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GOES-16 Peer/Stakeholder Product Validation Reviews


The tabs to the left list products. Clicking on a product tab will display all information related to that product.

  • ABI - L1b and Cloud
  • ABI - Surface
  • ABI - Other
  • GLM
  • EXIS
  • SUVI
  • MAG
  • SEISS

  • Radiances
  • Cloud and Moisture Imagery
  • Cloud Optical Depth
  • Cloud Particle Size Distribution
  • Clear Sky Mask
  • Cloud Top Height
  • Cloud Top Phase
  • Cloud Top Pressure
  • Cloud Top Temperature

GOES-R will measure Radiances in 16 visible, near-infrared, and infrared spectral bands at high spatial and temporal resolutions. These Radiances will be used to identify cloudy and cloud-free regions within the satellites’ field of view. Data provided by the 16 spectral channels will be used to generate many GOES-R products, and will also be used in numerical weather prediction models, aiding meteorologists and others in monitoring and predicting all kinds of weather and other phenomena.

Beta (02/28/2017)
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Provisional (06/01/2017)
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Full (06/01/2018)
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The Cloud and Moisture Imagery product will utilize all 16 spectral bands of the GOES-R ABI to monitor the Earth, Atmosphere, and Ocean system. The measured reflectance (radiance) within the visible (infrared) bands will be converted into Brightness Values (BVs) and Brightness Temperatures (BTs), respectively. The BVs and BTs will be used to generate an array of products aiding forecasters in monitoring and predicting all kinds of hazards: weather, oceanographic, and climate-related phenomena.

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Full (06/01/2018)
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Cloud Optical Depth will use both the visible and the near-infrared bands during the daytime and a combination of infrared bands for night-time detection. This product, together with the Cloud Particle Size Distribution product, will provide valuable information about the radiative properties of clouds. These two properties will enhance climate prediction, as they will provide global climate models with higher quality data regarding the Earth’s energy and radiation budget.

Beta (06/8/2017)

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Provisional (02/22/2018)

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The Cloud Effective Particle Size will be computed using the same algorithm that estimates the Cloud Optical Depth. Using both the visible and near-infrared bands during the day and the infrared bands during the night, the GOES-R Cloud Optical and Microphysical Properties algorithm will retrieve, simultaneously with COD, the Cloud Particle Size. The Cloud Particle Size will provide valuable information about the radiative properties of clouds. This information combined with the information provided by the COD product will provide very accurate information about the Earth’s radiation budget, yielding more accurate climate prediction possibilities.


Cloud Optical Depth will use both the visible and the near-infrared bands during the daytime and a combination of infrared bands for night-time detection. This product, together with the Cloud Particle Size Distribution product, will provide valuable information about the radiative properties of clouds. These two properties will enhance climate prediction, as they will provide global climate models with higher quality data regarding the Earth’s energy and radiation budget.

Beta (06/8/2017)

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Provisional (02/22/2018)

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The Clear Sky Mask algorithm will take advantage of the high spatial and temporal resolution of the GOES-R ABI visible, near-infrared, and infrared bands to automatically produce a cloud classification for each pixel: cloudy, probably cloudy, clear, or probably clear. This information will be used extensively by downstream level-2 product algorithms that require the state of cloudiness in each pixel. Products such as Land Surface Temperature (LST) and Sea Surface Temperature (SST), for example, can only be reliably computed for pixels that are totally cloud free. The Clear Sky Mask product can be used by the NWP community to identify which ABI pixel information should be assimilated for use in numerical weather prediction models.


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The Cloud Top Height algorithm will use ABI infrared bands to simultaneously retrieve Cloud Top Height, Cloud Top Temperature, and Cloud Top Pressure for each cloudy pixel. These cloud products are a prerequisite for generating other downstream products that include the Cloud Layer product, Cloud Optical/Microphysical products, and the Derived Motion Wind products. Forecasters will be able to use this information to determine areas of cloud growth and likelihood of precipitation. Other operational applications of this product include its use in Aviation Terminal Aerodrome Forecasts (TAFs), supplementing upper-level cloud information to the ground-based Automated Surface Observing System (ASOS), and initialization of clouds in numerical weather prediction models.


Beta (05/16/2017)
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The Cloud Type algorithm will use four GOES-R ABI infrared spectral bands to determine four different cloud phases: warm (>0C) liquid water, supercooled liquid water, mixed, and ice. The Cloud Phase product is a prerequisite for generating other downstream products that include Cloud Height, Cloud Optical Properties, Fog Detection/Depth, and Aircraft Icing. The Cloud Top Phase product will enable meteorologists to better monitor and track changes in the water properties of clouds, improve icing forecasts for the aviation community, and aid in improving warnings for severe weather. Cloud Phase product information can also be used in advanced ABI applications such as severe weather prediction and tropical cyclone intensity estimation.


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Provisional (02/22/2018)

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The Cloud Top Height algorithm will use ABI infrared bands to simultaneously retrieve Cloud Top Height, Cloud Top Temperature, and Cloud Top Pressure for each cloudy pixel. These cloud products are a prerequisite for generating other downstream products that include the Cloud Layer product, Cloud Optical/Microphysical products, and the Derived Motion Wind products. Forecasters will be able to use this information to determine areas of cloud growth and likelihood of precipitation. Other operational applications of this product include its use in Aviation Terminal Aerodrome Forecasts (TAFs), supplementing upper-level cloud information to the ground-based Automated Surface Observing System (ASOS), and initialization of clouds in numerical weather prediction models.


Beta (05/16/2017)
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Provisional (02/16/2018)

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The Cloud Top Height algorithm will use ABI infrared bands to simultaneously retrieve Cloud Top Height, Cloud Top Temperature, and Cloud Top Pressure for each cloudy pixel. These cloud products are a prerequisite for generating other downstream products that include the Cloud Layer product, Cloud Optical/Microphysical products, and the Derived Motion Wind products. Forecasters will be able to use this information to determine areas of cloud growth and likelihood of precipitation. Other operational applications of this product include its use in Aviation Terminal Aerodrome Forecasts (TAFs), supplementing upper-level cloud information to the ground-based Automated Surface Observing System (ASOS), and initialization of clouds in numerical weather prediction models.


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  • Downward S/W Radiation: Surface
  • Fire/Hot Spot Characterization
  • Hurricane Intensity Estimation
  • Land Surface Temperature
  • Rainfall Rate/QPE
  • Reflected S/W Radiation: TOA
  • Sea Surface Temperature
  • Snow Cover

The Downward Shortwave Radiation (DSR) product is an estimate of the total amount of shortwave radiation (both direct and diffuse) that reaches the Earth’s surface. The product algorithm uses spectral channels in both the visible and the infrared in addition to data regarding albedo and atmospheric composition to compute the Downward Shortwave Radiation at the Earth’s surface. DSR has many applications both in the general and applied sciences. As one of the components of the surface energy budget, it is needed in climate studies. Used together with cloud and aerosol properties it provides estimates of cloud and aerosol effects (forcing). It is also used in surface energy budget models, land surface assimilation models such as those used at NOAA NCEP, NASA LDAS, and ocean assimilation models either as an input (providing observationally-based forcing term), or as an independent data source to evaluate model performance. DSR data are also employed in estimating heat flux components over the coastal ocean to drive ocean circulation models. In agriculture, DSR is used as input in crop modeling. In hydrology, it is used in watershed and run-off analysis, which is important for determining flood risks and dam monitoring. The solar energy industry also needs estimates of DSR for both real-time and short-term forecasts for building energy usage modeling and optimization. Since high irradiance values result in surface drying, DSR is also used in monitoring fire risk.

Beta (06/23/2017)
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Provisional (10/23/2018)
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The Fire/Hot Spot Characterization product makes use of both visible and IR spectral bands to locate fires and retrieve sub-pixel fire characteristics. The product greatly improves upon the currently available Fire Detection product by taking advantage of the higher spatial and temporal resolution available with the GOES-R Series ABI. Forecasters use this product to monitor wildfires, and more importantly, rapid changes in individual fires. Forecasters use this product as part of an arsenal of forecasting tools aimed at helping firefighting efforts.

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Provisional (03/30/2018)
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The Hurricane Intensity algorithm makes use of the ABI longwave infrared window band to monitor changes in the cloud top temperature near the tropical cyclone center. An analysis of the cloud top temperature field over the tropical cyclone center, together with a cloud pattern recognition analysis, enables the retrieval of an intensity estimate for the tropical cyclone valid at the time of the ABI image. The tropical storm intensity estimate is output as maximum sustained 1-minute surface winds (Kts), and minimum sea level pressure (MSLP) at the center (hPa) of the tropical storm. Hurricane Intensity estimates will provide critical guidance to forecasters at tropical cyclone forecast centers regarding tropical cyclone storm intensity from storm formation, through development and maturation, to dissipation.

Beta (09/25/2017)
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The Land Surface Temperature (LST) product is derived from GOES-R ABI longwave infrared spectral channels and is expected to be used in a number of applications in hydrology, meteorology, and climatology. Forecasters use it to forecast the occurrence of fog and frost. The land surface product is of fundamental importance to the net radiation budget at the Earth’s surface and to monitoring the state of crops and vegetation. It is an important indicator of both the greenhouse effect and the energy flux between the atmosphere and ground. Furthermore, it can be assimilated into climate, atmospheric, and land surface models to estimate sensible heat flux and latent heat flux.

Beta (05/24/2017)
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Provisional (03/19/2018)
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The ABI Rainfall Rate algorithm generates the baseline Rainfall Rate product from ABI IR brightness temperatures and is calibrated in real time against microwave-derived rain rates to enhance accuracy. The algorithm generates estimates of the instantaneous rainfall rate at each ABI IR pixel. The information provided by the QPE is used by forecasters and hydrologists in flood forecasting. Much of the flooding that occurs is related to some form of convective weather. The higher spatial and temporal resolution available on the GOES-R ABI is able to automatically resolve rainfall rates on a much finer scale, enabling weather forecasters to produce more timely and accurate flood advisories and warnings.

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The Reflected Shortwave Radiation product measures the total amount of shortwave radiation that exits the Earth through the top of the atmosphere. The algorithm uses several spectral channels in both the visible and infrared spectrum to measure the Reflected Shortwave Radiation. Information from this product provides an integral piece of the Earth’s radiation budget, aiding in climate modeling and prediction.

Beta (06/23/2017)
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Provisional (10/23/2018)
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The GOES-R Series provides forecasters with a Sea Surface Temperature (SST) for each cloud-free pixel over water identified by the ABI. The SST algorithm employed on the GOES-R Series uses hybrid physical-regression retrieval in order to produce a more accurate product. Knowledge of the SST can be beneficial for a large spectrum of operational applications that include: climate monitoring/forecasting, seasonal forecasting, operational weather and ocean forecasting, military and defense operations, validating or forcing ocean and atmospheric models, sea turtle tracking, coral bleach warnings and assessment, tourism, and commercial fisheries management.

Beta (05/24/2017)
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The fractional Snow Cover algorithm uses GOES-R ABI spectral information in the visible and near-visible portion of the energy spectrum to retrieve sub-pixel fractional Snow Cover and grain size estimates via computationally efficient spectral mixture modeling. This product will support a number of operational applications that include: assimilation into NOAA’s NOHRC snow model, as well as hydrologic forecasts and warnings, including river and flood forecasts, water management, snowpack monitoring and analysis, and climate studies.

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  • Aerosol Detection
  • Aerosol Optical Depth
  • Derived Motion Winds
  • Derived Stability Indices
  • Legacy Vertical Moisture Profile
  • Legacy Vertical Temperature Profile
  • Total Precipitable Water
  • Volcanic Ash: Detection & Height

The Aerosol Detection product will use several spectral bands made available on the GOES-R imager. The algorithm will use known spectral absorption and scattering properties of different aerosols to detect their presence in the atmosphere. The Aerosol Detection product will enable forecasters to better monitor areas of smoke and dust, which can be critical factors in visibility and air quality forecasts. In addition to short-term prediction, this product will also enable better monitoring of the long-term trends in aerosol quantities and distribution throughout the atmosphere.

Beta (05/24/2017)
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Provisional (12/06/2018)
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The Aerosol Optical Depth (AOD) product will utilize several spectral wavelengths of the ABI (Advanced Baseline Imager) to measure the reflectance properties of cloud-free pixels at the top of the atmosphere (TOA). These reflectance properties at the TOA are then fed into aerosol models to compute the surface reflectance and aerosol properties at the surface. The information provided by the AOD algorithm will aid meteorologists and others in making critical air quality, visibility, and aviation forecasts. In addition, AOD product will provide valuable data to be included in climate models and help climate scientists monitor and predict climate change.

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The Derived Motion Winds product is derived from using a sequence of visible or IR spectral bands to track the motion of cloud features and water vapor gradients. The resulting estimates of atmospheric motion are assigned heights by using the Cloud Height product. The Derived Motion Wind product provides vital tropospheric wind information over expansive regions of the earth devoid of in-situ wind observations that include oceans and Southern Hemisphere land masses. This product provides key wind observations to operational NWP data assimilation systems where their use has been demonstrated to improved numerical weather prediction forecasts including tropical cyclones. In addition, this product provides improved guidance for NWS field forecasters.

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The Derived Stability Indices such as Convective Available Potential Energy (CAPE), Lifted Index (LI), Totals Total (TT), Showalter Index (SI), and the K-Index (KI) will be computed from the retrieved atmospheric moisture and temperature profiles. These indices will aid forecasters in nowcasting severe weather by providing them with a plan view of these atmospheric stability parameters. Forecasters will use this information to monitor rapid changes in atmospheric stability over time at various geographic locations, thus improving their situational awareness in pre-convective environments for potential watch/warning scenarios.

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The Legacy Vertical Moisture Profile product estimates levels of temperature throughout the troposphere. This product is a continuation of the operational sounder product available on the previous GOES satellites. This product is used by NWS field forecasters and in numerical weather prediction models, providing information regarding the vertical temperature structure of the atmosphere. The vertical temperature structure information provided by this product is important for severe weather prediction as it is used to compute a number of atmospheric stability parameters which provide guidance to weather forecasters on the stability of the atmosphere.

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The Legacy Vertical Temperature Profile product estimates levels of temperature throughout the troposphere. This product is a continuation of the operational sounder product available on the previous GOES satellites. This product is used by NWS field forecasters and in numerical weather prediction models, providing information regarding the vertical temperature structure of the atmosphere. The vertical temperature structure information provided by this product is important for severe weather prediction as it is used to compute a number of atmospheric stability parameters which provide guidance to weather forecasters on the stability of the atmosphere.

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The Total Precipitable Water (TPW) product is computed from the retrieved atmospheric moisture profiles and represents the total integrated moisture in the atmospheric column from the surface to the top of the atmosphere. This product provides useful information to weather forecasters and hydrologists to improve their situational awareness for a number of situations that require forecasting of events, such as heavy rain, flash flooding, onset of Gulf of Mexico return flow, and the onset of the Southwest United States monsoon. The TPW product also serves to initialize the moisture field used in numerical weather prediction models.

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The Volcanic Ash product algorithm utilizes five GOES-R ABI infrared channels to automatically determine the height and mass loading properties of any pixel found to contain volcanic ash. Forecasters can use the Volcanic Ash product to identify areas where volcanic ash is present and potentially hazardous, and ultimately, issue more accurate aviation, air quality, and public health warnings. It is also expected that the Volcanic Ash product will be useful for initializing dispersion models and volcanic ash trajectory prediction models. The more accurate mass loading detection may also aid in forecasting short-term climate changes due to volcanic eruptions.

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  • Lightning: Events, Groups, Flashes

The GOES-R Series Geostationary Lightning Mapper (GLM) detects the light emitted by lightning at the tops of clouds day and night and collects information such as the frequency, location and extent of lightning discharges. The instrument measures total lightning, both in-cloud and cloud-to-ground, to aid in forecasting developing severe storms and a wide range of high-impact environmental phenomena including hailstorms, microburst winds, tornadoes, hurricanes, flash floods, snowstorms and fires.

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  • Solar Flux: Extreme Ultraviolet
  • Solar Flux: X-ray Irradiance

The GOES-R Series Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS) instrument includes a sensor that measures extreme ultraviolet (EUV) light from the sun. EUV radiation has major impacts on the ionosphere. Increased EUV radiation can result in radio blackouts of terrestrial high frequency (HF) communications. Increased EUV energy deposited in the Earth’s upper atmosphere (thermosphere) also results in increased atmospheric drag on satellites in low earth orbit (LEO). This EUV product provides improved measurements of these important wavelengths and information that assists operators of radio communication and navigation systems and satellites.

EXIS measures multiple x-ray and ultraviolet wavelengths. The specific wavelengths were chosen to monitor the different layers of the sun’s outer atmosphere and will be combined to create the full EUV spectrum of the sun every 30 seconds.

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The GOES-R Extreme Ultraviolet and X-Ray Irradiance Sensors (EXIS) measures light from the sun. The NOAA Space Weather Prediction Center (SWPC) relies on this product to issue warnings when there are large increases in solar X-ray output from solar flares. These X-ray flares cause changes in the ionosphere and are used by SWPC to give warnings of radio blackouts of terrestrial high frequency (HF) radio communications.

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  • Solar EUV Imagery

The GOES-R Series Solar Ultraviolet Imager (SUVI) Solar EUV Imagery products provide space weather scientists with images of the sun in several different EUV spectral bands. These high-resolution images will reveal details about the structure of active regions, filaments, and solar prominences. Also of interest to space and solar weather scientists are the boundaries of coronal holes and how the entire surface of the Sun behaves during solar flares. Higher-level products made from these imagery products by the NOAA Space Weather Prediction Center along with other organizations will provide early warning of potential radiation hazards, such as SEP events, flares, geomagnetic storms and radio blackouts.

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  • Geomagnetic Field

The Earth’s geomagnetic field surrounds the Earth and protects it from dangerous solar radiation. The Geomagnetic Field algorithm will monitor changes in the Earth’s geomagnetic field in three-dimensional space. These measurements are used to determine when Magnetopause crossings occur, which is important sign of the arrival of some major space weather events, such as Coronal Mass Ejections. Such massive events can cause Geomagnetically Induced Currents (GIC) in power grids, resulting in power outages. Because the magnetic field is used by the attitude control system of some satellites, these crossings are a sign that those satellites could experience issues as well. This product will help detect geomagnetic storms and sub-storms, providing early warnings to power and communication services.

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February 6 Meeting Minutes

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  • Energetic Heavy Ions
  • Magnetospheric e-/p+: Low Energy
  • Magnetospheric e-/p+: High Energy
  • Solar & Galactic Protons

The GOES-R Series Space Environment In-Situ Suite (SEISS) includes an energetic heavy ion sensor. The Energetic Heavy Ion product measured by this sensor measures energetic heavy ion fluxes in the Earth’s magnetosphere. Information provided by this product is used in tandem with the Magnetic Energetic Ion products, as well as the Solar and Galactic Proton product to provide a comprehensive picture of the energetic particle environment surrounding the Earth. This information aids scientists in assessing the risk of radiation posed to astronauts and high-altitude aircraft. These ions cause many of the same issues as the Solar & Galactic Protons, although the energy levels required for ions to have the same effect can be lower. This heavy ion product gives forecasters, operations personnel, and spacecraft designers critical data which will improves the capability to mitigate Single Event Effects (SEEs), Total Ionizing Dose (TID), and biological effects.

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The GOES-R Space Environment In-Situ Suite (SEISS) includes magnetic energetic ion sensors for both low and high energy levels. The low energy product gives the flux of low energy electrons and protons in the Magnetosphere. The results can be used to determine the degree of spacecraft charging experienced by GOES-R. Spacecraft charging can cause arcing to occur between differentially charged surfaces on a spacecraft or to the surrounding plasma. These discharges can damage or destroy critical hardware. Numerous satellites have experienced anomalies or failure due to this effect.

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The GOES-R Space Environment In-Situ Suite (SEISS) includes magnetic energetic ion sensors for both low and high energy levels. One of the space weather alerts issued by NOAA’s Space Weather Prediction Center (SWPC) will depend upon this product in the GOES-R Series era. These electrons are very penetrating, and can cause electrical breakdown and discharges of materials deep inside of equipment (Deep Dielectric Charging). They can also adversely affect high frequency radio transmissions and therefore GPS navigation.


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The GOES-R Series Space Environment In-Situ Suite (SEISS) includes a sensor that measures solar and galactic protons present within the Earth’s magnetosphere. This product will form the basis for SWPC’s Solar Radiation Storm Warnings. Humans exposed to large fluxes of these particles (astronauts, passengers/crews on high flying planes) can suffer biological effects. The storms can also cause blackouts of High Frequency (HF) radio communication near the poles. The resulting last-minute rerouting of transportation can have substantial economic impacts.

These particles also cause Single Event Effects (SEEs) which can have either temporary or permanent effects on satellites and instruments. The Total Ionizing Dose (TID) of these particles which equipment is subjected to also degrades performance and can reduce lifetime. Understanding the environment permits selection of parts and shielding to permit satellites to fulfill their mission.


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