cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6383770
title: Dataset of the survey on the digital transformation of business processes at universities in Germany

description: In spring 2022, a broad survey was conducted among all 423 German universities on the status and the future of the digitalisation of administrative business processes. During the research survey, participants gave or rejected their consent for the publication of their contribution as open data. Respecting the roughly 30% of participants who declined, we published all remaining data here on Zenodo. The raw version of the dataset contains filtered, but pseudonymised data. The second version of the dataset is modified by the quality control process as described in section 3.3. of the corresponding Data Paper. The published data also includes the catalogue of questions indicating the respective category of time and competency pattern in which the question was used. This catalogue also contains the match with the PDF printout of the web-based questionnaire and the corresponding variables (V1-V1073) of the data records. Finally, the general introduction as well as the proposed letter to the target groups are included in the data files for reference.
DOI: 10.5281/zenodo.8189322
title: CT Data of Battery Pouch Cell with Defects

description: These are CT slices as TIF files. Data: cubic voxels of (22 µm)³ You may also open the included project file in VGStudio or the free myVGL viewer (https://www.volumegraphics.com/en/download-viewer.html) or other compatible software. The sample was prepared by Johannes Münch. For further details see the following paper: https://doi.org/10.1002/ente.202300323
description: Measurement device funded by the European Union, Program EFRE - Horizon 2020 - InfraPro, Project MERL-G.
description: {"references": ["Raw measurement data: 10.5281/zenodo.8188961"]}
DOI: 10.5281/zenodo.8300659
title: Data and Code supplement to: Effects of intraspecific variation in a native species´ phenology on its coexistence with non-native plants

description: Data and code to generate the results of the paper published at Oikos "Effects of intraspecific variation in a native species´ phenology on its coexistence with non-native plants". Both R files can be independently run, and datasets include the raw data to generate the interaction coefficients according Lasthenia phenology or simulations to investigate the effect of intraspecific trait variation of Lasthenia population abundances.
DOI: 10.6073/pasta/74b690cd34d9d915d185fa6473ea2cf7
title: Data from oceanographic moorings deployed on the Antarctic Continental Shelf (and inshore) west of the Antarctic Peninsula as part of the Palmer Long Term Ecological Research Project (PAL LTER), 2007 - 2017.

description: Oceanographic moorings have been deployed beginning in January 2007 on the Antarctic Continental Shelf (and inshore) west of the Antarctic Peninsula as part of the Palmer Long Term Ecological Research Project (PAL LTER). The moorings have been located at several sites, each deployment lasting typically just under one year, as moorings are recovered at the beginning of the PAL LTER annual January cruise and deployed at the end of the cruise. Some sites have had mutliple deployments (ie, multiple years) while others have a mooring for only one year. Any given year had between 1 and 5 deployments. The moorings were subsurface typically with tops about 50 meters below the surface attempting to always sample the winter mixed layer and below. Each mooring consisted of a thermister string designed to well-capture the vertical temperature structure and betwee 1 and 7 current meters designed to capture the main features of the current structure. A conductivity cell was deployed infrequently to obtain salinity at a single depth.
DOI: 10.6084/m9.figshare.22770671
title: Non-Cognitive Data

description: Non-cognitive dataset 2
DOI: 10.7927/h4zk5dqs
title: Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, 1998-2016
title: Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), with GWR v1 (1998-2016)

description: The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, 1998-2016 consist of annual concentrations (micrograms per cubic meter) of ground-level fine particulate matter (PM2.5), with dust and sea-salt removed. This data set combines AOD retrievals from multiple satellite instruments including the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging SpectroRadiometer (MISR), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS). The GEOS-Chem chemical transport model is used to relate this total column measure of aerosol to near-surface PM2.5 concentration. Geographically Weighted Regression (GWR) is used with global ground-based measurements to predict and adjust for the residual PM2.5 bias per grid cell in the initial satellite-derived values. These estimates are primarily intended to aid in large-scale studies. Gridded data sets at 0.01 degrees are provided to allow users to agglomerate data as best meets their particular needs. Data sets are gridded at the finest resolution of the information sources that were incorporated, but do not fully resolve PM2.5 gradients at the gridded resolution due to influence by information sources at coarser resolutions. The data are distributed as GeoTIFF files and are in WGS 84 projection.
DOI: 10.18112/openneuro.ds004357.v1.0.0
title: Features-EEG
DOI: 10.5281/zenodo.10044076
title: Electron concentration profiles calculated using eight-component model of the ionospheric D-region and two different set of input atmospheric data

description: The files contain electron concentration Ne profiles during solar X-ray flares that occurred on 9-11 June 2014. The altitude range is 50-90 km.
Values of electron concentration were calculated using eight-component model of the ionospheric D-region and two different set of input atmospheric data (MSIS neutral atmosphere model and Aura satellite measurements). Results are obtained for ten VLF paths: from European transmitters ICV, TBB, GQD, GBZ, and DHO to Mikhnevo geophysical observatory (55°N 38°E) and A118 SID station (43°N 1°E).
The data is presented as MATLAB files. Each .mat file contains data and variable "description" with data's structure information.
DOI: 10.48577/jpl.ldqupk
title: Modeling Science Return from the Lunar Crater Radio Telescope on the Far Side of the Moon

description: The era following the separation of CMB photons from matter, until the emergence of the first stars and galaxies, is known as the Cosmic Dark Ages. The study of the electromagnetic radiation emitted by neutral hydrogen at the 21~cm rest wavelength is the only way to explore this significant phase of the history of the Universe, offering opportunities to investigate essential questions about dark matter physics, the standard cosmological model, and inflation. Due to cosmological redshift, this signal is now only observable at frequencies that cannot be accessed from the surface of the Earth due to ionospheric absorption and reflection. With the Lunar Crater Radio Telescope (LCRT), we aim at carrying out unprecedented measurements of the sky-averaged redshifted signal spectrum in the 4.7-47 MHz band, by deploying a 350m-diameter parabolic reflector mesh inside a lunar crater on the far side of the Moon and suspending a receiver at its focus. This work discusses the feasibility of the LCRT science goals through the development of a science model, with emphasis on post-processing techniques to extract the Dark Ages signal from the galactic foreground dominating the expected raw data. This model can be used to vary critical instrument and mission parameters to understand their effect on the quality of the retrieved signal.
DOI: 10.48577/jpl.8nakmm
title: AGU Talk on OCO-2 Emulator

description: No abstract available.
DOI: 10.48577/jpl.lejpgw
title: Multi-Project Telemetry-based Digital Twin Environment for Space-Mission Development, Analysis, and Operations

description: Real-time telemetry-based, 3D situational-awareness visualizations for deep space and earth-orbiting missions have proven to be vital during all mission phases from project for- mulation, mission development, design, verification, and post- launch operations. These visualizations play key roles in sending flight system health and status to engineers and communicat- ing mission goals to stakeholders and the public. This real- time telemetry-based visualization technology has been used for many previous NASA/JPL missions including Mars 2020, Mars Science Laboratory (MSL), Low-Density Supersonic Deceler- ator (LDSD), NASA’s Soil Moisture Active Passive (SMAP), Galileo, and many NASA/JPL robotic systems research and development projects. Despite the number of missions that use these visualizations to carry out mission operations, there currently exists no multi-project environment. The current development model of building new and unique telemetry vi- sualization software systems for each new mission is extremely cost-ineffective. In this paper, we, from JPL’s Mission Control Systems Section, introduce Theia, our multi-project space mis- sion telemetry-based visualization system which we offer as a low-cost, easily configurable, multi-project system inspired by our recent work on the Entry, Descent, and Landing (EDL) sequence for the Mars 2020 Perseverance Rover mission. The Theia telemetry visualization system is an end-to-end solution that listens to a real-time telemetry or simulation data source, processes, packages, and streams that data through secure WebSockets to multiple simultaneously connected web browser clients executing our TheiaJS 3D visualization engine. TheiaJS presents the data to the user through an interactive 3D in- terface, extendable as required by individual missions. We describe Theia’s complete system design and architecture, the construction and rendering of a flight-system Digital Twin, and the data pipeline needed to accurately and continuously update the Digital Twin and its environment. We illustrate Theia’s use using historical data from two previous missions: Mars Science Laboratory (MSL) and Mars Perseverance Rover 2020, as well as data from future missions such as NISAR and Psyche. In addition, we discuss challenges, system verification, validation, and integration with predictive models and analysis tools. We further explore Theia as the core of a fully integrated real-time flight mission analysis and visualization environment.
DOI: 10.48577/jpl.ip7sh1
title: CESM2-Assisted Analysis of GRACE/+FO Terrestrial Water Storage

description: No abstract available.
DOI: 10.48577/jpl.qj5lr1
title: AGU2023: An Open Source Framework for Federation of Earth System Digital Twins

description: No abstract available.
DOI: 10.48577/jpl.pddcnz
title: All-Metal Metasurface Antenna for W-band Radiometer

description: All metal metasurface antennas are under development for W-band radiometer at the NASA’s Jet Propulsion Laboratory. The metasurface antenna directs the radiated beam by the holographic approach. The pillbox beamformer is fed using one (or more) horns located at the focal plane of the parabolic reflector of the pillbox beamformer. These antennas are planar and low-profile and are thus suitable for Cubesat and Smallsat platforms. The proposed antenna demonstrates a directivity as high as 31 dBi with an aperture efficiency of 65%, and a reflection coefficient better than -15 dB in the desired 93-95 GHz frequency band. The antenna is being manufactured and the measured performance will be presented at the conference.
DOI: 10.48577/jpl.adeyg0
title: Towards Continental Vertical Land Maps from InSAR – in anticipation of the OPERA Project Displacement Products

description: No abstract available.
DOI: 10.48577/jpl.kbkzia
title: What does complexity science mean for Heliophysics? A living history and demonstrating a new paradigm in the study of GICs

description: No abstract available.
DOI: 10.48577/jpl.p7vmoo
title: Investigating the Formation Environments of Hydrated Silica in Syrtis Major, Mars

description: No abstract available.
DOI: 10.48577/jpl.4uxsap
title: Ring Seismology and Saturn's Winds, Composition Gradients, and Tides

description: No abstract available.
DOI: 10.48577/jpl.qip43m
title: OPERA talk at SNWG townhall

description: No abstract available.
DOI: 10.48577/jpl.ri8gk3
title: CARDAMOM 3.0: A versatile data assimilation framework to infer carbon, water, and energy cycling using diverse Earth observations

description: No abstract available.
DOI: 10.48577/jpl.v4j9e0
title: GUSTO Observations of the Dense Warm Interstellar Medium (D-WIM)

description: No abstract available.
DOI: 10.48577/jpl.fw9vdu
title: SBG Project Overview

description: No abstract available.
DOI: 10.48577/jpl.mxioyz
title: Water Vapor Measurements inside clouds and storms using a Differential Absorption Radar

description: NASA’s Vapor In-cloud Profiling Radar (VIPR) is a tunable G-band radar designed for in-cloud and precipitation humidity remote sensing. VIPR estimates humidity using the differential absorption radar (DAR) technique. This technique exploits the difference between atmospheric attenuation at different frequencies (“on” and “off” an absorption line) and combines it with the ranging capabilities of the radar to estimate the absorbing gas concentration along the radar path. We analyze the 5 VIPR humidity measurements during two NASA field campaigns: (1) the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign, with the objective of studying wintertime snowstorms focusing on East Coast cyclones; and (2) the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign which studied the synergy between DAR (VIPR) and differential absorption lidar (DIAL, the High altitude Lidar Observatory - HALO) measurements.We discuss a comparison with dropsondes launched during these 10 campaigns as well as an intercomparison against the ERA5 reanalysis fields. Thus, this study serves as an additional evaluation of ERA5 lower tropospheric humidity fields. Overall, in-cloud and in-snowstorm comparisons suggest that ERA5 and VIPR agree within 20% or better against the dropsondes. The exception is during SOA2RSE (i.e., in fair weather), where ERA5 exhibits up to a 50% underestimation above 4 km. We also show a smooth transition in water vapor profiles between the incloud and clear-sky measurements obtained from VIPR and HALO respectively, which highlights the complementary nature 15 of these two measurement techniques for future airborne and space-based missions.
DOI: 10.48577/jpl.0fjpth
title: Volcano Science and Applications Observation Needs From Future Topography Missions

description: No abstract available.
DOI: 10.48577/jpl.bstizx
title: OPERA winsar talk at AGU

description: No abstract available.
DOI: 10.48577/jpl.biqcyx
title: Northward shift and narrowing of the ITCZ in 20 years of AIRS data

description: A time series analysis of Atmospheric InfraRed Sounder (AIRS) data between 2002 and 2022 show that both mean northern and southern boundaries of the Inter Tropical Convergence Zone (ITCZ) have shifted north for land and ocean. Such a shift is plausible, but has not predicted and has heretofore not been observed. The northern and southern ITCZ boundaries for land both shift northward at a rate of about 30 km/decade. For ocean, the southern boundary shifts faster than the northern boundary, resulting in a contraction of the width of the ocean ITCZ. A narrowing of the ITCZ with global warming was qualitatively predicted from energy-based considerations. The decrease in the width has been seen in ERA (European Centre for Medium Range Forecast Reanalysis) and MERRA (Modern‐Era Retrospective analysis for Research and Applications) data between 1987-2016. That result is statistically consistent in the sign and the error bars with our observations.
DOI: 10.48577/jpl.vxzcau
title: Modeling soil moisture with cumulated closure phase of interferometric SAR measurements

description: No abstract available.
DOI: 10.48577/jpl.trotbm
title: NASA Deep Space Communications: Future Mission Trends and Their Implications

description: In support of NASA’s Space Communications and Navigation (SCaN) Program Systems Engineering (PSE) Office, the Jet Propulsion Laboratory (JPL) periodically models and analyzes projected future-mission demand on the Deep Space Network (DSN) out to a thirty-year horizon. These efforts culminate in a set of capacity, spectrum, capability, and network loading trends and associated implications that can then be used to inform decisions regarding the DSN’s evolution. This paper describes the findings and recommendations emerging from the latest iteration of these studies. These are always presented to SCaN for strategic planning and programmatic decisions. On the whole, three key factors appear to be driving how the DSN will need to evolve in the future: (1) unparalleled growth in the number of robotic spacecraft, (2) the emergence of relatively short but tracking-intensive human lunar exploration missions, and (3) dramatic data rate and associated data volume increases. The growth in robotic spacecraft numbers is projected to substantially raise the level of “baseload” demand on the network. On top of this, the intensive tracking associated with each 2-to-4 week human lunar mission is projected to create periodic peak demand levels well in excess of what the DSN has historically supported. To the extent that these missions and certain types of robotic science missions also require much higher data rates, larger-bandwidth uplink and downlink frequencies (e.g., 22/26 GHz) will be needed. And, the data volumes associated with these higher data rates will likely create data handling and management challenges far greater than what NASA has previously had to contend with for deep space missions. In the human Mars exploration era, these higher data rates, in combination with the extreme range distance when Mars is far from Earth, will necessitate arraying up multiple antennas in order to close the communications links – potentially exacerbating any unresolved antenna-hour demand issues in that timeframe. These findings suggest that, in addition to its planned 18m Lunar Exploration Ground System, NASA: (1) pursue commercial and international/university partner antenna agreements for backfilling antenna-hour supply shortages during peak demand periods, (2) implement ways to use existing antennas more efficiently (e.g., by improving antenna beam-sharing capabilities and equipping more antennas with expanded frequency band capabilities), (3) mitigate increases in “baseload” demand by building two additional antennas per Deep Space Communications Complex beyond what is currently planned, and (4) introduce new technologies and systems that ultimately change how deep space communications occur (e.g., “trunk link” relays at the Moon and Mars that “funnel” all the data from each location down to a single in-view antenna, Delay Tolerant Networking (DTN), optical communications, and autonomous spacecraft that “phone home” only as needed). SCaN-funded studies are currently in work to further investigate and refine these suggested measures.
DOI: 10.48577/jpl.fseb0g
title: Magma storage and transport along volcanic rift zones

description: No abstract available.
DOI: 10.48577/jpl.xs6rgd
title: Using Multiple Space-based Instruments to Constrain Emissions from Cities across the United States

description: No abstract available.
DOI: 10.5281/zenodo.10396657
title: redundant
DOI: 10.5281/zenodo.10396658
title: redundant
DOI: 10.48577/jpl.r9qum8
title: Evaluating Satellite-based XCO2 Measurements From OCO-2 and OCO-3 Against Ground-based TCCON and COCCON Measurements

description: No abstract available.
DOI: 10.48577/jpl.ol8nm7
title: Psyche Overview, AIAA TC presentation

description: No abstract available.
DOI: 10.48577/jpl.df5xwz
title: Leveraging Deep Learning for Physical Model Bias of Global Air Quality Estimates

description: Air pollution is the world’s largest environmental risk factor for human disease1 and premature death, resulting in more than 6 million premature deaths in 2019.2 Currently, there is still a challenge to model one of the most important air pollutants,3 surface ozone (O3), particularly at scales relevant for human health impacts, with4 the drivers of global ozone trends at these scales largely unknown, limiting the5 practical use of physics-based models. We employ a 2-D Convolutional Neural6 Network (CNN)-based U-Net architecture that estimates surface ozone MOMO-7 Chem model residuals, referred to as model bias. We demonstrate the potential8 of this technique in North America and Europe, highlighting its ability better9 to capture physical model residuals compared to a traditional machine learning10 method. We assess the impact of incorporating land use information from high-11 resolution satellite imagery to improve model estimates. Importantly, we discuss12 how our results can improve our scientific understanding of the factors impacting13 ozone bias at urban scales that can be used to improve environmental policy
DOI: 10.48577/jpl.p7sdyd
title: Exploring Mars with Autonomous Robots

description: No abstract available.
DOI: 10.48577/jpl.wdmbij
title: Using Unsupervised and Supervised Learning and Digital Twin for deep Convective Ice Storm Classification

description: Smart Ice Cloud Sensing (SMICES) is a small-sat concept in which a primary radar intelligently targets ice storms based on information collected by a lookahead radiometer. Critical to the intelligent targeting is accurate identification of storm/cloud types from eight bands of radiance collected by the radiometer. The cloud types of interest are: clear sky, thin cirrus, cirrus, rainy anvil, and convection core. We describe multi-step use of Machine Learning and Digital Twin of the Earth's atmosphere to derive such a classifier. First, a digital twin of Earth's atmosphere called a Weather Research Forecast (WRF) is used generate simulated lookahead radiometer data as well as deeper "science" hidden variables. The datasets simulate a tropical region over the Caribbean and a non-tropical region over the Atlantic coast of the United States. A K-means clustering over the scientific hidden variables was utilized by human experts to generate an automatic labelling of the data - mapping each physical data point to cloud types by scientists informed by mean/centroids of hidden variables of the clusters. Next, classifiers were trained with the inputs of the simulated radiometer data and its corresponding label. The classifiers of a random decision forest (RDF), support vector machine (SVM), Gaussian naïve bayes, feed forward artificial neural network (ANN), and a convolutional neural network (CNN) were trained. Over the tropical dataset, the best performing classifier was able to identify non-storm and storm clouds with over 80% accuracy in each class for a held-out test set. Over the non-tropical dataset, the best performing classifier was able to classify non-storm clouds with over 90% accuracy and storm clouds with over 40% accuracy. Additionally both sets of classifiers were shown to be resilient to instrument noise.
DOI: 10.48577/jpl.4zpejl
title: OPERA Coregistered Single Look Complex products from Sentinel-1 data

description: No abstract available.
DOI: 10.48577/jpl.ejdvzq
title: The 2 Stream-Exact Single Scattering (2S-ESS) Radiative Transfer Model

description: No abstract available.
DOI: 10.48577/jpl.l6dh4n
title: Hindcasting hydrologic conditions for California’s landslides triggered by the parade of atmospheric rivers (ARs) in January 2023

description: No abstract available.
DOI: 10.48577/jpl.sgulwr
title: Predictability of fossil fuel CO2 from air quality emissions

description: No abstract available.
DOI: 10.48577/jpl.sueooh
title: (ExEP) Exoplanet Exploration Program Technology Update

description: No abstract available.
DOI: 10.48577/jpl.4oahef
title: PROFILE

description: No abstract available.