26 Jan 2023
 | 26 Jan 2023
Status: this preprint is open for discussion.

A new high-resolution Coastal Ice-Ocean Prediction System for the East Coast of Canada

Jean-Philippe Paquin, François Roy, Gregory C. Smith, Sarah MacDermid, Ji Lei, Frédéric Dupont, Youyu Lu, Stephanne Taylor, Simon St-Onge-Drouin, Hauke Blanken, Michael Dunphy, and Nancy Soontiens

Abstract. This paper describes the Coastal Ice Ocean Prediction System for the East Coast of Canada (CIOPS-E) running operationally at Environment and Climate Change Canada (ECCC). CIOPS-E uses a one-way downscaling technique on a 1/36° horizontal grid (~2 km) to simulate high-resolution ice and ocean conditions over the northwest Atlantic Ocean and the Gulf of St. Lawrence (GSL). CIOPS-E is forced at its lateral boundaries with ECCC’s Regional Ice-Ocean Prediction System (RIOPS) and tidal conditions from the Oregon State University TPXO model. The three-dimensional temperature and salinity fields are spectrally nudged towards the RIOPS solution offshore of the 1500 m isobath to, effectively constrain mesoscale features in the Gulf Stream area. Over the continental shelf and the GSL, the CIOPS-E solution is free to develop fully according to model dynamics.

CIOPS-E is evaluated over one year from March 2019 to February 2020. Overall, the CIOPS-E improves the representation of tides compared to ECCC’s lower resolution systems: RIOPS (1/12°) and the Regional Marine Prediction System – Gulf of St. Lawrence (RMPS-GSL, 5 km). The accuracy of the tides are comparable to the TPXO at most coastal tide gauges. Sub-tidal water levels from CIOPS-E agree well with the observed seasonal variability and show improved errors statistics at all stations compared to RIOPS and RMPS-GSL. Improvements are especially noted for the GSL.

Sea surface temperatures (SSTs) from CIOPS-E are lower (higher) in spring (fall) over most of the GSL compared to satellite-derived analyses and RIOPS. Comparison with in-situ observations of SST show significant improvement in CIOPS-E with respect to the RMPS-GSL. Lastly, sea ice conditions in the GSL are compared with the Canadian Ice Service (CIS) charts and the RMPS-GSL model. The sea ice cover and thickness from the pseudo-analysis component (without data assimilation) shows an overestimation compared to the CIS estimates, which is subsequently corrected in the forecast phase through the direct insertion of a Radarsat image analysis product.

Jean-Philippe Paquin et al.

Status: open (until 23 Apr 2023)

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Jean-Philippe Paquin et al.

Jean-Philippe Paquin et al.


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Short summary
This paper present the Coastal Ice-Ocean Prediction System implemented operationally at Environment and climate change Canada. The objective is to enhance the numerical guidance in coastal areas to support electronic navigation and response to environmental emergencies in the aquatic environment. Model evaluation against observations shows improvements for most surface ocean variables in the coastal system compared to current coarser-resolution operational systems.