Arctic and N-Atlantic High-Resolution Ocean and Sea-Ice Model
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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Geosci. Model Dev. Discuss., 8, 1–52, 2015 www.geosci-model-dev-discuss.net/8/1/2015/ doi:10.5194/gmdd-8-1-2015 GMDD © Author(s) 2015. CC Attribution 3.0 License. 8, 1–52, 2015 This discussion paper is/has been under review for the journal Geoscientific Model Arctic and N-Atlantic Development (GMD). Please refer to the corresponding final paper in GMD if available. high-resolution ocean and sea-ice A high-resolution ocean and sea-ice model modelling system for the Arctic and North F. Dupont et al. Atlantic Oceans Title Page 1 3 4 3 2 2 F. Dupont , S. Higginson , R. Bourdallé-Badie , Y. Lu , F. Roy , G. C. Smith , Abstract Introduction J.-F. Lemieux2, G. Garric4, and F. Davidson5 Conclusions References 1MSC, Environment Canada, Dorval, QC, Canada 2MRD, Environment Canada, Dorval, QC, Canada Tables Figures 3Bedford Institute of Oceanography, Fisheries & Oceans Canada, Dartmouth, NS, Canada 4 Mercator-Océan, Toulouse, France J I 5Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, St. John’s, NF, Canada J I Received: 18 November 2014 – Accepted: 5 December 2014 – Published: 5 January 2015 Back Close Correspondence to: F. Dupont ([email protected]) Full Screen / Esc Published by Copernicus Publications on behalf of the European Geosciences Union. Printer-friendly Version Interactive Discussion 1 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Abstract GMDD As part of the CONCEPTS (Canadian Operational Network of Coupled Environmental PredicTion Systems) initiative, The Government of Canada is developing a high res- 8, 1–52, 2015 olution (1=12◦) ice–ocean regional model covering the North Atlantic and the Arctic 5 oceans. The objective is to provide Canada with short-term ice–ocean predictions and Arctic and N-Atlantic hazard warnings in ice infested regions. To evaluate the modelling component (as op- high-resolution posed to the analysis – or data-assimilation – component), a series of hindcasts for ocean and sea-ice the period 2003–2009 is carried out, forced at the surface by the Canadian Global Re- model Forecasts. These hindcasts test how the model represent upper ocean characteristics 10 and ice cover. Each hindcast implements a new aspect of the modelling or the ice– F. Dupont et al. ocean coupling. Notably, the coupling to the multi-category ice model CICE is tested. The hindcast solutions are then assessed using a validation package under develop- ment, including in-situ and satellite ice and ocean observations. The conclusions are: Title Page (1) the model reproduces reasonably well the time mean, variance and skewness of Abstract Introduction 15 sea surface height. (2) The model biases in temperature and salinity show that while the mean properties follow expectations, the Pacific Water signature in the Beaufort Conclusions References Sea is weaker than observed. (3) However, the modelled freshwater content of the Tables Figures Arctic agrees well with observational estimates. (4) The distribution and volume of the sea ice is shown to be improved in the latest hindcast thanks to modifications to the J I 20 drag coefficients and to some degree as well to the ice thickness distribution available in CICE. (5) On the other hand, the model overestimates the ice drift and ice thickness J I in the Beaufort Gyre. Back Close Full Screen / Esc 1 Introduction Printer-friendly Version The CONCEPTS (Canadian Operational Network of Coupled Environmental Predic- Interactive Discussion 25 Tion Systems) initiative has fostered collaborations between different federal depart- ments (Fisheries and Oceans Canada, Environment Canada and the Department of 2 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | National Defence) that yielded the development of several operational prediction sys- tems. These include a coupled (atmosphere–ice–ocean) Gulf of Saint-Lawrence sys- GMDD tem (officially operational since June 2011, Smith et al., 2012), the Global Ice–Ocean 8, 1–52, 2015 Prediction System (GIOPS, run in real-time since March 2014, Smith et al., 2014b), 5 a Great Lakes coupled system (still in development, Dupont et al., 2012), a regional ice-only prediction system (run in real-time since July 2013, Lemieux et al., 2014) and Arctic and N-Atlantic a regional Arctic-North Atlantic ice–ocean system based on the CREG12 (Canadian high-resolution REGional) configuration with a nominal horizontal resolution of 1=12◦. The latter is the ocean and sea-ice focus of this paper. The GIOPS, Great Lakes and CREG12-based systems are based model 10 on NEMO (Nucleus for European Modelling of the Ocean, http://www.nemo-ocean.eu), while the coupled Gulf of Saint-Lawrence system is transitioning to NEMO for the ice– F. Dupont et al. ocean component. The development of these systems has benefited greatly from a col- laboration with Mercator-Océan in France. Title Page The goal of the regional system based on CREG12 is to provide Canada with short- 15 term ice–ocean predictions and analyses covering parts of the North Atlantic and whole Abstract Introduction Arctic oceans at high resolution. For this purpose, the regional system will eventually Conclusions References be coupled to the regional weather prediction system and wave prediction system of Environment Canada. The coupled system is expected to improve regional weather Tables Figures and marine forecasting services such as issuing bulletins and warnings in ice infested 20 waters for navigation, energy-exploration and northern communities requirements. As J I such, the system development has benefited from financial support from the Canadian METAREA program and the Beaufort Regional Environmental Assessment (BREA) J I 1 project. However, before the full system (analysis + forecast) can be approved for op- Back Close erational use, we need to understand how to use the forecasting component to its full Full Screen / Esc 25 potential, following the best practices of the community running at comparable resolu- tions. Hence, a series of incremental hindcasts was performed using the forecasting Printer-friendly Version component, each implementing and testing a different aspect of ocean–ice modelling. Interactive Discussion 1The analysis covers the data-assimilation aspect of any prediction system. 3 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | These hindcasts are not long enough to test the full robustness of the model in pre- serving observed water and ice properties at climatic scales (i.e. several decades), as GMDD the initial conditions still imprint the model state after 8 years. Nevertheless, discrep- 8, 1–52, 2015 ancies between atmospheric forcing products and differences in upper-ocean and ice 5 physics are sufficient to create diverging upper-ocean and ice states and variabilities in this short period, that are worth investigating. Moreover, recent satellite missions and Arctic and N-Atlantic extensive and automotized observing in-situ programs (ARGO floats and ice-tethered high-resolution profilers to cite a few) create a wealth of data covering the hindcast period, which we ocean and sea-ice take advantage of in our validation approach. We are therefore testing the mean state model 10 of the model using a few variables, sometimes focusing on some integrated indices over time, or more extensively mapping the model-observation discrepancy in space F. Dupont et al. and time. In this contribution, we describe the model components and the validation strategy, Title Page along with results of the validation of the latest hindcast. The objective is to present to 15 the community the progress made and challenges met in developing a high resolution Abstract Introduction modelling system for the Arctic-Atlantic oceans, in the spirit of Megann et al.(2014). In Conclusions References assessing the performance of the latest hindcast in terms of ice properties (concentra- tion, thickness and velocity), we include comparison with an intermediate hindcast and Tables Figures the 1=12◦ resolution equivalent global simulation ORCA12-T321 of Mercator-Océan. 20 More precisely, Sect. 2 is divided into the description of the model (domain, model J I components and parameters; Sect. 2.1), the input bathymetry and other initial and boundary conditions (Sect. 2.2), and the description of the validation package (Sect. 2.3). J I Section 3 provides details of the hindcast simulations (Sect. 3.1), then describes the Back Close simulation results in terms of the statistics of the sea surface height, the hydrography Full Screen / Esc 25 and the general circulation (Sect. 3.2) and in terms of sea-ice metrics (concentration, thickness, volume and drift; Sect. 3.3). Section 4 concludes. Printer-friendly Version Interactive Discussion 4 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 Model setup, input data and validation package GMDD 2.1 Model description 8, 1–52, 2015 2.1.1 Domain configuration Arctic and N-Atlantic The global ORCA12 domain (ORCA family grid at a nominal horizontal resolution of ◦ high-resolution 5 1=12 in both longitudinal and latitudinal directions, Drakkar Group, 2007) is used to ocean and sea-ice derive a seamless (i.e., the “north-fold” discontinuity of the global grid is removed) re- model gional domain covering the whole Arctic Ocean and parts of the North Atlantic down ◦ to 27 N. The horizontal grid consists of 1580 × 1817 points on which resolution varies F. Dupont et al. from 8 km at the open boundary in the Atlantic Ocean to an average of 5 km in the Arc- 10 tic, and down to slightly below 2 km in some of the southern channels of the Canadian Arctic Archipelago (Fig.1). Title Page The spatial variation of the first Rossby radius of deformation is shown in Fig.2a. From about 40 km along the southern Atlantic boundary down to a few kilometers in Abstract Introduction the Labrador Sea, the Greenland, Iceland and Norwegian (GIN) seas and continental Conclusions References 15 shelves, the radius starts re-increasing in the deep Arctic Ocean to above 10 km.