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This document defines the guidelines, principles, and formats for user-facing tutorials that demonstrate how to use the Rubin Science Platform (RSP) to analyze data from the Legacy Survey of Space and Time (LSST). All Rubin staff and the broader science community should use these guidelines when contributing to the sets of Jupyter Notebook or documentation-based tutorials maintained by the Rubin Community Science team (CST).
The Space Infrared Telescope Facility (SIRTF) was launched in August, 2003, and renamed to the Spitzer Space Telescope in 2004. Two years of observing the universe in the wavelength range from 3 to 180 microns has yielded enormous scientific discoveries. Since this magnificent observatory has a limited lifetime, maximizing science viewing efficiency (ie, maximizing time spent executing activities directly related to science observations) was the key operational objective. The strategy employed for maximizing science viewing efficiency was to optimize spacecraft flexibility, adaptability, and use of observation time. The selected approach involved implementation of a multi-engine sequencing architecture coupled with nondeterministic spacecraft and science execution times. This approach, though effective, added much complexity to uplink operations and sequence development. The Jet Propulsion Laboratory (JPL) manages Spitzer s operations. As part of the uplink process, Spitzer s Mission Sequence Team (MST) was tasked with processing observatory inputs from the Spitzer Science Center (SSC) into efficiently integrated, constraint-checked, and modeled review and command products which accommodated the complexity of non-deterministic spacecraft and science event executions without increasing operations costs. The MST developed processes, scripts, and participated in the adaptation of multi-mission core software to enable rapid processing of complex sequences. The MST was also tasked with developing a Downlink Keyword File (DKF) which could instruct Deep Space Network (DSN) stations on how and when to configure themselves to receive Spitzer science data. As MST and uplink operations developed, important lessons were learned that should be applied to future missions, especially those missions which employ command-intensive operations via a multi-engine sequence architecture.
Precipitation is a key source of freshwater; therefore, observing global patterns of precipitation and its intensity is important for science, society, and understanding our planet in a changing climate. In 2014, the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA) launched the Global Precipitation Measurement (GPM) Core Observatory (CO) spacecraft. The GPM CO carries the most advanced precipitation sensors currently in space including a dual-frequency precipitation radar provided by JAXA for measuring the three-dimensional structures of precipitation and a well-calibrated, multifrequency passive microwave radiometer that provides wide-swath precipitation data. The GPM CO was designed to measure rain rates from 0.2 to 110.0 mm h1 and to detect moderate to intense snow events. The GPM CO serves as a reference for unifying the data from a constellation of partner satellites to provide next-generation, merged precipitation estimates globally and with high spatial and temporal resolutions. Through improved measurements of rain and snow, precipitation data from GPM provides new information such as details on precipitation structure and intensity; observations of hurricanes and typhoons as they transition from the tropics to the midlatitudes; data to advance near-real-time hazard assessment for floods, landslides, and droughts; inputs to improve weather and climate models; and insights into agricultural productivity, famine, and public health. Since launch, GPM teams have calibrated satellite instruments, refined precipitation retrieval algorithms, expanded science investigations, and processed and disseminated precipitation data for a range of applications. The current status of GPM, its ongoing science, and its future plans are presented.
The current gamma-ray/neutron instrumentation development effort at NASA Goddard Space Flight Center aims to extend the use of active pulsed neutron interrogation techniques to probe the subsurface elemental composition of planetary bodies in situ. Previous NASA planetary science missions, that used neutron and/or gamma-ray spectroscopy instruments, have relied on neutrons produced from galactic cosmic rays. One of the distinguishing features of this effort is the inclusion of a high intensity 14.1 MeV pulsed neutron generator synchronized with a custom data acquisition system to time each event relative to the pulse. With usually only one opportunity to collect data, it is difficult to set a priori time-gating windows to obtain the best possible results. Acquiring time-tagged, event-by-event data from nuclear induced reactions provides raw data sets containing channel/energy, and event time for each gamma ray or neutron detected. The resulting data set can be plotted as a function of time or energy using optimized analysis windows after the data are acquired. Time windows can now be chosen to produce energy spectra that yield the most statistically significant and accurate elemental composition results that can be derived from the complete data set. The advantages of post-processing gamma-ray time-tagged event-by-event data in experimental tests using our prototype instrument will be demonstrated.
We report the use of streaming data interfaces to perform fully online data processing for serial crystallography experiments, without storing intermediate data on disk. The system produces Bragg reflection intensity measurements suitable for scaling and merging, with a latency of less than 1 s per frame. Our system uses the CrystFEL software in combination with the ASAP::O data framework. In a series of user experiments at PETRA III, frames from a 16 megapixel Dectris EIGER2 X detector were searched for peaks, indexed and integrated at the maximum full-frame readout speed of 133 frames per second. The computational resources required depend on various factors, most significantly the fraction of non-blank frames ('hits'). The average single-thread processing time per frame was 242 ms for blank frames and 455 ms for hits, meaning that a single 96-core computing node was sufficient to keep up with the data, with ample headroom for unexpected throughput reductions. Further significant improvements are expected, for example by binning pixel intensities together to reduce the pixel count. We discuss the implications of real-time data processing on the `data deluge' problem from recent and future photon-science experiments, in particular on calibration requirements, computing access patterns and the need for the preservation of raw data.
NASA's LEARN Project is an innovative program that provides long-term immersion in the practice of atmospheric science for middle and high school in-service teachers. Working alongside NASA scientists and using authentic NASA Science Mission Directorate research data, teachers develop individual research topics of interest during two weeks in the summer while on-site at NASA Langley. With continued, intensive mentoring by NASA scientists, the teachers further develop their research throughout the academic year through virtual group meetings and data team meetings mirroring scientific collaborations. At the end of the first year, LEARN teachers present scientific posters. The LEARN experience has had such an impact that multiple teachers from the first two cohorts have elected to continue their research. The LEARN project evaluation has provided insights into particularly effective elements of this new approach. Findings indicate that teachers? perceptions of the scientific enterprise have changed, and that LEARN provided substantial resources to help them take real-world research to their students. This presentation will focus on key factors from LEARN?s implementation that inform best practices for the incorporation of authentic scientific research into teacher professional development experiences. We suggest that these factors should be considered in the development of other such experiences, including: (1) The involvement of a single scientist as both the project leader/manager and the project scientist, to ensure that the project can meet teachers? needs. (2) An emphasis on framing and approaching scientific research questions, so that teachers can learn to evaluate the feasibility of studies based on scope, scale, and availability of data. (3) Long term, ongoing relationships where teachers and scientists work as collaborators, beyond the workshop ?mold.? (4) A focus on meeting the needs of individual teachers, whether their needs relate to elements of research and analysis, or to their tight professional schedules. (5) Above all, flexibility and patience. LEARN builds relationships with teachers slowly, over a long period of time. In the middle, life often intervenes. LEARN has emphasized that teachers? success is more important than deadlines or following a rigid protocol.
The CheMin X-ray diffraction instrument on the Mars Science Laboratory rover has analyzed 18 rock and soil samples in Gale crater. Diffraction data allow for the identification of major crystalline phases based on the positions and intensities of well-defined peaks and also provides information regarding amorphous and poorly-ordered materials based on the shape and positions of broad scattering humps. The combination of diffraction data, elemental chemistry from APXS (Alpha Particle X-ray Spectrometer) and evolved gas analyses (EGA) from SAM (Sample Analysis at Mars) help constrain possible amorphous materials present in each sample (e.g., glass, opal, iron oxides, sulfates) but are model dependent. We present a novel method to characterize amorphous material in diffraction data and, through this approach, aim to characterize the phases collectively producing the amorphous profiles in CheMin diffraction data. This method may be applied to any diffraction data from samples containing X-ray amorphous materials, not just CheMin datasets, but we re-strict our discussion to Martian-relevant amorphous phases and diffraction data measured by CheMin or CheMin-like instruments.
"Extreme weather events, such as hurricanes, tornadoes, floods, droughts, heatwaves, and blizzards, can cause widespread damage, disrupting ecosystems, agricultural production, and economies. The frequency and intensity of these events have been increasing, likely due to climate change, raising concerns and the need for more accurate analysis and predictions. NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC) has migrated its long-term historical datasets, including precipitation data from MERRA-2 reanalysis, GLDAS land data assimilation, and IMERG satellite observations, to the cloud. This cloud-stored data enables scientists and researchers to utilize cloud computing for advanced modeling and forecasting of extreme weather events, eliminating the need to download large datasets. In this presentation, we will provide an overview of the cloud-based data and services managed by GES DISC; demonstrate methods for accessing and analyzing time series data stored in the cloud; and compare results across various datasets to address critical questions related to extreme precipitation. We will present use cases including: 1. Determining the average total precipitation in California during January and February from 2000 to 2024, and identifying anomalous precipitation in 2021. 2. Calculating the 10, 20, 50, and 100-year return periods for maximum daily rainfall based on 25 years of historical precipitation data (2000-2024) for Maryland.
To adequately explore high priority landing sites, scientists require rovers with greater mobility. Therefore, future Mars missions will involve rovers capable of traversing tens of kilometers (vs. tens of meters traversed by Mars Pathfinder's Sojourner). However, the current process by which scientists interact with a rover does not scale to such distances. A single science objective is achieved through many iterations of a basic command cycle: (1) all data must be transmitted to Earth and analyzed; (2) from this data, new targets are selected and the necessary information from the appropriate instruments are requested; (3) new commands are then uplinked and executed by the spacecraft and (4) the resulting data are returned to Earth, starting the process again. Experience with rover tests on Earth shows that this time intensive process cannot be substantially shortened given the limited data downlink bandwidth and command cycle opportunities of real missions. Sending complete multicolor panoramas at several waypoints, for example, is out of the question for a single downlink opportunity. As a result, long traverses requiring many science command cycles would likely require many weeks, months or even years, perhaps exceeding rover design life or other constraints. Autonomous onboard science analyses can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands, for example acquiring and returning spectra of "interesting" rocks along with the images in which they were detected. Such approaches, coupled with appropriate navigational software, address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing algorithms to enable such intelligent decision making by autonomous spacecraft. Reflecting the ultimate level of ability we aim for, this program has been dubbed the "Grad Student on Mars Project". We envision, for example, an appropriately intelligent Athena-like rover at the Pathfinder landing site might be able to traverse over the ridge towards "Twin Peaks" to obtain better information on the stratigraphy of these "streamlined islands" or of the size, composition and morphology of boulders located on them. Along the traverse, the intelligent rover would collect and analyze images and obtain spectra of geologically interesting features or regions. The intelligent rover might also traverse further up Arcs Vallis, and find additional paleoflood stage indicators such as slackwater deposits. Recognizing additional regions where boulders are imbricated, noting changes in their size, distribution, morphology, composition and the associated changes in channel geometry would yield important information on the outflow channel's paleoflood history, Representative images and associated supporting data from these locations could be downlinked to Earth along with the data requested by scientists from the previous uplink opportunity. Our initial work has focused on recognizing geologically interesting portions of images. Here we summarize some of the algorithms to date.
The current gamma-ray/neutron instrumentation development effort at NASA Goddard Space Flight Center aims to extend the use of active pulsed neutron interrogation techniques to probe the subsurface geochemistry of planetary bodies in situ. All previous NASA planetary science missions, that used neutron and/or gamma-ray spectroscopy instruments, have relied on a constant neutron source produced from galactic cosmic rays. One of the distinguishing features of this effort is the inclusion of a high intensity 14.1 MeV pulsed neutron generator synchronized with a custom data acquisition system to time each event relative to the pulse. With usually only one opportunity to collect data, it is difficult to set a priori time-gating windows to obtain the best possible results. Acquiring time-tagged, event-by-event data from nuclear induced reactions provides raw data sets containing channel/energy, and event time for each gamma ray or neutron detected. The resulting data set can be plotted as a function of time or energy using optimized analysis windows after the data are acquired. Time windows can now be chosen to produce energy spectra that yield the most statistically significant and accurate elemental composition results that can be derived from the complete data set. The advantages of post-processing gamma-ray time-tagged event-by-event data in experimental tests using our prototype instrument will be demonstrated.
The Solar Oscillations Investigation-Michelson Doppler Imager (SOI-MDI) for the SOHO (Solar and Heliospheric Observatory) mission is intended to investigate the solar interior using helioseismology techniques. The SOI program consists of a coordinated set of observations intended to address a set of science objectives, an MDI instrument, and a facility that will provide data reduction and analysis capability. The MDI instrument will take filtergrams to measure LOS velocity, line and continuum intensity, and LOS magnetic fields with both 4 and 1.2 arcsec resolution, The SOI study is designed to take advantage of the anticipated SOHO telemetry by organizining the observations into four programs: structure (at all times), dynamics (two months per year), campaign (eight hours per day, 10 months per year), and magnetic field (a few minutes per day).
The twin STEREO spacecraft were launched on October 26,2006 and, after spending several weeks in alignment orbits, became operational in heliocentric orbits on January 2 1,2007. The spacecraft are now in orbits similar to Earth's and are separating from each other at a rate of about 45 degrees per year as viewed from the sun. The STEREO spacecraft are each equipped with a complement of EUV, and white light imagers as well as particles and fields in situ instruments and a radio burst tracker. In addition to full resolution data downloaded once per day, each spacecraft broadcasts a real time telemetry 'beacon' stream containing compressed images and typically one minute averages of solar wind measurements and radio intensities. These real time data streams are received by a mix of NOAA and NASA-managed tracking stations and the data is transmitted by these stations to the STEREO Science Center at NASA Goddard Space Flight Center where they are processed into useable parameters with a latency of less than five minutes from receipt. As the two spacecraft recede from the sun-Earth line, triangulation of the imaging and radio measurements should allow better estimate of the speed and direction of coronal mass ejections, allowing a more precise estimate of their arrival at Earth. In situ particles and fields measurements, particularly for the spacecraft (Behind) trailing Earth in its orbit, will sample the solar wind that will eventually co-rotate around to the sun-Earth line. Late in the prime mission when the spacecraft are very far (>90 degrees) from the sun-Earth line, observations from the Behind spacecraft, will be particularly valuable for providing a preview of active regions well beyond the sun's East limb (as seen from Earth). Continually updated STEREO space weather data can be viewed and downloaded at http:/lstereo-ssc.nascom.nasa.govldata/beacon/.
NASA conducts field research in various Earth Science disciplines utilizing airborne and other non-satellite platforms to acquire in situ and remotely sensed observations indicative of physical processes across a range of scales. Field efforts are key in the development and validation of instruments and satellite algorithm refinements. The heterogeneous data, with a range of file formats, scales, and acquisition methods, support research in several science areas. NASA’s archive process assigns data products to discipline-oriented Distributed Active Archive Centers (DAACs) for stewardship. Over time, individual DAACs have developed tools for data browsing and serving disparate user bases. As science becomes more interdisciplinary, researchers need to incorporate observations from multiple campaigns, and multiple DAACs, into their work. Motivated in part by this shifting paradigm of needs, the Catalog of Archived Suborbital Earth Science Investigations (CASEI) was created. CASEI provides a single starting point to browse, search, and discover airborne and field data. Contextual metadata are organized and inter-linked allowing intuitive, integrated exploration across all NASA DAACs. Campaign science objectives, platform and instrument configurations, geographical details, geophysical concepts, and more are tracked in CASEI’s database, facilitating multi-parameter search, browse, and discovery of relevant data products. Researchers are able to directly access associated data products, via DOI links, regardless of the DAAC where they reside. Significant events, key time periods of high science interest within the longer-duration campaign effort, are also indicated and allow for a more efficient identification of critical data subsets. This presentation describes CASEI’s development, intensive metadata curation process, and demonstrates the web interface experience. Initial content metrics and plans for continued maintenance will also be discussed.
The world is becoming increasingly urbanized. As cities around the world continue to grow, it is important for urban planners and policymakers to understand how different urban configuration patterns affect the environment and human health. We aimed at identifying European urban configuration types, based on the Local Climate Zones categories and street design variables from Open Street Map, and evaluating their association with motorized traffic flows, Surface Urban Heat Island (SUHI) intensities, tropospheric nitrogen dioxide (NO 2 ), CO 2 per capita emissions and age-standardized mortality. We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal–Wallis test followed by a post-hoc Dunn's test. We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low-density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low-density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO 2 exposure were significantly higher in compact high density and open low rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low-density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO 2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health.
Aims. We investigate the utility of Rubin’s Data Preview 1 (DP1) for estimating stellar number density profiles across the Milky Way halo. Methods. We used stellar broad-band near-UV to near-IR ugrizy photometry released in Rubin’s DP1 to estimate distance and metallicity for blue main sequence stars brighter than r = 24 in three ~1.1 sq. deg. fields at southern Galactic latitudes. Results. Compared to TRILEGAL simulations of the Galaxy’s stellar content, we found a likely deficit of blue main sequence turn-off stars with 22 < r < 24. We interpreted this discrepancy as a signature of a steeper halo number density profile at galactocentric distances 10–50 kpc than the canonical ~1/r 3 profile assumed in TRILEGAL simulations. Conclusions. This interpretation is consistent with earlier suggestions based on observations of more luminous, but much less numerous, evolved stellar populations, along with a few pencil beam surveys of blue main sequence stars in the northern sky. These results bode well for the future Galactic halo exploration with Rubin’s Legacy Survey of Space and Time (LSST).
This data set contains observations of new particle formation (NPF) events collected at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory from 2018 to 2023. Measurements include particle number size distributions, radiance measurements, and associated meteorological variables from onsite instrumentation relevant for identifying and characterizing NPF events. Events were identified using standardized criteria and documented to support investigations of aerosol nucleation, growth dynamics, and their interactions with local atmospheric conditions. The data set provides a multi-year record that enables evaluation of seasonal and interannual variability in NPF occurrence and intensity at a mid-continental site. These data are intended to support studies of aerosol-cloud-climate interactions and model evaluation within both ARM and the broader atmospheric science community. More information can be found within the README_NPF_SGP_2018_2023.docx file.
The delay in the launching of the Galileo spacecraft, which was to be launched aboard the Space Shuttle Atlantis, caused by the Challenger accident resulted in a decrease in the Radioisotope Thermoelectric Generator (RTG) power. A change to the Inertial Upper Stage from the more powerful Centaur G-Prime resulted in a trajectory that requires gravity assists, once by Venus and twice by earth. The resulting peak solar intensity of this roundabout trajectory is more than twice the previous design value for the direct trajectory. The resulting changes in solar intensity range and the RTG power output were substantial and forced major thermal design changes. This paper discusses the thermal design and redesign of the Galileo Spun and Despun sciences. Data are presented on the allowable temperatures for the Spun and Despun sciences, the energy balance calculated for the Despun science, and the Despun science test results.
This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.