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Some of the Raman LIDAR applications for monitoring the atmosphere are reviewed. Following a definition of Raman scattering, the basic design of a Raman LIDAR system is described and the atmosphere-monitoring potentialities and limitations of the system are discussed, along with the possibilities of further progress.
Since the launch of TIROS I in 1960, the utility of remote sensing from orbit for monitoring the earth's weather has been conclusively demonstrated. The past decade has also seen progress in applying remote sensing to the observation of terrestrial features. Variations in snow and ice cover, surface water, river and lake turbidity, and other hydrological features are now being accurately observed from orbital altitudes by the Earth Resources Technology Satellite (ERTS-1), NOAA-2, and Nimbus 5. Satellite visible, infrared and microwave measurements will be continued over the next few years, with improved spatial and spectral accuracy, by Skylab, ERTS-B, and Nimbus F. Delineations of soil and snow moisture variations, thermal patterns in lakes and estuaries, and regions of heavy precipitation are among the results anticipated.
The goal of this program was the development of a SiC CVD growth of films thick enough to be useful as pseudo-substrates. The cold-walled CVD system was designed, assembled, and tested. Extrapolating from preliminary evaluation of SiC films grown in the system at relatively low temperatures indicates that the growth rate at the final temperatures will be high enough to make our approach practical. Modifications of the system to allow high temperature growth and cleaner growth conditions are in progress. This program was jointly funded by Wright Laboratory, Materials Directorate and NASA LeRC and monitored by NASA.
One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds
One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.
The progress in the development of a sensor for the detection of trace air constituents to monitor spacecraft air quality is reported. A continuous-wave (cw), external-cavity tunable diode laser centered at 1.55 micrometers is used to pump an optical cavity absorption cell in cw-cavity ringdown spectroscopy (cw-CRDS). Preliminary results are presented that demonstrate the sensitivity, selectivity and reproducibility of this method. Detection limits of 2.0 ppm for CO, 2.5 ppm for CO2, 1.8 ppm for H2O, 19.4 ppb for NH3, 7.9 ppb for HCN and 4.0 ppb for C2H2 are calculated.
The charge of the NOAA Drought Task Force is to coordinate and facilitate the various MAPP-funded research efforts with the overall goal of achieving significant advances in understanding and in the ability to monitor and predict drought over North America. In order to achieve this, the task force has developed a Drought Test-bed that individual research groups can use to test/evaluate methods and ideas. Central to this is a focus on three high profile North American droughts (1998-2004 western US drought, 2006-2007 SE US drought, 2011- current Tex-Mex drought) to facilitate collaboration among projects, including the development of metrics to assess the quality of monitoring and prediction products, and the development of an experimental drought monitoring and prediction system that incorporates and assesses recent advances. This talk will review the progress and plans of the task force, including efforts to help advance official national drought products, and the development of early warning systems by the National Integrated Drought Information System (NIDIS). Coordination with other relevant national and international efforts such as the emerging NMME capabilities and the international effort to develop a Global Drought Information System (GDIS) will be discussed.
- We will analyze the volcanic plume progression, spread and properties using space-based observations - OMPS LP, SAGE III/ISS, CALIPSO, TROPOMI - OMPS LP and SAGE III/ISS are limb instruments that measure the aerosol vertical profiles globally, while CALIPSO is a LIDAR that measures the backscatter and depolarization ratio of the aerosol profiles. -TROPOMI is a UV instrument that measures SO2 and absorbing aerosol total column - Volcanic plume in the upper stratosphere - The main plume in middle stratosphere - Volcanic aerosol transport to SH/NH - Volcanic aerosol optical properties
Abstract Large‐scale power systems exhibit more complex dynamics due to the increasing integration of inverter‐based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide‐Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large‐scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra‐high density synchrophasor and point‐on‐wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)‐based advanced applications are introduced, including AI‐based inertia estimation, AI‐based disturbance size and location estimation, AI‐based system stability assessment, and AI‐based data authentication.
The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.
A recent National Academies consensus report addresses monitoring and assessment of cumulative effects of large-scale and multiple restoration projects within the context of long-term environmental change. Fines and penalties from the Deepwater Horizon oil spill in the Gulf of Mexico (GoM) have supported hundreds of restoration projects at spatial scales not often possible in the past. Here, in this paper, the report committee members and staff provide personal reflections from our time working on the study. We found that gaps in data collection, issues with data accessibility, and a lack of synthesis and analysis are hindering the ability to answer a basic question: What are the impacts of these many restoration efforts on improving ecosystem health and productivity in the GoM at the regional and Gulf wide scale? Restoration efforts are occurring in environments where many trends are changing and exhibiting higher variability than in the past, suggesting that previously successful restoration practices may no longer be adequate to compensate for the effects of environmental changes and variability. Our proposed approach to these challenges includes employing emerging monitoring technologies; using conceptual models; devising an adaptive management framework; rethinking restoration outcome goals; assessing cumulative effects; and undertaking rigorous synthesis and analysis of existing information on long-term environmental trends and restoration efforts. Restoration scientists and practitioners working in the GoM have an unprecedented opportunity to demonstrate large-scale environmental recovery if advances in monitoring, synthesis, assessment, and action are taken quickly. We are cautiously optimistic that, with mid-course adjustments, continued progress toward large-scale environmental recovery is possible.
Every electron crystallography experiment is fundamentally constrained by radiation damage [1]. Despite its crucial importance, little is understood about the onset and progression of radiolysis in beam-sensitive molecular crystals [2]. Since the typical metric used for monitoring the degradation induced by radiolysis is the attenuation of Bragg reflections in electron diffraction patterns [3], the scope of previous analyses [2-6] has mostly been limited to indirect observation via the back focal plane. Here, a simultaneous visualization of the effects of electron beam-induced radiolysis—in both real space and reciprocal space—remains elusive.
RadTraQ is a python library housing routines related to assessing and monitoring the quality of a radar's quality and calibration. This library is a work in progress, currently housing scripts to plot radar CFADs, plot and analyze corner reflector scans, calculate noise floors, create cloud masks, and plot up average profiles for comparisons.
Techniques have been developed for defining coastal circulation patterns using sediment as a natural tracer, allowing the formulation of new circulation concepts in some geographical areas and, in general, a better capability for defining the seasonal characteristics of coastal circulation. An analytical technique for measurement of absolute water depth based upon the ratios of two MSS channels has been developed. Suspended sediment has found wide use as a tracer, but a few investigators have reported limited success in measuring the type and amount of sediment quantitatively from ERTS-1 digital data. Significant progress has been made in developing techniques for using ERTS-1 data to locate, identify, and monitor sea and lake ice. Ice features greater than 70 meters in width can be detected, and both arctic and antarctic icebergs have been identified. In the application area of living marine resources, the use of ERTS-1 image-density patterns as a potential indicator of fish school location has been demonstrated for one coastal commercial resource, menhaden. ERTS-1 data have been used to locate ocean current boundaries using ERTS-1 image-density enhancement, and some techniques are under development for measurement of suspended particle concentration and chlorophyll concentration. The interrelationship of water color and surface characteristics (sea state) are also being studied to improve spectral and spatial interpretive techniques.
It is suggested that progress in hail suppression research requires simultaneous improvements in methods of evaluating seeding effects and in monitoring the physical structure of the hailstorm and the hail growth processes. On this basis a case is made for the extensive use of multiple Doppler radar and chemical tracer techniques.
Network Control Center (NCC) Project metrics are captured during the implementation and testing phases of the NCCDS software development lifecycle. The metrics data collection and reporting function has interfaces with all elements of the NCC project. Close collaboration with all project elements has resulted in the development of a defined and repeatable set of metrics processes. The resulting data are used to plan and monitor release activities on a weekly basis. The use of graphical outputs facilitates the interpretation of progress and status. The successful application of metrics throughout the NCC project has been instrumental in the delivery of quality software. The use of metrics on the NCC Project supports the needs of the technical and managerial staff. This paper describes the project, the functions supported by metrics, the data that are collected and reported, how the data are used, and the improvements in the quality of deliverable software since the metrics processes and products have been in use.
Acoustical studies of atmospheric events like convective storms, shear-induced turbulence, acoustic gravity waves, microbursts, hurricanes, and clear air turbulence (CAT) over the past thirty years have established that these events are strong emitters of infrasound. Several mechanisms for the production of infrasound have been proposed, for example by the acceleration of vorticity or by space-time correlations of the turbulent Reynolds stresses (Lighthill theory). Electromagnetic (EM) sensors suffer two severe disadvantages in the detection of clear air turbulence and severe storms. The first is the inability to receive returns in clear air, where reflective targets (precipitation, particulate matter) are absent. The second disadvantage is that EM systems, being active, require scanning to locate an event, as opposed to a passive infrasonic array, which receives infrasonic radiation independently of event location. Further, EM systems, even weather radar ("NEXRAD"), do not have the extensive range (hundreds of miles) characteristic of infrasound. The leading laboratory for studies on atmospheric infrasound over the past thirty years has been the Environmental Technology Laboratory of the National Oceanic and Atmospheric Administration. This laboratory conducted measurements of infrasound from many sources, among which clear air turbulence was but a small part of the overall program. The summary of the results of this program suggests for development of a practical detection system. In other words, despite the progress made in this area, there does not exist today a National network of stations to monitor infrasound from turbulence. Under Innovative Partnership Program, Researchers at NASA Langley Research Center have been working to achieve that goal. As a first step, NASA Langley has designed and developed a portable infrasonic detection system which can be used to make useful infrasound measurements at a location where it was not possible previously. The design and results of the compact system, based upon laboratory and field experiments, will be presented.
A pin style bottom anode employs conductive steel rods that serve as the pathway for the high electrical power through rammed refractory at the bottom of a DC Electric Arc Furnace (EAF). Anode wear during operation is important to monitor, as anode replacement is expensive and impacts EAF productivity. Liquid steel penetration into the un-sintered refractory layer can result from rapid electrical power ramp-up, dips in furnace temperature, or operating the anode for too long between EAF campaigns. In extreme cases, the liquid steel may penetrate the bottom of the furnace when anode wear progresses too close to the bottom shell, which is extremely dangerous and must be avoided. The current state of the art for monitoring bottom anode wear employs thermocouples imbedded in the anode pins at points in the anode. However, this approach is not sensitive enough to detect localized damage to the anode, especially when cracking occurs. Here, the present work utilizes fiber optic sensors to monitor the health of the anode, by creating a real-time spatially distributed temperature map of the anode. Unlike the traditional thermocouples, these sensors can be mounted at significantly greater depths, provide distributed temperature measurements, and can withstand temperatures of up to 900°C. Additionally, they are able to perform temperature measurements with a spatial resolution of 1.3 mm at a 5 Hz acquisition rate, providing unprecedented high-density real time monitoring of anode health and increasing the efficiency, and safety of EAF operation.