Climate & weather

Ships of Opportunity - Air-sea fluxes - Meteorological and sea surface temperature - Real time

Enhancement of Measurements on Ships of Opportunity (SOOP)-Air Sea Flux sub-facility collects underway meteorological and oceanographic observations during scientific and Antarctic resupply voyages in the oceans adjacent to Australia. Data product is quality controlled observations. Research Vessel Real Time Air-Sea Fluxes, equips the Marine National Facility (MNF) (Research Vessels Southern Surveyor and Investigator), the Australian Antarctic Division (Research and Supply Vessels Aurora Australis and Nuyina), and Research Vessel Tangaroa with "climate quality" meteorological measurement systems, capable of providing high...

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

Data coverage

Enhancement of Measurements on Ships of Opportunity (SOOP)-Air Sea Flux sub-facility collects underway meteorological and oceanographic observations during scientific and Antarctic resupply voyages in the oceans adjacent to Australia. Data product is quality controlled observations. Research Vessel Real Time Air-Sea Fluxes, equips the Marine National Facility (MNF) (Research Vessels Southern Surveyor and Investigator), the Australian Antarctic Division (Research and Supply Vessels Aurora Australis and Nuyina), and Research Vessel Tangaroa with "climate quality" meteorological measurement systems, capable of providing high quality air-sea flux measurements and delivered to researchers on a near real-time basis. Obtaining the full set of air-sea fluxes essential for climate studies requires observations of: wind, air and sea temperature, humidity, pressure, precipitation, long- and short-wave radiation. The existing ship meteorological sensor sets are completed with IMOS instruments and a comprehensive annual calibration program implemented. Data streams are fed into existing ship data management systems, and broadcast via satellite back to Australia routinely. The observations are quality controlled at the Bureau of Meteorology. A daily file of 1-minute averages of the observations are generated shortly after 0000UTC and provided to IMOS.

Access & permitted use

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

http://creativecommons.org/licenses/by/4.0/

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