From a00648dfc2da7ba6c352f6b5a901c3ec97b77ccc Mon Sep 17 00:00:00 2001
From: r-ford <r-ford@users.noreply.github.com>
Date: Sun, 14 Apr 2024 16:12:44 +0000
Subject: [PATCH] deploy: bde5207211108bb42bed541c3acb6ef94773f9d4

---
 ...e0d1ee8aeb208995de1cb9c6493e0f3fa7d878.png | Bin 0 -> 69476 bytes
 ...da45a529926b94a8e62c02a6e5af7b2f59f167.png | Bin 0 -> 57595 bytes
 ...6c027a1bc2ef4ae483d275309d1fa71dc614fe.png | Bin 0 -> 37964 bytes
 ...0547d16d33b28aaf6df8526d2fd627bf3da697.png | Bin 0 -> 64916 bytes
 ...83f0131e329b22e3f077aedfbc0d0482e556c0.png | Bin 0 -> 81957 bytes
 ...8e9eab3d8024f23a52bc57d2a4f2932f78ff9b.png | Bin 0 -> 60582 bytes
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 ...836bdce10779ae336c2002f03b7f6b583f5d90.png | Bin 0 -> 47657 bytes
 _sources/notebooks/climate-modes-xeofs.ipynb  |   2 +-
 notebooks/climate-modes-xeofs.html            |  72 +++++++++---------
 notebooks/eof-intro.html                      |  20 ++---
 notebooks/notebook-template.html              |   4 +-
 searchindex.js                                |   2 +-
 13 files changed, 50 insertions(+), 50 deletions(-)
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diff --git a/_sources/notebooks/climate-modes-xeofs.ipynb b/_sources/notebooks/climate-modes-xeofs.ipynb
index 518e271..7382b24 100644
--- a/_sources/notebooks/climate-modes-xeofs.ipynb
+++ b/_sources/notebooks/climate-modes-xeofs.ipynb
@@ -275,7 +275,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we can see some modes of variability! EOF1 looks like ENSO or IPO, and EOF2 probably picking up a pattern of the recent temperature trend where the Southern Ocean and southeastern Pacific are slightly cooling. EOF3 and EOF4 appear to be showing some decadal modes of variability (PDO and maybe AMO), among other things. There is a lot going on in each of these maps, so to get a clearer index of some modes, we can restrict our domain. "
+    "Now we can see some modes of variability! EOF1 looks like ENSO or IPO, and EOF2 is probably picking up a pattern of the recent temperature trend where the Southern Ocean and southeastern Pacific are slightly cooling. EOF3 and EOF4 appear to be showing some decadal modes of variability (PDO and maybe AMO), among other things. There is a lot going on in each of these maps, so to get a clearer index of some modes, we can restrict our domain. "
    ]
   },
   {
diff --git a/notebooks/climate-modes-xeofs.html b/notebooks/climate-modes-xeofs.html
index ac0ef31..bb07c07 100644
--- a/notebooks/climate-modes-xeofs.html
+++ b/notebooks/climate-modes-xeofs.html
@@ -842,14 +842,14 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
     parent_stat:   Individual Values
     actual_range:  [-1.8, 42.32636]
     valid_range:   [-1.8, 45.0]
-    _ChunkSizes:   [1, 89, 180]</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2043</li><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-acb38ee8-ee02-470e-910e-26ff828a3bde' class='xr-array-in' type='checkbox' checked><label for='section-acb38ee8-ee02-470e-910e-26ff828a3bde' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[32728860 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-b1acb2d9-fa3a-40cf-ab57-4f913a8c2b8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b1acb2d9-fa3a-40cf-ab57-4f913a8c2b8f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-967dce0f-0d5a-4b81-a7c2-6024d251ef0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-967dce0f-0d5a-4b81-a7c2-6024d251ef0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e84bed8f-a606-4690-b864-64f762a5b7b7' class='xr-var-data-in' type='checkbox'><label for='data-e84bed8f-a606-4690-b864-64f762a5b7b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[88.0, -88.0]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
+    _ChunkSizes:   [1, 89, 180]</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2043</li><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c46f9fc2-1b48-4891-98a0-969a14828992' class='xr-array-in' type='checkbox' checked><label for='section-c46f9fc2-1b48-4891-98a0-969a14828992' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[32728860 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-c7688b22-04f0-4cb0-aa0e-5d767586c944' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c7688b22-04f0-4cb0-aa0e-5d767586c944' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-c717dbfc-5d64-41f0-ac2c-82067e19a0e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c717dbfc-5d64-41f0-ac2c-82067e19a0e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23d269ff-6a59-410e-9005-f204e9194d5b' class='xr-var-data-in' type='checkbox'><label for='data-23d269ff-6a59-410e-9005-f204e9194d5b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[88.0, -88.0]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,
         64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,
         40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,
         16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,
         -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,
        -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,
        -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,
-       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-11fcd200-6963-427d-9704-6c0d9ea6c6ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11fcd200-6963-427d-9704-6c0d9ea6c6ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51533a26-ab1d-496a-9291-5640e73d0ebb' class='xr-var-data-in' type='checkbox'><label for='data-51533a26-ab1d-496a-9291-5640e73d0ebb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[0.0, 358.0]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
+       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-7d3fade5-3c20-484e-aac1-83a064284764' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d3fade5-3c20-484e-aac1-83a064284764' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33e4903c-a1ad-490d-a34d-ed73f84df9a1' class='xr-var-data-in' type='checkbox'><label for='data-33e4903c-a1ad-490d-a34d-ed73f84df9a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[0.0, 358.0]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,
         24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,
         48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,
         72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,
@@ -864,10 +864,10 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
        288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,
        312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,
        336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],
-      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1854-01-01 ... 2024-03-01</div><input id='attrs-e3a59134-f4c4-4a21-bd9c-0ec3cafb5846' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3a59134-f4c4-4a21-bd9c-0ec3cafb5846' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60ea76bc-69d9-499b-a548-3701fa972f3b' class='xr-var-data-in' type='checkbox'><label for='data-60ea76bc-69d9-499b-a548-3701fa972f3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723.0, 81874.0]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1854-01-01T00:00:00.000000000&#x27;, &#x27;1854-02-01T00:00:00.000000000&#x27;,
+      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1854-01-01 ... 2024-03-01</div><input id='attrs-fa15260a-6c3e-4a7d-9067-78cc8735ba93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa15260a-6c3e-4a7d-9067-78cc8735ba93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-909d77a2-5a85-4725-be1c-5d227544365c' class='xr-var-data-in' type='checkbox'><label for='data-909d77a2-5a85-4725-be1c-5d227544365c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723.0, 81874.0]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1854-01-01T00:00:00.000000000&#x27;, &#x27;1854-02-01T00:00:00.000000000&#x27;,
        &#x27;1854-03-01T00:00:00.000000000&#x27;, ..., &#x27;2024-01-01T00:00:00.000000000&#x27;,
        &#x27;2024-02-01T00:00:00.000000000&#x27;, &#x27;2024-03-01T00:00:00.000000000&#x27;],
-      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9d7dc85f-7a52-4baf-aee0-9b2a202c2485' class='xr-section-summary-in' type='checkbox'  ><label for='section-9d7dc85f-7a52-4baf-aee0-9b2a202c2485' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c4454030-1342-4767-9565-f4b75791ddd8' class='xr-index-data-in' type='checkbox'/><label for='index-c4454030-1342-4767-9565-f4b75791ddd8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 88.0,  86.0,  84.0,  82.0,  80.0,  78.0,  76.0,  74.0,  72.0,  70.0,
+      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1a4ec07a-2e0d-4b36-bac6-f58a9af754af' class='xr-section-summary-in' type='checkbox'  ><label for='section-1a4ec07a-2e0d-4b36-bac6-f58a9af754af' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48b63821-1b72-4350-b789-e8b46730f8f6' class='xr-index-data-in' type='checkbox'/><label for='index-48b63821-1b72-4350-b789-e8b46730f8f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 88.0,  86.0,  84.0,  82.0,  80.0,  78.0,  76.0,  74.0,  72.0,  70.0,
         68.0,  66.0,  64.0,  62.0,  60.0,  58.0,  56.0,  54.0,  52.0,  50.0,
         48.0,  46.0,  44.0,  42.0,  40.0,  38.0,  36.0,  34.0,  32.0,  30.0,
         28.0,  26.0,  24.0,  22.0,  20.0,  18.0,  16.0,  14.0,  12.0,  10.0,
@@ -876,17 +876,17 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
        -32.0, -34.0, -36.0, -38.0, -40.0, -42.0, -44.0, -46.0, -48.0, -50.0,
        -52.0, -54.0, -56.0, -58.0, -60.0, -62.0, -64.0, -66.0, -68.0, -70.0,
        -72.0, -74.0, -76.0, -78.0, -80.0, -82.0, -84.0, -86.0, -88.0],
-      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-296a00d9-178d-4408-945d-af0be3a63c47' class='xr-index-data-in' type='checkbox'/><label for='index-296a00d9-178d-4408-945d-af0be3a63c47' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,  18.0,
+      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4fcda00b-88a9-4be3-98c3-dba519212a04' class='xr-index-data-in' type='checkbox'/><label for='index-4fcda00b-88a9-4be3-98c3-dba519212a04' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.0,   4.0,   6.0,   8.0,  10.0,  12.0,  14.0,  16.0,  18.0,
        ...
        340.0, 342.0, 344.0, 346.0, 348.0, 350.0, 352.0, 354.0, 356.0, 358.0],
-      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7e06e3ea-09b0-4b17-8ebf-bd6182d88159' class='xr-index-data-in' type='checkbox'/><label for='index-7e06e3ea-09b0-4b17-8ebf-bd6182d88159' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1854-01-01&#x27;, &#x27;1854-02-01&#x27;, &#x27;1854-03-01&#x27;, &#x27;1854-04-01&#x27;,
+      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-22df93a2-d7fb-4911-8c2a-01b5014a159b' class='xr-index-data-in' type='checkbox'/><label for='index-22df93a2-d7fb-4911-8c2a-01b5014a159b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1854-01-01&#x27;, &#x27;1854-02-01&#x27;, &#x27;1854-03-01&#x27;, &#x27;1854-04-01&#x27;,
                &#x27;1854-05-01&#x27;, &#x27;1854-06-01&#x27;, &#x27;1854-07-01&#x27;, &#x27;1854-08-01&#x27;,
                &#x27;1854-09-01&#x27;, &#x27;1854-10-01&#x27;,
                ...
                &#x27;2023-06-01&#x27;, &#x27;2023-07-01&#x27;, &#x27;2023-08-01&#x27;, &#x27;2023-09-01&#x27;,
                &#x27;2023-10-01&#x27;, &#x27;2023-11-01&#x27;, &#x27;2023-12-01&#x27;, &#x27;2024-01-01&#x27;,
                &#x27;2024-02-01&#x27;, &#x27;2024-03-01&#x27;],
-              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=2043, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fbb9f68e-bf08-41d9-8ca2-db1fd5fc8707' class='xr-section-summary-in' type='checkbox'  ><label for='section-fbb9f68e-bf08-41d9-8ca2-db1fd5fc8707' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8, 42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8, 45.0]</dd><dt><span>_ChunkSizes :</span></dt><dd>[1, 89, 180]</dd></dl></div></li></ul></div></div></div></div>
+              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=2043, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e75a60c-d1ac-4d83-84de-3c6b8ca20bfe' class='xr-section-summary-in' type='checkbox'  ><label for='section-8e75a60c-d1ac-4d83-84de-3c6b8ca20bfe' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8, 42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8, 45.0]</dd><dt><span>_ChunkSizes :</span></dt><dd>[1, 89, 180]</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>Check that the data looks as expected:</p>
 <div class="cell docutils container">
@@ -896,7 +896,7 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f4b475ba9b0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.QuadMesh at 0x7f3d0e1e69b0&gt;
 </pre></div>
 </div>
 <img alt="../_images/e916d7882e68d2252816f31c236a5711530a38dc2fbc11136cba6a2fbd9f4e16.png" src="../_images/e916d7882e68d2252816f31c236a5711530a38dc2fbc11136cba6a2fbd9f4e16.png" />
@@ -921,7 +921,7 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b4749aec0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d745c7a90&gt;
 </pre></div>
 </div>
 <img alt="../_images/792737bbd01dd9ba581e1d39d1e3f9726b7a17e69c5c03f3c161802ed7af6d31.png" src="../_images/792737bbd01dd9ba581e1d39d1e3f9726b7a17e69c5c03f3c161802ed7af6d31.png" />
@@ -934,10 +934,10 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3f191ba0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d05df97e0&gt;
 </pre></div>
 </div>
-<img alt="../_images/d0142dab514b5f804a6ab65c9b0a2117f4896110cff3e36d324d05acb535a3e3.png" src="../_images/d0142dab514b5f804a6ab65c9b0a2117f4896110cff3e36d324d05acb535a3e3.png" />
+<img alt="../_images/d01657b2b32124b20432bc29b4836bdce10779ae336c2002f03b7f6b583f5d90.png" src="../_images/d01657b2b32124b20432bc29b4836bdce10779ae336c2002f03b7f6b583f5d90.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -1318,7 +1318,7 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
     model:          EOF analysis
     software:       xeofs
     version:        2.3.2
-    date:           2024-04-14 15:58:19
+    date:           2024-04-14 16:11:27
     n_modes:        4
     center:         True
     ...             ...
@@ -1327,7 +1327,7 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
     verbose:        False
     compute:        True
     solver:         auto
-    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-aae133af-4282-4fa6-8d25-0463588eeb7b' class='xr-array-in' type='checkbox' checked><label for='section-aae133af-4282-4fa6-8d25-0463588eeb7b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.8261 0.03629 0.02652 0.01647</span></div><div class='xr-array-data'><pre>array([0.82605367, 0.03629283, 0.0265211 , 0.01646761])</pre></div></div></li><li class='xr-section-item'><input id='section-88abc0c0-2fd9-433b-aea1-15b4107195e9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-88abc0c0-2fd9-433b-aea1-15b4107195e9' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-080cec07-3e67-4025-9dac-441abb6a10f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-080cec07-3e67-4025-9dac-441abb6a10f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7817a0f9-2d21-490e-a88b-2fbc234ff5c9' class='xr-var-data-in' type='checkbox'><label for='data-7817a0f9-2d21-490e-a88b-2fbc234ff5c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8d587eb2-c8e6-48c3-be83-42dd12639ce1' class='xr-section-summary-in' type='checkbox'  ><label for='section-8d587eb2-c8e6-48c3-be83-42dd12639ce1' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-54670374-cc5f-4e21-a7a7-1d318f8e128b' class='xr-index-data-in' type='checkbox'/><label for='index-54670374-cc5f-4e21-a7a7-1d318f8e128b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3560c5b6-f2b5-4b91-885a-c4e217f9ae46' class='xr-section-summary-in' type='checkbox'  ><label for='section-3560c5b6-f2b5-4b91-885a-c4e217f9ae46' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 15:58:19</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
+    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-bbaaf306-2d8f-48d0-9f4b-cf637194dcf5' class='xr-array-in' type='checkbox' checked><label for='section-bbaaf306-2d8f-48d0-9f4b-cf637194dcf5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.8261 0.03629 0.02652 0.01647</span></div><div class='xr-array-data'><pre>array([0.82605367, 0.03629283, 0.0265211 , 0.01646761])</pre></div></div></li><li class='xr-section-item'><input id='section-700bef7a-9a92-4cdb-acc9-95ed3597786f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-700bef7a-9a92-4cdb-acc9-95ed3597786f' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-8432f24b-37ec-4df2-8ed2-5abf57a22619' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8432f24b-37ec-4df2-8ed2-5abf57a22619' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7129f9c8-3cc4-4446-8471-e36f2e538e37' class='xr-var-data-in' type='checkbox'><label for='data-7129f9c8-3cc4-4446-8471-e36f2e538e37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a822fb41-c7b5-44be-96ec-e7fe2e76d153' class='xr-section-summary-in' type='checkbox'  ><label for='section-a822fb41-c7b5-44be-96ec-e7fe2e76d153' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4b79cac6-8917-437f-aae6-11a0824dfbc6' class='xr-index-data-in' type='checkbox'/><label for='index-4b79cac6-8917-437f-aae6-11a0824dfbc6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eac04a1a-c1b6-4253-9316-1d45fc98148a' class='xr-section-summary-in' type='checkbox'  ><label for='section-eac04a1a-c1b6-4253-9316-1d45fc98148a' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 16:11:27</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <p>EOF1 explains 83% of the variance, and the map shows interhemispheric asymmetry. The corresponding PC has a period of one year, which we can see more clearly by only plotting a few years:</p>
 <div class="cell docutils container">
@@ -1337,7 +1337,7 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
 </div>
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-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f4b3dfad780&gt;]
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f3d04c15c60&gt;]
 </pre></div>
 </div>
 <img alt="../_images/1206ca70f269c3e5d11fdd6703af874f779b17cb816423e59b6f906e49a12acc.png" src="../_images/1206ca70f269c3e5d11fdd6703af874f779b17cb816423e59b6f906e49a12acc.png" />
@@ -1389,10 +1389,10 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3f0dd690&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d05d36d40&gt;
 </pre></div>
 </div>
-<img alt="../_images/8f1db5c298e04c0905796f68679997f86abb339fa742a3cf12d32179564074f5.png" src="../_images/8f1db5c298e04c0905796f68679997f86abb339fa742a3cf12d32179564074f5.png" />
+<img alt="../_images/00df743148a5028e5a7485650fe0d1ee8aeb208995de1cb9c6493e0f3fa7d878.png" src="../_images/00df743148a5028e5a7485650fe0d1ee8aeb208995de1cb9c6493e0f3fa7d878.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -1402,10 +1402,10 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3dc494b0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d048aafb0&gt;
 </pre></div>
 </div>
-<img alt="../_images/b45f41b4b8df7e722bc123afbf5ca9b7910ccbcb8b4d2a2af67ca4bd6f31d7f9.png" src="../_images/b45f41b4b8df7e722bc123afbf5ca9b7910ccbcb8b4d2a2af67ca4bd6f31d7f9.png" />
+<img alt="../_images/609b8b70a907f50ca94d46f9280547d16d33b28aaf6df8526d2fd627bf3da697.png" src="../_images/609b8b70a907f50ca94d46f9280547d16d33b28aaf6df8526d2fd627bf3da697.png" />
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@@ -1779,14 +1779,14 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
   fill: currentColor;
 }
 </style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;explained_variance_ratio&#x27; (mode: 4)&gt; Size: 32B
-array([0.12239579, 0.04715375, 0.03457925, 0.03194285])
+array([0.12239579, 0.04715375, 0.03457935, 0.0319431 ])
 Coordinates:
   * mode     (mode) int64 32B 1 2 3 4
 Attributes: (12/16)
     model:          EOF analysis
     software:       xeofs
     version:        2.3.2
-    date:           2024-04-14 15:59:00
+    date:           2024-04-14 16:12:10
     n_modes:        4
     center:         True
     ...             ...
@@ -1795,9 +1795,9 @@ <h2>Accessing and preparing the data<a class="headerlink" href="#accessing-and-p
     verbose:        False
     compute:        True
     solver:         auto
-    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1a3b8059-242d-4a0f-9111-14af5cc146ac' class='xr-array-in' type='checkbox' checked><label for='section-1a3b8059-242d-4a0f-9111-14af5cc146ac' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1224 0.04715 0.03458 0.03194</span></div><div class='xr-array-data'><pre>array([0.12239579, 0.04715375, 0.03457925, 0.03194285])</pre></div></div></li><li class='xr-section-item'><input id='section-467600df-d41e-480b-9b13-7c4abc4efc3d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-467600df-d41e-480b-9b13-7c4abc4efc3d' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-503d3604-3826-4841-a28e-7ceec6b98d49' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-503d3604-3826-4841-a28e-7ceec6b98d49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f71972a9-6fd6-45ae-8f78-50124060577a' class='xr-var-data-in' type='checkbox'><label for='data-f71972a9-6fd6-45ae-8f78-50124060577a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8acca55c-b206-4b7e-940d-ab72602717bb' class='xr-section-summary-in' type='checkbox'  ><label for='section-8acca55c-b206-4b7e-940d-ab72602717bb' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f2502b35-88a5-4ccd-9f8e-6e8c08939320' class='xr-index-data-in' type='checkbox'/><label for='index-f2502b35-88a5-4ccd-9f8e-6e8c08939320' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f8d7bd76-6385-4fc8-8114-f807fa307ea0' class='xr-section-summary-in' type='checkbox'  ><label for='section-f8d7bd76-6385-4fc8-8114-f807fa307ea0' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 15:59:00</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
+    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3923a759-2ff0-419a-88cf-78703902da7e' class='xr-array-in' type='checkbox' checked><label for='section-3923a759-2ff0-419a-88cf-78703902da7e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1224 0.04715 0.03458 0.03194</span></div><div class='xr-array-data'><pre>array([0.12239579, 0.04715375, 0.03457935, 0.0319431 ])</pre></div></div></li><li class='xr-section-item'><input id='section-826aea48-0ba7-43d1-bb12-f62e1187ef19' class='xr-section-summary-in' type='checkbox'  checked><label for='section-826aea48-0ba7-43d1-bb12-f62e1187ef19' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-f29c4edb-d60d-4b91-beb2-7ccb6f0cc87f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f29c4edb-d60d-4b91-beb2-7ccb6f0cc87f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47330299-a5fd-460a-9182-3773d253170b' class='xr-var-data-in' type='checkbox'><label for='data-47330299-a5fd-460a-9182-3773d253170b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a3ba52c8-dac7-4ef0-9558-4859ae5913c8' class='xr-section-summary-in' type='checkbox'  ><label for='section-a3ba52c8-dac7-4ef0-9558-4859ae5913c8' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b8e32e58-e3b6-458f-bb69-16bb0b4601bc' class='xr-index-data-in' type='checkbox'/><label for='index-b8e32e58-e3b6-458f-bb69-16bb0b4601bc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c35239de-6660-4fd0-ba68-6f3082bf7efb' class='xr-section-summary-in' type='checkbox'  ><label for='section-c35239de-6660-4fd0-ba68-6f3082bf7efb' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 16:12:10</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
 </div>
-<p>Now we can see some modes of variability! EOF1 looks like ENSO or IPO, and EOF2 probably picking up a pattern of the recent temperature trend where the Southern Ocean and southeastern Pacific are slightly cooling. EOF3 and EOF4 appear to be showing some decadal modes of variability (PDO and maybe AMO), among other things. There is a lot going on in each of these maps, so to get a clearer index of some modes, we can restrict our domain.</p>
+<p>Now we can see some modes of variability! EOF1 looks like ENSO or IPO, and EOF2 is probably picking up a pattern of the recent temperature trend where the Southern Ocean and southeastern Pacific are slightly cooling. EOF3 and EOF4 appear to be showing some decadal modes of variability (PDO and maybe AMO), among other things. There is a lot going on in each of these maps, so to get a clearer index of some modes, we can restrict our domain.</p>
 </section>
 <section id="el-nino-southern-oscillation-enso">
 <h2>El Niño Southern Oscillation (ENSO)<a class="headerlink" href="#el-nino-southern-oscillation-enso" title="Link to this heading"><i class="fas fa-link"></i></a></h2>
@@ -1827,10 +1827,10 @@ <h2>El Niño Southern Oscillation (ENSO)<a class="headerlink" href="#el-nino-sou
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3da37c70&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d0486ff40&gt;
 </pre></div>
 </div>
-<img alt="../_images/a5a36a2c71b2d8fb5e38e21708cbbfd914f9dd87e23641c4c35f991973f5e9e9.png" src="../_images/a5a36a2c71b2d8fb5e38e21708cbbfd914f9dd87e23641c4c35f991973f5e9e9.png" />
+<img alt="../_images/54747e18fcf9c109e84ad936956c027a1bc2ef4ae483d275309d1fa71dc614fe.png" src="../_images/54747e18fcf9c109e84ad936956c027a1bc2ef4ae483d275309d1fa71dc614fe.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -1840,10 +1840,10 @@ <h2>El Niño Southern Oscillation (ENSO)<a class="headerlink" href="#el-nino-sou
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3d957a30&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d0e065fc0&gt;
 </pre></div>
 </div>
-<img alt="../_images/3852676d3354ebb8bbfd20668a6c4d56e1a7ee7fb25f4c165e9ee2c421100f0d.png" src="../_images/3852676d3354ebb8bbfd20668a6c4d56e1a7ee7fb25f4c165e9ee2c421100f0d.png" />
+<img alt="../_images/7f72d88f32397dc10069cac7cd8e9eab3d8024f23a52bc57d2a4f2932f78ff9b.png" src="../_images/7f72d88f32397dc10069cac7cd8e9eab3d8024f23a52bc57d2a4f2932f78ff9b.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -2217,14 +2217,14 @@ <h2>El Niño Southern Oscillation (ENSO)<a class="headerlink" href="#el-nino-sou
   fill: currentColor;
 }
 </style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;explained_variance_ratio&#x27; (mode: 4)&gt; Size: 32B
-array([0.3297638 , 0.08714096, 0.05302952, 0.04715518])
+array([0.3297638 , 0.08714096, 0.05302952, 0.04715512])
 Coordinates:
   * mode     (mode) int64 32B 1 2 3 4
 Attributes: (12/16)
     model:          EOF analysis
     software:       xeofs
     version:        2.3.2
-    date:           2024-04-14 15:59:02
+    date:           2024-04-14 16:12:13
     n_modes:        4
     center:         True
     ...             ...
@@ -2233,7 +2233,7 @@ <h2>El Niño Southern Oscillation (ENSO)<a class="headerlink" href="#el-nino-sou
     verbose:        False
     compute:        True
     solver:         auto
-    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e86d4e5d-d312-4813-8716-0ff862cd6d54' class='xr-array-in' type='checkbox' checked><label for='section-e86d4e5d-d312-4813-8716-0ff862cd6d54' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.3298 0.08714 0.05303 0.04716</span></div><div class='xr-array-data'><pre>array([0.3297638 , 0.08714096, 0.05302952, 0.04715518])</pre></div></div></li><li class='xr-section-item'><input id='section-f5c6f5d4-4f1d-4a00-9839-9c29b5e62b9f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f5c6f5d4-4f1d-4a00-9839-9c29b5e62b9f' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-c8ec3dff-02d6-4ad6-8f79-a48a7078e41f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8ec3dff-02d6-4ad6-8f79-a48a7078e41f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97df2c19-8f63-4069-8732-0789b27b001e' class='xr-var-data-in' type='checkbox'><label for='data-97df2c19-8f63-4069-8732-0789b27b001e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-283a8d93-f45a-49b4-b2c4-49f98137f7d8' class='xr-section-summary-in' type='checkbox'  ><label for='section-283a8d93-f45a-49b4-b2c4-49f98137f7d8' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-feca31b9-ef7a-4cf2-8c0d-2510261f19ed' class='xr-index-data-in' type='checkbox'/><label for='index-feca31b9-ef7a-4cf2-8c0d-2510261f19ed' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f2bdc1c4-1658-4cdb-9ca6-86b3c5bba15f' class='xr-section-summary-in' type='checkbox'  ><label for='section-f2bdc1c4-1658-4cdb-9ca6-86b3c5bba15f' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 15:59:02</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
+    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d73ea3cb-be41-47cd-a23a-13cbf3e86c2f' class='xr-array-in' type='checkbox' checked><label for='section-d73ea3cb-be41-47cd-a23a-13cbf3e86c2f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.3298 0.08714 0.05303 0.04716</span></div><div class='xr-array-data'><pre>array([0.3297638 , 0.08714096, 0.05302952, 0.04715512])</pre></div></div></li><li class='xr-section-item'><input id='section-8d161620-cfa3-420c-a2e9-70c511ef0d29' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8d161620-cfa3-420c-a2e9-70c511ef0d29' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-fd76a70c-1e57-4dbf-8c19-53ce8d06d7c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd76a70c-1e57-4dbf-8c19-53ce8d06d7c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf7b92c2-9e4e-4391-aa6f-a716576c5f43' class='xr-var-data-in' type='checkbox'><label for='data-cf7b92c2-9e4e-4391-aa6f-a716576c5f43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-17c05ca8-5dc3-4c82-a01a-d59a8268203f' class='xr-section-summary-in' type='checkbox'  ><label for='section-17c05ca8-5dc3-4c82-a01a-d59a8268203f' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1df2cdb8-9690-42f2-a612-2c21e3f8ceaa' class='xr-index-data-in' type='checkbox'/><label for='index-1df2cdb8-9690-42f2-a612-2c21e3f8ceaa' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de94ab89-f5ab-4602-97fd-10844c6af04c' class='xr-section-summary-in' type='checkbox'  ><label for='section-de94ab89-f5ab-4602-97fd-10844c6af04c' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 16:12:13</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -2306,10 +2306,10 @@ <h2>Pacific Decadal Oscillation (PDO)<a class="headerlink" href="#pacific-decada
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3d537490&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d041a3a60&gt;
 </pre></div>
 </div>
-<img alt="../_images/432d0f79084a170620914ffb4c7ba2edb41dbe0ae1ac3bf30ae85fa45adf6402.png" src="../_images/432d0f79084a170620914ffb4c7ba2edb41dbe0ae1ac3bf30ae85fa45adf6402.png" />
+<img alt="../_images/c913472cbfca54962dd3a44c479a8c2e6e67b59c180915296c88ffb55be5af5e.png" src="../_images/c913472cbfca54962dd3a44c479a8c2e6e67b59c180915296c88ffb55be5af5e.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -2319,10 +2319,10 @@ <h2>Pacific Decadal Oscillation (PDO)<a class="headerlink" href="#pacific-decada
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f4b3db75cc0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;xarray.plot.facetgrid.FacetGrid at 0x7f3d048270d0&gt;
 </pre></div>
 </div>
-<img alt="../_images/6bb53c7427345784964a40d5f90b130beb757f276aababde51db5318bdea8f24.png" src="../_images/6bb53c7427345784964a40d5f90b130beb757f276aababde51db5318bdea8f24.png" />
+<img alt="../_images/2ae8060b6491292bf5a6f60d21da45a529926b94a8e62c02a6e5af7b2f59f167.png" src="../_images/2ae8060b6491292bf5a6f60d21da45a529926b94a8e62c02a6e5af7b2f59f167.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -2703,7 +2703,7 @@ <h2>Pacific Decadal Oscillation (PDO)<a class="headerlink" href="#pacific-decada
     model:          EOF analysis
     software:       xeofs
     version:        2.3.2
-    date:           2024-04-14 15:59:04
+    date:           2024-04-14 16:12:14
     n_modes:        4
     center:         True
     ...             ...
@@ -2712,7 +2712,7 @@ <h2>Pacific Decadal Oscillation (PDO)<a class="headerlink" href="#pacific-decada
     verbose:        False
     compute:        True
     solver:         auto
-    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1903961c-a2b7-45cb-a95b-c160af2829b5' class='xr-array-in' type='checkbox' checked><label for='section-1903961c-a2b7-45cb-a95b-c160af2829b5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1744 0.1108 0.07213 0.06708</span></div><div class='xr-array-data'><pre>array([0.17443642, 0.11083306, 0.07212811, 0.06708335])</pre></div></div></li><li class='xr-section-item'><input id='section-3f13a7e8-50e0-4455-b085-620d7dbeac79' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f13a7e8-50e0-4455-b085-620d7dbeac79' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3e1fb485-8145-49c5-822a-23bc397f310e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e1fb485-8145-49c5-822a-23bc397f310e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7af48a4-9c8a-43fd-9518-56b298597aa3' class='xr-var-data-in' type='checkbox'><label for='data-f7af48a4-9c8a-43fd-9518-56b298597aa3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4d392500-8cde-478e-b1fb-bec9edba5aad' class='xr-section-summary-in' type='checkbox'  ><label for='section-4d392500-8cde-478e-b1fb-bec9edba5aad' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cce0184d-9718-43a8-aacf-34323ed79ea4' class='xr-index-data-in' type='checkbox'/><label for='index-cce0184d-9718-43a8-aacf-34323ed79ea4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-259cf21c-34e9-491c-8756-5997b06bed92' class='xr-section-summary-in' type='checkbox'  ><label for='section-259cf21c-34e9-491c-8756-5997b06bed92' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 15:59:04</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
+    solver_kwargs:  {}</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'explained_variance_ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>mode</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-47765325-e84f-4e6e-a14e-e256e5ba1985' class='xr-array-in' type='checkbox' checked><label for='section-47765325-e84f-4e6e-a14e-e256e5ba1985' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1744 0.1108 0.07213 0.06708</span></div><div class='xr-array-data'><pre>array([0.17443642, 0.11083306, 0.07212811, 0.06708335])</pre></div></div></li><li class='xr-section-item'><input id='section-d4757a06-c022-4a54-959e-68c3baecea1d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d4757a06-c022-4a54-959e-68c3baecea1d' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mode</span></div><div class='xr-var-dims'>(mode)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-eeed8ccd-1fe6-478f-9fec-de80465b7897' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eeed8ccd-1fe6-478f-9fec-de80465b7897' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b407b983-753f-4004-865b-0f8a33556f18' class='xr-var-data-in' type='checkbox'><label for='data-b407b983-753f-4004-865b-0f8a33556f18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-39da85ee-b827-4312-a2d8-9fc142777c25' class='xr-section-summary-in' type='checkbox'  ><label for='section-39da85ee-b827-4312-a2d8-9fc142777c25' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>mode</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b262f821-3995-4d77-99f2-95685e179a83' class='xr-index-data-in' type='checkbox'/><label for='index-b262f821-3995-4d77-99f2-95685e179a83' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int64&#x27;, name=&#x27;mode&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-80c5fe07-4f48-42d0-bf04-2684ad74293a' class='xr-section-summary-in' type='checkbox'  ><label for='section-80c5fe07-4f48-42d0-bf04-2684ad74293a' class='xr-section-summary' >Attributes: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>model :</span></dt><dd>EOF analysis</dd><dt><span>software :</span></dt><dd>xeofs</dd><dt><span>version :</span></dt><dd>2.3.2</dd><dt><span>date :</span></dt><dd>2024-04-14 16:12:14</dd><dt><span>n_modes :</span></dt><dd>4</dd><dt><span>center :</span></dt><dd>True</dd><dt><span>standardize :</span></dt><dd>False</dd><dt><span>use_coslat :</span></dt><dd>True</dd><dt><span>check_nans :</span></dt><dd>True</dd><dt><span>sample_name :</span></dt><dd>sample</dd><dt><span>feature_name :</span></dt><dd>feature</dd><dt><span>random_state :</span></dt><dd>None</dd><dt><span>verbose :</span></dt><dd>False</dd><dt><span>compute :</span></dt><dd>True</dd><dt><span>solver :</span></dt><dd>auto</dd><dt><span>solver_kwargs :</span></dt><dd>{}</dd></dl></div></li></ul></div></div></div></div>
 </div>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -2732,7 +2732,7 @@ <h2>Pacific Decadal Oscillation (PDO)<a class="headerlink" href="#pacific-decada
 <div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Text(0.5, 1.0, &#39;PDO Index (detrended North Pacific SSTA EOF1)&#39;)
 </pre></div>
 </div>
-<img alt="../_images/fbf6125d5279312c26cf14046728eb7330cc0f4ae7b7019795f39366fc623456.png" src="../_images/fbf6125d5279312c26cf14046728eb7330cc0f4ae7b7019795f39366fc623456.png" />
+<img alt="../_images/793a2ed40343518858470a57b583f0131e329b22e3f077aedfbc0d0482e556c0.png" src="../_images/793a2ed40343518858470a57b583f0131e329b22e3f077aedfbc0d0482e556c0.png" />
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diff --git a/notebooks/eof-intro.html b/notebooks/eof-intro.html
index 706129e..5b0df57 100644
--- a/notebooks/eof-intro.html
+++ b/notebooks/eof-intro.html
@@ -510,13 +510,13 @@ <h2>Deriving the eigenvalue problem<a class="headerlink" href="#deriving-the-eig
 </tbody>
 </table>
 <p>This is now an optimization problem. To maximize the alignment between the basis and observations, we will maximize the projection of the vectors <span class="math notranslate nohighlight">\(\mathbf f_n\)</span> onto each basis vector using the sum of squares:</p>
-<div class="amsmath math notranslate nohighlight" id="equation-be6e0868-bab0-4574-95b6-976c6e079f3d">
-<span class="eqno">(1)<a class="headerlink" href="#equation-be6e0868-bab0-4574-95b6-976c6e079f3d" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
+<div class="amsmath math notranslate nohighlight" id="equation-f93a4f61-d48e-406d-b238-0130ae72a50a">
+<span class="eqno">(1)<a class="headerlink" href="#equation-f93a4f61-d48e-406d-b238-0130ae72a50a" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
 \sum_{n=1}^N(\mathbf f_n \cdot \mathbf e_m)^2
 \end{equation}\]</div>
 <p>for <span class="math notranslate nohighlight">\(m=1, 2, \dots, M\)</span>. We also require mutual orthonormality for the basis: <span class="math notranslate nohighlight">\(\mathbf e_i\cdot\mathbf e_j=\delta_{ij}\)</span>. Now, let’s define this quantity as <span class="math notranslate nohighlight">\(\psi(\mathbf e_m)\)</span>:</p>
-<div class="amsmath math notranslate nohighlight" id="equation-02d840c5-8cea-4c0d-b289-bc369a1ef79f">
-<span class="eqno">(2)<a class="headerlink" href="#equation-02d840c5-8cea-4c0d-b289-bc369a1ef79f" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
+<div class="amsmath math notranslate nohighlight" id="equation-3ffcfe62-7ec4-4f71-81f2-a74fea60ecbc">
+<span class="eqno">(2)<a class="headerlink" href="#equation-3ffcfe62-7ec4-4f71-81f2-a74fea60ecbc" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
 \begin{aligned}
 \psi(\mathbf e_m)\equiv\sum_{n=1}^N(\mathbf f_n \cdot \mathbf e_m)^2
 &amp;=\sum_{n=1}^N(\mathbf e_m^\mathrm T \mathbf f_n)(\mathbf f_n^\mathrm T\mathbf e_m)\\
@@ -527,8 +527,8 @@ <h2>Deriving the eigenvalue problem<a class="headerlink" href="#deriving-the-eig
 \end{equation}\]</div>
 <p>where <span class="math notranslate nohighlight">\(\mathbf R=\mathbf F\mathbf F^\mathrm T\)</span> is the covariance matrix of <span class="math notranslate nohighlight">\(\mathbf F\)</span>.</p>
 <p>We now seek the extrema of <span class="math notranslate nohighlight">\(\psi(\mathbf e)\)</span> (dropping the subscript <span class="math notranslate nohighlight">\(m\)</span> for convenience), which satisfy <span class="math notranslate nohighlight">\(\psi(\mathbf e+\delta\mathbf e)=\psi(\mathbf e)\)</span> for a small change <span class="math notranslate nohighlight">\(\delta\mathbf e\)</span> in the direction of <span class="math notranslate nohighlight">\(\mathbf e\)</span>. Then</p>
-<div class="amsmath math notranslate nohighlight" id="equation-cd3b83a3-932a-4c35-9f0c-8aa7a638f305">
-<span class="eqno">(3)<a class="headerlink" href="#equation-cd3b83a3-932a-4c35-9f0c-8aa7a638f305" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
+<div class="amsmath math notranslate nohighlight" id="equation-6bc17aad-b0d4-4a43-a436-200badf42c07">
+<span class="eqno">(3)<a class="headerlink" href="#equation-6bc17aad-b0d4-4a43-a436-200badf42c07" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
 \begin{aligned}
 \psi(\mathbf e+\delta\mathbf e)&amp;=(\mathbf e+\delta\mathbf e)^\mathrm T\mathbf R(\mathbf e+\delta\mathbf e)\\
 &amp;=\mathbf e^\mathrm T\mathbf R\mathbf e+2(\delta\mathbf e)^\mathrm T\mathbf R\mathbf e + (\delta\mathbf e)^\mathrm T\mathbf R\delta\mathbf e\\
@@ -537,13 +537,13 @@ <h2>Deriving the eigenvalue problem<a class="headerlink" href="#deriving-the-eig
 \end{aligned}
 \end{equation}\]</div>
 <p>where we only keep the terms first order in <span class="math notranslate nohighlight">\(\delta\mathbf e\)</span>. The optimization condition implies</p>
-<div class="amsmath math notranslate nohighlight" id="equation-563376db-1451-47fd-807e-1ca781f6961d">
-<span class="eqno">(4)<a class="headerlink" href="#equation-563376db-1451-47fd-807e-1ca781f6961d" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
+<div class="amsmath math notranslate nohighlight" id="equation-15f46f49-eb67-4fdb-8098-9e9d9a3077d7">
+<span class="eqno">(4)<a class="headerlink" href="#equation-15f46f49-eb67-4fdb-8098-9e9d9a3077d7" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
 (\delta\mathbf e)^\mathrm T\mathbf R\mathbf e=0
 \end{equation}\]</div>
 <p>By the orthonormality of the basis, we also require that these variations only change the direction of <span class="math notranslate nohighlight">\(\mathbf e\)</span>, so <span class="math notranslate nohighlight">\((\mathbf e+\delta\mathbf e)^\mathrm T(\mathbf e+\delta\mathbf e)=1\Rightarrow(\delta\mathbf e)^\mathrm T\mathbf e=0\)</span>, again only keeping terms first order in <span class="math notranslate nohighlight">\(\delta\mathbf e\)</span>. We can combine these two conditions, provided that we multiply the orthonormality condition by a constant that has the same units as the entries of <span class="math notranslate nohighlight">\(\mathbf R\)</span>:</p>
-<div class="amsmath math notranslate nohighlight" id="equation-50f61f70-f62c-4570-b6c4-212a2ea4ffd2">
-<span class="eqno">(5)<a class="headerlink" href="#equation-50f61f70-f62c-4570-b6c4-212a2ea4ffd2" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
+<div class="amsmath math notranslate nohighlight" id="equation-70f44d9d-b16d-469b-bad6-8e18625f73d7">
+<span class="eqno">(5)<a class="headerlink" href="#equation-70f44d9d-b16d-469b-bad6-8e18625f73d7" title="Permalink to this equation"><i class="fas fa-link"></i></a></span>\[\begin{equation}
 (\delta\mathbf e)^\mathrm T\mathbf R\mathbf e-\lambda(\delta\mathbf e)^\mathrm T\mathbf e=(\delta\mathbf e)^\mathrm T[\mathbf R\mathbf e-\lambda\mathbf e]=0
 \end{equation}\]</div>
 <p>Since <span class="math notranslate nohighlight">\(\delta\mathbf e\)</span> is arbitrary, we must have <span class="math notranslate nohighlight">\(\mathbf R\mathbf e-\lambda\mathbf e=0\)</span>, the eigenvalue problem for <span class="math notranslate nohighlight">\(\mathbf R\)</span>, or for nontrivial solutions, <span class="math notranslate nohighlight">\(|\mathbf R-\lambda\mathbf I|=0\)</span>.</p>
diff --git a/notebooks/notebook-template.html b/notebooks/notebook-template.html
index c45859f..b6f2e98 100644
--- a/notebooks/notebook-template.html
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@@ -514,8 +514,8 @@ <h5>of further and further<a class="headerlink" href="#of-further-and-further" t
 <section id="header-levels">
 <h6>header levels<a class="headerlink" href="#header-levels" title="Link to this heading"><i class="fas fa-link"></i></a></h6>
 <p>as well <span class="math notranslate nohighlight">\(m = a * t / h\)</span> text! Similarly, you have access to other <span class="math notranslate nohighlight">\(\LaTeX\)</span> equation <a class="reference external" href="https://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Typesetting%20Equations.html"><strong>functionality</strong></a> via MathJax (demo below from link),</p>
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+<div class="amsmath math notranslate nohighlight" id="equation-fd37418f-0ef0-431f-acbb-2a00b3943044">
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 \dot{x} &amp; = \sigma(y-x) \\
 \dot{y} &amp; = \rho x - y - xz \\
 \dot{z} &amp; = -\beta z + xy
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