barzaman Formation.

In this paper, we present a simple model to forecast global focal mechanisms. This model is based on a simple discrete counting distribution of the global centroid moment tensor catalog and it also includes, using a Bayesian scheme, the a priori information from the Anderson theory of faulting. Our model is tested against independent data of global large earthquakes with Ms≥7. We obtained statistically significant results, demonstrating that this simple model can satisfactorily forecast focal mechanisms at the global scale. These forecasts may inform short- to long-term hazard quantifications that require a finite source characterization, as well as real-time source inversion algorithms.

Several NE-striking sedimentary basins, including the representative Pearl River Mouth Basin, formed under a unified tectonic stress regime in the northern continental margin of the South China Sea during the Cenozoic. Studying the tectonic stress regime of the Pearl River Mouth Basin can provide constraints on the expansion and evolution of the South China Sea. Based on the analysis of high-precision 2D and 3D seismic data, the following results were obtained. (1) The T80 reflection interface (40 Ma) is an important unconformity interface and corresponds to a transformation in the tectonic stress regime. (2) From 40 Ma to 10.5 Ma (T80-T32 reflection interface), the Pearl River Mouth Basin was under an extensional tectonic stress regime with a N-S extensional direction. According to the research results of basins in the north of the South China Sea, a new tectonic evolution model of the South China Sea has been established, in which the South China Sea Oceanic Basin is deemed to have formed through approximately N-S extension under pre-existing tectonic conditions during 40-15.5 Ma. The new model is supported by the seawater depth and the seafloor geomorphy in the South China Sea Ocean Basin.

Energy spectra of ring current protons are crucial to understanding the ring current dynamics. Based on high-quality Van Allen Probes RBSPICE measurements, we investigate the global distribution of the reversed proton energy spectra using the 2013-2016 RBSPICE datasets. The reversed proton energy spectra are characterized by the distinct flux minima around 50 - 100 keV and flux maxima around 200 - 400 keV. Our results show that the reversed proton energy spectrum is prevalent inside the plasmasphere, with the occurrence rates > 90% at L ~ 2 - 4 during geomagnetically quiet periods. Its occurrence also manifests a significant decrease trend with increasing L-shell and enhanced geomagnetic activity. It is indicated that the substorm-associated processes are likely to lead to the disappearances of the reversed spectra. These results provide important clues for exploring the underlying physical mechanisms responsible for the formation and evolution of reversed proton energy spectra.

Several hypotheses about origin of the continental Moho are still debated, suggesting its multi-genetic origin. Here, we present quantitative estimation of the seismic properties and anisotropy of the crust-mantle transition in the Western Alps where newly formed (proto)-continental Moho is unusually shallow. We make use of teleseismic P-to-S converted-waves recorded by 12 stations deployed on top of the Ivrea body (IB), a volume of possibly serpentinised mantle peridotite below exhumed (U)HP crustal rocks. The IB has been mapped by gravity, magnetic, active and passive seismic surveys suggesting an extremely shallow Moho. We demonstrate that the P-to-S converted waves propagating through this region display coupled features: (a) they record expected presence of strong seismic velocity contrast at shallow depth due to the proto-continental Moho; (b) they are decomposed out of the radial plane due to anisotropic properties of rocks involved. The proto-continental Moho is recognized as a sharp increase in S-wave velocity (~0.6 to 1.1 km/s) at shallow depth of 5 to 15 km. The presence of anisotropy within the IB and overlying crustal rocks is testified by back-azimuthal dependence of the amplitude of P-to-S phases. The strength of anisotropy is large (12 ± 2 %) pointing out the presence of metamorphosed/hydrated material (e.g. serpentinite) below the Moho. Anisotropic directions are consistent across Moho in both crust and upper mantle, with a dip of 30° increasing eastward the main profile. The similarity of the anisotropy parameters between crust and upper mantle suggests they have been shaped by same deformation event.

Commonly-occurring stratification and synoptic tendencies lead to liquid clouds and warm precipitation processes in the PBL over large portions of the globe. The climate is so sensitive to these low-level clouds that they are identified in IPCC reports as major uncertainty sources for climate prediction; their representation in GCMs thus needs improvement. PBL clouds have therefore been scrutinized in numerous field campaigns over both ocean and land. The main method for measuring clouds in field campaigns is in-situ airborne probing and, though these data are invaluable, it is widely recognized that spatial and temporal sampling is innately poor. We then turn to remote sensing as a way of drastically improving spatial sampling since it delivers cloud properties over more than a line-of-flight through 3+1D space. The obvious tradeoff is, however, generally complicated connections between remotely-measured radiances and inherent cloud properties of real interest to cloud process modelers. Active remote sensing from below or above the clouds improves vastly over in-situ sampling, but its outcome remains confined to a “ribbon” of vertical profiles ordered in time (from below) or space (from above). Passive imaging has the complimentary problem of delivering a potentially wide horizontal swath of cloud properties, but integrated along the vertical. At least that is the conventional wisdom when it comes to the solar spectrum, where observed radiances from clouds are dominated by multiple scattering. Based on recent results from AirMSPI imaging at 20 km altitude, we challenge the perceived limitation of passive shortwave radiometry to deliver only column-integrated properties. We demonstrate that multi-pixel exploitation of multi-angle spectro-polarimteric imaging at solar wavelengths can be used to extract not only maps of microphysical properties but also 3D cloud structure for both PBL-topped stratiform layers and vertically-developed 3D clouds in convective regimes. A key realization is: airborne and space-based sensors offer radically different spatial and angular sampling opportunities with unique advantages in both cases. We look forward to future PBL-specific missions in space for their global reach. At the same time, there is a clear case for deploying high-altitude imagers in all future campaigns.

Space instruments rely heavily on modeling to predict and understand the instrument response, enabling a determination of the capabilities and resolution. The Bayesian approach provides a framework to incorporate prior knowledge and propagate uncertainty to predict the instrument response. We present an empirical Bayes model for the end-to-end performance of the Helium, Oxygen, Proton, and Electron (HOPE) mass spectrometers aboard the Van Allen Probes mission. In this model, we use a combination of external modeling, laboratory calibration, and expert opinion to construct the time-of-flight spectra and demonstrate good agreement with on-orbit data. The empirical Bayes model is applied to explore doubly charged ions and carbon, nitrogen, oxygen discrimination during the Van Allen Probes mission.

Cloud tomography (CT) is a promising approach in passive remote sensing using space-based imaging sensors like MISR and MODIS. In contrast with current cloud property retrievals in the VNIR-SWIR, which are grounded in 1D radiative transfer (RT), CT embraces the 3D nature of convective clouds. Forster et al. (2020) defined the “veiled core” (VC) of such clouds as the optically deep region where detailed 3D structure of the cloud has little impact on the multi-angle/multi-spectral images as long as average VC extinction and any significant cloud-scale gradient are preserved. Quantitatively, the difference between radiance fields escaping clouds remains commensurate with sensor noise when said clouds differ only in the small-scale distribution of extinction inside their VC. An important corollary for the large and ill-posed CT inverse problem is that the only unknowns of interest for the whole VC are its mean and any cloud-scale vertical trend in the extinction coefficient. Another ramification for CT algorithms under development is that the forward 3D RT model driving the inversion may be vastly simplified in the VC to gain efficiency. We explore that possibility here, assuming radiative diffusion as the simplified RT for the VC. We also describe the relevant RT physics that unfold in the VC and in the outer shell (OS) where detailed spatial structure does matter for image formation. This includes control by the VC of the cloud-scale contrast between brightnesses of illuminated and shaded boundaries, as well as the gradual blurring of spatial structure via directional diffusion with increasing optical distance into the OS. “Transport” space is the merger of 3D (or 1D) physical space and 2D direction space. Cloud image formation involves radiative diffusion processes (i.e., random walks) in both of these spaces, depending on what transport regime prevails. Fortunately for the future of computed CT and of passive cloud remote sensing in general, there is a clear spatial separation: asymptotic limit of radiative diffusion in the VC, standard RT in the OS. A hybrid forward model for CT will make use of this fact. Reference: Forster, L., Davis, A. B., Diner, D. J., & Mayer, B. (2021). Toward Cloud Tomography from Space Using MISR and MODIS: Locating the “Veiled Core” in Opaque Convective Clouds, Journal of the Atmospheric Sciences, 78(1), 155-166.

To provide guidance for the use of reanalysis data in the Central Taklimakan Desert (CTD), multiple reanalysis products are evaluated based on the radiosonde data obtained from two field experiments for the first time in the CTD, including the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5), ECMWF Reanalysis-Interim (ERA-Interim), Japanese 55-year Reanalysis (JRA55), Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA2), and the National Centers for Environmental Prediction-Department of Energy Reanalysis version 2 (NCEP2). The results show that reanalysis temperature (T), specific humidity (Q), geopotential height (GPH), and wind field (U and V components) are consistent with the radiosonde observations in terms of the vertical distribution. In general, ERA5 has the best performance in the CTD during the study period, followed closely by ERA-Interim. However, NCEP2 produces the largest error. The errors of all the reanalysis data show significant diurnal variations, and the diurnal variations differ from each other. Moreover, the results indicate that the reanalysis datasets have largest deviation at 850 hPa (near the ground), which means that the desert region may exist complex interactions between the land surface and the atmosphere. Therefore, more attention should be paid to the description of complex interactions between land and atmosphere over the moving-sand desert region in the numerical models.

Radars detect plasma trails created by the billions of small meteors that impact the Earth’s atmosphere daily, returning data used to infer characteristics of the meteoroid population and upper atmosphere. Researchers use models to investigate the dynamic evolution of the trails, enabling them to better interpret radar results. This paper presents a fully kinetic, 3D code to explore the impacts of three trail characteristics: length, neutral wind speed, and ablation altitude. The simulations characterize the turbulence that develops as the trail evolves and these are compared to radar data. They also show that neutral winds drive the formation of waves and turbulence in trails, and that wave amplitudes increase with neutral wind speed. The finite trail simulations demonstrate that the bulk motion of the trail flows with the neutral wind. A detailed analysis of simulated trail spectra yield spectral widths, and evaluate signal strength as a function of aspect angle. Waves propagate primarily along the length of the trail in all cases, and most power is in modes perpendicular to $\mathit{\vec{B}}$. Persistent waves develop at wavelengths corresponding to the gradient scale length of the original trail. Our results show that the rate at which power drops with respect to aspect angle in meter-scale modes increases from $5.7$ dB/degree to $6.9$ dB/degree with a 15 km increase in altitude. The results will allow researchers to draw more detailed and accurate information from non-specular radar observations of meteors.

Based on previous applications of laser altimetry to planetary geodesy at GSFC, we use the recently developed PyXover software package to analyze altimetric crossovers from the Mercury Laser Altimeter (MLA). Using PyXover, we place new constraints on Mercury’s geodetic parameters via least‐squares minimization of crossover discrepancies. We simultaneously solve for orbital corrections for each MLA ground track, for the geodetic parameters of the IAU‐recommended orientation model for Mercury (pole right‐ascension and declination coordinates, prime meridian rotation rate and librations), and for the Mercury’s Love number h2. We calibrate the formal errors of our solution based on closed‐loop simulations and on the level of robustness against a priori values, data selection, and parametrization. Our solution of the Mercury’s rotational parameters is consistent with published values. In particular, our new estimate for the orientation of the pole places Mercury in a Cassini state, with an obliquity ϵ = 2.031 ± 0.03 arcmin compatible with previous “surface” related measurements. Moreover, we provide a first data‐based estimate of the Love number h2 = 1.55 ± 0.65. The latter is consistent with expectations from models of Mercury’s interior, although its precision does not enable their refinement.

This study explores potential prospects of rare earth elements (REEs) in Mansehra Granitic Complex (MGC), including Mansehra Granite, Hakale Granite, microgranites and leucogranites in northwest Pakistan, as these highly fractionated S-type peraluminous granites have potential for hosting deposits of REEs. Petrographic and geochemical constraints including concentration of mafic minerals, presence of microcline, development of zoning in feldspar, strong negative Eu anomaly, negative Ba, Sr, Nb, Ti and Zr anomalies, and positive Rb and Cs anomaly advocates fractionation of MGC. Similarly, enriched Rb and Ba relative to Sr, high K2O and low CaO, trace element ratios of Rb/Sr, Rb/Ba, K/Ba, Nb/Ta and Zr/Hf, and strongly peraluminous nature with A/CNK > 1.1 are highly indicative of the differentiated nature of the studied granites. Despite of positive response towards fractionation constraints, MGC is overall barren in terms of REE and strategic metals mineralization. The elemental concentrations and trace element ratios of MGC—upon comparison with the recommended values given by different researchers for discrimination between barren and mineralized granites—also fail to prove ore-hosting potential of MGC. The composition of parent magma plays primary role in development of ore deposits. The contradictory behavior of MGC on fractionation graphs and mineralization potential diagrams indicates that parent magma of MGC had low concentration of ore elements.

The solar spectral irradiance (SSI) data set is a key record for studying and understanding the energetics and radiation balance in Earth’s environment. Understanding the long-term variations of the SSI over time scales of the 11-year solar activity cycle and longer is critical for many Sun-climate research topics. There are satellite measurements of the SSI since the 1970s that contribute to understanding the solar variability over Solar Cycles (SC) 21 to 24, with most of these SSI measurements in the ultraviolet and only recently in the visible and near infrared for SC-23 and SC-24. A limiting factor for the accuracy of the previous results is the uncertainties for the instrument degradation corrections. Analyses of the past SSI data sets have identified some irradiance offsets and some small residual instrumental trends. These corrections are applied and then combined with a previous SSI composite data set, called the GSFCSSI2 composite, to provide a new SSI composite, called the LASP GSFC SSI #3 (or SSI3). This improved composite extends the wavelength coverage down to 0.5 nm and up to 1600 nm and the time coverage up to 2020. The solar variability results from the SSI3 are consistent, of course, with the observations from which are used to create the SSI3, but they do differ with some solar variability models, in particular at longer than 900 nm. The development of the SSI3 composite also clarifies the importance of overlapping missions for studying the 11-year solar activity cycle, particularly for wavelengths longer than 200 nm.

The estimation of crustal structure and thickness is instrumental in understanding the formation and evolution of terrestrial planets. Initial planetary missions with seismic instrumentation on board face the additional challenge of dealing with seismic activity levels that are only poorly constrained a priori. For example, the lack of plate tectonics on Mars leads to low seismicity which could in turn hinder the application of many terrestrial data analysis techniques. Here we propose using a joint inversion of receiver functions and apparent incidence angles, which contain information on absolute S-wave velocities of the subsurface. Since receiver function inversions suffer from a velocity depth trade-off, we in addition exploit a simple relation which defines apparent S-wave velocity as a function of observed apparent P-wave incidence angles to constrain the parameter space. We then use the Neighbourhood Algorithm for the inversion of a suitable joint objective function. The resulting ensemble of models is then used to derive uncertainty estimates for each model parameter. In preparation for analysis of data from the InSight mission, we show the application of our proposed method on Mars synthetics and sparse terrestrial data sets from different geological settings using both single and multiple events. We use information theoretic statistical tests as a model selection criteria and discuss their relevance and implications in a seismological framework.

The solar X-ray irradiance is significantly heightened during the course of a solar flare, which can cause radio blackouts due to ionization of the atoms in the ionosphere. As the duration of a solar flare is not related to the size of that flare, it is not directly clear how long those blackouts can persist. Using a random forest regression model trained on data taken from X-ray light curves, we have developed a direct forecasting method that predicts how long the event will remain above background levels. We test this on a large collection of flares observed with GOES-15, and show that it generally outperforms simple linear regression. This forecast is computationally light enough to be performed in real time, allowing for the prediction to be made during the course of a flare.

Bark beetle outbreaks have impacted over 58 million acres of coniferous forest in the Western US since 2000, an area slightly larger than the state of Utah. Most of these beetle-impacted forests are in semi-arid, snow-dominated headwater catchments that generate a disproportionate fraction of water supplies. Limited previous studies have shown severe beetle-kill can cause mixed increases and decreases in streamflow. This study is the first to empirically explore changes in streamflow following a recent spruce beetle outbreak in southwest Colorado using a paired catchment approach. The period following beetle kill (2014-2019) was 0.95° C warmer and 5.8 cm/year drier than the 21-year period prior to the disturbance’s peak (1993-2013). There was no change in streamflow in the control basins after beetle kill. In contrast, post-beetle kill had 34% higher peak flows on average and consistent predictions of >14% increases in streamflow in wetter basins and >20% in drier basins. Our results suggest that higher streamflows are primarily driven by 44% higher runoff efficiencies during the snowmelt period. The increased flows due to beetle kill are occurring at a time when control catchments have unchanged runoff efficiencies. These findings are the first to clearly show streamflow increases following extensive spruce beetle kill in watersheds that contribute water to millions of downstream residents. Moreover, our findings contrast with evidence of unchanged or decreased streamflow following mountain pine beetle kill in nearby parts of Colorado, highlighting the need for better post-disturbance hydrologic predictions in these important montane forests.

We have studied the evolution of the heavy ions that expand in a cold background plasma. Two typical conditions are considered where only the debris ion’s initial total mass is significantly different. The work aims to illustrate the complex scaling behavior of the debris evolution in the early time of the High Altitude Nuclear Explosions (HANE). The simulation is performed via the hybrid model, in which the ions and electrons are treated as classical particles and mass-less fluid, respectively. Due to the imbalance of the electric and magnetic force on the debris ions, these debris particles will evolve into different collective patterns at the later times. These patterns manifest a rather different stopping behavior of the debris ions and an opposite drifting direction of the electron fluid. Further numerical and analytical calculations demonstrate that the imbalance depends not only on the number densities of the plasma ions, but also on the spatial variations of the magnetic fields. Our work reveals that the behavior of the debris ions scales non-linearly with their initial total mass, and this non-linearity complicates the scaling from laser experiment to HANE.