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NASA NTRS2008

Remote-Sensing Time Series Analysis, a Vegetation Monitoring Tool

The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.

McKellip, Rodney↗
NASA NTRS2013

NASA Tech Briefs, June 2013

Topics include: Cloud Absorption Radiometer Autonomous Navigation System - CANS, Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis, Discrete Data Qualification System and Method Comprising Noise Series Fault Detection, Simple Laser Communications Terminal for Downlink from Earth Orbit at Rates Exceeding 10 Gb/s, Application Program Interface for the Orion Aerodynamics Database, Hyperspectral Imager-Tracker, Web Application Software for Ground Operations Planning Database (GOPDb) Management, Software Defined Radio with Parallelized Software Architecture, Compact Radar Transceiver with Included Calibration, Software Defined Radio with Parallelized Software Architecture, Phase Change Material Thermal Power Generator, The Thermal Hogan - A Means of Surviving the Lunar Night, Micromachined Active Magnetic Regenerator for Low-Temperature Magnetic Coolers, Nano-Ceramic Coated Plastics, Preparation of a Bimetal Using Mechanical Alloying for Environmental or Industrial Use, Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO, Dual-Compartment Inflatable Suitlock, Modular Connector Keying Concept, Genesis Ultrapure Water Megasonic Wafer Spin Cleaner, Piezoelectrically Initiated Pyrotechnic Igniter, Folding Elastic Thermal Surface - FETS, Multi-Pass Quadrupole Mass Analyzer, Lunar Sulfur Capture System, Environmental Qualification of a Single-Crystal Silicon Mirror for Spaceflight Use, Planar Superconducting Millimeter-Wave/Terahertz Channelizing Filter, Qualification of UHF Antenna for Extreme Martian Thermal Environments, Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project, ISS Live!, Space Operations Learning Center (SOLC) iPhone/iPad Application, Software to Compare NPP HDF5 Data Files, Planetary Data Systems (PDS) Imaging Node Atlas II, Automatic Calibration of an Airborne Imaging System to an Inertial Navigation Unit, Translating MAPGEN to ASPEN for MER, Support Routines for In Situ Image Processing, and Semi-Supervised Eigenbasis Novelty Detection.

Source record↗
NASA NTRS1982

Recent SETI observations at Arecibo

Preliminary results are presented for a high-resolution search for narrowband signals from the direction of 210 nearby solar-type stars and five OH masers. The 305-m Arecibo radio telescope was used to seek narrowband radio emission at frequencies surrounding the 21-cm H I line and/or the 18-cm OH lines; the observations were made in right and left circular polarizations simultaneously. At the 98% level, 291 'birdies' were found, of which six sources at 18 cm and eight at 21 cm are considered potential candidates for reobservation and further study to identify the nature of the signals. It is noted that: (1) five of the 21-cm 'birdies' are probably H I clouds along the line of sight; (2) some of the 18-cm 'birdies' are associated with the extreme 13 frequency bands bordering unprotected bands above and below the established radio astronomy band; and (3) one of the 21-cm 'birdies' is distinctly narrowband and has no signal detected in the 'off' source.

Tarter, J. C.↗
NASA NTRS1994

Behavior of an inversion-based precipitation retrieval algorithm with high-resolution AMPR measurements including a low-frequency 10.7-GHz channel

A microwave-based, profile-type precipitation retrieval algorithm has been used to analyze high-resolution passsive microwave measurements over an ocean background, obtained by the Advanced Microwave Precipitation Radiometer (AMPR) flown on a NASA ER-2 aircraft. The analysis is designed to first determine the improvements that can be gained by adding brightness temperature information from the AMPR low-frequency channel (10.7 GHz) to a multispectral retrieval algorithm nominally run with satellite information at 19, 37, and 85 GHz. The impact of spatial resolution degradation of the high-resolution brightness temperature information on the retrieved rain/cloud liquid water contents and ice water contents is then quantified in order to assess the possible biases inherent to satellite-based retrieval. Careful inspection of the high-resolution aircraft dataset reveals five distinctive brightness temperature features associated with cloud structure and scattering effects that are not generally detectable in current passive microwave satellite measurements. Results suggest that the inclusion of 10.7-GHz information overcomes two basic problems associated with three-channel retrieval. Intercomparisons of retrievals carried out at high-resolution and then averaged to a characteristic satellite scale to the corresponding retrievals in which the brightness temperatures are first convolved down to the satellite scale suggest that with the addition of the 10.7-GHz channel, the rain liquid water contents will not be negatively impacted by special resolution degradation. That is not the case with the ice water contents as they appear ti be quite sensitive to the imposed scale, the implication being that as spatial resolution is reduced, ice water contents will become increasingly underestimated.

Smith, E. A.↗
NASA NTRS1998

ASCA Observations of the T Tauri Star SU Aurigae and the Surrounding L1517 Dark Cloud

We present the results of a approximately equals 40 ks pointed Advanced Satellite for Cosmology and Astrophysics (ASCA) observation of the L1517 star-forming region, centered on the X-ray-bright T Tauri star SU Aurigae. This star has the highest X-ray luminosity of any classical T Tauri star in the Taurus-Auriga region, and its optical spectra show evidence for both mass inflow and outflow. Strong X-ray emission was detected from SU Aur (L(sub x) = 10(exp 30.9) ergs s(exp -1)) as well as weaker emission from five other pre-main-sequence stars. Although no large-amplitude flares were detected, the X-ray emission of SU Aur showed clear variability in the form of a slow decline in count rate during the 1.3 day observation. We provide the first direct comparison of the coronal differential emission measure (DEM) distribution of a classical T Tauri star with that of a young main-sequence star of similar spectral type. The DEM distributions of SU Aur (G2; age 3 Myr) and the young solar-like star EK Draconis (GO V; age 70 Myr) are qualitatively similar, with both showing a bimodal temperature distribution characterized by a cool plasma component peaking at approximately 8-9 MK and a hot component peaking at approximately 20-21 MK. However, there is a striking difference in the relative proportion of plasma at high temperatures in the two stars, with hot plasma (>20 MK) accounting for approximately equals 80% of the volume emission measure of SU Aur, compared to only approximately equals 40% in EK Dra. These results provide new insight into the changes that will occur in the corona of a T Tauri star as it descends onto the main sequence. A sharp decline in the fraction of coronal plasma at flarelike temperatures will occur during the late-T Tauri and post-T Tauri phases, and other recent X-ray studies have shown that this decline will continue after the young solar-like star reaches the main sequence.

Skinner, Stephen L.↗
DOE OSTI2026

A Novel Segmentation Algorithm for the ARM User Facility All-Sky Imagers Using Machine Learning Applications

Cloud cover plays a pivotal role in modulating the Earth's energy budget through the reflection of incoming solar radiation and the trapping of outgoing longwave radiation. Ground-based all-sky imagers offer an objective assessment of cloud cover that can be used to estimate solar irradiance, classify cloud types, track cloud movement, and serve as a benchmark 10 for the evaluation of satellite and reanalysis data products. The Atmospheric Radiation Measurement (ARM) user facility has utilized all-sky imagers for more than 25 years to monitor cloud cover and augment its comprehensive suite of atmospheric measurements. Following the retirement of its Total Sky Imager (TSI), ARM recently deployed the TSI’s successor, the All Sky Imager (ASI-16 camera systems). To provide a smooth transition and continuity to the vast amount of knowledge gathered by the TSI over the years, while addressing typical deployment issues, we developed a novel pixel segmentation algorithm, 15 the ASI Sky Cover (ASISKYCOVER). ASISKYCOVER builds on the different strengths and properties of the TSI processing algorithm while integrating machine learning techniques, ensuring data validity and accuracy across diverse atmospheric conditions. It enhances cloud cover characterization with new features such as artifact detection and uncertainty quantification. ASISKYCOVER also includes cloud cover estimates for near-zenith (narrow field-of-view) and reduces susceptibility to false detections. This study introduces ASISKYCOVER, details its algorithm framework, and demonstrates its capabilities using a 20 year-long dataset from the ARM Southern Great Plains site. Comparisons with co-located TSI data and other ARM measurements, such as zenith-pointing radars and lidars, are presented, underscoring the ASISKYCOVER’s potential to improve cloud cover analyses and data evaluation efforts, as well as to be integrated into higher-level data products that synergize instrument suites to generate new and insightful information

Silber, Israel↗
NASA NTRS2008

Evaluation of Cloud Physical Properties of ECMWF Analysis and Re-Analysis (ERA-40 and ERA Interim) against CERES Tropical Deep Convective Cloud Object Observations

This study presents an approach that converts the vertical profiles of grid-averaged cloud properties from large-scale models to probability density functions (pdfs) of subgrid-cell cloud physical properties measured at satellite footprints. Cloud physical and radiative properties, rather than just cloud and precipitation occurrences, of assimilated cloud systems by the European Center for Medium-range Weather Forecasts (ECMWF) operational analysis (EOA) and ECMWF Re-Analyses (ERA-40 and ERA Interim) are validated against those obtained from Earth Observing System satellite cloud object data for January-August 1998 and March 2000 periods. These properties include ice water path (IWP), cloud-top height and temperature, cloud optical depth and solar and infrared radiative fluxes. Each cloud object, a contiguous region with similar cloud physical properties, is temporally and spatially matched with EOA and ERA-40 data. Results indicate that most pdfs of EOA and ERA-40 cloud physical and radiative properties agree with those of satellite observations of the tropical deep convective cloud-object type for the January-August 1998 period. There are, however, significant discrepancies in selected ranges of the cloud property pdfs such as the upper range of EOA cloud top height. A major discrepancy is that the dependence of the pdfs on the cloud object size for both EOA and ERA-40 is not as strong as in the observations. Modifications to the cloud parameterization in ECMWF that occurred in October 1999 eliminate the clouds near the tropopause but shift power of the pdf to lower cloud-top heights and greatly reduce the ranges of IWP and cloud optical depth pdfs. These features persist in ERA-40 due to the use of the same cloud parameterizations. The downgrade of data assimilation technique and the lack of snow water content information in ERA-40, not the coarser horizontal grid resolution, are also responsible for the disagreements with observed pdfs of cloud physical properties although the detection rates of cloud object occurrence are improved for small size categories. A possible improvement to the convective parameterization is to introduce a stronger dependence of updraft penetration heights with grid-cell dynamics. These conclusions will be rechecked using the ERA Interim data, due to recent changes in the ECMWF convective parameterization (Bechtold et al. 2004, 2008). Results from the ERA Interim will be presented at the meeting.

Xu, Kuan-Man↗
NASA NTRS1999

Improved Algorithm to Estimate Convective and Stratiform Rain from TRMM Microwave Radiometer Data

The rain rates associated with Mesoscale Convective Systems (MCSS) deduced from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) follow the well known log-normal type frequency distribution characteristic of conventional radars and rain gauges. On the other hand, the current microwave radiometer rain retrieval algorithms cannot give good representations of convective and stratiform precipitation. Thus they capture poorly this log-normal character. In particular, this is noticed clearly over land areas. The objective of the present study is to improve TRMM Microwave Imager (TMI) retrievals of convective and stratiform rain to a level comparable to the PR. For this purpose, we have developed a TMI rain retrieval algorithm that depends primarily on the 85 GHz brightness temperatures (Tbs) and their spatial distribution. We emphasize the 85 GHz channel because of its fine footprint size (about 5.5 km) and strong extinction property. The other spectral channels, because they are poorer in these respects, are given less importance. The brightness temperatures and spatial distribution information in the 85 GHz allows us to detect thunderstorms, or cumulonimbus clouds (Cbs), that are in different stages of development, as well as stratiform rain outside of these Cbs. Utilizing our retrieval technique, we have produced maps of convective and stratiform rain for several MCS events over land and ocean that agree well with those given by the PR. On average, the convective and stratiform rain rates given by our technique have an accuracy of about 15 % with respect to those given by the PR.

Prabhakara, C.↗
NASA NTRS1993

Fourier transform infrared studies of the interaction of HCl with model polar stratospheric cloud films

Heterogeneous reactions involving hydrochloric acid adsorbed on the surfaces of polar stratospheric clouds (PSCs) are postulated to contribute to polar ozone loss. Using FTIR spectroscopy to probe the condensed phase, we have examined the interaction of HCl with ice and nitric acid trihydrate (NAT) films representative of types II and I PSCs, respectively. For HCl pressures in the range of 10 exp -7 to 10 exp -5 Torr, our FTIR studies show that a small amount of crystalline HCl-6H2O formed on or in ice at 155 K. However, for higher HCl pressures, we observed that the entire film of ice rapidly converted into an amorphous 4:1 H2O:HCl mixture. From HCl-uptake experiments with P(HCl) = 8 x 10 exp -7 Torr, we estimate roughly that the diffusion coefficient of HCl in ice is around 2 x 10 exp -12 sq cm/s at 158 K. For higher temperatures more closely approximating those found in the stratosphere, we were unable to detect bulk HCl uptake by ice. Indirect evidence suggests that HCl adsorption onto the surface of model PSC films inhibited the evaporation of both ice and NAT by 3-5 K.

Koehler, Birgit G.↗
NASA NTRSDate not supplied

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗
NASA NTRSDate not supplied

A Dynamic PCA and Machine Learning Tool for Automated Identification of Solar Wind Disturbances Impacting Earth’s Magnetosphere

Earth’s magnetosphere is continuously impacted by solar wind and interplanetary magnetic field (IMF) disturbances, such as shocks, discontinuities, magnetic clouds and more. Understanding how such disturbances propagate from the Sun and what is their impact on the different magnetospheric domains is key to understanding and forecasting energy transfer from the solar wind to Earth. The large number of overlapping solar wind and magnetospheric missions carrying magnetometers and the recent advances in communications and data storage technologies have enabled an unprecedented quantity of high-fidelity magnetic field data captured by in-situ spacecraft to be available at the click of a button. However, this massive quantity of available data can prove unwieldy for researchers, limiting the identification of interesting phenomena and disturbances to a relatively small percentage of the total dataset. Several techniques have been previously developed for automated identification of specific types of magnetic anomalies, but these methods are typically mission-specific and can be difficult to generalize. We present initial results for a generic method of automated anomaly detection in magnetic field measurements based on dimensionality reduction and unsupervised clustering via machine learning. The benefit of our technique is its high degree of generalizability and flexibility which make it a most useful data survey tool for a wide range of magnetic field datasets. This method can also be applied simultaneously to other observed time-series properties like plasma density, pressure, and velocity for more accurate event identification. Additionally, the application of this method to data captured by multiple spacecraft enables the simultaneous identification of disturbances and the determination of their propagation characteristics. Initial evaluation of this technique has been performed using data from Magnetospheric MultiScale (MMS) and THEMIS-ARTEMIS missions, providing a testbed scenario for the future Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) platform instruments that will measure solar wind and IMF properties from lunar orbit onboard the Gateway station.

Miguel Martinez-Ledesma↗
NASA NTRS2001

Lidar Measurements of Wind, and Cloud & Aerosol Structures using HARLIE at the WVIOP, Sept/Oct 2000

The holographic scanning lidar HARLIE made continuous measurements of aerosol and cloud one-micron backscatter and derived the horizontal wind speed and direction at cloud height over the ARM (SGP) site during the water vapor campaign WVIOP, September 17 - October 6, 2000. Whenever possible, these measurements were compared with Loran-C winds as measured by the routine launches of Vaisala radiosonde balloons scheduled by the ARM project. Taken overall, the agreement between these two types of observation is excellent, which could be taken merely as a validation of the relatively new HARLIE technique. However, the detailed comparison for a given sonde launch clearly requires that, out of the HARLIE data which are taken all the time at all altitudes, one must select those segments that match the altitude-time trajectory of the sonde. Moreover, the conical HARLIE scan at a 45 deg. elevation angle covers a wide area that is more representative of the average wind conditions above the site than the isolated track of the sonde's ascent. We suggest that the HARLIE instrument offers a more general and improved representation of the horizontal wind profile whenever there is sufficient backscatter by clouds and aerosols for lidar operation. HARLIE is a rugged and compact lidar that operates from aircraft as well as from the ground and has been used in several meteorological campaigns. As a "direct detection" lidar, HARLIE does not require the complexity of a coherent detection system. The data reduction algorithms facilitate the rapid and accurate determination of wind speed and direction at all altitudes. Wind measurements and HARLIE performance data from WVIOP 2000 and other campaigns will be presented.

Schwemmer, Geary↗
NASA NTRS2013

An Investigation of the Kinematic and Microphysical Control of Lightning Rate, Extent and NOx Production using DC3 Observations and the NASA Lightning Nitrogen Oxides Model (LNOM)

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to quantify the relationship between storm physics, lightning characteristics and the production of nitrogen oxides via lightning (LNOx). The focus of this study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern LNOx production, such as flash rate, type and extent across Alabama during DC3. Prior studies have demonstrated that lightning flash rate and type is correlated to kinematic and microphysical properties in the mixed‐phase region of thunderstorms such as updraft volume and graupel mass. More study is required to generalize these relationships in a wide variety of storm modes and meteorological conditions. Less is known about the co‐evolving relationship between storm physics, morphology and three‐dimensional flash extent, despite its importance for LNOx production. To address this conceptual gap, the NASA Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection Network(TM) (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash rate, flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to multicell thunderstorms over Northern Alabama on two days during DC3 (21 May and 11 June 2012) in which aircraft observations of NOx are available for comparison. The LNOM lightning characteristics and LNOX production estimates are compared to the evolution of updraft and precipitation properties inferred from dual‐Doppler and polarimetric radar analyses applied to observations from a nearby radar network, including the UAH Advanced Radar for Meteorological and Operational Research (ARMOR). Given complex multicell evolution, particular attention is paid to storm morphology, cell mergers and possible dynamical, microphysical and electrical interaction of individual cells when testing various hypotheses.

Carey, Lawrence↗
NASA NTRS2013

An Investigation of the Kinematic and Microphysical Control of Lightning Rate, Extent and NOX Production using DC3 Observations and the NASA Lightning Nitrogen Oxides Model (LNOM)

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to quantify the relationship between storm physics, lightning characteristics and the production of nitrogen oxides via lightning (LNOx). The focus of this study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern LNOx production, such as flash rate, type and extent across Alabama during DC3. Prior studies have demonstrated that lightning flash rate and type is correlated to kinematic and microphysical properties in the mixed‐phase region of thunderstorms such as updraft volume and graupel mass. More study is required to generalize these relationships in a wide variety of storm modes and meteorological conditions. Less is known about the co‐evolving relationship between storm physics, morphology and three‐dimensional flash extent, despite its importance for LNOx production. To address this conceptual gap, the NASA Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection NetworkTM (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash rate, flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to multicell thunderstorms over Northern Alabama on two days during DC3 (21 May and 11 June 2012) in which aircraft observations of NOx are available for comparison. The LNOM lightning characteristics and LNOX production estimates are compared to the evolution of updraft and precipitation properties inferred from dual‐Doppler and polarimetric radar analyses applied to observations from a nearby radar network, including the UAH Advanced Radar for Meteorological and Operational Research (ARMOR). Given complex multicell evolution, particular attention is paid to storm morphology, cell mergers and possible dynamical, microphysical and electrical interaction of individual cells when testing various hypotheses.

Carey, Lawrence↗
NASA NTRS2005

Using Beta Cen to Probe the Photosphere-wind Connection in B Stars

In this project we began by identifying the large number of emission lines visible in the XMM-Newton RGS spectra of Beta Cen. A comprehensive analysis of the temperature structure of the hot gas was carried out by simultaneously fitting the data from all the instruments on the spacecraft. This resulted in a measured temperature range of 0.1-0.6 keV. In more detailed analysis, three characteristic plasma temperatures were found: 0.1, 0.2, and 0.6 keV. The research carried out at UW-Eau Claire primarily focused on two aspects of the data: the analysis of the forbidden line to intercombination line ratio for He-like ions and the time variability of the overall X-ray flux as detected in the direct X-ray images of the star. The analysis of the lines from He-like ions indicate that the Ne IX lines are formed no farther than about 4 stellar radii from the star's photosphere, while the N VI lines are formed within 11 stellar radii of the photosphere. X-ray flux variability would be particularly interesting for this star because it is a known Beta Cep-type variable as seen in optical light: similar variation in the X-ray region would forge an interesting link between the two wavebands. Initial analysis of the X-ray flux was complicated by spikes in the count rates early in the observation. Detailed analysis of the spectral characteristics these count rate anomalies indicated that these flares were probably not intrinsic to the star, rather they were contaminations of the data due to the passage of the satellite through soft proton clouds in the Earth's magnetosphere. An analysis of the light curve of the uncontaminated portions of the light curve did not reveal any variation on the known optical period of variation for this star, and a general search for periodic variability also did not find any significant periods of variation.

Miller, Nathan A.↗
NASA NTRS2014

The Kinematic and Microphysical Control of Lightning Rate, Extent and NOX Production

The Deep Convective Clouds and Chemistry (DC3) experiment seeks to quantify the relationship between storm physics, lightning characteristics and the production of nitrogen oxides via lightning (LNOx). The focus of this study is to investigate the kinematic and microphysical control of lightning properties, particularly those that may govern LNOx production, such as flash rate, type and extent across Alabama during DC3. Prior studies have demonstrated that lightning flash rate and type is correlated to kinematic and microphysical properties in the mixed-phase region of thunderstorms such as updraft volume and graupel mass. More study is required to generalize these relationships in a wide variety of storm modes and meteorological conditions. Less is known about the co-evolving relationship between storm physics, morphology and three-dimensional flash extent, despite its importance for LNOx production. To address this conceptual gap, the NASA Lightning Nitrogen Oxides Model (LNOM) is applied to North Alabama Lightning Mapping Array (NALMA) and Vaisala National Lightning Detection Network(TM) (NLDN) observations following ordinary convective cells through their lifecycle. LNOM provides estimates of flash rate, flash type, channel length distributions, lightning segment altitude distributions (SADs) and lightning NOx production profiles. For this study, LNOM is applied in a Lagrangian sense to multicell thunderstorms over Northern Alabama on two days during DC3 (21 May and 11 June 2012) in which aircraft observations of NOx are available for comparison. The LNOM lightning characteristics and LNOX production estimates are compared to the evolution of updraft and precipitation properties inferred from dual-Doppler and polarimetric radar analyses applied to observations from a nearby radar network, including the UAH Advanced Radar for Meteorological and Operational Research (ARMOR). Given complex multicell evolution, particular attention is paid to storm morphology, cell mergers and possible dynamical, microphysical and electrical interaction of individual cells when testing various hypotheses.

Carey, Lawrence↗
NASA NTRS1999

Combined Satellite and Surface-Based Estimation of the Intracloud/ Cloud-to-Ground Lightning Ratio Over the Continental United States

Four years of observations from the NASA Optical Transient Detector (OTD) and Global Atmospherics National Lightning Detection Network (NLDN) are combined to determine the geographic distribution of the intracloud/cloud to ground lightning ratio over the continental United States. The mean ratio over this region is 2.64-2.94, with a standard deviation of 1.1-1.3 and anomalies as low as 1.0 or less over the Rocky and Appalachian mountains and as high as 8-10 in the central-upper midwest. There is some indication that the ratio covaries with ground elevation, although the relationship is nonunique. Little evidence is found to support a latitudinal covariance, despite significant variation in the climatological mean tropopause pressure over the latitudes considered. The dynamic range of local variability is comparable to the range of values cited by previous studies for latitudinal variation from the deep tropics to midlatitudes. Local high anomalies of this ratio in the midwest are coincident with anomalies in the climatological percentage of positive CG occurrence, as well as in the occurrence of large positive CGs characteristic of MCS convective and trailing stratiform regions. This suggests that storm type, morphology and level of organization may dominate over environmental cofactors in the local determination of this ratio.

Boccippio, D. J.↗
NASA NTRSDate not supplied

MISR Level 2 TOA/Cloud Stereo parameters (MIL2TCST_V1)

The MISR Top-of-Atmosphere (TOA)/Cloud Stereo geophysical parameters include stereoscopically-derived cloud motion vectors (winds), cloud-top heights, and an accompanying cloud mask. The Stereo product geophysical parameters include a stereoscopically-derived cloud mask and cloud height on a 1.1 km grid. It also includes cloud motion vectors on a 70.4 km grid. The three types of stereo heights are: the BestWind heights are only calculated for those regions where the associated wind vectors passed the quality tests. Therefore, they have sparse coverage but since the wind correction is included, these contain our 'best guess' as to what the true heights are. The WithoutWind heights are calculated assuming a constant wind vector of zero. They have almost complete coverage and therefore form a nice 'pretty picture' of the relative cloud heights over small areas. The RawWind heights are a diagnostic product as they are calculated using all available wind vectors (even the bad ones). It is therefore recommended that one only use the Best and Without wind products. It is important to remember that the stereo matchers pick up the layer of maximum contrast, which is not necessarily the same as the highest cloud so all the stereo heights are keyed to this level of maximum contrast. Therefore, higher and thinner cirrus layers may not be detected by any of the height fields. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Horizontal_Resolution_Range=1 km - < 10 km or approximately .01 degree - < .09 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly].

EOSDIS↗