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NASA NTRS2009

Relationships Between Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes on Intraseasonal Time Scales

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20oN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Ramey, Holly S.↗

NASA NTRS2010

Relationships Between Tropical Deep Convection, Tropospheric Mean Temperature and Cloud-Induced Radiative Fluxes on Intraseasonal Time Scales

Intraseasonal variability of deep convection represents a fundamental mode of variability in the organization of tropical convection. While most studies of intraseasonal oscillations (ISOs) have focused on the spatial propagation and dynamics of convectively coupled circulations, we examine the projection of ISOs on the tropically-averaged temperature and energy budget. The area of interest is the global oceans between 20degN/S. Our analysis then focuses on these questions: (i) How is tropospheric temperature related to tropical deep convection and the associated ice cloud fractional amount (ICF) and ice water path (IWP)? (ii) What is the source of moisture sustaining the convection and what role does deep convection play in mediating the PBL - free atmospheric temperature equilibration? (iii) What affect do convectively generated upper-tropospheric clouds have on the TOA radiation budget? Our methodology is similar to that of Spencer et al., (2007) with some modifications and some additional diagnostics of both clouds and boundary layer thermodynamics. A composite ISO time series of cloud, precipitation and radiation quantities built from nearly 40 events during a six-year period is referenced to the atmospheric temperature signal. The increase of convective precipitation cannot be sustained by evaporation within the domain, implying strong moisture transports into the tropical ocean area. While there is a decrease in net TOA radiation that develops after the peak in deep convective rainfall, there seems little evidence that an "Infrared Iris"- like mechanism is dominant. Rather, the cloud-induced OLR increase seems largely produced by weakened convection with warmer cloud tops. Tropical ISO events offer an accessible target for studying ISOs not just in terms of propagation mechanisms, but on their global signals of heat, moisture and radiative flux feedback processes.

Ramey, Holly S.↗

DOE OSTI2025

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

The mission of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is to improve the understanding and representation of cloud and aerosol processes and their interaction with the Earth's surface in Earth system models (ESMs) by providing comprehensive field observations and supporting advanced data analytics. The ARM Cloud and Precipitation Measurements and Science Group (CPMSG) was chartered in March 2019 to help improve the performance and scientific impact of ARM measurements of clouds and precipitation. The group aims to identify and address gaps in measurement capabilities, maximize the scientific impact of ARM data, and effectively serve the scientific community. To achieve these goals, the group includes experts in cloud and precipitation science, as well as representatives from ARM infrastructure, including instrument mentors, engineers, data quality officers, and data product translators. Prior to CPMSG, early discussions on cloud and precipitation measurements primarily focused on improving radar systems, but have since evolved to include a broader scope involving radiometers and other instruments. Since its formation, the CPMSG has gathered feedback using science traceability matrices. CPMSG aims to keep these as living documents to show the measurement needs, scientific drivers, roadblocks, maturity of measurements and retrievals, and pathways to model improvements. The group meets quarterly to discuss and prioritize measurement and operational improvements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

ARM Cloud and Precipitation Measurements and Science Group (CPMSG) 2024 Workshop Report

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6

This paper documents the methodology and preliminary results from a perturbed parameter ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2–CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks are analyzed. The use of various emulators is explored in the multi-dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties, are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2–CAM6 PPE is publicly available and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g., coupling to the land surface).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Phenomena Portal: Large- Scale Visual Exploration of Atmospheric Phenomena

The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.

Muthukumaran Ramasubramanian↗

NASA NTRSDate not supplied

Arctic Radiation-Cloud-Aerosol-Surface Interaction eXperiment (ARCSIX)

The Arctic climate system is amidst a transition. Over the last 40 years, the Arctic sea ice pack has transformed from a predominantly thick, multi-year sea ice to a predominantly thin, seasonal sea ice, termed the “New Arctic”. The observed rapid changes in the Arctic sea ice pack are an integral part of the Arctic Amplification phenomenon and represent a response to and a feedback on global climate change. As a result, the role of the Arctic within the global climate system is changing. Substantial uncertainty exists in our understanding of the atmosphere-surface interactions within the Arctic system, limiting our knowledge of the Arctic’s role in the future climate. Advancing our understanding of the Arctic climate system requires (1) measurements of the coupling between radiative processes and sea ice surface properties during summer sea ice melt; (2) measurements of the processes controlling the predominant Arctic cloud regimes and their properties (Fig. 1); and (3) improvements in the ability to monitor Arctic cloud, radiation, and sea ice processes from space. A key challenge is that thin, low clouds that are radiatively important to the Arctic surface energy budget can go undetected (Fig. 1). The Arctic Radiation-Cloud-Aerosol-Surface-Interaction eXperiment (ARCSIX) is an airborne campaign based at the Pituffik Space Base in Greenland from May-August 2024 sponsored by the National Aeronautics and Space Administration (NASA) to address these needs. ARCSIX consists of two airborne measurement campaigns taking place in two 3-week intervals during the early and late sea ice melt season: late May through early June and late July through early August, respectively. ARCSIX science is guided by three broad science questions that encapsulate the key influences of radiation-cloud-aerosol-sea ice coupling and a remote sensing and modeling objective: Science Question 1 (Radiation): What is the impact of the predominant summer Arctic cloud types on the radiative surface energy budget? Science Question 2 (Cloud Life Cycle): What processes control the evolution and maintenance of the predominant cloud regimes in the summertime Arctic? Science Question 3 (Sea Ice): How do the two-way interactions between surface properties and atmospheric forcings affect the sea ice evolution? Remote Sensing and Modeling Objective: Enhance our long-term space-based monitoring and predictive capabilities of Arctic sea ice, clouds, and aerosols.

Patrick Taylor↗

NASA NTRS2020

Attribution of Chemistry-Climate Model Initiative (CCMI) Ozone Radiative Flux Bias from Satellites

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6-μm ozone band is a fundamental quantity for understanding chemistry-climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6-μm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Inter-comparison Project (ACCMIP) simulations. The principal culprits are tropical mid and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mWm-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mWm-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mWm-2). We found that AM3 and CMAM have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to difference processes. Overall, the multi-model ensemble mean bias is –133±98 mWm-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.

Aura Tropospheric Emission Spectrometer (TES) meas↗

NASA NTRS1993

The reionization of the universe: The feedback of galaxy formation on the intergalactic medium

The thermal and ionization evolution of a uniform intergalactic medium (IGM) composed of H and He, undergoing reionization, including the mean effect of gas clumps embedded in a smoothly distributed ambient gas were calculated. The rate equations for ionization and recombination were solved together with the equations of energy conservation, including the effects of cosmological expansion, radiative and Compton cooling, and the diffuse flux emitted by the gas, and radiative transfer. The contribution to the continuum opacity of the universe due to the observed quasar absorption line clouds (QALC'S) were included. A variety of sources of photoionization, including quasars and primeval galaxies, as well as the possibility that hydrodynamical processes deposit thermal energy in the IGM were considered. Applications of these calculations including the evolution of the Ly-alpha forest clouds are described. A self-consistent treatment of the thermal and ionization history of the intergalactic medium (IGM) must take account of the growth of structure in the universe, since the mean density of the IGM corresponds primarily to the time-varying uncollapsed fraction of the baryon-electron component of the matter, and the collapsed fraction, in turn, can have a feedback effect on this uncollapsed fraction by releasing ionizing radiation and thermal energy and by contributing to the opacity of the universe. The coupled evolution of the IGM and the emerging structure with a special focus on the reionization of the IGM, which is believed to have been completed by some redshift z is approximately greater than 4, as inferred from the absence of the Gunn-Peterson effect in the spectra of high z quasars, are studied. The results and implications of detailed, numerical calculations of the thermal and ionization balance and radiative transfer in a uniform IGM of H and He, including the mean effect of an evolving distribution of gas clumps embedded in a smoothly distributed ambient gas is described.

Shapiro, Paul R.↗

NASA NTRS2022

2022 Power Global Community (Gloco) Summit Summary Report

The Prediction Of Worldwide Energy Resources (POWER) Project 25th year of providing global solar and meteorology data products to the world. The goals of this event were to inform users of new, enhanced features, gather feedback on services, identify new requests and requirements, and capture more thorough user stories while identifying new user communities and partnership opportunities. The event was “virtual” and had over 580 registrants. Over the two-day event, the Summit was attended by 162 unique attendees representing 24 countries.

NASA↗

NASA NTRS1997

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.↗

NASA NTRSDate not supplied

The Surface Albedo of Sea Ice in CMIP6 and the Implications for the Surface Albedo Feedback

The Arctic has experienced rapid sea ice loss and a substantial decline in surface albedo, significantly impacting its radiation budget. Climate models from the Coupled Model Intercomparison Project (CMIP6) reproduce these changes. However, inconsistencies remain among models regarding the magnitude, spatial distribution, and seasonal patterns of Arctic surface albedo evolution. This study investigates these discrepancies by comparing model outputs with observation from the Clouds and the Earth's Radiant Energy System (CERES). We develop a decomposition method to assess the contributions of sea ice albedo, sea ice concentration, and sea ice extent to Arctic surface albedo. Over land, differences in snow cover account for the substantial inter-model spread in surface albedo, while over the ocean, sea ice albedo, concentration, and extent all contribute. Comparisons between CMIP6 and the Atmospheric Model Intercomparison Project (AMIP) simulations, which use identically prescribed sea ice concentrations, reveals considerable inter-model spread in Arctic Ocean surface albedo due to differences in sea ice albedo. Applying the decomposition method to projections shows that models predicting larger decreases in sea ice concentration and extent, especially in the Central Arctic, exhibit lower surface albedo and stronger sea ice albedo feedback. Beyond 2050, Arctic Ocean surface albedo decline is mainly influenced by sea ice extent indicating that the retreat of the ice edge is the most important process to constrain the surface albedo feedback. This study provides insights into factors contributing to the spread and changes in Arctic surface albedo and the associated sea ice albedo feedback.

Patrick C Taylor↗

NASA NTRS2004

Theoretical and Observational Determination of Global and Regional Radiation Budget, Forcing and Feedbacks at the Top-of-Atmosphere and Surface

Report consists of: 1. List of accomplishments 2. List of publications 3. Abstracts of published or submitted papers and 4. Subject invention disclosure. The accomplishments of the grant listed are: 1. Improved the third-order turbulence closure in cloud resolving models to remove the liquid water oscillation. 2. Used the University of California-Los Angeles (UCLA) large-eddy simulation (LES) model to provide data for radiation transfer testing. 3. Revised shortwave k-distribution models based on HITRAN 2000. 4. Developed a gamma-weighted two-stream radiative transfer model for radiation budget estimate applications. 5. Estimated the effect of spherical geometry to the earth radiation budget. 6. Estimated top-of-atmosphere irradiance over snow and sea ice surfaces. 7. Estimated the aerosol direct radiative effect at the top of the atmosphere. 8. Estimated the top-of-atmosphere reflectance of the clear-sky molecular atmosphere over ocean. 9. Developed and validated new set of Angular Distribution Models for the CERES TRMM satellite instrument (tropical) 10. Developed and validated new set of Angular Distribution Models for the CERES Terra satellite instrument (global) 11. Quantified the top-of-atmosphere direct radiative effect of aerosols over global oceans from merged CERES and MODIS observations 12 Clarified the definition of TOA flux reference level for radiation budget studies 13. Developed new algorithm for unfaltering CERES measured radiances 14. Used multiangle POLDER measurements to produce narrowband angular distribution models and examine the effect of scene identification errors on TOA albedo estimates 15. Developed and validated a novel algorithm called the Multidirectional Reflectance Matching (MRM) model for inferring TOA albedos from ice clouds using multi-angle satellite measurements. 16. Developed and validated a novel algorithm called the Multidirectional Polarized Reflectance Matching (MPRM) model for inferring particle shapes from ice clouds using multi-angle polarized satellite measurements. 17. Developed 4 advanced light scattering models including the three-dimensional (3D) uniaxial perfectly matched layer (UPML) finite-difference time-domain (FDTD) model. 18. Develop sunglint in situ measurement and study reflectance distribution in the sunglint area. 19. Lead a balloon-borne radiometer TOA albedo validation effort. 20. Developed a CERES surface UVB, UVA, and UV index product.

Loeb, Norman G.↗

DOE OSTI2024

Approach for energy efficient building design during early phase of design process

Energy consumption in the building sector is about 40% of total energy consumed globally and is trending upwards, along with its contribution to greenhouse gas (GHG) emissions. Given the adverse impacts of GHG emissions, it is crucial to integrate energy efficiency into building designs. The most significant opportunities for enhancing energy performance are present during the initial phases of building design, when there is less impact of other design constraints. Various tools exist for simulating different design options and providing feedback in terms of energy consumption and comfort parameters. These simulation outputs must then be analyzed to derive design solutions. This paper presents an innovative approach that utilizes user input parameters, processes them through cloud computing, and outputs easily understandable strategies for energy-efficient building design. The methodology employs Asynchronous Distributed Task Queues (DTQ) - a more scalable and reliable alternative to conventional speedup techniques-for conducting parametric energy simulations in the cloud. The goal of this approach is to assist design teams in identifying, visualizing, and prioritizing energy-saving design strategies from a range of possible solutions for each project. Furthermore, a tool ‘eDOT’ has been developed utilizing the discussed methodology. Unlike existing tools, eDOT leverages artificial intelligence to dynamically generate and provide design strategies during the early phases of design process. By simplifying the simulation process, eDOT enables design teams to make informed, data-driven decisions without needing to interpret complex simulation outputs. A case study simulated for two locations is provided in this paper to demonstrate the effectiveness of eDOT, further underscoring its practical impact on energy-efficient building design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2011

Kennedy Space Center ITC-1 Internship Overview

As an intern for Priscilla Elfrey in the ITC-1 department, I was involved in many activities that have helped me to develop many new skills. I supported four different projects during my internship, which included the Center for Life Cycle Design (CfLCD), SISO Space Interoperability Smackdown, RTI Teacher Mentor Program, and the Discrete Event Simulation Integrated Visualization Environment Team (DIVE). I provided the CfLCD with web based research on cyber security initiatives involving simulation, education for young children, cloud computing, Otronicon, and Science, Technology, Engineering, and Mathematics (STEM) education initiatives. I also attended STEM meetings regarding simulation courses, and educational course enhancements. To further improve the SISO Simulation event, I provided observation feedback to the technical advisory board. I also helped to set up a chat federation for HLA. The third project involved the RTI Teacher Mentor program, which I helped to organize. Last, but not least, I worked with the DIVE team to develop new software to help visualize discrete event simulations. All of these projects have provided experience on an interdisciplinary level ranging from speech and communication to solving complex problems using math and science.

Ni, Marcus↗

NASA NTRS2020

Global Distribution and 14-Year Changes in Erythemal Irradiance, UV Atmospheric Transmission, and Total Column Ozone 2005 – 2018 Estimated from OMI and EPIC Observations

Satellite data from the Ozone Measuring Instrument (OMI) and Earth Polychromatic Imaging Camera (EPIC) are used to study changes and global distribution of UV erythemal irradiance in mW/m(exp 2) E(ζ,φ,z,t) and the dimensionless UV index (E/25 mWm(exp 2)) over the Earth’s surface as a function of latitude ζ, longitude φ, altitude z, and time t. OMI time series data starting in January 2005 to December 2018 are used to estimate 14-year changes in erythemal irradiance, total column ozone TCO3, scene reflectivity LER, and aerosol absorption τA at specific land sites in the Northern and Southern Hemispheres using publicly available OMI data. Estimates of changes in atmospheric transmission ΔCτ(ζ,φ,z,t) derived from OMI measured cloud and haze reflectivity show an increase between 60°S to 45°S almost no average 14-year change from 55°S to 30°N but show an increase from 35°N to 55°N. This implies increased solar insolation at higher latitudes that suggests positive feedback for global warming. Changes in aerosol absorption of UV irradiance ΔCA(ζ,φ,z,t) derived from changes in τA are mostly in the equatorial region and at higher southern latitudes resulting in correlated changes in E. TCO3 derived from OMI data has increased at a rate of 2% per decade for the latitudes between 60°S to 10°N changing to a decrease of 1% per decade between 40°N to 60°N. The result is an average decrease in E(ζ,φ,z,t) at a rate of 2% per decade in the Southern Hemisphere and an increase between 40°N to 60°N. For some specific sites (latitudes from 55°S to 45°N) there has been little or no change in E(ζ,φ,z,t) for the period 2005 – 2018. Nearly half the sites show strong correlation effects of both short- and long-term cloud and absorbing aerosol change as well as anticorrelation with total column ozone change ΔTCO3. Synoptic EPIC data from the sunlit Earth are used to derive ozone and reflectivity needed for global images of the distribution of E(ζ,φ,z,t) from sunrise to sunset centered on the Americas, Europe-Africa, and Asia. EPIC data are used to show the latitudinal distribution of E(ζ,φ,z,t) from the equator to 75° for specific longitudes. Dangerously high amounts of erythemal irradiance (12 < UV index < 18) are found for many low latitude and high-altitude sites (e.g., San Pedro, Chile (2.45 km), La Paz, Bolivia (3.78 km). Lower UV indices at some equatorial or high-altitude sites (e.g., Quito, Ecuador) are moderated by the presence of persistent cloud effects. High UVI levels (UVI > 6) are also found at most mid-latitude sites during the summer months.

Ozone Measuring Instrument (OMI) and Earth Polychr↗

DOE OSTI2025

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS1990

Observed effects of landscape variability on convective clouds

A case is presented in which clouds are observed to form first over a mesoscale-size area (100 x 300 km) of harvested wheat in Oklahoma, where the ground temperature is warmer than adjoining areas dominated by growing vegetation. In addition, clouds are suppressed over relatively long bands downwind of small man-made lakes and areas characterized by heavy tree cover. The observed variability of cloud relative to landscape type is compared with that simulated with a one-dimensional boundary-layer model. Clouds form earliest over regions characterized by high, sensible heat flux, and are suppressed over regions characterized by high, latent heat flux during relatively dry atmospheric conditions. This observation has significance in gaining understanding of the feedback mechanisms of land modification on climate, as well as understanding relatively short-range weather forecasting.

Rabin, Robert M.↗