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Using mass–radius composition models, small planets (R≲ 2R_⊕) are typically classified into three types: iron-rich, nominally Earth-like, and those with solid/liquid water and/or atmosphere. These classes are generally expected to be variations within a compositional continuum. Recently, however, Luque & Pallé observed that potentially Earth-like planets around M dwarfs are separated from a lower-density population by a density gap. Meanwhile, the results of Adibekyan et al. hint that iron-rich planets around FGK stars are also a distinct population. It therefore remains unclear whether small planets represent a continuum or multiple distinct populations. Differentiating the nature of these populations will help constrain potential formation mechanisms. We present theRhoPopsoftware for identifying small-planet populations.RhoPopemploys mixture models in a hierarchical framework and a nested sampler for parameter and evidence estimates. UsingRhoPop, we confirm the two populations of Luque & Pallé with >4σsignificance. The intrinsic scatter in the Earth-like subpopulation is roughly half that expected based on stellar abundance variations in local FGK stars, perhaps implying M dwarfs have a smaller spread in the major rock-building elements (Fe, Mg, Si) than FGK stars. We applyRhoPopto the Adibekyan et al. sample and find no evidence of more than one population. We estimate the sample size required to resolve a population of planets with Mercury-like compositions from those with Earth-like compositions for various mass–radius precisions. Only 16 planets are needed when${\sigma }_{M_p}=5\%$and${\sigma }_{R_p}=1\%$. At${\sigma }_{M_p}=10\%$and${\sigma }_{R_p}=2.5\%$, however, over 154 planets are needed, an order of magnitude increase.

 

In 2016, the National Oceanic and Atmospheric Administration deployed the first iteration of an operational National Water Model (NWM) to forecast the water cycle in the continental United States. With many versions, an hourly, multi-decadal historic simulation is made available to the public. In all released to date, the files containing simulated streamflow contain a snapshot of model conditions across the entire domain for a single timestep which makes accessing  time series a technical and resource-intensive challenge. In the most recent release, extracting a complete streamflow time series for a single location requires managing 367,920 files (~16.2 TB). In this work we describe a reproducible process for restructuring a sequential set of NWM steamflow files for efficient time series access and provide restructured datasets for versions 1.2 (1993–2018), 2.0 (1993–2020), and 2.1 (1979–2022). These datasets have been made accessible via an OPeNDAP enabled THREDDS data server for public use and a brief analysis highlights the latest version of the model should not be assumed best for all locations. Lastly we describe an R package that expedites data retrieval with examples for multiple use-cases.

 

Abstract Infrasound may be used to detect the approach of hazardous volcanic mudflows, known as lahars, tens of minutes before their flow fronts arrive. We have analyzed signals from more than 20 secondary lahars caused by precipitation events at Fuego Volcano during Guatemala’s rainy season in May through October of 2022. We are able to quantify the capabilities of infrasound monitoring through comparison with seismic data, time lapse camera imagery, and high-resolution video of a well-recorded event on August 17. We determine that infrasound sensors, deployed adjacent to the lahar path and in small-aperture (10 s of meters) arrays, are particularly sensitive to remote detection of lahars, including small-sized events, at distances of at least 5 km. At Fuego Volcano these detections could be used to provide timely alerts of up to 30 min before lahars arrive at a downstream monitoring site, such as in the frequently impacted Ceniza drainage. We propose that continuous infrasound monitoring, from locations adjacent to a drainage, may complement seismic monitoring and serve as a valuable tool to help identify approaching hazards. On the other hand, infrasound arrays located a kilometer or more from the lahar path can be effectively used to track a lahar’s progression. 

Atmospheric aerosol particles impact Earth's radiation balance by acting as seeds for cloud droplet formation. Over half of global cloud seed particles are formed by nucleation, a process where gas‐phase compounds react to form stable particles. Reactions of sulfuric acid (SA) with a wide variety of atmospheric compounds have been previously shown to drive nucleation in the lower troposphere. However, global climate models poorly predict particle nucleation rates since current nucleation models do not describe nucleation for systems containing tens to hundreds of precursor compounds. The nucleation potential model (NPM) was recently developed to model SA nucleation of complex mixtures by measuring an effective base concentration using a 1‐nm condensation particle counter. This technique for estimating particle nucleation rates can be deployed at a much higher spatial and temporal resolution than current methods which require detailed knowledge of all nucleation reactions and measurements, typically using a mass spectrometer, of all nucleation precursor gases. This work expands NPM by showing that this model can capture enhancement and suppression of SA nucleation rates within a complex mixture of organic and inorganic acids, ambient air, and across a range of atmospherically relevant relative humidities. In addition, an expression for calculating atmospheric nucleation rates was also derived from the NPM. Ultimately, NPM provides a simple way to measure and model the extent compounds in a complex mixture enhance SA nucleation rates using a condensation particle counter.

 

This study explores the experiences of two teachers participating in professional development workshops focused on supporting implementation of SocioScientific Issues (SSI) and aspects of social justice into STEM classrooms. SSI are ill-defined problems, with a basis in science, but necessarily include moral and ethical decisions that cannot be resolved through science alone. These debatable issues can enhance learning of STEM by engaging students in real-world and authentic problems. The USTRIVE project was developed to foster STEM learning through integrated professional development workshops and the development of professional learning communities to support teachers in the use of SSI and incorporation of aspects of social justice in their STEM classrooms. Two research questions were investigated: (a) To what extent did teachers implement SSI into their lesson planning during the project and (b) In what ways did teachers’ designed lessons change from the beginning of the workshop? 

This study explores the experiences of two teachers participating in professional development workshops focused on supporting implementation of SocioScientific Issues (SSI) and aspects of social justice into STEM classrooms. SSI are ill-defined problems, with a basis in science, but necessarily include moral and ethical decisions that cannot be resolved through science alone. These debatable issues can enhance learning of STEM by engaging students in real-world and authentic problems. The USTRIVE project was developed to foster STEM learning through integrated professional development workshops and the development of professional learning communities to support teachers in the use of SSI and incorporation of aspects of social justice in their STEM classrooms. Two research questions were investigated: (a) To what extent did teachers implement SSI into their lesson planning during the project and (b) In what ways did teachers’ designed lessons change from the beginning of the workshop? 

With an increasing number of continental‐scale hydrologic models, the ability to evaluate performance is key to understanding uncertainty and making improvements to the model(s). We hypothesize that any model, running a single set of physics, cannot be “properly” calibrated for the range of hydroclimatic diversity as seen in the contenintal United States. Here, we evaluate the NOAA National Water Model (NWM) version 2.0 historical streamflow record in over 4,200 natural and controlled basins using the Nash‐Sutcliffe Efficiency metric decomposed into relative performance, and conditional, and unconditional bias. Each of these is evaluated in the contexts of meteorologic, landscape, and anthropogenic characteristics to better understand where the model does poorly, what potentially causes the poor performance, and what similarities systemically poor performing areas share. The primary objective is to pinpoint traits in places with good/bad performance and low/high bias. NWM relative performance is higher when there is high precipitation, snow coverage (depth and fraction), and barren area. Low relative skill is associated with high potential evapotranspiration, aridity, moisture‐and‐energy phase correlation, and forest, shrubland, grassland, and imperviousness area. We see less bias in locations with high precipitation, moisture‐and‐energy phase correlation, barren, and grassland areas and more bias in areas with high aridity, snow coverage/fraction, and urbanization. The insights gained can help identify key hydrological factors underpinning NWM predictive skill; enforce the need for regionalized parameterization and modeling; and help inform heterogenous modeling systems, like the NOAA Next Generation Water Resource Modeling Framework, to enhance ongoing development and evaluation.

 

We explore the capabilities of volcano opto‐acoustics, a promising technique for measuring explosion and infrasound resonance phenomena at open‐vent volcanoes. Joint visual and infrasound study at Yasur Volcano (Vanuatu) demonstrate that even consumer‐grade cameras are capable of recording infrasound with high fidelity. Passage of infrasonic waves, ranging from as low as 5 Pa to hundreds of Pa, from both explosions and persistent tremor, pressurizes and depressurizes ambient plumes inducing visible vaporization and condensation respectively. Optical tracking of these pressure wavefields can be used to identify spectral characteristics, which vary within Yasur's two deep craters and are distinct for explosion and tremor sources. Wavefield maps can illuminate the propagation of blasts as well as the dynamics of persistent infrasonic tremor associated with standing waves in the craters. We propose that opto‐acoustic monitoring is useful for extraction of near‐vent infrasound signal and for tracking volcanic unrest from a remote distance.