cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48577/jpl.dqtxx4
title: A Semi-Empirical Modeling of Soil Moisture, Vegetation and Surface Roughness Impact on CYGNSS Reflectometry Data

description: Data from the Cyclone Global Navigation Satellite System (CYGNSS) mission augmented with a physical surface scattering model were analyzed to develop a semi-empirical model, which consists of three main modeling components for soil moisture, vegetation and surface roughness. CYGNSS data collected from March 2017 to March 2020 were collocated with the soil moisture data from the Soil Moisture Active Passive (SMAP) mission and climatology Vegetation Water Content (VWC) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data. The matchup data were binned as a function of soil moisture, VWC and incidence angle. The CYGNSS data were calibrated using a coherent reflection equation to obtain an effective reflectivity. The response of CYGNSS effective reflectivity to soil moisture changes is consistent with the change of Fresnel reflectivity based on Mironov’s soil dielectric constant model used by the SMAP and Soil Moisture Ocean Salinity (SMOS) missions for soil moisture retrieval. The CYGNSS effective reflectivity decreases approximately linearly (in dB) with respect to the NDVI-VWC. The estimated values of vegetation attenuation parameter (b) agree with values published in the literature and are corroborated with the estimated values of b using the SMAP dual-polarized channel algorithm based on land cover types. A CYGNSS surface scattering map has been derived and reveals a mixed contribution of coherent and incoherent scattering effects and the effects of topography. The semi-empirical model, leveraging two of the key modeling functions used by microwave radiometry, will pave the way for a synergistic use of reflectometry and radiometry data for multi-parameter retrieval and development of consistent soil moisture products.
DOI: 10.48577/jpl.p49gwk
title: New approach to evaluate satellite derived XCO2 over oceans by integrating ship and aircraft observations

description: Abstract. Satellite observations provide spatially-resolved global estimates of column-averaged mixing ratios of CO2 (XCO2) over the Earth’s surface. The accuracy of these datasets can be validated against reliable standards in some areas, but other areas remain inaccessible. To date, limited reference data over oceans hinders successful uncertainty quantification or bias correction efforts, and precludes reliable conclusions about changes in the carbon cycle in some regions. Here, we propose a new approach to analyze and evaluate seasonal, interannual and latitudinal variations of XCO2 over oceans by integrating cargo-ship (SOOP, Ship Of Opportunity) and commercial aircraft (CONTRAIL, Comprehensive Observation Network for Trace gases by Airliner) observations with the aid of state-of-the art atmospheric chemistry-transport model calculations. The consistency of the “in situ based column-averaged CO2” dataset (in situ XCO2) with satellite estimates was analyzed over the Western Pacific between 2014 and 2017, and its utility as reference dataset evaluated. Our results demonstrate that the new dataset accurately captures seasonal and interannual variations of CO2. Retrievals of XCO2 over the ocean from GOSAT (Greenhouse gases observing satellite: NIES v02.75, National Institute for Environmental Studies; ACOS v7.3, Atmospheric CO2 Observation from Space) and OCO-2 (Orbiting Carbon Observatory, v9r) observations show a negative bias of about 1 parts per million (ppm) in northern midlatitudes, which was attributed to measurement uncertainties of the satellite observations. The NIES retrieval had higher consistency with in situ XCO2 at midlatitudes as compared to the other retrievals. At low latitudes, it shows many fewer valid data and high scatter, such that ACOS and OCO-2 appear to provide a better representation of the carbon cycle. At different times, the seasonal cycles of all three retrievals show positive phase shifts of one month relative to the in situ data. The study indicates that even if the retrievals complement each other, remaining uncertainties limit the accurate interpretation of spatiotemporal changes in CO2 fluxes. A continuous long-term XCO2 dataset with wide latitudinal coverage based on the new approach has a great potential as a robust reference dataset for XCO2 and can help to better understand changes in the carbon cycle in response to climate change using satellite observations.
DOI: 10.48577/jpl.v9saco
title: Mars’ Obliquity-Driven CO2 Exchange between the Atmosphere, Regolith, and Polar Cap

description: Discerning the total mass of Mars’ exchangeable CO2 inventory has been elusive for decades due to the unknown adsorptive capacity of its regolith. Now, however, the stratigraphy of Mars’ recently discovered South Polar Massive CO2 Ice Deposit (MCID) provides a record of orbit-driven CO2 exchange between its polar cap, atmosphere, and regolith with sufficient constraint to calculate the adsorptive capacity of its regolith and therefore the total mass of its exchangeable CO2 inventory. We use a numerical climate model and Markov Chain Monte Carlo analysis to show that the observed MCID stratigraphic record is most consistent with a total exchangeable CO2 inventory of 〖1.9〗_(-0.5)^(+1.0)×10^17 kg (49_(-12)^(+26) mbar), active regolith thickness of 244_(-92)^(+150) m, and regolith specific surface area of 〖1.0〗_(-0.7)^(+2.6)×10^4 m^2 kg^(-1). The maximum likelihood value for Mars’ adsorbed CO2 inventory is 1.3 ×10^17 kg (35 mbar), with a 68% confidence interval of 8.4 ×10^16 to 2.3 ×10^17 kg (22 to 62 mbar). Our best-fit model yields a peak mean annual surface pressure 30% lower than CO2 exchange models that neglect an adsorbing regolith. We provide machine-readable text files of our results to aid future study of Mars’ climate.
DOI: 10.48577/jpl.ckawcb
title: Deep Space Network Scheduling via Mixed Integer Linear Programming

description: NASA’s Deep Space Network (DSN) is a globally-spanning communications network responsible for supporting the interplanetary spacecraft missions of NASA and other international users. The DSN is a highly utilized asset, and the large demand for its’ services makes the assignment of DSN resources a daunting computational problem. In this paper, we cast the this challenging scheduling task as a Mixed-Integer Linear Programming (MILP) optimization. We offer a novel randomization technique which is capable solving the resulting MILP formulation for large large-scale instances of the DSN scheduling. A real-world DSN dataset is utilized to demonstrate the effectiveness of the proposed MILP model and randomization approach.
DOI: 10.48577/jpl.kbmeba
title: Improving Current-based Torque Sensing forHarmonic Drives Leveraging Asymmetry inDirectional Efficiency.

description: Torque estimation is a critical requirement for several manipulation and mobility tasks such as closed-loop force control, gravity compensation, contact detection, etc. This can be achieved by direct sensing with torque sensors which are heavy and significantly increase the load requirements of the system. An alternative approach is to using indirect sensing which estimates torques by measuring current consumption of the actuator. Unfortunately, this indirect approach suffers from low accuracy. We propose an estimation algorithm to improve this accuracy for the popular harmonic drive-based actuators. This is achieved by exploiting the asymmetry in efficiency which depends on the direction of torque transmission i.e. the efficiency of torque transmission is significantly lower in the output to input direction compared to input to output. This direction can be identified from the motor current and encoder data when the actuator has non-zero angular velocity but is not observable when the actuator is not moving. Our proposed solution significantly improves the accuracy for the former case and provides upper and lower bounds of torque estimates for the latter case. This is validated through experiments on hardware and comparison with ground truth from direct torque sensing.
DOI: 10.48577/jpl.xnxydh
title: Compact Scanning Retarding Potential Analyzer

description: A miniature scanning electrostatic energy analyzer has been developed for measurements of the ion energy distribution in low-pressure plasma discharges. The retarding potential analyzer utilizes four grids to reject the incident electron flux and discriminate the ion energy. It features a compact size of 5-mm diameter and 2.5-mm thick and uses a simple configuration to mount the grids and provide voltage isolation using high temperature ceramic cement. This avoids complicated MEMS fabrication techniques, and the selection of different grid transparencies eliminates the need for precise aperture alignment. Mounting on a fast-scanning 2-axis probe drive eliminates overheating of the ceramics and subsequent current leakage, which permits insertion into challenging locations and provides profiles of the ion energy in the plasma discharge. Guidelines for the analyzer design for high density operation are discussed, and the performance of the analyzer is shown for measurements in hollow cathode plume in xenon plasmas.
DOI: 10.48577/jpl.bdbhuo
title: Speckle Imaging Characterization of Radial Velocity Exoplanet Systems

description: We conducted speckle imaging observations of 53 stellar systems that were members of long-term radial velocity (RV) monitoring campaigns and exhibited substantial accelerations indicative of plane- tary or stellar companions in wide orbits. Our observations were made with blue and red filters using the Differential Speckle Survey Instrument at Gemini-South and the NN-Explore Exoplanet Stellar Speckle Imager at the WIYN telescope. The speckle imaging identifies eight luminous companions within 2′′ of the primary stars. In three of these systems—HD 1388, HD 87359, and HD 104304—the properties of the imaged companion are consistent with the RV measurements, suggesting that these companions may be associated with the primary and the cause of the RV variation. For all 53 stellar systems, we derive differential magnitude limits (i.e., contrast curves) from the imaging. We extend this analysis to include upper limits on companion mass in systems without imaging detections. In 25 systems, we rule out companions with mass greater than 0.2 M⊙, suggesting that the observed RV signals are caused by late M dwarfs or substellar (potentially planetary) objects. On the other hand, the joint RV and imaging analysis almost entirely rules out planetary explanations of the RV signals for HD 19522 and HD 114174 and suggests that the companion must have an angular separation be- low a few tenths of an arcsecond. This work highlights the importance of combined RV and imaging observations for characterizing the outer regions of nearby planetary systems.
DOI: 10.48577/jpl.jfp5nh
title: The Improved Capabilities of the Goldstone Solar System Radar Observatory

description: The Goldstone Solar System Radar (GSSR) facility is the largest fully steerable ground-based radar in the world for non-classified high-resolution ranging and imaging of planetary and small-body targets. Over the years the use of the GSSR to detect and characterize Near-Earth Objects (NEO) has become critical to keep track of potential Earth-impacting hazardous NEO. This manuscript relates the specific modifications made to the GSSR hardware and procedures in the last few years, as well as the new capabilities derived from those upgrades: reduced complexity in remote operations, increased experiment design versatility, and increased performance on bistatic radar experiments from GSSR to other complexes. In addition, we dedicate a section to provide an update on the current and near- future GSSR power capabilities as new klystrons are installed. The work detailed in this manuscript is intended to reach the broader science community in order to communicate how those modifications and the derived new capabilities can make science experiments more successful.
DOI: 10.48577/jpl.jucizt
title: The JPL Planetary and Lunar Ephemerides DE440 and DE441

description: The planetary and lunar ephemerides called DE440 and DE441 have been generated by fittingnumerically integrated orbits to ground-based and space-based observations. Compared to theprevious general-purpose ephemerides DE430, seven years of new data have been added tocompute DE440 and DE441, with improved dynamical models and data calibration. The orbit ofJupiter has improved substantially by fitting to the Juno radio range and Very Long Baseline Array(VLBA) data of the Juno spacecraft. The orbit of Saturn has been improved by radio range andVLBA data of the Cassini spacecraft, with improved estimation of the spacecraft orbit. The orbitof Pluto has been improved from use of stellar occultation data reduced against the GAIA starcatalog. The ephemerides DE440 and DE441 are fitted to the same data set, but DE441 assumesno damping between lunar liquid core and solid mantle, which avoids a divergence when integratedbackwards in time. Therefore, DE441 is less accurate than DE440 for the current century, butcovers a much longer duration of years –13,200 to +17,191, compared to DE440 covering years1550 to 2650.
DOI: 10.48577/jpl.sb8vjd
title: Polar Stratospheric Clouds: Satellite Observations, Processes, and Role in Ozone Depletion

description: Polar stratospheric clouds (PSCs) play important roles in stratospheric ozone depletion during winter and spring at high latitudes (e.g., the Antarctic ozone hole). PSC particles provide sites for heterogeneous reactions that convert stable chlorine reservoir species to radicals that destroy ozone catalytically. PSCs also prolong ozone depletion by delaying chlorine deactivation through the removal of gas-phase HNO 3 and H 2 O by sedimentation of large NAT (nitric acid trihydrate) and ice particles. Contemporary observations by the spaceborne instruments MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), MLS (Microwave Limb Sounder), and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) have provided an unprecedented polar vortex-wide climatological view of PSC occurrence and composition in both hemispheres. These data have spurred advances in our understanding of PSC nucleation and related dynamical processes, especially the firm evidence of widespread heterogeneous nucleation of both NAT and ice PSC particles, perhaps on nuclei of meteoritic origin. Heterogeneous chlorine activation appears to be well understood. Reaction coefficients on/in liquid droplets have been measured accurately, and while uncertainties remain for reactions on solid NAT and ice particles, they are considered relatively unimportant since under most conditions chlorine activation occurs on/in liquid droplets. There have been notable advances in the ability of chemical transport and chemistry-climate models to reproduce PSC temporal/spatial distributions and composition observed from space. Continued spaceborne PSC observations will facilitate further improvements in the representation of PSC processes in global models and enable more accurate projections of the evolution of polar ozone and the global ozone layer as climate changes.
DOI: 10.48577/jpl.tlfhgw
title: Closing the water cycle from observations across scales: Where do we stand?

description: Life on Earth is intimately connected to the availability of water in space and time. With a growing world population and living standards, human pressure on freshwater resources is continuously increasing, as is the exposure of humans to weather and climate-related extremes like droughts, storms, and floods. This is further exacerbated by climate change, e.g., by shifts in precipitation patterns or the intensification of extreme events. Hence human access and vulnerability to water resources is increasingly being challenged.The Global Climate Observing System (GCOS) defines a suite of Essential Climate Variables (ECVs), many of them related to the water cycle, that are required to systematically observe the Earth's changing climate. However, since long-term observations of these ECVs are typically derived from different observation techniques, platforms, instruments, and independent retrieval algorithms, they often lack the accuracy, completeness, resolution, and consistency required to characterize climate variability at multiple spatial and temporal scales. While climate change often manifests itself in subtle, yet impactful modifications of the water cycle, detecting them remains challenging.Here, we assess the capability of available ground and Earth observations of water cycle ECVs to consistently monitor the variability of the hydrological cycle at various spatial and temporal scales. We assess the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Based on the assessment, we discuss gaps in existing observation systems and formulate guidelines for future water cycle observation strategies.
DOI: 10.48577/jpl.qxewbb
title: Hybrid Retransmissions of Bundle Protocol for Reliable Deep-Space Vehicle Communications in Presence of Link Disruption

description: Targeted as the main protocol of delay/disruption-tolerant networking (DTN) for space, bundle protocol (BP) is intended to establish an overlay network for reliable file delivery in a heterogeneous networking environment. Reliable data transmission mechanisms of BP are presently under development. In this paper, a new transmission approach is proposed for BP for highly reliable data delivery in deep-space communications in presence of an unpredictable or random link disruption. The main idea of the proposed approach is to use a hybrid of proactive transmission and reactive transmission mechanisms during file transfer. Analytical models are built in various transmission cases to study the effect of link disruption on reliable transmission of BP, with focus on the number of failed transmission attempts, file delivery time and goodput performance normalized with respect to the total amount of data sent. The models are validated by the file transfer experiment over a PC-based testbed. A performance comparison between the proposed approach and the existing transmission approach with respect to transmission reliability is also presented.
DOI: 10.48577/jpl.toy1xc
title: Adapting Passive Microwave-Based Precipitation Algorithms to Variable Microwave Land Surface Emissivity to Improve Precipitation Estimation from the GPM Constellation

description: Future projections of global precipitation show substantial variability in location, duration, intensity and occurrence. A fully global satellite-based precipitation estimate that can transition across changing Earth surface conditions and complex land/water boundaries is an important capability for proper evaluation of the precipitation produced or diagnosed in weather and climate models. This capability inherently challenging owing to the complexity of the surface geophysical properties upon which the satellite-based instruments view. To date, these satellite observations originate from wide-swath passive microwave imagers and sounders. In contrast to open ocean and large water bodies, the surface emissivity contribution to passive microwave measurements is much more variable for land surfaces, with corresponding different sensitivities to near-surface precipitation.The NASA/JAXA Global Precipitation Measurement (GPM) spacecraft (2014-current) is equipped with a dual-frequency precipitation radar and a multichannel passive MW imaging sensor specifically dedicated to precipitation measurement, covering substantially more land surface than its predecessor (1997-2014) Tropical Rainfall Measuring Mission (TRMM). The synergy between GPM’s instruments has guided a number of new frameworks for passive microwave precipitation retrieval algorithms, whereby the information carried by the single narrow-swath precipitation radar is exploited to recover precipitation from a disparate constellation of passive MW imagers and sounders. With over six years of increased land surface coverage provided by GPM, new insight has been gained into the nature of the microwave surface emissivity over land and ice/snow covered surfaces, leading to improvements in a number of physical and semi-physical based precipitation retrieval techniques that adapt to variable Earth surface conditions. In this manuscript, the workings and capabilities of several of these approaches are highlighted.
DOI: 10.48577/jpl.aw9sdr
title: Integrating Field Observations and Reactive Transport Modeling to Predict Watershed Water Quality under Environmental Perturbations

description: Watersheds play a critical role in supplying water resources needed for humanuse and ecosystem health. Understanding and predicting how, when,and where changes in the quantity and quality of water resources occur underdierent environmental stresses including extreme events is crucial forsustainable management of water resources under a changing environment.However, few studies have attempted to quantify or identify the factors andprocess interactions controlling the impact of extreme events across watershedsystems. Only few large-scale studies include coordinated monitoringand modeling eorts, which limits our ability to assess the large-scale impactof extreme events on water supply and quality. Methods are lacking topropagate uncertainty in process understanding through an integrated hydrobiogeochemicalmodel framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformativeadvances in characterization technologies from high-resolution massspectrometry to airborne and satellite-based remote sensing. There are consequentrisks to our nations water security and to human and ecosystem healththat may become exacerbated with the increasing frequency of extreme eventsthat is projected for the coming decades. This paper reviews the current statusof watershed science for both water quantity and quality and identiescritical gaps in our current knowledge and modeling capability in addressingthe emergent needs in predicting watershed hydrologic and biogeochemicalresponses (i.e., water quantity and quality) under natural and anthropogenicperturbations. We highlight the need to (1) understand how environmentalperturbations including extreme events like oods and droughts propagatethrough watershed systems and assess their short- and long-term impactson watershed biogeochemistry, water quality and their recovery pathways;(2) develop and improve a watershed water quality model that reects thestate of scientic understanding gained from observations; and (3) constructa data-model fusion system for watershed characterization, process identi-cation, and mechanistic model parameterization. A large base of modeling,monitoring and data capabilities have been built by various federal governmentagencies given the relevance of water to their critical missions. Anemerging need is to build an integrated national capability for watershedwater availability and quality that can address water-related missions acrossmultiple federal agencies.