Mean Monthly Sea Surface Temperature (°C) for...
HELLOURL: https://pacific-data.sprep.org/system/files/Global_2010-2019_MeanSeaSurfaceTemp_MODIS.zip
This dataset contains rasters and a metadata file for global mean monthly sea surface temperature (°C) from 2010-2019. Rasters are in WGS84 coordinate system (EPSG 4326). Sea surface temperature is the temperature of the top millimeter of the ocean's surface. Sea surface temperatures influence weather, including hurricanes, as well as plant and animal life in the ocean. Like Earth's land surface, sea surface temperatures are warmer near the equator and colder near the poles. Currents like giant rivers move warm and cold water around the world's oceans. Some of these currents flow on the surface, and they are obvious in sea surface temperature images.
Warm ocean waters help form clouds and affect weather patterns. The sea's surface temperature is also correlated to the availability of tiny ocean plants, called phytoplankton. For all of these reasons scientists monitor the sea's surface temperature. These maps show satellite measurements of the sea's surface temperature for a given day, or for a span of days.
NASA standard processing and distribution of the Sea Surface Temperature (SST) products from the MODIS sensors is now performed using software developed by the Ocean Biology Processing Group (OBPG). The OBPG generates Level-2 SST products using the Multi-Sensor Level-1 to Level-2 software (l2gen), which is the same software used to generate MODIS ocean color products. The SST algorithm and quality assessment logic are the responsibility of the MODIS Science Team Leads for SST (currently P. Minnett and R. Evans of the Rosenstiel School of Marine and Atmospheric Science (RSMAS) at the University of Miami). Details of the SST processing implementation within l2gen are provided in this document. The description is valid for both the standard products distributed by the OBPG through the ocean color web and the products delivered to the Physical Oceanography DAAC, where the latter are subsequently repackaged for GHRSST distribution.
An historical discussion on the transition of SST processing from MODAPS/DAAC/RSMAS to OBPG, with comparison of products, is available here. At the time of transition, the OBPG was able to demonstrate exact consistency with the previous products. However, file formatting now follows OBPG conventions.
The Short-wave SST Algorithm makes use of MODIS bands 22 and 23 at 3.959 and 4.050 um. The brightness temperatures are derived from the observed radiances by inversion (in log space) of the radiance versus blackbody temperature relationship. For l2gen, these relationships were precomputed for the spectral response of each MODIS channel, and the tables were then stored in HDF files to be loaded at run-time. In modsst, the radiance versus blackbody temperature relationship was computed at run-time. The algorithm for computing short-wave SST (sst4) from observed brightness temperatures is shown below.
The long-wave SST algorithm makes use of MODIS bands 31 and 32 at 11 amd 12 um. The brightness temperatures are derived from the observed radiances by inversion (in linear space) of the radiance versus blackbody temperature relationship. For l2gen, these relationships were precomputed for the spectral response of each MODIS channel, and the tables were then stored in HDF files to be loaded at run-time. In modsst, the radiance versus blackbody temperature relationship was computed at run-time. The nonlinear SST algorithm was tuned for two different regimes based on brightness temperature difference. The algorithm for computing long-wave SST (sst) from observed brightness temperatures is shown below. Support for the VIIRS mission is currently work in progress.
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Additional Information
| Field | Value |
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| Updated on pacificdata.org | July 21, 2024 |
| Added to pacificdata.org | July 21, 2024 |
| Format | ZIP |
| License | SPREP Public License |
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| Size | 0B |
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