Medium Resolution Research Articles

TOWARDS HIGH RESOLUTION FEATURE MAPPNG WITH SENTINEL-2 IMAGES

Abstract. High resolution feature mapping from medium resolution imageries gained special attention among remote sensing user community with the launch of Copernicus’ Sentinel-2 mission due to its capability to provide global coverage with relatively high revisit time at no cost. In this paper, we have examined and evaluated the potential of high resolution (2.5m) feature mapping from Sentinel-2 imageries with the aid of artificial intelligence. Generative adversarial network (GAN) is used as single image super resolution (SISR) technology in this study. And SPOT satellite imageries are used as corresponding high-resolution images. From qualitative and quantitative analysis of the experimental results found that spectral quality of the generated images is adequate for remote sensing applications. In conclusion, high resolution feature mapping from Sentinel-2 images found to be feasible to a greater extent for remote sensing applications.

LANDSAT 9 IMAGERY BASED MANGROVE FOREST MAPPING USING MAXIMUM LIKELIHOOD CLASSIFIER AND SUPPORT VECTOR MACHINE ALGORITHM

The successful launch of Landsat 9 in 2021 emphasizes the commitment to the continuity of the Landsat mission to provide global medium resolution satellite records. The benefit of the availability of the Landsat dataset is the extraction of information related to mangrove forest cover through mapping, especially in Gili Lawang. The main challenge in mangrove mapping is selecting a classification method that provides the most accurate results. This article aims to explore the use of the Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM) algorithms in the context of mangrove mapping using Landsat 9 imagery on Gili Lawang. The two algorithms show differences in detecting the area of mangrove, non-mangrove and water bodies, respectively for SVM 371.89 ha, 58.11 ha, 3.73 ha; while the MLC algorithm is 328.88 ha, 98.41 ha, and 6.45 ha. The MLC algorithm identifies non-mangrove objects at the outer boundary of Gili Lawang, while SVM identifies the same area as mangrove objects due to the influence of the training area created and low separability. The SVM algorithm has better accuracy with a Kappa statistic of 0.85 compared to MLC with a value of 0.73.
 
 Keywords: Gili Lawang, Landsat 9, Mangrove, Support Vector Machine, Maximum Likelihood Classifier

Multi-scale multi-temporal landscape pattern analysis using high spatial urban scene classification

ABSTRACTUrban landscape pattern analysis is conducive to understanding the land cover distribution and changes and promoting urban spatial layout rationality and sustainable development. Previous research has often used low and medium spatial resolution data to classify urban land cover at the pixel level and then analyse landscape pattern indices. However, the underlying semantic information provided by pixel classification needs to consider the spatial correlation of surface features, and it is challenging to obtain high-level semantic information on urban functional areas and analyse the relationship between human activities and land use. Leveraging the abundant spatial characteristics in high-resolution remote sensing images, high spatial urban scene classification can infer the feature categories and spatial relationships between features to realize higher-level image interpretation and obtain regional urban scene details. And it contributes to urban planning and decision-making, better meeting the different demands. Therefore, this study aims at a novel methodological framework for landscape pattern analysis of cross-temporal multi-scale urban scene classification. The results imply that: (1) The high-resolution images can make up for the lack of information on urban functional zones in low and medium resolution images; (2) Landscape pattern analysis based on scene classification can analyse urban spatial relationships more rationally than traditional research; and (3) With the continuous advancement of urbanization, the urban functional zoning becomes more apparent, and the dominant industries have changed significantly from industry to commerce and services. This study expands the analytical application range of landscape ecology and remote sensing technology and provides new inspirations for urban planning, environmental monitoring, ecological protection.

Orbit determination for the binary Cepheid V1344 Aql

Context. Binary Cepheids play an important role in the investigation of the calibration of the classical Cepheid period-luminosity relationship. Therefore, a thorough study of individual Cepheids belonging to binary systems is necessary. Aims. Our aim is to determine the orbit of the binary system V1344 Aql using newly observed and earlier published spectroscopic and photometric data. Methods. We collected new radial velocity observations using medium resolution (R ≈ 11 000 and R ⪅ 20 000) spectrographs, and we updated the pulsation period of the Cepheid based on available photometric observations using an O − C diagram. Separating the pulsational and orbital radial velocity variations for each observational season (year), we determined the orbital solution for the system using χ2 minimisation. Results. The updated pulsation period of the Cepheid estimated for the epoch of HJD 2458955.83 is 7.476826 days. We determined orbital elements for the first time in the literature. The orbital period of the system is about 34.6 yr, with an eccentricity of e = 0.22.

SPLUS J142445.34–254247.1: An r-process–enhanced, Actinide-boost, Extremely Metal-poor Star Observed with GHOST

We report on a chemo-dynamical analysis of SPLUS J142445.34−254247.1 (SPLUS J1424−2542), an extremely metal-poor halo star enhanced in elements formed by the rapid neutron-capture process (r-process). This star was first selected as a metal-poor candidate from its narrowband S-PLUS photometry and followed up spectroscopically in medium resolution with Gemini-South/GMOS, which confirmed its low-metallicity status. High-resolution spectroscopy was gathered with GHOST at Gemini-South, allowing for the determination of the chemical abundances for 36 elements, from carbon to thorium. At [Fe/H] = −3.39, SPLUS J1424−2542 is one of the lowest-metallicity stars with measured Th and has the highest observed to date, making it part of the “actinide-boost” category of r-process–enhanced stars. The analysis presented here suggests that the gas cloud from which SPLUS J1424−2542 formed must have been enriched by at least two progenitor populations. The light-element (Z ≤ 30) abundance pattern is consistent with the yields from a supernova explosion of metal-free stars with 11.3–13.4 M ⊙, and the heavy-element (Z ≥ 38) abundance pattern can be reproduced by the yields from a neutron star merger (1.66 M ⊙ and 1.27 M ⊙) event. A kinematical analysis also reveals that SPLUS J1424−2542 is a low-mass, old halo star with a likely in situ origin, not associated with any known early merger events in the Milky Way.

Characterizing the effect of scaling errors on the spatial downscaling of mountain vegetation gross primary productivity

ABSTRACT High spatial resolution Gross Primary Productivity (GPP) estimation makes it feasible to better understand the spatial heterogeneity of mountain vegetation photosynthesis. Spatial downscaling is a practical approach to obtaining high resolution GPP estimates, whereas there is almost no attention given to the downscaled biases resulted from the widely reported scaling errors in medium or coarse resolution GPP estimates. To fill the above gap, this study adopted an eco-hydrological model to obtain 960 m resolution distributed GPP estimates (not including scaling errors) and lumped GPP estimates (including scaling errors) over four mountainous watersheds. Then, the distributed and lumped estimates were downscaled from 960 m to 30 m, respectively. Finally, the contribution of reducing scaling errors was characterized by the agreement index (d), BIAS and Root-Mean-Square-Error (RMSE) values between downscaled GPP and referenced GPP (directly generated at the spatial resolution of 30 m). Results showed that a large difference existed between lumped and distributed GPP, with d, BIAS, and RMSE of 0.79, 212, and 334 gC m−2 year−1, demonstrating that the scaling errors should be given enough attention to current coarse resolution GPP estimates. Before considering the scaling errors, large uncertainties were observed in the GPP downscaled from lumped values, with d, BIAS, and RMSE of 0.68, 220, and 480 gC m−2 year−1. After considering the scaling errors, a significant improvement was achieved in the GPP downscaled from distributed values, with an increased d value of 0.81, a decreased BIAS value of 10 gC m−2 year−1, and a decreased RMSE value of 388 gC m−2 year−1, indicating that reducing the medium or coarse resolution scaling errors would effectively improve the spatial downscaling of mountain vegetation GPP. Our study highlights the effect of scaling errors on the spatial downscaling of mountain vegetation productivity, which should be given more attention in the future carbon modeling.

Spatial structure of in situ reflectance in coastal and inland waters: implications for satellite validation

Validation of satellite-derived aquatic reflectance involves relating meter-scale in situ observations to satellite pixels with typical spatial resolution ∼ 10–100 m within a temporal “match-up window” of an overpass. Due to sub-pixel variation these discrepancies in measurement scale are a source of uncertainty in the validation result. Additionally, validation protocols and statistics do not normally account for spatial autocorrelation when pairing in situ data from moving platforms with satellite pixels. Here, using high-frequency autonomous mobile radiometers deployed on ships, we characterize the spatial structure of in situRrs in inland and coastal waters (Lake Balaton, Western English Channel, Tagus Estuary). Using variogram analysis, we partition Rrs variability into spatial and intrinsic (non-spatial) components. We then demonstrate the capacity of mobile radiometers to spatially sample in situRrs within a temporal window broadly representative of satellite validation and provide spatial statistics to aid satellite validation practice. At a length scale typical of a medium resolution sensor (300 m) between 5% and 35% (median values across spectral bands and deployments) of the variation in in situRrs was due to spatial separation. This result illustrates the extent to which mobile radiometers can reduce validation uncertainty due to spatial discrepancy via sub-pixel sampling. The length scale at which in situRrs became spatially decorrelated ranged from ∼ 100–1,000 m. This information serves as a guideline for selection of spatially independent in situRrs when matching with a satellite image, emphasizing the need for either downsampling or using modified statistics when selecting data to validate high resolution sensors (sub 100 m pixel size).

Mapping and Modelling of Land Use Change in Nepal

Land use changes are a common occurrence resulting from different factors in Nepal. There is a need for better understanding of the temporal and spatial change dynamics of land uses as well as their future projections. This paper assesses the land use change and its impact on carbon stocks and provides future scenarios of land use changes and their impacts on carbon stocks. The methods involved classification of medium resolution satellite image using Object Based Image Analysis (OBIA) techniques, analysis of the change across three time frames,modelling the future land use, and assessment of the impacts on carbon stocks. OBIA was used for the image segmentation and image classification for the assessment of land uses present in two different periods i.e. 2010 and 1990. The classification of the images was carried out using the spectral characteristics of the Landsat images. Image indices, i.e., Vegetation Index were used for land use classification.
 The land use changes over time and space was analysed using Geographical Information System (GIS) overlaying techniques. A future scenario model was prepared using Land Change Modeler of IDRISI software. The study has focused on the land use changes and their future projection based on the potential transition of the land uses. The comparison of land use maps from 1990 to 2010 shows that the different pattern of annual land use changes in different districts such as forest areas are increasing at annual rate of 0.3 per cent in Rasuwa, 2.3 percent in Gorkha and 0.6 per cent in Chitwan. Similarly, the agricultural land is decreasing at the annual rate of 0.2 per cent in Rasuwa, 2.4 per cent in Gorkha and 0.8 per cent in Chitwan. Likewise, the future projection of land uses in all the three sites was made using the previous land use pattern and driving forces. There was a 0.1 per cent change annually in forest coveragein both Gorkha and Rasuwa whereas Chitwan showed higher rate of forest cover change of 0.2 per cent annually.

Polar Cloud Detection of FengYun-3D Medium Resolution Spectral Imager II Imagery Based on the Radiative Transfer Model

The extensive existence of high-brightness ice and snow underlying surfaces in polar regions presents notable complexities for cloud detection in remote sensing imagery. To elevate the accuracy of cloud detection in polar regions, a novel polar cloud detection algorithm is proposed in this paper. Employing the MOD09 surface reflectance product, we compiled a database of monthly composite surface reflectance in the shortwave infrared bands specific to polar regions. Through the forward simulation of the correlation between the apparent reflectance and surface reflectance across diverse conditions using the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) radiative transfer model, we established a dynamic cloud detection model for the shortwave infrared channels. In contrast to a machine learning algorithm and the widely used MOD35 cloud product, the algorithm introduced in this study demonstrates enhanced congruence with the authentic cloud distribution within cloud products. It precisely distinguishes between the cloudy and clear-sky pixels, achieving rates surpassing 90% for both, while maintaining an error rate and a missing rate each under 10%. The algorithm yields positive results for cloud detection in polar regions, effectively distinguishing between ice, snow, and clouds. It provides robust support for comprehensive and long-term cloud detection efforts in polar regions.

JWST Detects Neon Line Variability in a Protoplanetary Disk

We report the first detection of variability in the mid-infrared neon line emission of a protoplanetary disk by comparing a JWST Mid-InfraRed Instrument Medium Resolution Spectrometer spectrum of SZ Cha taken in 2023 with a Spitzer Infrared Spectrograph Short-High spectrum of this object from 2008. We measure the [Ne iii]-to-[Ne ii] line flux ratio, which is a diagnostic of the high-energy radiation field, to distinguish between the dominance of EUV- or X-ray-driven disk photoevaporation. We find that the [Ne iii]-to-[Ne ii] line flux ratio changes significantly from ∼1.4 in 2008 to ∼0.2 in 2023. This points to a switch from EUV-dominated to X-ray-dominated photoevaporation of the disk. We present contemporaneous ground-based optical spectra of the Hα emission line that show the presence of a strong wind in 2023. We propose that this strong wind prevents EUV radiation from reaching the disk surface while the X-rays permeate the wind and irradiate the disk. We speculate that at the time of the Spitzer observations, the wind was suppressed and EUV radiation reached the disk. These observations confirm that the MIR neon emission lines are sensitive to changes in high-energy radiation reaching the disk surface. This highlights the [Ne iii]-to-[Ne ii] line flux ratio as a tool to gauge the efficiency of disk photoevaporation in order to provide constraints on the planet formation timescale. However, multiwavelength observations are crucial to interpret the observations and properly consider the star–disk connection.

Ejecta, Rings, and Dust in SN 1987A with JWST MIRI/MRS

Supernova (SN) 1987A is the nearest supernova in ∼400 yr. Using the JWST MIRI Medium Resolution Spectrograph, we spatially resolved the ejecta, equatorial ring (ER), and outer rings in the mid-infrared 12,927 days (35.4 yr) after the explosion. The spectra are rich in line and dust continuum emission, both in the ejecta and the ring. The broad emission lines (280–380 km s−1 FWHM) that are seen from all singly-ionized species originate from the expanding ER, with properties consistent with dense post-shock cooling gas. Narrower emission lines (100–170 km s−1 FWHM) are seen from species originating from a more extended lower-density component whose high ionization may have been produced by shocks progressing through the ER or by the UV radiation pulse associated with the original supernova event. The asymmetric east–west dust emission in the ER has continued to fade, with constant temperature, signifying a reduction in dust mass. Small grains in the ER are preferentially destroyed, with larger grains from the progenitor surviving the transition from SN into SNR. The ER dust is fit with a single set of optical constants, eliminating the need for a secondary featureless hot dust component. We find several broad ejecta emission lines from [Ne ii], [Ar ii], [Fe ii], and [Ni ii]. With the exception of [Fe ii] 25.99 μm, these all originate from the ejecta close to the ring and are likely to be excited by X-rays from the interaction. The [Fe ii] 5.34 to 25.99 μm line ratio indicates a temperature of only a few hundred K in the inner core, which is consistent with being powered by 44 Ti decay.

MINDS

Context. The Mid-InfraRed Instrument (MIRI) Medium Resolution Spectrometer (MRS) on board the James Webb Space Telescope (JWST) allows us to probe the inner regions of protoplanetary disks, where the elevated temperatures result in an active chemistry and where the gas composition may dictate the composition of planets forming in this region. The disk around the classical T Tauri star Sz 98, which has an unusually large dust disk in the millimetre with a compact core, was observed with the MRS, and we examine its spectrum here. Aims. We aim to explain the observations and put the disk of Sz 98 in context with other disks, with a focus on the H2O emission through both its ro-vibrational and pure rotational emission. Furthermore, we compare our chemical findings with those obtained for the outer disk from Atacama Large Millimeter/submillimeter Array (ALMA) observations. Methods. In order to model the molecular features in the spectrum, the continuum was subtracted and local thermodynamic equilibrium (LTE) slab models were fitted. The spectrum was divided into different wavelength regions corresponding to H2O lines of different excitation conditions, and the slab model fits were performed individually per region. Results. We confidently detect CO, H2O, OH, CO2, and HCN in the emitting layers. Despite the plethora of H2O lines, the isotopo-logue H218O is not detected. Additionally, no other organics, including C2H2, are detected. This indicates that the C/O ratio could be substantially below unity, in contrast with the outer disk. The H2O emission traces a large radial disk surface region, as evidenced by the gradually changing excitation temperatures and emitting radii. Additionally, the OH and CO2 emission is relatively weak. It is likely that H2O is not significantly photodissociated, either due to self-shielding against the stellar irradiation, or UV shielding from small dust particles. While H2O is prominent and OH is relatively weak, the line fluxes in the inner disk of Sz 98 are not outliers compared to other disks. Conclusions. The relative emitting strength of the different identified molecular features points towards UV shielding of H2O in the inner disk of Sz 98, with a thin layer of OH on top. The majority of the organic molecules are either hidden below the dust continuum, or not present. In general, the inferred composition points to a sub-solar C/O ratio (<0.5) in the inner disk, in contrast with the larger than unity C/O ratio in the gas in the outer disk found with ALMA.

Impact of segmentation algorithms on multisensor LULC classification in a semiarid Mediterranean area

Geographic object-based image analysis methods usually provide better results than pixel-based methods for classifying land use and land cover from high and medium resolution satellite imagery. This study compares the results of Random Forest (RF) and Multilayer Perceptron (MLP) when used to classify the segments obtained on an RGB+NIR Sentinel-2 image using three different segmentation algorithms, Multiresolution (MR), Region Growing (RG), and Mean-Shift (MS). The hyperparameters of these algorithms were optimised minimising the intra-object heterogeneity and maximizing the inter-object heterogeneity, integrating them in an optimization loop. Geometric and two different centrality and dispersion statistics were computed from some Sentinel-1, Sentinel-2 and LiDAR variables over the segments, and used as features to classify the datasets. The highest segment cross-validation accuracies were obtained with RF using MR segments: 0.9048 (k=0.8905), while the highest accuracies calculated with test pixels were obtained with MLP using MR segments: 0.9447 (k=0.9303), both with the mean and standard deviation of the feature set. Although the overall accuracy is quite high, there are problems with some classes in the confusion matrix and, significant misclassification appear when a qualitative analysis of the final maps is performed, indicating that the accuracy metrics may be overestimated and that a qualitative analysis of the results may also be necessary.

Detection of 12 426 SB2 candidates in the LAMOST-MRS, using a binary spectral model

ABSTRACT We use an updated method for the detection of double-lined spectroscopic binaries (SB2s) using Vsin i values from spectral fits. The method is applied to all spectra from Large sky Area Multi-Object fiber Spectroscopic Telescope Medium Resolution Survey. Using this method, we detect 12 426 SB2 candidates, where 4321 are already known and 8105 are new discoveries. We check their spectra manually to minimize possible false positives. We also detect several cases of contamination of the spectra by solar light. Additionally, for candidates with multiple observations, we compute mass ratios with systemic velocities and determine Keplerian orbits. We present an updated catalogue of all SB2 candidates together with additional information for some of them in separate data tables.

Spectroscopic triples and a chance alignment: a solution for the problem of suspicious mass ratios for SB2s from Wilson method

ABSTRACT We selected three double-lined spectroscopic binary systems which have extreme mass ratios, if measured using the Wilson method. We analysed medium resolution spectroscopic observations and space-based photometry and find that all these systems are not SB2, but rather triple systems and a chance alignment of another star with SB1 that have an unseen component. Therefore, suspicious mass ratios determined by the Wilson method for some double-lined spectroscopic binary systems aren’t correct as these systems are more complex.

Deep learning and automatic reference label harvesting for Sentinel-1 SAR-based rapid tropical dry forest disturbance mapping

The advent of temporally dense radar data such as the Sentinel-1 SAR have opened the door for rapid forest disturbance detection in the humid tropics. Tropical dry forest disturbance detection, however, were challenged by seasonality and more open canopy characteristics. In this manuscript, we proposed a Sentinel-1 SAR and deep learning based rapid forest disturbance detection approach for tropical dry forests. We demonstrated a weakly supervised method for reference label harvesting based on medium resolution globally available forest and forest disturbance maps. We trained a deep neural network model to derive forest and forest disturbance probabilities from Sentinel-1 images in the first step. We then implemented a probabilistic disturbance detection and refinement method to map forest disturbances in near real-time in two test regions in Paraguay and Mozambique. We mapped new forest disturbances in an emulated near real-time scenario for 2020 and 2021 and evaluated the spatial accuracy of the disturbance alerts by generating area adjusted precision, recall and F-1 score. We also evaluated the improvement in timeliness of disturbance detection by estimating mean time difference of disturbance events detection with that of Landsat-based GLAD alerts. The generated alerts in Paraguay and Mozambique achieved a precision, recall and F-1 score of 0.99, 0.61, 0.75 and 0.97, 0.51, 0.66, respectively. The proposed method detected disturbances with a mean of 21 days (± 18 days) earlier in Paraguay and 18 days (± 18 days) earlier in Mozambique than the Landsat-based GLAD alerts. These results demonstrated the efficacy of the proposed method and its viability to be used in an operational setting to generate large area rapid near real-time disturbance alerts in the dry tropics.

A new approach to quantify chlorophyll-a over inland water targets based on multi-source remote sensing data

Chlorophyll-a (Chl-a) concentration is a reliable indicator of phytoplankton biomass and eutrophication, especially in inland waters. Remote sensing provides a means for large-scale Chl-a estimation by linking the spectral water-leaving signal from the water surface with in situ measured Chl-a concentrations. Single-sensor images cannot meet the practical needs for long-term monitoring of Chl-a concentrations due to cloud cover and satellite operational lifetimes. However, quantifying long-term inland water Chl-a concentrations using multi-source remote sensing data remains a problem, as improper input of satellite reflectance products will affect the accuracy of Chl-a over inland waters, as well as existing models cannot meet the need for multi-source remote sensing data to retrieve high precision Chl-a. To explore these problems towards a solution, four reflectance data derived from Ocean and Land Colour Instrument (OLCI), MultiSpectral Instrument (MSI), and Operational Land Imager (OLI) were evaluated against in situ measurements of Erhai Lake. Reflectance data from these sensors were assessed to determine their consistency. Results indicate that R_rhos products (i.e., surface reflectance, a semi-atmospheric correction reflectance) that controlled for the atmospheric diffuse transmittance were highly correlated with the measured reflectance values. The in situ reflectance also confirmed the higher fidelity of satellite reflectance in the green-red band. Subsequently, a new extreme gradient boosting (XGB) model applied to multi-source remote sensing data is proposed to estimate long-term inland water Chl-a concentrations. Comparative experiments showed the XGB model with R_rhos products outperformed other solutions, providing accurate estimates for daily, monthly, and long-term trends in Erhai Lake. The XGB model was finally processed 3954 R_rhos reflectance data derived from OLCI, ENVISAT Medium Resolution Imaging Spectrometer (MERIS), MSI, and OLI sensors, mapping Chl-a concentrations in Erhai Lake over a 20-year period. This study could serve as a reference for the long-term Chl-a monitoring using multi-source remote sensing data to support inland lake management and future water quality evaluation.

DMD Based Multi-Object Spectrograph for INdian Spectroscopic and Imaging Space Telescope: INSIST

INdian Spectroscopic and Imaging Space Telescope (INSIST) is the next-generation UV-Optical space mission proposed by the Indian Astronomical community motivated by the great success of India’s first multi-wavelength Astronomical satellite (ASTROSAT) where Ultra Violet Imaging Telescope (UVIT) was one of the main payload launched in 2015 by Indian Space Research Organisation. INSIST is primarily designed for photometry observation in three bands (g-[400[Formula: see text]nm–550[Formula: see text]nm], u-[300[Formula: see text]nm–400[Formula: see text]nm] and UV-[150[Formula: see text]nm–300[Formula: see text]nm]) simultaneously over 0.25 sq.degree field of view. INSIST is equipped with a low resolution [[Formula: see text]] spectrograph for multi-Object slitless spectroscopy over the imaging field of view and also has a medium resolution [[Formula: see text]] spectrograph for multi-object slit spectroscopy in UV-band over ∼6 sq.arcmin sky. MEMS-based Digital Micromirror Device [DMD] is used to form configurable slits for the selection of objects at the focal plane of the telescope for multi-object slit spectrograph. Multi-Object spectrograph with DMD as a re-configurable slit for INSIST is designed and the performance of the spectrograph is presented.

JADES: Discovery of extremely high equivalent width Lyman-α emission from a faint galaxy within an ionized bubble at z = 7.3

We report the discovery of a remarkable Lyα emitting galaxy at z = 7.2782, JADES-GS+53.16746−27.7720 (shortened to JADES-GS-z7-LA), with rest-frame equivalent width, EW0(Lyα) = 388.0 ± 88.8 Å and UV magnitude −17.0. The spectroscopic redshift is confirmed via rest-frame optical lines [O II], Hβ and [O III] in its JWST/NIRSpec Micro-Shutter Assembly (MSA) spectrum. The Lyα line is detected in both lower resolution (R ∼ 100) PRISM as well as medium resolution (R ∼ 1000) G140M grating spectra. The line spread function-deconvolved Lyα full width at half maximum in the grating is 383.9 ± 56.2 km s−1 and the Lyα velocity offset compared to the systemic redshift is 113.3 ± 80.0 km s−1, indicative of very little neutral gas or dust within the galaxy. We estimate the Lyα escape fraction to be > 70%. JADES-GS-z7-LA has a [O III]/[O II] ratio (O32) of 11.1 ± 2.2 and a ([O III] + [O II])/Hβ ratio (R23) of 11.2 ± 2.6, consistent with low metallicity and high ionization parameters. Deep NIRCam imaging also revealed a close companion source (separated by 0.23″), which exhibits similar photometry to that of JADES-GS-z7-LA, with a photometric excess in the F410M NIRCam image consistent with [O III] + Hβ emission at the same redshift. The spectral energy distribution of JADES-GS-z7-LA indicates a “bursty” star formation history, with a low stellar mass of ≈107 M⊙. Assuming that the Lyα transmission through the intergalactic medium is the same as its measured escape fraction, an ionized region of size > 1.5 pMpc is needed to explain the high Lyα EW and low velocity offset compared to systemic seen in JADES-GS-z7-LA. Owing to its UV-faintness, we show that it is incapable of single-handedly ionizing a region large enough to explain its Lyα emission. Therefore, we suggest that JADES-GS-z7-LA (and possibly the companion source) may be a part of a larger overdensity, presenting direct evidence of overlapping ionized bubbles at z > 7.

Impact of lateral melting on Arctic sea ice simulation in a coupled climate model

Lateral melting is an important process driving the sea ice decay, yet it is not well represented in many Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This study explores the impact of lateral melting on Arctic sea ice simulation by implementing lateral melting and floe size parameterization schemes in the medium resolution version of the Beijing Climate Center Climate System Model. Results from a series of CMIP6 historical-type experiments indicate that inclusion of lateral melting results in a reduction in both the Arctic sea ice concentration and thickness, thus improving the sea ice extent and volume simulation. Lateral melting increases open waters, leading to an enhanced net sea surface heat flux into the ocean and further increased lateral and bottom melting. This positive feedback is intensified from 1982 to 2014, particularly when the floe size parameterization scheme is introduced. This accelerates the Arctic sea ice decline from 1982 to 2014 in the model, which is more consistent with observations. Further analysis indicates that the enhancement of this feedback is associated with accelerated lateral melting due to the increased (decreased) trend of the sea surface temperature (floe size) from 1982 to 2014. This study highlights that sea ice lateral melting is an important factor affecting the simulation of Arctic sea ice decline and needs to be better represented in current climate models.