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Dynamic Impact of the Southern Annular Mode on the Antarctic Ozone Hole Area
No full textThis study investigates the impact of dynamic variability of the Southern Hemisphere (SH) polar middle atmosphere on the ozone hole area. We analyze the influence of the southern annular mode (SAM) and planetary waves (PWs) on ozone depletion from 19 years (2005–2023) of aura microwave limb sounder (MLS) geopotential height (GPH) measurements. We employ empirical orthogonal function (EOF) analysis to decompose the GPH variability into distinct spatial patterns. EOF analysis reveals a strong relationship between the first EOF (representing the SAM) and the Antarctic ozone hole area (γ = 0.91). A significant negative lag correlation between the August principal component of the second EOF (PC2) and the September SAM index (γ = -0.76) suggests that lower stratospheric wave activity in August can precondition the polar vortex strength in September. The minor sudden stratospheric warming (SSW) event in 2019 is an example of how strong wave activity can disrupt the polar vortex, leading to significant temperature anomalies and reduced ozone depletion. The coupling of PWs is evident in the lag correlation analysis between different altitudes. A “bottom-up” propagation of PWs from the lower stratosphere to the mesosphere and a potential “top-down” influence from the mesosphere to the lower stratosphere are observed with time lags of 21–30 days. These findings highlight the complex dynamics of PW propagation and their potential impact on the SAM and ozone layer. Further analysis of these correlations could improve one-month lead predictions of the SAM and the ozone hole area.This work is supported by NASA’s Sun-Climate research at Goddard Space Flight Center.https://www.mdpi.com/2072-4292/17/5/83
Animal-microbial ecology in anchialine habitats
No full textAnimals often shape environmental microbial communities, which can in turn influence animal gut microbiomes. Invasive species in critical habitats may reduce grazing pressure from native species and shift microbial communities. The landlocked coastal ponds, pools, and caves that make up the Hawaiian anchialine ecosystem support an endemic shrimp (Halocaridina rubra) that grazes on diverse benthic microbial communities, including orange cyanobacterial-bacterial crusts and green algal mats. Here, we asked how shrimp: (1) shape the abundance and composition of microbial communities, (2) respond to invasive fishes, and (3) whether their gut microbiomes are affected by environmental microbial communities. We demonstrate that ecologically relevant levels of shrimp grazing significantly reduce epilithon biomass. Shrimp grazed readily and grew well on both orange crusts and green mat communities. However, individuals from orange crusts were larger, despite crusts having reduced concentrations of key fatty acids. DNA profiling revealed shrimp harbor a resident gut microbiome distinct from the environment, which is relatively simple and stable across space (including habitats with different microbial communities) and time (between wild-caught individuals and those maintained in the laboratory for >2 yr). DNA profiling also suggests shrimp grazing alters environmental microbial community composition, possibly through selective consumption and/or physical interactions. While this work suggests grazing by endemic shrimp plays a key role in shaping microbial communities in the Hawaiian anchialine ecosystem, the hypothesized drastic ecological shifts resulting from invasive fishes may be an oversimplification as shrimp may largely avoid predation. Moreover, environmental microbial communities may have little influence on shrimp gut microbiomes.We thank S. Hau, R.A. Mackenzie, T. Sakihara, and M. Ramsey for help with fieldwork, and T. Cook and the Hualalai Four Seasons and Waikoloa Resorts for generous on-site assistance and permission to collect. Funding was provided by NSF DEB-2020099 to JCH, NSF DEB-0949855 and DEB-2020081 to SRS, and the Cornell University Atkinson Center for Sustainability.https://onlinelibrary.wiley.com/doi/abs/10.1002/lno.1218
Infinite Transformations in a Suitcase: Encountering Human-DNA Interaction through Poetry-infused Wine
No full textTEI '25: Proceedings of the Nineteenth International Conference on Tangible, Embedded, and Embodied Interaction, Bordeaux/Talence France, March 4-7, 2025Interacting with materials, including biological and living materials, that embody computation and information has increasingly been of interest to the TEI community. In recent years, increased access to low-cost synthetic biology tools and techniques has made it easier for non-experts to experiment with modifying living organisms for creative and artistic purposes, including at the molecular DNA level. A challenge has been to create engaging and culturally-mediated experiences to make these human-DNA interactions accessible to diverse audiences. Infinite Transformations in a Suitcase is a multimedia installation that creates a mediative space inviting reflection on the resilience of culture. At its center is a glass of poetry-infused wine created using genetically modified yeast cells whose DNA contains an encoding of a 14th-century Sufi poem by Hafiz of Shiraz, surrounded by video of it being written in Farsi calligraphy. By combining multiple embodied and abstract poetic elements, the installation invites the audience to reflect on the materiality and movement of culture.This work is supported by a UMBC Imaging Research Center (IRC) Faculty Research Fellowship and a UMBC Summer Research Faculty Fellowship. We also received support from the National Science Foundation (Grants DRL-2005502, DRL-2005484, and DRL-2415876).https://dl.acm.org/doi/10.1145/3689050.370767
The Magnetically Induced Radial Velocity Variation of Gliese 341 and an Upper Limit to the Mass of Its Transiting Earth-sized Planet
No full textThe Transiting Exoplanet Survey Satellite (TESS) mission identified a potential 0.88R⊕ planet with a period of 7.577 days, orbiting the nearby M1V star GJ 341 (TOI 741.01). This system has already been observed by the James Webb Space Telescope (JWST) to search for presence of an atmosphere on this planet. Here, we present an in-depth analysis of the GJ 341 system using all available public data. We provide improved parameters for the host star, an updated value of the planet radius, and support the planetary nature of the object (now GJ 341 b). We use 57 HARPS radial velocities to model the magnetic cycle and activity of the host star, and constrain the mass of GJ 341 b to upper limits of 4.0 M⊕ (3σ) and 2.9 M⊕ (1σ). We also rule out the presence of additional companions with M sin i > 15.1 M⊕, and P < 1750 days, and the presence of contaminating background objects during the TESS and JWST observations. These results provide key information to aid the interpretation of the recent JWST atmospheric observations and other future observations of this planet.This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE1745303 and by NASA under award No. 80GSFC21M0002. This publication is funded in part by the Alfred P. Sloan Foundation under grant G202114194https://iopscience.iop.org/article/10.3847/1538-4357/ad9dd
18-Hour Neighbhoods in the DC Area
No full textUrban and transit planner, data analyst, app-maker, and recently former USDOT official David Schneider created the concept of an 18-hour neighborhood to measure the vibrancy of urban life using retail around transit stations. Sunil Dasgupta talks with Schneider about his methodology, how he applied it to the Washington DC region, and the implications of his research. At dmvtransittourism.com. Music by Washington art-pop rock band Catscan!https://open.spotify.com/episode/41n6WXVc4LXjnBPAkiTHG
Analyses of Virtual Ship-Tracks Systematically Underestimate Aerosol-Cloud Interactions Signals
No full textShip-tracks are important natural/opportunistic experiments to study aerosol-cloud interactions (ACIs). However, detectable ship-tracks are not produced in many instances. Virtual ship-tracks have been conceived to expand the scale of ACIs analyses. Cloud responses in virtual ship-tracks differ strongly from those of detected ones. Here we show that the current approach of virtual ship-tracks can lead to systematic biases and errors and suggest necessary improvements. Errors in trajectory modeling introduce mismatches between areas actually affected by ship-emissions and virtual ship-track locations, that is, positional errors. Positional errors systematically underestimate ACI signals and the underestimate is severe as indicated by analysis of cloud droplet number concentration changes. The assumption of fixed ship-track width also systematically diminishes resulting aerosol effects by more than 10%, which leads to a forcing difference of around 0.1 Wm⁻². We make suggestions to improve the simulation of virtual ship-tracks so that their full potential for studying ACIs can be unleashed.We acknowledge funding support from NASA MEaSUREs and TASNPP programs Grants 80NSSC24K0458 and 80NSSC24M0045 NOAA ERB program Grant NA23OAR4310299 and DOEASR Grant DE SC0024078https://onlinelibrary.wiley.com/doi/abs/10.1029/2024GL11435
Multi?Scale Spatial Effects Determine Nest Success in Small Urban Forest Patches
No full textUrban development and resulting habitat fragmentation affect species populations and inter-specific relationships. While urban ecology research often focuses on species distribution and abundance in habitat fragments, less is known about how urban environments affect reproductive success. Here, we show that factors driving songbird nest success in small urban forest patches vary with landscape-specific edge effects and Light Detection and Ranging (LiDAR) derived vegetation structure. Nest success declined within 30 meters of patch edge, but only in more developed urban landscapes. In addition, nest success increased along two fundamental axes of vegetation structure in urban fragments: overstory density and number of ground-to-canopy gaps. Hence, results indicate that forest fragmentation can generate sufficient variation in ecological conditions to create heterogeneity in edge effects and vegetation structure even across the limited urban development gradient. These findings expand to our understanding of fragmentation effects beyond the traditional rural-developed paradigm.The study was supported by the University of Maryland Baltimore Countyhttps://onlinelibrary.wiley.com/doi/10.1002/wll2.7000
Long-term trends in daytime cirrus cloud radiative effects: Analyzing twenty years of Micropulse Lidar Network measurements at Greenbelt, Maryland in eastern North America
No full textThis pioneering study elucidates the long-term trends and intricate variability of the radiative impacts and optical characteristics of cirrus clouds over two decades, from 2003 to 2022 at the NASA GSFC in Greenbelt, Maryland, USA, headquarters of the Micropulse Lidar Network (MPLNET) project. Over twenty years, analysis of the net cloud radiative effects (CREs) at both the top-of-the-atmosphere (TOA) and surface (SFC) reveals decreases in radiative flux by -0.0017 and -0.0035 W m⁻² yr⁻¹ and -0.0027 and -0.048 W m⁻² yr⁻¹, respectively (based on the constrained solutions for lidar-derived 523/527/532 nm extinction coefficient (m⁻¹) solved for lidar ratios bounded by both 20 and 30 sr). Concurrently, pivotal attributes such as cloud boundary temperature and altitude and integrated optical depth exhibit noteworthy stability, punctuated only by minor seasonal shifts. This study also uncovers a persistent decline in surface albedo, with a derived trend of -0.00036 yr⁻¹. We further find that the interrelationship between CRE and surface albedo variation intensifies notably during winter months. This leads to speculation that a decrease in the number of days of snow and ice is the main driver of the decrease in surface albedo. The decline in radiative flux at both the TOA and SFC can be perceived as a positive feedback loop that leads to increased atmospheric warming. The unveiled trends underscore the intricate synergy between albedo, radiative flux, and climate dynamics, pressing the need for vigilant monitoring of these shifts, given their profound implications for future climatic and circulatory phenomena.The NASA Micro Pulse Lidar Network is supported by the NASA Earth Observing System and Radiation Sciences Programhttps://egusphere.copernicus.org/preprints/2025/egusphere-2025-1237
Apprentice v Intern
No full textIn 2023, Maryland set up a commission to expand apprenticeships in the state and the commission released its interim report in February 2025: . Commission chair Jacob Hsu, a Baltimore technology entrepreneur, and member Jim Rosapepe, state senator from College Park, home of the University of Maryland, joined Sunil Dasgupta to talk about the report, the tradeoffs between internships, and apprenticeships, and the failures of higher education to meet the labor market. Music by Washington art-pop rock band Catscan!https://open.spotify.com/episode/1y3mIrRvVQTavoQIJCWNL
A LSTM with Dual-stage Attention Method to Predict Amine Emissions for Carbon Dioxide Capture and Storage
No full text2024 IEEE International Conference on Big Data (BigData), Washington, DC, USA, 15-18 December 2024To mitigate climate change impacts, carbon capture technologies have been implemented at significant CO2 emission points, such as industrial sites and electric power generation facilities. Solvent-based carbon capture solutions are pivotal in reducing atmospheric CO2 levels and enhancing air quality by capturing harmful pollutants. Amine-based solvents, favored for their efficiency in post-combustion CO2 capture, are susceptible to thermal and oxidative degradation, leading to complex emissions profiles that demand comprehensive management strategies. We develop a Machine Learning model designed to predict future amine emissions in real-time, thereby assisting in the formulation of mitigation strategies required for the operation of capture plants. We conducted an experiment using data from test campaigns run at the Technology Centre Mongstad (TCM). We employed a Long Short-Term Memory (LSTM) autoencoder model with dual-stage attention mechanisms to predict amine emissions using historical data. The results were quite promising: we achieved a mean absolute percentage error ranging from 5.8% to 6.8% percent for the real-time prediction of amine emissions. The results are better than existing approaches using simpler machine learning models as well as the standard LSTM autoencoder model.https://ieeexplore.ieee.org/document/1082532