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At least 325 records · Page 18

The Meteorology of Storms that Produce Narrow Bipolar Events

Narrow Bipolar Events (NBEs) are compact intracloud discharges that produce the most powerful lightning‐related radio frequency signals that have been observed. However, their luminosity is below the threshold for detectability from current and past spaceborne optical sensors. NBEs have been loosely associated with convective intensity, but their occurrence tends to be highly localized in time and space within a thunderstorm, and there remain many questions about whether and to what extent they are significantly related to meteorological processes within thunderstorms. Using the North Alabama Lightning Mapping Array (NALMA), the National Lightning Detection Network, and available Doppler and polarimetric radar data, case studies will be presented for storm events that produced large numbers of NBEs (~10s‐100s) during their lifetimes. NBEs are documented via a method that identifies high peak power (>40‐50 dBW) initial VHF sources within a specific altitude band in the upper levels of thunderstorms. The production of NBEs, including spatial and temporal variability, will be compared to the radar‐inferred kinematic and microphysical structure and evolution of thunderstorms, as well as their NALMA‐ and NLDN‐inferred electrical characteristics. The results should provide new insights into the relationships between NBEs and thunderstorm processes.

Lang, Timothy J.↗

An Intercomparison Between Radar Reflectivity and the IR Cloud Classification Technique for the TOGA-COARE Area

Satellite infrared (IR) and visible (VIS) images from the Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) experiment are investigated through the use of Clustering Analysis. The clusters are obtained from the values of IR and VIS counts and the local variance for both channels. The clustering procedure is based on the standardized histogram of each variable obtained from 179 pairs of images. A new approach to classify high clouds using only IR and the clustering technique is proposed. This method allows the separation of the enhanced convection in two main classes: convective tops, more closely related to the most active core of the storm, and convective systems, which produce regions of merged, thick anvil clouds. The resulting classification of different portions of cloudiness is compared to the radar reflectivity field for intensive events. Convective Systems and Convective Tops are followed during their life cycle using the IR clustering method. The areal coverage of precipitation and features related to convective and stratiform rain is obtained from the radar for each stage of the evolving Mesoscale Convective Systems (MCS). In order to compare the IR clustering method with a simple threshold technique, two IR thresholds (Tir) were used to identify different portions of cloudiness, Tir=240K which roughly defines the extent of all cloudiness associated with the MCS, and Tir=220K which indicates the presence of deep convection. It is shown that the IR clustering technique can be used as a simple alternative to identify the actual portion of convective and stratiform rainfall.

Carvalho, L. M. V.↗

Distributed Monitoring of the R(sup 2) Statistic for Linear Regression

The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more dependent target variables. This problem becomes challenging for large scale data in a distributed computing environment when only a subset of instances is available at individual nodes and the local data changes frequently. Data centralization and periodic model recomputation can add high overhead to tasks like anomaly detection in such dynamic settings. Therefore, the goal is to develop techniques for monitoring and updating the model over the union of all nodes data in a communication-efficient fashion. Correctness guarantees on such techniques are also often highly desirable, especially in safety-critical application scenarios. In this paper we develop DReMo a distributed algorithm with very low resource overhead, for monitoring the quality of a regression model in terms of its coefficient of determination (R2 statistic). When the nodes collectively determine that R2 has dropped below a fixed threshold, the linear regression model is recomputed via a network-wide convergecast and the updated model is broadcast back to all nodes. We show empirically, using both synthetic and real data, that our proposed method is highly communication-efficient and scalable, and also provide theoretical guarantees on correctness.

Bhaduri, Kanishka↗

Winds Measured by the Rover Environmental Monitoring Station (REMS) During the Mars Science Laboratory (MSL) Rover's Bagnold Dunes Campaign and Comparison with Numerical Modeling Using MarsWRF

A high density of REMS wind measurements were collected in three science investigations during MSL's Bagnold Dunes Campaign, which took place over approx. 80 sols around southern winter solstice (Ls approx. 90deg) and constituted the first in situ analysis of the environmental conditions, morphology, structure, and composition of an active dune field on Mars. The Wind Characterization Investigation was designed to fully characterize the near-surface wind field just outside the dunes and confirmed the primarily upslope/downslope flow expected from theory and modeling of the circulation on the slopes of Aeolis Mons in this season. The basic pattern of winds is 'upslope' (from the northwest, heading up Aeolis Mons) during the daytime (approx. 09:00-17:00 or 18:00) and 'downslope' (from the southeast, heading down Aeolis Mons) at night (approx. 20:00 to some time before 08:00). Between these times the wind rotates largely clockwise, giving generally westerly winds mid-morning and easterly winds in the early evening. The timings of these direction changes are relatively consistent from sol to sol; however, the wind direction and speed at any given time shows considerable intersol variability. This pattern and timing is similar to predictions from the MarsWRF numerical model, run at a resolution of approx. 490 m in this region, although the model predicts the upslope winds to have a stronger component from the E than the W, misses a wind speed peak at approx. 09:00, and under-predicts the strength of daytime wind speeds by approx. 2-4 m/s. The Namib Dune Lee Investigation reveals 'blocking' of northerly winds by the dune, leaving primarily a westerly component to the daytime winds, and also shows a broadening of the 1 Hz wind speed distribution likely associated with lee turbulence. The Namib Dune Side Investigation measured primarily daytime winds at the side of the same dune, in support of aeolian change detection experiments designed to put limits on the saltation threshold, and also appears to show the influence of the dune body on the local flow, though less clearly than in the lee. Using a vertical grid with lower resolution near the surface reduces the relative strength of nighttime winds predicted by MarsWRF and produces a peak in wind speed at approx. 09:00, improving the match to the observed diurnal variation of wind speed, albeit with an offset in magnitude. The annual wind field predicted using this grid also provides a far better match to observations of aeolian dune morphology and motion in the Bagnold Dunes. However, the lower overall wind speeds than observed and disagreement with the observed wind direction at approx. 09:00 suggest that the problem has not been solved and that alternative boundary layer mixing schemes should be explored which may result in more mixing of momentum down to the near-surface from higher layers. These results demonstrate a strong need for in situ wind data to constrain the setup and assumptions used in numerical models, so that they may be used with more confidence to predict the circulation at other times and locations on Mars.

Newman, Claire E.↗

Development of an Automated Reader for Analysis and Storage of Personnel Dosimeter Badge Data

The collection and archiving of data from personnel dosimeters has become increasingly important in light of the lowered Threshold Limit Values (TLV) for HydraZine (HZ), MonoMethylHydrazine (MMH), and Unsymmetrical DiMethylHydrazine (UDMH). The American Conference of Government Industrial Hygienists (ACGIH) lowered the TLV from 100 parts per billion (ppb) to IO ppb and has caused increased concern over long term exposures of personnel to trace levels of these hypergols and other potentially harmful chemicals. An automated system of reading the exposure levels of personnel dosimeters and storing exposure data for subsequent evaluation has been developed. The reading of personnel dosimeter badges for exposure to potentially harmful vapor concentrations of hydrazines or other chemicals is performed visually by comparing the color developed by the badge with a calibrated color comparator. The result obtained using visual comparisons of the developed badge color with the comparator may vary widely from user to user. The automated badge reader takes the variability out of the dosimeter reading by accurately comparing the reflectance obtained from a colored spot on the badge with a reading on the same spot prior to any exposure to chemical vapors. The observed difference between the reflectance values is used as part of a calculation of the dose value for the badge based on a stored calibration curve. The badge reader also stores bar-code data unique to each badge, as well as bar-code information on the user, as part of the permanent badge record. The start and stop exposure times for each badge are recorded and can be used as part of the calculated concentration, in ppm, for each badge logged during a recording period. The badge reader is equipped with a number of badge holders, each of which is unique to a specific type of personnel dosimeter badge. This gives the reader maximum flexibility to allow for the reading of several different types of badges. Test results of the badge reader for several different types of personnel dosimeter badges are presented within the body of this paper.

Meneghelli, B. J.↗

Development of an Automated Reader for Analysis and Storage of Personnel Dosimeter Badge Data

The collection and archiving of data from personnel dosimeters has become increasingly important in light of the lowered threshold limit values (TLV) for hydrazine (HZ), monomethylhydrazine (MMH), and unsymmetrical dimethylhydrazine (UDMH). The American Conference of Government Industrial Hygienists (ACGIH) lowered the TLV from 100 parts per billion (ppb) to 10 ppb and has caused increased concern over long term exposures of personnel to trace levels of these hypergols and other potentially harmful chemicals. An automated system of reading the exposure levels of personnel dosimeters and storing exposure data for subsequent evaluation has been developed. The reading of personnel dosimeter badges for exposure lo potentially harmful vapor concentrations of hydrazines or other chemicals is performed visually by comparing the color developed by the badge with a calibrated color comparator. The result obtained using visual comparisons of the developed badge color with the comparator may vary widely from user to user. The automated badge reader takes the variability out of the dosimeter reading by accurately comparing the reflectance obtained from a colored spot on the badge with a reading on the same spot prior to any exposure to chemical vapors. The observed difference between the reflectance values is used as part of a calculation of the dose value for the badge based on a stored calibration curve. The badge reader also stores bar-code data unique to each badge, as well as bar-code information on the user, as part of the permanent badge record. The start and stop exposure times for each badge are recorded and can be used as part of the calculated concentration, in ppm, for each badge logged during a recording period. The badge reader is equipped with a number of badge holders, each of which is unique to a specific type of personnel dosimeter badge. This gives the reader maximum flexibility to allow for the reading of several different types of badges. Test results of the badge reader for several different types of personnel dosimeter badges are presented within the body of this paper.

Meneghelli, B. J.↗

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412,443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 x 10(exp -4), 5.49 x 10(exp -4), 4.48 x 10(exp -4), 2.51 x 10(exp -4), 8.83 x 10(exp -5), and 1.36 x 10(exp -4)/sr, respectively, and 1.09 x 10(exp -2)/cu.mgm for the chlorophyll-a concentration (Chl-a), 2.09 x 10(exp -3)/m for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (a(sub g) (412)), and 3.7 mg/cu.m for particulate organic carbon (POC). These R(sub rs) values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Concha, Javier↗

Research opportunities with the Centrifuge Facility

The Centrifuge Facility on Space Station Freedom will consist of a 2.5-meter diameter Centrifuge accommodating two concentric rings of habitats and providing variable g-forces between 0.01 g and 2.0 g; modular habitats providing housing and lifesupport for rats, mice, and plants; a habitat holding system providing power, water, airflow and other utilities to several modular habitats; and a life sciences glovebox, an isolated work volume accommodating simultaneous operations by at least two scientists and providing lighting, airflow, video and data access, and other experiment support functions. The centrifuge facility will enable long-duration animal and plant microgravity research not previously possible in the NASA flight research program. It will offer unprecedented opportunities for use of on-board 1-g control populations and statistically significant numbers of specimens. On orbit 1-g controls will allow separation of the effects of microgravity from other environmental factors. Its selectable-g and simultaneous multiple-g capabilities will enable studies of gravitational thresholds, the use of artificial gravity as a countermeasure to the effects of microgravity, and ready simulation of Lunar and Martian gravities.

Funk, Glenn A.↗

The Second SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-2)

Eight international laboratories specializing in the determination of marine pigment concentrations using high performance liquid chromatography (HPLC) were intercompared using in situ samples and a variety of laboratory standards. The field samples were collected primarily from eutrophic waters, although mesotrophic waters were also sampled to create a dynamic range in chlorophyll concentration spanning approximately two orders of magnitude (0.3 25.8 mg m-3). The intercomparisons were used to establish the following: a) the uncertainties in quantitating individual pigments and higher-order variables (sums, ratios, and indices); b) an evaluation of spectrophotometric versus HPLC uncertainties in the determination of total chlorophyll a; and c) the reduction in uncertainties as a result of applying quality assurance (QA) procedures associated with extraction, separation, injection, degradation, detection, calibration, and reporting (particularly limits of detection and quantitation). In addition, the remote sensing requirements for the in situ determination of total chlorophyll a were investigated to determine whether or not the average uncertainty for this measurement is being satisfied. The culmination of the activity was a validation of the round-robin methodology plus the development of the requirements for validating an individual HPLC method. The validation process includes the measurements required to initially demonstrate a pigment is validated, and the measurements that must be made during sample analysis to confirm a method remains validated. The so-called performance-based metrics developed here describe a set of thresholds for a variety of easily-measured parameters with a corresponding set of performance categories. The aggregate set of performance parameters and categories establish a) the overall performance capability of the method, and b) whether or not the capability is consistent with the required accuracy objectives.

Source record↗

A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL

Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.

hydration↗

Climate Limits Across Space and Time on European Forest Structure

The impact climate has on forests has been extensively studied. However, the large scale effect climate has on forest structures, such as average diameters, heights and basal area are understudied in a spatially explicit manner. The limits, tipping points and thresholds that climate places on forest structures dictate the services a forest may provide, the vulnerability of a forest to mortality and the potential value of the timber there within. The majority of current research either investigates climate impacts on forest pools and fluxes, on a tree physiological scale or on case studies that are used to extrapolate results and potential impacts. A spatially explicit study on how climate affects forest structure over a large region would give valuable information to stakeholders who are more concerned with ecosystem services that cannot be described by pools and fluxes but require spatially explicit information - such as biodiversity, habitat suitability, and market values. In this study, we quantified the limits that climate (maximum, minimum temperature and precipitation) places on 3 forest structures, diameter at breast height, height, and basal area throughout Europe. Our results show clear climatic zones of high and low upper limits for each forest structure variable studied. We also spatially analyzed how climate restricts the potential bio-physical upper limits and creates tipping points of each forest structure variable and which climate factors are most limiting. Further, we demonstrated how the climate change has affected 8 individual forests across Europe and then the continent as a whole. We find that diameter, height and basal area are limited by climate in different ways and that areas may have high upper limits in one structure and low upper limits in another limited by different climate variables. We also found that even though individual forests may have increased their potential upper limit forest structure values, European forests as a whole have lost, on average, 5.0%, 1.7% and 6.5% in potential mean forest diameter, height and basal area, respectively.

Moreno, Adam La Salle↗

The Characterization of Deep Convective Clouds as an Invariant Calibration Target and as a Visible Calibration Technique

Deep convective clouds (DCCs) are ideal visible calibration targets because they are bright nearly isotropic solar reflectors located over the tropics and they can be easily identified using a simple infrared threshold. Because all satellites view DCCs, DCCs provide the opportunity to uniformly monitor the stability of all operational sensors, both historical and present. A collective DCC anisotropically corrected radiance calibration approach is used to construct monthly probability distribution functions (PDFs) to monitor sensor stability. The DCC calibration targets were stable to within 0.5% and 0.3% per decade when the selection criteria were optimized based on Aqua MODerate Resolution Imaging Spectroradiometer 0.65-micrometer-band radiances. The Tropical Western Pacific (TWP), African, and South American regions were identified as the dominant DCC domains. For the 0.65-micrometer band, the PDF mode statistic is preferable, providing 0.3%regional consistency and 1%temporal uncertainty over land regions. It was found that the DCC within the TWP had the lowest radiometric response and DCC over land did not necessarily have the highest radiometric response. For wavelengths greater than 1 micrometer, the mean statistic is preferred, and land regions provided a regional variability of 0.7%with a temporal uncertainty of 1.1% where the DCC land response was higher than the response over ocean. Unlike stratus and cirrus clouds, the DCC spectra were not affected by water vapor absorption.

Doelling, David R.↗

Propagation of Radiosonde Pressure Sensor Errors to Ozonesonde Measurements

Several previous studies highlight pressure (or equivalently, pressure altitude) discrepancies between the radiosonde pressure sensor and that derived from a GPS flown with the radiosonde. The offsets vary during the ascent both in absolute and percent pressure differences. To investigate this problem further, a total of 731 radiosonde-ozonesonde launches from the Southern Hemisphere subtropics to Northern mid-latitudes are considered, with launches between 2005 - 2013 from both longer-term and campaign-based intensive stations. Five series of radiosondes from two manufacturers (International Met Systems: iMet, iMet-P, iMet-S, and Vaisala: RS80-15N and RS92-SGP) are analyzed to determine the magnitude of the pressure offset. Additionally, electrochemical concentration cell (ECC) ozonesondes from three manufacturers (Science Pump Corporation; SPC and ENSCI-Droplet Measurement Technologies; DMT) are analyzed to quantify the effects these offsets have on the calculation of ECC ozone (O3) mixing ratio profiles (O3MR) from the ozonesonde-measured partial pressure. Approximately half of all offsets are 0.6 hPa in the free troposphere, with nearly a third 1.0 hPa at 26 km, where the 1.0 hPa error represents 5 persent of the total atmospheric pressure. Pressure offsets have negligible effects on O3MR below 20 km (96 percent of launches lie within 5 percent O3MR error at 20 km). Ozone mixing ratio errors above 10 hPa (30 km), can approach greater than 10 percent ( 25 percent of launches that reach 30 km exceed this threshold). These errors cause disagreement between the integrated ozonesonde-only column O3 from the GPS and radiosonde pressure profile by an average of +6.5 DU. Comparisons of total column O3 between the GPS and radiosonde pressure profiles yield average differences of +1.1 DU when the O3 is integrated to burst with addition of the McPeters and Labow (2012) above-burst O3 column climatology. Total column differences are reduced to an average of -0.5 DU when the O3 profile is integrated to 10 hPa with subsequent addition of the O3 climatology above 10 hPa. The RS92 radiosondes are superior in performance compared to other radiosondes, with average 26 km errors of -0.12 hPa or +0.61 percent O3MR error. iMet-P radiosondes had average 26 km errors of -1.95 hPa or +8.75 percent O3MR error. Based on our analysis, we suggest that ozonesondes always be coupled with a GPS-enabled radiosonde and that pressure-dependent variables, such as O3MR, be recalculated-reprocessed using the GPS-measured altitude, especially when 26 km pressure offsets exceed 1.0 hPa 5 percent.

pressure measurements↗

The Biological Flight Research Facility

NASA Ames Research Center is building a research facility, the Biological Flight Research Facility (BFRF), to meet the needs of life scientists to study the long-term effects of variable gravity on living systems. The facility will be housed on Space Station Freedom and is anticipated to operate for the lifetime of the station, approximately 30 years. It will allow plant and animal biologists to study the role of gravity, or its absence, at varying gravity intensities for varying periods of time and with various organisms. The principal difference between current Spacelab missions and those on Space Station Freedom, other than length of mission, will be the capability to perform on-orbit science procedures and the capability to simulate earth gravity. Initially, the facility will house plants and rodents in habitats which can be maintained at microgravity or can be placed on a 2.5-m diam centrifuge. However, the facility is also being designed to accommodate future habitats for small primates, avian, and aquatic specimens. The centrifuge will provide 1 g for controls and will also be able to provide gravity from 0.01 to 2.0 g for threshold gravity studies as well as hypergravity studies. The BFRF will provide the means to conduct basic experiments to gain an understanding of the effects of microgravity on the structure and function of plants and animals, as well as investigate the role of gravity as a potential countermeasure for the physiological changes observed in microgravity.

Johnson, Catherine C.↗

The Biological Flight Research Facility

NASA Ames Research Center (ARC) is building a research facility, the Biological Flight Research Facility (BFRF), to meet the needs of life scientists to study the long-term effects of variable gravity on living systems. The facility will be housed on Space Station Freedom and is anticipated to operate for the lifetime of the station, approximately thirty years. It will allow plant and animal biologists to study the role of gravity, or its absence, at varying gravity intensities for varying periods of time and with various organisms. The principal difference between current Spacelab missions and those on Space Station Freedom, other than length of mission, will be the capability to perform on-orbit science procedures and the capability to simulate earth gravity. Initially the facility will house plants and rodents in habitats which can be maintained at microgravity or can be placed on a 2.5 meter diameter centrifuge. However, the facility is also being designed to accommodate future habitats for small primates, avian, and aquatic specimens. The centrifuge will provide 1 g for controls and will also be able to provide gravity from 0.01 to 2.0 g for threshold gravity studies as well as hypergravity studies. Included in the facility are a service unit for providing clean chambers for the specimens and a glovebox for manipulating the plant and animal specimens and for performing experimental protocols. The BFRF will provide the means to conduct basic experiments to gain an understanding of the effects of microgravity on the structure and function of plants and animals, as well as investigate the role of gravity as a potential countermeasure for the physiological changes observed in microgravity.

Johnson, Catherine C.↗

Capturing Complex Multivariate Time Series Interactions to Detect High-Risk Adverse Events During Flight

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

Capturing Multivariate Time Series Interactions to Detect High‑Risk Instability During Approach

The reduction of aviation safety metrics below target thresholds continue to drive down the number of aviation fatalities and accidents. To meet future safety demands, sustained efforts by aviation agencies promoting safety assurance processes and systems have prompted ongoing research on identifying and mitigating in-flight risks. With the projected increase in passenger load factor and rollout of more autonomous systems into the national airspace, the need to detect high-risk events in-time or ahead-of-time is becoming increasingly crucial. New anomaly detection and precursor identification algorithms will need to scale to different airframes, levels of autonomy, and system complexity. While the pervasiveness of deep learning has resulted in the development of performant anomaly detection methods, these sophisticated models currently suffer from low end-user interpretability. Building off our previous work on identifying adverse events in multivariate flight data during descent, we propose a data-driven approach for detecting in-flight adverse events caused by the complex interplay of flight variables. Our approach utilizes ordinal patterns of important aircraft stability variables (e.g., airspeed and descent rate) to capture multivariate flight dynamics that can be used to predict the onset of unstable approaches, a high-risk adverse event that can occur during approach. Through the use of ordinal patterns, we aim to create more interpretable detection models of in-flight adverse events that can be translated to future autonomous systems without difficulty. Our analysis shows the presence of distinct ordinal pattern distributions that can be used to predict unstable approaches 1 minute ahead of time with an accuracy of 0.69 and a recall of 0.73 and 30 seconds ahead with an accuracy of 0.70 and a recall of 0.86.

Risk detection↗

Validation of Proposed Go-Around Criteria Under Various Environmental Conditions

This paper evaluates the effects of environmental conditions on touchdown performance under varying approach states and validates proposed go-around criteria developed using data from a previously conducted study under these various environmental conditions. An experiment was conducted using Boeing 737-800 and Airbus A330-200 Level D full-flight simulators in which 24 pilots flew multiple approaches under different approach conditions and environmental variables. Pilots were instructed to always land the aircraft, even from conditions considered to be an unstable approach. Various touchdown performance metrics were analyzed. In addition, pilots’ perceptions of risk under the various unstable approach conditions and resulting landings were assessed. The results of the study revealed that wind speed/direction and visibility had a stronger effect on touchdown performance than the approach parameters. Specifically, wind had a highly significant effect on longitudinal and lateral touchdown point, as well as a significant effect on sink-rate at touchdown. Wind and visibility, along with localizer deviation, also had a strong effect on pilots’ perception of risk and workload ratings. Furthermore, the study confirmed that touchdown performance was similar among the runs with a 300-foot and 500-foot starting gate, as was found in the previously conducted experiment. These results support the previous finding that lowering the go-around decision gate to 300-foot might be acceptable, but suggest that certain environmental conditions might warrant altered thresholds of the proposed go-around criteria at this gate. Finally, the findings of this experiment highlight the importance of environmental factors in the assessment of risk of unwanted outcomes on approach and landing.

Transport Aircraft↗