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At least 1,135 records · Page 63

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

interference↗

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗

NASA Engineering and Safety Center Lunar Rover Design Concepts Assessments

Mass is a significant risk to programs and projects as they transition from formulation to implementation, especially in larger human space systems where delivery mass or volume can be a constrained commodity. • Concepts developed without an adequate systems-engineering basis, including design and operations experience, may miss significant functionality and subsequent mass required for integration or operations. • Further uncertainty can be associated with not fully understanding design best practices and standards that drive mass, such as design for minimum risk or fault tolerance.1 • Finally, the appropriate systems engineering mass properties management rigor and technical discipline insight are required to set the mass baseline, including appropriate mass growth allowance (MGA) to ensure program success. Mass is a key quantity that should be constantly monitored by the systems engineer and the program/project management stakeholder to ensure mission compatibility throughout the project life cycle. In addition, mass is a key programmatic performance metric monitored by the NASA Chief Financial Officer for current and future program cost estimating. NASA Exploration Systems sought an assessment of reasonableness with respect to different potential rover concepts that balances mass needs and human-class cargo lander capabilities. Appropriate systems engineering mass properties management rigor and technical discipline insight were used, and are required to set the mass baseline, including appropriate MGA to ensure program success. Two independent Lunar rover concepts were evaluated, with a goal to understand concept credibility and the Lunar rover designs potential extensibility for Mars surface operations. A notional generic rover concept is shown in Figure 1.

Systems Engineering↗

A new approach to the linear theory of single-species tearing in two-dimensional quasi-neutral sheets

We have developed the linear theory of collisionless ion tearing in a two-dimensional magnetotail equilibrium for a single resonant species. We have solved the normal mode problem for tearing instability by an algorithm that employs particle-in-cell simulation to calculate the orbit integrals in the Maxwell-Vlasov eigenmode equation. The results of our single-species tearing analysis can be applied to ion tearing where electron effects are not included. We have calculated the tearing growth rate as a function of the magnetic field component B(sub n) normal to the current sheet for thick and thin current sheets, and we show that marginal stability occurs when the normal gyrofrequency Omega(sub n) is comparable to the Harris neutral sheet growth rate. A cross-tail B(sub y) component has little effect on the growth rate for B(sub y) approximately = B(sub n). Even in the limit B(sub y) much greater than B(sub n), the mode is strongly stabilized by B(sub n). We report than random pitch angle scattering can overcome the stabilizing effect of B(sub n) and drive the growth rate up toward the Harris neutral sheet (B(sub n) = 0) value when the pitch angle diffusion rate is comparable to Omega(sub n).

Brittnacher, M.↗

Short Duration Bioastronautics Investigation 1904: Human Factors Assessment of Vibration Effects on Visual Performance during Launch

The primary objective of the Short Duration Bioastronautics Investigation (SDBI) 1904 was to determine visual performance limits during Shuttle operational vibration and g-loads, specifically through the determination of minimal usable font sizes using Orion-type display formats. Currently there is little to no data available to quantify human visual performance under the extreme g- and vibration conditions of launch. Existing data on shuttle vibration magnitude and frequency is incomplete and does not address human visual performance. There have been anecdotal reports of performance decrements from shuttle crews, but no structured data have been collected. Previous work by NASA on the effects of vibration and linear g-loads on human performance was conducted during the Gemini era, but these experiments were performed using displays and controls that are dramatically different than current concepts being considered by the Constellation Program. Recently, three investigations of visual performance under vibration have been completed at NASA Ames Research Center: the first examining whole-body vibration, the second employing whole-body vibration coupled with a sustained g-load, and a third examining the effects of peak versus extended duration vibration. However, all of these studies were conducted using only a single x-axis direction (eyeballs in/out). Estimates of thrust oscillations from the Constellation Ares-I first stage are driving the need for realistic human performance requirements. SDBI 1904 was an opportunity to address the need for requirements by conducting a highly focused and applied evaluation in a relevant spaceflight environment. The SDBI was a companion effort to Detailed Test Objective (DTO) 695, which measured shuttle seat accelerations (vibration) during ascent. Data from the SDBI will serve an important role in interpreting the DTO vibration data. Both SDBI 1904 and DTO 695 were low impact with respect to flight resources, and combined, they represent an efficient and focused problem solving approach. This project provided (a) immediate data for developing preliminary human performance vibration requirements; (b) flight validated inputs for ongoing and future ground-based research; and (c) preliminary information related to Orion display format design.

Thompson, Shelby↗

Updated Human Mars Ascent Vehicle Concept in Support of NASA’s Strategic Analysis Cycle 2021

The NASA Artemis program has brought significant change to the agency’s human exploration strategy over the last several years. The human exploration of Mars remains an ultimate objective of the overall human exploration strategy. However, how the agency intends to execute initial human exploration of Mars has shifted to better align with current policy. These changes find their way into the design of key architecture elements, such as the Mars Ascent Vehicle (MAV). Of the numerous changes in the conceptual human Mars architecture, two in particular have had significant impact on the design of the human MAV: the desire for minimal surface infrastructure for initial human Mars missions, and technology investment timelines in support of initial human missions to Mars. The first leads to a surface mission architecture targeting a 30-day surface duration with two crewmembers. The second drives out in-situ resource utilization (ISRU) from the initial sortie. As a result, the reference MAV design for initial human Mars missions in the Human Exploration and Operations Mission Directorate’s Strategic Analysis Cycle 2021 (SAC21) is based around supporting the return of 2 crew from the surface of Mars, without surface ISRU. This has led to several design changes since 2019, when details of a reference human MAV were last published. The MAV concept for SAC21 consists of a two-stage vehicle capable of supporting two crew for 84 hours. This duration is derived from a baseline ascent trajectory targeting an apoapsis rendezvous with the habitation element in a nominal 5-sol Mars aggregation orbit. With the goal of minimizing technology investments for the initial surface sortie removing ISRU from the trade space, the MAV must now be landed either fully loaded with propellant, or with some portion of the propellant off-loaded. Landing a partially-fueled MAV will require additional surface assets to perform robotic propellant transfer on the surface of Mars from a pre-emplaced propellant depot. Furthermore, cryogenic fluid management and storage for extended duration with no losses represents additional technology investment that would have to be made to support cryogenic-based propellant concepts that have been the baseline in past architectures. As a result, the SAC21 architecture utilizes a storable propellant-based MAV propulsion system to minimize these potential technology investments incurred by cryogenic-based propulsion systems. Recent efforts also focused on evaluating the sensitivity of key design parameters, such as landing site latitude, elevation, and local atmospheric conditions. All play a large role in determining the predicted propellant requirements of the MAV. Understanding their potential impacts is important because of the rippling effects of changes to the MAV design on other architecture elements, such as entry, descent, landing, and transportation systems. Results indicate up to +2% to -4% wet mass variation due to landing site latitude, with higher latitudes greater than 70 degrees North resulting in greater than 6% wet mass increases. The MAV saw reduced impact due to atmospheric design parameters, which only accounting for -0.6% to +0.4% wet mass variation.

Douglas J. Trent↗

Hybrid integrated optic modules for real-time signal processing

The most recent progress on four relatively new hybrid integrated optic device modules in LiNbO3 waveguides and one in YIG/GGG waveguide that are currently being studied are discussed. The five hybrid modules include a time-integrating acoustooptic correlator, a channel waveguide acoustooptic frequency shifter/modulator, an electrooptic channel waveguide total internal reflection moculator/switch, an electrooptic analog-to-digital converter using a Fabry-Perot modulator array, and a noncollinear magnetooptic modulator using magnetostatic surface waves. All of these devices possess the desirable characteristics of very large bandwidth (GHz or higher), very small substrate size along the optical path (typically 1.5 cm or less), single-mode optical propagation, and low drive power requirement. The devices utilize either acoustooptic, electrooptic or magnetooptic effects in planar or channel waveguides and, therefore, act as efficient interface devices between a light wave and temporal signals. Major areas of application lie in wideband multichannel optical real-time signal processing and communications. Some of the specific applications include spectral analysis and correlation of radio frequency (RF) signals, fiber-optic sensing, optical computing and multiport switching/routing, and analog-to-digital conversion of wide RF signals.

Tsai, C. S.↗

Development of Reliable Life Support Systems

The life support systems on the International Space Station (ISS) are the culmination of an extensive effort encompassing development, design, and test to provide the highest possible confidence in their operation on ISS. Many years of development testing are initially performed to identify the optimum technology and the optimum operational approach. The success of this development program depends on the accuracy of the system interfaces. The critical interfaces include the specific operational environment, the composition of the waste stream to be processed and the quality of the product. Once the development program is complete, a detailed system schematic is built based on the specific design requirements, followed by component procurement, assembly, and acceptance testing. A successful acceptance test again depends on accurately simulating the anticipated environment on ISS. The ISS Water Recovery System (WRS) provides an excellent example of where this process worked, as well as lessons learned that can be applied to the success of future missions. More importantly, ISS has provided a test bed to identify these design issues. Mechanical design issues have included an unreliable harmonic drive train in the Urine Processor's fluids pump, and seals in the Water Processor's Catalytic Reactor with insufficient life at the operational temperature. Systems issues have included elevated calcium in crew urine (due to microgravity effect) that resulted in precipitation at the desired water recovery rate, and the presence of an organosilicon compound (dimethylsilanediol) in the condensate that is not well removed by the water treatment process. Modifications to the WRS to address these issues are either complete (and now being evaluated on ISS) or are currently in work to insure the WRS has the required reliability before embarking on a mission to Mars.

Carter, Layne↗

Development of Reliable Life Support Systems

The life support systems on the International Space Station (ISS) are the culmination of an extensive effort encompassing development, design, and test to provide the highest possible confidence in their operation on ISS. Many years of development testing are initially performed to identify the optimum technology and the optimum operational approach. The success of this development program depends on the accuracy of the system interfaces. The critical interfaces include the specific operational environment, the composition of the waste stream to be processed and the quality of the product. Once the development program is complete, a detailed system schematic is built based on the specific design requirements, followed by component procurement, assembly, and acceptance testing. A successful acceptance test again depends on accurately simulating the anticipated environment on ISS. The ISS Water Recovery System (WRS) provides an excellent example of where this process worked, as well as lessons learned that can be applied to the success of future missions. More importantly, ISS has provided a test bed to identify these design issues. Mechanical design issues have included an unreliable harmonic drive train in the Urine Processor's fluids pump, and seals in the Water Processor's Catalytic Reactor with insufficient life at the operational temperature. Systems issues have included elevated calcium in crew urine (due to microgravity effect) that resulted in precipitation at the desired water recovery rate, and the presence of an organosilicon compound (dimethylsilanediol) in the condensate that is not well removed by the water treatment process. Modifications to the WRS to address these issues are either complete (and now being evaluated on ISS) or are currently in work to insure the WRS has the required reliability before embarking on a mission to Mars.

Carter, Layne↗

Driving Stresses in Mars Polar Ice Caps and Conditions for Ice Flow

Measurements of the topography of the North polar ice cap by the Mars Orbiter Laser Altimeter (MOLA) show that the ice cap is 2950 +/- 200 meters thick. The volume of the cap is about 1.2 x 10(exp 6) cu km covering an area of 1.04 x 10(exp 6) sq km, which is about 40 percent of the Greenland ice sheet in volume and 62 percent in area. The composition of the Northern cap was previously concluded to be predominately H2O, rather than CO2 ice, based on thermodynamic considerations of the insustainablity of CO2 during summer. Principal questions about the cap are: does the ice move and at what rate, is the cap currently growing or depleting in volume, and how and when was the cap formed? Recent research on terrestrial ice sheets indicates that rates of ice deformation at the low stress values characteristic of ice sheets are significantly higher than the rates given by the classic viscous-plastic flow laws commonly used.

Zwally, H. Jay↗

Airoscope command system

A PCM telemetry command system is presented having a capacity of 256 unique commands, an end-to-end actuation time of less than 250 milliseconds, and an address plus complementary command code to provide security against the acceptance of anything but intended commands. The system consists of a ground-based encoder and a balloon-borne decoder, both built using low-current drain, high reliability CMOS logic elements. Commands are normally issued by a simple switch closure to +5VDC on the appropriate input line, however as a backup mode, the 8-bit command may be entered manually on 8 toggle switches and executed via a SEND button. In any case, the command is then serialized into a PCM bit stream and sent via a P-Band radio link to the DECODER aloft. All 256 outputs from the DECODER are buffered through drivers and thus may be used to drive CMOS, TTL, or DTL logic.

Barrows, W.↗

A Method for Aircraft Concept Selection Using Multicriteria Interactive Genetic Algorithms

The problem of aircraft concept selection has become increasingly difficult in recent years as a result of a change from performance as the primary evaluation criteria of aircraft concepts to the current situation in which environmental effects, economics, and aesthetics must also be evaluated and considered in the earliest stages of the decision-making process. This has prompted a shift from design using historical data regression techniques for metric prediction to the use of physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to arbitrarily choose a sub-optimum baseline vehicle. These concept decisions such as the type of control surface scheme to use, though extremely important, are frequently made without sufficient understanding of their impact on the important system metrics because of a lack of computational resources or analysis tools. This paper describes a hybrid subjective/quantitative optimization method and its application to the concept selection of a Small Supersonic Transport. The method uses Genetic Algorithms to operate on a population of designs and promote improvement by varying more than sixty parameters governing the vehicle geometry, mission, and requirements. In addition to using computer codes for evaluation of quantitative criteria such as gross weight, expert input is also considered to account for criteria such as aeroelasticity or manufacturability which may be impossible or too computationally expensive to consider explicitly in the analysis. Results indicate that concepts resulting from the use of this method represent designs which are promising to both the computer and the analyst, and that a mapping between concepts and requirements that would not otherwise be apparent is revealed.

Buonanno, Michael↗

PRA and Conceptual Design

Once a project obtains approval, decision makers have to consider a variety of alternative paths for completing the project and meeting the project objectives. How decisions are made involves a variety of elements including: cost, experience, current technology, ideologies, politics, future needs and desires, capabilities, manpower, timing, available information, and for many ventures management needs to assess the elements of risk versus reward. The use of high level Probabilistic Risk Assessment (PRA) Models during conceptual design phases provides management with additional information during the decision making process regarding the risk potential for proposed operations and design prototypes. The methodology can be used as a tool to: 1) allow trade studies to compare alternatives based on risk, 2) determine which elements (equipment, process or operational parameters) drives the risk, and 3) provide information to mitigate or eliminate risks early in the conceptual design to lower costs. Creating system models using conceptual design proposals and generic key systems based on what is known today can provide an understanding of the magnitudes of proposed systems and operational risks and facilitates trade study comparisons early in the decision making process. Identifying the "best" way to achieve the desired results is difficult, and generally occurs based on limited information. PRA provides a tool for decision makers to explore how some decisions will affect risk before the project is committed to that path, which can ultimately save time and money.

DeMott, Diana↗

Risk Management for Dynamic Radioisotope Power Systems

The implementation of dynamic power conversion technology in Radioisotope Power Systems (RPS) for spaceflight has potential for improved specific power and efficiency, compared with existing Radioisotope Thermoelectric Generators (RTGs). This proposed expansion of current RPS technology necessitates a full exploration of the requirements, goals, and concerns related to risks in developing and deploying such systems. The nature of dynamic systems also presents a new set of challenges related to the presence of moving machinery not intrinsic to traditional RTG units. A general RPS risk management methodology is outlined, which is used to identify and assess the variables and operational scenarios introducing risk throughout the design, fabrication, and system integration processes. This paper will demonstrate how mission requirements for Dynamic RPS concepts (DRPS) drive decisions throughout the development process. This work will define the standard practices for decision making within the scope of the risks associated with DRPS hardware development and deployment in sensitive spacecraft near sensitive payloads. Examples of potential risk areas are analyzed for the proposed dynamic systems, and compared to those associated with traditional RTG technologies. This analysis shows the promise for DRPS systems to elevate and extend the capabilities for power systems used in future NASA missions.

Matthes, Christopher S. R.↗

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

Health Monitoring and Prognostics for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously approved and published information.

Systems Health Managent↗

Vapor/Mist Used to Lubricate Gears After Loss of Primary Lubrication System

Loss of lubrication in rotorcraft drive systems is a demanding requirement placed on drive system manufacturers. The drive system must operate for at least 30 minutes once the primary lubrication system has failed. This test is a military requirement that must be passed prior to certification of the aircraft. As new aircraft engines, operating at higher speeds, are fielded, the requirements for the drive system become increasingly more difficult. Also, the drive system must be lightweight, which minimizes the opportunity to use the gear bodies to absorb the tremendous amount of heating that takes place. In many cases, the amount of heat generated because of the high speed and load requires an emergency lubrication system that negatively impacts the aircraft's weight, complexity, and cost. A single mesh spur gear test rig is being used at the NASA Glenn Research Center to investigate possible emergency lubrication system improvements that will minimize the impact of having these systems onboard rotorcraft. A technique currently being investigated uses a vapor/mist system to lubricate the contacting surfaces after the primary lubrication system has been shut down. A number of tests were conducted in which the vapor/mist used the same lubricant as the primary system, but at a greatly reduced flow rate. Each test was initiated with the primary lubrication system operational and at steady-state conditions for a given speed and load. Then the primary lubrication system was shut down, and the vapor/mist lubrication system was initiated. An example of the tests conducted is shown in the figures. These preliminary tests have uncovered a mechanism that provides a lubricious, carbonaceous solid on the surface that actually reduces the surface temperature of the meshing gear teeth during operation. Surface analysis of the carbonaceous solid revealed it was graphitic. This mechanism is the synthetic lubricant "coking" on the active profile of the gears, which reduces the friction between the contacting gear surfaces. The level of load affects the onset of this mechanism: the higher the load, the sooner coking takes place. Future work will investigate several other factors that could improve the already promising results that have been attained.

Handschuh, Robert F.↗

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.↗