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Nemo-Nordic 1.0: a NEMO-based ocean model for the Baltic and North seas – research and operational applications.

Authors :
Hordoir, Robinson
Axell, Lars
Höglund, Anders
Dieterich, Christian
Fransner, Filippa
Gröger, Matthias
Liu, Ye
Pemberton, Per
Schimanke, Semjon
Andersson, Helen
Ljungemyr, Patrik
Nygren, Petter
Falahat, Saeed
Nord, Adam
Jönsson, Anette
Lake, Iréne
Döös, Kristofer
Hieronymus, Magnus
Dietze, Heiner
Löptien, Ulrike
Source :
Geoscientific Model Development; 2019, Vol. 12 Issue 1, p363-386, 24p
Publication Year :
2019

Abstract

We present Nemo-Nordic, a Baltic and North Sea model based on the NEMO ocean engine. Surrounded by highly industrialized countries, the Baltic and North seas and their assets associated with shipping, fishing and tourism are vulnerable to anthropogenic pressure and climate change. Ocean models providing reliable forecasts and enabling climatic studies are important tools for the shipping infrastructure and to get a better understanding of the effects of climate change on the marine ecosystems. Nemo-Nordic is intended to be a tool for both short-term and long-term simulations and to be used for ocean forecasting as well as process and climatic studies. Here, the scientific and technical choices within Nemo-Nordic are introduced, and the reasons behind the design of the model and its domain and the inclusion of the two seas are explained. The model's ability to represent barotropic and baroclinic dynamics, as well as the vertical structure of the water column, is presented. Biases are shown and discussed. The short-term capabilities of the model are presented, especially its capabilities to represent sea level on an hourly timescale with a high degree of accuracy. We also show that the model can represent longer timescales, with a focus on the major Baltic inflows and the variability in deep-water salinity in the Baltic Sea. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1991959X
Volume :
12
Issue :
1
Database :
Complementary Index
Journal :
Geoscientific Model Development
Publication Type :
Academic Journal
Accession number :
134618277
Full Text :
https://doi.org/10.5194/gmd-12-363-2019