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At least 667 records · Page 37

RELAMPAGO Lightning Mapping Array Update

GLM (Geostationary Lightning Mapper) Science Hypothesis for RELAMPAGO (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations): Argentinian storms produce some of the highest flash rates ever recorded from space; Due to similarity in geographic and atmospheric environments between Argentina and the U.S. High Plains, we hypothesize that many of these storms have anomalous charge structures, with predominantly positive charge in the mid-levels; Thus, most intracloud lightning flashes are smaller, occur at lower altitudes, and occur in more optically thick portions of the cloud; Therefore, we hypothesize that GLM (and LIS (Lightning Imaging Sensor)) flash rates are biased low in many Argentinian storms, due to reduced optical detection efficiency.

Lang, Timothy↗

NASA's Land, Atmosphere Near Real-Time Capability for EOS (LANCE): Delivering Data and Imagery to Meet the Needs of Near Real-Time Applications

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) is a virtual system that provides near real-time EOS data and imagery from the AIRS, AMSR2, LIS (ISS), MISR, MLS, MODIS, MOPITT, OMI, OMPS, and VIIRS instruments, to meet the needs of scientists and application users interested in monitoring a wide variety of natural and man-made phenomena. NRT imagery from LANCE are available through NASA's Global Imagery Browse Services (GIBS), Worldview, FIRMS and most recently through Worldview Snapshots – a low band width application that has replaced the Rapid Response Subsets. Over the past year: data and imagery from the Lightning Imaging Sensor (LIS) on board the International Space Station (ISS), OMPS and VIIRS-Land have been added to LANCE. In the coming year LANCE will integrate the MODIS NRT Global Flood product, VIIRS Black Marble nighttime lights and Cloud Mask and Aerosol Dark Target from VIIRS Atmosphere. Here we provide a brief overview of LANCE, focusing on what's new and describing how these new data sets have been used to monitor lightning flashes, hurricanes and fires. For more information on LANCE visit: https://earthdata.nasa.gov/lance.

Davies, Diane↗

Lightning Enriched Global Precipitation Feature Database

The Tropical Rainfall Measurement Mission (TRMM) has provided a wealth of insight about lightning and precipitation in the tropics. However TRMM did not provide coverage outside the tropics and sub-tropics (i.e., beyond ±38°latitude), and hence it was unable to sample the lightning activity and precipitation features over a large fraction of mid-latitude continents and oceans, including extratropical cyclone storm tracks. The Global Precipitation Measurement (GPM) mission picks up where TRMM left off in that it provides information on precipitation features in the mid-and high latitudes (up to 65°N/S). However, GPM lacks a lightning instrument that can provide additional insights into mid-latitude thunderstorm activity and distribution. Hence we integrate observations from coincident the ISS Lightning Imaging Sensor (LIS) and the World Wide Lightning Location Network (WWLLN) observations with measurements from the GPM constellation of satellites, in particular to extend the existing GPM Precipitation Feature (PF) database so its data parameters are similar to that of the TRMM PF database (i.e., precipitation + lighting). Currently, WWLLN and ISS-LIS lightning have been collocated into precipitation features defined from GPM core satellite and constellation satellites observations.

Precipitation↗

Nitrogen Oxides in the Global Upper Troposphere: Interpreting Cloud-Sliced NO2 Observations from the OMI Satellite Instrument

Nitrogen oxides (NOx≡NO+NO2) in the upper troposphere (UT) have a large impact on global tropospheric ozone and OH (the main atmospheric oxidant). New cloud-sliced observations of UT NO2 at 450–280 hPa (∼6–9 km) from the Ozone Monitoring Instrument (OMI) produced by NASA and the Royal Netherlands Meteorological Institute (KNMI) provide global coverage to test our understanding of the factors controlling UT NOx. We find that these products offer useful information when averaged over coarse scales (20°×32°, seasonal), and that the NASA product is more consistent with aircraft observations of UT NO2. Correlation with Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) satellite observations of lightning flash frequencies suggests that lightning is the dominant source of NOx to the upper troposphere except for extratropical latitudes in winter. The NO2 background in the absence of lightning is 10–20 pptv. We infer a global mean NOx yield of 280±80 moles per lightning flash, with no significant difference between the tropics and midlatitudes, and a global lightning NOx source of 5.9±1.7 Tg N a(exp −1). There is indication that the NOx yield per flash increases with lightning flash footprint and with flash energy.

Marais, Eloise A.↗

The Evolution and Extratropical Transition of Tropical Cyclones from a GPM, ISS LIS and GLM Perspective

Not much is known about the evolution of lightning within extra-tropical cyclones traversing the mid-latitudes, especially its oceans. To facilitate such studies we combine a recently constructed precipitation features (PF) database obtained from the Global Precipitation Measurement (GPM) mission constellation of satellites with lightning observations from the Geostationary Lightning Mapper (GLM) onboard GOES-16 and the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS). The goal of this study is to provide a new observationally-based view of the tropical to extra-tropical transition and its impact on lightning production. Such data fusion approaches, as presented here, will also be important in future satellite studies of convective precipitation.

Gatlin, Patrick↗

Application of New Technology to Future Celestial Trackers

New developments in image sensors and optical materials have opened the door to dramatic mass and power reductions in celestial tracker designs. The rapid development of active pixel sensors (APS) has provided a new detector choice offering high on-chip integration of support circuitry at reduced power consumption. Silicon-Carbide (Si-C) optics are one of the new developments in low-mass optical components. We describe the celestial tracker needs of an Autonomous Feature and Star Tracking (AFAST) system designed for autonomous spacecraft control. Details of a low mass celestial tracker, based on a low power APS array and optimized for an AFAST system, are discussed.

active↗

Approaches and Analysis for On-Focal-Plane Analog-to-Digital Conversion

This paper presents approaches for on-focal-plane analog-to-digital conversion (ADC). Common approaches and architectures for ADC and their utility for on-focal-plane integration are discussed. Candidate approaches are analyzed with respect to required amplifier gain, bandwidth, capacitance matching, noise and offsets as a function of ADC resolution. A column-parallel ADC architecture appears to be an effective compromise of chip area, power, circuit speed and ADC resolution. The discussion is valid for both infrared focal-plane arrays (FPAs) and visible image sensors.

analog-to-digital↗

Homogenized Water Vapor Absorption Band Radiances From International Geostationary Satellites

In the past 20+ years, GEO Imagers with infrared 6.5‐μm bands have been observing the Earth's atmosphere, providing useful information of upper tropospheric moisture. Due to the instrumental differences and local viewing angles in GEO satellites, these observations are not consistent for generating climate data records (CDRs). In this study, a methodology has been developed to homogenize the 6.5‐μm radiances from the international GEO satellites, to generate a consistent CDR. Validations with Infrared Atmospheric Sounding Interferometer radiances from Metops for 2015–2017for seven GEO Imager sensors show that the GEO radiances are homogenized well with small standard deviation and biases of the differences (smaller for newer sensors), temporally stable radiometric accuracy, and weak angle dependency (even weaker for sensors with two water vapor bands). The homogenized 20+ years of consistent 6.5‐μm radiance CDR can be used to evaluate reanalysis and climate models, especially the diurnal variation of the model simulation.

Water Vapor↗

Intercalibration of the reflective solar bands of MODIS and MISR instruments on the Terra platform

The multispectral imaging sensors on the Terra platform have been operating for over two decades facilitating a variety of scientific applications. The MODIS sensor provides the largest spectral coverage of 0.41 to 14.2 μm, acquiring data at three different spatial resolutions, 250 m, 500 m, and 1 km. The MISR instrument views the Earth using nine discrete cameras pointed at fixed angles including viewing the nadir direction at a spatial resolution of 275 m and covering a wavelength range from 0.44 to 0.86 μm. Being on the same platform, the two sensors complement each other in terms of spatial coverage (and target viewing geometry) and facilitate synergistic applications using multispectral data. A consistent radiometric calibration between these sensors is a prerequisite for creating high quality science products from their observations. Both instruments underwent intensive prelaunch characterization, with calibration monitored on-orbit using their onboard calibrators. In this paper, we perform a calibration inter-comparison of the spectrally matching bands of the two instruments using vicarious techniques. Vicarious techniques include multiyear simultaneous views of the North African desert, North Atlantic Ocean and Dome Concordia, thereby covering the different parts of the dynamic range. Also included in this work are the near-simultaneous top-of-atmosphere (TOA) reflectance measurements from Railroad Valley, USA, as provided by the RadCalNet (converted to TOA), that are used as a calibration reference to compare the on-orbit observations between MODIS and MISR.

Intercalibration↗

The Multiplatform Precipitation Feature (MPF) Database: Synthesizing Satellite and Ground-Based Precipitation and Lightning Datasets for Convective Studies

NASA’s Lightning Imaging Sensor (LIS) and the Global Precipitation Measurement (GPM) mission have contributed a wealth of data toward global lightning and precipitation studies, respectively. Combining lightning and precipitation datasets leverages their unique insights into deep convective processes that inform about characteristics of convection and its intensity. Recent efforts to synthesize the LIS and GPM datasets prepare the opportunity for unprecedented large-scale, value-added multiplatform analyses of convection. This data synthesis proof-of-concept study elaborates on the creation of a database of reflectivity-based multiplatform precipitation features (MPFs) that capture a combination of information extracted from spatiotemporally coincident lightning and precipitation data within individual storm features. The space-based GPM Dual-frequency Precipitation Radar (DPR) provides a record of precipitation data, while the GPM Validation Network (VN) additionally incorporates ground-based polarimetric Doppler radar data to provide microphysical and kinematic context to DPR data. The LIS instrument onboard the International Space Station has contributed lightning observations since 2017. MPFs encapsulating information from these datasets are created from isolated regions of filtered, smoothed DPR reflectivity data to which ellipses are fit. Each MPF includes feature location, size, and eccentricity information as well as summary reflectivity characteristics. They also include summaries of precipitation microphysics and derived three-dimensional wind available from ground-based radar data. LIS data provides standard lightning characteristics such as flash count and density to each MPF as well as other informative metrics such as flash area and radiance. Each MPF file includes information about the original data from which the MPF and its characteristics were determined, allowing end-user reconstruction of the ellipse and deeper “level I” analysis of captured data. This database of VN-LIS MPFs enables broad statistical analysis of the relationships between the microphysical, kinematic, and electrical properties of convection. Preliminary results from a demonstration of the database will be described as well as ongoing efforts and avenues for future work.

Lightning↗

Quality Assurance of ISS LIS lightning Data

Optical lighting detection from space has been ongoing since 1995 from the Optical Transient detector (1995-2000), then later by the Lightning Imaging Sensors (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite (1997-2015) and the International Space Station (ISS) (ISS 2017-present). A rapid readout (2 ms) 128x128 pixel CCD (Charge-coupled Device) array detects optical transients from lightning (events) and transmits the observations to ground. Ground processing determines whether individual events are likely due to lightning or noise. Likely lightning events are then grouped into groups, flashes, and areas and their location on the earth are determined. The lightning data are saved in orbit files; each file containing the time, location, and intensity of the lightning events, groups, flashes, and areas detected during one orbit. Even after this processing anomalies may exist in some of the orbits. A manual quality assurance (QA) procedure is performed monthly to assess the data and omit orbits with obvious anomalies from the dataset. These files are not included in the final dataset that has undergone QA. The manual QA was developed during the OTD mission to identify artifacts that made it through ground processing algorithms. The manual QA process was continued for the TRMM and ISS LIS missions. Many anomalies have been identified and software updates now address many of them. However, some anomalies still occur in the processed datasets. The manual QA process examines the data for obvious issues in the lightning files that passed through the processing algorithms. These files are considered anomalous and are not included in the final QA dataset. Some issues that may cause an orbit to be considered anomalous include: obvious noise (excess events that make it through the processing), suspect geolocation, and excessive missing data packets. As an example, one way noise manifests is as “streaks” in lightning climatology plots. These streaks are especially apparent in low lightning rate regions (eg., over oceans). Since there is no method at present to extract these anomalies during processing, orbit files with significant anomalies are identified and removed from the final QA ISS LIS dataset. The final QA dataset can be obtained files from the Global Hydrometeorological Resource Center (GHRC). This presentation will provide examples of the various anomalies and examine how often the various anomalies occur and how much data is lost due to the omission of the anomalous orbits. Comparisons with OTD and TRMM LIS will also be examined.

ISS↗

Interannual Lightning Variability within the TRMM LIS Dataset Using an ENSO Perspective

The Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) was used to investigate inter-annual variability of lightning from 1998-2014 within the 38° S – 38° N range. Previous studies have indicated that the El-Niño/Southern Oscillation (ENSO) phenomenon is one significant contributor to inter-annual lightning variability, potentially the dominant mechanism on the global scale. This period of 16 years contained four warm- (El Niño), eight cold- (La Niña), and four neutral-phase ENSO years based on the oceanic Niño index. Large magnitude lightning anomalies were found during the warm phase of ENSO, with mean warm-phase anomalies of > 10 Fl (1000 km) −2 min −1 in north-central Africa and Argentina. This includes a +35 Fl (1000 km) −2 min −1 anomaly in Argentina during the 2009 El Niño. In general, large-scale anomalies of thermodynamic properties and upper-atmospheric vertical motion coincided with the lightning anomalies observed in both Africa and South America. The anomaly over north-central Africa, however, was characterized by a 6-week shift in the annual lightning maximum with the warm phase, a result of the more complex environmental response to ENSO over the Sahel. The most consistent ENSO anomalies with appreciable lightning were found in southeastern Africa, northwestern Brazil, central Mexico, and the southern Red Sea. Of these, all but the Mexico region had enhanced lightning with the cold phase and suppressed lightning with the warm phase.

Austin G. Clark↗

Leveraging the Multiplatform Precipitation Feature Database of Combined Ground Radar and Satellite Lightning Observations for Convective Studies

The Multiplatform Precipitation Feature (MPF) database combines coincident observations of lightning from space with satellite- and ground-based radar data in a storm-based, feature-defined framework. The concept for the MPF database stems from the motivation to extend the scale and scope of investigations into the complex connections between ice precipitation, updrafts, and lightning in thunderstorms. The earliest iteration of the MPF database incorporates NASA International Space Station Lightning Imaging Sensor (ISS LIS) observations alongside the NASA Global Precipitation Measurement (GPM) Mission Dual-frequency Precipitation Radar (DPR) and Validation Network (VN). Because of the specific role of the GPM VN in forming the first MPFs, this subset is referred to as the VNMPF database. The synthesis of these multi-scale and multi-resolution observations leveraged each platform’s unique insights into convective properties and processes, offering a more complete view of deep convection over the large viewing area afforded by satellite coverage. The VNMPF database established the feasibility and infrastructure to combine microphysical, kinematic, and lightning observations from multiple satellite- and ground-based platforms. Following this successful proof-of-concept, recent progress has expanded the MPF database to make use of coincident ISS LIS lightning observations and data from the operational Weather Surveillance Radar - 1988 Doppler (WSR-88D) network, where individual WSR-88D proximity facilitates vertical wind retrievals via dual-Doppler analysis. These database changes have expanded the scope of the dataset by removing the requirement for coincident GPM and ISS LIS overpasses. This increases the sample size dramatically and facilitates analysis of higher-resolution radar-derived properties. These advancements allow both storm-scale and unprecedented broad statistical analyses of deep convection from electrical, kinematic, and microphysical perspectives over the contiguous United States. This presentation outlines the construction of the new MPF database and introduces some preliminary analyses of the convection captured within it. Early results summarize relationships based on updraft characteristics ascertained from WSR-88D dual-Doppler three-dimensional wind retrievals, properties of ice microphysics gleaned from dual-polarization analyses, and electrical characteristics observed by the ISS LIS. The expanded scale and scope offered by more than five years of ISS LIS observations enable new insights into regional and seasonal variations in the microphysical, kinematic, and electrical relationships of convection. Analysis of the database highlights the potential for advancements in lightning meteorology made possible by combining large-scale spaceborne lightning detection and proven storm interrogation tools such as operational polarimetric Doppler radar.

Lightning↗

Exploring Lightning and Convective Processes Using the Ground-Radar Multiplatform Precipitation Feature Database

The Multiplatform Precipitation Feature (MPF) database synthesizes coincident spaceborne and ground-based lightning and radar data in a framework of storm-based features, fusing broader spaceborne detection capabilities with process-based, storm-level analysis practices. The MPF database was designed to extend the scale and scope of investigations into the complex connections between precipitation, updrafts, and lightning. The NASA International Space Station Lightning Imaging Sensor (ISS LIS) serves as the source of lightning information for the database. The first iteration of the MPF database leveraged the NASA Global Precipitation Measurement (GPM) mission spaceborne Dual-frequency Precipitation Radar (DPR) to define features, along with contributions of microphysics data and vertical wind retrievals from the GPM Validation Network (VN) of ground-based radar data. The dependency on coincident ISS and GPM satellite overpasses of radars in a dual-Doppler configuration significantly limited the size of the initial database of features, referred to as VNMPFs, but established the database infrastructure and feasibility. We present here a second iteration of the MPF database that omits the GPM DPR and VN, instead incorporating data directly from selected proximal installations of the operational Next Generation Radar (NEXRAD) network that facilitate vertical wind retrievals via dual-Doppler analysis. These features based exclusively on ground-based polarimetric Doppler radar are hereafter referred to as Ground-Radar MPFs (GRMPFs). Removing the restriction of a coincident GPM overpass appreciably increases the size of the GRMPF database while incorporating more detailed information from higher-resolution radar data and retrievals. This expansion allows for unprecedented broad, robust statistical analyses of the electrical, kinematic, and microphysical characteristics of deep convective processes. These results highlight the potential for advancements in lightning meteorology made possible by combining multiple perspectives from global lightning measurements and ground-based radar data.

Lightning↗

Overview of Lightning Science at NASA Marshall Space Flight Center

NASA Marshall Space Flight Center (MSFC) is a recognized world leader in the science of lightning. To date, MSFC has led three space-based global lightning observing missions and has helped lead multiple suborbital field campaigns involving lightning observations. Recently, the MSFC Lightning Team is closing out the recently completed International Space Station Lightning Imaging Sensor (ISS LIS) mission, including developing a nearly three-decade global climatology of lightning from space. This work also includes integrating lightning observations with data from NASA precipitation missions. The Team is also busy analyzing data from a recent airborne field campaign that observed dozens of terrestrial gamma-ray flashes (TGFs) from intense tropical thunderstorms. Lightning Team members are also leaders in validation of the Geostationary Lightning Mapper (GLM) operated by NOAA, and in developing lightning safety applications and studying the relationship between lightning and wildfires. The Lightning Team also studies chemical production by lightning and contributes to the National Climate Assessment (NCA). Finally, the Lightning Team is busy developing the next generation of spaceborne lightning sensors to broaden our understanding of the relationships between lightning, weather, climate, and atmospheric composition.

Timothy Lang↗

Towards A Multi-Decadal Climatology of Lightning From Space

Since 1995, NASA has launched three different low-Earth orbit (LEO) missions to observe global lightning from space: the Optical Transient Detector (OTD), the Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS), and the International Space Station (ISS) LIS. ISS LIS completed its mission in November 2023, and is currently in Phase F, producing final data.

Timothy J Lang↗

Towards a Combined Low-Earth Orbit Lightning Climatology: Current Work and Assessing South Atlantic Anomaly Influence

This presentation discusses the current status and ongoing work towards a low-Earth orbit (LEO) lightning climatological product that includes both Lightning Imaging Sensors (LIS) and the Optical Transient Detector (OTD). The project builds upon the work by Cecil et al. (2014) to include the LIS on the International Space Station (ISS), featuring additional inter-instrumental comparisons to more accurately depict the unique capabilities of each instrument. A closer examination of the interference from the South Atlantic Anomaly (SAA) was also conducted on all three LEO sensors. The SAA is a region of the magnetosphere roughly spanning the south-central Atlantic wherein the inner Van Allen radiation belts are closer to Earth than anywhere else, subjecting spacecraft in LEO to significantly higher radiation flux levels. This radiation can produce interference with the LIS and OTD instruments, manifesting as non-lightning luminous events. While these events can be identified easily enough, they can occur in such quantities that they overwhelm the sensors’ processors and effectively ‘blind’ them. This is called the First-In First-Out (FIFO) buffer overflow, and this blinded time reduced the instruments’ view-time as a result. The FIFO overflow and view-time can reliably be used to track the SAA interference (Clark et al. 2024), which allows for the lightning counts attributable to the SAA to be assessed. The impact that the SAA had on the quality of observations from the LEO lightning instrumentation and the significance for the resulting climatological products was investigated. Substantial areas of interference were identified for all three instruments using the view-time and quality flags, each with a unique shape and temporal evolution. The temporal evolution and general region affected are of particular importance when constructing a climatological product, as there are notable reductions to view-time over prolonged periods across a lightning-rich region. However, a temporal element also makes isolating the subsequent impact on the lightning signal significantly more challenging. Lightning counts in this region are highly seasonal and exhibit inter-annual variability, which is compounded by the nature of LEO observations. This study includes preliminary analysis of the impact that the SAA has on the lightning counts given the notable impact shown in the metadata.

Austin G Clark↗