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This paper presents a reconfigurable intelligent surface (RIS) design and simulation aimed at enhancing beamforming and beam steering capabilities for 5G and 6G mobile communications. The proposed design introduces a 2- bit unit cell design, having four distinct phase states that can be tuned by a single varactor diode. This configuration has a 5x5 array and provides efficient operation at 23.8 GHz within the 5G New Radio (NR) frequency range 2 (FR2). The proposed RIS design demonstrates unique beam steering capabilities ranging from −60∘ to 60∘ in the azimuth plane which is crucial for extending coverage into the mm-wave coverage. The performance of the RIS is simulated using the CST 3D electromagnetic simulator, focusing on radar cross section (RCS) pattern for optimization. The simulation results reveal effective beam steering capabilities ranging from -10° to -60° and 10° to 60°, with a minimum scan loss of approximately 3 dB. The proposed RIS exhibits the high angular reciprocity that handles the incident waves up to 110∘ at an oblique 60∘ angle. 

Abstract Climate-driven permafrost thaw can release ancient carbon to the atmosphere, begetting further warming in a positive feedback loop. Polar ice core data and young radiocarbon ages of dissolved methane in thermokarst lakes have challenged the importance of this feedback, but field studies did not adequately account for older methane released from permafrost through bubbling. We synthesized panarctic isotope and emissions datasets to derive integrated ages of panarctic lake methane fluxes. Methane age in modern thermokarst lakes (3132 ± 731 years before present) reflects remobilization of ancient carbon. Thermokarst-lake methane emissions fit within the constraints imposed by polar ice core data. Younger, albeit ultimately larger sources of methane from glacial lakes, estimated here, lagged those from thermokarst lakes. Our results imply that panarctic lake methane release was a small positive feedback to climate warming, comprising up to 17% of total northern hemisphere sources during the deglacial period. 

Abstract Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present‐day greenhouse gas (GHG) budgets. We compare bottom‐up (data‐driven upscaling and process‐based models) and top‐down (atmospheric inversion models) budgets of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom‐up approaches estimate higher land‐to‐atmosphere fluxes for all GHGs. Both bottom‐up and top‐down approaches show a sink of CO₂in natural ecosystems (bottom‐up: −29 (−709, 455), top‐down: −587 (−862, −312) Tg CO₂‐C yr⁻¹) and sources of CH₄(bottom‐up: 38 (22, 53), top‐down: 15 (11, 18) Tg CH₄‐C yr⁻¹) and N₂O (bottom‐up: 0.7 (0.1, 1.3), top‐down: 0.09 (−0.19, 0.37) Tg N₂O‐N yr⁻¹). The combined global warming potential of all three gases (GWP‐100) cannot be distinguished from neutral. Over shorter timescales (GWP‐20), the region is a net GHG source because CH₄dominates the total forcing. The net CO₂sink in Boreal forests and wetlands is largely offset by fires and inland water CO₂emissions as well as CH₄emissions from wetlands and inland waters, with a smaller contribution from N₂O emissions. Priorities for future research include the representation of inland waters in process‐based models and the compilation of process‐model ensembles for CH₄and N₂O. Discrepancies between bottom‐up and top‐down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well‐distributed in situ GHG measurements and improved resolution in upscaling techniques. 

Abstract While basaltic volcanism is dominant during rifting and continental breakup, felsic magmatism may be a significant component of some rift margins. During International Ocean Discovery Program (IODP) Expedition 396 on the continental margin of Norway, a graphite‐garnet‐cordierite bearing dacitic unit (the Mimir dacite) was recovered in two holes within early Eocene sediments on Mimir High (Site U1570), a marginal high on the Vøring Transform Margin. Here, we present a comprehensive textural, petrological, and geochemical study of the Mimir dacite in order to assess its origin and discuss the geodynamic implications. The major mineral phases (garnet, cordierite, quartz, plagioclase, alkali feldspar) are hosted in a fresh rhyolitic, vesicular, glassy matrix that is locally mingled with sediments. The major element chemistry of garnet and cordierite, the presence of zircon inclusions with inherited cores, and thermobarometric calculations all support an upper crustal metapelitic origin. While most magma‐rich margin models favor crustal anatexis in the lower crust, thermobarometric calculations performed here show that the Mimir dacite was produced at upper‐crustal depths (<5 kbar, 18 km depth) and high temperature (750–800°C) with up to 3 wt% water content. In situ U‐Pb analyses on zircon inclusions give a magmatic crystallization age of 54.6 ± 1.1 Ma, consistent with emplacement that post‐dates the Paleocene‐Eocene Thermal Maximum. Our results suggest that the opening of the Northeast Atlantic was associated with a phase of low‐pressure, high‐temperature crustal anatexis preceding the main phase of magmatism. 

The accelerated warming conditions of the high Arctic have intensified the extensive thawing of permafrost. Retrogressive thaw slumps (RTSs) are considered as the most active landforms in the Arctic permafrost. An increase in RTSs has been observed in the Arctic in recent decades. Continuous monitoring of RTSs is important to understand climate change-driven disturbances in the region. Manual detection of these landforms is extremely difficult as they occur over exceptionally large areas. Only very few studies have explored the utility of very high spatial resolution (VHSR) commercial satellite imagery in the automated mapping of RTSs. We have developed deep learning (DL) convolution neural net (CNN) based workflow to automatically detect RTSs from VHRS satellite imagery. This study systematically compared the performance of different DLCNN model architectures and varying backbones. Our candidate CNN models include: DeepLabV3+, UNet, UNet++, Multi-scale Attention Net (MA-Net), and Pyramid Attention Network (PAN) with ResNet50, ResNet101 and ResNet152 backbones. The RTS modeling experiment was conducted on Banks Island and Ellesmere Island in Canada. The UNet++ model demonstrated the highest accuracy (F1 score of 87%) with the ResNet50 backbone at the expense of training and inferencing time. PAN, DeepLabV3, MaNet, and UNet, models reported mediocre F1 scores of 72%, 75%, 80%, and 81% respectively. Our findings unravel the performances of different DLCNNs in imagery-enabled RTS mapping and provide useful insights on operationalizing the mapping application across the Arctic. 

We present our work on constructing a template Baryonic Tully-Fisher Relation (BTFR) from galaxies in the local universe that have primary distances. We utilize HI 21 cm line data from the complete Arecibo Legacy Fast ALFA (ALFALFA) survey and the digital HI archive from Springob et al. 2005; we also use photometry from the Sloan Digital Sky Survey (SDSS) and the NASA Sloan Atlas (NSA) MANGA v1_0_2 database; lastly, we have also made use of the Extragalactic Distance Database (EDD) for identifying galaxies with primary distances. After cross-matching the galaxies in these catalogues, we identify some 144 galaxies which meet our requirements for having all the necessary HI and photometry data, having primary distances, residing within 30 Mpc, and having low enough uncertainties to be considered reliable data points. An important trait of this data set is the prominence of low-mass, low-luminosity dwarves. Notably, we find the values for the slope, intercept and intrinsic scatter of the relation to be around 2.3, 4.8, and 0.4, respectively. Further, while unresolved velocity widths have historically produced shallower slopes, and while the BTFR has been shown to have a higher intrinsic scatter for low-mass galaxies, these precedents are not enough to explain the deviation of our data from the “standard” values of the BTFR. This work therefore raises several questions about why this discrepancy exists, how it can be resolved, and what we can learn from it. The authors would like to acknowledge the support of NSF/AST-1714828 and the Brinson Foundation. 

The pressing nature of climate change and its associated impacts requires a climate literate citizenry. Climate change education in K-12 settings may provide a unique opportunity to make inroads towards climate literacy. However, many K-12 teachers avoid teaching climate change because they are uncomfortable with the subject or do not see its relevance to their curriculum. Removing barriers to climate change professional development (CCPD) for teachers may help increase confidence in teaching about climate change. To understand the perceived barriers to participating in CCPD, a survey was conducted with 54 middle school science teachers who did not respond to a previous invitation to participate in a CCPD program. The most significant barrier was time to participate. The participants were also asked to rate their confidence about whether climate change is happening. The results were compared between teachers who were confident climate change was happening and those who were not to examine whether these beliefs influenced teachers’ perceptions of barriers. Those who were confident climate change was happening were less likely to perceive administrative support, interest in the workshop, and knowledge of climate change content as barriers. However, both groups of teachers reported that time was the primary barrier rather than the topic. This suggests that, rather than developing unique strategies, existing best practices in teacher professional development can be used to support CCPD opportunities. Additional recommendations include thinking creatively about how to create time for teachers to attend and making the professional development directly relevant to teacher’s local contexts. 

The sources of atmospheric methane (CH4) during the Holocene remain widely debated, including the role of high latitude wetland and peatland expansion and fen-to-bog transitions. We reconstructed CH4 emissions from northern peatlands from 13,000 before present (BP) to present using an empirical model based on observations of peat initiation (>3600 14C dates), peatland type (>250 peat cores), and contemporary CH4 emissions in order to explore the effects of changes in wetland type and peatland expansion on CH4 emissions over the end of the late glacial and the Holocene. We find that fen area increased steadily before 8000 BP as fens formed in major wetland complexes. After 8000 BP, new fen formation continued but widespread peatland succession (to bogs) and permafrost aggradation occurred. Reconstructed CH4 emissions from peatlands increased rapidly between 10,600 BP and 6900 BP due to fen formation and expansion. Emissions stabilized after 5000 BP at 42 ± 25 Tg CH4 y-1 as high-emitting fens transitioned to lower-emitting bogs and permafrost peatlands. Widespread permafrost formation in northern peatlands after 1000 BP led to drier and colder soils which decreased CH4 emissions by 20% to 34 ± 21 Tg y-1 by the present day.