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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

The Influence of Roughness on Gear Surface Fatigue

Gear working surfaces are subjected to repeated rolling and sliding contacts, and often designs require loads sufficient to cause eventual fatigue of the surface. This research provides experimental data and analytical tools to further the understanding of the causal relationship of gear surface roughness to surface fatigue. The research included evaluations and developments of statistical tools for gear fatigue data, experimental evaluation of the surface fatigue lives of superfinished gears with a near-mirror quality, and evaluations of the experiments by analytical methods and surface inspections. Alternative statistical methods were evaluated using Monte Carlo studies leading to a final recommendation to describe gear fatigue data using a Weibull distribution, maximum likelihood estimates of shape and scale parameters, and a presumed zero-valued location parameter. A new method was developed for comparing two datasets by extending the current methods of likelihood-ratio based statistics. The surface fatigue lives of superfinished gears were evaluated by carefully controlled experiments, and it is shown conclusively that superfinishing of gears can provide for significantly greater lives relative to ground gears. The measured life improvement was approximately a factor of five. To assist with application of this finding to products, the experimental condition was evaluated. The fatigue life results were expressed in terms of specific film thickness and shown to be consistent with bearing data. Elastohydrodynamic and stress analyses were completed to relate the stress condition to fatigue. Smooth-surface models do not adequately explain the improved fatigue lives. Based on analyses using a rough surface model, it is concluded that the improved fatigue lives of superfinished gears is due to a reduced rate of near-surface micropitting fatigue processes, not due to any reduced rate of spalling (sub-surface) fatigue processes. To complete the evaluations, surface inspection were completed. The surface topographies of the ground gears changed substantially due to running, but the topographies of the superfinished gears were essentially unchanged with running.

Krantz, Timothy↗
NASA NTRS2019

Uncertainties in Evapotranspiration Estimates over West Africa

An evapotranspiration (ET) ensemble composed of 36 land surface model (LSM) experiments and four diagnostic datasets (GLEAM, ALEXI, MOD16, and FLUXNET) is used to investigate uncertainties in ET estimate over five climate regions in West Africa. Diagnostic ET datasets show lower uncertainty estimates and smaller seasonal variations than the LSM-based ET values, particularly in the humid climate regions. Overall, the impact of the choice of LSMs and meteorological forcing datasets on the modeled ET rates increases from north to south. The LSM formulations and parameters have the largest impact on ET in humid regions, contributing to 90% of the ET uncertainty estimates. Precipitation contributes to the ET uncertainty primarily in arid regions. The LSM-based ET estimates are sensitive to the uncertainty of net radiation in arid region and precipitation in humid region. This study serves as support for better determining water availability for agriculture and livelihoods in Africa with earth observations and land surface models.

land surface model↗
NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗
NASA NTRS1994

A simple hydrologically based model of land surface water and energy fluxes for general circulation models

A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment (FIFE) intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.

Liang, XU↗
NASA NTRS2020

Impact of Surface Albedo Assimilation on Snow Estimation

Surface albedo has a significant impact in determining the amount of available net radiation at the surface and the evolution of surface water and energy budget components. The snow accumulation and timing of melt, in particular, are directly impacted by the changes in land surface albedo. This study presents an evaluation of the impact of assimilating Moderate Resolution Imaging Spectroradiometer (MODIS)-based surface albedo estimates in the Noah multi-parameterization (Noah-MP) land surface model, over the continental US during the time period from 2000 to 2017. The evaluation of simulated snow depth and snow cover fields show that significant improvements from data assimilation (DA) are obtained over the High Plains and parts of the Rocky Mountains. Earlier snowmelt and reduced agreements with reference snow depth measurements, primarily over the Northeast US, are also observed due to albedo DA. Most improvements from assimilation are observed over locations with moderate vegetation and lower elevation. The aggregate impact on evapotranspiration and runoff from assimilation is found to be marginal. This study also evaluates the relative and joint utility of assimilating fractional snow cover and surface albedo measurements. Relative to surface albedo assimilation, fractional snow cover assimilation is found to provide smaller improvements in the simulated snow depth fields. The configuration that jointly assimilates surface albedo and fractional snow cover measurements is found to provide the most beneficial improvements compared to the univariate DA configurations for surface albedo or fractional snow cover. Overall, the study also points to the need for improving the albedo formulations in land surface models and the incorporation of observational uncertainties within albedo DA configurations.

surface albedo↗
NASA NTRS1978

Statistical model for asperity-contact time fraction in elastohydrodynamic lubrication

Relations for the asperity contact time fraction during elastohydrodynamic (EHD) lubrication of a typical ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces were used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately 4 to 5. This thickness ratio is several times larger than reported in the literature where one-dimensional random surface models were used.

Sidik, S. M.↗
NASA NTRS1990

A rough-surface thermophysical model for airless planets

A model for determining diurnal temperatures in spherical-section depressions and which encompasses both subsurface heat-flow and direct and scattered sunlight effects is presently applied to the disk-integrated thermal emission of a rough planetary surface with nonzero thermal inertia. Attention is given to the variation with roughness and thermal inertia of the beaming parameter eta, which characterizes zero-phase thermal emission by comparison with a smooth, nonrotating body and is almost independent of albedo for a given surface roughness. The thermal phase curve of Ceres is noted to be well matched by the model features of (1) prograde rotation, (2) 44-deg rms surface slope, and (3) a thermal inertia that is 30 percent of the lunar value.

Spencer, John R.↗
NASA NTRS2006

Optimal Design of Passive Flow Control for a Boundary-Layer-Ingesting Offset Inlet Using Design-of-Experiments

This research will investigate the use of Design-of-Experiments (DOE) in the development of an optimal passive flow control vane design for a boundary-layer-ingesting (BLI) offset inlet in transonic flow. This inlet flow control is designed to minimize the engine fan-face distortion levels and first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. Numerical simulations of the BLI inlet are computed using the Reynolds-averaged Navier-Stokes (RANS) flow solver, OVERFLOW, developed at NASA. These simulations are used to generate the numerical experiments for the DOE response surface model. In this investigation, two DOE optimizations were performed using a D-Optimal Response Surface model. The first DOE optimization was performed using four design factors which were vane height and angles-of-attack for two groups of vanes. One group of vanes was placed at the bottom of the inlet and a second group symmetrically on the sides. The DOE design was performed for a BLI inlet with a free-stream Mach number of 0.85 and a Reynolds number of 2 million, based on the length of the fan-face diameter, matching an experimental wind tunnel BLI inlet test. The first DOE optimization required a fifth order model having 173 numerical simulation experiments and was able to reduce the DC60 baseline distortion from 64% down to 4.4%, while holding the pressure recovery constant. A second DOE optimization was performed holding the vanes heights at a constant value from the first DOE optimization with the two vane angles-of-attack as design factors. This DOE only required a second order model fit with 15 numerical simulation experiments and reduced DC60 to 3.5% with small decreases in the fourth and fifth harmonic amplitudes. The second optimal vane design was tested at the NASA Langley 0.3- Meter Transonic Cryogenic Tunnel in a BLI inlet experiment. The experimental results showed a 80% reduction of DPCP(sub avg), the circumferential distortion level at the engine fan-face.

Allan, Brian G.↗
NASA NTRS2006

Optimal Design of Passive Flow Control for a Boundary-Layer-Ingesting Offset Inlet Using Design-of-Experiments

This research will investigate the use of Design-of-Experiments (DOE) in the development of an optimal passive flow control vane design for a boundary-layer-ingesting (BLI) offset inlet in transonic flow. This inlet flow control is designed to minimize the engine fan face distortion levels and first five Fourier harmonic half amplitudes while maximizing the inlet pressure recovery. Numerical simulations of the BLI inlet are computed using the Reynolds-averaged Navier-Stokes (RANS) flow solver, OVERFLOW, developed at NASA. These simulations are used to generate the numerical experiments for the DOE response surface model. In this investigation, two DOE optimizations were performed using a D-Optimal Response Surface model. The first DOE optimization was performed using four design factors which were vane height and angles-of-attack for two groups of vanes. One group of vanes was placed at the bottom of the inlet and a second group symmetrically on the sides. The DOE design was performed for a BLI inlet with a free-stream Mach number of 0.85 and a Reynolds number of 2 million, based on the length of the fan face diameter, matching an experimental wind tunnel BLI inlet test. The first DOE optimization required a fifth order model having 173 numerical simulation experiments and was able to reduce the DC60 baseline distortion from 64% down to 4.4%, while holding the pressure recovery constant. A second DOE optimization was performed holding the vanes heights at a constant value from the first DOE optimization with the two vane angles-of-attack as design factors. This DOE only required a second order model fit with 15 numerical simulation experiments and reduced DC60 to 3.5% with small decreases in the fourth and fifth harmonic amplitudes. The second optimal vane design was tested at the NASA Langley 0.3-Meter Transonic Cryogenic Tunnel in a BLI inlet experiment. The experimental results showed a 80% reduction of DPCPavg, the circumferential distortion level at the engine fan face.

Allan, Brian G.↗
NASA NTRS2023

Impact of Design Factors for ESA CCI Satellite Soil Moisture Data Assimilation over Europe

In this study, soil moisture retrievals of the combined active–passive ESA Climate Change Initiative (CCI) soil moisture product are assimilated into the Noah-MP land surface model over Europe using a one-dimensional ensemble Kalman filter and an 18-yr study period. The performance of the data assimilation (DA) system is evaluated by comparing it with a model-only experiment (at in situ sites) and by assessing statistics of innovations and increments as DA diagnostics (over the entire domain). For both assessments, we explore the impact of three design choices, resulting in the following insights. 1) The magnitude of the assumed observation errors strongly affects the skill improvements evaluated against in situ stations and internal diagnostics. 2) Choosing between climatological or monthly cumulative distribution function matching as the observation bias correction method only has a marginal effect on the in situ skill of the DA system. However, the internal diagnostics suggest a more robust system parameterization if the observations are rescaled monthly. 3) The choice of atmospheric reanalysis dataset to force the land surface model affects the model-only skill and the DA skill improvements. The model-only skill is higher with input from the MERRA-2 than with input from the ERA5 reanalysis, resulting in larger DA skill improvements for the latter. Additionally, we show that the added value of the DA strongly depends on the quality of the satellite retrievals and land cover, with the most substantial soil moisture skill improvements occurring over croplands and skill degradation occurring over densely forested areas.

Soil moisture↗
NASA NTRS1988

Estimating surface soil moisture from satellite microwave measurements and a satellite derived vegetation index

Normalized 18-GHz microwave brightness temperatures, T(B), and a vegetation index determined from satellite radiometer data are combined with climatically modeled surface moisture estimates to constrain a simple physically based soil moisture model. It is found that the normalized T(B) values correlated well with soil moisture when the data were segregated by vegetation index range, but less so when all the data were combined. By using the vegetation index parameter, the model is shown to account for about 70 percent of the variability in modeled surface soil moisture.

Owe, Manfred↗
NASA NTRS1998

Comparison of Response Surface and Kriging Models in the Multidisciplinary Design of an Aerospike Nozzle

The use of response surface models and kriging models are compared for approximating non-random, deterministic computer analyses. After discussing the traditional response surface approach for constructing polynomial models for approximation, kriging is presented as an alternative statistical-based approximation method for the design and analysis of computer experiments. Both approximation methods are applied to the multidisciplinary design and analysis of an aerospike nozzle which consists of a computational fluid dynamics model and a finite element analysis model. Error analysis of the response surface and kriging models is performed along with a graphical comparison of the approximations. Four optimization problems are formulated and solved using both approximation models. While neither approximation technique consistently outperforms the other in this example, the kriging models using only a constant for the underlying global model and a Gaussian correlation function perform as well as the second order polynomial response surface models.

Simpson, Timothy W.↗
DOE OSTI2025

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Parallelized Carbon Oxidation and Surface Recession Model in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that often consist of a carbon-based reinforcement and a polymeric matrix. During Earth re-entry, they endure high-temperature oxidation and surface recession. Oxidation is an important mechanism for ablation, sometimes leading to the weakening, spallation, or failure of the oxidized fibers at the surface and in the char layer. However, more details are required including accurate material properties of the fiber microstructure, whether the fibers recede homogenously or localized at pits, and the role of pyrolysis outgassing in order to evaluate the role oxidation plays in the degradation and failure mechanisms of these materials. In this work, we demonstrate a parallelizable oxidation-driven ablation model developed for detailed, large-scale simulations in the DSMC code SPARTA. We also develop robust algorithms which handle the conservation of the surface state after an ablation step. Finally, we verify our model for both simple and more complex chemistry as well as microstructures with reaction statistics, oxidation depth calculations, and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗
NASA NTRS2014

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Blankenship, Clay B.↗
NASA NTRS1989

Connectionist model-based stereo vision for telerobotics

Autonomous stereo vision for range measurement could greatly enhance the performance of telerobotic systems. Stereo vision could be a key component for autonomous object recognition and localization, thus enabling the system to perform low-level tasks, and allowing a human operator to perform a supervisory role. The central difficulty in stereo vision is the ambiguity in matching corresponding points in the left and right images. However, if one has a priori knowledge of the characteristics of the objects in the scene, as is often the case in telerobotics, a model-based approach can be taken. Researchers describe how matching ambiguities can be resolved by ensuring that the resulting three-dimensional points are consistent with surface models of the expected objects. A four-layer neural network hierarchy is used in which surface models of increasing complexity are represented in successive layers. These models are represented using a connectionist scheme called parameter networks, in which a parametrized object (for example, a planar patch p=f(h,m sub x, m sub y) is represented by a collection of processing units, each of which corresponds to a distinct combination of parameter values. The activity level of each unit in the parameter network can be thought of as representing the confidence with which the hypothesis represented by that unit is believed. Weights in the network are set so as to implement gradient descent in an energy function.

Hoff, William↗
NASA NTRS2014

Assessing the Utility of 3-km Land Information System Soil Moisture Data for Drought Monitoring and Hydrologic Applications

The NASA Short term Prediction Research and Transition (SPoRT) Center in Huntsville, AL has been running a real-time configuration of the Noah land surface model within the NASA Land Information System (LIS) since June 2010. The SPoRT LIS version is run as a stand-alone land surface model over a Southeast Continental U.S. domain with 3-km grid spacing. The LIS contains output variables including soil moisture and temperature at various depths, skin temperature, surface heat fluxes, storm surface runoff, and green vegetation fraction (GVF). The GVF represents another real-time SPoRT product, which is derived from the Moderate Resolution Imaging Spectroradiometer instrument aboard NASA's Aqua and Terra satellites. These data have demonstrated operational utility for drought monitoring and hydrologic applications at the National Weather Service (NWS) office in Huntsville, AL since early 2011. The most relevant data for these applications have proven to be the moisture availability (%) in the 0-10 cm and 0-200 cm layers, and the volumetric soil moisture (%) in the 0-10 cm layer. In an effort to better understand their applicability among locations with different terrain, soil and vegetation types, SPoRT is conducting the first formal assessment of these data at NWS offices in Houston, TX, Huntsville, AL and Raleigh, NC during summer 2014. The goal of this assessment is to evaluate the LIS output in the context of assessing flood risk and determining drought designations for the U.S. Drought Monitor. Forecasters will provide formal feedback via a survey question web portal, in addition to the NASA SPoRT blog. In this presentation, the SPoRT LIS and its applications at NWS offices will be presented, along with information about the summer assessment, including training module development and preliminary results.

White, Kristopher D.↗