Aerosol Detection (including smoke and dust)
  • “The Aerosol Detection product uses several spectral bands made available on the GOES-16 satellite imager. The algorithm uses 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 are critical factors in visibility and air quality forecasts. In addition to short-term prediction, this product also enables better monitoring of the long-term trends in aerosol quantities and distribution throughout the atmosphere.”
GOES-16 aerosol detection product from April 27, 2017.
Credit: GOES R
Aerosol Optical Depth
  • “The Aerosol Optical Depth (AOD) product utilizes 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 of the Earth. 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 provides valuable data to be included in climate models and help climate scientists monitor and predict climate change.”
Aerosol Optical Depth Product over the US northern Plains states from August 11-12, 2018.
​Credit: CIMMS
Clear Sky Masks
  • “The Clear Sky Mask algorithm takes advantage of the high spatial and temporal resolution of the GOES-16 ABI visible, near-infrared, and infrared bands to automatically produce a cloud classification for each pixel: cloudy, probably cloudy, clear, or probably clear. 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 is used by the NWP community to identify which ABI pixel information should be formatted for use in numerical weather prediction models.”
Clear Sky Mask Product from March 5, 2018.
​Credit: CIMMS
Cloud and Moisture Imagery
  • “The Cloud and Moisture Imagery product will utilize all 16 spectral bands of the GOES-16 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 are used to generate an array of products aiding forecasters in monitoring and predicting all kinds of hazards: weather, oceanographic, and climate-related phenomena.”
GOES-16 Advanced Baseline Imager (ABI) imagery for each of the instrument’s 16 bands on December 18, 2017.
Credit: GOES R
Cloud Optical Depth
  • “Cloud Optical Depth uses both the visible and the near-infrared bands during the daytime and a combination of infrared bands for night-time detection purposes. This product, together with the Cloud Particle Size Distribution product, provides valuable information about the radiative properties of clouds. These two properties act to enhance climate prediction, as they provide global climate models with higher quality data regarding the Earth’s energy and radiation budget.”
GOES-16 cloud optical depth product, January 24, 2018.
Credit: GOES R
Cloud Particle Size Distribution
  • “The Cloud Effective Particle Size is 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-16 Cloud Optical and Microphysical Properties algorithm retrieves, simultaneously with COD, the Cloud Particle Size. The Cloud Particle Size provides valuable information about the radiative properties of clouds. This information combined with the information provided by the COD product provides very accurate information about the Earth’s radiation budget, yielding more accurate climate prediction possibilities.”
GOES-16 cloud particle size distribution product, April 9, 2017.
Credit: GOES R
Cloud Particle Size Distribution Product from over North Dakota on November 6, 2018.
​Credit: CIMMS
Cloud Top Height
  • “The Cloud Top Height algorithm uses 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 products that include the Cloud Layer product, Cloud Optical/Microphysical products, and the Derived Motion Wind products. Forecasters use this information to determine areas of cloud growth and the 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 prediction of clouds in numerical weather prediction models.”
GOES-16 cloud top height (feet) product, February 13, 2018.
Credit: GOES R
Cloud Top Height Product over North Dakota on November 6, 2019.
​Credit: CIMMS
Cloud Top Phase
  • “The Cloud Type algorithm uses four GOES-16 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 products that include Cloud Height, Cloud Optical Properties, Fog Detection/Depth, and Aircraft Icing. The Cloud Top Phase product enables 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 is also used in advanced ABI applications such as severe weather prediction and tropical cyclone intensity estimation.”
GOES-16 cloud top phase product, January 12, 2018.
Credit: GOES R
Cloud Top Phase Product over North Dakota on November 6, 2018.
​Credit: CIMMS
Cloud Top Pressure
  • “The Cloud Top Height algorithm uses 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 products that include the Cloud Layer product, Cloud Optical/Microphysical products, and the Derived Motion Wind products. Forecasters use this information to determine areas of cloud growth and the 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 prediction of clouds in numerical weather prediction models.”
GOES-16 cloud top pressure (hPa) product, February 13, 2018.
Credit: GOES R
Cloud Top Temperature
  • “The Cloud Top Height algorithm uses 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 products that include the Cloud Layer product, Cloud Optical/Microphysical products, and the Derived Motion Wind products. Forecasters use this information to determine areas of cloud growth and the 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 prediction of clouds in numerical weather prediction models.”
GOES-16 cloud top temperature (deg. C) product, February 13, 2018.
Credit: GOES R
Derived Motion Winds
  • “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 which lack localized wind observations that include oceans and Southern Hemisphere land masses. This product provides key wind observations to operational Numerical Weather Prediction (NWP) systems where their use has been demonstrated to improved NWP forecasts including tropical cyclones. In addition, this product provides improved guidance for National Weather Service field forecasters.”
GOES-16 derived motion winds product using ABI Band 14 on November 23, 2017. High level (100-400 hPa) winds are shown in violet; mid-level (400-700 hPa) are shown in cyan; and low levels (below 700 hPa) are shown in yellow.
Credit: GOES R
Derived Motion Winds Product on October 20, 2017.
​Credit: Satellite Liaison Blog
Derived Stability Indices
  • “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) are computed from the retrieved atmospheric moisture and temperature profiles. These indices aid forecasters in nowcasting (i.e., very short-term forecasts of) severe weather by providing them with a plan view of these atmospheric stability parameters. Forecasters 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.”
GOES-16 derived stability indices product from July 1, 2017, including lifted index (upper left), convective available potential energy (upper middle), total totals (upper right), K-index (lower left) and Showalter index (lower middle).
Credit: GOES R
Downward Shortwave Radiation: Surface
  • “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 National Center of Environmental Prediction, NASA Land Data Assimilation Systems, and ocean assimilation models either as an input (providing an 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.”
GOES-16 downward shortwave radiation product, April 30, 2018.
Credit: GOES R
Fire/Hot Spot Characterization
  • “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-16 Series ABI platform. 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 across the contiguous United States.”
GOES-16 active fire product from September 3, 2017. Fire pixels are shown in red.
Credit: GOES R
Hurricane Intensity Estimation
  • “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 provide critical guidance to forecasters at tropical cyclone forecast centers regarding tropical cyclone storm intensity from storm formation, through development and maturation, to dissipation.”
GOES-16 hurricane intensity estimation qualitative analysis for Hurricane Irma in 2017. Left: Irma’s track. Right: GOES-16 hurricane intensity estimates (red line) compared to observed intensity (blue line).
Credit: GOES R
Land Surface Temperature (Skin)
  • “The Land Surface Temperature (LST) product is derived from GOES-16 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.”
GOES-16 land surface temperature product, February 20, 2018.
Credit: GOES R
Land Surface Temperature Product over the Central US states from October 3-4, 2018.
​Credit: Satellite Liaison​ Blog
Legacy Vertical Temperature Profile
  • “The Legacy Vertical Temperature Profile product estimates levels of temperature throughout the troposphere. This product is used by National Weather Service 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.”
GOES-16 legacy vertical temperature profile product, July 1, 2017.
Credit: GOES R
Rainfall Rate / QPE
  • “The ABI Rainfall Rate algorithm generates the baseline Rainfall Rate product from ABI Infrared 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 Infrared 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-16 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.”
GOES-16 rainfall rate product, March 23, 2018.
Credit: GOES R
Reflected Shortwave Radiation: TOA
  • “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.”
GOES-16 reflected shortwave radiation product, April 30, 2018.
Credit: GOES R
Sea Surface Temperature (Skin)
  • “The GOES-16 Series provides forecasters with a Sea Surface Temperature (SST) for each cloud-free pixel over water identified by the Advanced Baseline Imager. 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.”
GOES-16 sea surface temperature product, February 26, 2018.
Credit: GOES R
Snow Cover
  • “The fractional Snow Cover algorithm uses GOES-16 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 National Operational Hydrologic Remote Sensing Center snow model, as well as hydrologic forecasts and warnings, including river and flood forecasts, water management, snowpack monitoring and analysis, and climate studies.”
Example of the snow cover product (right figure) as generated by the GOES-R snow cover algorithm using MODIS data (left image) over the Colorado Rockies on April 30, 2017.
Credit: GOES R
Total Precipitable Water
  • “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, the onset of Gulf of Mexico return flow, and the onset of the Southwest United States monsoon.”
GOES-16 total precipitable water product, July 1, 2017.
Credit: GOES R
Volcanic Ash: Detection and Height
  • “The Volcanic Ash product algorithm utilizes five GOES-16 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.”
GOES-16 false color imagery (upper left), ash confidence (upper right), ash/dust cloud height (lower left), and ash/dust loading (lower right), from February 2, 2018.
Credit: GOES R