Authors / CoAuthors
Huang, Z.
Abstract
<p>The dataset measures the long-term seasonal variations of the sea surface temperature (SST) of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly SST images between July 2002 and December 2017 are used to calculate the standard deviations of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is Celsius degree. <p>This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.
Product Type
dataset
eCat Id
115323
Contact for the resource
Author
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Resource provider
Cnr Jerrabomberra Ave and Hindmarsh Dr GPO Box 378
Canberra
ACT
2601
Australia
Digital Object Identifier
Keywords
- ( Feature type )
-
- SST
- ( Instrument )
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- MODIS
- Australian and New Zealand Standard Research Classification: Fields of Research
-
- Earth Sciences
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- National Environmental Science Program
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- Marine Biodiversity Hub
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- Published_External
Publication Date
2018-01-04T00:54:05
Creation Date
2017-11-28T00:00:00
Security Constraints
Legal Constraints
Status
Purpose
Maintenance Information
asNeeded
Topic Category
oceans
Series Information
Lineage
The daily MODIS Aqua SST images processed to Level 2 were obtained from the Integrated Marine Observing System (IMOS; http://imos.org.au/) remote sensing facility. The SST algorithm used is the the Ocean Biology Process Group (OBPG) daytime long-wave algorithm (Franz 2006), which is based on MODIS band 31 (11µm) and band 32 (12μm). The monthly SST images were generated by mosaicking the daily SST images, where the overlapping locations have average values of the overlapping cells. The seasonal standard deviations were then calculated from the monthly images of the corresponding seasons between July 2002 and December 2017. For example, the winter standard deviation was obtained from all June, July and August images. The spring standard deviation was obtained from all September, October and November images. The summer standard deviation was obtained from all December, January and February images. The autumn standard deviation was obtained from all March, April and May images.
Parent Information
Extents
[-60, 10, 80, 180]
Reference System
Spatial Resolution
0.01 dd
Service Information
Associations
Source Information