Atmospheric Parameters Research Articles

Validation of millimetre and sub-millimetre atmospheric collision-induced absorption at Chajnantor

Due to the importance of a reference atmospheric radiative transfer model for both planning and calibrating ground-based observations at millimetre and sub-millimetre wavelengths, we have undertaken a validation campaign consisting of acquiring atmospheric spectra under different weather conditions, in different diurnal moments and seasons, with the Atacama Pathfinder EXperiment (APEX), due to the excellent stability of its receivers and the very high frequency resolution of its back-ends. As a result, a dataset consisting of 56 spectra within the 157.3-742.1 GHz frequency range, at kilohertz resolution (smoothed to sim 2-10 MHz for analysis), and spanning one order of magnitude (sim 0.35-3.5 mm) in precipitable water vapour columns, has been gathered from October 2020 to September 2022. These data are unique for their quality and completeness and, due to the proximity of APEX to the Atacama Large Millimeter/Submillimeter Array (ALMA), they provide an excellent opportunity to validate the atmospheric radiative transfer model currently installed in the ALMA software. The main issues addressed in the study are possible missing lines in the model, line shapes, vertical profiles of atmospheric physical parameters and molecular abundances, seasonal and diurnal variations, and collision-induced absorption (CIA), to which this paper is devoted, in its N$_2$-N$_2$ + N$_2$-O$_2$ + O$_2$-O$_2$ (dry) and N$_2$-H$_2$O + O$_2$-H$_2$O (`foreign' wet) mechanisms. All these CIA terms should remain unchanged in the above-mentioned ALMA atmospheric model as a result of this work.

Updraft Width Modulates Ambient Atmospheric Controls on Convective Cloud Depth

AbstractThe depth of convective clouds affects vertical transport of atmospheric constituents, influencing downstream weather and climate. Atmospheric controls on the maximum depth reached by moist convection are investigated with radar‐tracked convective cells tagged with sounding‐derived atmospheric parameters from a field campaign in central Argentina. Regression analyses show that narrow (<12‐km diameter) and wide (>16‐km diameter) cell depths respond to disparate factors, where cell areas are defined using composite reflectivity signatures. Undiluted lifted parcel indices including convective available potential energy (CAPE) and level of neutral buoyancy (LNB) are top predictors of wide cell maximum depth while mid‐tropospheric relative humidity is the top predictor of narrow cell maximum depth. Because narrow cells are more numerous than wide cells, the overall outcome of the full cell population does not strongly correlate with CAPE and LNB conditions. Tracked cells and atmospheric conditions in a simulation with 3‐km grid spacing covering the field campaign produce similar results to those observed. Narrow cells that are relatively deep have a cooler and moister mid‐troposphere with weaker free tropospheric subsidence, while relatively deep wide cells have much warmer and moister lower tropospheric conditions. These atmospheric differences are present 1 hr before cell initiation at both a fixed observing site and variable cell initiation locations. Simulated narrow cell maximum equivalent potential temperature decreases with height at a rate similar to the ambient vertical gradient, causing these cells to fall short of their LNB and supporting the view that entrainment‐driven dilution is a dominant control on their depth.

Improving Atmospheric Correction Algorithms for Sea Surface Skin Temperature Retrievals from Moderate-Resolution Imaging Spectroradiometer Using Machine Learning Methods

Satellite-retrieved sea-surface skin temperature (SSTskin) is essential for many Near-Real-Time studies. This study aimed to assess the potential to improve the accuracy of satellite-based SSTskin retrieval in the Caribbean region by using atmospheric correction algorithms based on four readily available machine learning (ML) approaches: eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), Random Forest (RF), and the Artificial Neural Network (ANN). The ML models were trained on an extensive dataset comprising in situ SST measurements and atmospheric state parameters obtained from satellite products, reanalyzed datasets, research cruises, surface moorings, and drifting buoys. The benefits and shortcomings of various ML methods were assessed through comparisons with withheld in situ measurements. The results demonstrate that the ML-based algorithms achieve promising accuracy, with mean biases within 0.07 K when compared with the buoy data and ranging from −0.107 K to 0.179 K relative to the ship-derived SSTskin data. Notably, both XGBoost and RF stand out for their superior correlation and efficacy in the statistical results of validation. The improved SSTskin derived using the ML-based algorithms could enhance our understanding of vital oceanic and atmospheric characteristics and have the potential to reduce uncertainty in oceanographic, meteorological, and climate research.

An Empirical Sample of Spectra of M-type Stars with Homogeneous Atmospheric-parameter Labels

The discrepancies between theoretical and observed spectra, and the systematic differences between various spectroscopic parameter estimates, complicate the determination of atmospheric parameters of M-type stars. In this work, we present an empirical sample of 5105 M-type star spectra with homogeneous atmospheric parameter labels through stellar-label transfer and sample cleaning. We addressed systematic discrepancies in spectroscopic parameter estimates by adopting recent results for Gaia EDR3 stars as a reference standard. Then, we used a density-based spatial clustering of applications with noise to remove unreliable samples in each subgrid of parameters. To confirm the reliability of the stellar labels, a five-layer neural network was utilized, randomly partitioning the samples into training and testing sets. The standard deviations between the predicted and actual values in the testing set are 14 K for T eff, 0.06 dex for logg, and 0.05 dex for [M/H], respectively. In addition, we conducted an internal cross validation to enhance validation and obtained precisions of 11 K, 0.05 dex, and 0.05 dex for T eff, logg, and [M/H], respectively. A grid of 1365 high-signal-to-noise ratio (S/N) spectra and their labels, selected from the empirical sample, was utilized in the stellar parameter pipeline for M-type stars of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), producing an almost seamless Kiel distribution diagram for LAMOST DR10 and DR11 data. The atmospheric parameters for M-type stars from LAMOST DR11 show improved precision compared to the data from DR9, with improvements (for spectra with S/N higher than 10) from 118 to 67 K in T eff, 0.2 to 0.07 dex in logg, and 0.29 to 0.14 dex in [M/H].

A low-cost instrumentation for monitoring of the environmental radioactivity

In this work, a low-cost radiation monitoring instrumentation for measuring the environmental gamma radioactivity together with some atmospheric parameters was designed and produced. The device has been built with market available components. The detector section of the device uses a Si-PIN photo-diode as an active element. A tiny current produced from the energy deposition of gamma rays in silicon is amplified in two stages, firstly with a charge sensitive amplifier (CSA) and secondly with a shaping amplifier (SA). The amplified signal is further processed to be converted into digital pulses for counting. The monitor station is designed to be operated remotely in self-sufficient mode, equipped with LoRA module running at 500 MHz to transfer the data remotely to a base station. The base station also includes a LoRA module to receive the data and stores it in an SD card while an OLED display visualizes the recent measurement. Multiple monitor stations can be used to control the radioactivity level in a field simultaneously. This field could be used inside or outside of an interested facility. The noise limit of the detector developed was determined to be as low as 20 keV photon energy. The low-energy detection limit was conservatively set to 40 keV which was still below the 64 keV of the naturally occurring 234Th. Counting the events for hourly, daily or weekly provide statistically significant data depending on the activity of the interested region. All gamma energies above 40 keV from the decays of naturally occurring radioisotopes can be practically observed with this device. The anomalies can be detected using various mathematical algorithms that can be embedded into the microprocessor and the results can be shared with the public.

Impact of boundary layer parameterizations on simulated seasonal meteorology over North-East India

This study evaluated the accuracy of six planetary boundary layer (PBL) parameterization schemes in simulating two different seasons of pre-monsoon and monsoon in India's North-East region through the Weather Research and Forecasting (WRF) model. Twelve one-month simulations were conducted with the PBL schemes, six each for April (pre-monsoon) and July (monsoon), and the model outputs were compared against observations. Three non-local schemes, Asymmetric Convective Model (ACM2), Yonsei University (YSU), Shin-Hong (HONG), and three local schemes, Quasi Normal Scale Elimination (QNSE), Mellor Yamada Janjic (MYJ) and Mellor Yamada Nakanishi Nino (MYNN3), were tested. The meteorological variables of temperature, relative humidity (RH), wind speed, wind direction, and rainfall were evaluated, and the performance of each scheme for each meteorological variable is reported. The 2m temperature (T2) variable was well simulated by ACM2, MYJ in April, and YSU in July, while MYNN3 best simulated the 2m RH (RH2) during both seasons. 10m wind speed (WS10) and directions (WD10) were better simulated by MYNN3, HONG and YSU. HONG also best-simulated rainfall in April and MYJ in July. April and July being rainfall periods, an analysis of the schemes’ simulated rainfall frequency was also carried out. Moreover, the PBL schemes were also ranked, considering their combined performance with all the above meteorological parameters. While considering both the seasons and all meteorological variables, the scale-aware scheme, HONG, was the best scheme and can be used to simulate both seasons. Additionally, an in-depth analysis of surface and atmospheric parameters was also carried out to reason the simulated meteorology. QNSE expends the highest amount of its surface energy through surface evaporation, leading to the lowest surface skin temperature and T2 predictions. In contrast, MYNN3 produced the lowest mixing, which caused the moistest boundary layer, highest RH, cloud cover, and highly overestimated rainfall. Besides evaluation, which will help to choose a suitable PBL scheme for weather predictions in this region, this study also identifies the characteristics and deficiencies of PBL and surface layer schemes for improvement.

Spatial and temporal analysis of decomposition models in China

This study presents a comprehensive evaluation of 15 decomposition models (12 empirical and 3 atmospheric transmittance models) for estimating diffuse horizontal irradiance at 17 radiation sites in China, using hourly radiation data from 2011 to 2020. Our results show distinct patterns in model performance across different geographical regions, seasons, and sky conditions. The Liu model demonstrates the best overall performance with an RMSE of 78.20 W/m2, while model accuracy shows significant geographical variation, performing best in South and Southeast China (RMSE<70 W/m2) and worst in the Qinghai-Tibet Plateau and Northwest China (RMSE>90 W/m2). Seasonal analysis reveals better performance in winter than in summer, with RMSE differences approaching 40 W/m2, mainly due to the higher proportion of solar elevation angles exceeding 30° in summer. Under different sky conditions (classified by clearness index: 0–0.35 for overcast, 0.35–0.65 for partly cloudy, 0.65–1 for clear skies), most models follow an RMSE pattern of partly cloudy > clear sky > overcast. However, the Reindl2, Boland, DIRINT, and DIRINDEX models deviate from this trend due to their formula structure and sensitivity to atmospheric parameters. To reduce these regional disparities, we propose a new region-specific model selection strategy: the DIRINDEX model for eastern regions, DIRINT for central areas, and Karatasou for western regions. This combined approach reduces the overall RMSE to 73.17 W/m2. This research deepens our understanding of the application of decomposition models in China's complex geographical and climatic conditions, offering valuable references for solar radiation modeling and renewable energy forecasting in diverse climatic regions.

BD+44°493: Chemo-dynamical Analysis and Constraints on Companion Planetary Masses from WIYN/NEID Spectroscopy* *The WIYN Observatory is a joint facility of the University of Wisconsin Madison, Indiana University, NSF NOIRLab, the Pennsylvania State University, Purdue University, and Princeton University. Based on data collected at the Subaru Telescope, which is operated by the National Astronomical Observatory of Japan. Based on observations made

In this work, we present high-resolution (R ∼ 100,000), high signal-to-noise ratio (S/N ∼ 800) spectroscopic observations for the well-known, bright, extremely metal-poor, carbon-enhanced star BD+44°493. We determined chemical abundances and upper limits for 17 elements from WIYN/NEID data, complemented with 11 abundances redetermined from Subaru and Hubble data, using the new, more accurate, stellar atmospheric parameters calculated in this work. Our analysis suggests that BD+44°493 is a low-mass (0.83 M ⊙), old (12.1–13.2 Gyr) second-generation star likely formed from a gas cloud enriched by a single metal-free 20.5 M ⊙ Population III star in the early Universe. With a disk-like orbit, BD+44°493 does not appear to be associated with any major merger event in the early history of the Milky Way. From the precision radial-velocity NEID measurements (median absolute deviation = 16 m s−1), we were able to constrain companion planetary masses around BD+44°493 and rule out the presence of planets as small as msini=2 M J out to periods of 100 days. This study opens a new avenue of exploration for the intersection between stellar archaeology and exoplanet science using NEID.

Near-infrared Spectroscopy of the Sun and Solar Analog Star HD 76151: Compiling an Extensive Line List in the Y, J, H, and K Bands

Determining the physical nature of a star requires precise knowledge of its stellar atmospheric parameters, including effective temperature, surface gravity, and metallicity. This study presents a new atomic line list covering a broad spectral range (1–2.5 μm; YJHK bands) for iron (Fe) and α-elements (Ca, Mg, Ti, Si) to improve stellar parameter determination using near-infrared (NIR) spectroscopy. We highlight the limitations of existing line lists, stemming primarily from inconsistencies in oscillator strengths for ionized iron lines within the Apache Point Observatory Galactic Evolution Experiment DR17. The line list was validated using the high-resolution and high-quality disk-center NIR spectra of the Sun and its solar analog HD 76151. As a result of the spectroscopic analyses, the effective temperature of HD 76151 was calculated as 5790 ± 170 K, surface gravity as 4.35 ± 0.18 cgs, metal abundance as 0.24 ± 0.09 dex, and microturbulence velocity of 0.30−0.3+0.5 km s−1 by combining the optical and NIR line lists. A comparison of the model atmospheric parameters calculated for HD 76151 with the PARSEC isochrones resulted in a stellar mass of 1.053−0.068+0.056M⊙ , radius 1.125−0.011+0.035R⊙ , and an age of 5.5−2.1+2.5 Gyr. For the first time, kinematic and dynamical orbital analyses of HD 76151 using a combination of Gaia astrometric and spectroscopic data showed that the star was born in a metal-rich region within the solar circle and is a member of the thin disk population. Thus, the slightly metal-rich nature of the star, as reflected in its spectroscopic analysis, was confirmed by dynamical orbital analysis.

Atmospheric Turbulence Parameters Deduced from VerticalProfile of Cn2

The proposed framework can capture realistic spatiotemporal variations in atmospheric turbulence parameters based on local meteorological conditions, such as Fried's parameter r0, isoplanatic angles θ0, seeing ε, scintillation rate , and the wavefront coherence time τ0. Those parameters have been deduced from the refractive index structure parameter Two Iraqi locations were compared, specifically the middle and southern borders, and atmospheric turbulence parameters relevant to astronomical observation were measured, lines were drawn at latitudes 34.26° and 28.31°, respectively. The methodology included collecting meteorological data from both sites and performing numerical simulations based on atmospheric turbulence parameters. According to the criteria of air turbulence, the results showed that the middle of Iraq was better than the southern location for astronomical observation.

Precise physical parameters of three late-type eclipsing binary giant stars in the Large Magellanic Cloud

Detached eclipsing binaries (DEBs) allow for the possibility of a precise characterization of their stellar components. They offer a unique opportunity for deriving their physical parameters nearly independent of a model for a number of systems consisting of late-type giant stars. We aim to expand the sample of low-metallicity late-type giant stars with precisely determined parameters. We determine the fundamental parameters, such as the mass and radius, or the effective temperature for three long-period late-type eclipsing binaries from the Large Magellanic Cloud: OGLE-LMC-ECL-25304, OGLE-LMC-ECL-28283, and OGLE-IV LMC554.19.81. Subsequently, we determine the evolutionary stages of the systems. We fit the light curves from the OGLE project and radial velocity curves from high-resolution spectrographs using the Wilson-Devinney code. The spectral analysis was performed with the GSSP code and resulted in the determination of atmospheric parameters such as effective temperatures and metallicities. We used the isochrones provided by the MIST models based on the MESA code to derive the evolutionary status of the stars. We present the first analysis of three DEBs composed of similar helium-burning late-type stars that pass through the blue loop. The estimated masses for OGLE-LMC-ECL-29293 (G4III + G4III) are $M_1=2.898 and $M_2=3.153 $M_ and the stellar radii are $R_1=19.43 and $R_2=19.30 $R_ OGLE-LMC-ECL-25304 (G4III + G5III) has stellar masses of $M_1=3.267 and $M_2=3.229 $M_ and radii of $R_1=23.62 and $R_2=25.10 $R_ OGLE-IV LMC554.19.81 (G2III + G2III) has masses of $M_1=3.165 and $M_2=3.184 $M_ and radii of $R_1=18.86 and $R_2=19.64 $R_ All masses were determined with a precision better than 2&lt;!PCT!&gt; and the precision for the radii is better than 1.5&lt;!PCT!&gt;. The ages of the stars are in the range of 270-341 Myr.

High-Resolution Spaceborne SAR Geolocation Accuracy Analysis and Error Correction

High-accuracy geolocation is crucial for high-resolution spaceborne SAR images. Most advanced SAR satellites have a theoretical geolocation accuracy better than 1 m, but this may be unrealizable with less accurate external data, such as atmospheric parameters and ground elevations. To investigate the actual SAR geolocation accuracy in common applications, we analyze the properties of different geolocation errors, propose a geolocation procedure, and conduct experiments on TerraSAR-X images and a pair of Tianhui-2 images. The results show that based on GNSS elevations, the geolocation accuracy is better than 1 m for TerraSAR-X and 2 m/4 m for the Tianhui-2 reference/secondary satellites. Based on the WorldDEM and the SRTM, additional geolocation errors of 2 m and 4 m are introduced, respectively. By comparing the effectiveness of different tropospheric correction methods, we find that the GACOS mapping method has advantages in terms of resolution and computational efficiency. We conclude that tropospheric errors and ground elevation errors are the primary factors influencing geolocation accuracy, and the key to improving accuracy is to use higher-accuracy DEMs. Additionally, we propose and validate a geolocation model for the Tianhui-2 secondary satellite.

The effects of atmospheric plasma spray parameters on structure and mechanical properties of titanium dioxide coatings

The effects of atmospheric plasma spray parameters on structure and mechanical properties of titanium dioxide coatings

Statistical Analysis of Atmospheric Delay Gradient and Rainfall Prediction in a Tropical Region

In recent years, precipitable water vapor has emerged as a key atmospheric parameter in weather prediction research. However, relying on only one parameter does not always accurately predict rainfall, as other atmospheric parameters also contribute to initiating rain events. In our previous study, we explored a methodology for rainfall forecasting based on the atmospheric delay gradient at an individual station in the tropical region. Commonly referred to as the atmospheric gradient, it accounts for the delay in GNSS signals due to changes in horizontal refractivity while propagating through the troposphere to the ground station. This paper discusses the spatial and temporal correlation of the gradient with precipitation occurring over a region. We have investigated different features, such as gradient magnitude, gradient convergence, and the flux of the atmospheric gradient, to propose potential nowcasting criteria for precipitation in the tropical climatic zone. The atmospheric gradient in the surrounding region orients toward the area of precipitation as the rain event approaches. This gradient gradually alters its orientation and converges toward the region of rainfall at the time of precipitation, introducing the concept of gradient convergence. This phenomenon results in an inward gradient flux at the time of the downpour, which presents a potential parameter for rainfall prediction over an area. We also proposed investigating area sizes of 4° × 4° or 8° × 8°, depending on the gradient feature, to establish a forecasting methodology for rainfall. The weather front in the tropical region begins to initiate 12 h before the actual time of occurrence and advances toward the area where it will have an impact from a more distant location. This article presents a detailed investigation of various features of the atmospheric gradient and its potential to nowcast rainfall for a region, as well as proposes the lead time for long-term weather predictions. Furthermore, a deep neural network has been employed to predict rainfall events for the next 6 h over an area in the tropical region.

Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements

Abstract. Accurately modelling optical snow properties like snow albedo and specific surface area (SSA) are essential for monitoring the cryosphere in a changing climate and are parameters that inform hydrologic and climate models. These snow surface properties can be modelled from spaceborne imaging spectroscopy measurements but rely on digital elevation models (DEMs) of relatively coarse spatial scales (e.g. Copernicus at 30 m), which degrade accuracy due to errors in derived products such as slope and aspect. In addition, snow deposition and redistribution can change the apparent topography, and thereby static DEMs may not be considered coincident with the imaging spectroscopy dataset. Testing in three different snow climates (tundra, maritime, alpine), we established a new method that simultaneously solves snow, atmospheric, and terrain parameters, enabling a solution that is more unified across sensors and introduces fewer sources of uncertainty. We leveraged imaging spectroscopy data from Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and PRecursore IperSpettrale della Missione Applicativa (PRISMA) (collected within 1 h) to validate this method and showed a 25 % increase in performance for the radiance-based method over the static method when estimating SSA. This concept can be implemented in missions such as Surface Biology and Geology (SBG), the Environmental Mapping and Analysis Program (EnMap), and the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME).

Upper Ocean Thermodynamic Response to Coupling Currents to Wind Stress over the Gulf Stream

We use high-resolution coupled atmosphere–ocean model simulations over the Gulf Stream extension region during a winter season to examine the upper ocean thermodynamic response to including current feedback to atmospheric wind stress. We demonstrate that a model that includes current feedback leads to significant changes in the structure and transport of heat throughout the upper ocean in comparison to the same model without current feedback. We find that including the current feedback leads to changes in the upper ocean temperature pattern that match the vorticity pattern. Areas with cyclonic ocean vorticity, typically north of the Gulf Stream extension, correspond to areas with warmer temperatures throughout the water column. Areas with anticyclonic ocean vorticity, typically south of the Gulf Stream extension, correspond to areas with cooler temperatures throughout the water column. We also find that including current feedback leads to an overall reduction in the submesoscale vertical heat flux spectra across all spatial scales, with differences in the submesoscale vertical heat flux corresponding to SST minus mixed layer temperature differences. The direct impact of current feedback on the thermodynamic structure within the upper ocean also has indirect impacts on other aspects of the ocean, such as the energy transfer between the ocean and the atmosphere, ocean stratification, and acoustic parameters.

Machine learning-based modelling of zenith wet delay using terrestrial meteorological data in the Brazilian territory

Abstract. The Zenith Total Delay (ZTD) is one of the primary error sources derived from the neutral atmosphere associated with the GNSS (Global Navigation Satellite Systems) technique. Zenith Wet Delay (ZWD) is the smallest part of the ZTD, but the high variability is caused by spatial-temporal variation, making the modelling of this component a challenging task. Although ZWD is considered an error in GNSS positioning, it is also a variable composed mainly of water vapour and can, therefore, be used for atmospheric investigations, and assists in climate studies for precipitation events. In this work, a model was trained to estimate the delay wet component from surface atmospheric parameters. The training data comes from 29 radiosonde stations around Brazil, for a six-year period (2017 to 2022), with data collected at 12 h UTC (Universal Time Coordinated). The model was validated using the holdout technique, with 70% of the data used in training and 30% for validation (cross-validation analysis). The generated model achieved a RMSE (Root Mean Squared Error) of approximately 38 mm, with an 81% of determination coefficient.

Geophysical Coupling Before Three Earthquake Doublets Around the Arabian Plate

In this study, we analysed lithospheric, atmospheric, and top-side ionospheric magnetic field data six months before the three earthquake doublets occurred in the last ten years around the Arabian tectonic plate. They occurred in 2014, close to Dehloran (Iran), in 2018, offshore Kilmia (Yemen) and in 2022, close to Bandar-e Lengeh (Iran). For all the cases, we considered the equivalent event in terms of total released energy and mean epicentral coordinates. The lithosphere was investigated by calculating the cumulative Benioff strain with the USGS earthquake catalogue. Several atmospheric parameters (aerosol, SO2, CO, surface air temperature, surface latent heat flux humidity, and dimethyl sulphide) have been monitored using the homogeneous data from the MERRA-2 climatological archive. We used the three-satellite Swarm constellation for magnetic data, analysing the residuals after removing a geomagnetic model. The analysis of the three geo-layers depicted an interesting chain of lithosphere, atmosphere, and ionosphere anomalies, suggesting a geophysical coupling before the Dehloran (Iran) 2014 earthquake. In addition, we identified interesting seismic accelerations that preceded the last 20 days, the Kilmia (Yemen) 2018 and Bandar-e Lengeh (Iran) 2022 earthquake doublets. Other possible interactions between the geolayers have been observed, and this underlines the importance of a multiparametric approach to properly understand a geophysical complex topic as the preparation phase of an earthquake.

Physical Parameters and Properties of 20 Cold Brown Dwarfs in JWST

We present a comprehensive analysis of 20 T and Y dwarfs using spectroscopy from the Near-Infrared Spectrograph (NIRSpec) CLEAR/PRISM and Mid-Infrared Instrument (MIRI) low-resolution spectrometer instruments on the James Webb Space Telescope. To characterize the atmospheric parameters, we utilize two atmospheric model grids: the Sonora Elf Owl and ATMO2020++. The effective temperatures derived from the two models are relatively consistent, and metallicities are both close to solar values. However, significant discrepancies are found in other parameters, particularly in surface gravity, with the values obtained from the Sonora Elf Owl models typically being about 1 dex lower than those from the ATMO2020++ models. Further comparisons using the ATMO2020 models highlight that the adiabatic convective process introduced in the ATMO2020++ models has a significant impact on the determination of surface gravity. Using the fitted effective temperatures and absolute parallaxes from the literature, we derive radii for the brown dwarfs, which range from approximately 0.8–1.2 R Jup. The estimated masses and ages, derived using evolutionary tracks, indicate that most brown dwarfs in our sample have masses below 30 M Jup and are younger than 6 Gyr. Specifically, Y dwarfs have masses ranging from 2 to 20 M Jup and ages between 0.1 and 6.7 Gyr. In addition, we discuss the determination of atmospheric parameters using only NIRSpec or MIRI spectra. Comparisons with results from the combined spectra show that the effective temperatures and surface gravities derived solely from NIRSpec spectra are largely consistent with those obtained from the combined spectra.

S-process nucleosynthesis in chemically peculiar binaries

Context. Around half of the heavy elements in the Universe are formed through the slow neutron capture (s-) process, which takes place in thermally pulsing asymptotic giant branch (AGB) stars with masses of 1 − 6 M⊙. The nucleosynthetic imprint of the s-process can be studied by observing the material on the surface of binary barium (Ba), carbon (C), CH, and carbon-enhanced metal-poor (CEMP) stars. Aims. We study the s-process by observing the luminous components of binary systems polluted by a previous AGB companion. Our radial velocity (RV) monitoring program establishes an ongoing collection of binary stars exhibiting enrichment in s-process material for the study of elemental abundances, the production of s-process material, and binary mass transfer. Methods. From high-resolution optical spectra, we measured RVs for 350 stars and derived stellar parameters for approximately 150 stars using ATHOS. For a subsample of 24 chemically interesting stars, we refined our atmospheric parameters using ionization and excitation balance with the Xiru program. We used the MOOG code to compute one-dimensional local thermodynamic equilibrium (1D-LTE) abundances of carbon, magnesium, s-process elements (Sr, Y, Zr, Mo, Ba, La, Ce, Nd, Pb), and Eu to investigate neutron capture events and stellar chemical composition. We estimated dynamical stellar masses via orbital optimization using Markov chain Monte Carlo techniques in the ELC program, and we compared our results with low-mass AGB models in the FUll-Network Repository of Updated Isotopic Tables &amp; Yields (FRUITY) database. Results. In our abundance subsample, we find enhancements in s-process material in spectroscopic binaries, a signature of AGB mass transfer. We add the element Mo to the abundance patterns, and for 12 stars we add Pb detections or upper limits, as these are not known in the literature. Computed abundances are in general agreement with the literature. Comparing our abundances to dilution-modified FRUITY yields, we find correlations in s-process enrichment and AGB mass, which are supported by dynamical modeling from RVs. Conclusions. From our high-resolution observations, we expand heavy element abundance patterns and highlight binarity in our chemically interesting systems. We find trends in s-process element enhancement from AGB stars, and agreement between theoretical and dynamically modeled masses. We investigate evolutionary stages for a small subset of our stars.