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How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?

Given the tradeoffs between spatial and temporal resolution, questions about resolution optimality are fundamental to the study of global snow. Answers to these questions will inform future scientific priorities and mission specifications. Heterogeneity of mountain snowpacks drives a need for daily snow cover mapping at the slope scale (≤30 m) that is unmet for a variety of scientific users, ranging from hydrologists to the military to wildlife biologists. But finer spatial resolution usually requires coarser temporal or spectral resolution. Thus, no single sensor can meet all these needs. Recently, constellations of satellites and fusion techniques have made noteworthy progress. The efficacy of two such recent advances is examined: (1) a fused MODIS–Landsat product with daily 30 m spatial resolution and (2) a harmonized Landsat 8 and Sentinel 2A and B (HLS) product with 3–4 d temporal and 30 m spatial resolution. State-of-the-art spectral unmixing techniques are applied to surface reflectance products from 1 and 2 to create snow cover and albedo maps. Then an energy balance model was run to reconstruct snow water equivalent (SWE). For validation, lidar-based Airborne Snow Observatory SWE estimates were used. Results show that reconstructed SWE forced with 30 m resolution snow cover has lower bias, a measure of basin-wide accuracy, than the baseline case using MODIS (463 m cell size) but greater mean absolute error, a measure of per-pixel accuracy. However, the differences in errors may be within uncertainties from scaling artifacts, e.g., basin boundary delineation. Other explanations are (1) the importance of daily acquisitions and (2) the limitations of downscaled forcings for reconstruction. Conclusions are as follows: (1) spectrally unmixed snow cover and snow albedo from MODIS continue to provide accurate forcings for snow models and (2) finer spatial and temporal resolution through sensor design, fusion techniques, and satellite constellations are the future for Earth observations, but existing moderate-resolution sensors still offer value.

Edward H. Bair↗

Deblurring

In most instances, traditional EEG methodology provides insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. This article describes a method called Deblurring for increasing the spatial detail of the EEG and for fusing neurophysiologic and neuroanatomic data. Deblurring estimates potentials near the outer convexity of the cortex using a realistic finite element model of the structure of a subject's head determined from their magnetic resonance images. Deblurring is not a source localization technique and thus makes no assumptions about the number or type of generator sources. The validity of Deblurring has been initially tested by comparing deblurred data with potentials measured with subdural grid recordings. Results suggest that deblurred topographic maps, registered with a subject's magnetic resonance imaging and rendered in three dimensions, provide better spatial detail than has heretofore been obtained with scalp EEG recordings. Example results are presented from research studies of somatosensory stimulation, movement, language, attention and working memory. Deblurred ictal EEG data are also presented, indicating that this technique may have future clinical application as an aid to seizure localization and surgical planning.

Non-NASA Center↗

Data-Driven Method for Groundwater-Level Mapping and Monitoring-Well Network Optimization at Hanford

This report summarizes the initial results and outcomes of a physics-informed, data-driven groundwater level (GWL) mapping capability for the Hanford Site. GWL mapping at Hanford is typically conducted annually and requires a significant amount of computational and expert resources, and it does not allow assessment of the informational value of specific monitoring wells. The proposed method produces spatially and temporally resolved fields consistent with sparse, irregularly sampled, and nonuniformly distributed well measurements. Implemented successfully, this capability will allow rapid mapping of groundwater levels and provide an opportunity to optimize monitoring activities (both location and sampling frequency) based on data information value evaluation. The approach integrates a diffusion-based generative model – trained on MODFLOW simulation data from the Plateau-to-River (P2R) model – with score-based data assimilation (SDA), allowing observation-conditioned mapping without retraining for each monitoring-network layout.

54 ENVIRONMENTAL SCIENCES↗

Flow transition with 2-D roughness elements in a 3-D channel

We develop a new numerical approach to study the spatially evolving instability of the streamwise dominant flow in the presence of roughness elements. The difficulty in handling the flow over the boundary surface with general geometry is removed by using a new conservative form of the governing equations and an analytical mapping. The numerical scheme uses second-order backward Euler in time, fourth-order central differences in all three spatial directions, and boundary-fitted staggered grids. A three-dimensional channel with multiple two-dimensional-type roughness elements is employed as the test case. Fourier analysis is used to decompose different Fourier modes of the disturbance. The results show that surface roughness leads to transition at lower Reynolds number than for smooth channels.

Liu, Zhining↗

A Near-Infrared and Thermal Imager for Mapping Titan's Surface Features

Approximately 10% of the solar insolation reaches the surface of Titan through atmospheric spectral windows. We will discuss a filter based imaging system for a future Titan orbiter that will exploit these windows mapping surface features, cloud regions, polar storms. In the near-infrared (NIR), two filters (1.28 micrometer and 1.6 micrometer), strategically positioned between CH1 absorption bands, and InSb linear array pixels will explore the solar reflected radiation. We propose to map the mid, infrared (MIR) region with two filters: 9.76 micrometer and 5.88-to-6.06 micrometers with MCT linear arrays. The first will map MIR thermal emission variations due to surface albedo differences in the atmospheric window between gas phase CH3D and C2H4 opacity sources. The latter spans the crossover spectral region where observed radiation transitions from being dominated by thermal emission to solar reflected light component. The passively cooled linear arrays will be incorporated into the focal plane of a light-weight thin film stretched membrane 10 cm telescope. A rad-hard ASIC together with an FPGA will be used for detector pixel readout and detector linear array selection depending on if the field-of-view (FOV) is looking at the day- or night-side of Titan. The instantaneous FOV corresponds to 3.1, 15.6, and 31.2 mrad for the 1, 5, and 10 micrometer channels, respectively. For a 1500 km orbit, a 5 micrometer channel pixel represents a spatial resolution of 91 m, with a FOV that spans 23 kilometers, and Titan is mapped in a push-broom manner as determined by the orbital path. The system mass and power requirements are estimated to be 6 kg and 5 W, respectively. The package is proposed for a polar orbiter with a lifetime matching two Saturn seasons.

Aslam, S.↗

Legacy surface change analyses of the 1993 Rock Valley earthquake sequence for direct comparison to planned NA-22 underground conventional high-explosive experiments (Source Physics Experiment 3 (SPE3) - RV/DC Task 1.3 FY22 Final Report)

Recent work under two previous phases of the NNSA NA-22 Source Physics Experiment (SPE) have shown that underground chemical high-explosive experiments can produce detectable surface changes that differ in spatial extent and vertical magnitude depending on the geologic media at the site (Schultz-Fellenz et al., 2018; 2020; Crawford et al., 2021). Neither of these two prior phases of SPE identified natural earthquake-related surface effects in the same region that occurred at a similar depth as the explosive experiments for direct comparison. While earthquakes can also produce surface changes that are detectable using remote sensing data analyses, it is expected that the pattern and spatial extent of surface changes would vary between earthquakes and explosions. However, no direct-observed surface-change signature comparison between earthquakes and explosions has ever been performed. The SPE Phase 3 Rock Valley/Direct Comparison (RV/DC) program presents a unique opportunity to investigate and characterize co-occurrence of both earthquakes and explosions. In this project, we worked to address five tasks in a workflow, as follows: 1. Identify and obtain existing high-resolution legacy satellite and aerial imagery as close in time before and after the 1993 Rock Valley earthquake sequence to temporally constrain the analyses. 2. Transform these pre-earthquake and post-earthquake datasets into digital elevation models (DEMs) using geospatial analysis software packages (e.g., ArcGIS, Agisoft Metashape, and Google Earth Engine). 3. Perform DEM differencing analyses to assess and quantify earthquake-related changes from the 1993 sequence, and develop map products that visualize these analyses. 4. Use the analyses from (3) to: (a) assess spatial distribution and magnitude of surface changes due to the 1993 Rock Valley earthquake sequence, and (b) determine parameters of forthcoming, planned explosion-related surface change data collection from sensors mounted on unmanned aerial vehicles (UAVs) (e.g., spatial extent of collection, design and density of survey control, sensors to deploy, forward speed and line spacing of UAV flight lines, flight altitude). 5. Develop a summary report on the analyses, including how the analyses define parameters and identify focus areas for any future surface change analytical field campaigns related to the explosive experiment. Analyzing these legacy data and identifying whether they can detect any surface changes related to the earthquake sequence facilitates opportunities for direct signature comparison of surface change from explosions at one location, which has never previously been performed. Comparing the surface change signatures from a co-located and depth-equivalent earthquake and an explosion could help to advance remote sensing event discrimination techniques. This report summarizes the work completed toward this ambitious goal.

42 ENGINEERING↗

Geochemical Mapping of 4 Vesta Begins

By December, the NASA Dawn spacecraft will have descended to a low altitude mapping orbit (LAMO), where the Gamma Ray and Neutron Detector (GRaND) will acquire global mapping data for up to four months. Measurements by GRaND will help answer elusive questions about how Vesta differentiated and the nature of processes that shaped Vesta s surface. The data will be analyzed to determine the abundances of Mg, Si, Fe, K, Th, and H at a spatial resolution of roughly 300 km full-width-at-half-maximum from a 465 km radius orbit. Thermal and fast neutron counting data will be analyzed to determine the neutron macroscopic absorption cross section and average atomic mass, providing constraints on additional elements, such as Ca and Al. GRaND will quantify the elemental composition of coarse spatial units identified by Dawn s Framing Camera (FC) and the Visible & Infrared Spectrometer (VIR). In addition, GRaND will map the mixing ratio of compositional end members selected from the howardite, eucrite and diogenite (HED) meteorites, determine the relative proportions of plagioclase and mafic minerals, and search for compositions that are absent or under-represented in the meteorite collection. While it is generally thought that Vesta s crust on a regional scale should be well-represented by linear mixing of HED whole-rock compositions, there are hints that Vesta may be more diverse than implied by this model. For example, the discovery of K-rich impact glasses in howardites suggests that K-rich rocks may be present on a portion of Vesta s surface, and the analysis of diogenites indicates considerable variability in the magmatic processes that formed them. The chemical composition of materials within Vesta s south polar structure may provide further clues to how it formed. An impact might have exposed mantle and lower crustal materials, which should have a distinctive compositional signature. We present the analysis of data acquired by GRaND from cruise through the descent to LAMO, including GRaND s sensitivity to different elements and geochemical processes.

Prettyman, Thomas H.↗

A Radiation Hard Multi-Channel Digitizer ASIC for Operation in the Harsh Jovian Environment

In 1995, the Galileo spacecraft arrived at Jupiter to conduct follow-up experiments on pathfinder Pioneer and key Voyager discoveries especially at Io, Europa, Ganymede and Callisto. These new observations helped expand our scientific knowledge of the prominent Galilean satellites; studies revealed diversity with respect to their geology, internal structure, evolution and degree of past and present activity. Jupiter's diverse Galilean satellites, of which three are believed to harbor internal oceans, are central to understanding the habitability of icy worlds. Galileo provided for the first time compelling evidence of a near-surface global ocean on Europa. Furthermore, by understanding the Jupiter system and unraveling the history of its evolution from initial formation to the emergence of possible habitats and life, gives insight into how giant planets and their satellite systems form and evolve. Most important, new light is shed on the potential for the emergence and existence of life in icy satellite oceans. In 2009, NASA released a detailed Jupiter Europa Mission Study (EJSM) that proposed an ambitious Flagship Mission to understand more fully the satellites Europa and Ganymede within the context of the Jovian system. Key to EJSM is the NASA led Jupiter Europa Orbiter (JEO) and the ESA led Jupiter Ganymede Orbiter (JGO). JEO and JGO would execute a choreographed exploration of the Jovian system before settling into orbit around Europa and Ganymede, respectively. The National Academies Planetary Decadal Survey, 2011 has listed the NASA-led JEO as the second highest priority mission for the decade 2013-2022, and if chosen it would be launched in 2020 with arrival at Jupiter in 2025. If the JEO mission is not chosen it is anticipated that there will be opportunities in future decadal cycles. Jupiter Orbit Insertion (JOI) begins a 30-month Jovian system tour followed by nine months of science mapping after Europa Orbit Insertion (EOI) in July 2028. The orbiter will ultimately impact the surface of Europa after the mission is completed. The current JEO mission concept includes a range of instruments on the payload, to monitor dynamic phenomena (such as Io's volcanoes and Jupiters atmosphere), map the Jovian magnetosphere and its interactions with the Galilean satellites, and characterize water oceans beneath the ice shells of Europa and Ganymede. The payload includes a low mass (3.7 Kg) and low power (< 5 W) Thermal Instrument (TI) concept for measuring possible warm thermal anomalies on Europa s cold surface caused by recent (< 10,000 years) eruptive activity. Regions of anomalously high heat flow will be identified by thermal mapping using a nadir pointing, push-broom filter radiometer that provides far-IR imagery in two broad band spectral wavelength regions, 8-20 m and 20-100 m, for surface temperature measurements with better than a 2 K accuracy and a spatial resolution of 250 m/pixel obtained from a 100 Km orbit. The temperature accuracy permits a search for elevated temperatures when combined with albedo information. The spatial resolution is sufficient to resolve Europa's larger cracks and ridge axial valleys. In order to accomplish the thermal mapping, the TI uses sensitive thermopile arrays that are readout by a custom designed low-noise Multi-Channel Digitizer (MCD) ASIC that resides very close to the thermopile linear array outputs. Both the thermopile array and the MCD ASIC will need to show full functionality within the harsh Jovian radiation environment, operating at cryogenic temperatures, typically 150 K to 170 K. In the following, a radiation mitigation strategy together with a low risk Radiation-Hardened-By-Design (RHBD) methodology using commercial foundry processes is given for the design and manufacture of a MCD ASIC that will meet this challenge.

Aslam, Shahid↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Generating Ground Reference Data for a Global Impervious Surface Survey

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Tilton, James C.↗

An atlas of high-resolution IRAS maps on nearby galaxies

An atlas of far-infrared IRAS maps with near 1 arcmin angular resolution of 30 optically large galaxies is presented. The high-resolution IRAS maps were produced with the Maximum Correlation Method (MCM) image construction and enhancement technique developed at IPAC. The MCM technique, which recovers the spatial information contained in the overlapping detector data samples of the IRAS all-sky survey scans, is outlined and tests to verify the structural reliability and photometric integrity of the high-resolution maps are presented. The infrared structure revealed in individual galaxies is discussed. The atlas complements the IRAS Nearby Galaxy High-Resolution Image Atlas, the high-resolution galaxy images encoded in FITS format, which is provided to the astronomical community as an IPAC product.

Rice, Walter↗

A High Speed, Radiation Hard X-Ray Imaging Spectroscometer for Planetary Investigations

X-ray observations provide a unique window into fundamental processes in planetary physics, and one that is complementary to observations obtained at other wavelengths. We propose to develop an X-ray imaging spectrometer (0.1-10 keV band) that, on orbital planetary missions, would measure the elemental composition, density, and temperature of the hot plasma in gas giant magnetospheres, the interaction of the Solar wind with the upper atmospheres of terrestrial planets, and map the elemental composition of the surfaces of the Galilean moons and rocky or icy airless systems on spatial scales as small as a few meters. The X-ray emission from gas giants, terrestrial planets and moons with atmospheres, displays diverse characteristics that depend on the Solar wind's interaction with their upper atmospheres and/or magnetospheres. Our imaging spectrometer, as part of a dedicated mission to a gas giant, will be a paradigm changing technology. On a mission to the Jovian system, our baseline instrument would map the elemental composition of the rocky and icy surfaces of the Galilean moons via particle-induced X-ray fluorescence. This instrument would also measure the temperature, density and elemental abundance of the thermal plasma in the magnetosphere and in the Io plasma torus (IPT), explore the interaction of the Solar wind with the magnetosphere, and characterize the spectrum, flux, and temporal variability of X-ray emission from the polar auroras. We will constrain both the mode of energy transport and the effective transport coefficients in the IPT and throughout the Jovian magnetosphere by comparing temporal and spatial variations of the X-ray emitting plasma with those seen from the cooler but energetically dominant 5 eV plasma.

Kraft, R. P.↗

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗

Radar Altimetry For Topographical Mapping

Two altimeter concepts based on spaceborne synthetic-aperture-radar (SAR) proposed to gather global, uniformly sampled, high-resolution, topographical data on land and ice. Wide swath and high pulse rate of SAR makes possible to acquire spatially contiguous data over large areas in reasonable amount of time, and time needed for altimetric processing of SAR data considerably less than that needed to generate topographical maps from stereoscopic photographs. Radar less vulnerable to cloud cover and other weather conditions than optical techniques.

Im, Eastwood↗

Spatial Study 2022: Surface Water Samples, Cotton Strip Degradation, and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides data and photos generated from sample collection during the same one-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. The contents include surface water geochemistry data; river substrate grain size photos; stream depth data; manual chamber open channel respiration data; and field metadata (including qualitative information on instream and river corridor characteristics). Grain size photos can be used to improve estimates of channel substrate D50 data. The dataset also includes tensile strength and photos from cotton strip field degradation experiments; five-week sensor time series temperature, dissolved oxygen, pressure, pH, specific conductance, chlorophyll A, and turbidity data; plots of the sensor data; and R scripts used to generate the plots. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. SSS data published in the CM data package were not included in this data package. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Additionally, sensor data from a similar 2021 spatial study can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052 and 2021 sample data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1898914. The 2021 spatial study had some sites in common with this 2022 spatial study. This dataset is comprised of three photo folders and one main data folder with six subfolders. The photo folders contain photographs and videos of cotton strip retrieval and sediment quadrats. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) total suspended solids (TSS) data and cotton strip tensile strength data and averages; (5) field protocol; (6) readme; (7) methods codes; (8) international generic sample number (IGSN) mapping file; (9) sensor installation methods summary; (10) stream depth and averages; and (11) Ultrameter data and averages. The Sonar subfolder consists of Sonar time-series depth data and a processing script. The BarotrollAtm, DepthHOBO, MantaRiver, miniDOT, and miniDOTManualChamber subfolders contain time-series data, plots, and summary files. All files are .csv, .pdf, .txt, .R, .Rmd, .jpg, .jpeg, .AVI, .mp4, or .mov. The data package was originally published in April 2023. It was updated in August 2023 (v2; modified files) and September 2024 (v3; modified files). See the change history section in the readme for details. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Mapping the Moon in Soft x Rays: Promises and Challenges

Recent ROSAT images reported by Schmitt et el. show that the sunlit part of the Moon is a significant source of very soft x rays. Stimulated by these observations, Edwards et al. have made an analysis of the response of the Moon to the solar soft x ray and EUV spectrum. They argue that much of the observed emission is in the form of discrete fluorescence lines in the energy range 25 to 100 eV, and that these lines are generally much stronger than the adjacent directly scattered solar background. On this basis they suggest that soft x ray fluorescence can be used to remotely obtain high-precision elemental maps of the lunar surface. Edwards et al. have continued to develop this idea and have suggested a system using soft x ray telescopes in lunar orbit, which could also obtain very good spatial resolution. This combination could be extremely valuable in furthering our understanding of lunar chemistry and potential resource distributions. High spatial resolution combined with the thin surface layer from which these soft x rays arise suggests the exciting possibility that x ray telescopes could map lunar volcanic volatiles from orbit.

Housley, R. M.↗

A Comprehensive Stress Drop Map From Trench to Depth in the Northern Chilean Subduction Zone

We compute stress drops for earthquakes in Northern Chile recorded between 2007 and 2021. By applying two analysis techniques, (a) the spectral ratio (SR) method and (b) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s functions (EGF) for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell-wise obtained global EGF's to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismotectonic domains. Albeit only small differences of median stress drop, strike-perpendicular depth sections clearly reveal systematic variations, with earthquakes at different seismotectonic locations exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth-dependent increase of median stress drop. Additionally, we observe spatio-temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures.

58 GEOSCIENCES↗

Airborne far-infrared observations of the galactic center region

Maps of a region 10 arcmin in diameter around the galactic center made simultaneously in three wavelength bands at 30, 50, and 100 microns with about 1 arcmin resolution are presented, and the distribution of far-IR luminosity and color temperature across this region is derived. The position of highest far-IR surface brightness coincides with the peak of the late-type stellar distribution and with the H II region Sgr A West. The high spatial and temperature resolution of the data is used to identify features of the far-IR maps with known sources of near-IR, radio continuum, and molecular emission. The emission mechanism and energy sources for the far-IR radiation are analyzed qualitatively, and it is concluded that all of the observed far-IR radiation from the galactic-center region can be attributed to thermal emission from dust heated both by the late-type stars and by the ultraviolet sources which ionize the H II regions. A self-consistent model for the far-IR emission from the galactic-center region is presented. It is found that the visual extinction across the central 10 pc of the Galaxy is only about 3 mag and that the dust density is fairly uniform in this region. An upper limit of 10 million suns is set on the luminosity of any still unidentified source of 0.1- to 1-micron radiation at the galactic center.

Gatley, I.↗