Climate & weather

NOAA/PMEL Ocean Climate Stations Moorings

The mission of the Ocean Climate Stations (OCS) Project is to make meteorological and oceanic measurements from autonomous platforms. Calibrated, quality-controlled, and well-documented climatological measurements are available on the OCS webpage and the OceanSITES Global Data Assembly Centers (GDACs), with near-realtime data available prior to release of the complete, downloaded datasets. OCS measurements served through the Big Data Program come from OCS high-latitude moored buoys located in the Kuroshio Extension (32°N 145°E) and the Gulf of Alaska (50°N 145°W). Initiated in 2004 and 2007, the respective moored buoys, KEO and...

Listed for discovery. Access is provided by the original publisher under its terms.

Data coverage

The mission of the Ocean Climate Stations (OCS) Project is to make meteorological and oceanic measurements from autonomous platforms. Calibrated, quality-controlled, and well-documented climatological measurements are available on the OCS webpage and the OceanSITES Global Data Assembly Centers (GDACs), with near-realtime data available prior to release of the complete, downloaded datasets. OCS measurements served through the Big Data Program come from OCS high-latitude moored buoys located in the Kuroshio Extension (32°N 145°E) and the Gulf of Alaska (50°N 145°W). Initiated in 2004 and 2007, the respective moored buoys, KEO and Papa, measure a suite of surface and subsurface essential ocean variables. The surface suite includes air temperature, relative humidity, shortwave and longwave radiation, barometric pressure, winds, and rain, while subsurface instrumentation includes temperature, salinity, and ocean currents. Individual buoy deployments are stitched together into a continuous time-series, which is synced to the OceanSITES GDACs, and subsequently, to BDP.

Access & permitted use

Review the publisher’s documentation for availability, eligibility and permitted uses, including commercial analysis, model training and redistribution.

NOAA data disseminated through NODD are open to the public and can be used as desired. NOAA makes data openly available to ensure maximum use of our data, and to spur and encourage exploration and innovation throughout the industry. NOAA requests attribution for the use or dissemination of unaltered NOAA data. However, it is not permissible to state or imply endorsement by or affiliation with NOAA. If you modify NOAA data, you may not state or imply that it is original, unaltered NOAA data.

Need help sourcing data?

Tell us your required fields, population, geography and time period. We can review suitable sources and licensing options.

Request sourcing help

Related data sources

Climate and weatherPublic download

NOAA Global Daily Climate Observations

Daily precipitation, temperature, snowfall and other surface observations from the Global Historical Climatology Network across international stations.

NOAA National Centers for Environmental Information
Climate & weatherExternal source; review access terms

(EXPERIMENTAL) NOAA FourCastNet Global Forecast System (FourCastNetGFS) (EXPERIMENTAL)

The FourCastNet Global Forecast System (FourCastNetGFS) is an experimental system set up by the National Centers for Environmental Prediction (NCEP) to produce medium range global forecasts. The model runs on a 0.25 degree latitude-longitude grid (about 28 km) and 13 pressure levels. The model produces forecasts 4 times a day at 00Z, 06Z, 12Z and 18Z cycles. Major atmospheric and surface fields including temperature, wind components, geopotential height, relative humidity and 2 meter temperature and 10 meter winds are available. The products are 6 hourly forecasts up to 10 days. The data format is GRIB2. The FourCastNetGFS...

NOAA
Geospatial dataExternal source; review access terms

10m Annual Land Use Land Cover (9-class)

This dataset, produced by Impact Observatory, Microsoft, and Esri, displays a global map of land use and land cover (LULC) derived from ESA Sentinel-2 imagery at 10 meter resolution for the years 2017 - 2024. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, which used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. Each global map was produced by applying this model to the Sentinel-2 annual scene...

Impact Observatory