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NASA NTRSDate not supplied

NASA’s Earth System Observatory Formulation Progress

The 2017 Earth Science Decadal Survey by the National Academies of Science, Engineering, and Medicine identified five foundational observations, or Designated Observables (DO), to be implemented as missions by NASA. To address these five DO areas – Surface Biology and Geology; Mass Change; Aerosols; Cloud, Convection, and Precipitation; and Surface Deformation and Change – NASA is developing the Earth System Observatory (ESO) as an array of Earth-focused, interconnected satellite missions. The ESO will build on the strong history of international partnerships in NASA Earth science, with initial participation and collaboration on these missions across space agency partners including the Japanese Aerospace Exploration Agency (JAXA), Centre National D'Etudes Spatiales (CNES), Canadian Space Agency (CSA), Deutsches Zentrum für Luft- und Raumfahrt (DLR), and Agenzia Spaziale Italiana (ASI). Targeting launch dates in the late 2020s and early 2030s, the ESO will work as a single observatory, with each satellite in the ESO delivering its own valuable information, but taken together, the data and imagery will provide the global community with a multidimensional, holistic view of the Earth. In addition to furthering the world’s scientific knowledge, data gathered by ESO missions will provide actionable science to inform decisions related to climate change, disaster mitigation, and wildfires, improve real-time agricultural processes, and many other applications. This paper will provide an overview of the ESO development activities, as well as an update on the individual ESO missions currently in formulation – Atmosphere Observing System, Gravity Recovery and Climate Experiment-Continuity, and Surface Biology and Geology – including current mission architectures and concepts, international partner collaboration, science community engagement, and applications efforts, as well as how ESO data will be freely open and accessible to users all over the world.

NASA Earth Science↗

NASA NTRS2004

Asteroid Exploration with Autonomic Systems

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. The prospective ANTS (Autonomous Nano Technology Swarm) mission comprises autonomous agents including worker agents (small spacecra3) designed to cooperate in asteroid exploration under the overall authoriq of at least one ruler agent (a larger spacecraft) whose goal is to cause science data to be returned to Earth. The ANTS team (ruler plus workers and messenger agents), but not necessarily any individual on the team, will exhibit behaviors that qualify it as an autonomic system, where an autonomic system is defined as a system that self-reconfigures, self-optimizes, self-heals, and self-protects. Autonomic system concepts lead naturally to realistic, scalable architectures rich in capabilities and behaviors. In-depth consideration of a major mission like ANTS in terms of autonomic systems brings new insights into alternative definitions of autonomic behavior. This paper gives an overview of the ANTS mission and discusses the autonomic properties of the mission.

Truszkowski, Walt↗

NASA NTRS2007

Processing AIRS Scientific Data Through Level 2

The Atmospheric Infrared Spectrometer (AIRS) Science Processing System (SPS) is a collection of computer programs, denoted product generation executives (PGEs), for processing the readings of the AIRS suite of infrared and microwave instruments orbiting the Earth aboard NASA s Aqua spacecraft. AIRS SPS at an earlier stage of development was described in "Initial Processing of Infrared Spectral Data' (NPO-35243), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 39. To recapitulate: Starting from level 0 (representing raw AIRS data), the PGEs and their data products are denoted by alphanumeric labels (1A, 1B, and 2) that signify the successive stages of processing. The cited prior article described processing through level 1B (the level-2 PGEs were not yet operational). The level-2 PGEs, which are now operational, receive packages of level-1B geolocated radiance data products and produce such geolocated geophysical atmospheric data products such as temperature and humidity profiles. The process of computing these geophysical data products is denoted "retrieval" and is quite complex. The main steps of the process are denoted microwave-only retrieval, cloud detection and cloud clearing, regression, full retrieval, and rapid transmittance algorithm.

Oliphant, Robert↗

NASA NTRS2008

25th Space Simulation Conference. Environmental Testing: The Earth-Space Connection

Topics covered include: Methods of Helium Injection and Removal for Heat Transfer Augmentation; The ESA Large Space Simulator Mechanical Ground Support Equipment for Spacecraft Testing; Temperature Stability and Control Requirements for Thermal Vacuum/Thermal Balance Testing of the Aquarius Radiometer; The Liquid Nitrogen System for Chamber A: A Change from Original Forced Flow Design to a Natural Flow (Thermo Siphon) System; Return to Mercury: A Comparison of Solar Simulation and Flight Data for the MESSENGER Spacecraft; Floating Pressure Conversion and Equipment Upgrades of Two 3.5kw, 20k, Helium Refrigerators; Affect of Air Leakage into a Thermal-Vacuum Chamber on Helium Refrigeration Heat Load; Special ISO Class 6 Cleanroom for the Lunar Reconnaissance Orbiter (LRO) Project; A State-of-the-Art Contamination Effects Research and Test Facility Martian Dust Simulator; Cleanroom Design Practices and Their Influence on Particle Counts; Extra Terrestrial Environmental Chamber Design; Contamination Sources Effects Analysis (CSEA) - A Tool to Balance Cost/Schedule While Managing Facility Availability; SES and Acoustics at GSFC; HST Super Lightweight Interchangeable Carrier (SLIC) Static Test; Virtual Shaker Testing: Simulation Technology Improves Vibration Test Performance; Estimating Shock Spectra: Extensions beyond GEVS; Structural Dynamic Analysis of a Spacecraft Multi-DOF Shaker Table; Direct Field Acoustic Testing; Manufacture of Cryoshroud Surfaces for Space Simulation Chambers; The New LOTIS Test Facility; Thermal Vacuum Control Systems Options for Test Facilities; Extremely High Vacuum Chamber for Low Outgassing Processing at NASA Goddard; Precision Cleaning - Path to Premier; The New Anechoic Shielded Chambers Designed for Space and Commercial Applications at LIT; Extraction of Thermal Performance Values from Samples in the Lunar Dust Adhesion Bell Jar; Thermal (Silicon Diode) Data Acquisition System; Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports; Exhaustive Thresholds and Resistance Checkpoints; Reconfigurable HIL Testing of Earth Satellites; FPGA Control System for the Automated Test of MicroShutters; Ongoing Capabilities and Developments of Re-Entry Plasma Ground Tests at EADS-ASTRIUM; Operationally Responsive Space Standard Bus Battery Thermal Balance Testing and Heat Dissipation Analysis; Galileo - The Serial-Production AIT Challenge; The Space Systems Environmental Test Facility Database (SSETFD), Website Development Status; Simulated Reentry Heating by Torching; Micro-Vibration Measurements on Thermally Loaded Multi-Layer Insulation Samples in Vacuum; High Temperature Life Testing of 80Ni-20Cr Wire in a Simulated Mars Atmosphere for the Sample Analysis at Mars (SAM) Instrument Suit Gas Processing System (GPS) Carbon Dioxide Scrubber; The Planning and Implementation of Test Facility Improvements; and Development of a Silicon Carbide Molecular Beam Nozzle for Simulation Planetary Flybys and Low-Earth Orbit.

Packard, Edward↗

NASA NTRS2010

NASA Tech Briefs, March 2010

Topics covered include: Software Tool Integrating Data Flow Diagrams and Petri Nets; Adaptive Nulling for Interferometric Detection of Planets; Reducing the Volume of NASA Earth-Science Data; Reception of Multiple Telemetry Signals via One Dish Antenna; Space-Qualified Traveling-Wave Tube; Smart Power Supply for Battery-Powered Systems; Parallel Processing of Broad-Band PPM Signals; Inexpensive Implementation of Many Strain Gauges; Constant-Differential-Pressure Two-Fluid Accumulator; Inflatable Tubular Structures Rigidized with Foams; Power Generator with Thermo-Differential Modules; Mechanical Extraction of Power From Ocean Currents and Tides; Nitrous Oxide/Paraffin Hybrid Rocket Engines; Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents; Probabilistic Multi-Factor Interaction Model for Complex Material Behavior; Foldable Instrumented Bits for Ultrasonic/Sonic Penetrators; Compact Rare Earth Emitter Hollow Cathode; High-Precision Shape Control of In-Space Deployable Large Membrane/Thin-Shell Reflectors; Rapid Active Sampling Package; Miniature Lightweight Ion Pump; Cryogenic Transport of High-Pressure-System Recharge Gas; Water-Vapor Raman Lidar System Reaches Higher Altitude; Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes; Wide-Field-of-View, High-Resolution, Stereoscopic Imager; Electrical Capacitance Volume Tomography with High-Contrast Dielectrics; Wavefront Control and Image Restoration with Less Computing; Polarization Imaging Apparatus; Stereoscopic Machine-Vision System Using Projected Circles; Metal Vapor Arcing Risk Assessment Tool; Performance Bounds on Two Concatenated, Interleaved Codes; Parameterizing Coefficients of a POD-Based Dynamical System; Confidence-Based Feature Acquisition; Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery; Universal Decoder for PPM of any Order; Algorithm for Stabilizing a POD-Based Dynamical System; Mission Reliability Estimation for Repairable Robot Teams; Processing AIRS Scientific Data Through Level 3; Web-Based Requesting and Scheduling Use of Facilities; AutoGen Version 5.0; Time-Tag Generation Script; PPM Receiver Implemented in Software; Tropospheric Emission Spectrometer Product File Readers; Reporting Differences Between Spacecraft Sequence Files; Coordinating "Execute" Data for ISS and Space Shuttle; Database for Safety-Oriented Tracking of Chemicals; Apparatus for Cold, Pressurized Biogeochemical Experiments; Growing B Lymphocytes in a Three-Dimensional Culture System; Tissue-like 3D Assemblies of Human Broncho-Epithelial Cells; Isolation of Resistance-Bearing Microorganisms; Oscillating Cell Culture Bioreactor; and Liquid Cooling/Warming Garment.

Source record↗

NASA NTRS2012

An Overview of MODIS On-orbit Operation, Calibration, and Lessons

Two nearly identical copies of the Moderate Resolution Imaging Spectroradiometer (MODIS) have successfully operated onboard the Terra and Aqua spacecraft for more than II years and 9 years since their launch in December 1999 and May 2002, respectively. MODIS is a key instrument for the NASA's Earth Observing System (EOS) missions. MODIS observations have produced an unprecedented amount and a broad range of data products and significantly benefited the science and user community. Its follow-on instrument, the Visible/Infrared Imager Radiometer Suite (VIIRS) on-board the NPOESS Preparatory Project (NPP) spacecraft, is currently scheduled for launch in late October, 2011. The NPP serves as a bridge mission between EOS and the Joint Polar Satellite System (JPSS). MODIS collects data in 36 spectral bands, covering spectral regions from visible (VIS) to long-wave infrared (L WIR), and at three different spatial resolutions. Because of its stringent design requirements, MODIS was built with a complete set of onboard calibrators, including a solar diffuser (SO), a solar diffuser stability monitor (SDSM), a blackbody (BB), a spectroradiometric calibration assembly (SRCA), and a space view (SV) port. Except for tbe SRCA, VIlRS carries the same set of onboard calibrators as MODIS. The SD/SDSM system is used together to calibrate tbe reflective solar bands (RSB). The BB is designed for the thermal emissive bands (TEB) calibration. Similar to Terra and Aqua MODIS, VIlRS will also make regular lunar observations to monitor RSB radiometric calibration stability. In this paper, we provide an overview of MODIS on-orbit operation and calibration activities and present issues identified and lessons learned from mission-long instrument operations and implementation of various calibration and characterization strategies. Examples of both Terra and Aqua MODIS instrument on-orbit performance, including their similarities and unique characteristics, are discussed in tbe context of what might be expected from and benefited to tbe NPP VIlRS operation and calibration. It is anticipated that MODIS experience and lessons will also provide valuable information for other earth observing missions/sensors.

Xiong, Jack↗

NASA NTRS2005

Mission leverage education: NSU/NASA innovative undergraduate model

The BEST Lab (Center for Excellence in Science Education), the Center for Materials Research (CMR), and the Chemistry, Mathematics, Physics, and Computer Science (CS) Departments at Norfolk State University (NSU) joined forces to implement MiLEN(2) IUM - an innovative approach tu integrate current and emerging research into the undergraduate curricula and train students on NASA-related fields. An Earth Observing System (EOS) mission was simulated where students are educated and trained in many aspects of Remote Sensing: detector physics and spectroscopy; signal processing; data conditioning, analysis, visualization; and atmospheric science. This model and its continued impact is expected to significantly enhance the quality of the Mathematics, Science, Engineering and Technology (MSET or SMET) educational experience and to inspire students from historically underrepresented groups to pursue careers in NASA-related fields. MiLEN(2) IUM will be applicable to other higher education institutions that are willing to make the commitment to this endeavor in terms of faculty interest and space.

Chaudhury, S. Raj↗

NASA NTRS2012

Leveraging Data Intensive Computing to Support Automated Event Services

A large portion of Earth Science investigations is phenomenon- or event-based, such as the studies of Rossby waves, mesoscale convective systems, and tropical cyclones. However, except for a few high-impact phenomena, e.g. tropical cyclones, comprehensive records are absent for the occurrences or events of these phenomena. Phenomenon-based studies therefore often focus on a few prominent cases while the lesser ones are overlooked. Without an automated means to gather the events, comprehensive investigation of a phenomenon is at least time-consuming if not impossible. An Earth Science event (ES event) is defined here as an episode of an Earth Science phenomenon. A cumulus cloud, a thunderstorm shower, a rogue wave, a tornado, an earthquake, a tsunami, a hurricane, or an EI Nino, is each an episode of a named ES phenomenon," and, from the small and insignificant to the large and potent, all are examples of ES events. An ES event has a finite duration and an associated geolocation as a function of time; its therefore an entity in four-dimensional . (4D) spatiotemporal space. The interests of Earth scientists typically rivet on Earth Science phenomena with potential to cause massive economic disruption or loss of life, but broader scientific curiosity also drives the study of phenomena that pose no immediate danger. We generally gain understanding of a given phenomenon by observing and studying individual events - usually beginning by identifying the occurrences of these events. Once representative events are identified or found, we must locate associated observed or simulated data prior to commencing analysis and concerted studies of the phenomenon. Knowledge concerning the phenomenon can accumulate only after analysis has started. However, except for a few high-impact phenomena. such as tropical cyclones and tornadoes, finding events and locating associated data currently may take a prohibitive amount of time and effort on the part of an individual investigator. And even for these high-impact phenomena, the availability of comprehensive records is still only a recent development. A major reason for the lack of comprehensive ,records for the majority of the ES phenomena is the perception that they do not pose immediate and/or severe threat to life and property and are thus not consistently tracked. monitored, and catalogued. Many phenomena even lack commonly accepted criteria for definitions. However. the lack of comprehensive records is also due to the increasingly prohibitive volume of observations and model data that must be examined. NASA Earth Observing System Data Information System (EOSDIS) alone archives several petabytes (PB) of satellite remote sensing data and steadily increases. All of these factors contribute to the difficulty of methodically identifying events corresponding to a given phenomenon and significantly impede systematic investigations. In the following we present a couple motivating scenarios, demonstrating the issues faced by Earth scientists studying ES phenomena.

Clune, Thomas L.↗

NASA NTRSDate not supplied

MISR Browse data (MISBR_V4)

A MISR Browse Tool is available to allow easy access to ellipsoid-derived, true-color images for each camera reduced to 2.2 km resolution. The MISR red, green and blue bands are used to create the true-color image in JPEG format. The image is intentionally clipped and gamma-stretched to make cloud, ocean and land features visible. The user may find the Browse Tool helpful before ordering data. The tool's purpose is to search and view images in the on-line user interface. However, the browse product can be ordered separately. The Browse Tool page has Orbit-to-Date and Lat/Lon-to-Path/Block conversion tools to help identify particular MISR geographic locations and data files. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.2 km; Longitude_Resolution=2.2 km; Horizontal_Resolution_Range=1 km - < 10 km or approximately .01 degree - < .09 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly].

IMAGE↗

NASA NTRS2000

Earth Science Enterprise Scientific Data Purchase Project: Verification and Validation

This paper presents viewgraphs on the Earth Science Enterprise Scientific Data Purchase Project's verification,and validation process. The topics include: 1) What is Verification and Validation? 2) Why Verification and Validation? 3) Background; 4) ESE Data Purchas Validation Process; 5) Data Validation System and Ingest Queue; 6) Shipment Verification; 7) Tracking and Metrics; 8) Validation of Contract Specifications; 9) Earth Watch Data Validation; 10) Validation of Vertical Accuracy; and 11) Results of Vertical Accuracy Assessment.

Jenner, Jeff↗

NASA NTRSDate not supplied

From the Ground Up: Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) Comparison of Vertical Profiles with 2022 Student Airborne Research Program (SARP) In Situ Data

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument, installed on the International Space Station (ISS) in 2017, has completed over five years of data collection and the accompanying production of science data products. SAGE III/ISS is a solar and lunar occultation instrument that scans the light from the Sun and Moon through the limb of the Earth’s atmosphere to produce vertical profiles of aerosol, ozone, water vapor, and other trace gasses. This year provided the unique opportunity to compare in situ data collected during the NASA Student Airborne Research Program (SARP) summer airborne campaign with data collected by SAGE III/ISS on coincident overpasses. SARP, a summer internship program typically for rising undergraduate seniors, provides students with an opportunity to gain hands-on experience making earth system measurements using NASA’s airborne science platforms. The NASA DC-8 flying laboratory collected in-situ measurements of ozone and other trace gasses during the summer 2022 SARP campaign. While the general focus with SARP is on the airborne research component, this year, a suite of 10 ozonesonde launches spatially and temporally co-located with the research flights collected atmospheric state and in-situ ozone measurements from inland southern California. This presentation shows the results of comparing SAGE III/ISS vertical profiles with those of in situ data collected during the summer 2022 SARP campaign.

In Situ↗

DOE OSTI2026

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

NASA NTRS1994

A survey of geographical information systems applications for the Earth Science and Applications Division, Space Sciences Laboratory, Marshall Space Flight Center

The purpose of this document is to introduce Geographical Information System (GIS) terminology and summarize interviews conducted with scientists in the Earth Science and Applications Division (ESAD). There is a growing need in ESAD for GIS technology. With many different data sources available to the scientists comes the need to be able to process and view these data in an efficient manner. Since most of these data are stored in vastly different formats, specialized software and hardware are needed. Several ESAD scientists have been using a GIS, specifically the Man-computer Interactive Data Access System (MCIDAS). MCIDAS can solve many of the research problems that arise, but there are areas of research that need more powerful tools; one such example is the multispectral image analysis which is described in this document. Given the strong need for GIS in ESAD, we recommend that a requirements analysis and implementation plan be developed using this document as a basis for further investigation.

Rickman, D.↗

NASA NTRS2015

Mars2020 Entry, Descent, and Landing Instrumentation (MEDLI2): Science Objectives and Instrument Requirements

NASAs exploration and technology roadmaps call for capability advancements in Mars entry, descent, and landing (EDL) systems to enable increased landed mass, a higher landing precision, and a wider planetary access. It is also recognized that these ambitious EDL performance goals must be met while maintaining a low mission risk in order to pave the way for future human missions. As NASA is engaged in developing new EDL systems and technologies via testing at Earth, instrumentation of existing Mars missions is providing valuable engineering data for performance improvement, risk reduction, and an improved definition of entry loads and environment. The most notable recent example is the Mars Entry, Descent and Landing Instrument (MEDLI) suite hosted by Mars Science Laboratory for its entry in Aug 2012. The MEDLI suite provided a comprehensive dataset for Mars entry aerodynamics, aerothermodynamics and thermal protection system (TPS) performance. MEDLI data has since been used for unprecedented reconstruction of aerodynamic drag, vehicle attitude, in-situ atmospheric density, aerothermal heating, and transition to turbulence, in-depth TPS performance and TPS ablation. [1,2] In addition to validating predictive models, MEDLI data has demonstrated extra margin available in the MSL forebody TPS, which can potentially be used to reduce vehicle parasitic mass. The presentation will introduce a follow-on MEDLI instrumentation suite (called MEDLI2) that is being developed for Mars-2020 mission. MEDLI2 has an enhanced scope that includes backshell instrumentation, a wider forebody coverage, and instruments that specifically target supersonic aerodynamics. Similar to MEDLI, MEDLI2 uses thermal plugs with embedded thermocouples and ports through the TPS to measure surface pressure. MEDLI2, however, also includes heat flux sensors in the backshell and a low range pressure transducer to measure afterbody pressure.

Aerothermodynamics↗

DOE OSTI2016

Modeling Sustainability: Population, Inequality, Consumption, and Bidirectional Coupling of the Earth and Human Systems

Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. Here, we argue that in order to understand the dynamics of either system, Earth System Models must be coupled with Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as United Nations population projections.This makes current models likely to miss important feedbacks in the real Earth–Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. Lastly, the importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth–Human system models for devising effective science-based policies and measures to benefit current and future generations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1985

NASA plans for spaceborne lidar - The Earth Observing System

The use of laser techniques to observe the earth's atmosphere and surface from space is examined. An Earth Observing System is proposed as the platform for performing lidar observations. The objectives and capabilities of the Lidar Atmospheric Sounder and Altimeter (LASA) are described. The measurement techniques for collecting temperature, pressure, and water vapor profiles, the vertical distribution of ozone in the stratosphere and troposphere, and atmospheric particulates profiles are discussed. The LASA requirements for altimetry and retroranging are considered. The Doppler Lidar Wind Sensor which provides data on wind velocity is analyzed. These laser systems with increased spatial resolution and accuracy form an efficient information system for studying earth science developments.

Curran, R. J.↗

NASA NTRS1991

Early-EOS data and information system

NASA's Earth Observing System (EOS), an integral part of the U.S. Global Change Research Program, will provide simultaneous observations from a suite of instruments in low-earth orbit. The EOS Data and Information System (EOSDIS) will handle the data from those instruments, as well as provide access to observations and related information from other earth science missions. The Early-EOSDIS Program will provide initial improved support for global change research by building upon present capabilities and data, and will establish a working prototype EOSDIS for selected archiving, distribution, and information management functions by mid-1994.

Ludwig, George H.↗