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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021

From August 8 through August 16 of 2021, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Data was collected around five NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27, Teller mm 47, Kougarok mm 64, Kougarok mm 86, and Council mm 71. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. A Phase One iXM-RS100F camera was integrated with the Riegl sensor to collect RGB imagery. This data package contains LiDAR point clouds (.las), RGB imagery (tif), 1 m or 50 cm Digital Elevation Models (.tif) generated from the LiDAR data, and shapefiles of the .las tiling system for each site (.shp). Two supplemental documents are also included in the package: 1) a report describing data collection details, GNSS corrections, and processing steps and 2) a document describing the LiDAR Classification used (.pdf). This survey was conducted towards the end of the summer on the Seward Peninsula, and can be paired with data collected in April of 2022 during the snow-on campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022" (Singhania et.al, 2023) (NGA314). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Process-Oriented Diagnostics: Principles, Practice, Community Development, and Common Standards

Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.

58 GEOSCIENCES↗
NASA NTRS2013

Impact of Radiatively Interactive Dust Aerosols in the NASA GEOS-5 Climate Model: Sensitivity to Dust Particle Shape and Refractive Index

We investigate the radiative effects of dust aerosols in the NASA GEOS-5 atmospheric general circulation model. GEOS-5 is improved with the inclusion of a sectional aerosol and cloud microphysics module, the Community Aerosol and Radiation Model for Atmospheres (CARMA). Into CARMA we introduce treatment of the dust and sea salt aerosol lifecycle, including sources, transport evolution, and sinks. The aerosols are radiatively coupled to GEOS-5, and we perform a series of multi-decade AMIP-style simulations in which dust optical properties (spectral refractive index and particle shape distribution) are varied. Optical properties assuming spherical dust particles are from Mie theory, while those for non-spherical shape distributions are drawn from a recently available database for tri-axial ellipsoids. The climatologies of the various simulations generally compare well to data from the MODIS, MISR, and CALIOP space-based sensors, the ground-based AERONET, and surface measurements of dust deposition and concentration. Focusing on the summertime Saharan dust cycle we show significant variability in our simulations resulting from different choices of dust optical properties. Atmospheric heating due to dust enhances surface winds over important Saharan dust sources, and we find a positive feedback where increased dust absorption leads to increased dust emissions. We further find that increased dust absorption leads to a strengthening of the summertime Hadley cell circulation, increasing dust lofting to higher altitudes and strengthening the African Easterly Jet. This leads to a longer atmospheric residence time, higher altitude, and generally more northward transport of dust in simulations with the most absorbing dust optical properties. We find that particle shape, although important for radiance simulations, is a minor effect compared to choices of refractive index, although total atmospheric forcing is enhanced by greater than 10 percent for simulations incorporating a spheroidal shape distribution versus ellipsoidal or spherical shapes.

radiative forcing↗
NASA NTRS2004

Climate Response to the Increase in Tropospheric Ozone since Preindustrial Times: A Comparison between Ozone and Equivalent CO2 Forcings

We examine the characteristics of the climate response to anthropogenic changes in tropospheric ozone. Using a general circulation model, we have carried out a pair of equilibrium climate simulations with realistic present-day and preindustrial ozone distributions. We find that the instantaneous radiative forcing of 0.49 W m(sup -2) due to the increase in tropospheric ozone since preindustrial times results in an increase in global mean surface temperature of 0.28 C. The increase is nearly 0.4 C in the Northern Hemisphere and about 0.2 C in the Southern Hemisphere. The largest increases (greater than 0.8 C) are downwind of Europe and Asia and over the North American interior in summer. In the lower stratosphere, global mean temperatures decrease by about 0.2 C due to the diminished upward flux of radiation at 9.6 micrometers. The largest stratospheric cooling, up to 1.0 C, occurs over high northern latitudes in winter, with possibly important implications for the formation of polar stratospheric clouds. To identify the characteristics of climate forcing unique to tropospheric ozone, we have conducted two additional climate equilibrium simulations: one in which preindustrial tropospheric ozone concentrations were increased everywhere by 18 ppb, producing the same global radiative forcing as present-day ozone but without the heterogeneity; and one in which CO2 was decreased by 25 ppm relative to present day, with ozone at present-day values, to again produce the same global radiative forcing but with the spectral signature of CO2 rather than ozone. In the first simulation (uniform increase of ozone), the global mean surface temperature increases by 0.25 C, with an interhemispheric difference of only 0.03 C, as compared with nearly 0.2 C for the heterogeneous ozone increase. In the second simulation (equivalent CO2), the global mean surface temperature increases by 0.36 C, 30% higher than the increase from tropospheric ozone. The stronger surface warming from CO2 is in part because CO2 forcing (obscured by water vapor) is shifted relatively poleward where the positive ice-albedo feedback amplifies the climate response and in part because the magnitude of the CO2 forcing in the mid-troposphere is double that of ozone. However, we find that CO2 is far less effective than tropospheric ozone in driving lower stratospheric cooling at high northern latitudes in winter.

Mickley L. J.↗
NASA NTRS2011

Developing a Prototype ALHAT Human System Interface for Landing

The goal of the Autonomous Landing and Hazard Avoidance Technology (ALHAT) project is to safely execute a precision landing anytime/anywhere on the moon. This means the system must operate in any lighting conditions, operate in the presence of any thruster generated regolith clouds, and operate without the help of redeployed navigational aids or prepared landing site at the landing site. In order to reach this ambitious goal, computer aided technologies such as ALHAT will be needed in order to permit these landings to be done safely. Although there will be advanced autonomous capabilities onboard future landers, humans will still be involved (either onboard as astronauts or remotely from mission control) in any mission to the moon or other planetary body. Because many time critical decisions must be made quickly and effectively during the landing sequence, the Descent and Landing displays need to be designed to be as effective as possible at presenting the pertinent information to the operator, and allow the operators decisions to be implemented as quickly as possible. The ALHAT project has established the Human System Interface (HSI) team to lead in the development of these displays and to study the best way to provide operators enhanced situational awareness during landing activities. These displays are prototypes that were developed based on multiple design and feedback sessions with the astronaut office at NASA/ Johnson Space Center. By working with the astronauts in a series of plan/build/evaluate cycles, the HSI team has obtained astronaut feedback from the very beginning of the design process. In addition to developing prototype displays, the HSI team has also worked to provide realistic lunar terrain (and shading) to simulate a "out the window" view that can be adjusted to various lighting conditions (based on a desired date/time) to allow the same terrain to be viewed under varying lighting terrain. This capability will be critical to determining the effect of terrain/lighting on the human pilot, and how they use windows and displays during landing activities. The Apollo missions were limited to about 28 possible launch days a year due to lighting and orbital constraints. In order to take advantage of more landing opportunities and venture to more challenging landing locations, future landers will need to utilize sensors besides human eyes for scanning the surface. The ALHAT HSI system must effectively convey ALHAT produced information to the operator, so that landings can occur during less "optimal" conditions (lighting, surface terrain, slopes, etc) than was possible during Apollo missions. By proving this capability, ALHAT will simultaneously provide more flexible access to the moon, and greater safety margins for future landers. This paper will specifically focus on the development of prototype displays (the Trajectory Profile Display (TPD), Landing Point Designation (LPD), and Crew Camera View (CCV) ), implementation of realistic planetary terrain, human modeling, and future HSI plans.

Hirsh, Robert L.↗
DOE OSTI2026

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Evaluating the Impact of Chemical Complexity and Horizontal Resolution on Tropospheric Ozone Over the Conterminous US With a Global Variable Resolution Chemistry Model

A new configuration of the Community Earth System Model (CESM)/Community Atmosphere Model with full chemistry (CAM-chem) supporting the capability of horizontal mesh refinement through the use of the spectral element (SE) dynamical core is developed and called CESM/CAM-chem-SE. Horizontal mesh refinement in CESM/CAM-chem-SE is unique and novel in that pollutants such as ozone are accurately represented at human exposure relevant scales while also directly including global feedbacks. CESM/CAM-chem-SE with mesh refinement down to ∼14 km over the conterminous US (CONUS) is the beginning of the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0). Here MUSICAv0 is evaluated and used to better understand how horizontal resolution and chemical complexity impact ozone and ozone precursors over CONUS as compared to measurements from five aircraft campaigns, which occurred in 2013. This field campaign analysis demonstrates the importance of using finer horizontal resolution to accurately simulate ozone precursors such as nitrogen oxides and carbon monoxide. In general, the impact of using more complex chemistry on ozone and other oxidation products is more pronounced when using finer horizontal resolution where a larger number of chemical regimes are resolved. Large model biases for ozone near the surface remain in the Southeast US as compared to the aircraft observations even with updated chemistry and finer horizontal resolution. This suggests a need for adding the capability of replacing sections of global emission inventories with regional inventories, increasing the vertical resolution in the planetary boundary layer, and reducing model biases in meteorological variables such as temperature and clouds.

MUSICA↗
NASA NTRSDate not supplied

Using XR for Improving Scientific Discovery With Numerical Weather Models

Earth science (ES) digital twins will help us understand the complex interactions and interrelationships that make up our Earth system and the impacts of earth science phenomena on it. Our work addresses two underdeveloped areas in current ES digital twin work: improving the understanding and interaction with ES model outputs by using Virtual and Mixed Reality (XR) tools and improving the non-intuitive mapping of continuous ES natural phenomena to gridded reference frames in current numerical models. Traditionally, scientists working on ES view and analyze the results of calculated or measured observables with static 1-dimensional (1D), 2D or 3D plots displayed on flat computer screens or paper. Using such limited mediums, it can be very difficult to identify, track and understand the evolution of key features due to poor viewing angles and the nature of flat computer screens. In addition, numerical models, such as the NASA Goddard Earth Observing System (GEOS) ES model, are almost exclusively formulated, visualized and analyzed in an Eulerian reference frame with fixed grid points in space and time. However, ES phenomena such as convective clouds, hurricanes and wildfire smoke plumes are visualized and analyzed in a Lagrangian reference frame: therefore it is often difficult and unnatural to understand these phenomena in relation to each other, visualized either in an Eulerian or Lagrangian context. In 3D visualizations, data generally takes one of three forms: gridded (e.g., voxelized) data, where space is divided into regions; point clouds, where data is represented as a set of points; and meshes, where objects are rendered as surfaces composed of small polygons (usually triangles). A gridded, Eulerian reference frame has been the default representation for the 2D visual analysis of atmospheric data in part because the numerical methods used to generate atmospheric model data in the first place use a gridded approach, with equations defining the relationships between the physical variables in each of a grid's cells across successive timesteps. In our work, we are particularly interested in data from GEOS. Another reason why gridded representations tend to be used for visualizing data from such models is because trajectories are difficult to interpret from representations on 2D surfaces, due to line-of-sight ambiguity. Instead of a fixed grid from GEOS, we embed a trajectory model to simulate particles' movement throughout a GEOS run. We then ingest these particle trajectories as animated point clouds with a NASA open source XR toolkit, the Mixed Reality Exploration Toolkit (MRET), and merge GEOS data with ES phenomena data onto one combined visualization that the user can intuitively interact with. Efficient rendering of arbitrarily large point clouds is an ongoing challenge being addressed by the computer science community, with the GPU-based optimizations and efficient GPU memory utilization a common theme of recent advances, especially for XR, where sustained high frame rate is mandatory to save the user from suffering due to simulation sickness. In this work, we describe and evaluate our progress in choosing and implementing appropriate methods for rendering arbitrarily large point clouds within MRET for XR. While tracking the XR headset enables the immersion of a user within a 3D scene of a data visualization, tracking of XR handheld controllers or user’s hands enables us to implement intuitive user interactions with the visualized datasets. Conventional tools require a user working with an ES visualization to conduct many interactions to commit their intended selections or manipulations with a visualized dataset; for example to specify a set of points in 3D space. Doing so in a 2D flat screen interface has traditionally required specifying a set of points in three distinct 2D coordinate systems (XY, XZ, and YZ), which is cumbersome. In other scientific domains, it has been shown that specifying or selecting a location or volume in XR using handheld controllers or tracked hands allows for greater speed and accuracy. We anticipate the same will hold true for atmospheric data, and we will share initial results of measuring the utility of such an interface. Notably, as the data being visualized is generated by GEOS as a prediction based on initial conditions, an intended application of our tool is to serve as part of an iterative feedback loop. Through XR, a scientist will review and manipulate a GEOS model run, modifying the conditions as needed to do subsequent runs of GEOS. Thereby, XR-based improvements to speed and accuracy of 3D tagging of points minimizes the effort required by both the scientist and the computer cluster conducting the necessary calculations.

Thomas Grubb↗
DOE OSTI2020

Convectively Forced Diurnal Gravity Waves in the Maritime Continent

Long-lived, zonally propagating diurnal rainfall disturbances are a highly pronounced and common feature in the Maritime Continent (MC). A recent study argues that these disturbances can be explained as diurnally phase-locked gravity waves. Here we explore the origins of these waves through regional cloud-permitting numerical model experiments. The gravity waves are reproduced and isolated in the model framework through the combined use of realistic geography and diurnally cyclic lateral boundary conditions representative of both characteristic easterly and westerly background zonal flow regimes. These flow regimes are characteristic of the Madden–Julian oscillation (MJO) suppressed and active phase in the MC, respectively. Tests are conducted wherein Borneo, Sumatra, or both islands and/or their orography are removed. These tests imply that the diurnal gravity waves are excited and maintained directly by latent heating from the vigorous mesoscale convective systems (MCSs) that form nocturnally in both Borneo and Sumatra. Removing orography has only a secondary impact on both the MCSs and the gravity waves, implying that it is not critical to these waves. We therefore hypothesize that diurnal gravity waves are fundamentally driven by mesoscale organized deep convection, and are only sensitive to orography to the measure that the convection is affected by the orography and its mesoscale flows. Factor separation further reveals that the nonlinear interaction of synchronized diurnal cycles in Sumatra and Borneo slightly amplifies this gravity wave mode compared to if either island existed in isolation. This nonlinear feedback appears most prominently at longitudes directly between the two islands.

Ruppert, Jr., James H.↗
NASA NTRS2006

Heliosheath Space Environment Interactions with Icy Bodies in the Outermost Solar System

The Voyager 1 and 2 spacecraft are exploring the space environment of the outermost solar system at the same time that earth-based astronomy continues to discover new icy bodies, one larger than Pluto, in the transitional region outward from the Classical Kuiper Belt to the Inner Oort Cloud. Some of the Scattered Disk Objects in this region periodically pass through the heliosheath, entered by Voyager 1 in Dec. 2004 and later expected to be reached by Voyager 2, and out even beyond the heliopause into the Very Local Interstellar Medium. The less energetic heliosheath ions, important for implantation and sputtering processes, are abundant near and beyond the termination shock inner boundary, but the source region of the more penetrating anomalous cosmic ray component has not yet been found. Advantageous for modeling of icy body interactions, the measured heliosheath flux spectra are relatively more stable within this new regime of isotropic compressional magnetic turbulence than in the upstream heliospheric environment. The deepest interactions and resultant radiation-induced chemistry arise from the inwardly diffusing component of the galactic cosmic ray ions with significant intensity modulation also arising in the heliosheath beyond Voyager 1. Surface gardening by high-velocity impacts of smaller bodies (e.g., fragments of previous KBO collisions) and dust is a further space weathering process setting the time scales for long term exposure of different regolith layers to the ion irradiation. Sputtering and ionization of impact ejecta grains may provide a substantial feedback of pickup ions for multiple cycles of heliosheath acceleration and icy body interaction. Thus the space weathering interactions are potentially of interest not only for effects on sensible surface composition of the icy bodies but also for evolution of the heliosheath plasma energetic ion, and neutral emission environment.

Cooper, John F.↗
NASA NTRS2012

Global Air Quality and Climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH4), ozone precursors (O3), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O3 precursor CH4 would slow near-term warming by decreasing both CH4 and tropospheric O3. Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NOx) emissions, which increase tropospheric O3 (warming) but also increase aerosols and decrease CH4 (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH4 volatile organic compounds (NMVOC) warm by increasing both O3 and CH4. Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O3 and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O3 and SOA.

ozone↗
NASA NTRS2006

Atmospheric Teleconnection over Eurasia Induced by Aerosol Radiative Forcing during Boreal Spring

The direct effects of aerosols on global and regional climate during boreal spring are investigated based on numerical simulations with the NASA Global Modeling and Assimilation Office finite-volume general circulation model (fvGCM) with Microphyics of Clouds with the Relaxed Arakawa Schubert Scheme (McRAS), using aerosol forcing functions derived from the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The authors find that anomalous atmospheric heat sources induced by absorbing aerosols (dust and black carbon) excite a planetary-scale teleconnection pattern in sea level pressure, temperature, and geopotential height spanning North Africa through Eurasia to the North Pacific. Surface cooling due to direct effects of aerosols is found in the vicinity and downstream of the aerosol source regions, that is, South Asia, East Asia, and northern and western Africa. Significant atmospheric heating is found in regions with large loading of dust (over northern Africa and the Middle East) and black carbon (over Southeast Asia). Paradoxically, the most pronounced feature in aerosol-induced surface temperature is an east west dipole anomaly with strong cooling over the Caspian Sea and warming over central and northeastern Asia, where aerosol concentrations are low. Analyses of circulation anomalies show that the dipole anomaly is a part of an atmospheric teleconnection pattern driven by atmospheric heating anomalies induced by absorbing aerosols in the source regions, but the influence was conveyed globally through barotropic energy dispersion and sustained by feedback processes associated with the regional circulations. The surface temperature signature associated with the aerosol-induced teleconnection bears striking resemblance to the spatial pattern of observed long-term trend in surface temperature over Eurasia. Additionally, the boreal spring wave train pattern is similar to that reported by Fukutomi et al. associated with the boreal summer precipitation seesaw between eastern and western Siberia. The results of this study raise the possibility that global aerosol forcing during boreal spring may play an important role in spawning atmospheric teleconnections that affect regional and global climates.

Kim, Maeng-Ki↗
NASA NTRS1998

Fifteen Years of Laboratory Astrophysics at Ames

Tremendous strides have been made in our understanding of interstellar material over the past fifteen years thanks to significant, parallel developments in two closely related areas: observational astronomy and laboratory astrophysics. Fifteen years ago the composition of interstellar dust was largely guessed at, the concept of ices in dense molecular clouds ignored, and the notion of large, abundant, gas phase, carbon-rich molecules widespread throughout the interstellar medium (ISM) considered impossible. Today the composition of dust in the diffuse ISM is reasonably well constrained to cold refractory materials comprised of amorphous and crystalline silicates mixed with an amorphous carbonaceous material containing aromatic structural units and short, branched aliphatic chains. In the dense ISM, these cold dust particles are coated with mixed-molecular ices whose compositions are very well known. Lastly, the signature of carbon-rich polycyclic aromatic hydrocarbons (PAHs), shockingly large molecules by early interstellar chemistry standards, is widespread throughout the ISM. This great progress has only been made possible by the close collaboration of laboratory experimentalists with observers and theoreticians, all with the goal of applying their skills to astrophysical problems of direct interest to NASA programs. Such highly interdisciplinary collaborations ensure fundamental, in depth coverage of the wide-ranging challenges posed by astrophysics. These challenges include designing astrophysically focused experiments and data analysis, tightly coupled with astrophysical searches spanning 2 orders of magnitude in wavelength, and detailed theoretical modeling. The impact of our laboratory has been particularly effective as there is constant cross-talk and feedback between quantum theorists; theoretical astrophysicists and chemists; experimental physicists; organic, physical and petroleum chemists; and infrared and UV/Vis astronomers. In this paper, two examples of the Ames Program will be given. We have been involved in identifying 9 out of the 14 interstellar pre-cometary ice species known, determined their abundances and the physical nature of the ice structure. Details on our ice work are given in the paper by Sandford et al. Our group is among the pioneers of the PAH model. We built the theoretical framework, participated in the observations and developed the experimental techniques needed to test the model. We demonstrated that the ubiquitous infrared emission spectrum associated with many interstellar objects can be matched by laboratory spectra of neutral and positively charged PAHs and that PAHs were excellent candidates for the diffuse interstellar band (DIB) carriers. See Salama et al. and Hudgins et al.

Allamandola, L. J.↗
NASA NTRS2014

Climate Trends in the Arctic as Observed from Space

The Arctic is a region in transformation. Warming in the region has been amplified, as expected from ice-albedo feedback effects, with the rate of warming observed to be approx. 0.60+/-0.07 C/decade in the Arctic (>64degN) compared to approx. 0.17 C/decade globally during the last three decades. This increase in surface temperature is manifested in all components of the cryosphere. In particular, the sea ice extent has been declining at the rate of approx. 3.8%/decade, whereas the perennial ice (represented by summer ice minimum) is declining at a much greater rate of approx.11.5%/decade. Spring snow cover has also been observed to be declining by −2.12%/decade for the period 1967-2012. The Greenland ice sheet has been losing mass at the rate of approx. 34.0Gt/year (sea level equivalence of 0.09 mm/year) during the period from 1992 to 2011, but for the period 2002-2011, a higher rate of mass loss of approx. 215 Gt/year has been observed. Also, the mass of glaciers worldwide declined at the rate of 226 Gt/year from 1971 to 2009 and 275 Gt/year from 1993 to 2009. Increases in permafrost temperature have also been measured in many parts of the Northern Hemisphere while a thickening of the active layer that overlies permafrost and a thinning of seasonally frozen ground has also been reported. To gain insight into these changes, comparative analysis with trends in clouds, albedo, and the Arctic Oscillation is also presented.

arctic↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Simulating the Effects of Surface Energy Partitioning on Convective Organization: Case Study and Observations in the US Southern Great Plains

Realistic cloud-resolving simulations were performed to study the effects of surface energy partitioning (surface sensible and latent heat fluxes) on the organization of isolated convection into larger mesoscale convective systems (MCSs) near the US Southern Great Plains. The role of cold pools in mediating surface-convection interactions was explored. Better organized MCSs tended to occur in the experiments with perturbed wetter soil (and more active vegetation), regardless of the effects of soil moisture on the diurnal timing of convective triggering. Wetter soil led to shallower boundary layers and more convective available potential energy than drier soil. The roles of cold pools on convection are lifecycle-stage dependent: A dry surface allows more numerous colliding cold pools, thereby aiding in convective triggering by reducing entrainment in the early stages, and providing gust-front uplift in later stages. However, horizontal propagation of the cold-pool density current can outrun the convective system, creating a slantwise updraft and thus weakening the gust front uplift in later stages. This effect calls into question previous cold pool parameterizations, in which the gust front uplift is mainly proportional to the negative buoyancy of cold air. Finally, both the model and observation show an enhancement of surface latent heat flux during the passage of a gust front at night, suggesting that a positive feedback between the surface and convection helps MCSs to persist into the nighttime.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Workstation-Based Real-Time Mesoscale Modeling Designed for Weather Support to Operations at the Kennedy Space Center and Cape Canaveral Air Station

This paper describes the capabilities and operational utility of a version of the Mesoscale Atmospheric Simulation System (MASS) that has been developed to support operational weather forecasting at the Kennedy Space Center (KSC) and Cape Canaveral Air Station (CCAS). The implementation of local, mesoscale modeling systems at KSC/CCAS is designed to provide detailed short-range (less than 24 h) forecasts of winds, clouds, and hazardous weather such as thunderstorms. Short-range forecasting is a challenge for daily operations, and manned and unmanned launches since KSC/CCAS is located in central Florida where the weather during the warm season is dominated by mesoscale circulations like the sea breeze. For this application, MASS has been modified to run on a Stardent 3000 workstation. Workstation-based, real-time numerical modeling requires a compromise between the requirement to run the system fast enough so that the output can be used before expiration balanced against the desire to improve the simulations by increasing resolution and using more detailed physical parameterizations. It is now feasible to run high-resolution mesoscale models such as MASS on local workstations to provide timely forecasts at a fraction of the cost required to run these models on mainframe supercomputers. MASS has been running in the Applied Meteorology Unit (AMU) at KSC/CCAS since January 1994 for the purpose of system evaluation. In March 1995, the AMU began sending real-time MASS output to the forecasters and meteorologists at CCAS, Spaceflight Meteorology Group (Johnson Space Center, Houston, Texas), and the National Weather Service (Melbourne, Florida). However, MASS is not yet an operational system. The final decision whether to transition MASS for operational use will depend on a combination of forecaster feedback, the AMU's final evaluation results, and the life-cycle costs of the operational system.

Manobianco, John↗
DOE OSTI2020

Collaborative Research: Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales (Final Technical Report)

The Regional Arctic System Model (RASM) at process resolving configurations has been used to (i) advance understanding of physical processes and feedbacks involved in Arctic amplification and (ii) understand and potentially reduce uncertainty in prediction of arctic climate change at seasonal to decadal scales. RASM consists the atmosphere (Weather and Research Forecasting model, WRF), ocean (Parallel Ocean Program, POP), sea ice (CICE), land hydrology (Variable Infiltration Capacity model, VIC), river routing scheme (RVIC), marine biogeochemistry components and the coupling framework (CPL7). Its domain is pan-Arctic, with the atmosphere and land components configured on a 50-km or 25-km grid and four configurations of the ocean and sea ice components: 1/12°(~9.3km) or 1/48°(~2.4km) and 45 or 60 vertical layers. These RASM configurations have been motivated by the emerging exascale capability for high performance computing to improve model fidelity. The dynamical downscaling of reanalysis allows comparison of RASM results with observations in place and time to: (i) advance system level understanding of physical processes and coupling involved in an event, (ii) optimize model parameter space, (iii) diagnose and reduce model biases and (iv) produce realistic and consistent across all the components initial conditions for predictions and predictability studies, which are all unique capabilities not available in global Earth System Models (ESMs). An evaluation of RASM 1.0 (Cassano et al. 2017) revealed that it had a cold bias over the oceans and a warm bias over land areas due largely to cloud and radiation biases in the model, with too little cloud cover simulated over land and too much cloud cover simulated over sub-polar oceans. This study has motivated an upgrade to WRF version 3.7.1 in RASM and allowed for the inclusion of the radiative impact of convective clouds. A variety of atmospheric physics parameterizations were evaluated against observations (e.g. data from the Arctic Clouds in Summer Experiment (ACSE); Sedlar et al. 2020) to identify an optimal suite of WRF physics options in RASM. The RASM with the optimized WRF physics were used to study the impact of strong mesoscale winds over the ocean around the southern tip of Greenland (DuVivier and Cassano 2016) and their impact on oceanic convection (DuVivier et al. 2017a). Data from the PolarWinds field campaign were used to evaluate WRF boundary layer physics and resolution impacts on the simulation of a Greenland barrier wind event (DuVivier et al. 2017b). The RVIC streamflow routing model has been implemented in RASM to realistically represent high-resolution streamflow processes (Hamman et al. 2017) and to couple the land buoyancy fluxes to the ocean. The RASM-RVIC high-resolution data set of all coastal freshwater fluxes for the Arctic drainage basin and surrounding areas for 1979-2014 was published as a separate product (https://doi.org/10.5281/zenodo.293037). The fidelity of atmospheric momentum transfer to and the response of polar marine Ekman layer in RASM and Community Earth System Model (CESM) was investigated by Roberts et al. (2015). The increased frequency of oceanic flux exchange in CESM, following the RASM guidance, caused a considerable increase in the median inertial ice speed across the Southern Ocean and parts of the Arctic. A comprehensive evaluation of the RASM1.0 atmosphere-ocean-sea ice-land interface was completed by Brunke et al. (2018). RASM was also demonstrated for its capability to simulate extreme events in agreement with observations in space and time (Lee et al. submitted). In particular, the development of three open water events, known as polynyas, have been simulated north of Greenland in February of 2011, 2017 and 2018, in agreement with satellite observations for the past four decades. The optimized RASM sea ice results have been favorably evaluated against satellite observations and a subset of eleven CMIP6 models (Watts et al. submitted). In a complementary project, Jin et al. (2018) have shown that RASM with higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice conditions, concentrations of nutrients and ice algae, in comparison to results from the coarse-resolution (1°) CESM. In two other complementary studies, RASM results were used (i) to explain areas of concentrated use by bowhead whales, the seasonal progression in the use, and the physical environment within those areas (Citta et al. 2015) and (ii) for a synthesis of fall bowhead whales distribution and migration in the Bering-Chukchi-Beaufort (BCB) Sea to investigate whale movements and feeding to the local ocean hydrography and currents (Citta et al. 2018). However, the multi-decadal output from the CESM Large Ensemble yielded unrealistic forcing. Instead, the shorter NCEP CFSv2 9-month forecasts were successfully tested and afforded an increased ensemble size (~30) to demonstrate gains of dynamical downscaling at sub-seasonal to intra-annual time scales. The improved model physics and coupling among RASM model components have yielded more realistic representation of the sea ice cover and consistent across all model components initial conditions. Consequently, RASM demonstrates significant gains compared to simulation of sea ice in the NCEP reanalysis. In addition, RASM 6-month ensemble forecasts yield very realistic sea ice distribution, which demonstrates both significant gains of dynamical downscaling and the continued impact of the initial conditions on forecasts out to 6 months (https://nps.edu/web/rasm/predictions). A follow up study using RASM for dynamical downscaling of the more realistic CESM initialized Decadal Prediction Large Ensemble output is currently ongoing as part of the DOE RGMA HiLAT-RASM project.

54 ENVIRONMENTAL SCIENCES↗