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<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>
Cross correlating SPT-3G 220 GHz noise properties
</title>
<link rel="stylesheet" href="styles.css">
<!-- MathJax -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML"></script>
<!-- MathJax equation numbering -->
<script type="text/x-mathjax-config">
MathJax.Hub.Config({
TeX: { equationNumbers: { autoNumber: "AMS" } }
});
MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\(','\\)']]}});
</script>
</head>
<body>
<script type="text/javascript" src="scripts/pager.js"></script>
<link rel="stylesheet" type="text/css" href="scripts/pager.css">
<div class="container content">
<main>
<article class="page">
<h1 id='top' class="page-title"> Cross correlating SPT-3G 220 GHz noise properties </h1>
<p class="page-author"> Dylan Mahoney</p>
<p class="page-date"> 8 June 2021 </p>
<h2>Outline and scope</h2>
<p>
This posting presents empirical cross-correlations of the observed 220 GHz noise properties
(here $Q,$U, and $Q/$U) with MERRA-2 variables.
</p>
<hr>
<!-- Fix the table to be accurate !-->
<h2>Correlation inputs </h2>
I've taken a (somewhat physically motivated) subset of the MERRA-2 dataset above the pole
and used as inputs for this study. The full description can be found in <a href='Bosilovich785.pdf'>Bosilovich785.pdf</a>. NOTE: I'll update this table soon to reflect the current variables being used.
<br>
<table>
<tr>
<th>Variable</th>
<th>Description</th>
<th>Dataset</th>
</tr>
<tr>
<td>T</td>
<td>Air temperature, K</td>
<td>inst3_3d_asm_Np</td>
</tr>
<tr>
<td>U</td>
<td>Eastward wind, m/s</td>
<td>inst3_3d_asm_Np</td>
</tr>
<tr>
<td>V</td>
<td>Northward wind, m/s</td>
<td>inst3_3d_asm_Np</td>
</tr>
<tr>
<td>QI</td>
<td>Mass fraction of cloud ice water, kg/kg</td>
<td>inst3_3d_asm_Np</td>
</tr>
<tr>
<td>QL</td>
<td>Mass fraction of cloud liquid water, kg/kg</td>
<td>inst3_3d_asm_Np</td>
</tr>
<tr>
<td>INCLOUDQI</td>
<td>In cloud cloud ice for radiation, kg/kg</td>
<td>tavg3_3d_cld_Np</td>
</tr>
<tr>
<td>CLOUD</td>
<td>Cloud fraction for radiation, 1</td>
<td>tavg3_3d_cld_Np</td>
</tr>
<tr>
<td>TAUCLI</td>
<td>In cloud optical thickness for ice clouds, 1</td>
<td>tavg3_3d_cld_Np</td>
</tr>
<tr>
<td>TAUCLW</td>
<td>In cloud optical thickness for water clouds, 1</td>
<td>tavg3_3d_cld_Np</td>
</tr>
<tr>
<td>TQI</td>
<td>Total precipitable ice water, kg/m^2</td>
<td>inst1_2d_asm_Nx</td>
</tr>
<tr>
<td>TQL</td>
<td>Total precipitable liquid water, kg/m^2</td>
<td>inst1_2d_asm_Nx</td>
</tr>
<tr>
<td>TQV</td>
<td>Total precipitable water vapor, kg/m^2</td>
<td>inst1_2d_asm_Nx</td>
</tr>
<tr>
<td>TROPQ</td>
<td>Tropopause specific humidity using blended TROPP estimate, kg/kg</td>
<td>inst1_2d_asm_Nx</td>
</tr>
<tr>
<td>TROPT</td>
<td>Tropopause temperature using blended TROPP estimate, K</td>
<td>inst1_2d_asm_Nx</td>
</tr>
</table>
Additionally, I've broken up the elevation range according to the temperature profile shown in <a href=https://arxiv.org/abs/1707.08400>https://arxiv.org/abs/1707.08400</a>
into regions that are below, in the middle of, and above the inversion layer.
<br>
<br>
<table>
<tr>
<th>Layer</th>
<th>Minimum elevation</th>
<th>Maximum elevation</th>
</tr>
<tr>
<td>SURFACE</td>
<td>0 m</td>
<td>500 m</td>
</tr>
<tr>
<td>INVERSION</td>
<td>500 m</td>
<td>2000 m</td>
</tr>
<tr>
<td>HIGH</td>
<td>2000 m</td>
<td>∞</td>
</tr>
</table>
<h2>Timestream pager</h2>
<figure>
<img alt="Timestream pager" id="pager_one" src="#"/>
<figcaption>
In this pager we show the cross correlations of the SPT-3G 220 GHz polarized noise data and the MERRA-2 data. Blank plots indicate that no meaningful data could be read from MERRA-2.
</figcaption>
<script type="text/javascript">
pager.link("#pager_one",
{
'MERRA-2 variable|merrakey': ['QI', 'QL', 'QV','T', 'TQI', 'TQL','TQV'],
'SPT variable|sptkey':['T','Q','U','Q/U|QUratio','Q-U'],
'SPT frequency|sptfreq':['220'],
'Minimum ell|lowest_ell':['10','30','70','110'],
'Maximum ell|highest_ell':['150','250','350'],
'Statistical test|stat_test':['Linear Regression|linregress','Spearman','Kolmogorov-Smirnov around median|ks'],
'Time type|tid':['Time-averaged|tavg','Instantaneous|inst','Time-averaged - Instantaneous|delta'],
'Ranks|rank':['True','False'],
'Log(x)|logx':['True','False'],
'Log(y)|logy':['True','False'],
'Abs(x)|absx':['True','False'],
'Plot type|type':['Timestream|time_series', 'Scatter plot|scatter'],
},
function(params) {
var dim;
if (params['merrakey'] == 'QI' | params['merrakey'] == 'QL' | params['merrakey'] == 'QV' | params['merrakey'] == 'T') {
dim = 3
} else {
dim = 2
}
var xLabel = params['merrakey'];
if (dim == 2 & params['tid'] == 'delta') {
xLabel = 'Delta_'+xLabel
}
if (dim == 2 & params['tid'] != 'delta') {
xLabel = params['tid']+'_'+xLabel
}
if (dim == 3 & params['tid'] == 'delta') {
xLabel = "Variance_of_Delta_"+xLabel
}
if (dim == 3 & params['tid'] != 'delta') {
xLabel = "Variance_of_"+params['tid']+'_'+xLabel
}
var yLabel = params['sptkey'];
var yRangeString = params['sptfreq']+'GHz_ell='+params['lowest_ell']+'-'+params['highest_ell']+'_'
if (params['rank'] == 'True') {
xLabel = 'rank('+xLabel+')'
yLabel = 'rank('+yLabel+')'
}
else {
if (params['logy'] == 'True') {
yLabel = 'log('+yLabel+')'
}
if (params['absx'] == 'True') {
xLabel = 'abs('+xLabel+')'
}
if (params['logx'] == 'True') {
xLabel = 'log('+xLabel+')'
}
}
var dateString = '_20190322-20191231_';
var outfile;
if (params['type'] == 'scatter') {
outfile = 'MainPagerPlots/'+yRangeString+yLabel+'_vs_'+xLabel+'_'+params['stat_test']+dateString+'scatter.png'
}
else if (params['type'] == 'time_series') {
outfile = 'MainPagerPlots/'+yRangeString+yLabel+'_vs_'+xLabel+dateString+'time_series.png'
}
//outfile = 'MainPagerPlots/220GHz_ell=10-150_log(QUratio)_vs_abs(Delta_TQI)_20190322-20191231_time_series.png'
return outfile
});
pager.setparams({
'merrakey':'QI',
'sptkey':'QUratio',
'sptfreq':'220',
'lowest_ell':'110',
'highest_ell':'250',
'stat_test':'Spearman',
'tid':'delta',
'rank':'False',
'logx':'False',
'logy':'False',
'absx':'False',
'type':'scatter',
});
</script>
</figure>
<hr>
</article>
</main>
</div>
<script type="text/javascript">
plupdate();
</script>
</body>
</html>