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NASA NTRS2015

Odyssey Mars Orbiter - Thirteen Years of On-Orbit Navigation

The Odyssey spacecraft has been in Mars orbit since October 24, 2001 and has nearly completed 61,490 orbits. Navigation operational objectives include the following: Control the local mean solar time for science observations; for most of the mission, this varied from 3:45 pm to 5:20 pm. Currently, an orbit trim maneuver planned for November 10, 2015 will place Odyssey at 6:45 pm/6:45 am at equator crossings in order to observe early morning ground frost, fog and clouds. Initially, Odyssey was late by 42 minutes for an over-flight of the critical seven minutes of Phoenix's entry, descent and landing (EDL). Odyssey was successfully positioned for this over-flight using the Delta V from angular momentum desaturations (AMD). Similar results for the Mars Science Laboratory's EDL and Comet Siding Spring's minimum risk location will be presented. Odyssey has and continues to relay significant quantities of rover data. Navigation successfully models frequent AMD Delta Vs in order to generate accurate sixty-day trajectory predictions; a typical timing error is 25 seconds after 60 days. However, unexpected events, such as safe-mode entries with their larger and more frequent thrusting, severely impact that trajectory accuracy. Impacted trajectories can have timing errors ranging from a few minutes to ten-to-fifteen minutes after sixty-days. Other analyses (briefly stated) include: a) the offset of the orbital ground track pattern after an initial cycle of 30 days or 362 orbits and b) an operations environment of continuous thrusting if/when one of the three remaining reaction wheels fails.

trajectory accuracy↗

NASA NTRS2017

CEDAR-GEM Challenge for Systematic Assessment of Ionosphere/Thermosphere Models in Predicting TEC During the 2006 December Storm Event

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered.

Shim, J. S.↗

NASA NTRS2020

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated - EDDI measures evaporative demand through potential evapotranspiration, and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks, and to implement the appropriate actions for preparation of drought onset.

Adelaide Schmid↗

NASA NTRS2020

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin Utilizing NASA Earth Observations

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated -EDDI measures evaporative demand through potential evapotranspiration, and and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks to implement the appropriate actions for preparation of drought onset.

DEVELOP Project Summary↗

NASA NTRS2021

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗

NASA NTRS2021

Satellite imaging reveals increased proportion of population exposed to floods

Flooding affects more people than any other environmental hazard and hinders sustainable development. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods. Where and how floods occur and who is exposed are changing as a result of rapid urbanization4, flood mitigation infrastructure and increasing settlements in floodplains6. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255–290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58–86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods.

B.Tellman↗

NASA NTRS1987

A multispacecraft study of the injection and transport of solar energetic particles

The November 22, 1977 and December 27, 1977 solar energetic particle (SEP) events observed simultaneously by the Helios and the Voyager space probes and the ISEE 1 satellite are described. The spacecraft instruments indicated flux increases for H, He, and (for November 22) for O and Fe, with the energy range of 0.5-20 MeV per nucleon. It was found that the data can be well fitted by a model based on the spherically symmetric Fokker-Planck equation including convection, diffusion, and adiabatic deceleration, assuming that the radial interplanetary diffusion coefficient increases in proportion to the heliocentric radius to the power of 0.6 and that there is an extended particle injection at the sun. This extended injection is of crucial importance for the event of November 22, where the injection functions are strongly dependent on times associated with a soft energy spectrum.

Beeck, J.↗

NASA NTRSDate not supplied

An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms

A surrogate artificial neural network/machine learning model was developed to predict the acoustic interaction for a fixed-pitch rotor in proximity to a downstream cylindrical airframe typical of small Unmanned Aerial System (sUAS) platforms. The model was trained to predict the acoustic waveform under representative hover conditions as a function of rotational speed, airframe proximity, and observer angle. Training data were acquired in an anechoic chamber on both isolated rotors and rotor-airframe configurations. Acoustic amplitude and phase of the revolution-averaged interaction were predicted, which required up to 25 harmonics to capture the impulse event caused by the blade’s approach and departure from the airframe. Prediction performance showed, on average, that the models could estimate the acoustic amplitude and phase over the relevant harmonics for unseen conditions with 86% and 75% accuracy, respectively, enabling a time domain reconstruction of the waveform for the range of geometric and flow parameters tested.

acoustics↗

NASA NTRSDate not supplied

An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms

acoustics↗

NASA NTRS2010

The Relationship of Magnetotail Flow Bursts and Ground Onset Signatures

It has been known for decades that auroral substorm onset occurs on (or at least near) the most equatorward auroral arc, which is thought to map to the near geosynchronous region. The lack of auroral signatures poleward of this arc prior to onset has been a major criticism of flow-burst driven models of substorm onset. The combined THEMIS 5 spacecraft in-situ and ground array measurements provide an unprecedented opportunity to examine the causal relationship between midtail plasma flows, aurora, and ground magnetic signatures. I first present an event from 2008 using multi-spectral all sky imager data from Gillam and in-situ data from THEMIS. The multispectral data indicate an equatorward moving auroral form prior to substorm onset. When this forms reaches the most equatorward arc, the arc brightens and an auroral substorm begins. The THEMIS data show fast Earthward flows prior to onset as well. I discuss further the association of flow bursts and Pi2 pulsations, in the con text of the directly-driven Pi2 model. This model directly links flows and Pi2 pulsations, providing an important constraint on substorm onset theories.

Kepko, Larry↗

NASA NTRS2002

CEM2k and LAQGSM Codes as Event-Generators for Space Radiation Shield and Cosmic Rays Propagation Applications

Space radiation shield applications and studies of cosmic ray propagation in the Galaxy require reliable cross sections to calculate spectra of secondary particles and yields of the isotopes produced in nuclear reactions induced both by particles and nuclei at energies from threshold to hundreds of GeV per nucleon. Since the data often exist in a very limited energy range or sometimes not at all, the only way to obtain an estimate of the production cross sections is to use theoretical models and codes. Recently, we have developed improved versions of the Cascade-Exciton Model (CEM) of nuclear reactions: the codes CEM97 and CEM2k for description of particle-nucleus reactions at energies up to about 5 GeV. In addition, we have developed a LANL version of the Quark-Gluon String Model (LAQGSM) to describe reactions induced both by particles and nuclei at energies up to hundreds of GeVhucleon. We have tested and benchmarked the CEM and LAQGSM codes against a large variety of experimental data and have compared their results with predictions by other currently available models and codes. Our benchmarks show that CEM and LAQGSM codes have predictive powers no worse than other currently used codes and describe many reactions better than other codes; therefore both our codes can be used as reliable event-generators for space radiation shield and cosmic ray propagation applications. The CEM2k code is being incorporated into the transport code MCNPX (and several other transport codes), and we plan to incorporate LAQGSM into MCNPX in the near future. Here, we present the current status of the CEM2k and LAQGSM codes, and show results and applications to studies of cosmic ray propagation in the Galaxy.

Mashnik, S. G.↗

NASA NTRSDate not supplied

NAIRAS Model Nowcasting and Forecasting of the Aviation Radiation Environment

The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) predicts dosimetric quantities for quantifying human radiation exposure and differential/integral flux/fluence quantities for assessing single event effects (SEE) in avionic systems from galactic cosmic rays (GCR), trapped inner belt protons, and solar energetic particle (SEP) events from the Earth’s surface to the space environment. Real-time predictions of the aviation radiation environment are available at NASA Goddard Space Flight Center’s Community Coordinated Modeling Center (CCMC) integrated Space Weather Analysis (iSWA) data feeds and cygnets, and a run-on-request (RoR) capability has also been deployed at CCMC. Recent model improvements include a more accurate atmospheric ionizing radiation transport methodology and more robust and reliable SEP nowcast dose predictions. In addition, preliminary results of SEP dose forecasts are shown by coupling the University of Malaga Solar Energetic Particle (UMASEP) model of integral proton flux forecasts with the NAIRAS model. These model updates and improvements are presented, and results are shown for aircraft, high-latitude balloon, and low-Earth orbit flights during quiescent and solar-geomagnetic disturbed conditions. Model comparisons with flight measurements are also shown.

NAIRAS↗

NASA NTRS2010

Impact of Atmospheric Infrared Sounder (AIRS) Thermodynamic Profiles on Regional Precipitation Forecasting

In data sparse regions, remotely-sensed observations can be used to improve analyses and lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles in clear and cloudy regions with accuracy which approaches that of radiosondes. The purpose of this paper is to describe an approach to assimilate AIRS thermodynamic profile data into a regional configuration of the Advanced Research WRF (ARW) model using WRF-Var. Quality indicators are used to select only the highest quality temperature and moisture profiles for assimilation in clear and partly cloudy regions, and uncontaminated portions of retrievals above clouds in overcast regions. Separate error characteristics for land and water profiles are also used in the assimilation process. Assimilation results indicate that AIRS profiles produce an analysis closer to in situ observations than the background field. Forecasts from a 37-day case study period in the winter of 2007 show that AIRS profile data can lead to improvements in 6-h cumulative precipitation forecasts resulting from improved thermodynamic fields. Additionally, in a convective heavy rainfall event from February 2007, assimilation of AIRS profiles produces a more unstable boundary layer resulting in enhanced updrafts in the model. These updrafts produce a squall line and precipitation totals that more closely reflect ground-based observations than a no AIRS control forecast. The location of available high-quality AIRS profiles ahead of approaching storm systems is found to be of paramount importance to the amount of impact the observations will have on the resulting forecasts.

Chou, S.-H.↗

NASA NTRS2004

Characteristics of Heavy Summer Rainfall in Southwestern Taiwan in Relation to Orographic Effects

On the windward side of southwestern Taiwan, about a quarter to a half of all rainfall during mid-July through August from 1994 to 2000 came from convective systems embedded in the southwesterly monsoon flow. k this study, the causes of two heavy rainfall events (daily rainfall exceeding 100 mm day over at least three rainfall stations) observed over the slopes and/or lowlands of southwestern Taiwan were examined. Data from European Center for Medium-Range Weather Forecasts /Tropical Ocean- Global Atmosphere (EC/TOGA) analyses, the rainfall stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) and the conventional surface stations over Taiwan, and the simulation results from a regional-scale numerical model were used to accomplish the objectives. In one event (393 mm day on 9 August 1999), heavy rainfall was observed over the windward slopes of southern Taiwan in a potentially unstable environment with very humid air around 850 hPa. The extreme accumulation was simulated and attributed to orographic lifting effects. No preexisting convection drifted in from the Taiwan Strait into western Taiwan.

Chen, Ching-Sen↗

NASA NTRS1998

Using Global Simulations of the Magnetosphere for Multi-Satellite Mission Planning and Data Analysis

We use global simulations of Earth's magnetosphere to assess the scientific return from a multi-satellite mission in the magnetosphere. We examine 4 different scenarios with 20, 40, 80, and 160 satellites, respectively. The satellite orbits are randomized with perigee distances ranging from 2 to 5R(sub E), apogee distances between 10 and 50 R(sub E), and within +/-5R(sub E) of the geocentric solar ecliptic (GSE) equator. For each of these satellite configurations we examine the expected observations during a typical substorm by using time traces obtained from a global simulation at the satellite positions. The 160 satellite configuration yields sufficient information to distinguish between different substorm models without any temporal/spatial ambiguities. An 80 satellite configuration still provides sufficient information for this task, however for fewer events with good satellite conjunctions and with less statistical certainty. For constellations with fewer than 40 satellites time-space ambiguities are likely to remain in the observation. However, any multi-satellite constellation would be a quantum leap in magnetospheric research because of the unprecedented coverage of other regions, because it would enable new measurement techniques that are unique to multi-satellite missions, and because it would enable the use of data assimilation techniques in global models for the first time.

Raeder, Joachim↗

NASA NTRS1999

Climatic Variability of Precipitation from the Seasonal Cycle to ENSO Using GPCP's Merged Data Product and SSM/I-Based Microwave Estimates

Satellite estimates and gauge observations of precipitation are useful in understanding the water cycle, analyzing climatic variability, and validating climate models. The Global Precipitation Climatology Project (GPCP) released a community merged precipitation data set for the period July 1987 through the present, and has recently extended that data set back to 1986. One objective of this study is to use GPCP estimates to describe and quantify the seasonal variation of precipitation, with emphasis on the Asian summer monsoon. Another focus is the 1997-98 El Nino Southern Oscillation (ENSO) and associated extreme precipitation events. The summer monsoon tends to be drier than normal in El Nino ears. This was not observed for 1997 or 1998, while for 1997 the NCEP model produced the largest summer rain rates over India in years. This inconsistency will be examined. The average annual global precipitation rate is 2.7 mm day as estimated by GPCP, which is similar to values computed from long-term climatologies. From 30 deg N to 30 deg S the average precipitation rate is 2.7 mm day over land with a maximum in the annual cycle occurring in February-March, when the Amazon basin receives abundant rainfall. The average precipitation rate is 3.1 mm day over the tropical oceans, with a peak earlier in the season (November-December), corresponding with the transition from a strong Pacific Intertropical Convergence Zone (ITCZ) from June to November to a strong South Pacific Convergence Zone (SPCZ) from December to March. The seasonal evolution of C, C, the Asian summer monsoon stands out with rains in excess of 15 mm day off the coast of Burma in June. The GPROF pentad data also captures the onset of the tropical Pacific rainfall patterns associated with the 1997-98 ENSO. From February to October 1997 at least four rain-producing systems traveled from West to East in the equatorial corridor. A rapid transition from El Nino to La Nina conditions occurred in May-June 1998. GPCP and GPROF were used to construct precipitation-based ENSO indices to monitor El Ninos (EL) and La Ninas and (LI).

Curtis, Scott↗

NASA NTRS1996

Crack Development in Cross-Ply Laminates Under Uniaxial Tension

This study addresses matrix-dominated failures in carbon fiber/polymer matrix composite laminates in a cross-ply lay-up. The events of interest are interlaminar fracture in the form of transverse cracks in the 90' plies and longitudinal splitting in the 0 deg plies and interlaminar fracture in the form of 0/90 delamination. These events were observed using various nondestructive evaluation (NDE) techniques during static tensile tests. Acoustic emission (AE) x radiography, and edge view microscopy were the principal ones utilized in a real-time environment. A comparison of the NDE results with an analytical model based on the classical linear fracture mechanics concept of strain energy release rate as a criterion for crack growth was performed. The virtual crack closure theory was incorporated with a finite element model to generate strain energy release rate curves for the analytical case. Celion carbon fiber/polyimide matrix (G30-500/PMR-15) was the material tested with cross-ply lay-ups of (0(2)/90(6))s and (0(4)/90(4))s. The test specimens contained thermally induced cracks caused by the high-temperature processing. The analytical model was updated to compensate for the initial damage and to study further accumulation by taking into account the crack interactions. By correlating the experimental and analytical data, the critical energy release rates were found for the observable events of interest.

Gyekenyesi, Andrew L.↗

NASA NTRS2021

Northern Great Plains Disasters: Using Earth Observations to Enhance Flood Monitoring on Tribal Lands in the Northern Great Plains

In 2019, the Great Plains experienced unprecedented catastrophic flooding. Large flood events are predicted to increase in frequency and severity, posing risks to communities in this region, particularly Tribal Nations. We used data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), imagery from the Sentinel-2 MultiSpectral Instrument (MSI), and digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM) within Google Earth Engine to map historical floods in the region beginning in 2014 with particular attention to the Rosebud Sioux Reservation and the tribal lands of other Great Plains Tribal Water Alliance members. This historical mapping used C-SAR for a combined method approach with a Z-score algorithm in addition to an index for flooded short vegetation. We also developed a flood risk map by weighting different flood predictor variables according to flood risk literature. These variables included soil drainage from the Soil Survey Geographic Database (SSURGO); elevation, slope, and Topographic Wetness Index (TWI) derived from digital elevation models; precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS); land cover from the National Land Cover Database (NLDC); and Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 Operational Land Imager (OLI). From the flood extent and risk maps, we identified widespread flooding in short vegetation (including cropland) and noted flood susceptibility in regions exhibiting high social vulnerability and low community resilience (FEMA indices). We created an ArcGIS Online StoryMap to share project background, results, and data. Additionally, we provided a written tutorial so partners may replicate the flood mapping for future flood events.

Anna Ballasiotes↗