The ocean/overflow test group induces a density current flowing down a continental slope and is documented in Petersen et al. 2015.

The domain is periodic on the zonal boundaries and solid on the meridional boundaries. Salinity is constant throughout the domain (at 35 PSU). The initial temperature is bimodal with low temperature throughout the continental shelf region of 10 deg C and high temperature over the slope and deep ocean of 20 deg C. This perturbation initiates slumping of the cold, denser water mass and flow down the slope as a bottom boundary current.


By default, the sigma coordinate is used. There appears to be an implementation error for other vertical coordinate options. For the default test case, the horizontal resolution is 10 km. For the RPE test case, the horizontal resolution is 2 km.

The test group includes 2 test cases. All test cases have 2 steps, initial_state, which defines the mesh and initial conditions for the model, and forward, which performs time integration of the model. For the RPE test, there is an additional analysis step which computes the RPE through time in relation to the initial RPE and visualizes vertical cross-sections through the center of the domain.

config options

All 3 test cases share the same set of config options:

# Options related to the overflow case

# The width of the domain in the across-slope dimension (km)
width = 40

# The length of the domain in the along-slope dimension (km)
length = 200

# Viscosity values to test for rpe test case
viscosities = 1, 5, 10, 100, 1000


ocean/overflow/default is the default version of the overflow test case for a short (12 min) test run and validation of prognostic variables for regression testing.


Since mixing is a strong function of horizontal viscosity, this test case ocean/overflow/rpe_test performs 40-hour integrations of the model forward in time at 5 different values of the viscosity (with steps named rpe_test_1_nu_1, rpe_test_2_nu_5, etc.). Results of these tests have been used to evaluate spurious dissipation in relation to different models and vertical grid choices (Petersen et al. 2015).