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Welcome to NASA's Earth Science Enterprise

There are strong scientific indications that natural change in the Earth system is being accelerated by human intervention. As a result, planet Earth faces the possibility of rapid environmental changes that would have a profound impact on all nations. However, we do not fully understand either the short-term effects of our activities, or their long-term implications - many important scientific questions remain unanswered. The National Aeronautics and Space Administration (NASA) is working with the national and international scientific communities to establish a sound scientific basis for addressing these critical issues through research efforts coordinated under the U.S. Global Change Research Program, the International Geosphere-Biosphere Program, and the World Climate Research Program. The Earth Science Enterprise is NASA's contribution to the U.S. Global Change Research Program. NASA's Earth Science Enterprise will use space- and surface-based measurement systems to provide the scientific basis for understanding global change. The space-based components will provide a constellation of satellites to monitor the Earth from space. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). The overall objective of the EOS Program is to determine the extent, causes, and regional consequences of global climate change. EOS will provide sustained space-based observations that will allow researchers to monitor climate variables over time to determine trends. A constellation of EOS satellites will acquire global data, beginning in 1998 and extending well into the 21st century.

Source record↗

Overview of Mars Science Laboratory (MSL) Environmental Program

This viewgraph presentation is an overview of the Mars Science Laboratory (MSL) program. The engineering objectives of the program are to create a Mobile Science Laboratory capable of one Mars Year surface operational lifetime (670 Martian sols = 687 Earth days). It will be able to land and operation over wide range of latitudes, altitudes and seasons It must have controlled propulsive landing and demonstrate improved landing precision via guided entry The general science objectives are to perform science that will focus on Mars habitability, perform next generation analytical laboratory science investigations, perform remote sensing/contact investigations and carry a suite of environmental monitoring instruments. Specific scientific objectives of the MSL are: (1) Characterization of geological features, contributing to deciphering geological history and the processes that have modified rocks and regolith, including the role of water. (2) Determination of the mineralogy and chemical composition (including an inventory of elements such as C, H, N, O, P, S, etc. known to be building blocks for life) of surface and near-surface materials. (3) Determination of energy sources that could be used to sustain biological processes. (4) Characterization of organic compounds and potential biomarkers in representative regolith, rocks, and ices. (5) Determination the stable isotopic and noble gas composition of the present-day bulk atmosphere. (6) Identification potential bio-signatures (chemical, textural, isotopic) in rocks and regolith. (7) Characterization of the broad spectrum of surface radiation, including galactic cosmic radiation, solar proton events, and secondary neutrons. (8) Characterization of the local environment, including basic meteorology, the state and cycling of water and C02, and the near-surface distribution of hydrogen. Several views of the planned MSL and the rover are shown. The MSL environmental program is to: (1) Ensure the flight hardware design is capable of surviving all the environments throughout its mission life time, including ground, transportation, launch, cruise, entry decent and landing (EDL) and surface operation environments. (2) Verify environmental testing and analysis have adequately validated the flight hardware's ability to withstand all natural, self-induced, and mission-activity-induced environments. The planned tests to ascertain the capability of the MSL to perform as desired are reviewed.

spacecraft↗

The LAKE model input dataset for three Arctic lakes

This dataset contains meteorological data collected for three Arctic lakes and compiled to satisfy input requirements of the LAKE 2.0 model. The dataset was generated to act as a benchmarking dataset for future model-data inter-comparisons. The LAKE 2.0 model simulates temperatures within the water later and the sedimentary layer of a lake. The LAKE2.0. is an open-source code and available to download via this weblike http://tesla.parallel.ru/Viktor/LAKE/-/wikis/LAKE-model (last visit July 14, 2021). The meteorological data are required to simulate the surface energy balance at the surface of a lake. This dataset includes a compilation of the meteorological data pulled from multiple data streams, including National Oceanic and Atmospheric Administration (NOAA) climate data, Circumarctic Lakes Observation Network (CALON) data, and the United States Geological Survey (USGS) data. The data were compiled for three Arctic lakes: FoxDen (66.55877, -164.45670), Atqasuk (70.452497, -156.951984), and Toolik (68.63150, -149.60740). Each meteorological data is in comma-delimited format (file extension ‘.dat’) and includes eight columns: Temperature [K], Pressure [Pa], longwave downward radiation [W/m2], shortwave downward radiation [W/m2], “U” wind speed [m/s], ”V” wind speed [m/s], humidity [kg/kg], precipitation [m/s]. In addition to the meteorological data file, we included setup and driver files. The Toolik lake is the deepest out of three lakes and has inflowing and outflowing groundwater data. InflowOutflowREADME.txt has more information about inflow and outflow flies. The other two lakes are much shallower and modeled as a closed system (i.e. no water inflow or outflow).

54 ENVIRONMENTAL SCIENCES↗

CHESS 2025: Waveform LiDAR data from NEON AOP surveys

This dataset provides Level 1 (L1) full-waveform light detection and ranging (LiDAR) data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. Waveform LiDAR data can provide more detailed information about objects on the ground than discrete point clouds typically do, and they are often used for granular target segmentation and characterization of subcanopy vegetation. 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. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary waveform LiDAR data delivered by NEON and are provided per flightline in compressed Pulsewaves format, an open-source binary file standard. A Pulsewaves object comprises a two files: a pulse (.pls) file, which stores the geographic origin, outgoing vector, and metadata for every laser pulse emitted by the scanner, and a wave file (.wvs), which stores the sequential amplitude samples of the outgoing pulse and the returning signals. The files are published here in their compressed forms (.plz, .wvz). All waveform data were processed following the theoretical workflow described in the NEON L0-to-L1 Waveform LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022a); however, the Pulsewaves output format differs from a legacy format described in that document. Waveform amplitude samples are recorded at 1 nanosecond intervals. All coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Waveform data for the UPTA survey area were collected without incident and the published records are complete. However, both the ALMO and CRBU collections experienced issues that resulted in incomplete data for those areas. On collection day 2018-06-16 a hardware failure caused the waveform digitizer to lose data from the eastern edge of the ALMO site (Figure 22). The waveform data for flightlines 2–20 could not be extracted from the digitizer, and the data proved unrecoverable. As a result, a portion of the site does not have coverage with waveform data. Although no hardware failure was observed during collection over the CRBU area, final waveform files generated by vendor software contained only ~25% of the expected number of return pulses. After discovery, NEON initiated troubleshooting with the vendor. The root cause of the data ablation had not been identified at the time of publication. Additional data will be published in an update to this package if further recovery proves successful. 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.

2018 NEON and 2025 CHESS Campaigns↗

The Diurnal Cycle of East Pacific Convection, Moisture, and CYGNSS Wind Speed and Fluxes

The far eastern tropical Pacific is one of the rainiest locations on Earth. This region is characterized by a robust diurnal cycle with precipitation initiating over the Andes mountains in Colombia in the late afternoon and moving offshore overnight while organizing into mesoscale convective systems (MCSs). As the MCSs move westward, they can seed tropical easterly waves that develop into tropical cyclones. Novel measurements of near-surface wind speeds and latent heat flux (LHFLX) from the Cyclone Global Navigation Satellite System (CYGNSS) mission and ERA5 reanalysis are used to evaluate changes to regional flow patterns, moisture, and LHFLX that favor a strong westward propagating diurnal cycle of precipitation in this region. Days with strongly versus weakly westward propagating diurnal precipitation are compared during the extended boreal summer of the CYGNSS era (May–October 2018–2021). Strongly propagating days have a more moist lower troposphere with stronger vertically integrated moisture flux convergence than days with weakly propagating precipitation. The enhanced low-level moisture is supported by increased wind-driven LHFLX from stronger regional flows including the Choco and Caribbean Low-Level Jets and Panama and Papagayo gap winds. Increased offshore convergence and vorticity also help sustain convection during the days with strongly propagating precipitation. Background variations in the physical environment, as opposed to diurnal variations, seem more important for supporting a robust diurnal cycle of precipitation in the region.

54 ENVIRONMENTAL SCIENCES↗

Advanced Terrestrial Simulator (ATS) evaluation dataset at 7 catchments across the continental United States

This dataset comprises of the input files and other files required for Advanced Terrestrial Simulator (ATS) simulations at 7 catchments across the continental United States. ATS is an integrated surface-subsurface hydrology model. We include Jupyter notebooks (within scripts folder) for individual catchments showing information (including data sources, river network, soil, geology, landuse types etc.) on preparing the machine readable input files. ATS observation output files are provided in the output folder. Figures and analyses (.xlsx sheets) are also provided. The catchments include, Taylor River Upstream (Colorado); (b) Cossatot River (Arkansas); (c) Panther Creek (Alabama); (d) Little Tennessee River (North Carolina and Georgia); (e) Mayo River (Virginia); (f) Flat Brook (New Jersey); (g) Neversink River headwaters (New York). Readme files are provided inside the directories providing more details. Files types include: .xml, .h5, .xlsx, .png, .ipynb, .py, .nc, .txt. All of the files types can be accessed by open source software, details on software requirements are following: .xml (any text editors including notepad and textedit), .h5 (in python using hdf libraries), .xlsx (WPS Office Spreadsheets, OpenOffice Calc, LibreOffice Calc, Microsoft Office etc.), .png (any image viewer), .ipynb (Jupyter notebook), .py (any text editors including notepad and textedit), .nc (using python or other open source software).

54 ENVIRONMENTAL SCIENCES↗

Airborne Lidar Simulator for the Lidar Surface Topography (LIST) Mission

In 2007, the National Research Council (NRC) completed its first decadal survey for Earth science at the request of NASA, NOAA, and USGS. The Lidar Surface Topography (LIST) mission is one of fifteen missions recommended by NRC, whose primary objectives are to map global topography and vegetation structure at 5 m spatial resolution, and to acquire global surface height mapping within a few years. NASA Goddard conducted an initial mission concept study for the LIST mission in 2007, and developed the initial measurement requirements for the mission.

Yu, Anthony W.↗

Airborne Instrument Simulator for the Lidar Surface Topography (LIST) Mission

In 2007, the National Research Council (NRC) completed its first decadal survey for Earth science at the request of NASA, NOAA, and USGS. The Lidar Surface Topography (LIST) mission is one of fifteen missions recommended by NRC, whose primary objectives are to map global topography and vegetation structure at 5 m spatial resolution, and to acquire global coverage with a few years. NASA Goddard conducted an initial mission concept study for the LIST mission 2007, and developed the initial measurement requirements for the mission.

Yu, Anthony W.↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter (WDM) physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the WDM physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations & experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments of and contemporary challenges for theoretical methods and experimental techniques needed to describe, create and diagnose WDM. A large part of this roadmap is dedicated to specific WDM systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

dense astrophysical objects↗

Multi-modal surface analysis of porous films under operando conditions

Practical catalysts with a porous framework, such as zeolites, host catalytic reactions at active sites engrained in the pores and channels of the scaffold. The mechanism of interaction at these active sites, defining catalyst performance, remains elusive, in large part, due to the lack of surface characterization methods available for thick films or powders. Here, we present thin film analogs of practical catalysts that allow for the implementation of surface characterization tools, including advanced microscopy and operando spectroscopy methodologies. Specifically, we investigated bilayer silica, MFI nanosheets, and UiO-66 thin films using a multi-modal approach addressing film growth, characterization, and gas adsorption aimed at understanding catalytic activity, reactivity, and selectivity properties, as defined by molecular-level changes in the reaction mechanism.

36 MATERIALS SCIENCE↗

Influence of urban extent discrepancy on the estimation of surface urban heat island intensity: A global-scale assessment in 892 cities

The estimation of surface urban heat island intensity (SUHII) is crucial for studying the urban thermal environment, which is influenced not only by the commonly known definition of rural reference but also by the delineation of urban extent. Existing studies relies on various urban extent products defined in different ways, and the influence of urban extent discrepancy (UED) on SUHII estimates still remains unclear. In this study, we collected five open-source global urban extent products (GUEPs) for the year 2015 and corresponding daily land surface temperature (LST) observations (MYD11A1). Based on these products, we quantified the UED-induced uncertainty in SUHII estimates by comparing absolute difference (ΔSUHII AD ) and relative difference (ΔSUHII RD ) in SUHII among GUEPs across 892 global cities. Additionally, we introduced an ISF-constrained (ISF–C) method to reduce SUHII differences among GUEPs by constraining the impervious surface fraction (ISF) within urban and rural extents. The results show that urban extents delineated by different GUEPs are not consistent, leading to their difference in ISF as well as LST, which in turn causes uncertainties in the estimated SUHII. On average for global cities, the annual daytime and nighttime ΔSUHII AD are 0.46 ± 0.02 °C (mean ± 95% confidence interval) and 0.24 ± 0.01 °C, with corresponding ΔSUHII RD of 42.0 ± 2.7% and 35.2 ± 2.3%, respectively. The UED-induced uncertainty in SUHII estimates varies among climate zones, and the annual daytime ΔSUHII RD averaged for cities located in the arid zone reaches up to 60.8 ± 6.6%, which is nearly twice as high as that in other climate zones. More importantly, both ΔSUHII AD and ΔSUHII RD show lower values when using the ISF-C method, implying the effectiveness of this method. This study highlights the non-negligible impact of UED on the estimation of SUHII, which requires more attention due to the inconsistency of urban extents among current products.

54 ENVIRONMENTAL SCIENCES↗

Model data for Flood Frequency Analysis using Stochastic Storm Transposition and an Integrated Surface-Subsurface Hydrological Model

This archived provides scripts and input files used for the implementation of a novel approach to conduct process-based Flood Frequency Analysis using a Stochastic Storm Transposition (SST) and an Integrated Surface-Subsurface Hydrological Model (ISSHM). As a proof-of-concept, this study uses the ISSHM, Advanced Terrestrial Simulator (Amanzi-ATS) model, and the SST model, RainyDay, to conduct flood frequency analysis by simulating the flood response to 5,000 annual synthetic storm events in a ~2000 km2 Southeast Texas watershed.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include TXT, CSV, DAT, SBATCH, SHP, TIF, NetCDF, and HDF5 files, which can be read through Python scripts. The input files for the ATS model and RainyDay model have .XML and .SST extensions, respectively, and can be edited in any commonly used text editors.This archive contains:* Scripts and data files essential for generating the ATS model input. It uses the Watershed Workflow package to produce both mesh and ATS input files. * Jupyter notebooks designated for the ATS model evaluation, covering both long-term simulations and 40 rainfall-runoff events.* Input files required to simulate SST storm events using RainyDay.

54 ENVIRONMENTAL SCIENCES↗

Ionic Liquid Facilitated Solvent‐Phase Polymerization of Ultrasmooth Coatings of Polycatecholamines

Mussel-inspired polycatecholamine coatings and films have proven to be versatile materials for surface modification. However, the progress of chemically modified coatings with tailored properties has been slow due to the lack of definitive evidence of their polymeric structure. Polycatecholamines form aggregates during polymerization, and their formation mechanism has been a subject of debate owing to their insolubility in traditional molecular solvents. Exploiting the capability of ionic liquids (ILs) to exhibit strong electrostatic interactions, herein, the first solution-phase polymerization approach is reported to achieve polymerization of four catecholamines – dopamine (DA), norepinephrine (NE), L-3,4-dihydroxyphenylalanine (L-DOPA), and adrenaline (AD). Kinetic control over the polymerization process in the solution phase enabled it to follow the process with 1 H NMR spectroscopy, revealing the formation of structural features of resulting complex heterogeneous and soluble polymers. The polymers are both covalent and associative in nature. Solution phase polymerization prevented the formation of large aggregates in the solution, thus facilitating the formation of coatings that are ultra-smooth and have root mean square roughness of the order of sub-nm to nm scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Y-12 Groundwater Protection Program Groundwater and Surface Water Sampling and Analysis Plan (CY 2021)

This plan provides a description of the groundwater and surface water quality monitoring activities planned for calendar year (CY) 2021 at the U.S. Department of Energy Y-12 National Security Complex (Y-12) that will be managed by the Y-12 Groundwater Protection Program (GWPP). Groundwater and surface water monitoring is performed by the GWPP. Groundwater and surface water monitoring will be performed in three hydrogeologic regimes at Y-12: the Bear Creek Hydrogeologic Regime (Bear Creek Regime), the Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime), and the Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime). The Bear Creek and East Fork regimes are located in Bear Creek Valley and the Chestnut Ridge Regime is located south of Y-12. Additional surface water monitoring will be performed north of Pine Ridge along the boundary of the Oak Ridge Reservation. The following sections of this report provide details regarding the CY 2021 groundwater and surface water monitoring activities. Section 2 describes the monitoring locations in each regime and the processes used to select the sampling locations. A description of the field measurements and laboratory analytes is provided in Section 3. Sample collection methods and procedures are described in Section 4, and Section 5 lists the documents cited for more detailed operational and technical information. The narrative sections of the report reference several appendices. Figures (maps and diagrams) and tables (excluding a data summary table presented in Section 4) are in Appendix A and Appendix B, respectively. Groundwater Monitoring Schedules (when issued throughout CY 2021) will be inserted in Appendix C, and addenda to this plan (if issued) will be inserted in Appendix D. Laboratory requirements (bottle lists, holding times, etc.) are provided in Appendix E, and an approved Waste Management Plan is provided in Appendix F. Modifications to the CY 2021 monitoring program may be necessary during implementation. Changes in programmatic requirements may alter the analytes specified for selected monitoring wells or may add or remove wells from the planned monitoring network. Each modification to the monitoring program will be approved by the Y-12 GWPP manager and documented as an addendum to this sampling and analysis plan.

54 ENVIRONMENTAL SCIENCES↗

Land surface dynamics and meteorological forcings modulate land surface temperature characteristics

This study examines the effect of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) distribution over West Africa (WA). We employ fourteen machine-learning models, which preserve nonlinear relationships, to downscale LST and other predictands while preserving the geographical variability of WA. Our results showed that the random forest model performs best in downscaling predictands. This is important for the sub-region since it has limited access to mainframes to power multiplex machine-learning algorithms. In contrast to the northern regions, the southern regions consistently exhibit healthy vegetation. Also, areas with unhealthy vegetation coincide with hot LST clusters. The positive Normalized Difference Vegetation Index (NDVI) trends in the Sahel underscore rainfall recovery and subsequent Sahelian greening. The southwesterly winds cause the upwelling of cold waters, lowering LST in southern WA and highlighting the cooling influence of water bodies on LST. Identifying regions with elevated LST is paramount for prioritizing greening initiatives, and our study underscores the importance of considering LVCET factors in urban planning. Topographic slope-facing angles, heat loads, and diurnal anisotropic heat all contribute to variations in LST, emphasizing the need for a holistic approach when designing resilient and sustainable landscapes.

54 ENVIRONMENTAL SCIENCES↗

NASAs Evolvable Mars Campaign: Mars Moons Robotic Precursor

Human exploration missions to the moons of Mars are being considered within NASA's Evolvable Mars Campaign (EMC) as an intermediate step for eventual human exploration and pioneering of the surface of Mars. A range of mission architectures is being evaluated in which human crews would explore one or both moons for as little as 14 days or for as long as 500 days with a variety of orbital and surface habitation and mobility options being considered. Relatively little is known about the orbital, surface, or subsurface characteristics of either moon. This makes them interesting but challenging destinations for human exploration missions during which crewmembers must be able to effectively conduct scientific exploration without being exposed to undue risks due to radiation, dust, micrometeoroids, or other hazards. A robotic precursor mission to one or both moons will be required to provide data necessary for the design and operation of subsequent human systems and for the identification and prioritization of scientific exploration objectives. This paper identifies and discusses considerations for the design of such a precursor mission based on current human mission architectures. Objectives of a Mars' moon precursor in support of human missions are expected to include: 1) identifying hazards on the surface and the orbital environment at up to 50-km distant retrograde orbits; 2) collecting data on physical characteristics for planning of detailed human proximity and surface operations; 3) performing remote sensing and in situ science investigations to refine and focus future human scientific activities; and 4) prospecting for in situ resource utilization. These precursor objectives can be met through a combination or remote sensing (orbital) and in-situ (surface) measurements. Analysis of spacecraft downlink signals using radio science techniques would measure the moon's mass, mass distribution, and gravity field, which will be necessary to enable trajectory planning. Laser altimetry would precisely measure the moon's shape and improve the accuracy of radio science measurements. A telescopic imaging camera would map the moon at submeter resolution and photograph selected areas of interest at subcentimeter resolution and a visible and near-infrared (0.4-3.0 mm) imaging spectrograph would produce a global map of mineral composition variations at a resolution of tens of meters and maps of selected areas of interest at meter resolution. Additional remote sensing capabilities could include a thermal infrared imager (heat flow, thermal inertia, and grain size distributions), a gamma-ray and neutron detector (atomic composition), a ground-penetrating radar (internal structure), and a magnetometer and Langmuir probe (magnetic properties and plasma field). Once on the surface of Phobos or Deimos, necessary instrumentation would include a penetrometer (regolith compressive strength), a motion-imagery camera (to observe the penetrometer tests before, during, and after contact), a dust-adhesion witness plate and camera (dust levitation), a microimager (dust particle sizes and shapes), and an alpha-proton-X-ray, X-ray fluorescence, Mossbauer, or Raman spectrometer (atomic and mineral composition of surface materials) and an optional temperature probe (regolith thermal properties). A variety of robotic mission design options to enable both orbital and surface measurements are being considered that include fully integrated and modular approaches. In-situ measurements from at least one surface location would be required, with additional measurement locations possible through use of multiple landers, through propulsive relocation of a single lander, or through electromechanical surface translation by a walking or hopping lander vehicle, which could also serve to evaluate such mobility capabilities for subsequent human missions. Preliminary orbital analysis suggests that remote sensing would likely be performed while in a distant retrograde orbit around the target moon. Mission design options to enable characterization of both Mars’ moons in a single mission are also being studied.

Gernhardt, Michael L.↗

Dy adsorption on and intercalation under graphene on 6 H -SiC(0001) surface from first-principles calculations

Previous experimental observations motivate clarification of configuration stabilities and kinetic processes for intercalation of guest atoms into a layered van der Waals material such as a graphene-SiC system. From our first-principles density functional theory (DFT) calculations, we analyze Dy adsorption and intercalation for graphene on a 6H-SiC(0001) surface, where the system includes two single-atom-thick graphene layers: the top-layer graphene (TLG) and the underling buffer-layer graphene (BLG) above the terminal Si layer. Our chemical potential analysis shows that intercalation of a single Dy atom into the gallery between TLG and BLG is more favorable than adsorption on TLG but that intercalation into the gallery underneath BLG is highly unfavorable. We obtain diffusion barriers of ~0.45 and 0.54 eV for a Dy atom diffusing on and under TLG, respectively. We find that the direct penetration of a Dy atom from the graphene top into the gallery under TLG is almost inhibited below a temperature of ~1400 K due to a large global barrier of at least ~3.5 eV. Instead, we find that a single Dy atom on TLG can easily intercalate by crossing a TLG step (e.g., a zigzag step presaturated by a Dy chain or a reconstructed zigzag step zz57). Additionally, we also perform DFT calculations for different Dy coverages to demonstrate how the favorability of Dy intercalation, as well as the corresponding interlayer spacings, depend on the coverage. Consequently, we can provide general insight and guidance for extensively studied systems involving intercalation of foreign atoms into graphene on a SiC substrate.

36 MATERIALS SCIENCE↗

Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery

As the spatial and temporal resolution of remotely sensed imagery has improved over the last four decades, algorithms for monitoring and mapping seasonal changes in surface properties have evolved rapidly. Most recently, the availability of daily PlanetScope imagery has created new opportunities for monitoring the land surface phenology (LSP) of terrestrial ecosystems at high spatial resolution. However, the quality and value of LSP information from PlanetScope imagery have not been systematically examined. In this paper, we evaluate the character and quality of LSP information derived from PlanetScope by comparing time series of vegetation indices and LSP metrics from PlanetScope to corresponding time series and LSP metrics derived from Harmonized Landsat 8 and Sentinel-2 (HLS) imagery and PhenoCams at six sites that span a diverse range of land cover types and climate. Results show that vegetation index time series from all three data sources show high temporal correlation, and LSP metrics derived from HLS, PlanetScope, and PhenoCam show high agreement with negligible bias. Semi-variograms for phenometrics estimated from PlanetScope imagery indicate that the majority of spatial variance captured in PlanetScope phenometrics occurs well below the spatial resolution HLS imagery. At the same time, LSP metrics from HLS are most strongly correlated with the 50–75% quantiles of 3 m LSP metrics from PlanetScope. This indicates that HLS captures the average phenology at sub-pixel scale captured in PlanetScope imagery. Here, our results represent the first comprehensive comparison of LSP metrics estimated from PlanetScope and publicly available moderate spatial resolution imagery, and provide insights regarding: (1) the quality and character of LSP metrics derived from HLS and PlanetScope; and (2) the relative merits and trade-offs associated with the use of each data source for LSP studies.

54 ENVIRONMENTAL SCIENCES↗