diff --git a/docs/source/examples/CloseHeatBudget_POP2.ipynb b/docs/source/examples/CloseHeatBudget_POP2.ipynb index 8e87cd3a..657eb07b 100644 --- a/docs/source/examples/CloseHeatBudget_POP2.ipynb +++ b/docs/source/examples/CloseHeatBudget_POP2.ipynb @@ -6,7 +6,7 @@ "source": [ "# Calculate POP2 heat budget using xgcm\n", "\n", - "In this notebook, we are going to use xgcm with metrics to demonstrate budget closure. This notebook was contributed by [Anna-Lena Deppenmeier](https://github.com/ALDepp).\n", + "In this notebook, we are going to use xgcm with metrics to demonstrate budget closure for the 0.1 degree horizontal resolution version of POP2. Note that the lower resolution has more parameterizations and therefore does not close following this notebook. This notebook was contributed by [Anna-Lena Deppenmeier](https://github.com/ALDepp).\n", "\n", "\n", "This is an image of the POP output structure on the horizontal B-grid courtesy of [Yassir Eddebbar](https://github.com/Eddebbar).\n", @@ -747,7 +747,7 @@ "metadata": {}, "source": [ "#### i) Total heat advection\n", - "
We use grid.diff and multiply and divide by the volumes ourselves is the way POP outputs the fluxes. It performs a division by the cell area before saving the terms, which would not be accounted for if we used grid.derivative. Note that we also multiply by dsxgcm.VOL.values and then divide by dsxgcm.VOL. This is due to the same issue, there is a mis-alignment in the grid in this output term that xgcm would not like, and we are getting around it this way. This might be specific to POP and it should likely be possible to use grid.derivative for other models.
" + "We use grid.diff and multiply and divide by the volumes ourselves is the way POP outputs the fluxes. It performs a division by the cell area before saving the terms, which would not be accounted for if we used grid.derivative. Note that we also multiply by dsxgcm.VOL.values and then divide by dsxgcm.VOL. This is due to the same issue, there is a mis-alignment in the grid in this output term that xgcm would not like, and we are getting around it this way. This might be specific to POP and it should likely be possible to use grid.derivative for other models. The variables used here are online accumulated transports as output by the model. If you calculate according to udT/dx etc you will have the transport from the mean fields, and miss the eddy contribution below the timescale of your averaging operator (e.g. monthly for monthly output).
" ] }, {