CSIRO Atlas of Regional Seas (CARS)

CARS is a digital climatology, or atlas of seasonal ocean water properties. It comprises gridded fields of mean ocean properties over the period of modern ocean measurement, and average seasonal cycles for that period. It is derived from a quality-controlled archive of all available historical subsurface ocean property measurements - primarily research vessel instrument profiles and autonomous profiling buoys. As data availability has enormously increased in recent years, the CARS mean values are inevitably biased towards the recent ocean state.

A number of global ocean climatologies are presently available, such as NODC's World Ocean Atlas. CARS is different as it employs extra stages of in-house quality control of input data, and uses an adaptive-lengthscale loess mapper to maximise resolution in data-rich regions, and the mapper's "BAR" algorithm takes account of topographic barriers. The result is excellent definition of oceanic structures and accuracy of point values.


spans the southern 2/3 of the world's oceans, from 70S to 26N, except in the Atlantic where is reaches only to 10N. The six water properties mapped in are temperature, salinity, oxygen, nitrate, silicate, phosphate. It comprises historic mean fields and average seasonal cycles, derived from all available historical subsurface ocean property measurements (primarily research vessel instrument casts and autonomous profiling buoys.)

Information for a given year

CARS does not provide information for any given year. CARS is created by averaging/interpolating all available oceanographic cast data, most of which was collected in the last 50 years. Especially when trying to provide an estimate at every location and every depth in the world's oceans, there is not enough data to resolve any one year, so we ignore the year of collection of each observation and retain only the day-of-year - and then fit a mean and mean-seasonal-cycle at each point.

In the Western Equatorial Pacific and the Gulf of Carpentaria we apply corrections for interannual signals, but in general any such signals will effect the maps, both by these signals being aliased into spatial structure or seasonal cycles, and by biasing towards the interannual anomaly of data-rich periods.


The User acknowledges that the Product was developed by CSIRO for its own research purposes. The CSIRO will not therefore be liable for interpretation of or inconsistencies, discrepancies, errors or omissions in any or all of the Product as supplied.

Any use of or reliance by the User on the Product or any part thereof is at the User's own risk and CSIRO shall not be liable for any loss or damage howsoever arising as a result of such use.
The User agrees that whenever the Product or imagery/data derived from the Product are published by the User, the CSIRO Marine Laboratories shall be acknowledged as the source of the Product.

The User agrees to indemnify and hold harmless CSIRO in respect of any loss or damage (including any rights arising from negligence or infringement of third party intellectual property rights) suffered by CSIRO as a result of User's use of or reliance on the Data.


Ridgway K.R., J.R. Dunn, and J.L. Wilkin, Ocean interpolation by four-dimensional least squares -Application to the waters around Australia, J. Atmos. Ocean. Tech., Vol 19, No 9, 1357-1375, 2002

Dunn J.R., and K.R. Ridgway, Mapping ocean properties in regions of complex topography, Deep Sea Research I : Oceanographic Research, 49 (3) (2002) pp. 591-604

Temperature [DegC] (include Argo, no Argo)
Salinity [PSU] (include Argo, no Argo)
oxygen [ml/l]
nitrate [umol/l]
phosphate [umol/l]
silicate [umol/l]
Zonal Global by 0.5 deg
Meridional 70S to 0N by 0.5 deg
Vertical0, 5, 10, 20, 30, 40, 50, 60, 70, 75, 80, 90, 100, 110, 120, 125, 130, 140, 150, 160, 170, 175, 180, 190, 200, 210, 220, 225, 230, 240, 250, 260, 270, 275, 280, 290, 300, 325, 350, 375, 400, 425, 450, 475, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1750, 1800, 1900, 2000, 2250, 2500, 2750, 3000, 3250, 3500, 3750, 4000, 4250, 4500, 4750, 5000, 5500
Volume 1.8 GB
Server public:
Acquired Oct 4, 2017
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