GOES-R (Geostationary Operational Environmental Satellite-R) 3rd Generation Series
The next-generation (3rd) geostationary weather satellite family of NOAA, under development at NOAA and at NASA, will start with the GOES-R spacecraft and its newly defined sensor complement. Obviously, such an undertaking, truly of decadal dimension, represents a great challenge for any organization, since it involves the development of new space and ground segments, along with observation instruments, of spacecraft, new operation procedures and data processing algorithms - all on the basis of state-of-the-art technology, demanding user requirements, and available funding resources.
GOES-R is a collaborative development and acquisition effort between NOAA and NASA. The overall GOES Program is managed by NOAA of DOC (Department of Commerce), which establishes requirements, provides funding, and distributes environmental data for the United States. DOC is the approval authority for the GOES-R budget, Ground Segment Project procurement and overall program acquisition strategy. NOAA is accountable to DOC for successful GOES-R development and operational mission success. - NASA/GSFC is teaming with NOAA to manage the design and development of the spacecraft series and its sensor complement. Program activities occur at the co-located Program and Project Offices at Goddard Space Flight Center (GSFC), Greenbelt, MD.
The definition/requirements phase of the next-generation project started in 2000. The first GOES users conference followed in 2001 (May 22-24, 2001, Boulder CO). A major science objective is to provide considerably improved observation capabilities, relative to the GOES-I-M-O-P series, in four key areas: a) spatial resolution, b) spectral coverage and resolution, c) temporal refreshment rates (also detection, change diagnosis, and tracking of hurricanes), and d) radiometric sensitivity. 1) 2) 3) 4) 5) 6) 7) 8) 9) 10) 11)
The 3rd generation GOES spacecraft series will provide critical atmospheric, hydrologic, oceanic, climatic, solar, and space data. Additional capabilities include improved direct services, such as: GBR (GOES-R Re-Broadcast), S&R (Search & Rescue), DCS (Data Collection System), EMWIN (Emergency Managers Weather Information Network), and LRIT (Low Rate Information Transmission) communications.
The goals of the GOES-R mission are:
• Maintain continuous, reliable operational environmental, and storm warning systems to protect life and property
• Monitor the Earth's surface and space environmental and climate conditions
• Introduce improved atmospheric and oceanic observations and data dissemination capabilities (increased spatial, temporal and spectral resolution)
• Develop and provide new and improved applications and products for a wide range of federal agencies, state and local governments, and private users.
The GOES R system is planned to operate for a period of at least 14 years (design life), providing a remote sensing capability to acquire and disseminate regional environmental imagery and specialized meteorological, climatic, terrestrial, oceanographic, solar-geophysical and other data to central processing centers and distributed direct users. GOES R will operate with improved latency, full hemispheric coverage, including the periods of eclipse at the vernal equinoxes.
An overall consolidated architecture (space segment and ground segment) is considered that can evolve with time to meet at least some of the growing performance requirements of the user community in such service fields as data distribution and analysis.
Figure 1: Continuity of the GOES operational satellite program as of June 2014 (image credit: NOAA) 12)
Figure 2: Artist's view of the GOES-R spacecraft in orbit (image credit: NASA, NOAA, LM)
The GOES-R space segment:
The GOES-R space segment consists of a constellation of one or more satellites each nominally located at 75º West longitude (East location) and at 137º West longitude (West location) at geostationary altitude (~35,786 km), 0º inclination. 13)
The GOES-West location in the GOES-R series is to be 137º W instead of current 135º W -this eliminates conflicts with other satellite systems in X-band frequency at 135º W. During the on-orbit storage period, the satellites will be positioned at 105º West longitude and a Launch/Check-out position is reserved at 90º West longitude. 14) 15)
Figure 3: Illustration of the GOES-R series spacecraft locations (image credit: GOES-R Program Office)
Table 1: Mission requirements for GOES-R 3rd generation spacecraft series
In December 2008, NASA, in coordination with NOAA, selected Lockheed Martin Space Systems Company of Denver to build the GOES-R series spacecraft. The contractor will design, develop and deliver the GOES-R series of spacecraft and provide pre-launch, launch and post-launch support. Lockheed will design and develop the spacecraft in its Newtown PA, Sunnyvale CA, and Denver CO facilities. 16) 17) 18)
In May 2009, NOAA and NASA presented a re-evaluation of the previous contract award resulting in a series of corrective actions. The basic contract is for two satellites with options for two additional satellites. 19)
GOES-R solution builds upon a derivative of the renowned A2100 geosynchronous spacecraft bus (a commercial-type bus with considerable space heritage) and proven precision imaging capabilities from previous remote sensing programs. The satellite dry mass (spacecraft and payloads) is estimated to be < 2800 kg; power capability > 4 kW (EOL). 20) 21)
Figure 4: GOES-R spacecraft configuration (image credit: NASA, NOAA, LM)
On Nov. 9, 2012, the GOES-R Program successfully passed the Mission Critical Design Review (MCDR). 22)
C&DH (Command and Data Handling) subsystem: C&DH serves as the hub for all data received by and sent from the spacecraft. The CCSDS (Consultative Committee for Space Data Systems) recommendations for both packet telemetry and telecommand communications are being implemented.
The SpaceWire bus was selected as the best solution for on-board high-speed communications. GOES-R instrument-to-spacecraft data rates are between 10 and 100 Mbit/s. Also, error detection and correction, at the source packet level, is needed. Early in the GOES-R development program, a decision was made to develop a GOES-R specific SpaceWire technology to aid in cost and risk reduction. In response to this direction reference hardware and software solutions have been fully developed and verified to be compliant with the SpaceWire standard and GOES-R Project requirements. A SpaceWire ASIC (Application Specific Integrated Circuit) was developed by BAE (British AeroSpace). 23) 24)
GOES-R project has developed a Reliable Data Delivery Protocol (GRDDP) that is based on SpaceWire capabilities for link connection and re-connection, error detection, virtual channels and routing. This protocol has been presented to and accepted by the SpaceWire Working Group and assigned a Protocol ID (PID) 238. GRDDP, also known as PID 238, does not attempt to duplicate or improve on the considerable capabilities provided by SpaceWire. This protocol builds on top of SpaceWire the ability to recover lost packets, reorder packets, and to ensure to higher level processes that packets are as error free as possible. 25)
The GOES-R requirements for PID 238 are to utilize the SpaceWire capabilities to provide a packet delivery protocol that is able to detect and recover lost packets. The protocol is also required to be flexible so that it can be adapted as needed to different host data throughput requirements and resources. PID 238 intentionally does not specify an implementation. It defines a set of capabilities, but does not require that all capabilities be implemented for all applications.
Of the 5 GOES-R instruments, 2 have implemented PID 238 in FPGAs, and the other three have implemented the protocol in software on the embedded microcontroller in the BAE SpaceWire ASIC. Each of the GOES-R instruments are implementing the SpaceWire and PID 238 interface as a point-to-point architecture. Modeling the proposed spacecraft data system has shown no changes are required in any instrument implementation including the addition of several SpaceWire routers.
The most simple instrument with very small data throughput requirements and minimal processor resources, the largest instrument with the highest data throughput requirements, and the spacecraft C&DH that interfaces to them all have implemented PID 238 to the same specification. All of the instruments as well as the spacecraft recognize a common method for detecting and recovering data link errors and lost packets.
GOES-R instrument data rates ranging from 50kb to 66MHz are easily managed by the combination of PID 238 over SpaceWire. Many parameters of PID 238 can be tuned to match the reliability requirements and a node’s ability to support the required complexity. PID 238 has proven able to adapt to those capabilities and data rates due to its inherent flexibility. PID 238 is documented and extensively tested. It is available and ready to be applied to SpaceWire applications (Ref. 25).
Figure 5: Simplified spacecraft design with multiple SpaceWire routers (image credit: NASA, Ref. 25)
• HRIT (High Rate Information Transmission).
• LRIT (Low Rate Information Transmission). The LRIT service evolves from the current WEFAX system which provides a wide dissemination of GOES imagery and other data at the relatively low information rate of 128 kbit/s. The LRIT has a requirement to upgrade the user information rate to 256 kbit/s.
• EMWIN (Emergency Managers Weather Information Network). A service provided though a transponder onboard the GOES satellite. EMWIN is a suite of data access methods that make available a live stream of weather and other critical information to Local Emergency Managers and the Federal Emergency Management Agency (FEMA).
• GRB (GOES Re-Broadcast) services. GRB provides processed mission data to the user community. Raw data from the environmental sensors is processed into calibrated navigated data sets at the receive site. The processed data is then uplinked to GOES for broadcast to users within view of the satellite.
Figure 6: GOES-R mission interfaces (image credit: NOAA, NASA) 26)
Figure 7: Illustration of the deployed GOES-R spacecraft (image credit: NOAA, NASA) 27)
GOES-R development status (program milestones):
• Oct. 9, 2014: The GLM (Geostationary Lightning Mapper) instrument for GOES-R completed development and testing and is now ready for integration with the spacecraft. 28)
• In September 2014, a team of technicians and engineers at Lockheed Martin has successfully mated together the large system and propulsion modules of the first GOES-R series weather satellite at the company’s Space Systems facilities in Littleton near Denver, Colorado. The system module of the A2100-based satellite houses more than 70 electronics boxes that comprise the three major electrical subsystems; command and data handling, communication, and electrical power. The propulsion core contains the integrated propulsion system and serves as the structural backbone of the satellite. 29) 30)
- With the core spacecraft completed, the team will begin installing the six weather and solar-monitoring instruments onto the satellite. All six GOES-R instruments were delivered to begin spacecraft integration. They are: ABI (Advanced Baseline Imager), EXIS (Extreme X-ray Irradiance Sensors), GLM (Geostationary Lightning Mapper), SEISS (Space Environment In-situ Suite), SUVI (Solar Ultraviolet Imager ), and the Magnetometer. Two instruments, EXIS and SUVI were installed on the sun-pointing platform of the spacecraft. 31)
• July 30, 2014: The GOES-R Series Program SIR (System Integration Review) was successfully held July 22–24, 2014 at Lockheed Martin Space Systems Corporation in Littleton, CO. The SIR determines if the flight and ground segments and components are available and ready to be integrated into the overall system. It also reviews whether the facilities, support personnel and integration plans and procedures are ready for integration. 32)
• May 2014: Propulsion Core Module delivered to Lockheed Martin, Denver. With the delivery of the system module and the propulsion module, the weather satellite will now undergo the important integration and testing phase so that it can be available in late 2015. 33) 34)
In addition to four satellites in the series (R, S, T and U), Lockheed Martin is also designing and building the SUVI (Solar Ultraviolet Imager) and the GLM (Geostationary Lightning Mapper) instruments that will each fly aboard each of the spacecraft. The SUVI was recently installed on the GOES-R satellite’s sun pointing platform.
Figure 8: The Propulsion Module (left) and System Module (right) of the first GOES-R series weather satellite arrived in Lockheed Martin’s cleanroom near Denver where they will now undergo integration and testing (image credit: Lockheed Martin)
• April 2014: The GOES-R spacecraft system module Pre-Shipment Review was held April 11 at Lockheed Martin’s facility in Newtown, PA. The system module was shipped on April 14 and arrived at Denver International Airport via C-17 large military transport aircraft late on April 15. It then safely completed its journey to Lockheed Martin’s Littleton, CO, facility by convoy on April 16.
• May 2012: GOES-R Weather Satellite Passes CDR (Critical Design Review). The week-long review included a series of comprehensive presentations from each of the system and subsystem subject matter experts representing all facets of the spacecraft. The team demonstrated that the design and operations are understood and sufficiently mature to begin the build and integration phase. 35)
Launch: The GOES-R satellite is scheduled for launch in Q2 2016 on an Atlas-5 541 vehicle from the Cape Canaveral Air Force Station, FL. The launch provider is United Launch Services. The GOES-R 3rd generation series (R, S, T, U) and its sensor complement are expected to provide continued observation services for a period of at least 22 years.
Orbit: Geostationary orbit, altitude = 35,786 km, longitude = 75º W.
GOES-R series satellites will have two operational locations: 75º W and 137º W longitude. Any GOES-R series satellite stored on-orbit will be located at 105º W longitude.
Sensor complement (ABI, SUVI, EXIS, GLM, SEISS, MAG)
The GOES (Geostationary Operational Environmental Satellite) family of satellites has a history of supporting meteorological and climate observations dating back to 1974.
Unlike the GOES-I/M and GOES-N/P series, the 3rd generation GOES-R series spacecraft do not contain a “sounder”. Legacy sounding products are derived based on ABI data through the GS (Ground System). - Instead, a GLM (Geostationary Lightning Mapper) will greatly improve storm hazard identification and increase warning lead-time during both day and night, providing continuous monitoring of lightning activity. 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:
- Earth-pointed “business end” of GOES
- Highly stable, precision pointed platform
- Dynamically isolated from the rest of the spacecraft
- Supports operation of the ABI and GLM
- Utilizes a Sun Pointing Platform (SPP) housed on the solar array yoke
- The SPP provides a stable platform that tracks the seasonal and daily movement of the sun relative to the spacecraft
- Supports operation of the SUVI and EXIS
- SEISS and the Magnetometer provide localized measurements of particles and fields in geosynchronous orbit
- Accommodation challenges include: a) a wide variance in Field-of-View (FOV) requirements for the SEISS sensors, and, b) a boom to provide relative magnetic isolation for the Magnetometer.
ABI (Advanced Baseline Imager):
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. 38) 39) 40) 41) 42) 43) 44)
The instrument is providing 16 bands of multispectral data, with two bands in VIS (0.47 µm & 0.64 µm) and 14 bands in IR (0.86 µm to 13.3 µm). The spatial resolution is band-dependent, the IGFOV (Instantaneous Geometric Field of View) ranges from 0.5 km at nadir for broadband visible, 1.0 km for SWIR, and 2.0 km for MWIR and TIR data. The instrument features three “imaging sectors” with a simultaneous observation capability, referred to as: FD (Full Disk), CONUS, and Mesoscale. Full Disk includes the synoptic Earth view from GEO. The CONUS (Contiguous USA) sector covers a target area of 5000 km x 3000 km; the Mesoscale sector covers a nominal region of 1000 km x 1000 km (at nadir projection). 45)
ABI has two imaging modes, namely Mode 3 and Mode 4. Mode 3 imaging can provide 1 FD image, 3 CONUS and 30 Mesoscale images, every 15 minutes. Mode 4 can provide 30 Mesoscale images every 15 minutes as well as a Full Disk every 5 minutes.
The following four requirements of the NWS (National Weather Service) are considered with highest priority: 46)
1) Continuous instrument operation capability including the eclipse phases at the vernal equinoxes of the GEO orbit
2) Simultaneous observation capability for the modes “full-disk” and “CONUS” (Contiguous USA).
3) Improvement of the temporal instrument imagery resolutions.
- Full-disk Earth observation within 15 minutes
- CONUS, or the equivalent of a nadir-viewed rectangle (3000 km x 500 km) every 5 minutes (goal of 1 minute)
- Imagery of minimum size 1000 km x 1000 km (nadir) every 30 seconds
- A capability must exist to observe concurrently the CONUS and full-disk imagery along with all other imaging activities, such as space locks, blackbody calibrations, and star observations
4) Improvement of the spatial resolution of the imagery. The current GOES Imager spatial resolution (1 km in VIS and 4 km in IR) must be doubled for ABI. 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:
• VIS band (0.64 µm): 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
• SWIR band (1.6 µm): Daytime cloud/snow/ice discrimination, total cloud cover, aviation weather analysis for icing, smoke from low-burn-rate fires
• MWIR band (3.9 µm): Fog and low-cloud discrimination at night, fire identification, volcanic eruption and ash, daytime reflectivity for snow/ice
• MWIR band (7.0 µm): Middle-tropospheric water vapor tracking, jet stream identification, hurricane track forecasting, mid-latitude storm forecasting, severe weather analysis
• TIR band (11.2 µm): Continuous day/night cloud analysis for many general forecasting applications, precipitation estimates, severe weather analysis and prediction, cloud drift winds, hurricane strength and track analysis, cloud top heights, volcanic ash, winter storms, cloud phase/particle size (in mid-band products)
• TIR band (12.3 µm): Continuous cloud monitoring for numerous applications, low-level moisture, volcanic ash trajectories, cloud particle size (in mid-band products)
• TIR band (13.3 µm): Cloud top height assignments for cloud-drift winds, cloud products for ASOS supplement, tropopause delineation, cloud opacity.
Application spectrum of the five additional bands.
• VIS band (0.47 µm): This band is used for aerosol detection and visibility estimation
• VIS band (0.86 µm): This band provides synergy with AVHRR/3 band 2. The band is used for determining vegetation amount, aerosols and ocean/land studies.
• SWIR band (1.378 µm): This band is similar to a MODIS band. It does not see into the lower troposphere due to water vapor sensitivity, thus it provides excellent daytime sensitivity to very thin cirrus.
• TIR band (8.5 µm): This band permits the detection of volcanic cloud with sulfuric acid aerosols, thin cirrus in conjunction with 11 µm band and determination of cloud microphysical properties with the 11.2 µm and 12.3 µm bands. This includes a more accurate delineation of ice from water clouds during day or night
• TIR band (10.3 µm): The band permits the determination of microphysical properties of clouds with the 11.2 and 12.3 µm bands. This includes a more accurate determination of cloud particle size during the day or night.
In May 2001, NASA awarded formulation phase contracts to three companies: ITT Industries' Aerospace/Communications Division, Fort Wayne, IN; BATC (Ball Aerospace & Technologies Corp.) of Boulder, CO; and Raytheon SBRS (Santa Barbara Remote Sensing), Goleta, CA. Under terms of the contracts, each company developed detailed engineering plans for the future instrument. In Sept. 2004, NASA on behalf of NOAA has selected ITT Industries to design and develop the ABI instrument.
Note: In 2011, the ITT Corporation split into three companies: ITT, Xylem, and ITT Exelis. The ABI instrument was developed at ITT Exelis in Fort Wayne, IN.
Table 3: Key performance parameter comparison of 2nd and 3rd generation imagers (Ref. 50)
Table 4: Requirements overview for the ABI instrument
Table 5: Overview of the spectral band allocation for the ABI instrument
Figure 9: Schematic view of the ABI instrument (image credit: ITT) 47)
Table 6: Approximate number of ABI pixels for various support modes (Ref. 40)
ABI cryocooler: NGAS (Northrop Grumman Aerospace Systems) has developed and tested a two-stage pulse tube (PT) cooler of JAMI (Japanese Advanced Meteorological Imager) heritage flown on the Japanese MTSAT-1R mission (launch Feb. 26, 2005). The ABI cooler system incorporates an integral HEC (High Efficiency Cryocooler) pulse tube cooler and a remote coaxial cold head. The two-stage cold head was designed to provide large cooling power at 53 K and 183 K, simultaneously. 48) 49)
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 two cooler systems are referred to as TDU (Thermo-Dynamic Units); in addition, there are two associated CCE (Cooler Control Electronics) units that provide power and control functions to the TDUs.
Figure 10: Illustration of the PFM TDU (image credit: NGAS)
Figure 11: The CCE (Cooler Control Electronics) device (image credit: NGAS)
The TDU has a size of 370 mm x 350 mm x 130 mm (width x depth x height) with a mass of 5.5 kg. The size of CCE is 235 mm x 205 mm x 85 mm (width x depth x height) with a mass of 3.8 kg. The requirements on the cooler call for: 2.27 W of cooling at 53.0 K and 5.14 W of cooling at 183.1 K.
INR (Image Navigation and Registration):
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. 50)
INR on the current GOES program preceding GOES-R (2nd generation) employs image motion compensation (IMC) on board the spacecraft/imager to assure the image line of sight is accurately pointed to desired locations on the Earth scene. 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. The navigated samples are then re-sampled using a 4 x 4 sample kernel to form the 14 µrad pixels which form the Earth disk image.
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. Per the GOES-R GIRD (General Interface Requirements Document), the spacecraft provides the following information to allow the instrument to collect scenes:
- Quaternion: ~ 100 µrad uncertainty (sampled at 1 Hz)
- Attitude rate measurements: < 20 µrad drift over 15 minutes (sampled at 100 Hz)
- Spacecraft position: 35 m in-track, 35 m cross-track and 70 m radial over 15 minutes (sampled at 1 Hz)
- Spacecraft velocity: < 6 cm/sec uncertainty per axis (sampled at 1 Hz).
Reference frame definitions: Image navigation and registration uses data and measurements defined in a number of different coordinate frames. The primary reference frame is J2000 which is the inertial frame in which the star catalog coordinates are defined. Star coordinates are updated to a True of date frame and then to an EFC (Earth Centered Fixed) coordinate frame with the X-axis oriented to the station longitude for GOES. 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. ABI commanding and image navigation is defined relative to the Fixed Grid Frame defined as an ideal Geosynchronous orbit located at the GOES east or GOES west station longitude.
Table 7: GOES-R INR metric performance requirements
Figure 12: Reference frames used in the INR process (image credit: ITT)
Figure 13: .ABI image navigation and registration process (image credit: ITT)
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. 51)
Figure 14: Photo of the ABI instrument (image credit: ITT) 52)
SUVI (Solar Ultra Violet Imager):
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. The SUVI provides narrowband imaging in the soft X-ray to EUV wavelength range (9.4 nm - 30.4 nm) at a high cadence (up to 3 images/s). 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. SUVI will continue the mission performed by the current GOES-M/P series SXI (Solar X-ray Imager) instrument. 53) 54)
Figure 15: Photo of the SUVI instrument assembly (image credit: LM ATC)
Status of SUVI:
- In November 2012, the Lockheed Martin team met the requirements of a Pre-Environmental Review (PER). The Lockheed Martin SUVI instrument has met all requirements of the PER.
- The next major review will be the Pre-Ship or Pre-Storage Review in May 2013. The team is on plan for instrument delivery in Oct. 2013 to the Lockheed Martin Space Systems facility in Denver for integration with the spacecraft. 57)
- Dec. 2013: A Lockheed Martin team has completed the SUVI (Solar Ultraviolet Imager) instrument. The instrument will be delivered in 2014 for integration with the first GOES-R spacecraft at Lockheed Martin's Space Systems facility in Denver. 58)
- April 2014: Lockheed Martin has delivered the SUVI instrument for GOES-R integration. 59)
EXIS (Extreme Ultra Violet and X-ray Irradiance Sensor):
EXIS contains two full disk instruments, the EUVS (EUV Sensor) and the XRS (X-Ray Sensor). The EUVS is a full disk detector measuring EUV flux in the 5 - 127 nm range as compared to the 10 – 126 nm range for GOES-N. EUV radiation plays a key role in heating the thermosphere and creating the ionosphere. The EXIS instrument has been designed and developed at LASP (Laboratory for Atmospheric and Space Physics) at the University of Colorado, Boulder, CO (PI: Frank Eparvier). 60) 61)
NOAA requires the realtime monitoring of the solar irradiance variability that controls the variability of the terrestrial upper atmosphere (ionosphere and thermosphere). 62)
• The EUVS device monitors solar variations that directly affect satellite drag/tracking and ionospheric changes, which impact communications and navigation operations. This information is critical to understanding the outer layers of the Earth’s atmosphere.
- Through a combination of measurements and modeling, EUVS determines the solar EUV spectral irradiance in the 5 -127 nm range.
- Pre-GOES-R EUVS: Transmission grating spectrographs covering five broad bandpasses.
- EUVS for GOES-R: Three reflection grating spectrographs measuring specific solar emission lines from which fullspectrum is reconstructed with a model.
• The XRS instrument monitors solar flares that can disrupt communications and degrade navigational accuracy, affecting satellites, astronauts, high latitude airline passengers, and power grid performance.
- XRS measures the solar soft x-ray irradiance in two bandpasses at 0.05-0.4 nm and 0.1-0.8 nm
- Pre-GOES-R XRS: Ionization chamber instruments with limited dynamic range (solar min unresolved in noise and bright flares clipped)
- XRS for GOES-R: Solid state detectors that capture full dynamic range of solar variability.
Table 8: Key measurement requirements of EXIS
Figure 16: Illustration of the EXIS instrument (image credit: LASP, NOAA)
Table 9: EXIS instrument parameters
GLM (Geostationary Lightning Mapper):
GLM is also referred to as LMS (Lightning Mapper Sensor). The GLM mission consists of an optical imaging instrument of GHCC (Global Hydrology and Climate Center) at NASA/MSFC (Marshall Space Flight Center, Huntsville, AL). 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:
- Diagnose and forecast the transient evolution of severe storm events, such as tornadoes, microbursts, hail storms and flash floods
- Improve mesoscale model forecasts and satellite-based retrievals of convective properties
- Improve forecast models through rapid-update assimilation of lightning data
- Examine the seasonal to interannual variability of storms and to develop a lightning climatology.
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. 63) 64) 65) 66)
Table 10: Specification of the GLM instrument
In Sept. 2007, a NASA/NOAA contract was awarded to LM ATC (Lockheed Martin Advanced Technology Corporation) of Palo Alto, CA to build the GLM instrument. 67)
The GLM instrument consists of a staring imager optimized to detect and locate lightning. The major subsystems of the instrument are: an imaging system, a focal plane assembly, real-time event processors, a formatter, power supply, and interface electronics. The imaging subsystem is a fast f/1.2 telescope with a 12 cm aperture diameter and a 1 nm bandwidth interference filter. 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.), the science data output of the GLM instrument consists primarily of events, not images. 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.
Figure 17: Photo of the GLM engineering unit (image credit: GHCC, NOAA)
Event filtering approaches: 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.
• Spatial filtering is used which matches the IFOV of each detector element in the GLM focal plane array to the typical cloud-top area illuminated by a lightning stroke (i.e., in the order of about 10 km). This results in an optimal sampling of the lightning scene relative to the background illumination.
• Spectral filtering is obtained by using a narrowband interference filter centered on a strong optical emission line (e.g., OI at 777.4 nm) in the lightning spectrum. This method further maximizes the lightning signal relative to the reflected daylight background.
• GLM employs temporal filtering which takes advantage of the difference in lightning pulse duration which is on the order of 400 µs versus the background illumination which tends to be constant on the time scale of seconds. 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.
• Since the ratio of the background illumination to the lightning signal often exceeds 100 to 1 at the focal plane, a fourth technique, a modified frame-to-frame background subtraction is implemented to remove the slowly varying background signal from the raw data coming off the GLM focal plane. 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 500 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. 68).
The large data rate of about 5 Gbit/s is read out from the focal plane of GLM into several RTEPs for event detection and data compression. 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 64-bit data structure describing the identity of the pixel, the camera frame (i.e. time) in which it occurred, its intensity with respect to the background, and the value of the background itself. Performing on-board image processing in the RTEPs, and reporting changes in the Earth scene by exception only (when an event is triggered) reduces the downlink data bandwidth of the instrument to a reasonable level, from 14 bit/pixel x (1372 x 1300) pixels/frame x 500 frames/s = 12.5 Gbit/s of raw video data to just ~6 Mbit/s of processed event data.
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.
Architectural drivers: 68)
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.
• Patented Variable Pixel Pitch: The GLM CCD was designed such that the GSD (Ground Sample Distance), i.e. the projected area of each pixel on the Earth’s surface, is approximately constant with a target value of 8 km matched to the typical size of a storm cell. 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.
• RTEP (Real Time Event Processor) adjustability: 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 18 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.
Figure 18: Small portion of cloud scene, as viewed by GLM (image credit: Lockheed Martin STAR Labs)
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. The total noise in each pixel (1σ, in units of DN) is simulated in Figure 19; note that it varies by several counts over small spatial scales.
Figure 19: Total noise, 1σ (DN), image credit: Lockheed Martin STAR Labs
If one were to apply a single global detection threshold to this entire 90 x 90 pixel scene, selected such that the false event rate stayed below 100 events/s over this portion of the cloud scene, the global threshold would need to be 25 counts and the TNR would vary widely across the scene:
Figure 20: Threshold-to-noise ratio achieved by selecting a single detection threshold of 25 (image credit: Lockheed Martin STAR Labs)
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). - GLM does not use a global threshold in recognition of the fact that shot noise varies significantly from pixel to pixel due to the highly variable illumination of cloud tops. The event detection threshold is selected by the RTEP for each individual pixel from a 32-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 21. In this example, the threshold values were determined by the same criterion to keep the false event rate less than 100 events/sec.
Figure 21: Detection thresholds selected on a pixel-by-pixel basis (image credit: Lockheed Martin STAR Labs)
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 22):
Figure 22: Threshold-to-noise ratio when detection threshold is selected on a pixel-by-pixel basis (image credit: Lockheed Martin STAR Labs)
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 GLM RTEP design benefits directly from years of on-orbit experience with the LIS (Lightning Imaging Sensor) flying on the TRMM satellite.
• Narrow Band Filter: 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 23, 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: a SRF (Solar Rejection Filter) at ~30 nm FWHM that performs the task of rejecting the bulk of out-of-band radiation, a SBF (Solar Blocking Filter) at ~3 nm FWHM, and the key NBF (Narrow Band Filter) at ~1 nm FWHM. Due to their large size and stringent spectral requirements, these filters pushed the boundaries of manufacturing capabilities.
Figure 23: Worst-case 100% albedo Lambertian cloud spectral radiance at 777 nm, with atmospheric loss (mW/sr/cm2/µm),image credit: Lockheed Martin STAR Labs
• Frame Rate and CCD Well Depth: 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 24.
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 500 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.
Figure 24: Typical lightning optical pulse profile (image credit: Lockheed Martin STAR Labs)
Coherency Filter: 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. Most of the filters are based on work done on the LIS (Lightning Imaging Sensor). 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. An 80% cloud background albedo is assumed and the background of each pixel at a given time and illumination is calculated. The project can then determine which threshold will be selected for each pixel, and determine the detection efficiency of each pixel. Figure 25 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. When averaged over 24 hours and over the entire field of view, GLM is expected to detect 80% of lightning flashes.
Figure 25: Calculated detection efficiency of each GLM pixel, in percent, at 4 PM local time as seen from GOES-East satellite (image credit: Lockheed Martin STAR Labs)
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. Hemispherical coverage combined with round-the-clock operation at 500 frames/s will enable near real-time reporting of lightning flashes, giving unprecedented insight into the energetics of severe weather.
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.
Long-term trending of GLM lightning data will provide continuity with data sets from LIS (Lightning Imaging Sensor) flown on the TRMM satellite, and contribute to our understanding of decadal changes in the Earth’s climate.
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.
SEISS (Space Environmental In Situ Suite):
The SEISS instrument package monitors the near-Earth particle and electromagnetic environment in real-time. Monitoring of geomagnetically trapped electrons and protons; electrons, protons, and heavy ions of direct solar origin; and galactic background particles.
The SEISS package consists of the following instruments:
EHIS (Energetic Heavy Ion Sensor), designed and developed at NHU (New Hampshire University). The objective of EHIS is to measure the proton, electron, and alpha particle fluxes at GEO. The EHIS device incorporates a unique system design called ADIS (Angle Detecting Inclined Sensor).
MPS (Magnetospheric Particle Sensor). 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.
SGPS (Solar and Galactic Proton Sensor).
Figure 26: Schematic view of the SEISS instrument package (image credit: GOES-R project)
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 0.016 nT and response frequency of 2.5 Hz.
The MAG device is provided by Lockheed Martin, Newton, PA and is boom mounted on GOES-R.
Figure 27: Illustration of the boom-mounted MAG device (image credit: GOES-R project)
Ground Segment (GS) of the GOES-R series:
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. 71) 72)
In May 2009, NOAA selected the Harris Corporation - Government Communications Systems Division of Melbourne, FLA, to develop the GOES-R ground system, which will capture, process and distribute information from NOAA's next generation geostationary satellite series to users around the world. 73) 74) 75) 76) 77) 78) 79) 80)
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. In addition, the GS will provide a RBU (Remote Backup Facility), new and upgraded antenna capabilities to NOAA, and will develop a user distribution and access portal known as the GOES-R Access Subsystem.
The ground segment contract baseline and options include:
• Development of the core ground segment
- Mission management element
- Enterprise management element
- Product generation element
- Subset of product generation element: a) GRB (GOES Rebroadcast), b) AWIPS (Advanced Weather Information Processing System) distribution
- Internal telecommunications/networks (i.e., intra-site)
- Option 1: improved latency / option 2: additional L2+ products
• Total ground segment integration and checkout
- Integration of GFP systems, including antennas and GAS (GOES-R Access Subsystem)
- Interfaces to external systems, including CLASS and ADRS (Ancillary Data Relay System)
• Transition to NOAA operations.
Figure 28: Architectural overview of the GOES-R Ground System (image credit: GOES-R GS Project)
Table 11: GOES-N and GOES-R data transfer differences
GOES-R Ground Segment Sites:
The GOES-R GS will operate from three sites:
1) NSOF (NOAA Satellite Operations Facility) in Suitland, MD. NSOF will house the primary Mission Management (MM), Product Generation (PG), and Product Distribution (PD) functions.
2) WCDAS (Wallops Command and Data Acquisition Station), located at Wallops, VA. WCDAS will provide space communications services and selected Ground Segment functions.
3) RBU (Remote Backup) facility. RBU is a geographically isolated site, located in Fairmont, WV (West Virginia). RBU will function as a completely independent backup for designated MM, PG and PD functions for the production and delivery of critical cloud and moisture imagery products, and GOES Rebroadcast (GRB) data,and will be capable of remote operation from the NSOF and WCDAS. The RBU station will have visibility to all operational and on-orbit spare satellites. The Enterprise Management (EM) function supports GS components across all locations.
Figure 29: GOES-R Ground Segment Architecture (image credit: GOES-R GS Project, Ref. 80)
Figure 30: Operational sites of the GOES-R Ground Segment (image credit: GOES-R GS Project)
Spacecraft commands are generated by GS operators and are uplinked to the satellite through the primary command interface at the WCDAS (Wallops Command and Data Acquisition Station), located at Wallops, VA. Commands may also be generated at the NSOF (NOAA Satellite Operations Facility) in Suitland, MD and sent terrestrially to WCDAS for uplink via dedicated, high availability telecommunications circuits. Commands may also be generated from the RBU site in Fairmont, WV or may be distributed from one of the other two sites to RBU for uplink.
For GOES-R operations, the NSOF and WCDAS together comprise the “primary” sites and may be considered in certain respects as a single system. WCDAS provides the Earth-space communications functions, while primary console operations and higher-level product data functions are provided by NSOF. The RBU consolidates the mission-critical functionality of the NSOF and WCDAS into a single “backup” site that can operate completely independently.
Spacecraft telemetry data is received and processed at WCDAS during primary operations and at RBU in non-nominal or contingency situations. 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. These functions occur at NSOF and WCDAS during primary mission operations.
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. Product monitoring enables the operations team to identify anomalies in the instrument data being generated by the GS. Product monitoring is focused on Level 1b processed data included in the GRB (GOES Rebroadcast) data stream. It also provides for the monitoring of the signal quality of the uplinked and downlinked communications signals to ensure integrity of the received data.
Figure 31: RBU (Remote Backup) Facility, Fairmont, W.VA (image credit: GOES-R GS Project, Ref. 80)
GOES-R GS Antenna System:
Associated with the development of the GS is a set of new and upgraded antennas to support the transmission and receipt of GOES-R series satellite data, along with legacy GOES mission data. At WCDAS and RBU, these antennas will provide for raw data and telemetry receipt from the spacecraft in X-band. They will support command uplinking in S-band and will provide for the uplink of GRB L1b data at X-band. They will also be capable of receiving GRB data to perform quality monitoring of the GRB downlink in L-band.
Figure 32: Notional view of of a 16.4 m antenna station (image credit: NOAA, Harris)
At WCDAS, three new 16.4 m antennas will be installed into the existing NOAA antenna infrastructure. One of the existing 18 m antennas will be replaced, and two additional antennas will be added. All three antennas will support both the GOES-R series and legacy GOES missions. They will be designed to operate through a Category 2 hurricane without performance degradation.
Three new antenna stations will also be installed at the GOES-R RBU site. 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. Although the current GOES-R series mission does not include backup for legacy GOES at the RBU, the antennas at RBU will be capable of supporting both missions.
At NSOF, the existing 9.1 m antennas will be upgraded to be capable of receiving both GRB and legacy GVAR (GOES Variable) downlinks. This data receipt provides the primary path through which L1b data is sent to NSOF from WCDAS. 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.
Figure 33: Antenna system architecture components at each facility (image credit: NOAA, Harris)
In addition to the primary data streams, the GOES-R series antennas will support a set of Unique Payload Services. The HRIT/EMWIN (High Rate Information Transmission/Emergency Manager’s Weather Information Network) is uplinked in S-band and downlinked in L-band at WCDAS and RBU. The HRIT/EMWIN broadcast provides low-resolution GOES imagery and products, along with emergency weather forecasts and warnings generated by the NWS (National Weather Service). - In parallel, the GOES-R series system will support the collection of in-situ environmental sensor data from DCS (Data Collection System) platforms and will transpond commands to DCS platforms using the GOES-R antennas at WCDAS. Interfaces between the Antenna System and the HRIT/EMWIN and DCS systems will mirror those in place at WCDAS today, but with new and upgraded capabilities to support more DCS terminals and higher data rate signals for HRIT/EMWIN.
Figure 34: Photo of WCDAS (Wallops Command Data Acquisition Station), Wallops Island, VA (image credit: GOES-R GS Project, Ref. 80)
Core Ground Segment Functions:
The key functions of the Ground Segment are as follows:
1) MM (Mission Management):
The MM element provides the primary interface between the GS and the Space Segment. It is responsible for the following functional areas (Ref. 71):
• Space-ground communications
• Command generation
• Telemetry (TT&C) processing
• Mission operations
• Product monitoring.
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.
Figure 35: Ground segment functions (image credit: NOAA)
2) PG (Product Generation):
Raw data is received at WCDAS and processed through the antenna system and space-ground communications hardware until CCSDS-formatted packets are recovered. 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. For GLM (Geostationary Lightning Mapper) data, the data set is further processed algorithmically to produce a higher order Level 2+ (L2+) product. GLM L1b and L2+ data, along with the L1b data from all other instruments, is packaged for distribution via the GRB uplink. GRB is sent from PG through the space-ground communications equipment to be uplinked from WCDAS at X-band. The GRB link is transponded onboard the GOES-R Series satellites and downlinked in L-band within the satellite coverage area down to a 5º elevation angle. GRB data is freely available to any users within the coverage area who possess the appropriate equipment to receive the data.
GRB distribution is the primary means of providing L1b instrument data from WCDAS to NSOF. L1b is received at NSOF through the antenna system and is processed back to L1b data sets. This L1b data is then further processed through a set of algorithms to create higher order (L2+) science products. These include the GOES-R KPP (Key Performance Parameter) product of Cloud and Moisture Imagery, which is the critical higher order product required for mission success.
A total of 65 End-Products have been identified for the GOES-R GS. 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 algorithms are implemented by the GS development contractor based on ATBDs (Algorithm Theoretical Basis Documents) generated by NOAA’s Center for Satellite Applications and Research (STAR) in the case of L2+ End-Products and provided by the instrument vendor in the case of L1b End-Products. 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.
Depending on the algorithm used for generation of each L2+ product, ancillary data inputs may be required to create a given product. These ancillary inputs are aggregated from multiple sources such as numerical weather prediction models and snow/ice analyses through the ADRS (Ancillary Data Relay System). ADRS is being developed in conjunction with the GOES-R GS and will be configurable to meet algorithm needs over the life of the mission. ADRS will provide the ancillary data to the PG L2+ processing system to support the generation of these higher order products. Currently, 20 of the L2+ End-Products listed above require ancillary data inputs.
The PUG (Product Definition and Users' Guide) is defined in the following reference: 81)
3) PD (Product Distribution):
Once the End Products are generated, the core GS PD (Product Distribution) element ensures that data and products are provided to the appropriate entities. The core GS distributes data to the GAS (GOES-R Access Subsystem) via a dedicated network interface located at NSOF. GAS is the primary source of L2+ data for the majority of GOES users Data is also provided directly to NWS via the AWIPS (Advanced Weather Interactive Processing System) interface and to NOAA’s CLASS (Comprehensive Large Array-data Stewardship System) via dedicated interfaces.
The GOES-R Access System is being developed as a component of an overall upgrade of NOAA’s ESPC (Environmental Satellite Processing Center) under the ESPDS (Environmental Satellite Processing and Distribution System) development effort. 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. GAS will receive the L1b and L2+ products described in Figure 28, along with ancillary data, metadata, Instrument Calibration Data, sample outlier files for the ABI, and mission operations data (schedules, satellite configuration, operations schedules, and other operational information).
The core GS PD element will also provide sectorized cloud and moisture imagery directly to the NWS via the AWIPS interface. 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:
• Geographic coordinate corner points
• Map projection (Mercator, Lambert conformal, Polar Stereographic, or Fixed Grid)
• Spatial resolution
• Bit depth
• ABI channel
A “stressing case” consisting of a representative set of AWIPS data has been defined between the GOES-R GS and the NWS and is being used to provide a baseline capability for the system’s performance. The system will remain operationally configurable to respond to changing NWS needs within the parameters defined above.
All Level 0, L1b, and L2+ GOES-R data and products will be archived in NOAA’s CLASS repository for long-term preservation. 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. These non-operational users will interface with the CLASS via a we-based interface outside of the GOES-R system. In addition, Instrument Calibration Data, calibration coefficients, ancillary data, and L2+ parameter tables will be stored to enable detailed analysis and reprocessing by the meteorological and climatological communities. The GS-CLASS interface will be sized to support the distribution of over 2.5 TB of data per day per satellite.
Figure 36 depicts the complete flow of data from the satellite’s instruments through the products’ distribution to the user community.
Figure 36: The data flow of the GOES-R mission (image credit: GOES-R GS Project)
4) EM (Enterprise Management):
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. EM functions underpin the infrastructure that links the MM, PG, and PD functions and supports automation. 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. Components of the GS that are not a part of the core GS will report EM status through a core GS element (e.g., the Antenna system will report via MM and the GAS will report through PD).
In addition to status and monitoring, EM provides configuration and asset management functionality for the GS. The GS uses a consolidated CMART (Configuration Management and Anomaly Reporting and Tracking) system to manage the configuration of software builds, licenses, and database schema. CMART also provides the ability to distribute software and database updates throughout 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.
5) IS (Infrastructure):
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.
The GAMCATS (GOES-R Antenna Monitor, Control, and Test Subsystem) performs an analogous function to EM for the Antenna 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. During normal operations, the GOES-R antennas and associated equipment at both WCDAS and RBU will be monitored and controlled from the WCDAS operations room, with backup monitoring by operators at NSOF via remote GAMCATS workstation. GAMCATS will provide status information to the core GS MM element via event messages, and these will be relayed to the core GS EM element to provide a consolidated view of the GS status (Ref. 71).
Figure 37: Overview of GOES-R data distribution (image credit: NOAA, Ref. NO TAG#
GOES-R UPS (Unique Payload Services):
The GOES-R Unique Payload Services suite consists of transponder payloads providing communications relay services in addition to the primary GOES mission data. The UPS suite consists of the following elements: 82)
• DCS (Data Collection System)
• HRIT/EMWIN (High Rate information Transmission / Emergency Managers Weather Information Network).
• GRB (GOES-R Rebroadcast). GOES-R Rebroadcast is the primary space relay of Level 1b products and will replace the GOES VARiable (GVAR) service. GRB will provide full resolution, calibrated, navigated, near-real-time direct broadcast data. The content of the data distributed via GRB service is envisioned to be the full set of Level 1b products from all instruments onboard the GOES-R series spacecraft. This concept for GRB is based on analysis that a dual-pole circularly polarized L-band link of 12 MHz bandwidth may support up to a 31-Mbps data rate – enough to include all ABI channels in a lossless compressed format as well as data from GLM, SUVI, EXIS, SEISS, and MAG.
Table 12: Transition from GVAR to GRB (Ref. 79)
• SARSAT (Search and Rescue Satellite Aided Tracking) System. NOAA operates the SARSAT system to detect and locate mariners, aviators, and other recreational users in distress almost anywhere in the world at anytime and in almost any condition. This system uses a network of satellites to quickly detect and locate distress signals from emergency beacons onboard aircraft, vessels, and from handheld PLBs (Personal Locator Beacons. The SARSAT transponder that will be carried onboard the GOES-R satellite will provide the capability to immediately detect distress signals from emergency beacons and relay them to ground stations - called Local User Terminals. In turn, this signal is routed to a SARSAT Mission Control Center and then sent to a Rescue Coordination Center which dispatches a search and rescue team to the location of the distress.
GOES-R continues the legacy GEOSAR (Geostationary Search and Rescue) function of the SARSAT system onboard NOAA’s GOES satellites which has contributed to the rescue of thousands of individuals in distress. The SARSAT transponder will be modified slightly for GOES-R by being able to operate with a lower uplink power (32 dBm) enabling GOES-R to detect weaker signal beacons.
DCS (Data Collection System):
The objective of DCS is to collect near real-time environmental data from more than 19,000 data collection platforms located in remote areas where normal monitoring is not practical. The DCS receives data from platforms on ships, aircraft, balloons and fixed sites. These data are used to monitor seismic events, volcanoes, tsunami, snow conditions, rivers, lakes, reservoirs, ocean data, forest fire control, meteorological and upper air parameters.
The transmissions can occur on predefined frequencies and schedules, in response to thresholds in sensed conditions, or in response to interrogation signals. The transponder on board the GOES satellite detects this signal and then rebroadcasts it so that it can be picked up by other ground-based equipment. Federal, state and local agencies then monitor the environment through the transmission of observations from these surface-based data collection platforms. The platforms can be placed in remote locations and left to operate with minimal human intervention. The Data Collection System thus allows for more frequent and more geographically complete environmental monitoring. Enhancements to the DCS program during the GOES-R era include expansion in the total number of user-platform channels from 266 to 433.
Figure 38: Data flows of the DCS (image credit: NOAA/NESDIS, Ref. 82)
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The information compiled and edited in this article was provided by Herbert J. Kramer from his documentation of: ”Observation of the Earth and Its Environment: Survey of Missions and Sensors” (Springer Verlag) as well as many other sources after the publication of the 4th edition in 2002. - Comments and corrections to this article are always welcome for further updates (firstname.lastname@example.org).