CARS 2009 - CSIRO Atlas of Regional Seas - World monthly

Maintenance and Update Frequency: asNeeded Statement: Lineage Source data was ship-based CTD and hydrology casts from CSIRO Marine archives (1985-ongoing), the WOCE GHP, and the NODC July08 update of the World Ocean Database 2005, which was a collation of all possible casts from all countries, from...

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Bibliographic Details
Other Authors: AODN Data Manager (distributor), CSIRO Oceans and Atmosphere - Hobart (custodian), Data Officer (distributor), Integrated Marine Observing System (IMOS) (hasAssociationWith), Ridgway, Ken (hasPrincipalInvestigator), Wijffels, Susan (pointOfContact)
Format: Dataset
Language:unknown
Published: Integrated Marine Observing System
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Online Access:https://researchdata.edu.au/cars-2009-csiro-world-monthly/961126
Description
Summary:Maintenance and Update Frequency: asNeeded Statement: Lineage Source data was ship-based CTD and hydrology casts from CSIRO Marine archives (1985-ongoing), the WOCE GHP, and the NODC July08 update of the World Ocean Database 2005, which was a collation of all possible casts from all countries, from earliest records (1990) to 2008. Also includes smaller datasets from other data centres, and Argo and TAO data. Observed data were interpolated to 79 standard depths, and loess mapped to 1/2 degree grid. Positional accuracy Errors may occur in location of cast data. Interpolation from data of irregular spatial distribution will introduce uncertainty into the value assigned to each location (equivalently, the location assigned to a given value.) Parameter accuracy "map error" is an estimate of the "Standard Error of the Mean" (unlike OI, loess does not provide an error field.) The data source radius (for the mapping at each grid point) is also stored to give some insight into relative accuracy at different locations, and fields of data variance and RMS mapping-residuals are available. Logical consistency report Mapping was optimised to accurately locate horizontal structure and mean values in mapped properties, and to reveal annual and semi-annual signals. Depth layers were only loosely related to adjacent layers, and spatial mapping scales varied between layers. The mapping methods therefore were NOT optimised to resolve vertical structure, although potential temperature inversions in mean and seasonal profiles were substantially suppressed after mapping. Completeness All known reliable published data is used, but this can still be very sparse, especially at depth, and especially for some nutrients. In many places strong interannual signals or eddy noise will be aliased into spatial or seasonal signals, and smoothing can broaden frontal features. Statement: This dataset collection combines the following parameters: temperature, temperature anomaly, salinity, salinity anomaly, dissolved oxygen, nitrate, phosphate ...