Your access to IMOS National Reference Station Mooring data discovery and exploration is through the Australian Ocean Data Network (AODN) Portal.

The National Reference Station Network was designed to provide a framework for integrating both the national and regional components of the observing system. National components include integration of long-term time series of observations more spatially distributed and intensive short –term studies, establishing a coastal information infrastructure through development of national data standards and providing calibration and validation of coastal remote sensing.

On the regional scale the National Reference Stations provide focal points around which regional integrations can occur with other facilities including regional moorings, ocean gliders, AUVs, ocean radar, animal tracking and sensor networks.

The frequency of sampling at each site provides the opportunity for analysis at all temporal scales. Daily or weekly events which would not be detected by monthly samples can be studied, such as tides, respiration over daily cycles, diurnal migrations of the plankton and stratification of the water column. On larger temporal scales, events, which had the potential to be missed with single samples per month, can also be detected. Bias for low sampling in bad weather can be overcome, and events associated with bad weather, such as re‐suspension of sediments and episodic events can be sampled. An example of an episodic event was capture by the salinity and turbidity sensors at the North Stradbroke Island NRS during large scale flooding events in 2010-11 (van den Honert RC, McAneney,2011)). As freshwater carrying flood debris and sediments moved out of coastal catchments, the stations 20 m CTD sensor detected an increased variability in surface salinity (see figure 1), while the sensor deployed near the sea floor detected an increase in turbidity.

Time-series of salinity (A) and turbidity (B) measurements collected at the North Stradbroke Island station during a flood. The event was related to a controlled release of water from a large dam following rain across an already saturated catchment, which commenced on the 1st January 2011 (1), and continued to the10th. Peak rainfall occurred on the 7th (2), and water released from the dam late on the 11th (23:30) (3). Major flooding occurred across Brisbane city from the 12–14th (4), and peak turbidity of the plume disgorging to NRS NSI, which is , 41km distant from the river mouth, was observed on the 16th (5) (Lynch et al., 2014).

Important ecosystem relationships and changes that are missed with monthly, seasonal or annual sampling can be resolved. This is particularly important for coastal systems that can be highly influenced by catchment events such as floods causing sediment plumes. Events are particularly important for plankton, which have lifecycles of weeks to months. Frequent sampling is thus needed to obtain the timing of peak abundance and avoid aliasing of the signal. Phytoplankton blooms, upwelling events and eddies can all occur at rates that make them unlikely to be detected by a single monthly sample (see figure 2).

Time series of chlorophyll measured by the combined flourometer and turbidity sensor deployed at the Maria Island station during a December 2009 bloom event (Lynch et al. 2014)

Data processing and Quality Control

For many of the parameters collected by the NRS, quality control processes and data standards are needed.

Quality control comparison of (A) salinity at 20 m, measured by the moored CTD sensor (continuous red line) and the monthly bottle sampling program (closed black circles) and (B) water temperature at 20 m measured by the moored CTD sensor (continuous red line), the monthly sampling program (closed black circles), and from a gridded and interpolated satellite sea surface temperature product (blue line) at the Maria Island station (Lynch et al 2014)

The program has invested substantial time and effort into developing methodological tools for integrated biogeochemical sampling systems, methods for extracting and processing profiling sensor data and general data quality control standards for high frequency data. Documents related to quality control and sampling procedures can be found in the documentation page in the main National Mooring Network webpage.

In addition, as part of the broader ANMN facility a Matlab Toolbox ( ) was developed in conjunction with eMII that allows for parsing of data from a wide variety of instruments and basic quality control of data streams.


van den Honert RC, McAneney J (2011) The 2011 Brisbane floods: causes, impacts and implications.

Water. 3: 1149–1173. doi: 10.3390/w3041149.

Lynch, T, Morello, E, Evans, K, Richardson, A, Steinberg, C, Roughan, M, Thompson, P, Middleton, J, Feng, M, Brando, V, Tilbrook, B, Ridgway, K, Allen, S, Doherty, P, Hill, K, Moltmann, T 2014, IMOS National Reference Stations: a continental scaled physical, chemical and biological coastal observing system, PLoS One, vol. 9, no. 12, e113652, doi:10.1371/journal.pone.0113652