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.

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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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The ice thickness and age products will be produced for each pixel observed by the GOES-R ABI and covered with ice. There are no direct ABI channels related to the algorithm which actually relies on some other retrieved products from ABI and parameterization schemes such as cloud mask and ice surface temperature that would use some or all ABI channels for their retrievals. The ice thickness and age algorithm uses a one-dimensional thermodynamic ice model (OTIM) which is based on the surface energy balance at thermo-equilibrium and contains all components of the surface energy budget to estimate sea and lake ice thickness up to three meters. An estimate of the ice age is then based on the retrieval of ice thickness. The sea and lake ice age product will help climate forecasters monitor short and long term changes in sea and lake ice.

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The ice cover and concentration algorithm is responsible for the determination of all ABI pixels covered with ice, and estimation of ice concentration under clear conditions. Ice cover identifies if an ABI pixel is covered by ice and ice concentration reports the ratio of water surface covered by ice as a fraction (in tenths) of the area being considered. Total concentration includes all ice types that are present. The result of the ice cover algorithm is an ice "mask." Sea and lake ice influences the surface radiation budget, and affects the exchange of energy and moisture between the atmosphere and the underlying water. It is one of the key factors to consider in the atmospheric circulation, numerical weather forecasting, and climate models. Ice cover is also important for planning commercial transport. Ice cover and concentration are among the most important indices to study climate change. Accurate retrievals of ice cover and concentration are of high importance both to the scientific communities and to the public.

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The GOES-R Series ABI tracks the location of sea and lake ice against time, estimating the motion of sea and lake ice pixels for all clear and non-land ABI pixels. The sea and lake ice motion product will aid the shipping industry by providing valuable information on motion of potentially damaging sea and lake ice.

Land surface albedo (LSA) is defined as the ratio between outgoing and incoming irradiance at the earth surface. The LSA is a shortwave broadband blue-sky albedo over wavelengths between 0.4 and 3.0 µm. As the key component of surface energy budget, LSA can be used to drive/calibrate/validate climatic, mesoscale atmospheric, hydrological, and land surface models. Variation of LSA is also an important indicator of land cover and land use change. Analysis of long-term reliable albedo products will help better understand the human dimension of climate change and how the vegetation-albedo-climate feedbacks work. LSA is one of the Essential Climate Variables (ECVs) by the Global Climate Observing System (GCOS) of the World Meteorological Organization (WMO). The frequent temporal refresh rate, fine spectral resolution, and large spatial coverage make the Advanced Baseline Imager (ABI) a unique data source for mapping LSA.

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The land surface bidirectional reflectance factor (BRF), also referred to as surface reflectance (SR), is a ratio between outgoing radiance at one given direction and incoming radiance at another given direction (same or different from the incoming direction). BRF is produced at the following wavelengths: 0.47 µm, 0.64 µm, 0.86 µm, 1.61 µm, and 2.26 µm. The land surface bidirectional reflectance factor is a byproduct of the land surface albedo algorithm. BRF is used to create the GOES-R fractional snow cover product and for vegetation monitoring.

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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.

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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.

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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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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.

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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.

The aerosol particle size product will be derived for every clear pixel using the retrieved aerosol optical depth product and two pairs of ABI spectral bands in the visible and near-infrared spectrum. By comparing the reflectances of the different wavelengths, various aerosol properties including size can be calculated. The Ångström exponent, which describes the wavelength dependence of aerosol optical depth, is used as a proxy for aerosol particle size. Larger values of the Ångström exponent indicate smaller size particles and vice versa.

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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 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.

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 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 algoFlegacyrithm 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.

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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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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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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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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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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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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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