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Automated Detection of Events of Scientific Interest

A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

James, Mark↗

Model Agnostic Bayesian Framework for Online Anomaly/Event Detection in PMU Data

Phasor measurement units (PMU) are integral to the modernization and automation plan of the electric power industry. A PMU data signature contains system-level events (e.g., faults, generation/load change, etc.) and any measurement/device-related errors. Therefore, the reliable and resilient operation of power systems is equivalent to the quality of the PMU data and the situation awareness provided by its data signature. Despite recent progress, current state-of-the-art methods are not fool-proof and have certain limitations tracing an error/abnormality to sensor sub-components and grid systems. This is because of technical challenges imposed by the scarcity of the labeled information, loss of data quality, and non-stationarity of data. In this paper, we consider the online PMU data stream as an output of a stochastic process and pose the anomaly/event detection as a changepoint detection problem dealing with detecting parameter changes in the underlying stochastic processes. The proposed model-agnostic framework relies on: (a) feature extraction utilizing the minimum volume enclosing ellipsoids (MVEE) method from raw PMU observations and (b) a Bayesian framework of changepoint detection. The validity of the proposed methodology is discussed through numerical experiments on real-world utility-scale PMU data.

Hossain, Ramij Raja↗

Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies. Leveraging real-time operational data from the AGN-201 DT, the IFML algorithm identifies outliers without prior data labeling and operates as a lightweight, complementary approach to traditional physics-based anomaly detection methods for nuclear safeguards. In a simulated Red vs. Blue team exercise, the IFML algorithm successfully detected six significant unseen anomalies related to reactivity changes, achieving an accuracy of 99% for identifying operational deviationxs. These anomalies, caused by deliberate perturbations, were detected alongside known physics-based models, underscoring the potential of IFML to enhance real-time monitoring without displacing traditional methods. Further, this study highlights the applicability of IFML in nuclear environments by providing an additional, redundant layer of anomaly detection to improve safeguards and operational safety in complex systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Biomechanical Approach to Assessing Hip Fracture Risk

Bone loss in microgravity is well documented, but it is difficult to quantify how declines in bone mineral density (BMD) contribute to an astronaut's overall risk of fracture upon return. This study uses a biomechanical approach to assessing hip fracture risk, or Factor of Risk (Phi), which is defined as the ratio of applied load to bone strength. All long-duration NASA astronauts from Expeditions 1-18 were included in this study (n=25), while crewmembers who flew twice (n=2) were treated as separate subjects. Bone strength was estimated based on an empirical relationship between areal BMD at the hip, as measured by DXA, and failure load, as determined by mechanical testing of cadaver femora. Fall load during a sideways fall was calculated from a previously developed biomechanical model, which takes into account body weight, height, gender, and soft tissue thickness overlying the lateral aspect of the hip that serves to attenuate the impact force. While no statistical analyses have been performed yet, preliminary results show that males in this population have a higher FOR than females, with a post- flight Phi of 0.87 and 0.36, respectively. FOR increases 5.1% from preflight to postflight, while only one subject crossed the fracture "threshold" of Phi = 1, for a total of 2 subjects with a postflight Phi > 1. These results suggest that men may be at greater risk for hip fracture due largely in part to their relatively thin soft tissue padding as compared to women, since soft tissue thickness has the highest correlation (R(exp 2)= .53) with FOR of all subject-specific parameters. Future work will investigate changes in FOR during recovery to see if baseline risk levels are restored upon return to 1-g activity. While dual x-ray absorptiometry (DXA) is the most commonly used clinical measure of bone health, it fails to provide compartment-specific information that is useful in assessing changes to bone quality as a result of microgravity exposure. Peripheral quantitative computed tomography (pQCT) accomplishes this by imaging transverse "slices" of the long bones. This project was a re-analysis of a 90 day bed rest study to determine if changes to cortical and trabecular compartments could be detected in the distal tibia with statistical significance using a new pQCT image analysis method. Nearly all changes in bone mineral density (BMD) and cross sectional area (CSA) measures were seen with statistical significance, with the exception of a change in cortical BMD. Total bone CSA increased by 1.1 % (p =0.01), cortical CSA decreased by - 5.6% (p<0.001) and trabecular CSA increased by 1.76% (p=0.007); the combination of which suggests bone resorption occurred at the endocortical surface in response to mechanical unloading by bed rest. Furthermore, total BMD and trabecular BMD decreased (-3.8%, p=0.001 and -2.8%, p =0.007, respectively), while decreases in cortical BMD failed to reach significance (-1.2%, p=0.07). Given that compartment-specific changes are seen with significance and are likely to influence bone strength, it is recommended that pQCT remain a standard measure used in bed rest because it provides a unique measure by which to better evaluate the efficacy of countermeasures to microgravity-induced bone loss.

Ellman, Rachel↗

Chemical Schemes for Surface Modification of Icy Satellites: A Road Map

The icy Galilean Satellites of Jupiter are subject to magnetospheric plasma ion bombardment which induces chemical changes within the ice. The possible detection of CO2 on the surface of Ganymede by the Galileo spacecraft makes for a more complicatred chemistry and increases the number of chemical compounds that may then be present.

Galileo↗

Rapid Biochemical Analysis on the International Space Station (ISS): Preparing for Human Exploration of the Moon and Mars

The Lab-on-a-Chip Application Development - Portable Test System, known as LOCAD-PTS, was launched to the International Space Station (ISS) aboard Space Shuttle Discovery (STS-116) on December 9th,2006. Since that time, it has remained onboard ISS and has been operated by the crew on 10 separate occasions LOCAD-PTS is a handheld device for rapid biochemical analysis; it consists of a spectrophotometer, a series of interchangeable cartridges, a pipette and several clean/sterilized swabbing kits to obtain samples from ISS surfaces. Sampling, quantitative analysis and data retrieval is performed onboard, therefore reducing the need to return samples to Earth. Less than 20 minutes are required from sampling to data, significantly faster than existing culture-based methods on ISS, which require 3-5 days. Different cartridges are available for the detection of different target molecules (simply by changing the formulation within each cartridge), thereby maximizing the benefit and applications addressed by a single instrument. Initial tests on ISS have focused on the detection of the bact.erial macromolecule endotoxin, a component of bacterial cell walls. LOCAD-PTS detects endotoxin with a cartridge that contains a formulation known as Limulus Amebocyte Lysate (LAL) assay. LAL is derived from blood of the horseshoe crab, Limulus polyphemus, and detects enodotoxin with an enzyme cascade that triggers generation Of a yellow colored dye, p-nitroanaline. The more p-nitroanaline product, the more endotoxin is in the original sample. To enable quantitative analysis, the absorbance of this color is measured by LOCAD-PTS through a 395 nm filter and compared with an internal calibration curve, to provide a reading on the LED display that ranges from 0.05 Endotoxin Units (EU)/ml to 5 EU/ml. Several surface sites were analyzed within ISS between March 2007 and February 2008, including multiple locations in the US Laboratory Destiny, Node 1 Unity, AMock, and Service Module Zvezda. The goals of this initial study were to i) test the cleanliness of reagents/supplies on orbit, ii) test the crew's ability to collect and process a sample in microgravity without contamination, iii) demonstrate nominal function of the LOCAD-PTS, and iv) provide a general survey of endotoxin within the ISS. The surface sites varied greatly in terms of their frequency-of-use and material texture/composition; from relatively smooth aluminum, to fabric, to the room temperature vulcanizing (RTV) rubber of a Extravehicular Mobility Unit (EMU) spacesuit. Results showed that: i) the swabbing kits and reagents remained clean on orbit, ii) the crew could collect and process a sample without contamination, and iii) the LOCAD-PTS functioned nominally in > 99% of the 55 tests completed. We will present detailed results of the survey of endotoxin on ISS surfaces. These results and technology are important in the near-term - by providing an extra tool in the toolbox for ISS microbial monitoring. They are also important in the longer term as valuable preparation for human exploration of the Moon and Mars. One of the proposed science goals for the human exploration of Mars will be to detect and characterize any indigenous biological molecules that may exist on the Martian surface. To achieve that goal, the crew must have the technology available onboard to differentiate indigenous biology from any terrestrial biological material brought to Mars by the spacecraft and crew (termed 'forward contamination'). The LAL assay is already one of the official methods used by NASA's planetary protection program to certify cleanliness of interplanetary robotic spacecraft prior to launch; and therefore endotoxin is a good marker of forward contamination (as well as other microbial molecules detectable with LOCAD-PTS e.g. box-1, 3-glucan and lipoteichoic acid). Furthermore, the distribution and abundance of these molecules on the ISS provides a good indicator of what to expect on the Crew Exploratioehicle Orion, the lunar lander Antares, and future crewed spacecraft destined for Mars. In addition, technology such as LOCAD-PTS has been proposed to help evaluate forward contamination during lunar surface operations by the crew, as preparation for the human exploration of Mars.

Maule, J.↗

Distributed Outage Detection in Power Distribution Networks

Real time topology knowledge is essential for situational awareness of power distribution networks. Line outages change the topology of a distribution network. Hence, outage detection is an important task. Most of the existing outage detection algorithms are centralized, in which sensors communicate their data to a control center which performs outage detection using the received data. However, with the increasing size of the distribution network and with different areas of the network being monitored by different operators, communication is a bottleneck and scalability is a major concern. To address these issues, we propose a novel outage detection algorithm using a divide and conquer approach. First, we divide a distribution network into sub-networks, such that outage detection can be run in parallel in each sub-network independently ensuring scalability to large networks. Further, to reduce the latency, bandwidth and attenuation challenges associated with communications in a large network, we divide each sub-network into multiple control areas which communicate only with their neighbors. We employ a distributed iterative load estimation across the control areas of each sub-network and then use the load estimate for local outage detection in each control area. Here, the performance of our algorithm is evaluated for multiple feeder models and compared against traditional centralized outage detection algorithms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Bhutan Water Resources III: Analyzing Forest Disturbances and Climate Data in Bhutan to Create a Tool for Assisting the Himalayan Environment Rhythm Observation and Evaluation Systems (HEROES) Project

Forest disturbances from bark beetle outbreaks are a major concern in Bhutan, known to cause extensive tree mortality to pine and spruce forests. The NASA DEVELOP team partnered with the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER), the Bhutan Foundation, and the Karuna Foundation to assess forest changes for the districts of Bumthang and Haa from 2000 to 2018. The project used preprocessed meteorological data from the Climate Hazards Center Infrared Precipitation with Station (CHIRPS) and Famine Early Warning System Network Land Data Assimilation System (FLDAS), along with Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) to assess apparent forest disturbance occurrences and observed climate trends. Shuttle Radar Topography Mission (SRTM) was used to resolve variations in elevation and slope for mountainous regions. Using the Google Earth Engine LandTrendr (LT) code algorithm, along with Landsat data, the team developed an app called Forest Disturbances Detection Toolbox (FDDT) to assess forest changes in Bhutan. The app includes climate variables for the focus districts, along with LT variables, which allows the end users to further examine the cause of disturbances. The team compared geocoordinates for known disturbances with LT disturbance detection products. Although additional work is needed in the future to validate the project end products from the FDDT, the tool will be provided to the project partners to aid forest management efforts in Bhutan.

Tashi Choden↗

Temperature lapse rate as an adjunct to wind shear detection

Several meteorological parameters were examined to determine if measurable atmospheric conditions can improve windshear detection devices. Lapse rate, the temperature change with altitude, shows promise as being an important parameter in the prediction of severe wind shears. It is easily measured from existing aircraft instrumentation, and it can be important indicator of convective activity including thunderstorms and microbursts. The meteorological theory behind lapse rate measurement is briefly reviewed, and and FAA certified system is described that is currently implemented in the Honeywell Wind Shear Detection and Guidance System.

Zweifil, Terry↗

Discrimination among semi-arid landscape endmembers using the Spectral Angle Mapper (SAM) algorithm

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were acquired during three consecutive seasons of the year (26 Sep. 1989, 22 Mar. 1990, and 7 Aug. 1990) over an area of the High Plains east of Greeley, Colorado. This region contains extensive eolian deposits in the form of stabilized dune complexes (small scale parabolic dunes superimposed on large scale longitudinal and parabolic dunes). Due to the dunes' large scale (2-10 km) and low relief (1-5 m), the scaling relationships that contribute to the evolution of this landscape are nearly impossible to understand without the use of remote sensing. Additionally, climate models indicate that the High Plains could be one of the first areas to experience changes in climate caused by either global warming or cooling. During the past 10,000 years there were at least three periods of extensive sand activity, followed by periods of landscape stability, as shown in the stratigraphic record of this area. Therefore, if the past is an indication of the future, the monitoring of this landscape and its sensitive ecosystem is important for early detection of regional and global climate change.

Yuhas, Roberta H.↗

Exceptional stratospheric contribution to human fingerprints on atmospheric temperature

In 1967, scientists used a simple climate model to predict that human-caused increases in atmospheric CO 2 should warm Earth’s troposphere and cool the stratosphere. This important signature of anthropogenic climate change has been documented in weather balloon and satellite temperature measurements extending from near-surface to the lower stratosphere. Stratospheric cooling has also been confirmed in the mid to upper stratosphere, a layer extending from roughly 25 to 50 km above the Earth’s surface (S 25 − 50 ). To date, however, S 25 − 50 temperatures have not been used in pattern-based attribution studies of anthropogenic climate change. Here, we perform such a “fingerprint” study with satellite-derived patterns of temperature change that extend from the lower troposphere to the upper stratosphere. Including S 25 − 50 information increases signal-to-noise ratios by a factor of five, markedly enhancing fingerprint detectability. Key features of this global-scale human fingerprint include stratospheric cooling and tropospheric warming at all latitudes, with stratospheric cooling amplifying with height. In contrast, the dominant modes of internal variability in S 25 − 50 have smaller-scale temperature changes and lack uniform sign. These pronounced spatial differences between S 25 − 50 signal and noise patterns are accompanied by large cooling of S 25 − 50 (1 to 2 ° C over 1986 to 2022) and low S 25 − 50 noise levels. Our results explain why extending “vertical fingerprinting” to the mid to upper stratosphere yields incontrovertible evidence of human effects on the thermal structure of Earth’s atmosphere.

climate modeling↗

Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics

Bottom-up proteomic workflows rely on sequential preprocessing steps, commonly including peptide-to-protein aggregation (“roll-up”), to enhance data reliability and interpretability. While roll-up is effective for protein-centered analyses, it may be suboptimal for applications focused on post-translational modifications (PTMs) or protein structural changes, such as limited proteolysis–mass spectrometry (LiP-MS). Here, we investigate how different roll-up strategies influence site-level quantification in PTM differential analysis. Moreover, we introduce a novel site-centric roll-up approach tailored for LiP-MS, which quantifies proteolytic fragments rather than solely tryptic peptides. We benchmark these methods through simulation studies, comparing their sensitivity and specificity in detecting structural and PTM-driven changes. We found that the median and mean roll-up methods outperform the sum method in both PTM and LiP proteomics, and site-level quantification in LiP outperforms peptide-level quantification. Our findings offer the first systematic, data-driven guidance for selecting roll-up techniques in site-level proteomic analyses, with implications for both PTM-focused and structural proteomics studies.

aggregation↗

Dynamic Light-Scattering Probe Used for the Very Early Detection of Cataracts and to Measure Response to Therapy (or Treatment)

Half of all blindness worldwide is due to cataracts, and 34 million Americans over the age of 65 have cataracts. This figure is expected to rise to 70 million by the year 2030. Currently, no medical treatment is available to prevent or halt the progression of a cataract; nor is there any way to reverse a cataract once it has been detected by conventional methods. The only known treatment is surgical removal of the lens. It is estimated that over $5 billion will be spent this year for the treatment of cataract patients in the United States alone. According to Carl Kupfer, M.D., former Director of the National Eye Institute at the National Institutes of Health, "A delay in cataract formation of about 10 years would reduce the prevalence of visually disabling cataracts by about 45 percent." However, this vision remains a dream because of the lack of objective methods that can be used to detect cataracts very early and, hence, can be used for screening potential anticataract drugs. This is about to change. The National Eye Institute and NASA entered into a formal interagency agreement in late 1996 to develop and test a dynamic light-scattering (DLS) device to detect the earliest changes due to cataract formation. The new DLS probe developed by Dr. Ansari at the NASA Glenn Research Center is several orders of magnitude more sensitive than conventional clinical systems. This ultrahigh sensitivity enables the probe to detect the onset of a cataract before it has any effect on vision and allows researchers to test the effectiveness of anticataract drugs in reversing cataracts. This device (see the following illustration) was originally designed to study transport phenomena in microgravity fluid physics experiments onboard the space shuttle orbiters and space station. It will be very useful in testing anticataract drugs to halt or reverse the progression of cataracts during longitudinal clinical trials.

Ansari,Rafat R.↗

The atmospheric excitation of earth orientation changes during MERIT

Geodetic estimates of earth orientation variations detected during the MERIT campaign (September 1983-November 1984) are compared with corresponding meteorological data. The geodetic data were obtained using VLBI, lunar laser ranging, and satellite laser ranging and the meteorological data were from the NMC in the U.S. and the European Centre for Medium Range Weather Forecasting (ECMRWF) in the U.K. The effects of changes in pressure, wind, and the inverted barometer ocean response on the excitation of the polar motion and the length of day are examined. The comparison between the meteorological and geodetic data reveals that the equatorial vector component of the atmospheric angular momentum (AAM) has significant annual and semiannual variations. Good correlation is detected between the geodetic polar motion data and the NMC pressure inverted barometer data combined with the ECMRWF wind estimates and semiannual agreement with the NMC pressure data is observed. There is also good correlation between the ECMRWF and NMC polar vector component of the AAM data and the geodetic length of day estimates, and good semiannual agreement with NMC pressure data is noted.

Eubanks, T. M.↗

Magnetoelastic properties of multiferroic hexagonal ErMnO 3

Here, the strength and dynamics of magnetoelastic coupling through the paramagnetic (PM) – antiferromagnetic (AFM) – ferrimagnetic (FIM) transitions in multiferroic hexagonal ErMnO 3 have been investigated by Resonant Ultrasound Spectroscopy. Elastic stiffening by up to 2% below the PM – AFM transition at 80 K arises from biquadratic coupling between strain and the magnetic order parameter with relaxation times longer than ~10 -6 s for the response of spins to changes in strain. In contrast with YMnO 3 , the PM – AFM transition in ErMnO 3 is accompanied by a peak in acoustic loss immediately below the Néel point which is interpreted in terms of strain relaxation accompanying ordering of spins of Er 3+ at 4b sites. Changes in the magnetic ordering scheme at the AFM – FIM transition near 3 K are accompanied by elastic softening of ~0.03 %. During poling of the low temperature ferrimagnetic structure round magnetic hysteresis loops, small changes in elastic stiffness which arise due to the contribution of piezomagnetic and/or piezoelectric moduli are detected. Contributions of piezoelectric moduli to acoustic resonance frequencies also permit changes in the configuration of ferroelectric domains to be detected in response both to cycling through this transition and to application of a magnetic field. A peak in acoustic loss in the vicinity of 250 K is attributed to strain-mediated pinning/freezing of some aspect of the domain microstructure with an activation energy of ~0.25–0.3 eV. A return to the original elastic properties on heating to temperatures above ~250 K is interpreted in terms of backswitching of domains to the configuration they had at the start. These observations confirm the existence of subtle variations in magnetoelastic coupling behaviour relating to both the magnetic order parameters and magnetic domain structures.

36 MATERIALS SCIENCE↗

Cardiac R-wave detector with automatic sensitivity control

An electronic circuit that automatically changes its sensitivity was developed for detecting the bioelectric signal resulting from activation of the heart's ventricles. Regulation of sensitivity was accomplished with two feedback channels that maintain the sensitivity level between an upper and a lower limit. These limits are proportional to the R-wave amplitude. Tests on an experimental circuit demonstrated a capability to reject unwanted signal noise, illustrated difficulties encountered without sensitivity control, and presented closed loop transients which occurred for step changes in R-wave amplitude.

Gebben, V. D.↗

Role of MODIS Vegetation Phenology Products in the ForWarn System for Monitoring of Forest Disturbances in the Conterminous United States

This presentation discusses MODIS vegetation phenology products used in the ForWarn Early Warning System (EWS) tool for near real time regional forest disturbance detection and surveillance at regional to national scales. The ForWarn EWS is being developed by the USDA Forest Service NASA, ORNL, and USGS to aid federal and state forest health management activities. ForWarn employs multiple historical land surface phenology products that are derived from MODIS MOD13 Normalized Difference Vegetation Index (NDVI) data. The latter is temporally processed into phenology products with the Time Series Product Tool (TSPT) and the Phenological Parameter Estimation Tool (PPET) software produced at NASA Stennis Space Center. TSPT is used to effectively noise reduce, fuse, and void interpolate MODIS NDVI data. PPET employs TSPT-processed NDVI time series data as an input, outputting multiple vegetation phenology products at a 232 meter resolution for 2000 to 2011, including NDVI magnitude and day of year products for seven key points along the growing season (peak of growing season and the minima, 20%, and 80% of the peak NDVI for both the left and right side of growing season), cumulative NDVI integral products for the most active part of the growing season and sequentially across the growing season at 8 day intervals, and maximum value NDVI products composited at 24 day intervals in which each product date has 8 days of overlap between the previous and following product dates. MODIS NDVI phenology products are also used to compute nationwide NRT forest change products refreshed every 8 days. These include percent change in forest NDVI products that compare the current NDVI from USGS eMODIS products to historical MODIS MOD13 NDVI. For each date, three forest change products are produced using three different maximum value NDVI baselines (from the previous year, three previous years, and all previous years). All change products are output with a rainbow color table in which forests with the most severe NDVI decreases are assigned hot colors (yellow to red) and forests with prominent NDVI increases are assigned cold colors (blue tones). All mentioned products have been integrated as data layers into ForWarn s geospatial data viewer known as the U.S. Forest Change Assessment Viewer (FCAV). The latter is used to view and assess the context of the mentioned forest change products with respect to ancillary data layers, such as land cover, elevation, hydrologic features, climatic data, storm data, aerial disturbance surveys, fire data, and land ownership. The FCAV also includes a temporal NDVI profiler for viewing phenological change in multi-year NDVI associated with known or suspected regionally apparent forest disturbances (e.g., from fire and insects). ForWarn forest change products have been used to detect, track, and assess several biotic and abiotic regional forest disturbance events across the country, including ephemeral and longer lasting damage from storms, drought, and insects. Such change products are most effective for viewing severe disturbances affecting multiple MODIS pixels. MODIS vegetation phenology products contribute vital current information on forest conditions to the ForWarn system and this role is expected to grow as these products are refined and derivative products are added.

Spruce, Joseph P.↗

Automatic Jet Contrail Detection and Segmentation

Jet contrails are an important subset of cirrus clouds in the atmosphere, and thin cirrus are thought to enhance the greenhouse effect due to their semi-transparent nature. They are nearly transparent to the solar energy reaching the surface, but they reduce the planetary emission to space due to their cold ambient temperatures. Having 'seeded' the environment, contrails often elongate and widen into cirrus-like features. However, there is great uncertainty regarding the impact of contrails on surface temperature and precipitation. With increasing numbers of subsonic aircraft operating in the upper troposphere, there is the possibility of increasing cloudiness which could lead to changes in the radiation balance. Automatic detection and seg- mentation of jet contrails in satellite imagery is important because (1) it is impractical to compile a contrail climatology by hand, and (2) with the segmented images it will be possible to retrieve contrail physical properties such as optical thickness, effective ice crystal diameter and emissivity.

Weiss, J.↗