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XGC-6D is a geometric full-f Particle-In-Cell code on unstructured meshes including XGC-like unstructured mesh, tetrahedral mesh, etc. The code is particularly suitable to study boundary plasma with steep gradient and frequency higher than ion gyro-frequency. References: Wang Z, Qin H, Sturdevant B, Chang CS. Geometric electrostatic particle-in-cell algorithm on unstructured meshes. Journal of Plasma Physics. 2021;87(4):905870406.
Abstract Cold-air pools (CAPs), or stable atmospheric boundary layers that form within topographic basins, are associated with poor air quality, hazardous weather, and low wind energy output. Accurate prediction of CAP dynamics presents a challenge for mesoscale forecast models in part because CAPs occur in regions of complex terrain, where traditional turbulence parameterizations may not be appropriate. This study examines the effects of the planetary boundary layer (PBL) scheme and horizontal diffusion treatment on CAP prediction in the Weather Research and Forecasting (WRF) Model. Model runs with a one-dimensional (1D) PBL scheme and Smagorinsky-like horizontal diffusion are compared with runs that use a new three-dimensional (3D) PBL scheme to calculate turbulent fluxes. Simulations are completed in a nested configuration with 3-km/750-m horizontal grid spacing over a 10-day case study in the Columbia River basin, and results are compared with observations from the Second Wind Forecast Improvement Project. Using event-averaged error metrics, potential temperature and wind speed errors are shown to decrease both with increased horizontal grid resolution and with improved treatment of horizontal diffusion over steep terrain. The 3D PBL scheme further reduces errors relative to a standard 1D PBL approach. Error reduction is accentuated during CAP erosion, when turbulent mixing plays a more dominant role in the dynamics. Last, the 3D PBL scheme is shown to reduce near-surface overestimates of turbulence kinetic energy during the CAP event. The sensitivity of turbulence predictions to the master length-scale formulation in the 3D PBL parameterization is also explored. Significance Statement In this article, we demonstrate how a new framework for modeling atmospheric turbulence improves cold pool predictions, using a case study from January 2017 in the Columbia River basin (U.S. Pacific Northwest). Cold pools are regions of cold, stagnant air that form within valleys or basins, and improved forecasts could help to mitigate the risks they pose to air quality, transportation, and wind energy production. For the chosen case study, our tests show a reduction in temperature and wind speed errors by up to a factor of 2–3 relative to standard model options. These results strongly motivate continued development of the framework as well as its application to other complex weather events.
This study explores the effect of surface sensible and latent heat fluxes on monsoon depressions using a series of idealized convection-permitting simulations. Each experiment is initialized with a small-amplitude wave that is allowed to grow within an environment representative of the South Asian monsoon. Comparing experiments with and without interactive surface heat fluxes, it is found that these fluxes enhance the growth of the simulated vortices. Without interactive surface fluxes, the strengthening period is short and the vortices fail to reach intensities characteristic of stronger monsoon depressions. Using a large set of experiments in which the vertical and meridional shear are systematically varied, it is found that surface heat fluxes enhance intensity the most when the upper-level shear is weak, the lower-level shear and associated moist static energy (MSE) gradient are sufficiently steep, and the lower-level meridional shear is strong. Here, these experiments reveal two different regimes of convection-coupled monsoon depression growth: one in which convection is driven by MSE advection and one in which it is driven by surface heat fluxes and quasigeostrophic forcing for ascent. Both regimes require sufficiently strong meridional shear to achieve initial growth by barotropic instability.
Accurate estimation of specific differential phase ( K DP ) is necessary for rain rate estimation, attenuation correction, and hydrometeor classification algorithms. There are numerous published methods to process polarimetric radar observations of propagation differential phase shift (Φ DP ) and estimate K DP , but the corresponding K DP estimate uncertainty is unquantified. This study provides guidance on how commonly used K DP estimation algorithms perform in various environments. Here, we create numerous synthetic (“true”) K DP profiles, integrate over them to obtain “smoothed” Φ DP , and then add noise typical of S-band operational weather radar measurements. Each algorithm is applied to our noisy Φ DP profiles and compared to the true K DP profile such that the errors and uncertainty are quantified. The synthetic K DP profiles are Gaussian in shape, which allows systematic variations in their magnitude and width to determine how each algorithm performs in smooth, slowly changing K DP profiles, as well as steep profiles. Results demonstrate that algorithm performance is dependent on the Φ DP field received. These results are further supported by an error analysis of each algorithm for two more complicated synthetic K DP profiles. Some K DP algorithms allow users to change various tuning parameters; a subset of these tuning parameters is tested to provide guidance on how changing these parameters impacts algorithm performance. We then provide evidence that our known-truth framework provides insight into algorithm performance in observed data through two case studies.
Improvements to the Weather Research and Forecasting (WRF) Model are made to enable multiscale simulations over highly complex terrain with dynamically downscaled boundary conditions from the mesoscale to the microscale. Over steep terrain, the WRF Model develops numerical errors that are due to grid deformation of the terrain-following coordinates. An alternative coordinate system, the immersed boundary method (IBM), has been implemented into WRF, allowing for simulations over highly complex terrain; however, the new coordinate system precluded nesting within mesoscale simulations using WRF’s native terrain-following coordinates. Here, the immersed boundary method and WRF’s grid-nesting framework are modified to seamlessly work together. This improved framework for the first time allows for large-eddy simulation over complex (urban) terrain with IBM to be nested within a typical mesoscale WRF simulation. Simulations of the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma, are performed using a multiscale five-domain nested configuration, spanning horizontal grid resolutions from 6 km to 2 m. These are compared with microscale-only simulations with idealized lateral boundary conditions and with observations of wind speed/direction and SF 6 concentrations from a controlled release from intensive observation period 3. The multiscale simulation, which is configured independent of local observations, shows similar model skill predicting wind speed/direction and improved skill predicting SF 6 concentrations when compared with the idealized simulations, which require use of observations to set mean flow conditions. Use of this improved multiscale framework shows promise for enabling large-eddy simulation over highly complex terrain with dynamically downscaled boundary conditions from mesoscale models.
The terrain-following coordinate system used by many atmospheric models can cause numerical instabilities due to discretization errors as resolved terrain slopes increase and the grid becomes highly skewed. The immersed boundary (IB) method, which does not require the grid to conform to the terrain, has been shown to alleviate these errors, and has been used successfully for high-resolution atmospheric simulations over steep terrain, including vertical building surfaces. Since many previous applications of IB methods to atmospheric models have used very fine grid resolution (5 m or less), the present study seeks to evaluate IB method performance over a range of grid resolutions and aspect ratios. Two classes of IB algorithms, velocity reconstruction and shear stress reconstruction, are tested within the common framework of the Weather Research and Forecasting (WRF) Model. Performance is evaluated in two test cases, one with flat terrain and the other with the topography of Askervein Hill, both under neutrally stratified conditions. WRF-IB results are compared to similarity theory, observations, and native WRF results. Despite sensitivity to the location at which the IB intersects the model grid, the velocity reconstruction IB method shows consistent performance when used with a hybrid RANS/LES surface scheme. The shear stress reconstruction IB method is not sensitive to the grid intersection, but is less consistent and near-surface velocity errors can occur at coarse resolutions. This study represents an initial investigation of IB method variability across grid resolutions in WRF. Future work will focus on improving IB method performance at intermediate to coarse resolutions.
Background: Lagoons are common along coastlines worldwide and are important for biogeochemical element cycling, coastal biodiversity, coastal erosion protection and blue carbon sequestration. These ecosystems are frequently disturbed by weather, tides, and human activities. Here, we investigated a shallow lagoon in New England. The brackish ecosystem releases hydrogen sulfide particularly upon physical disturbance, causing blooms of anoxygenic sulfur-oxidizing phototrophs. To study the habitat, microbial community structure, assembly and function we carried out in situ experiments investigating the bloom dynamics over time. Results: Phototrophic microbial mats and permanently or seasonally stratified water columns commonly contain multiple phototrophic lineages that coexist based on their light, oxygen and nutrient preferences. We describe similar coexistence patterns and ecological niches in estuarine planktonic blooms of phototrophs. The water column showed steep gradients of oxygen, pH, sulfate, sulfide, and salinity. The upper part of the bloom was dominated by aerobic phototrophic Cyanobacteria, the middle and lower parts by anoxygenic purple sulfur bacteria (Chromatiales) and green sulfur bacteria (Chlorobiales), respectively. We show stable coexistence of phototrophic lineages from five bacterial phyla and present metagenome-assembled genomes (MAGs) of two uncultured Chlorobaculum and Prosthecochloris species. In addition to genes involved in sulfur oxidation and photopigment biosynthesis the MAGs contained complete operons encoding for terminal oxidases. The metagenomes also contained numerous contigs affiliating with Microviridae viruses, potentially affecting Chlorobi. Our data suggest a short sulfur cycle within the bloom in which elemental sulfur produced by sulfide-oxidizing phototrophs is most likely reduced back to sulfide by Desulfuromonas sp. Conclusions: The release of sulfide creates a habitat selecting for anoxygenic sulfur-oxidizing phototrophs, which in turn create a niche for sulfur reducers. Strong syntrophism between these guilds apparently drives a short sulfur cycle that may explain the rapid development of the bloom. The fast growth and high biomass yield of Chlorobi-affiliated organisms implies that the studied lineages of green sulfur bacteria can thrive in hypoxic habitats. This oxygen tolerance is corroborated by oxidases found in MAGs of uncultured Chlorobi. The findings improve our understanding of the ecology and ecophysiology of anoxygenic phototrophs and their impact on the coupled biogeochemical cycles of sulfur and carbon.
To avoid steep declines in the Tuscaloosa Marine Shale (TMS) production, wells are fracture-stimulated to release the hydrocarbons trapped in the matrix of the formation. An accurate estimation of Young’s modulus and Poisson’s ratio is essential for hydraulic fracture propagation. In addition, ignoring the highly heterogeneous and anisotropic character of TMS can lead to erroneous stress values, which subsequently affect hydraulic fracture width estimates and the overall hydraulic fracturing process. We have developed an empirical 1D geomechanical model that takes into account VTI anisotropy, and it is used to characterize the elastic mechanical properties of TMS in two wells. In the analyzed formation, the vertical Poisson’s ratio is less than the horizontal Poisson’s ratio, which suggests the necessity of an alternative to the ANNIE equations. The stiffness coefficients [Formula: see text] and [Formula: see text] were estimated using the relationships developed from the ultrasonic core data available for the two TMS. Further, correlations between the static and dynamic properties from laboratory tests were used to improve the minimum horizontal stress calculation. We compare VTI Young’s moduli, Poisson’s ratios, and minimum horizontal stress with the isotropic solution. VTI modeling improves the estimation of the elastic mechanical properties. The isotropic solution underestimates the minimum horizontal stress in the formation. Moreover, it was shown that the 20 ft shale interval below the TMS base is characterized by a low Young’s modulus (the vertical Young’s modulus is equal to 20 GPa, whereas the horizontal Young’s modulus is equal to 40 GPa) and may be a frac barrier.
We compared two methods for extracting the azimuth of maximum horizontal stress (SHmax) from 3D land-based seismic data generated by a P source and recorded with vertical geophones. In the first method, we used the direct-SV mode that is produced by all land-based P sources. P sources generate SV illumination that radiates in all azimuth directions from a source station and creates SV-P reflections that are recorded by vertical geophones. Unless stratigraphy has steep dip, SV-P raypaths recorded by vertical geophones are the reverse of P-SV raypaths recorded by horizontal geophones. Thus, SV-P data provide the same S-wave sensitivity to stress fields as popular P-SV data do. In the second method, we retrieved P-P reflections and then performed an amplitude-variation-with-azimuth (AVA) analysis of the amplitude-gradient behavior of P-P reflection wavelets. We did this analysis in narrow azimuth corridors to determine the gradient of reflection-wavelet amplitudes as a function of azimuth. This P-P AVA amplitude-gradient method has been of great interest in the reflection seismology community since it was introduced in the late 1990s. Each of these methods, AVA analysis of the gradient of P-P reflection amplitudes and azimuth-dependent arrival times of SV-P reflections, can be used to determine the azimuth of SHmax stress. We compare the results of the two methods with ground truth measurements of SHmax azimuth at a CO 2 sequestration site in the Michigan Basin. SHmax azimuths were determined from P-P and SV-P data at three major boundaries at depths of approximately 3500 ft (1067 m), 5500 ft (1676 m), and 7500 ft (2286 m). Two estimates of SHmax azimuth (one using SV-P data and one using P-P data) were made at each stacking bin inside a 24 mi 2 (62 km 2 ) image space. The result was approximately 98,000 estimates of SHmax azimuth across each of these three boundaries for each of these two prediction strategies. Histogram displays of PP AVA gradient estimates had peaks at correct azimuths of SHmax at all three depths, but the spread of the distributions widened with depth and split into two peaks at the deepest boundary. In contrast, each histogram of SHmax azimuth predicted by azimuth-dependent SV-P traveltimes had a single, definitive peak that was positioned at the correct SHmax azimuth at all three boundary depths.
Impulsive stimulated Raman scattering (ISRS) is a robust technique for studying low frequency (<300 cm –1 ) Raman vibrational modes, but ISRS has faced difficulty in translation to an imaging modality. A primary challenge is the separation of the pump and probe pulses. Here we introduce and demonstrate a simple strategy for ISRS spectroscopy and hyperspectral imaging that uses complementary steep edge spectral filters to separate the probe beam detection from the pump and enables simple ISRS microscopy with a single-color ultrafast laser source. ISRS spectra are obtained that span from the fingerprint region down to <50 cm –1 vibrational modes. Furthermore, hyperspectral imaging and polarization-dependent Raman spectra are also demonstrated.
Changing environmental conditions are forcing natural resource managers and communities to adapt their strategies to account for global shifts in precipitation, temperature, sea level and more, all of which are occurring in addition to local human impacts. Adapting to threats from climate change requires a fundamental shift in the practice of natural resource management through the development of forward-looking “climate-smart” goals and strategies. Here we present a proof-of-concept application of a decision-support tool to help design climate-smart management actions for the watershed and coral reef management plan for Guánica Bay watershed in southwest Puerto Rico. We also explore the connection between adaptation planning and coral reef resilience, using a recently developed Puerto Rico-wide reef resilience assessment. In the first phase of the study, we used the publicly available Adaptation Design Tool to draft initial climate-smart versions of twelve proposed management actions. In the second phase, two actions (dirt road management on steep slopes, and coral reef restoration) were further refined through consultations with local experts to make more detailed design adjustments; this included the option to use information from the coral reef resilience assessment to inform design improvements. The first phase resulted in moderately detailed assessments that broadly accounted for anticipated direct and indirect effects of climate change on the planned management actions. The second phase resulted in more site-specific technical assessments and additional important design details. The expert panel charged with discussing climate-smart reef restoration around Guánica used the reef resilience assessment to guide discussion of reef restoration, highlighting the importance of having such information available for adaptation planning. This study demonstrates how climate change impacts can be effectively incorporated into a management plan at the most granular level of planning and how a structured, formalized process can be as valuable as the resulting adaptation information.
Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecules in solution due to the need to include large numbers of solvent molecules. We present a machine-learned electron density model based on a Euclidean neural network framework that includes a built-in understanding of equivariance to model explicitly solvated double-stranded DNA. By training the machine learning model using molecular fragments that sample the key DNA and solvent interactions, we show that the model predicts electron densities of arbitrary systems of solvated DNA accurately, resolves polarization effects that are neglected by classical force fields, and captures the physics of the DNA-solvent interaction at the ab initio level.
This dataset contains measurements of the low-energetic magnetic excitations in the heavy-fermion material CeIn3. Neutron spectroscopy data were recorded on a single-crystal mosaic of around 2 g total mass at the spectrometer CNCS. In a first row of measurements with incident neutron energy 12 meV the excitations were mapped out in major parts of the first Brillouin zone. In a second row of measurements with 3.315 meV incident neutron energy, the gapless and relatively steep dispersion in the vicinity of the R-point, corresponding to (1/2,1/2,1/2) in reciprocal space, was investigated.
Established chronologies indicate a long-term ‘Hoabinhian’ hunter-gatherer occupation of Mainland Southeast Asia during the Terminal Pleistocene to Mid-Holocene (45 000–3000 years ago). Here, the authors re-examine the ‘Hoabinhian’ sequence from north-west Thailand using new radiocarbon and luminescence data from Spirit Cave, Steep Cliff Cave and Banyan Valley Cave. The results indicate that hunter-gatherers exploited this ecologically diverse region throughout the Terminal Pleistocene and the Pleistocene–Holocene transition, and into the period during which agricultural lifeways emerged in the Holocene. Hunter-gatherers did not abandon this highland region of Thailand during periods of environmental and socioeconomic change.
Abstract The global shift to electricity as the main energy carrier will require innovation in electrochemical energy storage (EES). EES systems are the key to the “electron energy economy,” minimizing losses and increasing reliability between energy supply and demand. However, steep challenges such as cost, cycle/calendar life, energy density, material availability, and safety limit widespread adoption of batteries for large-scale grid and vehicle applications. Battery innovation that meets today’s challenges will require new chemistries, which can originate from understanding charge transport phenomena at multiple time and length scales. The advancement of operando characterization can expedite this progress as changes can be observed during battery function. This article highlights progress in bulk and interfacial operando characterization of batteries. Specifically, a case study involving Fe 3 O 4 is provided demonstrating that combining X-ray absorption spectroscopy and isothermal microcalorimetry can provide real-time characterization of productive faradaic redox processes and parasitic interfacial reactions during (de)lithiation. Graphic abstract
This is the AmeriFlux version of the carbon flux data for the site US-xTA NEON Talladega National Forest (TALL). Site Description - The TALL terrestrial field site covers 5300 hectares within the larger Oakmulgee District of the Talladega National Forest (475,000 hectares) in west-central Alabama. TALL is located within the Gulf Coastal Plain which is the dominant physiographic province (52%) of NEON's Domain 8: Ozarks Complex. It is also where the upper coastal plain gives rise to the Appalachian foothills. The lands of this region are rich a mosaic of forest types and habitats. Steep ridges to rolling hills fading to hardwood bottoms make up the diversity of forest conditions found in Oakmulgee. While known for its longleaf forests, over 40% of Oakmulgee is covered with a mixture of hardwoods and wetlands.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xTA NEON Talladega National Forest (TALL). This is the FLUXNET version of the carbon flux data for the site US-xTA NEON Talladega National Forest (TALL) produced by applying the standard ONEFlux (1F) software. Site Description - The TALL terrestrial field site covers 5300 hectares within the larger Oakmulgee District of the Talladega National Forest (475,000 hectares) in west-central Alabama. TALL is located within the Gulf Coastal Plain which is the dominant physiographic province (52%) of NEON's Domain 8: Ozarks Complex. It is also where the upper coastal plain gives rise to the Appalachian foothills. The lands of this region are rich a mosaic of forest types and habitats. Steep ridges to rolling hills fading to hardwood bottoms make up the diversity of forest conditions found in Oakmulgee. While known for its longleaf forests, over 40% of Oakmulgee is covered with a mixture of hardwoods and wetlands.
This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xSP NEON Soaproot Saddle (SOAP). This is the FLUXNET version of the carbon flux data for the site US-xSP NEON Soaproot Saddle (SOAP) produced by applying the standard ONEFlux (1F) software. Site Description - The Soaproot Saddle is a complex terrain of coarse hills, steep slopes and narrow drainages. With an elevation of 3274 - 4537’ this site encompasses 1438 acres of mixed conifer forests that are experiencing high levels of mortality due to native Pine beetles. At the core of this site stands a 171’ tall flux tower that collects physical and chemical properties of atmosphere and related process. Soaproot Saddle also hosts an array of sensor measurements along with field observations collected by highly trained NEON staff. The automated instrument measurements and some of the terrestrial observational safor this field site are colocted with NEON's aquatic site, Upper Big Creek, which is located just north of Soaproot Saddle's site boundaries.