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NASA NTRS2015

Actuators Using Piezoelectric Stacks and Displacement Enhancers

Actuators are used to drive all active mechanisms including machines, robots, and manipulators to name a few. The actuators are responsible for moving, manipulating, displacing, pushing and executing any action that is needed by the mechanism. There are many types and principles of actuation that are responsible for these movements ranging from electromagnetic, electroactive, thermo-mechanic, piezoelectric, electrostrictive etc. Actuators are readily available from commercial producers but there is a great need for reducing their size, increasing their efficiency and reducing their weight. Studies at JPL’s Non Destructive Evaluation and Advanced Actuators (NDEAA) Laboratory have been focused on the use of piezoelectric stacks and novel designs taking advantage of piezoelectric’s potential to provide high torque/force density actuation and high electromechanical conversion efficiency. The actuators/motors that have been developed and reviewed in this paper are operated by various horn configurations as well as the use of pre-stress flexures that make them thermally stable and increases their coupling efficiency. The use of monolithic designs that pre-stress the piezoelectric stack eliminates the use of compression stress bolt. These designs enable the embedding of developed solid-state motors/actuators in any structure with the only macroscopically moving parts are the rotor or the linear translator. Finite element modeling and design tools were used to determine the requirements and operation parameters and the results were used to simulate, design and fabricate novel actuators/motors. The developed actuators and performance will be described and discussed in this paper.

rotary devices↗

NASA NTRS2017

Effective Assimilation of SMAP Observations Using Statistical Techniques

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

Kolassa, J.↗

NASA NTRS2017

A Consistent EPIC Visible Channel Calibration using VIIRS and MODIS as a Reference

The Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) satellite constantly images the sunlit disk of Earth from the Lagrange-1 (L1) point in 10 spectral channels spanning the UV, VIS, and NIR spectrums. Recently, the DSCOVR EPIC team has publicly released version 2 dataset, which has implemented improved navigation, stray-light correction, and flat-fielding of the CCD array. The EPIC 2-year data record must be well-calibrated for consistent cloud, aerosol, trace gas, land use and other retrievals. Because EPIC lacks onboard calibrators, the observations made by EPIC channels must be calibrated vicariously using the coincident measurements from radiometrically stable instruments that have onboard calibration systems. MODIS and VIIRS are best-suited instruments for this task as they contain similar spectral bands that are well-calibrated onboard using solar diffusers and lunar tracking. We have previously calibrated the EPIC version 1 dataset by using EPIC and VIIRS angularly matched radiance pairs over both all-sky ocean and deep convective clouds (DCC). We noted that the EPIC image required navigations adjustments, and that the EPIC stray-light correction provided an offset term closer to zero based on the linear regression of the EPIC and VIIRS ray-matched radiance pairs. We will evaluate the EPIC version 2 navigation and stray-light improvements using the same techniques. In addition, we will monitor the EPIC channel calibration over the two years for any temporal degradation or anomalous behavior. These two calibration methods will be further validated using desert and DCC invariant Earth targets. The radiometric characterization of the selected invariant targets is performed using multiple years of MODIS and VIIRS measurements. Results of these studies will be shown at the conference.

Haney, C. O.↗

NASA NTRS2019

Inflatable Technology: Using Flexible Materials to Make Large Structures

Space structures are one of the most critical components for any spacecraft, as they must provide the maximum amount of livable volume with the minimum amount of mass. Deployable structures can be used to gain additional space that would not normally fit under a launch vehicle shroud. This expansion capability allows it to be packed in a small launch volume for launch, and deploy into its fully open volume once in space. Inflatable, deployable structures in particular, have been investigated by NASA since the early 1950’s and used in a number of spaceflight applications. Inflatable satellites, booms, and antennas can be used in low-Earth orbit applications. Inflatable heatshields, decelerators, and airbags can be used for entry, descent and landing applications. Inflatable habitats, airlocks, and space stations can be used for in-space living spaces and surface exploration missions. Inflatable blimps and rovers can be used for advanced missions to other worlds. These applications are just a few of the possible uses for inflatable structures that will continued to be studied as we look to expand our presence throughout the solar system.

structures↗

NASA NTRS2016

Use of the NLP10x10 Sequential Quadratic Programming Algorithm To Solve Rotorcraft Hub Loads Minimisation Problems

Previous research and experimentation on the use of a non-linear programming constrained optimisation technique to define an optimal control vector for rotorcraft applications indicated that use of this methodology was feasible and desirable in many cases. In particular, use of non-linear programming methods that solve a sequence of related quadratic-programming sub-problems were used successfully to solve these problems. Accordingly, a licence for one of the latest versions of Professor Klaus Schittkowskis very successful Sequential Quadratic Programming NLPQLP software was obtained and used to experiment with and analyse typical optimisation problems of the type encountered in various rotorcraft wind tunnel and flight tests. This research resulted in the development of the general NLPQLP Computation System that could be used to solve problems of the type encountered in various rotorcraft applications where there is a linear dependence of the measurement vector on the control vector, and where equality andor inequality constraints might be imposed. This development was accomplished on a mainframe computer not part of actual wind tunnel andor flight-test experiment, but in a format which was transferable to wind tunnel lap-top computers. Emphasis was directed toward obtaining efficiency, robustness and speed in computation.The System was developed in support of the five-bladed SMART Rotor Active Flap Rotor Hub Loads analytical minimisation research. The design and development of the Computation System was tailored to address the particular requirements of the problem to minimise a performance metric function of measured hub load harmonic angular couple components by optimising the control vector harmonic flap angular couple components subject to constraints on the amplitudes of these control vector harmonic flap angular couple components. In addition, to facilitate real time wind tunnel experimentation, the ability to rapidly selectchange the particular hub load harmonic angular couple components andor the particular control vector harmonic angular couple components to be considered in the optimisation procedure was provided in the System. This capability allows the singling out of particular hub load frequencies andor particular flap angle frequencies to be analysed during testing operations. The System was used very successfully for the SMART Active Flap Rotor Hub minimisation problems considered in the study, the results of which were presented at the American Helicopter Society Fifth Decennial Aeromechanics Specialist Conference in January 2014. Excellent agreement between cases initiated with best guess starting estimates for the control vector elements and cases initiated with zero control vector starting element estimates resulted, indicating the robustness of the NLP10x10 algorithm.

Rotorcraft Hub Loads↗

NASA NTRS2017

Synergy Between Land Use and Climate Change Increases Future Fire Risk in Amazon Forests

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

Le Page, Yannick↗

NASA NTRS2019

Multimodel Analysis of Future Land Use and Climate Change Impacts on Ecosystem Functioning

Land use and climate changes both affect terrestrial ecosystems. Here, we used three combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1xRCP26, SSP3xRCP60, and SSP5xRCP85) as input to three dynamic global vegetation models to assess the impacts and associated uncertainty on several ecosystem functions: terrestrial carbon storage and fluxes, evapotranspiration, surface albedo, and runoff. We also performed sensitivity simulations in which we kept either land use or climate (including atmospheric CO2) constant from year 2015 on to calculate the isolated land use versus climate effects. By the 2080–2099 period, carbon storage increases by up to 87 ± 47 Gt (SSP1xRCP26) compared to present day, with large spatial variance across scenarios and models. Most of the carbon uptake is attributed to drivers beyond future land use and climate change, particularly the lagged effects of historic environmental changes. Future climate change typically increases carbon stocks in vegetation but not soils, while future land use change causes carbon losses, even for net agricultural abandonment (SSP1xRCP26). Evapotranspiration changes are highly variable across scenarios, and models do not agree on the magnitude or even sign of change of the individual effects. A calculated decrease in January and July surface albedo (up to −0.021 ± 0.007 and −0.004 ± 0.004 for SSP5xRCP85) and increase in runoff (+67 ± 6 mm/year) is largely driven by climate change. Overall, our results show that future land use and climate change will both have substantial impacts on ecosystem functioning. However, future changes can often not be fully explained by these two drivers and legacy effects have to be considered.

Krause, A.↗

NASA NTRS2019

Using GES DISC Data to Study Kilauea Volcano of 2018

Kilauea volcano in Hawaii which erupted in early May 2018 injected massive amount of SO2 and ash into the atmosphere. The lava flow during the eruption destroyed many home and neighborhoods. The SO2 plume during the eruption of Kilauea volcano is analyzed from May to August 2018 using multiple satellite products such as Level 2 TROPspheric Monitoring Instrument (TROPOMI) and Level 3 Ozone Monitoring Instrument (OMI) from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). GES DISC hosts multi-disciplinary Earth science data sets that can be used to analyze natural disasters, such as the Kilauea volcano. Additionally, GES DISC's Giovanni tool can be used to visualize these data. We acquired OMI through the subsetting function, which is processed by the GES DISC in-house developed backend software Level3/4 Regrider and Subsetter (L34RS) and TROPOMI using OPeNDAP.Data from the OMI OMSO2e product showed elevated levels of SO2 amounts during the eruption between May to August 2018. Similarly, ground-based stations at Hawaii Volcanoes National Park recorded higher SO2 concentrations during the same time period. This study uses wind direction from Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) to analyze the transport and dispersion of SO2 plume and map lava flows from the volcano using thermal images from Visible Infrared Imaging Radiometer Suite (VIIRS). Furthermore, satellite observations combined with socioeconomic and public health data are used to analyze its impact in public health.

KC, Binita↗

NASA NTRSDate not supplied

Improving Structural Test and Analysis Correlation Using Digital Image Correlation Boundary Measurements

Simplified idealizations, such as clamped or simply supported, are commonly used as support boundary conditions in modeling and analysis of tested aerospace structures. However, these simplifications are not always appropriate and characterization of the response of non-rigid boundaries is often required to improve test and analysis correlation. While e analysis models are typically modified to better represent the test, this modification is often not practical due to the complexities of the boundary response. A study is conducted to examine the use of digital image correlation (DIC) to measure the boundary support structure response and then to adjust the test data to remove the effects of the boundary response in order to improve test and analysis correlation. A high-aspect ratio composite wing test is the subject of the study. Three sources of boundary flexibility contributing to rigid body rotation of the test wing are identified and quantified using both DIC and conventional test data. The wing displacement test data are adjusted using DIC data for these sources. Wing displacement test data is also adjusted using direct measurement of wing rotation from a DIC system that monitored the top surface, root region of the wing, and using available conventional instrumentation. The adjusted data exhibits improved test and analysis correlation and demonstrated the benefit of using DIC along with conventional instrumentation to collect and interpret test data.

Andrew E Lovejoy↗

NASA NTRSDate not supplied

Variational Coupled Loads Analysis using the Hybrid Parametric Variation Method

Time-domain coupled loads analysis (CLA)is used to determine the response of a launch vehicle and payload system to transient forces, such as liftoff, engine ignitions and shutdowns, jettison events, and atmospheric flight loads, such as buffet. CLA, using Hurty/Craig-Bampton (HCB)component models, is the accepted method for the establishment of design-level loads for launch systems. However, uncertainty in the component models flows into uncertainty in predicted system results. Uncertainty in the structural responses during launch is a significant concern because small variations in launch vehicle and payload mode shapes and their interactions can result in significant variations in system loads. Uncertainty quantification (UQ)is used to determine statistical bounds on prediction accuracy based on model uncertainty. In this paper uncertainty is treated at the HCB component-model level. In an effort to account for model uncertainties and statistically bound their effect on CLA predictions, this work combines CLA with UQ in a process termed variational coupled loads analysis (VCLA). The modeling of uncertainty using a parametric approach, in which input parameters are represented by random variables, is common, but its major drawback is the resulting uncertainty is limited to the form of the nominal model. Uncertainty in model form is one of the biggest contributors to uncertainty in complex built-up structures. Model-form uncertainty can be represented using a nonparametric approach based on random matrix theory (RMT). In this work, UQ is performed using the hybrid parametric variation (HPV)method, which combines parametric with nonparametric uncertainty at the HCB component model level. The HPV method requires the selection of dispersion values for the HCB fixed-interface (FI)eigenvalues, and the HCB mass and stiffness matrices. The dispersions are based upon component test-analysis modal correlation results. During VCLA, random component models are assembled into an ensemble of random systems using a Monte Carlo (MC)approach. CLA is applied to each of the ensemble members to produce an ensemble of system-level responses for statistical analysis. The proposed methodology is demonstrated through its application to a buffet loads analysis of NASA’s Space Launch System (SLS)during the transonic regime fifty seconds after liftoff. Core stage (CS)section shears and moments are recovered, and statistics are computed.

Uncertainty Quantification↗

NASA NTRS2020

TURBOMAT-FR: Turbomachinery Aeroelastic Forced Response Analysis Automation Using MATLAB®: PART 1

The primary aim of this effort is to develop a software tool named “Turbomachinery Aeroelastic Analysis Tool for Forced Response (TURBOMAT-FR)” using MATLAB® (The MathWorks, Inc.) scripts. The tool will aid in performing routine forced response analysis of turbomachinery fan blades with the aid of the modal summation method (MSUM). The MSUM approach requires a modal solution consisting of modal displacements, modal frequencies, and modal stresses. The MATLAB® scripts facilitate easy extraction of the required quantities from the computational fluid dynamics (CFD) and MSC Nastran (Hexagon AB) solution files. These quantities are subsequently utilized by the MSUM approach to perform a complete forced response analysis.The MATLAB® scripts in TURBOMAT-FR are utilized in postprocessing of the MSC Nastran finite element analysis outputs in three types of solutions or steps, namely (1) stresses and displacements from static and steady response solution, (2) unsteady stresses and displacements from direct forced response solution, and (3) modal solution containing modal displacements and modal stresses. In step (4), separate MATLAB® scripts are also developed to read the processed outputs in step (3) and perform forced response analysis using MSUM. The TURBOMAT-FR MATLAB® scripts mentioned previously are presented in two reports designated “Part 1” and “Part 2”. The current report, Part 1, presents the scripts needed to accomplish steps (1) and (2), noted previously. This will be exclusively useful for performing only the static and steady response analysis and the forced response analysis using the direct forced response solution approach. Part 2 contains the TURBOMAT-FR MATLAB® scripts needed to accomplish steps (3) and (4). The MATLAB® scripts given in Part 2 facilitate the calculation of unsteady stresses using MSUM and provide an automated procedure associated with aeroelastic forced response analysis with different pressure files for the same structural model. The unsteady stresses calculated using MSUM in Part 2 can be compared with those presented in Part 1. A cantilevered blade-alone model subjected to a realistic pressure loading to a boundary was used for static and unsteady direct forced response analysis to demonstrate the effectiveness of the TURBOMATFR MATLAB® scripts.

MATLAB-Scripts↗

NASA NTRSDate not supplied

Pterodactyl: Guidance and Control of a Symmetric Deployable Entry Vehicle using an Aerodynamic Control System

The NASA-funded Pterodactyl project seeks to advance the state-of-the-art for varying entry vehicle types by developing unconventional guidance and control technologies for Deployable Entry Vehicles (DEVs) that can be applied to different entry vehicle configurations. Prior work by the authors [1–5] involved developing both traditional and novel integrated guidance and control solutions for a Pterodactyl Baseline Vehicle (PBV), a variant of an asymmetric DEV called the Lifting Nano ADEPT (LNA) [6]. In the prior studies, two different guidance schemes were designed and implemented for the PBV: (i) traditional bank angle guidance developed using the Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) and (ii) novel angle of attack and sideslip (α - β) guidance developed using FNPEG with Uncoupled Range Control [4]. Using Linear Quadratic Regulator (LQR) optimal control methods with state-feedback integral control designs, these guidance trajectories were designed to be tracked using (i) a conventional propulsive entry vehicle control hardware architecture - reaction control systems (RCS) and (ii) novel non-propulsive entry vehicle control systems - aerodynamic flap control system (FCS) and moving mass control system (MMCS) [1]. The novel FCS and MMCS architectures were designed to track α - β guidance commands while the RCS was designed to track bank angle commands. It was discovered that the asymmetric DEV, the PBV, experienced a non-zero induced roll moment due to sideslip that the FCS and MMCS architectures had limited capability to trim out. These two architectures were designed to provide independent angle of attack and sideslip commands with limited consideration for roll moment generation to trim. As a result, for the PBV, the FCS and MMCS configurations as designed, were limited in providing the control authority needed to track an α - β guidance trajectory [1]. These results form the motivation for the work presented in this paper - utilizing an aerodynamic control system to track α - β guidance commands for a symmetric DEV with the expectation that a symmetric entry vehicle will have zero or significantly reduced roll moment due to sideslip that the FCS can handle when tracking an α - β guidance trajectory. To demonstrate the feasibility of a novel guidance and control architecture on a DEV, we utilize a symmetric DEV, the PBV-II, for (i) the novel α - β guidance development using FNPEG with Uncoupled Range Control and (ii) LQR control design using eight aerodynamic control surfaces. This paper demonstrates that the novel uncoupled α - β guidance tracking can be achieved using aerodynamic control surfaces on a symmetric deployable entry vehicle configuration.

Wendy A Okolo↗

NASA NTRSDate not supplied

Detecting Short Term Drought Impact in the Southwest US Using GOES-16 ABI Data

Satellite optical remote sensing has been often used for monitoring broad-region vegetation change, for example, phenology observations and the year-to-year leaf area index (LAI) responses to climate oscillations. However, rapid responses of vegetation to day-to-day weather perturbations are difficult to detect using available optical remote sensing satellites because of the low frequency of the observations. Sun-synchronous optical sensors, such as Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR), can observe a target area once a day. Daily observations cannot distinguish whether short-term changes in Normalized Differential Vegetation Index (NDVI) are actual LAI change or cloud contamination. NOAA’s GOES satellites make observations every 10 to 15 minutes using the Advanced Baseline Imager (ABI). In this study, we used the Geostationary-NASA Earth Exchange (GeoNEX) L1G Top-of-Atmosphere (TOA) ABI data to detect drought impact on NDVI time series in the Southwest US. We used an empirical method to cancel the BRDF effect of varying solar zenith angle. The ABI was able to detect short term drought impacts as well as an NDVI decrease in the dry season. Increased NDVI right after a rainfall followed by an immediate decrease was observed. These ABI NDVI changes were correlated with the RGB time series from PhenoCam Network data. Results indicated that the ABI can be used for short-term analysis of LAI and can detect small LAI changes caused by drought in an arid area, suggesting the potential for its use in near-real time drought monitoring applications.

ABI↗

NASA NTRS2021

Using SMAP Level-4 Soil Moisture to Constrain MOD16 Evapotranspiration over the Contiguous USA

Evapotranspiration (ET) is a key hydrologic variable linking the Earth’s water, carbon and energy cycles. At large spatial scales, remote sensing-based (RS) models are often used to quantify ET. Despite the large number of RS ET models available, few include soil moisture as a key environmental input, which can degrade model accuracy and utility. Here, we use model assimilation enhanced soil moisture estimates from the NASA SMAP (Soil Moisture Active Passive) mission as a water supply control in the MOD16 ET algorithm framework. SMAP-derived daily surface (0-5cm depth) and root zone (0-1m depth) soil moisture are used with MODIS (Moderate Resolution Imaging Spectroradiometer) vegetation observations, and 4km gridded regional surface meteorology (Gridmet) as primary inputs for estimating daily ET and underlying model soil and stomatal conductance terms. We calibrated the model environmental response parameters using tower eddy covariance ET observations representing major North American biomes. The model ET results were validated using a holdout set of tower observations spanning a large regional climate gradient. The updated ET estimates outperform the baseline MOD16 product across all tower validation sites (RMSE = 0.758 vs 1.108 mm day-1; R2 = 0.68 vs0.45, respectively). Smaller relative improvements were obtained using a recalibrated model with 4km Gridmet meteorology, but no soil moisture control (RMSE = 0.813 mm day-1; R2 = 0.66), indicating that these changes are essential for the improved model performance. The soil moisture-constrained model improvements and relative benefits from the SMAP observations are greater in arid climates, consistent with stronger soil moisture control on ET in water-limited regions. The use of SMAP soil moisture as an additional model constraint improves MOD16 regional performance and provides a new framework for investigating both soil and atmosphere controls on ET.

SMAP↗

NASA NTRS2020

Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet(UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of>~0.4 and GEMS SSA values of<~0.95.Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

aerosol↗

NASA NTRS2021

Terra and Aqua MODIS Thermal Emissive Bands Calibration and RVS Stability Assessments Using an In Situ Ocean Target

MODIS, whose openly-public data have been used for over two decades to monitor and address global issues, has 16 Thermal Emissive Bands (TEBs) with central wavelengths that range from 3.7 μm to 14.4 μm, and are calibrated on-orbit using observations from its on-board blackbody. In order to maintain MODIS’ rich, well-calibrated archive of multispectral imagery and data, Earth targets are regularly used to track its long-term stability, as well as the consistency between the two sensors onboard the Terra and Aqua satellites. Moreover, these scenes can be used to compare MODIS Earth view data over the complete scan-angle range and evaluate the on-orbit performance of the TEBs response-versus-scan-angle (RVS) over mission lifetime. This manuscript focuses on evaluating the MODIS TEBs Collection (C6.1) radiometric calibration stability for both instruments using an in situ ocean target as reference (hereafter referred to as in situ sea surface temperature (SST)). Furthermore, it will assess the calibration consistency between the MODIS sensors. Lastly, it will analyze the on-orbit RVS stability for Terra and Aqua MODIS. Only cloud-free, nighttime MODIS TEB retrievals were used for the study. A normalization methodology is applied to standardize the MODIS data to the in situ SST. Additionally, spectral corrections were derived between some of the Terra and Aqua MODIS TEBs by using a combination of the MODIS Atmospheric Profile product and MODerate resolution atmospheric TRANsmission (MODTRAN) simulations. Results indicate that most MODIS TEBs exhibit mission-long trends of ±0.50 K – with Terra band 30 presenting the largest downward drift due to residual electronic cross-talk effects. Moreover, the calibration consistency analysis over a warm ocean target demonstrated that the average Terra-to-Aqua MODIS bias for most bands is well within ±0.50 K (bands 27 and 30 show the largest - electronic crosstalk-related - biases). Lastly, the MODIS TEBs RVS trends display changes of ±0.50 K (except for bands 25 and 27 at the end-of-scan angles) for both instruments. Overall, the MODIS TEBs remain well-calibrated and their RVSs aptly-characterized.

MODIS↗

NASA NTRSDate not supplied

Derivation and Testing of Consumptive Water Use Fraction for Specialty Crops

The Crop Consumptive Use Fraction (CCUF) expresses beneficial water use in the form of seasonal evapotranspiration of applied water (ETAW), relative to total irrigation volume. The metric is an indicator of the efficiency of agricultural water use and is a recommended component for preparation of agricultural water management plans in California. An FAO-56 based web application has been developed to facilitate retrospective evaluation of ETAW, and hence CCUF, at field level. The current application is optimized for prevailing climate in four of the state’s main growing regions: San Joaquin Valley, Sacramento Valley, Central Coast, and North Coast. User inputs include crop type, soil texture, irrigation method, daily irrigation volume, daily rainfall, and seasonal start/stop dates to define the analysis period. Time series of fractional green canopy cover (Fc), based on Landsat and Sentinel-2 Earth-resource satellite observations, are imported from NASA’s Satellite Irrigation Management Support (SIMS) system. Grass reference evapotranspiration (ETo) time series are accessed from Spatial CIMIS (California Irrigation Management Information System). Daily crop height (h) is estimated as a simple function of typical maximum height for the given crop type (from FAO-56) and Fc. A vegetation density coefficient (Kd) is derived from Fc and h. Stomatal control factors during mid-and late-season are applied to tree and vine crops. Typical values for minimum daily relative humidity and mean daily windspeed, derived from historical CIMIS weather data, are used to correct for regional deviations from standard climate (defined as RHmin=45%, windspeed =2m/s). The resulting daily basal crop coefficient (Kcb) represents the ET of a well-watered crop with minimal soil evaporation, relative to ETo. A soil water balance sub-model for the top 0.1 m is used to calculate daily evaporation coefficients (Ke). A second sub-model applies to the root zone to calculate crop water stress coefficients (Ks) and effective precipitation (Pe), which is the fraction of rainfall that is available for crop use. Those coefficients are combined with Kcb and ETo to calculate daily ETc. ETAW is then derived as cumulative ETc less cumulative Pe. For verification purposes, sensor installations were used to measure seasonal ETc in commercial fields for several annual and perennial specialty crops by soil water balance and energy balance methods. Model estimates of seasonal ETc show mean absolute error of <10% compared to the ground measurements.

Derivation↗

NASA NTRSDate not supplied

Controlled Rest: Investigating the Use of an In-Flight Sleepiness Countermeasure

INTRODUCTION: Sleepiness is commonly reported amongst commercial airline pilots and is recognized as a safety risk due to its impact on performance. Controlled Rest (CR) refers to a short, voluntary nap opportunity taken by pilots on the flight deck as a countermeasure to unanticipated sleepiness in flight. This study explores the profile of CR use in a long-haul commercial airline. METHODS: Forty-four pilots filled in an application-based sleep/work diary and wore actiwatches for approximately 2 weeks. Complete data sets from 239 flights including sleep diaries, actigraphy, and schedules were merged and analyzed. Sleep diary entries were used to set CR intervals in the actigraphy software, which was then used to predict sleep within these intervals. All time-stamps of sleep periods and flight schedules were adjusted for home-base time of the pilots. Pearson Correlations were used to assess the influence of pilot demographics on CR use. A mixed-effects logistic regression was used to analyze the impact of schedule factors on CR. RESULTS: Pilots reported taking CR on 46% (n=110) of observed flights. Average CR attempt duration was 43.1 ± 11.0 minutes. Eighty-percent (n=106/133) of all CR attempts were estimated by actigraphy to have successfully achieved sleep with an average sleep duration during successful rest periods of 31.7 ± 12.2 minutes. Captains reported taking CR on 38% of flights (n=39/102), compared to First Officers reporting 52% (n=71/137) of flights with CR (p=0.131). Age, experience, BMI, and sleep need were not associated with the percentage of flights with CR (all p>0.244). The following schedule factors were associated with a higher frequency of CR: night (55%, n=76) vs. day flights (34%, n=34); <10h (63%, n=80) vs. >10h duration flights (27%, n=30); return (60%, n=71) vs. outbound flights (33%, n=39); and 2-pilot (69%, n=83) vs. >2-pilot flights (23%, n=27) (all p≤0.001). There was a trend for more CR on eastbound flights, but this was not significant (eastbound: 51%, n= 57; westbound: 40%, n= 44; p=0.059). Of note, 22% (n=26) of augmented flights (>2-pilots) contained both CR and Bunk Rest (in a designated rest facility). DISCUSSION: Data from this airline show that pilots commonly use CR to mitigate sleepiness in-flight, especially on flights <10h duration and during home-base nighttime flights. Future studies are required to determine generalizability of these results to other airlines.

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