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Tributary channel networks formed by depositional processes
No full textUnderstanding the detailed structure of landscape topography is important when assessing risks in coastal plain areas susceptible to the combined effects of fluvial, pluvial and coastal flooding. Key to this analysis is the identification and characterization of drainage basins that control surface water flow, but the factors controlling the formation and evolution of drainages in low-relief coastal plains is not well known. Here, we analyse the distribution and morphology of coastal drainage networks using a compilation of airborne lidar covering the entirety of the Gulf of Mexico coastal plain between the Rio Grande and Mississippi rivers. We observe that the dendritic drainage basins that govern the coastal landscape have boundaries that are initially set and controlled by sinuous alluvial ridges defining previous courses of modern rivers that were abandoned through the process of channel avulsion. These depositional ridges form topographic highs on an otherwise low-relief coastal plain and define the initial extent and occurrence of the coastal drainages. While the basin boundaries are formed by depositional processes, they exhibit geometric scaling characteristics similar to basins interpreted to have evolved through erosion alone. This work presents evidence for the creation and evolution of erosional dendritic channel networks within depositional environments with broad implications for understanding floodplain channelization, partitioning and routing of sediment and water across low-relief landscapes, and timescales and mechanisms of landscape evolution
Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models
No full textThis study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150–200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking
Detecting Supercooled Water Clouds Using Passive Radiometer Measurements
No full textSupercooled water clouds (SWCs) have significant impacts on the Earth's radiation balance, aircraft ice accretion and precipitation augmentation. This study introduces an efficient algorithm to detect SWCs from passive radiometers, which combines information from the reflectance difference between 1.61 and 2.25 μm channels, the brightness temperature difference between the 8.5 and 11 μm channels, and the cloud top temperature. Validated by space radar and lidar measurements, our algorithm can correctly detect 91% of SWC pixels, better than current Visible Infrared Imager Radiometer Suite operational product. SWCs are found mostly over the mid- to high-latitude oceans and have a global occurrence frequency of ∼8% in cloudy skies. Since the channels used for the detection are available in most current operational polar and geostationary satellite radiometers, this SWC detection algorithm can be easily implemented for operations such as cloud monitoring, aviation safety, and SWC-related weather modification
Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics
No full textMounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIRv), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIRv and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIRv offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R² = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R² = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. Future efforts to fully integrate the complementary strengths of NIRv and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models
Dark matter direct detection in materials with spin-orbit coupling
No full textSemiconductors with O(meV) band gaps have been shown to be promising targets to search for sub-MeV mass dark matter (DM). In this paper we focus on a class of materials where such narrow band gaps arise naturally as a consequence of spin-orbit coupling (SOC). Specifically, we are interested in computing DM-electron scattering and absorption rates in these materials using state-of-the-art density functional theory techniques. To do this, we extend the DM interaction rate calculation to include SOC effects which necessitates a generalization to spin-dependent wave functions. We apply our new formalism to calculate limits for several DM benchmark models using an example ZrTe₅ target and show that the inclusion of SOC can substantially alter projected constraints
New Modules for the SEDMachine to Remove Contaminations from Cosmic Rays and Non-target Light: byecr and contsep
No full textCurrently time-domain astronomy can scan the entire sky on a daily basis, discovering thousands of interesting transients every night. Classifying the ever-increasing number of new transients is one of the main challenges for the astronomical community. One solution that addresses this issue is the robotically controlled Spectral Energy Distribution Machine (SEDM) which supports the Zwicky Transient Facility (ZTF). SEDM with its pipeline pysedm demonstrates that real-time robotic spectroscopic classification is feasible. In an effort to improve the quality of the current SEDM data, we present here two new modules, byecr and contsep. The first removes contamination from cosmic rays, and the second removes contamination from non-target light. These new modules are part of the automated pysedm pipeline and fully integrated with the whole process. Employing byecr and contsep modules together automatically extracts more spectra than the current pysedm pipeline. Using SNID classification results, the new modules show an improvement in the classification rate and accuracy of 2.8% and 1.7%, respectively, while the strength of the cross-correlation remains the same. Improvements to the SEDM astrometry would further boost the improvement of the contsep module. This kind of robotic follow-up with a fully automated pipeline has the potential to provide the spectroscopic classifications for the transients discovered by ZTF and also by the Rubin Observatory’s Legacy Survey of Space and Time
FIREbox: Simulating galaxies at high dynamic range in a cosmological volume
No full textWe introduce a suite of cosmological volume simulations to study the evolution of galaxies at high numerical resolution as part of the Feedback in Realistic Environments project. FIREbox, the principal simulation of the present suite, provides a representative sample of galaxies (~1000 galaxies with Mₛₜₐᵣ > 10^8 M_⊙ at z = 0) at a resolution (~ 20 pc, m_b ~ 6 x 10⁴ M_⊙) comparable to state-of-the-art galaxy zoom-in simulations. Furthermore, FIREbox captures the multiphase nature of the interstellar medium in a fully cosmological setting (L = 22.1 Mpc) thanks to its exceptionally high dynamic range (~10⁶) and the inclusion of multi-channel stellar feedback. Here, we focus on validating the predictions of FIREbox by comparing to observational data. We find that, at a given stellar mass (for Mₛₜₐᵣ < 10^(10.5-11) M_⊙), simulated galaxies have star formation rates, atomic and molecular gas masses, gas phase and stellar metallicities in broad agreement with observations. In addition, FIREbox shows that these galaxy scaling relations extend to the low mass regime (Mₛₜₐᵣ ~ 10⁷ M_⊙) and follow a (broken) power-law relationship. Also reproduced are the evolution of the cosmic HI density and the HI column density distribution at z ~ 0-5. At low z, FIREbox predicts a peak in the stellar-mass--halo-mass relation, but also a higher abundance of massive galaxies and a higher cosmic star formation rate density than observed, showing that stellar feedback alone is insufficient to reproduce the properties of massive galaxies at late times. Given its high resolution and sample size, FIREbox offers a baseline prediction of galaxy formation theory in a ΛCDM Universe while also highlighting modeling challenges to be addressed in next generation galaxy simulations
The Impact of Cosmic Rays on the Kinematics of the Circumgalactic Medium
No full textWe use hydrodynamical simulations of two Milky Way–mass galaxies to demonstrate the impact of cosmic-ray pressure on the kinematics of cool and warm circumgalactic gas. Consistent with previous studies, we find that cosmic-ray pressure can dominate over thermal pressure in the inner 50 kpc of the circumgalactic medium (CGM), creating an overall cooler CGM than that of similar galaxy simulations run without cosmic rays. We generate synthetic sight lines of the simulated galaxies' CGM and use Voigt profile-fitting methods to extract ion column densities, Doppler-b parameters, and velocity centroids of individual absorbers. We directly compare these synthetic spectral line fits with HST/COS CGM absorption-line data analyses, which tend to show that metallic species with a wide range of ionization potential energies are often kinematically aligned. Compared to the Milky Way simulation run without cosmic rays, the presence of cosmic-ray pressure in the inner CGM creates narrower O vi absorption features and broader Si iii absorption features, a quality that is more consistent with observational data. Additionally, because the cool gas is buoyant due to nonthermal cosmic-ray pressure support, the velocity centroids of both cool and warm gas tend to align in the simulated Milky Way with feedback from cosmic rays. Our study demonstrates that detailed, direct comparisons between simulations and observations, focused on gas kinematics, have the potential to reveal the dominant physical mechanisms that shape the CGM
Ultra-lightweight mirrors with high solar reflectivity and high infrared emissivity for sun-facing radiative thermal management in space
No full textWe report the design, fabrication, and characterization of ultralight coatings that employ Salisbury screen principles and the unique nature of ITO to achieve frequency selective broadband emissivity. Our coating comprises 60 nm SiO2, 10 nm ITO, 2.3 µm NeXolv LaRC CP1 polyimide and 300 nm Ag, and achieves an aerial mass of 4.07 gm-2. It has a calculated and measured visible spectrum reflectivity of R = 0.893 and R = 0.896 respectively when weighted against AM0 from 300 nm to 1800nm; and a calculated and measured IR spectrum emissivity of e = 0.574 and e = 0.554 weighted against a 300 K blackbody respectively. This simple coating design, fabricated on the centimeter scale, achieves broadband frequency selectivity, with the highest reported thermal performance for an ultralight sun-facing radiative energy management structure
Inclusive nonresonant multilepton probes of new phenomena at √s = 13 TeV
No full textAn inclusive search for nonresonant signatures of beyond the standard model (SM) phenomena in events with three or more charged leptons, including hadronically decaying τ leptons, is presented. The analysis is based on a data sample corresponding to an integrated luminosity of 138 fb^(−1) of proton-proton collisions at √s=13 TeV, collected by the CMS experiment at the LHC in 2016–2018. Events are categorized based on the lepton and b-tagged jet multiplicities and various kinematic variables. Three scenarios of physics beyond the SM are probed, and signal-specific boosted decision trees are used for enhancing sensitivity. No significant deviations from the background expectations are observed. Lower limits are set at 95% confidence level on the mass of type-III seesaw heavy fermions in the range 845–1065 GeV for various decay branching fraction combinations to SM leptons. Doublet and singlet vectorlike τ lepton extensions of the SM are excluded for masses below 1045 GeV and in the mass range 125–150 GeV, respectively. Scalar leptoquarks decaying exclusively to a top quark and a lepton are excluded below 1.12–1.42 TeV, depending on the lepton flavor. For the type-III seesaw as well as the vectorlike doublet model, these constraints are the most stringent to date. For the vectorlike singlet model, these are the first constraints from the LHC experiments. Detailed results are also presented to facilitate alternative theoretical interpretations