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ABI has two imaging modes, namely Mode 3 and Mode 4. Mode 4 can provide 30 Mesoscale images every 15 minutes as well as a Full Disk every 5 minutes. The intent is to allow for better identification and tracking of cloud and moisture signatures. The band selection has been optimized to meet all cloud, moisture, and surface observation requirements. The phenomena observed and the various applications are:. Daytime cloud imaging, snow and ice cover, severe weather onset detection, low-level cloud drift winds, fog, smoke, volcanic ash, flash flood analysis, hurricane analysis, winter storm analysis.

Middle-tropospheric water vapor tracking, jet stream identification, hurricane track forecasting, mid-latitude storm forecasting, severe weather analysis. Continuous cloud monitoring for numerous applications, low-level moisture, volcanic ash trajectories, cloud particle size in mid-band products. Cloud top height assignments for cloud-drift winds, cloud products for ASOS supplement, tropopause delineation, cloud opacity.

This band is used for aerosol detection and visibility estimation. It does not see into the lower troposphere due to water vapor sensitivity, thus it provides excellent daytime sensitivity to very thin cirrus. This includes a more accurate delineation of ice from water clouds during day or night. The band permits the determination of microphysical properties of clouds with the This includes a more accurate determination of cloud particle size during the day or night. Under terms of the contracts, each company developed detailed engineering plans for the future instrument.

In , the ITT Corporation split into three companies: Key performance parameter comparison of 2nd and 3rd generation imagers Ref. Ground storage On-orbit storage Mean mission life Design life. Requirements overview for the ABI instrument. Total water for stability, cloud phase, dust, SO 2 , rainfall. Overview of the spectral band allocation for the ABI instrument. Schematic view of the ABI instrument image credit: Approximate number of ABI pixels for various support modes Ref.

The two-stage cold head was designed to provide large cooling power at 53 K and K, simultaneously. NGAS evolved the design from on-orbit pulse tube cooler designs that the company has built and launched over the past decade. No failures have been experienced on any of these coolers on the seven satellite systems launched to date; some of these coolers are now approaching 11 years of failure-free operation. The PFM Proto-Flight Module cooler system for ABI consists of a linear pulse tube cold head that is integral to the compressor assembly and a coaxial remote pulse tube cold head; the two cold head design affords a means of cooling a detector array to its operational temperature while remotely cooling optical elements to reduce effects of radiation on imager performance and a second detector array.

The TDU has a size of mm x mm x mm width x depth x height with a mass of 5. The size of CCE is mm x mm x 85 mm width x depth x height with a mass of 3. The requirements on the cooler call for: Since ABI uses multiple focal plane modules for the channels of detector grids, the channel-to-channel registration can present a challenge if relative motion occurs from one focal plane module to another.

This is especially the case given the ABI channel-to-channel registration requirements are at sub-pixel levels. Once the image data are processed on ground, a series of manual landmarking registration techniques are applied to the image to improve the location of features in the image relative to known landmarks within the scene. The landmarking updates are also used to update the IMC coefficients for the following day's operation.

ABI INR relies on a ground-based real time image navigation process to achieve increased knowledge accuracy using precise encoder readings and star image data. During an Earth scene collection, the instrument uses attitude information provided by the spacecraft to compensate for the spacecraft's attitude motion; however the precise image navigation and registration is achieved through ground processing to determine where the image data were actually collected relative to the fixed grid scene. ABI collects scene image data as well as star measurements to maintain line of sight knowledge.

Image navigation uses ground processing algorithms to decompress, calibrate and navigate the image samples from the focal plane module detectors. Image collection performance for the ABI is governed by the attitude knowledge provided by the spacecraft, the control accuracy of the pointing servo control for the instrument and the diurnal line of sight variation. Image navigation and registration uses data and measurements defined in a number of different coordinate frames. The primary reference frame is J which is the inertial frame in which the star catalog coordinates are defined.

Orbit determination and body axis attitude reporting are done relative to a frame defined by the velocity vector and nadir referred to as to ORF Orbit Reference Frame. The ABI instrument alignment is referenced to a frame relative to the spacecraft body axis frame referred to as the IMF Instrument Mounting Frame and line of sight is referenced to a frame relative to the instrument mounting frame.

Frame-to-frame registration error is the difference in navigation error for any given pixel in two consecutive images within the same channel. Angular separation of any two pixels in a Frame. Reference frames used in the INR process image credit: ABI image navigation and registration process image credit: ABI's advanced design will provide users with twice the spatial resolution, six times the coverage rate, and more than three times the number of spectral channels compared to the current GOES Imagers.

The operations flexibility permits consistent collection of Earth scenes, eliminating time gaps in coverage by the need to prioritize some areas over others. These improvements will allow tomorrow's meteorologists and climatologists to significantly improve the accuracy of their products, both in forecasting and nowcasting. Photo of the ABI instrument image credit: However, its most unique feature is its operational flexibility - one instrument seamlessly interleaving the collection of multiple images of different sizes, locations, and repetition intervals plus the ability to collect scan data in any direction.

This enables the high temporal resolution imaging of severe weather events hurricanes, typhoons, tornados, etc. ABI's ability to interleave image collections ensures all regions will be imaged far more frequently than with the current imagers. Hence, ABI's image collections can be simplified to just three standard images:. The sizes of these images are provided in Table 9 and their locations are provided in Table Note that all images are defined in radians. Degrees and kilometer equivalents are provided for convenience. This information is also provided visually in Figure 39 , Figure 40 , and Figure In Figure 6 some possible locations are shown nadir, tornado in the mid-West, hurricane off the coast of Florida, lunar observation.

Sizes of the ABI operational images. Locations of the ABI operational images. An ABI scene definition defines the scan patterns needed to collect a desired image. Each scene is a collection of individual swaths. The ABI timeline defines when to collect each swath of each scene. ABI currently has two operational timelines, created by Harris based on our customer's requirements:. All operational ABI timelines include observations for radiometric and geometric calibration. All timelines start with a space look and blackbody observation and collect a space look at least every 30 seconds for radiometric calibration.

Hence, blackbody observations occur at least every 15 minutes, far more frequently than required to meet the IR calibration accuracy requirements. All operational ABI timelines include visible stars observations on average at least every s and IR stars observations on average at least every s for navigation i. Hence, observations of the solar calibration target are not included in the operational timelines.

They are collected using a custom timeline, which is run approximately every two weeks at the start of the operational mission and less frequently later in the mission. Custom scenes and timelines can be defined and uploaded at any time during the mission life. This is not currently an operational timeline.

However, it is expected to become an operational timeline once the GOES-R ground system parameters are updated to include processing and distribution of Full Disk image products on minute intervals in addition to the current 5 and 15 minute intervals and the users' systems have been updated to receive Full Disk products on minute intervals. Images collected by the baseline ABI timelines.

In the Scan Mode 3 and 6 timelines, a mesoscale image is collected every 30 seconds. However, ABI provides the user the option to define two different mesoscale image locations Meso 1 and Meso 2 and collect both of them at 1 minute intervals. This means two severe weather events can be monitored simultaneously. It is an enhancement provided by Harris to ensure our customers have the flexibility to address more than just the baseline scenarios. ABI's interleaved image collection approach can be easily seen in the "time-time iii " diagram for the Scan Mode 3 Timeline provided in Figure This diagram takes the second timeline, breaks it into second intervals and stacks them from top to bottom in sequential order.

It is "read" chronologically just like reading a paragraph — left to right from the top to the bottom. In time intervals where no Full Disk swaths are collected, explicit space look observations are performed.

1. Introduction

SUVI is a sun-pointed instrument, a normal-incidence multilayer-coated telescope, with the overall objective to provide information on solar activity and the effects of the sun on the Earth and the near-earth space environment. SUVI will monitor the entire dynamic range of solar X-ray features including coronal holes and solar flares and will provide data regarding the rapidly changing conditions is the Sun's atmosphere. These data are used for geomagnetic storm forecasts and for observations of solar energetic particle events related to flares.

Photo of the SUVI instrument assembly image credit: The team is on plan for instrument delivery in Oct. EUV radiation plays a key role in heating the thermosphere and creating the ionosphere. NOAA requires the realtime monitoring of the solar irradiance variability that controls the variability of the terrestrial upper atmosphere ionosphere and thermosphere.

This information is critical to understanding the outer layers of the Earth's atmosphere. Transmission grating spectrographs covering five broad bandpasses. Three reflection grating spectrographs measuring specific solar emission lines from which fullspectrum is reconstructed with a model. Ionization chamber instruments with limited dynamic range solar min unresolved in noise and bright flares clipped. Solid state detectors that capture full dynamic range of solar variability. Illustration of the EXIS instrument image credit: XRS monitors solar flares and helps predict solar proton events that can penetrate Earth's magnetic field.

The XRS is important in monitoring X-ray input into the Earth's upper atmosphere and alerts scientists to X-ray flares that are strong enough to cause radio blackouts and aide in space weather predictions this is different from the SUVI instrument which monitors solar flares via images on the X-ray spectrum. EXIS will provide more information on solar flares and include a more complete and detailed report of solar variability than is currently available. The EUVS will measure changes in the solar extreme ultraviolet irradiance which drive upper atmospheric variability on all time scales.

EUV radiation has major impacts on the ionosphere. An excess can result in radio blackouts of terrestrial high frequency communications at low latitudes. EUV flares also deposit large amounts of energy in Earth's upper atmosphere thermosphere causing it to expand into Low Earth Orbiting satellites, causing increased atmospheric drag and reduce the lifetime of satellites by degrading items such as solar panels.

The prime objective is to measure from GEO the total lightning activity on a continuous basis under both day and nighttime conditions over the Americas North and South and portions of the adjoining oceans. The GLM will provide continuous measurements of lightning and ice-phase precipitation. These measurements will be used to:. GLM permits the study of the electrosphere over dimensions ranging from the Earth's radius down to individual thunderstorms.

The instrument is capable of detecting all types of lightning phenomena at a nearly uniform coverage detection of storm formulation and severity. Near real-time data transmission to MSFC is required for processing and quality assurance and redistribution of the data within 1 minute of reception. The GLM instrument consists of a staring imager optimized to detect and locate lightning. The major subsystems of the instrument are: A broadband blocking filter is placed on the front surface of the filter substrate to maximize the effectiveness of the narrowband filter. GLM is a camera system that can be described in the usual terms of imaging systems resolution, spectral response, distortion, noise, clock rates, bit depth, etc.

To understand how GLM detects lightning, it helps to think of it as an event detector, and set aside for a moment our usual thoughts about cameras. Photo of the GLM engineering unit image credit: The daytime lightning signals tend to be buried in the background noise; hence, special techniques are implemented to maximize the lightning signal relative to this background noise. This results in an optimal sampling of the lightning scene relative to the background illumination. This method further maximizes the lightning signal relative to the reflected daylight background.

In an integrating sensor, such as GLM, the integration time specifies how long a particular pixel accumulates charge between readouts. The lightning SNR improves as the integration period approaches the pulse duration. An integration time of 2 ms technological limit is used to minimize pulse splitting and maximize lightning detectability. Each real-time event processor generates an estimate of the background scene imaged at each pixel of its section of the focal plane array. This background scene is updated during each frame readout sequence and, at the same time, the background signal is compared with the off-the-focal-plane signal on a pixel-by-pixel basis.

When the difference between these signals exceeds a selected threshold, the signal is identified as a lightning event and an event processing sequence is initiated. Principle of event detection: As a digital image processing system, GLM is designed to detect any positive change in the image that exceeds a selected detection threshold. This detection process is performed on a pixel-by-pixel basis in the RTEP Real Time Event Processor by comparing each successive value of the pixel sampled at Hz in the incoming digital video stream to a stored background value that represents the recent history of that pixel.

The background value is computed by an exponential moving average with an adjustable time constant k Ref. Each RTEP detects weak lightning flashes from the intense but slowly evolving background. The RTEP continuously averages the output from the focal plane over a number frames on a pixel-by-pixel basis to generate a background estimate. It then subtracts the average background estimate of each pixel from the current signal of the corresponding pixel. The subtracted signal consists of shot noise fluctuating about zero with occasional peaks due to lightning events.

When a peak exceeds the level of a variable threshold, it triggers comparator circuits and is processed by the rest of the electronics as a lightning event. An event is a bit data structure describing the identity of the pixel, the camera frame i. Operating at the Limits of Noise: The intensity of lightning pulses, like many phenomena in nature, approximately follows a power law. There are relatively fewer bright and easily detectable events, and a "long tail" of dim events that eventually get drowned out by instrument noise.

To achieve high detection efficiency, GLM must reach as far into this long tail as possible by operating with the lowest-possible detection threshold. The challenge of lightning event detection is then to lower the detection threshold so low that it starts flirting with instrument noise, where random excursions in the value of a pixel can trigger a so-called "false" event that does not correspond to an optical pulse. The GLM instrument, as built, is the result of years of trade-off studies and prototype testing that refined the present design. The architecture of GLM was driven by a number of important considerations, each of them with the common goal of maximizing lightning detection efficiency.

The following list summarizes these considerations. When following the development of severe thunderstorms it is important to track the lightning flash rate of individual storm cells, and therefore constant ground sample distance over the Earth is necessary. A deliberate choice was made to separate imaging from event detection, by functionally partitioning the instrument into a Sensor Unit that performs digital video imaging and an Electronics Unit that performs digital signal processing.

This partitioning approach, while it does cost mass and power, allows digital event detection algorithms and parameters to be more flexibly developed and optimized to operate reliably at the limits of instrument noise. In the RTEP, it is critically important to be able to select the threshold on a pixel-by-pixel basis. The following simulated example provides further insight into the need for controlling TNR Threshold-to-Noise Ratio in each pixel. Figure 46 shows a typical cloud scene near the terminator, simulated as GLM would see it, where grazing illumination creates a lot of contrast in the cloud tops.

Small portion of cloud scene, as viewed by GLM image credit: Because shot noise is of roughly the same order as electronics noise, pixels containing sunlit cloud tops will have more total noise than adjacent pixels containing shaded cloud tops. Threshold-to-noise ratio achieved by selecting a single detection threshold of 25 image credit: As a result, the false event rate is dominated by the brightly sunlit pixels, and detection efficiency suffers in pixels with shaded cloud tops yellow, orange and red.

The event detection threshold is selected by the RTEP for each individual pixel from a element lookup table indexed by the top five bits of the background in that pixel. Instead of applying a global threshold of 25, a different threshold value is selected for each pixel as shown in Figure Detection thresholds selected on a pixel-by-pixel basis image credit: Note how a higher threshold is applied to brightly sunlit pixels, and a threshold less than 25 is applied to shaded pixels, enhancing detection efficiency in all the pixels shaded blue.

In this example the false event rate is evenly distributed across this scene, as revealed by the uniformity of the corresponding TNR map, obtained simply by dividing the threshold by the total noise Figure Threshold-to-noise ratio when detection threshold is selected on a pixel-by-pixel basis image credit: By controlling TNR on a pixel-by-pixel basis and preventing a few bright pixels from dominating the false event budget, GLM can maximize detection efficiency by lowering the threshold in each pixel to its optimal value, peering deeper into the noise and detecting the dimmest optical pulses in the long tail of the lightning intensity distribution.

Threshold tables can be uploaded to the instrument and will be optimized during post-launch test. Of course, detection thresholds are only one aspect of a robust RTEP design, and a number of other adjustable parameters are available to fine-tune the behavior of the background tracking. For example, RTEP settings can be adjusted to accommodate repeated events in the same pixel to detect the continuing current events that often spark forest fires , to reduce spurious jitter events at contrast boundaries induced by minute disturbances in the instrument line of sight, or to mitigate the impact of stray light when entering and exiting eclipse.

The true test of a lightning mapper is its ability to detect dim lightning events emanating from a bright, zenith-illuminated cloud top. Clouds are nearly Lambertian reflectors with an albedo that sometimes approaches unity, so a large amount of undesired reflected sun light is present in the vicinity of the oxygen triplet. The worst-case spectral radiance of the cloud background is estimated in Figure 51 , for all seasonal and diurnal illumination conditions.

This background cloud radiance creates shot noise which can drown out dimmer lightning events. It is necessary to cut down the background signal using optical filters that have the narrowest feasible bandpass while still passing the majority of the lightning oxygen triplet.

GLM contains three filters of increasingly narrow spectral width: Due to their large size and stringent spectral requirements, these filters pushed the boundaries of manufacturing capabilities. GLM detects the individual optical pulses caused by lightning, on top of a bright background of sunlit clouds. In order to detect these pulses with good signal to noise, the frame rate must be optimized. The average duration of a lightning optical pulse is shown in Figure The frame rate should be closely matched to the average duration of the pulse.

If the frame rate is too low, then additional background is detected with no additional signal, lowering signal to noise. If the frame rate is too high, then the signal is split into adjacent frames, reducing signal to noise. The GLM frame rate is Hz, well matched to the duration of the lightning optical pulses. The frame rate and the CCD well depth must also be matched.

Lightning most often occurs in optically thick clouds, in the afternoon when the clouds are well illuminated by the Sun. The CCD well depth must be large enough to accommodate the expected background from bright clouds, at the frame rate matched to the pulse duration, and with the optical filters matched to the oxygen triplet emission line. The GLM CCD has a well depth of approximately 2 million electrons to be able to accommodate the bright background while leaving room to detect lightning events.

The frame rate, CCD well depth, and optical filters work together to optimize the signal to noise ratio for detecting lightning optical pulses. Typical lightning optical pulse profile image credit: The GLM hardware is designed to detect events, including many events caused by noise, and sends all these events to the ground for further processing. The first step in the processing is to remove the non-lightning events from the data stream.

The flashes are then identified by reviewing the remaining events.

GOES-R - eoPortal Directory - Satellite Missions

The ground processing algorithms include many filters designed to remove events not caused by lightning, including radiation hits and glint from Sun on the ocean. The most important filter is the coherency filter. This filter relies on the fact that true lightning events are coherent in time and space, whereas noise events are not. This is the filter that enables GLM to operate at the edge of the noise, sending many noise events to the ground and detecting fainter lightning events in the process.

As viewed from space, any given lightning flash will generate several to several tens of optical pulses. Flashes can be up to several seconds long, and contain multiple optical pulses detected in the same pixel or adjacent pixels. A noise event will not have this coherent behavior. Although many noise events may be triggered over the course of several seconds, they are unlikely to be in the same or adjacent pixels. The coherency filter calculates the probability that any given event is a noise event, based on the event intensity, the electronics noise, and the photon noise of the background.

When another event occurs in this same pixel or an adjacent pixel, the filter calculates the probability that both of these events are noise events, based on the new event intensity, the instrument and photon noise, and the time elapsed between the two events. When two events have a sufficiently low probability of both being noise, the events are reported as lightning events. This probability threshold is adjustable to allow more or less stringent filtering of the data as desired by the user community.

The overall performance of GLM is measured in terms of the fraction of the lightning flashes that are detected and reported. We call this the detection efficiency. In order to do this calculation, one must know the characteristics of lightning flashes. For our truth data set,high-altitude airplane data is used which provides the distribution function of the energy density of the brightest pulse in a flash. The event detection thresholds of GLM is compared, converted into the energy density units using the instrument calibration data, to the distribution function of the brightest pulse in a flash.

The threshold applied to a given pixel depends on the background in that pixel. The project can then determine which threshold will be selected for each pixel, and determine the detection efficiency of each pixel. Figure 53 shows an example of a predicted detection efficiency map. The vertical banding visible in the areas east of the terminator dark red corresponds to a different detection threshold being selected, resulting in a step change in the detection efficiency. Areas on the sunlit limb light blue have the lowest detection efficiency under these illumination conditions.

In conclusion, GLM will gather more spaceborne lightning data in the first few weeks of operations,than has been collected in the entire history of space flight. GLM has the potential to reduce fuel consumption of the air transport network by providing near real-time lightning maps, augmenting traditional radar detection to optimize air traffic management around areas of convective weather. Most importantly, GLM lightning data will be used in operational data products to forecast tornado activity with significantly greater warning time and reliability. Increased warning time and fewer false tornado warnings will save lives.

Monitoring of geomagnetically trapped electrons and protons; electrons, protons, and heavy ions of direct solar origin; and galactic background particles. This includes particles trapped within Earth's magnetosphere and particles arriving directly from the sun and cosmic rays which have been accelerated by electromagnetic fields in space. The information will be used to help scientists protect astronauts and high altitude aircraft from high levels of harmful ionizing radiation. MPS is a three-axis vector magnetometer to measure the magnitude and direction of the Earth's ambient magnetic field in three orthogonal directions in an Earth referenced coordinate system.

The magnetometer will provide a map of the space environment that controls charged particle dynamics in the outer region of the magnetosphere. The sensor measures electron and proton flux over an energy range of 30ev to 30kev. Spacecraft charging can cause ESD and arcing between two differently charged parts of the spacecraft. This discharge arc can cause serious and permanent damage to the hardware on board a spacecraft, which affects operation, navigation and interferes with measurements being taken.

The sensor will monitor medium and high energy protons and electrons which can shorten the life of a satellite. High energy electrons are extremely damaging to spacecraft because they can penetrate and pass through objects which can cause dielectric breakdowns and result in discharge damage inside of equipment. The objective of SGPS is to measure the solar and galactic protons found in the Earth's magnetosphere. These particular measurements are crucial to the health of astronauts on space missions, though passengers on certain airline routes may experience increased radiation exposure as well.

In addition, these protons can cause blackouts of radio communication near the Earth's poles and can disrupt commercial air transportation flying polar routes. The warning system allows airlines to reroute planes that would normally fly over Earth's poles.

The MAG will provide measurements of the space environment magnetic field that controls charged particle dynamics in the outer region of the magnetosphere. These particles can be dangerous to spacecraft and human spaceflight. The geomagnetic field measurements are important for providing alerts and warnings to many customers, including satellite operators and power utilities.

GOES Magnetometer data are also important in research, being among the most widely used spacecraft data by the national and international research community. The GOES-R Magnetometer products will be an integral part of the NOAA space weather operations, providing information on the general level of geomagnetic activity and permitting detection of sudden magnetic storms. In addition, measurements will be used to validate large-scale space environment models that are used in operations.

The MAG requirements are similar to the tri-axial fluxgates that have previously flown. GOES-R requires measurements of three components of the geomagnetic field with a resolution of 0. Illustration of the boom-mounted MAG device image credit: For the first time in GOES history, the GOES-R series will also be delivered with an integrated GS Ground System that provides a cohesive capability to provide data processing, control, and monitoring capabilities in an integrated system.

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The system also contains blade servers with 3, cores for product processing and distribution across all environments, delivering approximately 40 trillion floating point operations per second of processing power. The GS is comprised of a core development effort made up of mission management, product generation, product distribution, and enterprise management elements and supported by hardware and software infrastructure.

Mission management will provide the primary data receipt and command and control as well as mission planning, scheduling, and monitoring functionality in order to support the satellite operations processes of the GOES-R series. The product generation element will process raw instrument data into higher order products, including the creation of a direct broadcast data stream to be distributed hemispherically to the GOES user community.

Product distribution will provide data dissemination capabilities to ensure GOES-R products reach the user community, including dedicated pathways to the NWS National Weather Service for low-latency, high-availability imagery. The enterprise management element provides an integrated monitoring and reporting capability that will enable a comprehensive view of system status, while Infrastructure provides a pooled set of hardware and software resources to be used by the elements.

The RBU station will have visibility to all operational and on-orbit spare satellites. Telemetry includes both spacecraft health and safety information engineering telemetry and raw instrument data. Engineering telemetry is monitored by the system to support anomaly detection and resolution. Engineering telemetry is made available to operators at NSOF via terrestrial distribution. Mission management provides the primary mission operations as well, including real-time console operations, offline engineering and trending, bus and instrument health and safety and performance monitoring, anomaly detection and resolution, procedure development, spacecraft resource accounting, and special operations planning and execution.

One key function associated with mission management operations is mission planning and scheduling. The GS will provide maneuver planning and scheduling for routine operations as well as special operations such as station keeping, annual yaw flips, and engineering or science investigations outside of normal operations. Mission management also includes a detailed product monitoring function.


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Product monitoring enables the operations team to identify anomalies in the instrument data being generated by the GS. It also provides for the monitoring of the signal quality of the uplinked and downlinked communications signals to ensure integrity of the received data. Notional view of of a One of the existing 18 m antennas will be replaced, and two additional antennas will be added. They will be designed to operate through a Category 2 hurricane without performance degradation. These stations will be functionally identical to the WCDAS antennas and will also be capable of operating under more stressing conditions of ice and snow.

At NSOF, the existing 9. Because the NSOF antennas are currently in use supporting GOES operations, they will be taken offline one at a time to be upgraded, tested, and re-installed. Antenna system architecture components at each facility image credit: It is responsible for the following functional areas Ref. Space-ground communications functions are necessary to process the radio-frequency RF signals received from the satellite into usable information, and to generate the RF signals transmitted from the GS back to the satellite.

The antenna system being developed for GOES-R falls under the mission management element and serves as the front-end for transmission and receipt of the RF signals. An intermediate frequency IF interface between the antenna system and core GS passes these signals into the space-ground communications hardware, which turns them into information to be sent throughout the system.

Ground segment functions image credit: Those packets containing raw instrument data are recovered and processed to Level 0 L0 data reprocessed, unreconstructed instrument data at full resolution with communications artifacts removed. This L0 data is in turn radiometrically corrected calibrated and geometrically corrected navigated to produce a L1b radiance data set. GRB data is freely available to any users within the coverage area who possess the appropriate equipment to receive the data. Of these, 56 are generated based on data from the ABI.

ABI products focus on atmospheric, ocean, and land data and include subcategories such as clouds, radiation, and precipitation. In addition, the GLM will provide near real-time lightning data End-Products, and the space weather instruments will generate an additional 8 Level 1b End-Products. Each product has a set of performance parameter characteristics that identify the product's resolution, accuracy, refresh rate, latency, and precision.

The capability to deliver these products is divided into three phases known as Releases. The implementations will be validated against a reference data set to ensure that the output of the implemented algorithm correlates with the STAR implementation. Once the End Products are generated, the core GS PD Product Distribution element ensures that data and products are provided to the appropriate entities.

GAS will consist of a seven-day storage repository and a data distribution interface supporting both subscription-based and ad hoc data requests. GAS will also provide an API Application Programming Interface designed to support direct machine-machine distribution of data and products to outside systems. This interface is a high availability, low latency distribution channel that ensures that the NWS receives critical KPP data.

The core GS will provide a product sectorization capability that will be configurable based on the following parameters:. The system will remain operationally configurable to respond to changing NWS needs within the parameters defined above. This data repository serves as the primary storage for long-term climatological studies, as well as serving as the data source for users requiring data older than the previous seven days.

Figure 64 depicts the complete flow of data from the satellite's instruments through the products' distribution to the user community. The EM element of the core GS supports operational functions by supervising the overall systems and networks of the core GS. In the GOES-R context, supervision is the ability to monitor, report, and enable an operator response to anomalous conditions. While direct control of various systems may be implemented within the individual elements, EM provides a higher layer of supervision across the GS. GS operators at all sites will have access to the EM functionality for insight to their local site and to the distributed GS components, infrastructure, and interfaces.

The EM status is generally reported through an event message generated by a core GS component. Event messages provide a standardized means of communicating particular status information or alerts to EM from the other core GS components. As the EM functionality receives status and other information provided by the distributed GS functions, operators would be able to monitor, trend, and perform other supervisory activities. In addition to status and monitoring, EM provides configuration and asset management functionality for the GS.

The anomaly reporting and tracking components of CMART generates anomaly trouble tickets and supports the prioritization, tracking, and resolution of anomalies throughout the development and operations life cycle. Although not explicitly defined in the Government requirements, an Infrastructure element is being implemented within the core GS. Infrastructure provides a set of common services for the core GS that are utilized by multiple elements. These services include a network fabric, consolidated storage, database services, and an enterprise service bus. The network fabric is an IP Internet-Protocol -based network that provides intra-element and inter-element connectivity.

It also provides connectivity across GS sites, connects to external interfaces, and supports a defense-in-depth IT Information Technology security strategy. Consolidated storage provides a set of storage media and file structures that enable both short-term and long-term storage within the GS. The database services enable element-level databases through the use of relational database clusters. Finally, the enterprise service bus supports a common set of message exchanges for both intra-and inter-element communication. Consolidation of infrastructure functions under a common element enables more efficient hardware utilization, supports a standard design and implementation of common GS-wide functions, increases system flexibility, and helps centralize the management of the common functions of the system.

GAMCATS provides monitoring, control, and test functionality for the antenna control unit, receive elements, transmit elements, control ports of the switching system, RF switching, BITE Built-In Test Equipment , environmental and fire suppression system monitoring, waveguide dehydrator, and other related equipment across all sites.

The new satellite delivered experimental imagery with detail and clarity never achieved before. Its high resolution — four times higher than previous NOAA satellites — and views of Earth taken every 30 seconds allowed forecasters to monitor how and when storms developed. Data from GOES allowed forecasters to better assess and predict how much rain Hurricane Harvey would produce over Texas and see its rapid intensification, along with hurricanes Irma, Jose, and Maria.

Imagery from GOES helped forecasters spot new wildfires in California, Kansas, Oklahoma, and Texas, and determine which fires were hottest and where the fires were spreading. This critical information was shared with and used by firefighters and emergency managers. Forecasters are now able to predict with greater accuracy than before when fog and clouds will form and clear. The new satellite can also detect turbulence, enabling forecasters to issue timely advisories, aiding in aircraft and passenger safety.

Now that it is operational and the data is incorporated into the forecast process, we will be able to use it across all our service areas, starting with winter storms. Currently, GOES resides in a central checkout orbit of The magnetometers will be the only instruments that will continue to operate throughout the drift period. Even during the current extended test and check-out period, there are already a number of exciting examples of how GOES data were recently used during recent disastrous weather phenomena to track and observe hurricanes and their aftermath during the Atlantic Basin hurricane season Ref.

On previous GOES missions these high-resolution images were not routine, but with GOES's advanced capabilities, these images are now operational image credit: In western Washington State, fog forms frequently in the summer and fall. Skies are often clearer than in other seasons, allowing surface heat to escape and air to cool, which leads to fog.

But fog can happen any time of year if conditions are right. For phenomena that evolve quickly—like storms, or in this case, fog—this so-called geostationary orbit gives a timely view. Within two hours, the fog was about halfway into the strait; two hours later, the fog encountered the sharp landmass of Whidbey Island, which imparted a wave structure to the clouds.

The images are based on preliminary, non-operational data from GOES In addition to observing weather on Earth, GOES carries instruments for monitoring solar activity and space weather image credit: Story by Kathryn Hansen. Secretary of Commerce Wilbur Ross. It will improve forecasters' situational awareness and lead to more accurate, timely, and reliable watches and warnings.

The higher resolution will allow forecasters to see more details in storm systems, especially during periods of rapid strengthening or weakening. Also, GOES carries the first lightning detector flown in geostationary orbit. Total lightning data in-cloud and cloud-to-ground from the lightning mapper will provide critical information to forecasters, allowing them to focus on developing severe storms much earlier.

Positioning satellites in the East and West locations, along with an on-orbit spare, ensures that forecasters get a thorough look at developing weather systems that affect the U. During this three-month event, an assemblage of high-altitude planes, ground-based sensors, drones, and satellites will be used to fine-tune GOES's suite of brand new instruments.

From arid desserts and areas of dense vegetation, to open oceans and storms exhibiting lightning activity, these measurements will cover nearly everything NOAA's GOES satellites see from their orbit 35, km above the Earth. The data sets will be analyzed and compared to the data collected by the planes, drones, and sensors to validate and calibrate the instruments on the satellite.


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  • The mapper continually looks for lightning flashes in the Western Hemisphere, so forecasters know when a storm is forming, intensifying and becoming more dangerous. Rapid increases of lightning are a signal that a storm is strengthening quickly and could produce severe weather. When combined with radar and other satellite data, GLM data may help forecasters anticipate severe weather and issue flood and flash flood warnings sooner. In dry areas, especially in the western United States, information from the instrument will help forecasters, and ultimately firefighters, identify areas prone to wildfires sparked by lightning.

    This means more precious time for forecasters to alert those involved in outdoor activities of the developing threat. Brighter colors indicate more lightning energy was recorded; the color bar units are the calculated kW-hours of total optical emissions from lightning. The brightest storm system is located over the Gulf Coast of Texas image credit: The sun's year activity cycle is currently approaching solar minimum and during this time powerful solar flares become scarce and coronal holes become the primary space weather threat.

    Once operational, SUVI will capture full-disk solar images around-the-clock and will be able to see more of the environment around the sun than earlier NOAA geostationary satellites. This plasma interacts with the sun's powerful magnetic field, generating bright loops of material that can be heated to millions of degrees.

    Outside hot coronal loops, there are cool, dark regions called filaments which can erupt and become a key source of space weather when the sun is active. Other dark regions are called coronal holes, which occur where the sun's magnetic field allows plasma to stream away from the sun at high speed, resulting in cooler areas. The effects linked to coronal holes are generally milder than those of coronal mass ejections, but when the outflow of solar particles in intense, they can still pose risks to Earth.

    Various elements emit light at specific EUV and X-ray wavelengths depending on their temperature, so by observing in several different wavelengths, a picture of the complete temperature structure of the corona can be made. SUVI is essential to understanding active areas on the sun, solar flares and eruptions that may lead to coronal mass ejections which may impact Earth. Depending on the magnitude of a particular eruption, a geomagnetic storm can result that is powerful enough to disturb Earth's magnetic field.

    Such an event may impact power grids by tripping circuit breakers, disrupt communication and satellite data collection by causing short-wave radio interference and damage orbiting satellites and their electronics. These six images show the sun in each of SUVI's six wavelength, each of which is used to see a different aspect of solar phenomena, such as coronal holes, flares, coronal mass ejections, and so on image credit: A plot from SEISS data showed how fluxes of charged particles increased over a few minutes around the satellite on January 19, These particles are often associated with brilliant displays of aurora borealis at northern latitudes and borealis australis at southern latitudes; however, they can pose a radiation hazard to astronauts and other satellites, and threaten radio communications.

    The SEISS sensors have been collecting data continuously since January 8, , with an amplitude, energy and time resolution that is greater than earlier generations of NOAA's geostationary satellites. Solar flares are huge eruptions of energy on the sun and often produce clouds of plasma traveling more than a million miles an hour. When these clouds reach Earth they can cause radio communications blackouts, disruptions to electric power grids, errors in GPS navigation, and hazards to satellites and astronauts.

    The higher resolution EXIS instrument will provide new capabilities, including the ability to capture larger solar flares. An example of EXIS observations at two different wavelengths of a flare that peaked at This was a relatively small flare, yet the brightness of the sun in soft lower energy X-rays increased by a factor of EXIS will give NOAA and space weather forecasters the first indication that a flare is occurring on the sun, as well as the strength of the flare, how long it lasts, the location of the flare on the sun, and the potential for impacts here at Earth.

    The ABI covers the Earth five-times faster than the current generation GOES imagers and has four times greater spatial resolution, allowing meteorologists to see smaller features of the Earth's atmosphere and weather systems. We look forward to exploiting these new images, along with our partners in the meteorology community, to make the most of this fantastic new satellite.

    The image shows North and South America and the surrounding oceans image credit: This panel image shows the continental United States in the two visible, four near-infrared and 10 infrared channels on ABI, acquired on Jan. These channels help forecasters distinguish between differences in the atmosphere like clouds, water vapor, smoke, ice and volcanic ash image credit: MAG observations of Earth's geomagnetic field strength are an important part of NOAA's space weather mission, with the data used in space weather forecasting, model validation, and for developing new space weather models.

    Outboard MAG uncalibrated data from December 22, image credit: The satellite's instruments will continue to progress through their planned testing and calibration phases over the next several weeks Ref. This has placed the satellite approximately 35, km away with an inclination of 0. In the days that follow, the software will be transitioned from the 'orbit raising' mission phase to 'operational,' several maneuvers will be conducted to adjust the satellites precise orbit, and the magnetometer boom will be deployed.

    Testing and calibration of GOES will then begin. Since launch on Nov. The spacecraft is currently positioned in a sun-point attitude, which allows its solar array to harness the sun's power Ref. The next major milestone will be the second stage deployment of GOES-R's solar array, which is currently scheduled to occur on November 30, NASA collaboration roles go further than providing engineering and acquisition services for GOES; the agency also provides scientific support by welcoming NOAA's scientists to participate in its Earth science research mission teams.

    The collaboration is not limited to GOES, but includes NOAA's polar-orbiting operational satellites, where there is considerable overlap of mission activities. International collaboration is a high priority for NOAA to ensure that investments in satellite observations are interoperable and made available to the public, globally. The two agencies' new-generation satellites carry similar advanced imagers [i. Another example is the NOAA and the European Organisation for the Exploitation of Meteorological Satellites EUMETSAT 's Long-Term Cooperation Agreement, signed in , which builds on a year partnership in geostationary, polar-orbiting, and ocean altimetry satellites that has resulted in cost-saving benefits and increased the robustness of both agencies' observing systems.

    To learn more, visit https: The GOES Geostationary Operational Environmental Satellite family of satellites has a history of supporting meteorological and climate observations dating back to In addition, the satellite will contain a similar, but more powerful, suite of solar ultraviolet imaging and space weather monitoring equipment in comparison to previous GOES satellites. On the GOES-R "family tree" of instruments, there are three general classifications for the instrument payloads:. ABI is the next-generation 3rd multispectral imager, a 2-axis scanning radiometric imager, intended to begin a new era in US environmental remote sensing with greatly improved capabilities and features more spectral bands, faster imaging cycles, and higher spatial resolution than the current imager generation of GOES-N to -P.

    The ABI instrument is a significant advancement over current imager generation. The overall objectives of ABI are to provide high-resolution imagery and radiometric information of the Earth's surface, the atmosphere and the cloud cover measurement of the emitted and solar reflected radiance simultaneously in all spectral channels. Data availability, radiometric quality, simultaneous data collection, coverage rates, scan flexibility, and minimizing data loss due to the sun, are prime requirements of the ABI system.

    The instrument is providing 16 bands of multispectral data, with two bands in VIS 0. The instrument features three "imaging sectors" with a simultaneous observation capability, referred to as: ABI has two imaging modes, namely Mode 3 and Mode 4. Mode 4 can provide 30 Mesoscale images every 15 minutes as well as a Full Disk every 5 minutes. The intent is to allow for better identification and tracking of cloud and moisture signatures.

    The band selection has been optimized to meet all cloud, moisture, and surface observation requirements. The phenomena observed and the various applications are:. Daytime cloud imaging, snow and ice cover, severe weather onset detection, low-level cloud drift winds, fog, smoke, volcanic ash, flash flood analysis, hurricane analysis, winter storm analysis. Middle-tropospheric water vapor tracking, jet stream identification, hurricane track forecasting, mid-latitude storm forecasting, severe weather analysis.

    Continuous cloud monitoring for numerous applications, low-level moisture, volcanic ash trajectories, cloud particle size in mid-band products. Cloud top height assignments for cloud-drift winds, cloud products for ASOS supplement, tropopause delineation, cloud opacity. This band is used for aerosol detection and visibility estimation.

    It does not see into the lower troposphere due to water vapor sensitivity, thus it provides excellent daytime sensitivity to very thin cirrus. This includes a more accurate delineation of ice from water clouds during day or night. The band permits the determination of microphysical properties of clouds with the This includes a more accurate determination of cloud particle size during the day or night.

    Under terms of the contracts, each company developed detailed engineering plans for the future instrument. In , the ITT Corporation split into three companies: Key performance parameter comparison of 2nd and 3rd generation imagers Ref. Ground storage On-orbit storage Mean mission life Design life. Requirements overview for the ABI instrument. Total water for stability, cloud phase, dust, SO 2 , rainfall. Overview of the spectral band allocation for the ABI instrument.

    Schematic view of the ABI instrument image credit: Approximate number of ABI pixels for various support modes Ref. The two-stage cold head was designed to provide large cooling power at 53 K and K, simultaneously. NGAS evolved the design from on-orbit pulse tube cooler designs that the company has built and launched over the past decade. No failures have been experienced on any of these coolers on the seven satellite systems launched to date; some of these coolers are now approaching 11 years of failure-free operation. The PFM Proto-Flight Module cooler system for ABI consists of a linear pulse tube cold head that is integral to the compressor assembly and a coaxial remote pulse tube cold head; the two cold head design affords a means of cooling a detector array to its operational temperature while remotely cooling optical elements to reduce effects of radiation on imager performance and a second detector array.

    The TDU has a size of mm x mm x mm width x depth x height with a mass of 5. The size of CCE is mm x mm x 85 mm width x depth x height with a mass of 3. The requirements on the cooler call for: Since ABI uses multiple focal plane modules for the channels of detector grids, the channel-to-channel registration can present a challenge if relative motion occurs from one focal plane module to another.

    This is especially the case given the ABI channel-to-channel registration requirements are at sub-pixel levels. Once the image data are processed on ground, a series of manual landmarking registration techniques are applied to the image to improve the location of features in the image relative to known landmarks within the scene. The landmarking updates are also used to update the IMC coefficients for the following day's operation.

    ABI INR relies on a ground-based real time image navigation process to achieve increased knowledge accuracy using precise encoder readings and star image data. During an Earth scene collection, the instrument uses attitude information provided by the spacecraft to compensate for the spacecraft's attitude motion; however the precise image navigation and registration is achieved through ground processing to determine where the image data were actually collected relative to the fixed grid scene. ABI collects scene image data as well as star measurements to maintain line of sight knowledge.

    Image navigation uses ground processing algorithms to decompress, calibrate and navigate the image samples from the focal plane module detectors. Image collection performance for the ABI is governed by the attitude knowledge provided by the spacecraft, the control accuracy of the pointing servo control for the instrument and the diurnal line of sight variation. Image navigation and registration uses data and measurements defined in a number of different coordinate frames. The primary reference frame is J which is the inertial frame in which the star catalog coordinates are defined.

    Orbit determination and body axis attitude reporting are done relative to a frame defined by the velocity vector and nadir referred to as to ORF Orbit Reference Frame. The ABI instrument alignment is referenced to a frame relative to the spacecraft body axis frame referred to as the IMF Instrument Mounting Frame and line of sight is referenced to a frame relative to the instrument mounting frame. Frame-to-frame registration error is the difference in navigation error for any given pixel in two consecutive images within the same channel.

    Angular separation of any two pixels in a Frame. Reference frames used in the INR process image credit: ABI image navigation and registration process image credit: ABI's advanced design will provide users with twice the spatial resolution, six times the coverage rate, and more than three times the number of spectral channels compared to the current GOES Imagers. The operations flexibility permits consistent collection of Earth scenes, eliminating time gaps in coverage by the need to prioritize some areas over others. These improvements will allow tomorrow's meteorologists and climatologists to significantly improve the accuracy of their products, both in forecasting and nowcasting.

    Photo of the ABI instrument image credit: However, its most unique feature is its operational flexibility - one instrument seamlessly interleaving the collection of multiple images of different sizes, locations, and repetition intervals plus the ability to collect scan data in any direction. This enables the high temporal resolution imaging of severe weather events hurricanes, typhoons, tornados, etc. ABI's ability to interleave image collections ensures all regions will be imaged far more frequently than with the current imagers. Hence, ABI's image collections can be simplified to just three standard images:.

    The sizes of these images are provided in Table 9 and their locations are provided in Table Note that all images are defined in radians. Degrees and kilometer equivalents are provided for convenience. This information is also provided visually in Figure 39 , Figure 40 , and Figure In Figure 6 some possible locations are shown nadir, tornado in the mid-West, hurricane off the coast of Florida, lunar observation.

    Sizes of the ABI operational images. Locations of the ABI operational images. An ABI scene definition defines the scan patterns needed to collect a desired image. Each scene is a collection of individual swaths. The ABI timeline defines when to collect each swath of each scene. ABI currently has two operational timelines, created by Harris based on our customer's requirements:. All operational ABI timelines include observations for radiometric and geometric calibration. All timelines start with a space look and blackbody observation and collect a space look at least every 30 seconds for radiometric calibration.

    Hence, blackbody observations occur at least every 15 minutes, far more frequently than required to meet the IR calibration accuracy requirements. All operational ABI timelines include visible stars observations on average at least every s and IR stars observations on average at least every s for navigation i. Hence, observations of the solar calibration target are not included in the operational timelines.

    They are collected using a custom timeline, which is run approximately every two weeks at the start of the operational mission and less frequently later in the mission. Custom scenes and timelines can be defined and uploaded at any time during the mission life. This is not currently an operational timeline. However, it is expected to become an operational timeline once the GOES-R ground system parameters are updated to include processing and distribution of Full Disk image products on minute intervals in addition to the current 5 and 15 minute intervals and the users' systems have been updated to receive Full Disk products on minute intervals.

    Images collected by the baseline ABI timelines. In the Scan Mode 3 and 6 timelines, a mesoscale image is collected every 30 seconds. However, ABI provides the user the option to define two different mesoscale image locations Meso 1 and Meso 2 and collect both of them at 1 minute intervals. This means two severe weather events can be monitored simultaneously. It is an enhancement provided by Harris to ensure our customers have the flexibility to address more than just the baseline scenarios.

    ABI's interleaved image collection approach can be easily seen in the "time-time iii " diagram for the Scan Mode 3 Timeline provided in Figure This diagram takes the second timeline, breaks it into second intervals and stacks them from top to bottom in sequential order.

    It is "read" chronologically just like reading a paragraph — left to right from the top to the bottom. In time intervals where no Full Disk swaths are collected, explicit space look observations are performed. SUVI is a sun-pointed instrument, a normal-incidence multilayer-coated telescope, with the overall objective to provide information on solar activity and the effects of the sun on the Earth and the near-earth space environment. SUVI will monitor the entire dynamic range of solar X-ray features including coronal holes and solar flares and will provide data regarding the rapidly changing conditions is the Sun's atmosphere.

    These data are used for geomagnetic storm forecasts and for observations of solar energetic particle events related to flares. Photo of the SUVI instrument assembly image credit: The team is on plan for instrument delivery in Oct. EUV radiation plays a key role in heating the thermosphere and creating the ionosphere. NOAA requires the realtime monitoring of the solar irradiance variability that controls the variability of the terrestrial upper atmosphere ionosphere and thermosphere.

    This information is critical to understanding the outer layers of the Earth's atmosphere. Transmission grating spectrographs covering five broad bandpasses. Three reflection grating spectrographs measuring specific solar emission lines from which fullspectrum is reconstructed with a model. Ionization chamber instruments with limited dynamic range solar min unresolved in noise and bright flares clipped. Solid state detectors that capture full dynamic range of solar variability. Illustration of the EXIS instrument image credit: XRS monitors solar flares and helps predict solar proton events that can penetrate Earth's magnetic field.

    The XRS is important in monitoring X-ray input into the Earth's upper atmosphere and alerts scientists to X-ray flares that are strong enough to cause radio blackouts and aide in space weather predictions this is different from the SUVI instrument which monitors solar flares via images on the X-ray spectrum. EXIS will provide more information on solar flares and include a more complete and detailed report of solar variability than is currently available. The EUVS will measure changes in the solar extreme ultraviolet irradiance which drive upper atmospheric variability on all time scales.

    EUV radiation has major impacts on the ionosphere. An excess can result in radio blackouts of terrestrial high frequency communications at low latitudes. EUV flares also deposit large amounts of energy in Earth's upper atmosphere thermosphere causing it to expand into Low Earth Orbiting satellites, causing increased atmospheric drag and reduce the lifetime of satellites by degrading items such as solar panels. The prime objective is to measure from GEO the total lightning activity on a continuous basis under both day and nighttime conditions over the Americas North and South and portions of the adjoining oceans.

    The GLM will provide continuous measurements of lightning and ice-phase precipitation. These measurements will be used to:. GLM permits the study of the electrosphere over dimensions ranging from the Earth's radius down to individual thunderstorms. The instrument is capable of detecting all types of lightning phenomena at a nearly uniform coverage detection of storm formulation and severity. Near real-time data transmission to MSFC is required for processing and quality assurance and redistribution of the data within 1 minute of reception.

    The GLM instrument consists of a staring imager optimized to detect and locate lightning. The major subsystems of the instrument are: A broadband blocking filter is placed on the front surface of the filter substrate to maximize the effectiveness of the narrowband filter. GLM is a camera system that can be described in the usual terms of imaging systems resolution, spectral response, distortion, noise, clock rates, bit depth, etc. To understand how GLM detects lightning, it helps to think of it as an event detector, and set aside for a moment our usual thoughts about cameras.

    Photo of the GLM engineering unit image credit: The daytime lightning signals tend to be buried in the background noise; hence, special techniques are implemented to maximize the lightning signal relative to this background noise. This results in an optimal sampling of the lightning scene relative to the background illumination. This method further maximizes the lightning signal relative to the reflected daylight background. In an integrating sensor, such as GLM, the integration time specifies how long a particular pixel accumulates charge between readouts.

    The lightning SNR improves as the integration period approaches the pulse duration. An integration time of 2 ms technological limit is used to minimize pulse splitting and maximize lightning detectability. Each real-time event processor generates an estimate of the background scene imaged at each pixel of its section of the focal plane array. This background scene is updated during each frame readout sequence and, at the same time, the background signal is compared with the off-the-focal-plane signal on a pixel-by-pixel basis.

    When the difference between these signals exceeds a selected threshold, the signal is identified as a lightning event and an event processing sequence is initiated. Principle of event detection: As a digital image processing system, GLM is designed to detect any positive change in the image that exceeds a selected detection threshold. This detection process is performed on a pixel-by-pixel basis in the RTEP Real Time Event Processor by comparing each successive value of the pixel sampled at Hz in the incoming digital video stream to a stored background value that represents the recent history of that pixel.

    The background value is computed by an exponential moving average with an adjustable time constant k Ref. Each RTEP detects weak lightning flashes from the intense but slowly evolving background. The RTEP continuously averages the output from the focal plane over a number frames on a pixel-by-pixel basis to generate a background estimate. It then subtracts the average background estimate of each pixel from the current signal of the corresponding pixel.

    The subtracted signal consists of shot noise fluctuating about zero with occasional peaks due to lightning events. When a peak exceeds the level of a variable threshold, it triggers comparator circuits and is processed by the rest of the electronics as a lightning event. An event is a bit data structure describing the identity of the pixel, the camera frame i. Operating at the Limits of Noise: The intensity of lightning pulses, like many phenomena in nature, approximately follows a power law. There are relatively fewer bright and easily detectable events, and a "long tail" of dim events that eventually get drowned out by instrument noise.

    To achieve high detection efficiency, GLM must reach as far into this long tail as possible by operating with the lowest-possible detection threshold. The challenge of lightning event detection is then to lower the detection threshold so low that it starts flirting with instrument noise, where random excursions in the value of a pixel can trigger a so-called "false" event that does not correspond to an optical pulse. The GLM instrument, as built, is the result of years of trade-off studies and prototype testing that refined the present design. The architecture of GLM was driven by a number of important considerations, each of them with the common goal of maximizing lightning detection efficiency.

    The following list summarizes these considerations. When following the development of severe thunderstorms it is important to track the lightning flash rate of individual storm cells, and therefore constant ground sample distance over the Earth is necessary. A deliberate choice was made to separate imaging from event detection, by functionally partitioning the instrument into a Sensor Unit that performs digital video imaging and an Electronics Unit that performs digital signal processing.

    This partitioning approach, while it does cost mass and power, allows digital event detection algorithms and parameters to be more flexibly developed and optimized to operate reliably at the limits of instrument noise. In the RTEP, it is critically important to be able to select the threshold on a pixel-by-pixel basis. The following simulated example provides further insight into the need for controlling TNR Threshold-to-Noise Ratio in each pixel. Figure 46 shows a typical cloud scene near the terminator, simulated as GLM would see it, where grazing illumination creates a lot of contrast in the cloud tops.

    Small portion of cloud scene, as viewed by GLM image credit: Because shot noise is of roughly the same order as electronics noise, pixels containing sunlit cloud tops will have more total noise than adjacent pixels containing shaded cloud tops. Threshold-to-noise ratio achieved by selecting a single detection threshold of 25 image credit: As a result, the false event rate is dominated by the brightly sunlit pixels, and detection efficiency suffers in pixels with shaded cloud tops yellow, orange and red.

    The event detection threshold is selected by the RTEP for each individual pixel from a element lookup table indexed by the top five bits of the background in that pixel. Instead of applying a global threshold of 25, a different threshold value is selected for each pixel as shown in Figure Detection thresholds selected on a pixel-by-pixel basis image credit: Note how a higher threshold is applied to brightly sunlit pixels, and a threshold less than 25 is applied to shaded pixels, enhancing detection efficiency in all the pixels shaded blue.

    In this example the false event rate is evenly distributed across this scene, as revealed by the uniformity of the corresponding TNR map, obtained simply by dividing the threshold by the total noise Figure Threshold-to-noise ratio when detection threshold is selected on a pixel-by-pixel basis image credit: By controlling TNR on a pixel-by-pixel basis and preventing a few bright pixels from dominating the false event budget, GLM can maximize detection efficiency by lowering the threshold in each pixel to its optimal value, peering deeper into the noise and detecting the dimmest optical pulses in the long tail of the lightning intensity distribution.

    Threshold tables can be uploaded to the instrument and will be optimized during post-launch test. Of course, detection thresholds are only one aspect of a robust RTEP design, and a number of other adjustable parameters are available to fine-tune the behavior of the background tracking.

    For example, RTEP settings can be adjusted to accommodate repeated events in the same pixel to detect the continuing current events that often spark forest fires , to reduce spurious jitter events at contrast boundaries induced by minute disturbances in the instrument line of sight, or to mitigate the impact of stray light when entering and exiting eclipse. The true test of a lightning mapper is its ability to detect dim lightning events emanating from a bright, zenith-illuminated cloud top.

    Clouds are nearly Lambertian reflectors with an albedo that sometimes approaches unity, so a large amount of undesired reflected sun light is present in the vicinity of the oxygen triplet. The worst-case spectral radiance of the cloud background is estimated in Figure 51 , for all seasonal and diurnal illumination conditions. This background cloud radiance creates shot noise which can drown out dimmer lightning events.

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    It is necessary to cut down the background signal using optical filters that have the narrowest feasible bandpass while still passing the majority of the lightning oxygen triplet. GLM contains three filters of increasingly narrow spectral width: Due to their large size and stringent spectral requirements, these filters pushed the boundaries of manufacturing capabilities. GLM detects the individual optical pulses caused by lightning, on top of a bright background of sunlit clouds. In order to detect these pulses with good signal to noise, the frame rate must be optimized.

    The average duration of a lightning optical pulse is shown in Figure The frame rate should be closely matched to the average duration of the pulse. If the frame rate is too low, then additional background is detected with no additional signal, lowering signal to noise. If the frame rate is too high, then the signal is split into adjacent frames, reducing signal to noise. The GLM frame rate is Hz, well matched to the duration of the lightning optical pulses.

    The frame rate and the CCD well depth must also be matched. Lightning most often occurs in optically thick clouds, in the afternoon when the clouds are well illuminated by the Sun. The CCD well depth must be large enough to accommodate the expected background from bright clouds, at the frame rate matched to the pulse duration, and with the optical filters matched to the oxygen triplet emission line.

    The GLM CCD has a well depth of approximately 2 million electrons to be able to accommodate the bright background while leaving room to detect lightning events. The frame rate, CCD well depth, and optical filters work together to optimize the signal to noise ratio for detecting lightning optical pulses. Typical lightning optical pulse profile image credit: The GLM hardware is designed to detect events, including many events caused by noise, and sends all these events to the ground for further processing.

    The first step in the processing is to remove the non-lightning events from the data stream. The flashes are then identified by reviewing the remaining events. The ground processing algorithms include many filters designed to remove events not caused by lightning, including radiation hits and glint from Sun on the ocean. The most important filter is the coherency filter. This filter relies on the fact that true lightning events are coherent in time and space, whereas noise events are not. This is the filter that enables GLM to operate at the edge of the noise, sending many noise events to the ground and detecting fainter lightning events in the process.

    As viewed from space, any given lightning flash will generate several to several tens of optical pulses. Flashes can be up to several seconds long, and contain multiple optical pulses detected in the same pixel or adjacent pixels.

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    A noise event will not have this coherent behavior. Although many noise events may be triggered over the course of several seconds, they are unlikely to be in the same or adjacent pixels. The coherency filter calculates the probability that any given event is a noise event, based on the event intensity, the electronics noise, and the photon noise of the background. When another event occurs in this same pixel or an adjacent pixel, the filter calculates the probability that both of these events are noise events, based on the new event intensity, the instrument and photon noise, and the time elapsed between the two events.

    When two events have a sufficiently low probability of both being noise, the events are reported as lightning events. This probability threshold is adjustable to allow more or less stringent filtering of the data as desired by the user community. The overall performance of GLM is measured in terms of the fraction of the lightning flashes that are detected and reported. We call this the detection efficiency. In order to do this calculation, one must know the characteristics of lightning flashes. For our truth data set,high-altitude airplane data is used which provides the distribution function of the energy density of the brightest pulse in a flash.

    The event detection thresholds of GLM is compared, converted into the energy density units using the instrument calibration data, to the distribution function of the brightest pulse in a flash. The threshold applied to a given pixel depends on the background in that pixel. The project can then determine which threshold will be selected for each pixel, and determine the detection efficiency of each pixel. Figure 53 shows an example of a predicted detection efficiency map.

    The vertical banding visible in the areas east of the terminator dark red corresponds to a different detection threshold being selected, resulting in a step change in the detection efficiency. Areas on the sunlit limb light blue have the lowest detection efficiency under these illumination conditions. In conclusion, GLM will gather more spaceborne lightning data in the first few weeks of operations,than has been collected in the entire history of space flight.

    GLM has the potential to reduce fuel consumption of the air transport network by providing near real-time lightning maps, augmenting traditional radar detection to optimize air traffic management around areas of convective weather. Most importantly, GLM lightning data will be used in operational data products to forecast tornado activity with significantly greater warning time and reliability. Increased warning time and fewer false tornado warnings will save lives. Monitoring of geomagnetically trapped electrons and protons; electrons, protons, and heavy ions of direct solar origin; and galactic background particles.

    This includes particles trapped within Earth's magnetosphere and particles arriving directly from the sun and cosmic rays which have been accelerated by electromagnetic fields in space. The information will be used to help scientists protect astronauts and high altitude aircraft from high levels of harmful ionizing radiation.