Image navigation and registration for the geostationary lightning mapper (GLM)

Bezooijen, Roel W. H. van; Demroff, H.P.; Burton, Gregory; Chu, Donald; Yang, Shu

doi:10.1117/12.2242141

Cited by 5 publications

(6 citation statements)

References 2 publications

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“…The GLM L1b processing computes and utilizes the fixed grid coordinates then discards them during L2 processing. Therefore, the fixed grid coordinates of the flash, group, and event centroids are calculated from the L2 data by inverting the equations of Bezooijen et al ().…”

Section: Procedures For Constructing Glm Imagerymentioning

confidence: 99%

Meteorological Imagery for the Geostationary Lightning Mapper

et al. 2019

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The Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite‐R series of weather satellites provides point geolocations of lightning flashes that are further comprised of a hierarchy of geolocated groups and events. This study describes an open‐source method for reconstruction of imagery from those point detections that retains the quantitative physical measurements made by GLM, restores the spatial footprint of the events, and connects that spatial footprint to the groups and flashes. Meteorological signals are demonstrated to be more apparent in the gridded imagery than in the point detections, leading to their adoption by the United States National Weather Service as the first GLM product available in their real‐time displays. Analysis of a mesoscale convective system over Argentina confirms that there is a class of propagating lightning observed by GLM (distinct from that in storm cores) that can be visualized and quantified using our imagery‐based approach.

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Section: Procedures For Constructing Glm Imagerymentioning

confidence: 99%

Meteorological Imagery for the Geostationary Lightning Mapper

et al. 2019

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“…Since our goal is to identify corresponding L0 and L2 events, we navigate the L0 events to an ellipsoid approximating the tropopause as in the L2 ground processing. Navigation of GLM events can be boiled down to the following three steps: Compute a unit vector

{boldv}_{italicgf}

along the line of sight in the GLM functional coordinate frame (defined in van Bezooijen et al., 2016). Rotate

{boldv}_{italicgf}

into the International Terrestrial Reference System to obtain the vector

{boldv}_{italicit}

. Calculate the geodetic latitude and longitude of the point at which the line along

{boldv}_{italicit}

intersects the lightning ellipsoid. …”

Section: Data Extractionmentioning

confidence: 99%

“…The L2 processing maps, or navigates, the CCD coordinates of each pixel event to geodetic coordinates corresponding to the center of the pixel footprint at the time of the event. We have implemented all aspects of the image navigation procedure used in GLM ground processing (van Bezooijen et al., 2016 ) except for accounting for the Earth's nutation. Annual nutation effects are typically a few tens of arc seconds, which is comparable to the field of view of a single GLM pixel (~21 arcsec at the center of the focal plane).…”

Section: Data Extractionmentioning

confidence: 99%

Correction and calibration of atmospheric impact observations in GOES GLM data

Morris

Smith

Dotson

et al. 2022

Meteorit & Planetary Scien

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The Earth's atmosphere is impacted daily by both meteoroids and artificial objects. Calibrated observations of the emitted light at sufficiently high sampling rates can enable or improve the estimation of impactor attributes such as size, cohesion, trajectory, and composition, but are difficult to obtain owing to the unpredictability, brevity, and high dynamic (brightness) range of impacts. Ground‐based camera systems have successfully monitored small regions of the atmosphere at video frame rates and with limited radiometric capabilities, but most impacts occur over the 70% of the Earth's surface covered by water and are therefore missed by these networks. The Geostationary Lightning Mapper (GLM) instruments aboard Geostationary Operational Environmental Satellites 16 and 17 provide near‐hemispherical coverage at 500 frames per second. These data have been shown to contain the signatures of many independently confirmed impacts, often from both viewing angles simultaneously, and constitute an observational resource that is currently unparalleled in the public domain. NASA's Asteroid Threat Assessment Project has implemented an automated impact detection pipeline that processes data from GLM daily. Given a detected impact, the GLM data contain a wealth of information for use in quantitative follow‐up analyses. However, impact events differ from lightning in ways that violate key assumptions built into GLM's design. The result is that GLM's onboard processing introduces errors into pixel observations of impact events and the calibrated energies near the periphery of the detector may be substantially overestimated. We present methods for mitigating these and other issues to produce a data product more suitable for impact analyses than the existing GLM lightning product.

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“…Recovery of flux in calibrated units is further complicated by the fact that the object's altitude, velocity, size, and view angle all affect the spectral irradiance at the GLM detector. The reported GLM group time is corrected for light time but to typical lightning altitudes of approximately 10km [31], whereas bolides are typically around 80km [27]. A parallel effort within ATAP aims to recover calibrated light curves from the Level 0 data products, including uncertainties.…”

Section: Goes Glm Datamentioning

confidence: 99%

“…If there is an event in the stereo region detected by both GLM-16 and GLM-17 each ground track can be re-navigated by raising the altitude until ground track parallax errors are minimized. The standard GLM ground segment pipeline [29] cannot determine altitude so the GLM Level 2 data product assumes a lightning altitude that is approximately 10 km above the earth's surface [31]. Bolides are luminous at much higher altitudes (usually well above 30km).…”

Section: Manual Bolide Candidate Vettingmentioning

confidence: 99%

An Automated Bolide Detection Pipeline for GOES GLM

Smith,

Morris,

Rumpf

et al. 2021

Preprint

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Image navigation and registration for the geostationary lightning mapper (GLM)

Cited by 5 publications

References 2 publications

Meteorological Imagery for the Geostationary Lightning Mapper

Meteorological Imagery for the Geostationary Lightning Mapper

Correction and calibration of atmospheric impact observations in GOES GLM data

An Automated Bolide Detection Pipeline for GOES GLM

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