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At least 1,351 records · Page 75

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Impact of prescribed fire on soil microbial communities in a Southern Appalachian Forest clear-cut

Escalating wildfire frequency and severity, exacerbated by shifting climate patterns, pose significant ecological and economic challenges. Prescribed burns, a common forest management tool, aim to mitigate wildfire risks and protect biodiversity. Nevertheless, understanding the impact of prescribed burns on soil and microbial communities in temperate mixed forests, considering temporal dynamics and slash fuel types, remains crucial. Our study, conducted at the University of Tennessee Forest Resources AgResearch and Education Center in Oak Ridge, TN, employed controlled burns across various treatments, and the findings indicate that low-intensity prescribed burns have none or minimal short-term effects on soil parameters but may alter soil nutrient concentrations, as evidenced by significant changes in porewater acetate, formate, and nitrate concentrations. These burns also induce shifts in microbial community structure and diversity, with Proteobacteria and Acidobacteria increasing significantly post-fire, possibly aiding soil recovery. In contrast, Verrucomicrobia showed a notable decrease over time, and other specific microbial taxa correlated with soil pH, porewater nitrate, ammonium , and phosphate concentrations. Our research contributes to understanding the intricate relationships between prescribed fire, soil dynamics, and microbial responses in temperate mixed forests in the Southern Appalachian Region, which is valuable for informed land management practices in the face of evolving environmental challenges.

Microbiology↗

PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset

This study presents the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR-Now) near-real-time precipitation dataset. This dataset provides hourly, quasi-global, infrared-based precipitation estimates at 0.04° × 0.04° spatial resolution with a short latency (15–60 min). It is intended to supersede the PERSIANN–Cloud Classification System (PERSIANN-CCS) dataset previously produced as the near-real-time product of the PERSIANN family. We first provide a brief description of the algorithm’s fundamentals and the input data used for deriving precipitation estimates. Second, we provide an extensive evaluation of the PDIR-Now dataset over annual, monthly, daily, and subdaily scales. Last, the article presents information on the dissemination of the dataset through the Center for Hydrometeorology and Remote Sensing (CHRS) web-based interfaces. The evaluation, conducted over the period 2017–18, demonstrates the utility of PDIR-Now and its improvement over PERSIANN-CCS at all temporal scales. Specifically, PDIR-Now improves the estimation of rain/no-rain days as demonstrated by a critical success index (CSI) of 0.53 compared to 0.47 of PERSIANN-CCS. In addition, PDIR-Now improves the estimation of seasonal and diurnal cycles of precipitation as well as regional precipitation patterns erroneously estimated by PERSIANN-CCS. Finally, an evaluation is carried out to examine the performance of PDIR-Now in capturing two extreme events, Hurricane Harvey and a cluster of summer thunderstorms that occurred over the Netherlands, where it is shown that PDIR-Now adequately represents spatial precipitation patterns as well as subdaily precipitation rates with a correlation coefficient (CORR) of 0.64 for Hurricane Harvey and 0.76 for the Netherlands thunderstorms.

Rainfall↗

SN 2018fif: The Explosion of a Large Red Supergiant Discovered in Its Infancy by the Zwicky Transient Facility

High-cadence transient surveys are able to capture supernovae closer to their first light than ever before. Applying analytical models to such early emission, we can constrain the progenitor stars' properties. Here, we present observations of SN 2018fif (ZTF 18abokyfk). The supernova was discovered close to first light and monitored by the Zwicky Transient Facility (ZTF) and the Neil Gehrels Swift Observatory. Early spectroscopic observations suggest that the progenitor of SN 2018fif was surrounded by relatively small amounts of circumstellar material compared to all previous cases. This particularity, coupled with the high-cadence multiple-band coverage, makes it a good candidate to investigate using shock-cooling models. We employ the SOPRANOS code, an implementation of the model by Sapir & Waxman and its extension to early times by Morag et al. Compared with previous implementations, SOPRANOS has the advantage of including a careful account of the limited temporal validity domain of the shock-cooling model as well as allowing usage of the entirety of the early UV data. We find that the progenitor of SN 2018fif was a large red supergiant with a radius of $R={744.0}_{-128.0}^{+183.0}\,{R}_{\odot }$ and an ejected mass of ${M}_{\mathrm{ej}}={9.3}_{-5.8}^{+0.4}\,{M}_{\odot }$. Our model also gives information on the explosion epoch, the progenitor's inner structure, the shock velocity, and the extinction. The distribution of radii is double-peaked, with smaller radii corresponding to lower values of the extinction, earlier recombination times, and a better match to the early UV data. If these correlations persist in future objects, denser spectroscopic monitoring constraining the time of recombination, as well as accurate UV observations (e.g., with ULTRASAT), will help break the extinction/radius degeneracy and independently determine both.

79 ASTRONOMY AND ASTROPHYSICS↗

Causal relationships of vegetation productivity with root zone water availability and atmospheric dryness at the catchment scale

Abstract. This study explores the causal relationships between catchment water availability, vapor pressure deficit, and gross primary productivity (GPP) across 341 catchments in the contiguous US. Seasonal climatic, hydrological, and vegetation characteristics were represented using the Horton index, ecological aridity index, evaporative fraction index, and carbon uptake efficiency. Statistical methods, including circularity statistics, correlation analysis, and causality tests, were employed to determine the complex interactions between catchment wetness, atmospheric dryness, and vegetation carbon uptake. The results revealed a maximum lag of 2 months in the intra-annual variability of catchment water supply–productivity and atmospheric water demand–productivity relationships, with hysteresis patterns varying with the catchment's hydrological characteristics. In catchments not permanently under water-limited or energy-limited conditions, vegetation experiences hydrological stress during the peak growing period, coinciding with the highest gross primary productivity and carbon uptake efficiency being out of phase with the Horton index and in phase with the evaporative fraction index. Causality analysis highlights strong temporal continuity in GPP seasonal characteristics, with a cause–effect relationship between catchment water supply, atmospheric demand, and vegetation productivity spanning a maximum of 2 months. These findings underscore the need for a comprehensive functional framework that integrates catchment water supply, atmospheric demand, and vegetation productivity to enhance our understanding and predictive capabilities with regard to ecosystem responses to climate change.

54 ENVIRONMENTAL SCIENCES↗

Enhanced imaging of electronic hot spots using quantum squeezed light

Detecting electronic hot spots is important for understanding the heat dissipation and thermal management of electronic and semiconductor devices. Optical thermoreflective imaging is being used to perform precise temporal and spatial imaging of heat on wires and semiconductor materials. We apply quantum squeezed light to perform thermoreflective imaging on micro-wires, surpassing the shot-noise limit of classical approaches. We obtain a far-field temperature sensing accuracy of 42 mK after 50 ms of averaging and show that a 256×256 pixel image can be constructed with such sensitivity in 10 min. We can further obtain single-shot temperature sensing of 1.6 K after only 10 μs of averaging, enabling a dynamical study of heat dissipation. Not only do the quantum images provide accurate spatiotemporal information about heat distribution but also the measure of quantum correlation provides additional information, inaccessible by classical techniques, which can lead to a better understanding of the dynamics. We apply the technique to both aluminum and niobium microwires and discuss the applications of the technique in studying electron dynamics at low temperatures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Modeling phonon-mediated quasiparticle poisoning in superconducting qubit arrays

Correlated errors caused by ionizing radiation impacting superconducting qubit chips are problematic for quantum error correction. Such impacts generate quasiparticle (QP) excitations in the qubit electrodes, which temporarily reduce qubit coherence significantly. The many energetic phonons produced by a particle impact travel efficiently throughout the device substrate and generate quasiparticles with high probability, thus causing errors on a large fraction of the qubits in an array simultaneously. Here, we describe a comprehensive strategy for the numerical simulation of the phonon and quasiparticle dynamics in the aftermath of an impact. We compare the simulations with experimental measurements of phonon-mediated QP poisoning and demonstrate that our modeling captures the spatial and temporal footprint of the QP poisoning for various configurations of phonon downconversion structures. We thus present a path forward for the operation of superconducting quantum processors in the presence of ionizing radiation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Quantitative phenotyping of crop roots with spectral electrical impedance tomography: a rhizotron study with optimized measurement design

Background: Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results: Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass (R 2 = 0.82) and root surface area (R 2 = 0.8). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion: Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

59 BASIC BIOLOGICAL SCIENCES↗

Time-dependent gravity in Southern California, May 1974 to April 1979

The Southern California gravity survey, begun in May 1974 to obtain high spatial and temporal density gravity measurements to be coordinated with long-baseline three dimensional geodetic measurements of the Astronomical Radio Interferometric Earth Surveying project, is presented. Gravity data was obtained from 28 stations located in and near the seismically active San Gabriel section of the Southern California Transverse Ranges and adjoining San Andreas Fault at intervals of one to two months using gravity meters relative to a base station standard meter. A single-reading standard deviation of 11 microGal is obtained which leads to a relative deviation of 16 microGal between stations, with data averaging reducing the standard error to 2 to 3 microGal. The largest gravity variations observed are found to correlate with nearby well water variations and smoothed rainfall levels, indicating the importance of ground water variations to gravity measurements. The largest earthquake to occur during the survey, which extended to April, 1979, is found to be accompanied in the station closest to the earthquake by the largest measured gravity changes that cannot be related to factors other than tectonic distortion.

Whitcomb, J. H.↗

Low- to Middle-Latitude X-Ray Emission from Jupiter

The Chandra X-ray Observatory (CXO) observed Jupiter during the period 24-26 February 2003 for approx. 40 hours (4 Jupiter rotations), using both the spectroscopy array of the Advanced CCD Imaging Spectrometer (ACIS-S) and the imaging array of the High-Resolution Camera (HRC-I). Two ACIS-S exposures, each -8.5 hours long, were separated by an HRC-I exposure of approx. 20 hours. The low- to middle-latitude nonauroral disk X-ray emission is much more spatially uniform than the auroral emission. However, the low- to middle-latitude X-ray count rate shows a small but statistically significant hour angle dependence and depends on surface magnetic field strength. In addition, the X-ray spectra from regions corresponding to 3-5 gauss and 5-7 gauss surface fields show significant differences in the energy band 1.26-1.38 keV, perhaps partly due to line emission occurring in the 3-5 gauss region but not the 5-7 gauss region. A similar correlation of surface magnetic field strength with count rate is found for the 18 December 2000 HRC-I data, at a time when solar activity was high. The low- to middle-latitude disk X-ray count rate observed by the HRC-I in the February 2003 observation is about 50% of that observed in December 2000, roughly consistent with a decrease in the solar activity index (F10.7 cm flux) by a similar amount over the same time period. The low- to middle-latitude X-ray emission does not show any oscillations similar to the approx. 45 min oscillations sometimes seen from the northern auroral zone. The temporal variation in Jupiter's nonauroral X-ray emission exhibits similarities to variations in solar X-ray flux observed by GOES and TIMED/SEE. The two ACIS-S 0.3-2.0 keV low- to middle-latitude X-ray spectra are harder than the auroral spectrum and are different from each other at energies above 0.7 keV, showing variability in Jupiter's nonauroral X-ray emission on a timescale of a day. The 0.3-2.0 keV X-ray power emitted at low to middle latitudes is 0.21 GW and 0.39 GW for the first and second ACIS-S exposures, respectively. We suggest that X-ray emission from Jupiter's disk may be largely generated by the scattering and fluorescence of solar X rays in its upper atmosphere, especially at times of high incident solar X-ray flux. However, the dependence of count rate on surface magnetic-field strength may indicate the presence of some secondary component, possibly ion precipitation from radiation belts close to the planet.

Bhardwaj, Anil↗

SN 2018fif: The Explosion of a Large Red Supergiant Discovered in its Infancy by the Zwicky Transient Facility

High-cadence transient surveys are able to capture supernovae closer to their first light than ever before. Applying analytical models to such early emission, we can constrain the progenitor stars' properties. In this paper, we present observations of SN 2018fif (ZTF 18abokyfk). The supernova was discovered close to first light and monitored by the Zwicky Transient Facility (ZTF) and the Neil Gehrels Swift Observatory. Early spectroscopic observations suggest that the progenitor of SN 2018fif was surrounded by relatively small amounts of circumstellar material compared to all previous cases. This particularity, coupled with the high-cadence multiple-band coverage, makes it a good candidate to investigate using shock-cooling models. We employ the SOPRANOS code, an implementation of the model by Sapir & Waxman and its extension to early times by Morag et al. Compared with previous implementations, SOPRANOS has the advantage of including a careful account of the limited temporal validity domain of the shock-cooling model as well as allowing usage of the entirety of the early UV data. We find that the progenitor of SN 2018fif was a large red supergiant with a radius of R = 744.0 (sup +183.0) (sub -128.0) R⨀ and an ejected mass of M(sub ej) = 9.3 (sup +0.4)(sub -5.8) M⨀. Our model also gives information on the explosion epoch, the progenitor's inner structure, the shock velocity, and the extinction. The distribution of radii is double-peaked, with smaller radii corresponding to lower values of the extinction, earlier recombination times, and a better match to the early UV data. If these correlations persist in future objects, denser spectroscopic monitoring constraining the time of recombination, as well as accurate UV observations (e.g., with ULTRASAT), will help break the extinction/radius degeneracy and independently determine both.

Supernovae↗

High fidelity simulations of contaminant dispersion in an urban environment with comparison to magnetic resonance imaging measurements

The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets both include millions of measurement voxels and the comparisons highlight the complex 3D nature of the flow including strong vertical velocities in spanwise street canyons and flow acceleration in streamwise street canyons. The concentration fields are qualitatively similar albeit the LES shows larger dispersion. A quantitative analysis with performance measures compares the datasets pointwise and demonstrates that the two 3D datasets are similar with respect to many measures including a fractional bias of 0.02 (ideal=0.0), correlation coefficient of 0.87 (ideal = 1.0), and the fraction points within a factor of 2 is 0.98 (ideal = 1.0). Plume analysis compares the arrival and residence time of contaminant and is found to vary significantly with location within the urban environment with arrival times between 0 and 1.25 and differences within the contaminant cloud less than 10% at most locations.

54 ENVIRONMENTAL SCIENCES↗

Baseline [ 18 F]GTP1 tau PET imaging is associated with subsequent cognitive decline in Alzheimer’s disease

Background: The role and implementation of tau PET imaging for predicting subsequent cognitive decline in Alzheimer’s disease (AD) remains uncertain. This study was designed to evaluate the relationship between baseline [ 18 F]GTP1 tau PET and subsequent longitudinal change across multiple cognitive measures over 18 months. Methods: Our analyses incorporated data from 67 participants, including cognitively normal controls (n = 10) and β-amyloid (Aβ)-positive individuals ([ 18 F] florbetapir Aβ PET) with prodromal (n = 26), mild (n = 16), or moderate (n = 15) AD. Baseline measurements included cortical volume (MRI), tau burden ([ 18 F]GTP1 tau PET), and cognitive assessments [Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR), 13-item version of the Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog13), and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)]. Cognitive assessments were repeated at 6-month intervals over an 18-month period. Associations between baseline [ 18 F]GTP1 tau PET indices and longitudinal cognitive performance were assessed via univariate (Spearman correlations) and multivariate (linear mixed effects models) approaches. The utility of potential prognostic tau PET cut points was assessed with ROC curves. Results: Univariate analyses indicated that greater baseline [ 18 F]GTP1 tau PET signal was associated with faster rates of subsequent decline on the MMSE, CDR, and ADAS-Cog13 across regions of interest (ROIs). In multivariate analyses adjusted for baseline age, cognitive performance, cortical volume, and Aβ PET SUVR, the prognostic performance of [ 18 F]GTP1 SUVR was most robust in the whole cortical gray ROI. When AD participants were dichotomized into low versus high tau subgroups based on baseline [ 18 F]GTP1 PET standardized uptake value ratios (SUVR) in the temporal (cutoff = 1.325) or whole cortical gray (cutoff = 1.245) ROIs, high tau subgroups demonstrated significantly more decline on the MMSE, CDR, and ADAS-Cog13. Conclusions: Our results suggest that [ 18 F]GTP1 tau PET represents a prognostic biomarker in AD and are consistent with data from other tau PET tracers. Tau PET imaging may have utility for identifying AD patients at risk for more rapid cognitive decline and for stratification and/or enrichment of participant selection in AD clinical trials.

60 APPLIED LIFE SCIENCES↗

Multifrequency analysis of a decametric storm observed at Voyager 1 and ground-based observatories

Observations of a Jovian decametric non-Io-A noise storm made from Voyager 1, the University of Florida Radio Observatory, the University of Texas Radio Astronomy Observatory, and the Jupiter station at Goddard Space Flight Center at frequencies of 26.3, 22.2, 20.0, and 18.0 MHz were found to be correlated. The activity observed at the ground stations occurred 68 min after the corresponding activity at Voyager 1. After correction is made for propagation time differences, this delay is reduced to 34 min. It is demonstrated that at each frequency the envelope of the individual-event beams occurring during the storm (some or all of which are associated with dynamic spectral arcs) is a quasi-constant structure that corotates with the inner Jovian magnetosphere, and that the width of this envelope beam is frequency dependent. The width increases as frequency is decreased, mainly because of the change in position of the trailing-edge beam boundary. Evidence for a relatively slow temporal change in beam geometry is also presented.

Maeda, K.↗

System and Method for Finite Element Simulation of Helicopter Turbulence

The present invention provides a turbulence model that has been developed for blade-element helicopter simulation. This model uses an innovative temporal and geometrical distribution algorithm that preserves the statistical characteristics of the turbulence spectra over the rotor disc, while providing velocity components in real time to each of five blade-element stations along each of four blades. for a total of twenty blade-element stations. The simulator system includes a software implementation of flight dynamics that adheres to the guidelines for turbulence set forth in military specifications. One of the features of the present simulator system is that it applies simulated turbulence to the rotor blades of the helicopter, rather than to its center of gravity. The simulator system accurately models the rotor penetration into a gust field. It includes time correlation between the front and rear of the main rotor, as well as between the side forces felt at the center of gravity and at the tail rotor. It also includes features for added realism, such as patchy turbulence and vertical gusts in to which the rotor disc penetrates. These features are realized by a unique real time implementation of the turbulence filters. The new simulator system uses two arrays one on either side of the main rotor to record the turbulence field and to produce time-correlation from the front to the rear of the rotor disc. The use of Gaussian Interpolation between the two arrays maintains the statistical properties of the turbulence across the rotor disc. The present simulator system and method may be used in future and existing real-time helicopter simulations with minimal increase in computational workload.

McFarland, R. E.↗

Dynamical Modulation of Solar Flare Electron Acceleration due to Plasmoid-shock Interactions in the Looptop Region

A fast-mode shock can form in the front of reconnection outflows and has been suggested as a promising site for particle acceleration in solar flares. Recent developments in the study of magnetic reconnection have shown that numerous plasmoids can be produced in a large-scale current layer. Here we investigate the dynamical modulation of electron acceleration in the looptop region when plasmoids intermittently arrive at the shock by combining magnetohydrodynamics simulations with a particle kinetic model. As plasmoids interact with the shock, the looptop region exhibits various compressible structures that modulate the production of energetic electrons. The energetic electron population varies rapidly in both time and space. The number of 5–10 keV electrons correlates well with the compression area, while that of >50 keV electrons shows good correlation with the strong compression area but only moderate correlation with shock parameters. We further examine the impacts of the first plasmoid, which marks the transition from a quasi-steady shock front to a distorted and dynamical shock. The number of energetic electrons is reduced by ~20% at 15–25 keV and nearly 40% for 25–50 keV, while the number of 5–10 keV electrons increases. In addition, the electron energy spectrum above 10 keV evolves softer with time. We also find that double or even multiple distinct sources can develop in the looptop region when the plasmoids move across the shock. Our simulations have strong implications to the interpretation of nonthermal looptop sources, as well as the commonly observed fast temporal variations in flare emissions, including the quasi-periodic pulsations.

79 ASTRONOMY AND ASTROPHYSICS↗

Picture this SELFI: Submillimeter Enceladus Life Fundamentals Instrument

The Submillimeter Enceladus Life Fundamentals Instrument (SELFI) is a passive remote sensing submillimeter heterodyne spectrometer being developed at NASA GSFC under NASA's Maturation of Instruments for Solar System Exploration (MatISSE) program. SELFI will advance submillimeter receiver technology by 1) investigating the chemical and isotopic compositions and corresponding densities of Enceladus' plume material, their vertical thermal structures, and the transport mechanisms within the plumes, and 2) characterizing the source regions from which the plumes emerge. The Enceladus plumes are important in the context of life and habitability of its subsurface ocean environment. SELFI remote sensing measurements will 1) measure the spatial and temporal variabilities in the plume chemical compositions, 2) provide insight in to Enceladus' subsurface ocean environment by monitoring H2O, HDO, d18O, and d17O, 3) constrain the oxidation state of the subsurface ocean using H2O2 and O3, and 4) utilize the SO2 and H2S spectral signatures to constrain the impact arising from both the sea-floor volcanoes and pre-biotic molecules. Moreover, the detection of the remaining molecular species (14 in total) is vital to improving the current state of knowledge of Enceladus' subsurface ocean habitability this also permits us to explore the chemical alteration processes arising from primordial volatiles that have been observed in comets. Lastly, SELFI's continuum observations enable the correlation between observed variations in plume activity with surface temperatures.SELFI is currently being developed under a technology maturation program that will advance the RF-to-digital electronics of a submillimeter-wave heterodyne spectrometer to simultaneously observe fourteen molecular species with resonances between 530 GHz and 600 GHz. SELFI will have fine radiometric resolution, high spectral resolution (resolving power R > 106), multiple continuum channels and a high dynamical range, necessary to map Enceladus across its 30 K to 250 K temperature range. Under the MatISSE program, SELFI will advance from TRL 4 to 6 four key technologies of the RF-to-digital subsystem, which are: 1) the RF low noise amplifier design; 2) the single-sideband (SSB) mixer and local oscillator; 3) the IF assembly down-converter that maps the fourteen species to 2 x 500 MHz bandwidth; and 4) the digital spectrometer electronics.

Racette, Paul↗

A Spatially Coherent Global Soil Moisture Product with Improved Temporal Resolution

Global soil moisture products that are completely independent of any type of ancillary data and solely rely on satellite observations are presented. Additionally, we further develop an existing downscaling technique that enhances the spatial resolution of such products to approximately 11 km. These products are based on internal modules of the Land Parameter Retrieval Model (LPRM), an algorithm that uses the radiative transfer equation to link soil moisture, vegetation optical depth and land surface temperature to observed brightness temperatures. The soil moisture product that is independent of any type of ancillary data uses the internally calculated dielectric constant as a soil moisture proxy. This data product is not influenced by errors associated with coarse-scale global soil property maps or by any other type of forcing (e.g. re-analysis) data and is therefore solely based on satellite microwave observations. The second step builds upon recent developments to increase the spatial resolution of the LPRM retrievals using a smoothing filter downscaling method. With this method we can attain a spatial resolution that can be more useful at the scale of local and regional hydrological studies as well. The steps presented in this paper were applied to observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). The newly derived data sets were validated using ground-based observations from the International Soil Moisture Network (ISMN). The internally calculated dielectric constant product results in significantly more days with valid retrievals than the original soil moisture data products, in particular over arid regions. The dielectric constant product resulted in similar correlations with in situ data as the original soil moisture data product. Together, these findings demonstrate the usefulness of this new dielectric constant product for the hydrological modeling community and climate studies. A case study on the Australian Fitzroy catchment demonstrated that the downscaled data product has a more detailed spatial description of soil moisture, especially during wet and dry conditions with more pronounced dry and wet regions within the catchment. The increased resolution data products could therefore improve runoff predictions and this study demonstrated the potential added value of a transitioning from a spatial resolution of 56 km toward a higher resolution of 11 km. The hydrological implications of these newly developed data records are not only linked to AMSR-E satellite data, but also to the next generation Soil Moisture Active and Passive (SMAP) mission where a 9 km spatial resolution is the target resolution for satellite soil moisture products. The new data products will not replace the current LPRM products, but will be added to the existing array of data products and will become publicly available through our data portals.

spatial↗