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NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗

NASA NTRSDate not supplied

IceCube: Demonstration of an 883 GHz Radiometer for Ice Cloud Remote Sensing

IceCube was a technology demonstration of an 883 GHz heterodyne radiometer on a 3U CubeSat for ice cloud characterization. The project was a collaboration between Goddard Space Flight Center, Virginia Diodes Inc., and Wallops Flight Facility. IceCube was launched to the International Space Station (ISS) in April 2017, and was deployed to the orbit in May 2017. The radiometer measured ice cloud emissions from an ISS orbit for over 15 months. IceCube generated the first 883 GHz cloud map over a large operation temperature range of (5 ºC—37 ºC). Cloud ice plays a major role in the cloud precipitation process and Earth’s energy budget. Ice clouds are used in global circulation models as tuning parameters to achieve model agreement with observation at the top of the atmosphere in the radiation budget and at the bottom for precipitation, however, due to a lack of accurate ice cloud measurements large uncertainties exist in these models. Submillimeter wave remote sensing is capable of addressing this issue by measuring cloud ice mass and microphysical properties in the middle-to-upper troposphere. This fills the sensitivity gap not covered by the visible/infrared and microwave sensors [1]. The goal of IceCube was to increase the TRL of a heterodyne 883 GHz radiometer (using commercial parts) from 5 to 7 by validating the performance in a relevant spaceflight environment. The design of the radiometer was driven by frequency of operation, bandwidth, calibration, available power, and thermal environment requirements. The design included a 15 mm aperture off-axis parabolic reflector with a Potter feed horn, an 883 GHz 2nd-harmonic mixer that is fed by a local oscillator chain with a 24.3 GHz dielectric resonator (MLA), followed by a 6 GHz bandwidth centered at 9 GHz intermediate frequency assembly (IFA), receiver interface card, and power distribution unit. The IFA included an internal noise diode calibration to separate the MLA performance from the rest of the system. For this the radiometer had four operational states: antenna, antenna + noise, reference, and reference + noise; each state’s duration was 10 ms. The total power dissipation of the instrument was 5.6 W. The spacecraft had spinning capabilities to provide a cold sky view for calibration. We present the instrument design, ground test results, challenges, and highlight some of the flight measurements.

N Ehsan↗

DOE OSTI2024

IoT-Based Comfort Control and Fault Diagnostics System for Energy-Efficient Homes

This project studies an Internet of Things (IoT)-based comfort control and fault diagnostics system (referred as iComfort in this report) for energy-efficient homes. The system delivers an occupant-comfort-oriented thermal environment adaptive to fault scenarios and achieves HVAC energy savings in a cost-effective and straightforward way. This smart iComfort home system consists of the following key features. 1) Cost-effectiveness and scalability of the entire hardware and software system: The system includes low-cost temperature, humidity, and airflow sensors, and a Raspberry Pi-based local hub that interfaces with the cloud and IoT-enabled devices. The cost is low, not only for sensors, but also the costs associated with sensor installation, system setup and commissioning, data communication and storage, and data analytics (e.g., the development of automated fault detection and diagnosis (AFDD), as well as adaptive control strategies that are both computationally efficient and practical to implement). 2) Energy performance and user satisfaction: The system delivers user satisfaction and energy savings. This includes a) ease of use, b) optimal occupant thermal comfort, and c) accurate system feedback (e.g., low false alarm of AFDD strategies). 3) Favorable demonstrated prototype performance: The prototype tested at the Pacific Northwest National Laboratory (PNNL) Lab Homes demonstrates the accuracy of fault detections and diagnoses and shows thermal comfort improvement and energy savings through adaptive and optimal HVAC operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

Convective Transport and Evolution of Clouds and aerosols in the Asian Summer Monsoon Region

The existence of a persistent layer in the lowermost stratosphere in the Asian Monsoon region is well-known and has been observed by satellites and also in situ by balloon-borne sensors. This aerosol layer has been observed to persist every year by both SAGE sensors and by CALIOP, between the tropopause and the lower boundary of the Junge stratospheric sulfate layer. But how does this layer form and why? Apparently, aerosols are lofted by convection form the Indian and Asian continents, into the upper troposphere/lower stratosphere (UT/LS) area in the middle of a persistent anticyclone associate with the Asian summer monsoon. But some mysteries remain. The top of this aerosol layer is well above the altitude of maximum convective outflow, so why is the top of the aerosol layer so high? Are the aerosols coming from China or from India? And finally, is there an observable impact of these aerosol on thin cirrus distributions in the UT/LS? We explore the interesting difference in altitude between the ATAL layer and the convective cloud top height, using observations from CALIOP and from SAGE. In the process of doing this we examine the accuracy of both CALIOP and SAGE cloud/aerosol discrimination, and the impact of various averaging lengths. We compare the apparent "observational tropopause" with observations from COSMIC, CALIOP (clouds), and with modeled interpolation from MERRA-2. We also compare CALIOP and CloudSat daytime cloud top heights for convective clouds with the vertical aerosol distribution, and evaluate convection in this region as represented by MERRA-2. Finally, and maybe most importantly we compare convective cloud top heights and temperatures with diurnal variability during the most recent years by using observations from the geostationary Himawari satellite. How representative are the twice-daily A-Train observations, when compared to the natural diurnal variability of convection? The goal is to establish the origins of these UT/LS aerosols, whether these aerosol distributions can be completely explained by convective transport, and to evaluate convective lofting of aerosol by models. Ultimately, the convective lofting of aerosols as modeled is needed to explain the Asian Monsoon aerosol distributions. The observations contribute much-needed information to enhance the model accuracy.

clouds↗

DOE OSTI2017

New Solar Irradiance Measurements from the Miniature X-Ray Solar Spectrometer Cubesat

The goal of the Miniature X-ray Solar Spectrometer ( MinXSS ) CubeSat is to explore the energy distribution of soft X-ray (SXR) emissions from the quiescent Sun, active regions, and during solar flares and to model the impact on Earth's ionosphere and thermosphere. The energy emitted in the SXR range (0.1–10 keV) can vary by more than a factor of 100, yet we have limited spectral measurements in the SXRs to accurately quantify the spectral dependence of this variability. The MinXSS primary science instrument is an Amptek, Inc. X123 X-ray spectrometer that has an energy range of 0.5–30 keV with a nominal 0.15 keV energy resolution. Two flight models have been built. The first, MinXSS -1, has been making science observations since 2016 June 9 and has observed numerous flares, including more than 40 C-class and 7 M-class flares. These SXR spectral measurements have advantages over broadband SXR observations, such as providing the capability to derive multiple-temperature components and elemental abundances of coronal plasma, improved irradiance accuracy, and higher resolution spectral irradiance as input to planetary ionosphere simulations. MinXSS spectra obtained during the M5.0 flare on 2016 July 23 highlight these advantages and indicate how the elemental abundance appears to change from primarily coronal to more photospheric during the flare. MinXSS -1 observations are compared to the Geostationary Operational Environmental Satellite ( GOES ) X-ray Sensor (XRS) measurements of SXR irradiance and estimated corona temperature. Additionally, a suggested improvement to the calibration of the GOES XRS data is presented.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2008

Microwave Radiometers from 0.6 to 22 GHz for Juno, a Polar Orbiter around Jupiter

A compact radiometer instrument is under development at JPL for Juno, the next NASA New Frontiers mission, scheduled to launch in 2011. This instrument is called the MWR (MicroWave Radiometer), and its purpose is to measure the thermal emission from Jupiter's atmosphere at selected frequencies from 0.6 to 22 GHz. The objective is to measure the distributions and abundances of water and ammonia in Jupiter's atmosphere, with the goal of understanding the previously unobserved dynamics of the subcloud atmosphere, and to discriminate among models for planetary formation in our solar system. The MWR instrument is currently being developed to address these science questions for the Juno mission. As part of a deep space mission aboard a solar-powered spacecraft, MWR is designed to be compact, lightweight, and low power. The entire MWR instrument consists of six individual radiometer channels with approximately 4% bandwidth at 0.6, 1.25,2.6,5.2, 10,22 GHz operating in direct detection mode. Each radiometer channel has up to 80 dB of gain with a noise figure of several dB. The highest frequency channel uses a corrugated feedhorn and waveguide transmission lines, whereas all other channels use highly phase stable coaxial cables and either patch array or waveguide slot array antennas. Slot waveguide array antennas were chosen for the low loss at the next three highest frequencies and patch array antennas were implemented due to the mass constraint at the two lowest frequencies. The six radiometer channels receive their voltage supplies and control lines from an electronics unit that also provides the instrument communication interface to the Juno spacecraft. For calibration purposes each receiver has integrated noise diodes, a Dicke switch, and temperature sensors near each component that contributes to the noise figure. In addition, multiple sensors will be placed along the RF transmission lines and the antennas in order to measure temperature gradients. All antennas and RF transmission lines must withstand low temperatures and the harsh radiation environment surrounding Jupiter; the receivers and control electronics are protected by a radiation-shielding enclosure on the Juno spacecraft that also provides for a benign and stable operating temperature environment. This paper will focus on the concept of the MWR instrument and will present results of one breadboard receiver channel.

receiver↗

DOE OSTI2023

Control methods for mitigating flow oscillations in a supercritical CO 2 recompression closed Brayton cycle

A dynamic model of a 10 MWe supercritical CO 2 (sCO 2 ) recompression closed Brayton power generation cycle is used to investigate control methods for mitigating oscillations in flow conditions and power demand load, especially as the load ramp rate is increased and the load setpoint is more closely tracked. The focus is on control of the main compressor inlet temperature (MCIT) since oscillations are prompted by the strong nonlinearities in sCO 2 fluid properties near the critical point and by changes in system inventory for efficient load management. In this study, the oscillatory behavior during load ramping is first shown and then two potential control solutions for substantially reducing oscillations are given: 1) the use of the main compressor inlet guide vanes (IGV) and 2) bypassing a portion of the sCO 2 around the cooler to maintain the MCIT. These control methods reduce the effect of cycle feedback from interactions between the MCIT and load. When implementing either control method, a load setpoint ramp of 7.5%/min was maintainable while achieving closer load setpoint tracking with limited oscillations. Finally, the impact of sensor noise on the control was examined since derivative action was used in the IGV and cooler sCO 2 bypass control. Finally, while some effect was evident, signal noise was not problematic to the control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1993

A satellite-borne radar wind sensor (RAWS)

Modeling global atmospheric circulations and forecasting the weather would improve if worldwide information on winds aloft were available. Accurate prediction of weather is important to agriculture, shipping, air traffic, and many other fields. Global system models of climate are of great importance. Current global atmospheric models use pressure measurements and thermodynamic properties to calculate the effects of wind for use in Numerical Weather Prediction (NWP) models. Inputs to the NWP models are temperature, pressure and wind velocities at different heights. Clearly direct wind measurements could significantly improve the NWP model performance. The RAdar Wind Sounder (RAWS) program at the University of Kansas is a study of the feasibility and the trade-offs in the design of a space-based radar system to measure wind vectors. This can be done by measuring the Doppler shift of cloud and rain returns from three or more points and calculating the components of the wind vector. The RAWS study to date uses the candidate system selected after preliminary study of frequencies and sensitivities. Two frequencies chosen, 10 and 35 GHz, allow higher sensitivity for clouds and more penetration for rain. The past year was devoted to modeling the signal-to-noise ratio (SNR) achievable for the two frequencies. The determination of SNR versus cloud penetration depth used a cloud backscattering and attenuation model in the appropriate radar equation. Calculations assumed reasonable losses in reception and transmission, in addition to the atmospheric attenuation. We discovered that ice clouds provide a higher SNR than previously calculated, but some water clouds give lower SNRs than we calculated before. One of the primary issues in the SNR calculation was the choice of the drop size distribution. Although Xin used several distributions (e.g., log normal, Khrigian and Mazin), this year we used the Deirmendjian cloud model. SNR versus cloud penetration plots were generated to validate the candidate system. Rain, which appears in the cloud models at the lower altitudes, provides ample SNR, as do the higher clouds composed of ice particles. However, in some cloud situations we found the sensitivity for the clouds was marginal or inadequate. At 35 GHz, two of the cloud models characterized by 1 to 2 g/cu m of water content at altitudes extending from 150 to 1500 meters, produced a sufficient SNR. Other models, however, with water contents ranging from 0.5 to 4 g/cu m and altitudes up to 4000 meters, exhibit SNR of -3 to -23 dB, largely because of attenuation in the upper cloud layers. These results coupled with the lower SNR at 10 GHz, led to an investigation of alternate frequencies. The rain present beneath these clouds provides adequate SNR at 10 GHz, and in most cases, at GHz.

Moore, Richard K.↗

DOE OSTI2025

In Situ Atmospheric Plume Thermometry via Carbon Monoxide Spectral Profile: Laboratory and Field Validation

For small molecules with large rotational constants, knowing the relative intensities of the ro-vibrational transitions can be used to determine the temperature within a gas plume. We demonstrate the use of carbon monoxide (CO) as an in situ spectroscopic probe of gas plume temperature by application of both laboratory and standoff Fourier transform infrared spectroscopy to monitor the CO spectral response at different temperatures. Here, the measured CO rotational contours were analyzed using a simple Boltzmann model to deduce the population distribution of the J-levels, from which the in-plume temperature is deduced. The method was vetted by comparing deduced temperatures in both static laboratory measurements of known temperatures, as well as field measurements using a simulated smokestack release. For the smokestack experiments, spectroscopically deduced temperatures were compared to readings from a series of thermocouples placed at strategically sampled distances along the plume trajectory. Both the spectroscopically-derived and thermocouple-measured temperatures revealed an expansion-induced (mixing) rapid cooling of the plume, with the infrared thermometry values displaying greater temperature values which are believed to better represent the actual plume temperatures.

Analysis of rotational structure↗

DOE OSTI2022

Minimizing Fraud in the Carbon Offset Market Using Blockchain Technologies

Fraud in the Environmental Benefit Credit (EBC) markets is pervasive. To make matters worse, the cost of creating EBCs is often higher than the market price. Consequently, a method to create, validate, and verify EBCs and their relevance is needed to mitigate fraud. The EBC market has focused on geologic (fossil fuel) CO 2 sequestration projects that are often over budget and behind schedule and has failed to capture the "lowest hanging fruit" EBCs - terrestrial sequestration via the agricultural industry. This project reviews a methodology to attain possibly the least costly EBCs by tracking the reduction of inputs required to grow crops. The use of bio- stimulant products, such as humate, allows a farmer to use less nitrogen without adversely affecting crop yield. Using less nitrogen qualifies for EBCs by reducing nitrous oxide emissions and nitrate runoff from a farmer's field. A blockchain that tracks the bio-stimulant material from source to application provides a link between a tangible (bio-stimulant commodity) and the associated intangible (EBCs) assets. Covert insertion of taggants in the bio-stimulant products creates a unique barcode that allows a product to be digitally tracked from beginning to end. This process (blockchain technology) is so robust, logical, and transparent that it will enhance the value of the associated EBCs by mitigating fraud. It provides a real time method for monetizing the benefits of the material. Substantial amounts of energy are required to produce, transport, and distribute agricultural inputs including fertilizer and water. Intelligent optimization of the use of agricultural inputs can drive meaningful cost savings. Tagging and verification of product application provides a valuable understanding of the dynamics in the water/food energy nexus, a major food security and sustainability issue. As technology in agriculture evolves so to must methods to verify the Enterprise Resource Planning (ERP) potential of innovative solutions. The technology reviewed provides the ability to combine blockchain and taggants ("taggant blockchains") as the engine by which to (1) mitigate fraudulent carbon credits; (2) improve food chain security, and (3) monitor and manage sustainability. The verification of product quality and application is a requirement to validate benefits. Recent upgrades to humic and fulvic quality protocols known as ISO CD 19822 TC134 offers an analytical procedure. This work has been assisted by the Humic Products Trade Association and International Humic Substance Society. In addition, providing proof of application of these products and verification of the correct application of prescriptive humic and bio-stimulant products is required. Individual sources of humate have unique and verifiable characteristics. Additionally, methods for prescription of site- specific agricultural inputs in agricultural fields are available. (See US Patents 734867B2, US 90658633B2.) Finally, a method to assure application rate is required through the use of taggants. Sensors using organic solid to liquid phase change nanoparticles of various types and melting temperatures added to the naturally occurring materials provide a barcode. Over 100 types of nanoparticles exist ensuring numerous possible barcodes to reduce industry fraud. Taggant materials can be collected from soil samples of plant material to validate a blockchain of humic, fulvic and other soil amendment products. Other non-organic materials are also available as taggants; however, the organic tags are biodegradable and safe in the environment allowing for use during differing application timeliness.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2024

Artificial Intelligence Medical Support for Long-Duration Space Missions

We envision an artificial intelligence (AI) based system that will provide support and recommendations to the crew medical officer (CMO) and ground flight surgeon during long-duration space missions. Such a system would be pretrained on the knowledgebase of clinical knowledge on Earth, minimizing the amount of Earth data that needs to be transferred into space. Then during deployment, the system would be constantly refined through active learning from diverse streams of data from sensors in the spacecraft, data collected daily from individual astronauts, and human-in-the-loop feedback from the crew. The model could be interrogated for predictions and recommendations on personalized crew health based on the overall status of the spacecraft, medicinal stores, and status of other crew members. Adaptation techniques would be used to incorporate spaceflight data that have very different distributions from the training data due to the extreme environment. Edge computing and the most advanced neuromorphic processing would enable computation in scenarios with low power and bandwidth, while dimensionality reduction would be employed to ensure that the input data streams from spaceflight are as small as possible. In order to realize this long-term vision, several hardware and software aspects need to be developed and assembled. First, models pretrained on Earth biomedical data would need to be evaluated for predictive accuracy, and the best one selected. That model would need to be adapted to learn from diverse, sparse, and inconsistently measured data streams, as well as human-in-the-loop feedback. A data integration, standardization, and dimensionality reduction methodology would need to be developed to handle all data types and feed them into the model. Once the software and data infrastructure is developed, it would need to be integrated with small footprint compute processors and tested in high-radiation, high-vibration, unregulated temperature situations. As a short-term goal, we recommend to focus on the development of the data and model software structure. Several large language models (LLM) already exist that have been trained on Earth biomedical and clinical knowledgebases, including BioMedLLM, Med-PaLM, SPOKE LLM, and Foresight. These models need to be evaluated for accuracy and the best one chosen for a proof-of-concept structure, while maintaining awareness of the accelerating AI field and incorporating any newly improved model architectures as needed. Then, we recommend to develop a database of synthetic data types to mimic the diverse data streams that are expected in a long-duration space mission. This should include environmental and microbial data from the spacecraft, non-invasive data from wearables and point-of-care devices employed by astronauts, and more invasive molecular and physiological monitoring of clinical and biomarker data from astronauts. The data standardization methodology should be developed, and these data streams used to refine the clinical LLM. Several scenarios should be developed that could plausibly come up in a long-duration space mission, and changes or aberrations introduced to the data at specific times to mimic these scenarios. Then, question and answer tasks should be designed to interrogate the model for predictions and recommendations, with acceptable answers already identified.

Artificial Intelligence↗

NASA NTRS2019

Sea Surface Salinity Distribution in the Southern Ocean as Observed from Space

Large-scale spatial and temporal variabilities of sea surface salinity (SSS) in the Southern Ocean from 2011 to 2017 were studied using products derived from microwave sensors on board Aquarius, Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active and Passive (SMAP) satellites. Four products, three from Aquarius and one from SMOS, were evaluated and shown to be generally consistent within 0.3 to 0.6 psu and agree favorably with in situ measurements. However, although the Aquarius products show consistent seasonality of SSS with high values of 34.45 psu in October and low values of 33.40 psu in May, theSMOS and SMAP products lack such seasonal variations. This may be caused by larger uncertainties in the SMOS and SMAP data due in part to the lack of concurrent scatterometer measurements that is used to correct for roughness effects. The four products provide similar spatial distributions of SSS with root mean square difference from 0.25 to 0.58 psu. Differences among Aquarius products are mainly due to varying salinity retrieval algorithms, smoothing, and masking of sea ice, while the SMOS product showed the highest SSS deviation that is likely due to the bias adjustment done on the data set. Our analyses show that SSS in the Southern Ocean region has significant meridional variations with the lowest SSS near the ice edge and highest at lower latitudes. The SSS is also lowest in summer indicating the predominant influence of sea ice and glacial melt, but it stays low near ice edges even during the growth season. Salinity together with temperature is the key parameters that control the state and circulation of the World's oceans. The large‐scale distribution of the sea surface salinity of the Southern Ocean is quantified for the first time using Aquarius, Soil Moisture and Ocean Salinity, and Soil Moisture Active and Passive satellite microwave data. Seasonal and interannual changes in the distribution as affected by the sea ice cover, surface temperature, and precipitation are evaluated. Comparative studies were done, using four different products that are publicly available, in conjunction with in situ observations to gain insights into the true nature of the distribution and how consistently the sea surface salinity is depicted by the different products. There are general consistencies in the products, and discrepancies are attributed to different algorithms, smoothing techniques, and sea ice masking. Aquarius data are shown to have higher accuracy than Soil Moisture and Ocean Salinity and Soil Moisture Active and Passive products in part because of having concurrent scatterometer that provides accurate correction to roughness effects.

Garcia-Eidell, Cynthia↗

NASA NTRS2001

Large Scale Characteristics and Variability of the Global Sea Ice Cover

More than two decades of satellite passive microwave data are used to study and evaluate the large scale characteristics and the changing state of the sea ice cover in both the Northern and Southern Hemispheres. Satellite data provide day/night almost continuous observation of global sea ice cover thereby enabling quantitative variability studies at various time scales. Despite coarse sensor resolution, spatial detail is provided through the use of sea ice concentrations which are derived using an algorithm that determines the fraction of ice and open water within each satellite footprint. Large seasonal fluctuations in the extent are apparent with those of the Southern Hemisphere having larger amplitudes but less symmetrical seasonal distribution than those of the Northern Hemisphere. The large scale interannual variability of the ice cover has been evaluated globally as well as regionally and in the Northern Hemisphere, the yearly anomaly maps show a predominance of positive values in the 1980s and negative values in the 1990s. Regression analysis show that the ice extent and ice area are on a decline at the rate of -2.0 +/- 0.5% and -3.1 +/- 0.3% per decade, respectively, in the Northern Hemisphere but there are regions like the Bering Sea with positive trends. What is intriguing, however, is that the perennial sea ice cover has been declining at a much faster rate than for the entire hemisphere, i.e., 6.7 +/- 2.4% and 8.3 +/- 2.4 % per decade for ice extent and ice area, respectively. The perennial ice cover consists mainly of thick multiyear ice floes, and its persistent decline would mean a reduction in the average thickness of sea ice and a change in the overall characteristics of the Arctic sea ice cover. Furthermore, the yearly anomaly patterns are coherent with those of surface temperatures derived from 19 years of thermal infrared AVHRR data. The latter also shows that in consolidated ice regions, the average temperature during summer minima has been increasing at about 0.9 +/- 0.6 K per decade.

Comiso, Josefino C.↗

NASA NTRS2017

Development and Testing of a Friction-Based Post-Installable Fiber-Optic Monitoring System for Subsea Applications

This paper presents the design and development of a friction-based coupling device for a fiber-optic monitoring system capable of measuring pressure, strain, and temperature that can be deployed on existing subsea structures. A summary is provided of the design concept, prototype development, prototype performance testing, and subsequent design refinements of the device. The results of laboratory testing of the first prototype performed at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) are also included. Limitations of the initial concept were identified during testing and future design improvements were proposed and later implemented. These new features enhance the coupling of the sensor device and improve the monitoring system measurement capabilities. A major challenge of a post-installed instrumentation monitoring system is to ensure adequate coupling between the instruments and the structure of interest for reliable measurements. Friction-based devices have the potential to overcome coupling limitations caused by marine growth and soil contamination on flowlines, risers, and other subsea structures. The work described in this paper investigates the design and test of a friction-based coupling device (herein referred to as a friction clamp) which is suitable for pipelines and structures that are suspended in the water column as well as for those that are resting on the seabed. The monitoring elements consist of fiberoptic sensors that are bonded to a stainless steel clamshell assembly with a high-friction surface coating. The friction clamp incorporates a single hinge design to facilitate installation of the clamp and dual rows of opposing fasteners to distribute the clamping force along the structure. The friction clamp can be modified to be installed by commercial divers in shallow depths or by remotely operated vehicles in deep-water applications. NASA-JSC was involved in the selection and testing of the friction coating, and in the design and testing of the prototype clamp device. Four-inch diameter and eight-inch diameter sub-scale friction clamp prototypes were built and tested to evaluate the strain measuring capabilities of the design under different loading scenarios. The testing revealed some limitations of the initial design concept, and subsequent refinements were explored to improve the measurement performance of the system. This study was part of a collaboration between NASA-JSC and Astro Technology Inc. within a study called Clear Gulf. The primary objective of the Clear Gulf study is to develop advanced instrumentation technologies that will improve operational safety and reduce the risk of hydrocarbon spillage. NASA provided unique insights, expansive test facilities, and technical expertise to advance technologies that will benefit the environment, the public, and commercial industries.

Bentley, Nicole L.↗

NASA NTRS2000

Seven-Year SSM/I-Derived Global Ocean Surface Turbulent Fluxes

A 7.5-year (July 1987-December 1994) dataset of daily surface specific humidity and turbulent fluxes (momentum, latent heat, and sensible heat) over global oceans has been retrieved from the Special Sensor Microwave/Imager (SSM/I) data and other data. It has a spatial resolution of 2.0 deg.x 2.5 deg. latitude-longitude. The retrieved surface specific humidity is generally accurate over global oceans as validated against the collocated radiosonde observations. The retrieved daily wind stresses and latent heat fluxes show useful accuracy as verified by those measured by the RV Moana Wave and IMET buoy in the western equatorial Pacific. The derived turbulent fluxes and input variables are also found to agree generally with the global distributions of annual-and seasonal-means of those based on 4-year (1990-93) comprehensive ocean-atmosphere data set (COADS) with adjustment in wind speeds and other climatological studies. The COADS has collected the most complete surface marine observations, mainly from merchant ships. However, ship measurements generally have poor accuracy, and variable spatial coverages. Significant differences between the retrieved and COADS-based are found in some areas of the tropical and southern extratropical oceans, reflecting the paucity of ship observations outside the northern extratropical oceans. Averaged over the global oceans, the retrieved wind stress is smaller but the latent heat flux is larger than those based on COADS. The former is suggested to be mainly due to overestimation of the adjusted ship-estimated wind speeds (depending on sea states), while the latter is suggested to be mainly due to overestimation of ship-measured dew point temperatures. The study suggests that the SSM/I-derived turbulent fluxes can be used for climate studies and coupled model validations.

Chou, Shu-Hsien↗

DOE OSTI2021

Smart Methane Emission Detection System Development (Final Report)

Working with the Department of Energy’s National Energy Technology Laboratory, Southwest Research Institute® (SwRI®) developed a system to identify methane leaks reliably, accurately, and autonomously at critical midstream sections of the natural gas distribution network in real- time for the purpose of mitigating methane emissions using Optical Gas Imaging (OGI) cameras. SwRI’s Smart Leak Detection – Methane (SLED/M) adds a high degree of automation to the process of methane leak detection to minimize sources of human error, minimize response time to a leak event, and maximize midstream visibility. Furthermore, SwRI has been working towards integrating Quantitative OGI (QOGI) capabilities into this existing technology. By leveraging Deep Learning, SwRI now has the capability to estimate fugitive emission leak rates quickly and reliably, which allows operators to detect emissions, quantify leak rate, prioritize repairs, and validate the repairs in a single instrument. The next generation QOGI technology leverages the same cameras used in Leak Detection and Repair (LDAR) programs, with improvements in safety and speed for traditional quantification-based repairs, ultimately leading to less overhead cost for the operators. The goals for this research were to develop two types of models with the following goals: 1. Run in real-time on the edge (≥ 12 Hz) 2. Classification: Achieve less than 5% false positive detection 3. Classification: Achieve ≥ 95% methane plume detection rate 4. Regression: achieve ≤ 10 standard cubic feet per hour (scfh) prediction > 70% of the time In order to achieve these results, multiple infrared (IR) and other sensors were investigated in tandem with the midwave IR (MWIR) OGI to provide additional information to train the underlying models. Information on atmospheric conditions including humidity, temperature, pressure, and solar radiation was provided by a weather station. Several machine learning and deep learning architectures and methods, including looking at quantized classification networks and regressions networks, were explored. As further data was collected, curated, and labeled, it allowed for more refined regressive networks to be adequately trained, leading to better insight into the true flow rates being observed. An important valuable deliverable of this research effort was the development of an advanced network which underwent multiple iterations capable of giving a continuous output. The current network has a predicted mean average percentage error (MAPE) of 12.3% just outside our target goal of 10.00%, but an accuracy of 97.78% at ±50 scfh, well within the overall goal for the Department of Energy (DOE) program. Upon closer inspection, it was observed that more than 10% of datapoints contributing to the MAPE predictions were the result of low flow rate predictions and are beyond the sensitivity of instrument measurement as a result of normal operational variation and noise.

03 NATURAL GAS↗

NASA NTRS1995

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Comiso, Joey C.↗

DOE OSTI2015

Wireless and chip-less passive radiation sensors for high dose monitoring

The safety of nuclear infrastructures may involve the monitoring of many parameters in harsh environments (high radiation level, high temperature, high pressure,..). If technological solutions exist for transducers part in such environments, the electronic part used in reader is not appropriate and still a challenging task. Well-known solutions to remove the electronic part from the harsh environment consist of connecting the transducer and the reader by long electrical wires or performing ex situ remote sensing. However wires may practically be difficult to implement while ex situ measurements are not compatible with on line monitoring. Wireless and passive sensors working in harsh environments could be an appropriate solution for the remote sensing of critical parameters. Passive sensors without electronics in the sensing unit are available (e.g., SAW sensors) but they suffer from short reading range (typically lower than 10 meters). In order to overcome this range limitation a new class of electromagnetic transducers was developed in the mid-2000's. The operating principle is based on the modification of the properties of high-frequency (>> 1 GHz) passive electromagnetic devices by the quantity to be measured. Based on this principle a wide range of sensing properties can be addressed and a large number of materials can be chosen. Moreover the use of high frequency allows reducing the size of the sensor elements (antenna, transducer) and enhancing the immunity to multi-path. Several principles of RF transducers have been already validated by LAAS-CNRS (e;g; pressure, temperature, stress) as well as radar-based solution for the wireless long-range sensors interrogation. The sensor dosimeter exploit here the known property of Hydrogen-Pressure Dosimeters (HPD) for which the polymer material dehydrogenates under nuclear irradiation. The transducer principle is described. The irradiation will generate the out-gazing (hydrogen) of the polymer inside a micro-chamber. The resulting overpressure leads to the deflection of a silicon membrane which modifies the resonant frequency of the RF resonator. Tests structures have been designed in order to quantify the HDPE out-gazing inside a micro-cavity by measuring the deflection of a boss silicon membrane with a mechanical profiler. A specific set up using interferometry method has been also developed to evaluate the pressure generated inside the micro-cavity. The procedure consists in applying a pressure that pushes the membrane to recover a flat membrane. This condition is monitored thanks to the extinction of the Newton rings. Irradiations have been performed up to 30 kGy using 6 MeV focused e-beam providing by electron accelerator. Membrane deflection and generated pressure around 0.2 μm/mg{sub HDPE}/kGy and 70 mbar/mg{sub HDPE}/kGy has been obtained for a 70 μm thick membrane. In order to characterize the hermetic sealing of the micro-chamber under hydrogen over-pressure, membrane deflection after irradiation has been recorded during 50 days. The variations of membrane deflection are randomly distributed and generally lower than ±5%, showing a good hermeticity during this period. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗