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NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS1977

Chemical character of the partially flooded Smythii Basin based on Al/Si orbital X-ray data

Orbital X-ray fluorescence data indicate that continuous mare-basalt flooding is confined to the northeastern quadrant of the Smythii Basin. Al/Si values for soils in the unflooded northwestern section of the Smythii Basin closely approximate those for the adjacent terra to the west. Terra soils east of Mare Smythii, however, are unusually aluminous compared to terra soils west of the basin. This pronounced contrast between Al/Si values for terra soils to the east and west of Smythii as well as the minimal difference in values between the northwestern section of the basin and adjacent terra to the west are most likely due to a chemically homogeneous layer of ejecta from a large impact event west of Mare Smythii, such as that which formed the Crisium Basin. An alternate hypothesis is that the unflooded section of the basin is predominantly original basin floor material, indicating that the impact forming the 4km deep Smythii Basin did not penetrate into a horizon chemically different from the terra west of Smythii. The chemical contrast between the terra east and west of Smythii, then, would be ascribed to lateral heterogeneity within the lunar crust

Andre, C. G.↗
NASA NTRS1990

Lunar Polar Coring Lander

Plans to build a lunar base are presently being studied with a number of considerations. One of the most important considerations is qualifying the presence of water on the Moon. The existence of water on the Moon implies that future lunar settlements may be able to use this resource to produce things such as drinking water and rocket fuel. Due to the very high cost of transporting these materials to the Moon, in situ production could save billions of dollars in operating costs of the lunar base. Scientists have suggested that the polar regions of the Moon may contain some amounts of water ice in the regolith. Six possible mission scenarios are suggested which would allow lunar polar soil samples to be collected for analysis. The options presented are: remote sensing satellite, two unmanned robotic lunar coring missions (one is a sample return and one is a data return only), two combined manned and robotic polar coring missions, and one fully manned core retrieval mission. One of the combined manned and robotic missions has been singled out for detailed analysis. This mission proposes sending at least three unmanned robotic landers to the lunar pole to take core samples as deep as 15 meters. Upon successful completion of the coring operations, a manned mission would be sent to retrieve the samples and perform extensive experiments of the polar region. Man's first step in returning to the Moon is recommended to investigate the issue of lunar polar water. The potential benefits of lunar water more than warrant sending either astronauts, robots or both to the Moon before any permanent facility is constructed.

Angell, David↗
NASA NTRS2022

Mars Terrain Segmentation with Less Labels

Planetary rover systems need to perform terrain segmentation to identify drivable areas as well as identify specific types of soil for sample collection. The latest Martian terrain segmentation methods rely on supervised learning which is very data hungry and difficult to train where only a small number of labeled samples are available. Moreover, the semantic classes are defined differently for different applications (e.g., rover traversal vs. geological) and as a result the network has to be trained from scratch each time, which is an inefficient use of resources. This research proposes a semi-supervised learning framework for Mars terrain segmentation where a deep segmentation network trained in an unsupervised manner on unlabeled images is transferred to the task of terrain segmentation trained on few labeled images. The network incorporates a backbone module which is trained using a contrastive loss function and an output atrous convolution module which is trained using a pixel-wise cross-entropy loss function. Evaluation results using the metric of segmentation accuracy show that the proposed method with contrastive pre-training outperforms plain supervised learning by 2%-10%. Moreover, the proposed model is able to achieve a segmentation accuracy of 91.1% using only 161 training images (1% of the original dataset) compared to 81.9% with plain supervised learning.

Wilson, Brian D↗
NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗
NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗
NASA NTRS1982

The Apollo 15 regolith - Comparative petrology of drive tube 15010/15011 and drill core section 15003

Two Apollo 15 regolith cores - double drive-tube 15010/15011 and deep drill core section 15003 - were compared. The drive tube was taken from near the edge of Hadley Rille within the mare region and the drill core was taken from the landing site, approximately the same distance as the drive tube from the Apennine Front. Optical modes were done on the two cores, each of which was divided into three stratigraphic units defined by minor differences in grain size and modal abundances. Electron microprobe data were collected on the mineral and glass fragments within each unit. Fused-soil-free bulk chemistries were calculated for each unit by modal recombination, using our modal data and average compositional and density data for soil components. It is found that the drive tube and drill core section are fairly homogeneous units both chemically and modally. Both soils are submature to immature. There are, however, significant differences between the cores. The drill core shows significant enrichments of highland lithic-fragments and highland-derived minerals and glasses relative to the drive tube. These differences are attributed to the fresh nature of the drive tube soil whose major source material is mare basalt ejecta from the shallow bedrock.

Walker, R. J.↗
NASA NTRS2000

Mechanical Abrasion as a Low Cost Technique for Contamination-Free Sample Acquisition from a Category IVA Clean Platform

The proposed Mars Sample Transfer Chain Architecture provides Planetary Protection Officers with clean samples that are required for the eventual release from confinement of the returned Martian samples. At the same time, absolute cleanliness and sterility requirement is not placed of any part of the Lander (including the deep drill), Mars Assent Vehicle (MAV), any part of the Orbiting Sample container (OS), Rover mobility platform, any part of the Minicorer, Robotic arm (including instrument sensors), and most of the caching equipment on the Rover. The removal of the strict requirements in excess of the Category IVa cleanliness (Pathfinder clean) is expected to lead to significant cost savings. The proposed architecture assumes that crosscontamination renders all surfaces in the vicinity of the rover(s) and the lander(s) contaminated. Thus, no accessible surface of Martian rocks and soil is Earth contamination free. As a result of the latter, only subsurface samples (either rock or soil) can be and will be collected for eventual return to Earth. Uncontaminated samples can be collected from a Category IVa clean platform. Both subsurface soil and rock samples can be maintained clean if they are collected by devices that are self-contained and clean and sterile inside only. The top layer of the sample is removed in a manner that does not contaminate the collection tools. Biobarrier (e.g., aluminum foil) covering the moving parts of these devices may be used as the only self removing bio-blanket that is required. The samples never leave the collection tools. The lids are placed on these tools inside the collection device. These single use tools with the lid and the sample inside are brought to Earth in the OS. The lids have to be designed impenetrable to the Earth organisms. The latter is a well established art.

Dolgin, B.↗
NASA NTRS2021

High Performance, Web-Based, Real-Time Telemetry Visualization for Deep Space Mission Support and Operations

The Jet Propulsion Laboratory’s Mission ControlSystems Section and Mobility and Robotic Systems Section havepartnered to developed a high-performance telemetry visualizationsystem, based on our mature, web-based, 3D visualizationsoftware technology, that provides mission trajectory designers,operations personnel and reconstruction analysts with a highlyaccurate, re-usable, multi-mission solution to interactively visualizeresults from Entry, Descent and Landing (EDL) simulations,real-time mission test beds, live telemetry streams during criticalmission events, such as landing, as well as post-event reconstructionanalysis. This work builds on previous mission visualizationsystems that we have deployed for a variety of flight missions andJPL organizations including NASA’s Mars Science Laboratory(MSL), NASA’S Low Density Supersonic Decelerator (LDSD),NASA’s Soil Moisture Active Passive (SMAP), JPL’s MoonRiseLunar sample return proposal. JPL’s mission design teams, JPL’sOffice of Naval Research tasks, and JPL’s Education and PublicOutreach Office.

Wenzel, Sean↗
NASA NTRS1990

Geology, geohydrology, and soils of NASA, Kennedy Space Center: A review

Sediments underlying Kennedy Space Center (KSC) have accumulated in alternating periods of deposition and erosion since the Eocene. Surface sediments are of Pleistocene and Recent ages. Fluctuating sea levels with the alternating glacial-interglacial cycles have shaped the formation of the barrier island. Merritt Island is an older landscape whose formation may have begun as much as 240,000 years ago, although most of the surface sediments are not that old. Cape Canaveral probably dates from less than 7,000 years B.P. (before present) as does the barrier strip separating Mosquito Lagoon from the Atlantic Ocean. Merritt Island and Cape Canaveral have been shaped by progradational processes but not continuously so, while the Mosquito Lagoon barrier has been migrating landward. Deep acquifers beneath KSC are recharged inland but are highly mineralized in the coastal region and interact little with surface vegetation. The Surficial acquifer has formed in the Pleistocene and Recent deposits and is recharged by local rainfall. Sand ridges in the center of Merritt Island are important to its recharge.

Schmalzer, Paul A.↗
NASA NTRS2015

Exploring Our Solar System with CubeSats and NanoSats

The Jet Propulsion Laboratory (JPL) is NASA's lead center for robotic exploration of our solar system. We are known for our large, flagship missions, such as Voyager, which gave humanity its first close look at Jupiter and Saturn; and the Mars Rovers, which have excited millions worldwide with their daring landing exploits. Less familiar to those outside NASA may be our role in developing the Kepler mission, which has discovered more than 2000 planets around other stars; or the recently launched Soil Moisture Active Passive (SMAP) mission, one of many JPL Earth Science missions. A recent JPL initiative has emphasized low cost missions that use rapidly evolving technology developed for CubeSats and NanoSat s to explore our solar system. Costs are significantly lower (by one or two orders of magnitude) than for conventional JPL missions, and development time is also significantly shorter. At present 21 such CubeSat flight projects are under way at the laboratory with various partners : some in flight, some in development, some in advanced formulation. Four are planned as deep space missions. To succeed in exploring deep space CubeSat/NanoSat missions have to address several challenges: the more severe radiation environment, communications and navigation at a distance, propulsion, and packaging of instruments that can return valuable science into a compact volume/mass envelope. Instrument technologies, including cameras, magnetometers, spectrometers, radiometers, and even radars are undergoing miniaturization to fit on these smaller platforms. Other key technologies are being matured for smallsats and NanoSats in deep space, including micro -electric propulsion, compact radio (and optical) communications, and onboard data reduction. This paper will describe missions that utilize these developments including the first two deep space CubeSats (INSPIRE), planned for launch in 2017; the first pair of CubeSats to be sent to another planet (MARCO), manifested with the InSight Mars lander launch in March of 2016; a helicopter "drone" on Mars to extend the reach of future rovers; plans for a Lunar Flashlight mission to shine a light on the permanently shadowed craters of the Moon's poles; a Near Earth Asteroid CubeSat missio n; and a CubeSat constellation to demonstrate time series measurements of storm systems on Earth. From these beginnings, the potential for CubeSats and NanoSats to add to our knowledge of the solar system could easily grow exponentially. Imagine if every deep space mission carried one or more CubeSats that could operate independently (even for a brief period) on arrival at their target body. At only incremental additional cost, such spacecraft could go closer, probe deeper, and provide science measurements that we would not risk with the host spacecraft. This paper will describe examples including a NanoSat to probe the composition of Venus' atmosphere, impactors and close flybys of Europa, lunar probes, and soft landers for the moons of Mars. Low cost access to deep space also offers the potential for independent CubeSat/NanoSat missions - allowing us to characterize the population of near Earth asteroids for example, deploy a constellation around Venus, or take closer looks at the asteroid belt.

Deep Space↗
NASA NTRS2012

The Search for Life on Mars

For centuries, the planet Mars has been regarded as a possible abode for life. Serious searches for the signatures of life began in the 19th century, and continue via telescopic investigations and landed missions. While early work focused on phenomenology and bordered on fantasy, modern scientific inquiry has emphasized the search for chemical signatures of life in the soil and rocks at the planet's surface, and the search for biomarker gases in the atmosphere. Living systems produce more than 90% of Earth's atmospheric methane; the balance is of geochemical origin. The discovery of methane on Mars will be described, along with the ongoing extended search for clues to its origins. The possible origins of Mars methane will be discussed in the context of terrestrial analogue sites where geologic and biologic methane production now occurs - ranging from sub-permafrost zones in the arctic to hydrothermal vents in the deep ocean. Terrestrial organisms that could prosper on Mars today will be mentioned. I will briefly touch upon experiments conducted by landed spacecraft, ranging from the Viking Life Science Experiments in 1976 to the impending Mars Science laboratory, and the Trace Gas Orbiter and ExoMars missions now being developed for flight in the coming decade.

Mumma, Michael J.↗
NASA NTRS2014

The Impacts of Microphysics and Planetary Boundary Layer Physics on Model Simulations of U.S. Deep South Summer Convection

Convection-allowing numerical weather simula- tions have often been shown to produce convective storms that have significant sensitivity to choices of model physical parameterizations. Among the most important of these sensitivities are those related to cloud microphysics, but planetary boundary layer parameterizations also have a significant impact on the evolution of the convection. Aspects of the simulated convection that display sensitivity to these physics schemes include updraft size and intensity, simulated radar reflectivity, timing and placement of storm initi- ation and decay, total storm rainfall, and other storm features derived from storm structure and hydrometeor fields, such as predicted lightning flash rates. In addition to the basic parameters listed above, the simulated storms may also exhibit sensitivity to im- posed initial conditions, such as the fields of soil temper- ature and moisture, vegetation cover and health, and sea and lake water surface temperatures. Some of these sensitivities may rival those of the basic physics sensi- tivities mentioned earlier. These sensitivities have the potential to disrupt the accuracy of short-term forecast simulations of convective storms, and thereby pose sig- nificant difficulties for weather forecasters. To make a systematic study of the quantitative impacts of each of these sensitivities, a matrix of simulations has been performed using all combinations of eight separate microphysics schemes, three boundary layer schemes, and two sets of initial conditions. The first version of initial conditions consists of the default data from large-scale operational model fields, while the second features specialized higher- resolution soil conditions, vegetation conditions and water surface temperatures derived from datasets created at NASA's Short-term Prediction and Operational Research Tran- sition (SPoRT) Center at the National Space Science and Technology Center (NSSTC) in Huntsville, AL. Simulations as outlined above, each 48 in number, were conducted for five midsummer weakly sheared coastal convective events each at two sites, Mobile, AL (MOB) and Houston, TX (HGX). Of special interest to operational forecasters at MOB and HGX were accuracy of timing and placement of convective storm initiation, reflectivity magnitudes and coverage, rainfall and inferred lightning threat.

McCaul, Eugene W., Jr.↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRS2018

A Multi-Satellite Assimilation and Modeling Platform to Construct a Global and Complete view of the Hydrologic Cycle

What captivates me about the research field of satellite remote sensing of the earth system science is the opportunity to help human beings by addressing challenging questions related to the current and future availability of natural resources for domestic, agricultural, and industrial needs. For example, a continuously varying climate poses a threat to the water resource, not only in developing countries, but also in economically well-developed regions, creating the urgent need to characterize and predict its spatial and temporal availability. Specifically, my curiosity is driven by the challenge of merging cutting-edge space technology and earth observations (i.e., remote sensing) with state-of-the-art models for the purpose of improving our scientific knowledge about the variability and the change of the hydrologic cycle.The only practical way to observe the land surface processes (e.g., hydrologic cycle) on continental to global scales is via satellite remote sensing. Though remote sensing can make spatially comprehensive measurements of various components of the land surface system, it cannot provide direct information on the entire system, and the measurements represent only a snapshot in time. Physical based models may be used to continuously predict the temporal and spatial earth processes, but these predictions are often poor, due to model initialization, parameter and meteorological forcing errors, and inadequate model physics and/or resolution. Thus, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses of both) to provide a superior land surface state estimate. This is the goal of land surface data assimilation. Data assimilation provides a better estimate of the environmental states than either models or observations could individually do. The broad concept of data assimilation can be applied to various disciplines such as hydrology, ecology, environmental hazards, agriculture and economy.My research is targeted to integrating multiple satellite information having multi-sensor and multi-resolution assimilation within today's state-of-the-art hydrologic models. Multi-sensor and multi-resolution assimilation techniques represent a necessary milestone in future earth science applications because they offer the capability of comprehensively integrating disparate types of earth observations via deep-learning techniques. A multi-satellite assimilation and modeling platform will ultimately provide a robust and complete dataset to more fully understand earth's dynamics. In fact, the multi-satellite assimilation platforms build a comprehensive description of the earth processes that is geared toward accurately representing the complexity of natural and anthropogenic interactions in land surface processes. Most importantly, these platforms are suitable as decision support tools for applications across different aspects of earth system science.My recent work has focused on recent multi-sensor data assimilation techniques targeted at improving snow, soil moisture, groundwater, and terrestrial water storage hydrological states.

Girotto, Manuela↗
NASA NTRS1980

Solar flare and galactic cosmic ray tracks in lunar samples and meteorites - What they tell us about the ancient sun

Evidence regarding the past activity of the sun in the form of nuclear particle tracks in lunar samples and meteorites produced by heavy ions in galactic cosmic rays and solar flares is reviewed. Observations of track-rich grains found in deep lunar cores and meteorite interiors are discussed which demonstrate the presence of solar flare activity for at least the past 4 billion years, and the similarity of track density profiles from various lunar and meteoritic samples with those in a glass filter from Surveyor 3 exposed at the lunar surface for almost three years is presented as evidence of the relative constancy of the solar flare energy spectrum over the same period. Indications of a heavy ion enrichment in solar flares are considered which are confirmed by recent satellite measurements, although difficult to quantify in lunar soil grains. Finally, it is argued that, despite previous claims, there exists as yet no conclusive evidence for either a higher solar activity during the early history of the moon or a change in galactic cosmic ray intensity, average composition or spectrum over the last 50 million years.

Crozaz, G.↗