{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Argo Canada BGC Quality Control"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# import package\n",
"import bgcArgoDMQC as bgc\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Oxygen DMQC\n",
"\n",
"For delayed mode quality control, we need to (1) visually inspect the data as a DMQC operator and (2) compute a gain by comparing the data to a reference source, typically WOA, NCEP, or ERA5 data. For both of these tasks, we will load the data via the [synthetic profile file](https://archimer.ifremer.fr/doc/00445/55637/). `bgcArgoDMQC` can load these files given a WMO number, and has functions for visualizing and performing QC on the data within."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\GordonC\\Documents\\projects\\bgcArgoDMQC\\bgcArgoDMQC\\unit.py:36: RuntimeWarning: invalid value encountered in log\n",
" Ts = np.log((298.15 - T)/(273.15 + T))\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# define a WMO number you want to look at\n",
"wmo = 4900869\n",
"# load into a synthetic profile object\n",
"syn = bgc.sprof(wmo)\n",
"# look at the current state of QC flags for T, S, and DO\n",
"g1 = syn.plot(kind='qcprofiles', varlist=['TEMP', 'PSAL', 'DOXY'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see above that most T/S points are good, with a few obvious outliers in red. THe oxygen data also look all good. This is an old float, but for current floats the QC flag for unadjusted oxygen should be 3 (probably bad). If we want to see just good data (QC flags of 1, 2, 5, 8) so that the scale on the salinity plot isn't so bad, we can run:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# get rid of bad flags\n",
"syn.clean()\n",
"# re-make above plot\n",
"g2 = syn.plot(kind='qcprofiles', varlist=['TEMP', 'PSAL', 'DOXY'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As a QC operator it would be out job to set the flags for `DOXY` to 3 in the D-mode file. Since none of the \"good\" points look wrong (note - its hard to tell in a big cloud of points like this, I usually look at profiles indiviually but that would be overkill in this notebook), our visual inspection is done and we can calulate the gain. Since this is an older float, there are no in-air measurements made by the optode. Therefore we will calcualte the gain by comparing surface values to WOA data."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Extracting WOA data for Jan\n",
"Extracting WOA data for Feb\n",
"Extracting WOA data for Mar\n",
"Extracting WOA data for Apr\n",
"Extracting WOA data for May\n",
"Extracting WOA data for Jun\n",
"Extracting WOA data for Jul\n",
"Extracting WOA data for Aug\n",
"Extracting WOA data for Sep\n",
"Extracting WOA data for Oct\n",
"Extracting WOA data for Nov\n",
"Extracting WOA data for Dec\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"Bounding climatological profile(s) missing data - taking simple average of available data.\n",
"\n",
"Calculating gains using WOA surface data and float O2 percent saturation...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\Users\\GordonC\\Documents\\projects\\bgcArgoDMQC\\bgcArgoDMQC\\interp\\interp.py:207: RuntimeWarning: Mean of empty slice\n",
" woa_interp[:,i] = np.nanmean(np.nanmean(D3, axis=2), axis=1)\n",
"c:\\Users\\GordonC\\Documents\\projects\\bgcArgoDMQC\\bgcArgoDMQC\\core\\core.py:1005: RuntimeWarning: Mean of empty slice\n",
" mean_float_data[i,2] = np.nanmean(subset_o2sat)\n",
"c:\\ProgramData\\Anaconda3\\envs\\py39\\lib\\site-packages\\numpy\\lib\\nanfunctions.py:1670: RuntimeWarning: Degrees of freedom <= 0 for slice.\n",
" var = nanvar(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n"
]
}
],
"source": [
"# calculate the gains\n",
"gains = syn.calc_gains(ref='WOA')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The `ref` keyword argument sets the reference dataset. In this case we set it to WOA data. By default `ref` is set to `'NCEP'`, but in this case that would return all `NaN` values since there is no in-air data for this float.\n",
"\n",
"We can also visualize the gains in a single line:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# plot gains over time, show source data\n",
"g3 = syn.plot('gain', ref='WOA')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I find this plot particularly useful, as sometimes it is a good indicator to go back and inspect certain profiles. We see a couple large spikes in the suface float data. Are those spikes real, or should we go back and have a closer look at those profiles? This could change our mean gain a little, and perhaps we would flag some data as bad that we didn't notice before."
]
}
],
"metadata": {
"interpreter": {
"hash": "8571e7f3e92f6e490cddd84ef78d4e4e0b96a1f565959148b10a39523fba88f5"
},
"kernelspec": {
"display_name": "Python 3.9.7 ('py39')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.7"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}