Patterns of variability in Sea Surface Temperature (SST) are related to distribution of phytoplankton communities in the surface ocean.
License
Unknown
Data Format
Zarr
Data Format (other)
No response
Access protocol
S3
Source File Organization
A global, gap-free, gridded, daily 1 km Sea Surface Temperature (SST) dataset created by merging multiple Level-2 satellite SST datasets. MUR Level 4 SST dataset in Zarr format. The zarr-v1/ directory contains a zarr store chunked (5, 1799, 3600) along the dimensions (time, lat, lon).
Example URLs
Amazon Resource Name (ARN)
arn:aws:s3:::mur-sst/zarr-v1
AWS Region
us-west-2
AWS CLI Access (No AWS account required)
aws s3 ls --no-sign-request s3://mur-sst/zarr-v1/
Authorization
None
Transformation / Processing
Files are already available in zarr format; data will need to be 'combined' with other parameters to be used for diatom algorithm input.
Target Format
Zarr
Comments
MUR SST from NASA will be one of four parameters concatenated for use as input to a diatom biomass prediction algorithm.
Dataset Name
Multi-Scale Ultra High Resolution (MUR) Sea Surface Temperature (SST)
Dataset URL
https://registry.opendata.aws/mur/#usageexa
Description
Patterns of variability in Sea Surface Temperature (SST) are related to distribution of phytoplankton communities in the surface ocean.
License
Unknown
Data Format
Zarr
Data Format (other)
No response
Access protocol
S3
Source File Organization
A global, gap-free, gridded, daily 1 km Sea Surface Temperature (SST) dataset created by merging multiple Level-2 satellite SST datasets. MUR Level 4 SST dataset in Zarr format. The zarr-v1/ directory contains a zarr store chunked (5, 1799, 3600) along the dimensions (time, lat, lon).
Example URLs
Authorization
None
Transformation / Processing
Files are already available in zarr format; data will need to be 'combined' with other parameters to be used for diatom algorithm input.
Target Format
Zarr
Comments
MUR SST from NASA will be one of four parameters concatenated for use as input to a diatom biomass prediction algorithm.