The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of
ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than
optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of
ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than
optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of
ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than
optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. The sensor spatial resolution is 300m. The CONUS images use a 50m land mask, while the Alaska product uses a less refined 500m land mask. The temporal resolution depends on the sensor and date with best coverage since 2018, as images utilize sensors on two Sentinel-3 satellites.

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of
ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than
optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of
ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than
optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. The sensor spatial resolution is 300m. The CONUS images use a 50m land mask, while the Alaska product uses a less refined 500m land mask. The temporal resolution depends on the sensor and date with best coverage since 2018, as images utilize sensors on two Sentinel-3 satellites.

Cyanobacteria Assessment Network (CyAN) is a multi-agency project among EPA, the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the United States Geological Survey (USGS) to support the environmental management and public use of U.S. lakes and estuaries by providing a capability of detecting and quantifying cyanobacteria algal blooms. The sensor spatial resolution is 300m. The CONUS images use a 50m land mask, while the Alaska product uses a less refined 500m land mask. The temporal resolution depends on the sensor and date with best coverage since 2018, as images utilize sensors on two Sentinel-3 satellites.

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of
ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than
optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

This dataset provides instantaneous sea-ice velocity on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.