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We have constructed a sensitive submillimeter receiver for the NASA Kuiper Airborne Observatory (KAO) which at present operates in the 500-750 GHz band. The DSB receiver noise temperature is about 5 h nu/k(sub B) over the 500-700 GHz range. This receiver has been used to detect H2O(18)O, HCl, and CH in interstellar molecular clouds, and also to search for C(+) emission from the highly redshifted galaxy (z = 2.3) IRAS 10214.
This paper will discuss findings of a collaborative lightning research project between National Aeronautics and Space Administration, the Massachusetts Institute of Technology and the National Weather Service office In Melbourne Florida. In August 1996, NWS/MLB received a workstation which incorporates data from the KMLB WSR-88D, Cloud to Ground (CG) stroke data from the National Lightning Detection Network (NLDN), and 3D volumetric lightning data collected from the Kennedy Space Centers' Lightning Detection And Ranging (LDAR) lightning system. The two primary objectives of this lightning workstation, called Lightning Imaging Sensor Data Applications Display (USDAD), are to: observe how total lightning relates to severe convective storm morphology over central Florida, and compare ground based total lightning data (LDAR) to a satellite based lightning detection system. This presentation will focus on objective #1. The LISDAD system continuously displays CG and total lighting activity overlaid on top of the KMLB composite reflectivity product. This allows forecasters to monitor total lightning activity associated with convective cells occurring over the central Florida peninsula and adjacent coastal waters. The LISDAD system also keeps track of the amount of total lightning data, and associated KMLB radar products with individual convective cells occurring over the region. By clicking on an individual cell, a history table displays flash rate information (CG and total lightning) in one minute increments, along with radar parameter trends (echo tops, maximum dBz and height of maximum dBz) every 5 minutes. This history table Is updated continuously, without user intervention, as long as the cell is identified. Reviewing data collected during the 1997 wet season (21 cases) revealed that storms which produced severe weather (hall greater or = 0.75 in. or wind damage) typically showed a rapid rise In total lightning prior to the onset of severe weather. On average, flash rate increases of 25 FPM per minute over a time scale of approximately 5 minutes were common. These pulse severe storms typically reached values of 150 to 200 FPM with some cells exceeding 400 FPM. One finding which could have a direct application to the warning process is that the rapid increase in lightning typically occurred in advance of the warning issuance time. Comparisons between the ending time of the rapid rate increase and the time of when the warning was issued by NWS/MLB meteorologist exhibited a lead time of 8 minutes. It is conceivable that if close monitoring of the LISDAD system by operational meteorologist is routinely performed, warnings for pulse severe storms could be issued up to 4 to 6 minutes earlier than what is issued currently.
The launch of NASA's Terra spacecraft marks a new era of comprehensive monitoring of the Earth's atmosphere, oceans, and continents from a single space-based platform. Data from the five Terra instruments will create continuous, long-term records of the state of the land, oceans, and atmosphere. Together with data from other satellite systems launched by NASA and other countries, Terra will inaugurate a new self-consistent data record that will be gathered over the next 15 years. The science objectives of NASAs Earth Observing System (EOS) program are to provide global observations and scientific understanding of land cover change and global productivity, climate variability and change, natural hazards, and atmospheric ozone. Observations by the Terra instruments will: provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover; improve our ability to detect human impacts on the Earth system and climate, identify the "fingerprint" of human activity on climate, and predict climate change by using the new global observations in climate models; help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts, and start long-term monitoring of global climate change and environmental change.
We consider the radiative cooling of fully shielded molecular astrophysical gas over a wide range of temperatures ( 10 K < T < 2500 K) and H2 densities ( 10(exp 3)/cc < n(H2) < 10(exp 10)/cc). Our model for the radiative cooling of molecular gas includes a detailed treatment of the interstellar chemistry that determines the abundances of important coolant molecules, and a detailed treatment of the excitation of the species H2, CO, H2O, HCl, O2, C, O, and their isotopic variants where important. We present results for the total radiative cooling rate and for the cooling rate due to individual coolant species, as a function of the gas temperature, density, and optical depth. We have also computed the individual millimeter, submillimeter, and far-infrared line strengths that contribute to the total radiative cooling rate, and we have obtained example spectra for the submillimeter emission expected from molecular cloud cores. Many of the important cooling lines will be detectable using the Infrared Space Observatory and the Submillimeter Wave Astronomy Satellite.
Custom-designed two-micron phototransistors have been developed using Liquid Phase Epitaxy (LPE), Molecular Beam Epitaxy (MBE) and Metal-Organic Chemical Vapor Deposition (MOCVD) techniques under Laser Risk Reduction Program (LRRP). The devices were characterized in the Detector Characterization Laboratory at NASA Langley Research Center. It appears that the performance of LPE- and MBE-grown phototransistors such as responsivity, noise-equivalent-power, and gain, are better than MOCVD-grown devices. Lidar tests have been conducted using LPE and MBE devices under the 2-micrometer CO2 Differential Absorption Lidar (DIAL) Instrument Incubator Program (IIP) at the National Center for Atmospheric Research (NCAR), Boulder, Colorado. The main focus of these tests was to examine the phototransistors performances as compared to commercial InGaAs avalanche photodiode by integrating them into the Raman-shifted Eye-safe Aerosol Lidar (REAL) operating at 1.543 micrometers. A simultaneous measurement of the atmospheric backscatter signals using the LPE phototransistors and the commercial APD demonstrated good agreement between these two devices. On the other hand, simultaneous detection of lidar backscatter signals using MBE-grown phototransistor and InGaAs APD, showed a general agreement between these two devices with a lower performance than LPE devices. These custom-built phototransistors were optimized for detection around 2-micrometer wavelength while the lidar tests were performed at 1.543 micrometers. Phototransistor operation at 2-micron will improve the performance of a lidar system operating at that wavelength. Measurements include detecting hard targets (Rocky Mountains), atmospheric structure consisting of cirrus clouds and boundary layer. These phototransistors may have potential for high sensitivity differential absorption lidar measurements of carbon dioxide and water vapor at 2.05-micrometers and 1.9-micrometers, respectively.
On-orbit firings of both liquid and solid rocket motors provide localized disturbances to the plasma in the upper atmosphere. Large amounts of energy are deposited to ionosphere in the form of expanding exhaust vapors which change the composition and flow velocity. Charge exchange between the neutral exhaust molecules and the background ions (mainly O+) yields energetic ion beams. The rapidly moving pickup ions excite plasma instabilities and yield optical emissions after dissociative recombination with ambient electrons. Line-of-sight techniques for remote measurements rocket burn effects include direct observation of plume optical emissions with ground and satellite cameras, and plume scatter with UHF and higher frequency radars. Long range detection with HF radars is possible if the burns occur in the dense part of the ionosphere. The exhaust vapors initiate plasma turbulence in the ionosphere that can scatter HF radar waves launched from ground transmitters. Solid rocket motors provide particulates that become charged in the ionosphere and may excite dusty plasma instabilities. Hypersonic exhaust flow impacting the ionospheric plasma launches a low-frequency, electromagnetic pulse that is detectable using satellites with electric field booms. If the exhaust cloud itself passes over a satellite, in situ detectors measure increased ion-acoustic wave turbulence, enhanced neutral and plasma densities, elevated ion temperatures, and magnetic field perturbations. All of these techniques can be used for long range observations of plumes in the ionosphere. To demonstrate such long range measurements, several experiments were conducted by the Naval Research Laboratory including the Charged Aerosol Release Experiment, the Shuttle Ionospheric Modification with Pulsed Localized Exhaust experiments, and the Shuttle Exhaust Ionospheric Turbulence Experiments.
The Diffuse Interstellar Bands (DIBs) are a set of apporoximately 500 absorption bands that are seen in the spectra of reddened stars (i.e., stars obscured by the presence of interstellar clouds in their line of sight). The first DIBs were detected in the visible over a century ago. Diffuse Interstellar Bands are now detected from the near ultraviolet to the near infrared in the spectra of reddened stars spanning a variety of interstellar environments in our local, and in other galaxies. Although DIB carriers are a significant part of the interstellar chemical inventory as they account for a noticeable fraction of the interstellar extinction, the nature of their carriers is still unknown over a century after the detection of the first bands. DIB carriers are stable and ubiquitous in a broad variety of interstellar environments and play a unique role in interstellar physics and chemistry. It has long been realized that the solving of the DIB problem requires a strong synergy between astronomical observations, laboratory astrophysics and astrochemistry, quantum chemistry calculations and astrophysical modeling of line-of-sights. In this review, we'll present and discuss the current state of this perplexing problem. We'll review the progress and the failures that have been encountered in the long quest for the identification of the carriers of these ubiquitous interstellar bands.
Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.
We carried out a {sup 12}CO(3-2) survey of 52 southern stars with a wide range of IR excesses (L {sub IR}/L {sub *}) using the single-dish telescopes APEX and ASTE. The main aims were (1) to characterize the evolution of molecular gas in circumstellar disks using L {sub IR}/L {sub *} values as a proxy of disk dust evolution, and (2) to identify new gas-rich disk systems suitable for detailed study with ALMA. About 60% of the sample (31 systems) have L {sub IR}/L {sub *} > 0.01, typical of T Tauri or Herbig AeBe stars, and the rest (21 systems) have L {sub IR}/L {sub *} < 0.01, typical of debris disks. We detect CO(3-2) emission from 20 systems, and 18 (90%) of these have L {sub IR}/L {sub *} > 0.01. However, the spectra of only four of the newly detected systems appear free of contamination from background or foreground emission from molecular clouds. These include the early-type stars HD 104237 (A4/5V, 116 pc) and HD 98922 (A2 III, 507 pc, as determined in this work), where our observations reveal the presence of CO-rich circumstellar disks for the first time. Of the other detected sources, many could harbor gaseous circumstellar disks, but our data are inconclusive. For these two newly discovered gas-rich disks, we present radiative transfer models that simultaneously reproduce their spectral energy distributions and the {sup 12}CO(3-2) line profiles. For both of these systems, the data are fit well by geometrically flat disks, placing them in the small class of non-flaring disks with significant molecular gas reservoirs.
Theoretical studies and experimental results obtained at Coulommiers airport showed the capability of Proust radar to detect wind shears, in clear air condition as well as in presence of clouds or rain. Several examples are presented: in a blocking highs situation an atmospheric wave system at the Brunt-Vaisala frequency can be clearly distinguished; in a situation of clouds without rain the limit between clear air and clouds can be easily seen; and a windshear associated with a gust front in rainy conditions is shown. A comparison of 30 cm clear air radar Proust and 5 cm weather Doppler radar Ronsard will allow to select the best candidate for wind shear detection, taking into account the low sensibility to ground clutter of Ronsard radar.
The Ocean Color Instrument (OCI), which will be integrated with the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite, will collect science data that will be used to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared (SWIR) Detection Assembly (SDA), built and characterized by Utah State University Space Dynamics Laboratory (SDL), is a subsystem of OCI consisting of 32 channels covering seven discrete optical bands of interest. A total of 16 SWIR Detection Subassemblies (SDSs) compose the SDA and house the cold optical system. The science data optical input for each SDS is supplied by a 0.22 NA multimode fiber interfacing with a fiber adapter. The diverging light from the fiber is collimated, split by a dichroic beamsplitter to two separate channels, filtered by the science filter, and then reimaged onto the single-element detectors with a final 0.76 NA. Aspheric, diamond-turned powered elements are used throughout the optical design. Fabrication and alignment tolerance analysis/budgets are balanced to ensure the optical system meets throughput requirements. All systems are aligned at ambient temperature using an InSb camera and an in-line illumination microscope system to directly image the active detector area through the science filters. Compensators used during alignment are detector focus and decenter, which are adjusted via photoetched shims in increments of 25 µm. Average focus and centering errors were less than 8 µm among all 32 flight and 10 flight spare detectors. Each SDS spectral response and conversion gain was verified at operational temperature of -65°C in vacuum.
In many types of clouds, multiple hydrometeor populations can be present at the same time and height. Studying the evolution of these different hydrometeors in a time–height perspective can give valuable information on cloud particle composition and microphysical growth processes. However, as a prerequisite, the number of different hydrometeor types in a certain cloud volume needs to be quantified. This can be accomplished using cloud radar Doppler velocity spectra from profiling cloud radars if the different hydrometeor types have sufficiently different terminal fall velocities to produce individual Doppler spectrum peaks. Here we present a newly developed supervised machine learning radar Doppler spectra peak-finding algorithm (named PEAKO). In this approach, three adjustable parameters (spectrum smoothing span, prominence threshold, and minimum peak width at half-height) are varied to obtain the set of parameters which yields the best agreement of user-classified and machine-marked peaks. The algorithm was developed for Ka-band ARM zenith-pointing radar (KAZR) observations obtained in thick snowfall systems during the Atmospheric Radiation Measurement Program (ARM) mobile facility AMF2 deployment at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The performance of PEAKO is evaluated by comparing its results to existing Doppler peak-finding algorithms. The new algorithm consistently identifies Doppler spectra peaks and outperforms other algorithms by reducing noise and increasing temporal and height consistency in detected features. In the future, the PEAKO algorithm will be adapted to other cloud radars and other types of clouds consisting of multiple hydrometeors in the same cloud volume.
Habitable zone dust levels are a key unknown that must be understood to ensure the success of future space missions to image Earth analogs around nearby stars. Current detection limits are several orders of magnitude above the level of the solar system's zodiacal cloud, so characterization of the brightness distribution of exo-zodi down to much fainter levels is needed. To this end, the Large Binocular Telescope Interferometer (LBTI) will detect thermal emission from habitable zone exo-zodi a few times brighter than solar system levels. Here we present a modeling framework for interpreting LBTI observations, which yields dust levels from detections and upper limits that are then converted into predictions and upper limits for the scattered light surface brightness. We apply this model to the HOSTS survey sample of nearby stars; assuming a null depth uncertainty of 10{sup –4} the LBTI will be sensitive to dust a few times above the solar system level around Sun-like stars, and to even lower dust levels for more massive stars.
Supernova remnants (SNRs) are the most attractive candidates for the acceleration sites of Galactic cosmic rays. We report the detection of GeV γ-ray emission with the Pass 8 events recorded by the Fermi Large Area Telescope (Fermi-LAT) in the vicinity of the shell-type SNR CTB 37B that is likely associated with the TeV γ-ray source HESS J1713–381. The photon spectrum of CTB 37B is consistent with a power law with an index of 1.89 ± 0.08 in the energy range of 0.5–500 GeV, and the measured flux connects smoothly with that of HESS J1713–381 at a few hundred GeV. No significant spatial extension and time variation are detected. The multi-wavelength data can be well fitted with either a leptonic model or a hadronic one. However, parameters of both models suggest more efficient particle acceleration than typical SNRs. Meanwhile, the X-ray and γ-ray spectral properties of CTB 37B show that it is an interesting source bridging young SNRs dominated by non-thermal emission and old SNRs interacting with molecular clouds.
Smart inverters of distributed energy resources can enable cloud computing, condition monitoring, result visualization, remote control, and peer-to-peer energy trading in advanced power systems. However, the advent of data injection attacks in the communication architecture can alter measurement characteristics of power grids and have devastating consequences. In this article, we propose a time sequence machine learning-based anomaly detection methodology for detecting cyber intrusion into control signal setpoints and dc voltage signal measurement bias of the voltage source converter (VSC) in wind generators. We first investigated the effects of four types of denial of service, tampering signal, and stealthy-type data intrusion attacks on smart VSCs and overall wind farms. We then proposed a novel time sequence machine learning-based intrusion detection framework that can be implemented to detect different cyberattacks in the VSCs. The performance of the proposed framework has been compared with that of autoencoder and clustering-based intrusion detection framework. The proposed framework was validated by using the IEEE 39 bus power system in the presence of four wind farms in different locations. Using several metrics for intrusion detection performance, we validated the effectiveness of the proposed framework.
Laser heterodyne observations of submillimeter emissions from carbon monoxide in the Orion molecular cloud are reported. High frequency and spatial resolution observations were made at the NASA Infrared Telescope Facility on Mauna Kea by the use of an optically pumped laser local oscillator and quasi-optical Schottky diode mixer for heterodyne detection of the J = 6 - 5 rotational transition of CO at 434 microns. Spectral analysis of the 434-micron emission indicates that the emitting gas is optically thin and is at a temperature above 180 K. Results thus demonstrate the potential contributions of ground-based high-resolution submillimeter astronomy to the study of active regions in interstellar molecular clouds.
Purpose: To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). Methods: The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discrete models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. Results: On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μ{sub recon} = − 2.7 × 10{sup −3} mm{sup −1}, σ{sub recon} = 7.0 × 10{sup −3} mm{sup −1}) and (μ{sub CT} = − 2.5 × 10{sup −3} mm{sup −1}, σ{sub CT} = 5.3 × 10{sup −3} mm{sup −1}), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.
We report the detection of CO(J=2−1) coincident with the super star cluster (SSC) Mrk 71-A in the nearby Green Pea analog galaxy, NGC 2366. Our observations with the Northern Extended Millimeter Array reveal a compact, ∼7 pc, molecular cloud whose mass (10{sup 5} M{sub ⊙}) is similar to that of the SSC, consistent with a high star formation efficiency, on the order of 0.5. There are two spatially distinct components separated by 11 km s{sup −1}. If expanding, these could be due to momentum-driven stellar wind feedback. Alternatively, we may be seeing remnants of the infalling, colliding clouds responsible for triggering the SSC formation. The kinematics are also consistent with a virialized system. These extreme, high-density, star-forming conditions inhibit energy-driven feedback; the co-spatial existence of a massive, molecular cloud with the SSC supports this scenario, and we quantitatively confirm that any wind-driven feedback in Mrk 71-A is momentum-driven, rather than energy-driven. Since Mrk 71-A is a candidate Lyman continuum emitter, this implies that energy-driven superwinds may not be a necessary condition for the escape of ionizing radiation. In addition, the detection of nebular continuum emission yields an accurate astrometric position for the Mrk 71-A. We also detect four other massive molecular clouds in this giant star-forming complex.