Repository: AI4S2S/s2spy (language: python)

Issue:
Support non-daily data in `preprocessor`
The current preprocessor only supports operations with daily data. We need to extend its functionality for data with different temporal resolution (e.g. weekly, monthly and annualy).


Discussion / hints:

Fix patch:
diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index b426b80..3c63d8b 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -17,7 +17,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ['ubuntu-latest', 'macos-latest', 'windows-latest']
-        python-version: ['3.8', '3.9', '3.10']
+        python-version: ['3.9', '3.10']
     steps:
       - uses: actions/checkout@v3
       - name: Set up Python ${{ matrix.python-version }}
diff --git a/docs/notebooks/tutorial_preprocessing.ipynb b/docs/notebooks/tutorial_preprocessing.ipynb
index 3386f3e..9e53b2c 100644
--- a/docs/notebooks/tutorial_preprocessing.ipynb
+++ b/docs/notebooks/tutorial_preprocessing.ipynb
@@ -41,17 +41,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The preprocessor is instatiated with the basic settings, the size of the rolling window, the detrending method, and if climatology should be removed from the data."
+    "The preprocessor is instatiated with the basic settings, the size of the rolling window, the detrending method, and if climatology should be removed from the data. <br>\n",
+    "User needs to inform preprocessor the temporal resoltuion of their data, by setting the `timescale` argument to be either `daily`, `weekly` or `monthly` timescale."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "preprocessor = preprocess.Preprocessor(\n",
     "    rolling_window_size=25,\n",
+    "    timescale=\"daily\",\n",
     "    detrend=\"linear\",\n",
     "    subtract_climatology=True,\n",
     ")"
@@ -67,7 +69,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -76,9 +78,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'slope': <xarray.Dataset>\n",
+       " Dimensions:    (latitude: 5, longitude: 13)\n",
+       " Coordinates:\n",
+       "   * longitude  (longitude) float64 177.5 182.5 187.5 192.5 ... 227.5 232.5 237.5\n",
+       "   * latitude   (latitude) float64 47.5 42.5 37.5 32.5 27.5\n",
+       " Data variables:\n",
+       "     sst        (latitude, longitude) float64 9.69e-20 1.011e-19 ... 4.13e-19,\n",
+       " 'intercept': <xarray.Dataset>\n",
+       " Dimensions:    (latitude: 5, longitude: 13)\n",
+       " Coordinates:\n",
+       "   * longitude  (longitude) float64 177.5 182.5 187.5 192.5 ... 227.5 232.5 237.5\n",
+       "   * latitude   (latitude) float64 47.5 42.5 37.5 32.5 27.5\n",
+       " Data variables:\n",
+       "     sst        (latitude, longitude) float64 -0.06268 -0.06537 ... -0.2671}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "preprocessor.trend"
    ]
@@ -95,9 +121,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fa88d4a9f00>]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "preprocessor.climatology[\"sst\"].isel(latitude=0, longitude=0).plot()"
    ]
@@ -114,9 +161,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(9.6901858e-20)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "preprocessor.trend[\"slope\"].sst.isel(latitude=0, longitude=0).values"
    ]
@@ -131,7 +189,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -140,9 +198,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Detrended and climatology removed')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "fig, (ax1, ax2) = plt.subplots(nrows=2, figsize=(8, 6))\n",
     "data.sst.isel(latitude=0, longitude=0).plot(ax=ax1)\n",
@@ -154,19 +233,1078 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7fa88d78f850>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "preprocessed_data.sst.sel(time=slice(\"1980-08-01\", \"1980-08-31\")).mean(dim=\"time\").plot()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`preprocess` module can also work with monthly data and weekly data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<defs>\n",
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+       ".xr-wrap {\n",
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+       "  min-width: 300px;\n",
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+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
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+       ".xr-header {\n",
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+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
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+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (longitude: 13, latitude: 5, time: 756)\n",
+       "Coordinates:\n",
+       "  * longitude  (longitude) float64 177.5 182.5 187.5 192.5 ... 227.5 232.5 237.5\n",
+       "  * latitude   (latitude) float64 47.5 42.5 37.5 32.5 27.5\n",
+       "  * time       (time) datetime64[ns] 1959-01-31 1959-02-28 ... 2021-12-31\n",
+       "Data variables:\n",
+       "    sst        (time, latitude, longitude) float32 277.4 277.6 ... 292.3 292.0\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.1 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Wed Jun 14 17:26:04 2023: cdo remapbil,/Users/semv/surfdriv...\n",
+       "    CDO:          Climate Data Operators version 2.2.0 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c09b6d18-8224-41e8-ae6b-092413cbcacf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c09b6d18-8224-41e8-ae6b-092413cbcacf' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>longitude</span>: 13</li><li><span class='xr-has-index'>latitude</span>: 5</li><li><span class='xr-has-index'>time</span>: 756</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9f90af05-fd1b-4117-a1c4-42351628ab09' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9f90af05-fd1b-4117-a1c4-42351628ab09' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>177.5 182.5 187.5 ... 232.5 237.5</div><input id='attrs-02e91f37-239a-44c6-b40f-b16be00e4cd5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02e91f37-239a-44c6-b40f-b16be00e4cd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50a9ed79-1978-4f38-ba9b-a4d9b3683f8a' class='xr-var-data-in' type='checkbox'><label for='data-50a9ed79-1978-4f38-ba9b-a4d9b3683f8a' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([177.5, 182.5, 187.5, 192.5, 197.5, 202.5, 207.5, 212.5, 217.5, 222.5,\n",
+       "       227.5, 232.5, 237.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>47.5 42.5 37.5 32.5 27.5</div><input id='attrs-bb9488aa-c3ac-4887-8fc3-ff6a3c48bed6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb9488aa-c3ac-4887-8fc3-ff6a3c48bed6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5e91386-006e-4cc2-9794-57db633e2223' class='xr-var-data-in' type='checkbox'><label for='data-c5e91386-006e-4cc2-9794-57db633e2223' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([47.5, 42.5, 37.5, 32.5, 27.5])</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'>1959-01-31 ... 2021-12-31</div><input id='attrs-16a1f9e3-fb6d-43b4-809c-76b0dab5c798' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16a1f9e3-fb6d-43b4-809c-76b0dab5c798' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-072b678d-2959-4fe7-8086-14f2342b87b6' class='xr-var-data-in' type='checkbox'><label for='data-072b678d-2959-4fe7-8086-14f2342b87b6' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1959-01-31T00:00:00.000000000&#x27;, &#x27;1959-02-28T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1959-03-31T00:00:00.000000000&#x27;, ..., &#x27;2021-10-31T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2021-11-30T00:00:00.000000000&#x27;, &#x27;2021-12-31T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1f4d289-b57d-4177-b91e-9a02130f7bef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f1f4d289-b57d-4177-b91e-9a02130f7bef' class='xr-section-summary' >Data variables: <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>sst</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>277.4 277.6 277.8 ... 292.3 292.0</div><input id='attrs-9b638dc3-2939-4d12-9089-e3e93b316ca7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b638dc3-2939-4d12-9089-e3e93b316ca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8880bbad-32c4-47ef-ab23-5eaae1410153' class='xr-var-data-in' type='checkbox'><label for='data-8880bbad-32c4-47ef-ab23-5eaae1410153' 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>Sea surface temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([[[277.40073, 277.6279 , 277.7694 , ..., 282.3852 , 282.8096 ,\n",
+       "               nan],\n",
+       "        [282.7301 , 282.57626, 282.02402, ..., 285.72598, 284.86093,\n",
+       "               nan],\n",
+       "        [287.82767, 287.17755, 286.64212, ..., 288.72626, 288.1231 ,\n",
+       "               nan],\n",
+       "        [290.6062 , 289.83264, 289.76697, ..., 291.1458 , 290.19458,\n",
+       "         288.94797],\n",
+       "        [293.87387, 293.7268 , 293.70178, ..., 293.41284, 293.10214,\n",
+       "         292.0388 ]],\n",
+       "\n",
+       "       [[276.75162, 277.16586, 277.42624, ..., 281.86755, 282.37717,\n",
+       "               nan],\n",
+       "        [281.56403, 281.99307, 281.91763, ..., 284.82755, 284.4361 ,\n",
+       "               nan],\n",
+       "        [286.8903 , 287.58203, 286.33282, ..., 287.46478, 286.883  ,\n",
+       "               nan],\n",
+       "        [289.77252, 289.48434, 289.48236, ..., 290.39053, 289.64542,\n",
+       "         288.40143],\n",
+       "        [293.3107 , 293.65695, 293.53024, ..., 292.9035 , 292.55746,\n",
+       "...\n",
+       "               nan],\n",
+       "        [286.20068, 286.26608, 286.02347, ..., 286.75162, 286.50018,\n",
+       "               nan],\n",
+       "        [294.01035, 293.0325 , 292.1922 , ..., 290.85007, 289.14417,\n",
+       "               nan],\n",
+       "        [297.1921 , 296.92133, 296.73325, ..., 292.63638, 291.7731 ,\n",
+       "         289.92053],\n",
+       "        [299.46545, 299.3709 , 298.74316, ..., 293.87393, 293.2437 ,\n",
+       "         293.14737]],\n",
+       "\n",
+       "       [[279.7184 , 280.05756, 280.29132, ..., 282.16486, 282.8297 ,\n",
+       "               nan],\n",
+       "        [285.14566, 284.96268, 284.1657 , ..., 285.62872, 284.71063,\n",
+       "               nan],\n",
+       "        [291.5078 , 291.00693, 290.08035, ..., 289.3486 , 287.78378,\n",
+       "               nan],\n",
+       "        [294.35788, 294.05692, 294.00876, ..., 291.5811 , 290.32263,\n",
+       "         289.0222 ],\n",
+       "        [297.03598, 297.08896, 297.1094 , ..., 293.00586, 292.31573,\n",
+       "         291.99316]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-de9c2530-e8af-4cae-9773-8f01c4bf3eba' class='xr-section-summary-in' type='checkbox'  ><label for='section-de9c2530-e8af-4cae-9773-8f01c4bf3eba' 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>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-37aecd3d-b616-4474-a44d-deae57a231d3' class='xr-index-data-in' type='checkbox'/><label for='index-37aecd3d-b616-4474-a44d-deae57a231d3' 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(Float64Index([177.5, 182.5, 187.5, 192.5, 197.5, 202.5, 207.5, 212.5, 217.5,\n",
+       "              222.5, 227.5, 232.5, 237.5],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-af5a4305-4f25-4c20-a6a2-72f60d95f765' class='xr-index-data-in' type='checkbox'/><label for='index-af5a4305-4f25-4c20-a6a2-72f60d95f765' 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(Float64Index([47.5, 42.5, 37.5, 32.5, 27.5], dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;))</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-00503842-cbfe-44f6-9c5c-d2f013380183' class='xr-index-data-in' type='checkbox'/><label for='index-00503842-cbfe-44f6-9c5c-d2f013380183' 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;1959-01-31&#x27;, &#x27;1959-02-28&#x27;, &#x27;1959-03-31&#x27;, &#x27;1959-04-30&#x27;,\n",
+       "               &#x27;1959-05-31&#x27;, &#x27;1959-06-30&#x27;, &#x27;1959-07-31&#x27;, &#x27;1959-08-31&#x27;,\n",
+       "               &#x27;1959-09-30&#x27;, &#x27;1959-10-31&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2021-03-31&#x27;, &#x27;2021-04-30&#x27;, &#x27;2021-05-31&#x27;, &#x27;2021-06-30&#x27;,\n",
+       "               &#x27;2021-07-31&#x27;, &#x27;2021-08-31&#x27;, &#x27;2021-09-30&#x27;, &#x27;2021-10-31&#x27;,\n",
+       "               &#x27;2021-11-30&#x27;, &#x27;2021-12-31&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=756, freq=&#x27;M&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-77563fba-3973-49f9-ba0c-b29f1ad91526' class='xr-section-summary-in' type='checkbox'  checked><label for='section-77563fba-3973-49f9-ba0c-b29f1ad91526' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.2.1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Jun 14 17:26:04 2023: cdo remapbil,/Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/grid_5.txt /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_2deg_Pacific_175_240E_25_50N_newgrid.nc /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_5deg_Pacific_175_240E_25_50N_newgrid.nc\n",
+       "Wed Jun 14 17:25:22 2023: cdo -setgrid,/Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/grid.txt /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_2deg_Pacific_175_240E_25_50N.nc /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_2deg_Pacific_175_240E_25_50N_newgrid.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.2.0 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (longitude: 13, latitude: 5, time: 756)\n",
+       "Coordinates:\n",
+       "  * longitude  (longitude) float64 177.5 182.5 187.5 192.5 ... 227.5 232.5 237.5\n",
+       "  * latitude   (latitude) float64 47.5 42.5 37.5 32.5 27.5\n",
+       "  * time       (time) datetime64[ns] 1959-01-31 1959-02-28 ... 2021-12-31\n",
+       "Data variables:\n",
+       "    sst        (time, latitude, longitude) float32 277.4 277.6 ... 292.3 292.0\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.1 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Wed Jun 14 17:26:04 2023: cdo remapbil,/Users/semv/surfdriv...\n",
+       "    CDO:          Climate Data Operators version 2.2.0 (https://mpimet.mpg.de..."
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# create monthly data\n",
+    "data_monthly = data.resample(time='M').mean()\n",
+    "data_monthly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preprocessor = preprocess.Preprocessor(\n",
+    "    rolling_window_size=3,\n",
+    "    timescale=\"monthly\",\n",
+    "    detrend=\"linear\",\n",
+    "    subtract_climatology=True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preprocessor.fit(data_monthly)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fa88d7136d0>]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "preprocessor.climatology[\"sst\"].isel(latitude=0, longitude=0).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<defs>\n",
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+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
+       " *\n",
+       " */\n",
+       "\n",
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+       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+       "  --xr-border-color: #1F1F1F;\n",
+       "  --xr-disabled-color: #515151;\n",
+       "  --xr-background-color: #111111;\n",
+       "  --xr-background-color-row-even: #111111;\n",
+       "  --xr-background-color-row-odd: #313131;\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (longitude: 13, latitude: 5, time: 3288)\n",
+       "Coordinates:\n",
+       "  * longitude  (longitude) float64 177.5 182.5 187.5 192.5 ... 227.5 232.5 237.5\n",
+       "  * latitude   (latitude) float64 47.5 42.5 37.5 32.5 27.5\n",
+       "  * time       (time) datetime64[ns] 1959-01-04 1959-01-11 ... 2022-01-02\n",
+       "Data variables:\n",
+       "    sst        (time, latitude, longitude) float32 277.7 277.9 ... 291.9 291.5\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.1 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Wed Jun 14 17:26:04 2023: cdo remapbil,/Users/semv/surfdriv...\n",
+       "    CDO:          Climate Data Operators version 2.2.0 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f6e32e84-d411-445c-a2ef-035647f27cf4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f6e32e84-d411-445c-a2ef-035647f27cf4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>longitude</span>: 13</li><li><span class='xr-has-index'>latitude</span>: 5</li><li><span class='xr-has-index'>time</span>: 3288</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-75dedbc4-e2cd-4c50-a902-0f4054a011d1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-75dedbc4-e2cd-4c50-a902-0f4054a011d1' 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'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>177.5 182.5 187.5 ... 232.5 237.5</div><input id='attrs-abd6672f-22d1-420f-93de-e852bc2c83ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abd6672f-22d1-420f-93de-e852bc2c83ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53e1b283-2447-431a-a4bb-83023b3f80dc' class='xr-var-data-in' type='checkbox'><label for='data-53e1b283-2447-431a-a4bb-83023b3f80dc' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([177.5, 182.5, 187.5, 192.5, 197.5, 202.5, 207.5, 212.5, 217.5, 222.5,\n",
+       "       227.5, 232.5, 237.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>47.5 42.5 37.5 32.5 27.5</div><input id='attrs-e668f4f7-b246-4f98-8f3f-4e23cb1ed030' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e668f4f7-b246-4f98-8f3f-4e23cb1ed030' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71c62154-faa4-47eb-afaa-f13d5fb3a6a9' class='xr-var-data-in' type='checkbox'><label for='data-71c62154-faa4-47eb-afaa-f13d5fb3a6a9' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([47.5, 42.5, 37.5, 32.5, 27.5])</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'>1959-01-04 ... 2022-01-02</div><input id='attrs-a790cdb4-3590-4d1e-9ce5-05f2fb6e88e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a790cdb4-3590-4d1e-9ce5-05f2fb6e88e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-359b84ab-400e-4964-83ba-4d8edb24f4b7' class='xr-var-data-in' type='checkbox'><label for='data-359b84ab-400e-4964-83ba-4d8edb24f4b7' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1959-01-04T00:00:00.000000000&#x27;, &#x27;1959-01-11T00:00:00.000000000&#x27;,\n",
+       "       &#x27;1959-01-18T00:00:00.000000000&#x27;, ..., &#x27;2021-12-19T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2021-12-26T00:00:00.000000000&#x27;, &#x27;2022-01-02T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-247851ba-a9cb-4cbc-8b31-4fe75d90269d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-247851ba-a9cb-4cbc-8b31-4fe75d90269d' class='xr-section-summary' >Data variables: <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>sst</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>277.7 277.9 277.9 ... 291.9 291.5</div><input id='attrs-2345c2ee-c2ba-471c-8937-24347a3cc625' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2345c2ee-c2ba-471c-8937-24347a3cc625' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1c51d97-c0e2-4fb7-ad9a-f88e0dbe2151' class='xr-var-data-in' type='checkbox'><label for='data-d1c51d97-c0e2-4fb7-ad9a-f88e0dbe2151' 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>Sea surface temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([[[277.66852, 277.8844 , 277.9375 , ..., 282.86426, 283.1456 ,\n",
+       "               nan],\n",
+       "        [282.6742 , 282.6958 , 282.34048, ..., 286.32742, 285.1657 ,\n",
+       "               nan],\n",
+       "        [288.11072, 287.68347, 287.04132, ..., 289.23132, 288.3932 ,\n",
+       "               nan],\n",
+       "        [290.91217, 290.3166 , 290.34082, ..., 291.51956, 290.5543 ,\n",
+       "         289.17664],\n",
+       "        [294.4867 , 294.1872 , 294.26318, ..., 293.65778, 293.29797,\n",
+       "         292.1985 ]],\n",
+       "\n",
+       "       [[277.6069 , 277.78702, 277.9086 , ..., 282.54233, 282.94983,\n",
+       "               nan],\n",
+       "        [283.02725, 282.80396, 282.17807, ..., 285.929  , 285.0148 ,\n",
+       "               nan],\n",
+       "        [288.22372, 287.3955 , 286.8698 , ..., 288.9831 , 288.36795,\n",
+       "               nan],\n",
+       "        [290.9692 , 290.1386 , 290.08856, ..., 291.35034, 290.38916,\n",
+       "         289.0759 ],\n",
+       "        [294.20145, 294.00247, 293.9659 , ..., 293.5605 , 293.26157,\n",
+       "...\n",
+       "               nan],\n",
+       "        [284.9085 , 284.67834, 283.8765 , ..., 285.1376 , 284.32806,\n",
+       "               nan],\n",
+       "        [291.08884, 290.94116, 289.75748, ..., 288.95074, 287.43976,\n",
+       "               nan],\n",
+       "        [293.9081 , 293.6846 , 293.54013, ..., 291.20496, 289.9285 ,\n",
+       "         288.69037],\n",
+       "        [296.66522, 296.69873, 296.80203, ..., 292.81348, 292.20053,\n",
+       "         291.69656]],\n",
+       "\n",
+       "       [[279.41714, 279.96906, 280.25067, ..., 281.27374, 281.87842,\n",
+       "               nan],\n",
+       "        [284.58093, 285.1439 , 284.26334, ..., 284.69818, 283.6732 ,\n",
+       "               nan],\n",
+       "        [290.84113, 290.76297, 289.69775, ..., 288.4673 , 286.98627,\n",
+       "               nan],\n",
+       "        [293.4377 , 293.53214, 293.60376, ..., 290.91037, 289.41095,\n",
+       "         288.38275],\n",
+       "        [296.38336, 296.31876, 296.57596, ..., 292.62134, 291.9403 ,\n",
+       "         291.5357 ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e16a665d-06fe-42fb-a4aa-0053aa7bb1e7' class='xr-section-summary-in' type='checkbox'  ><label for='section-e16a665d-06fe-42fb-a4aa-0053aa7bb1e7' 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>longitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6ca2bb78-0ae6-4a0c-8e6c-be1764a8d125' class='xr-index-data-in' type='checkbox'/><label for='index-6ca2bb78-0ae6-4a0c-8e6c-be1764a8d125' 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(Float64Index([177.5, 182.5, 187.5, 192.5, 197.5, 202.5, 207.5, 212.5, 217.5,\n",
+       "              222.5, 227.5, 232.5, 237.5],\n",
+       "             dtype=&#x27;float64&#x27;, name=&#x27;longitude&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>latitude</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-edd02abb-7b23-4a73-b8dd-7e977de99fec' class='xr-index-data-in' type='checkbox'/><label for='index-edd02abb-7b23-4a73-b8dd-7e977de99fec' 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(Float64Index([47.5, 42.5, 37.5, 32.5, 27.5], dtype=&#x27;float64&#x27;, name=&#x27;latitude&#x27;))</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-af105c93-bb7a-40cd-9958-a3cd8fe1a857' class='xr-index-data-in' type='checkbox'/><label for='index-af105c93-bb7a-40cd-9958-a3cd8fe1a857' 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;1959-01-04&#x27;, &#x27;1959-01-11&#x27;, &#x27;1959-01-18&#x27;, &#x27;1959-01-25&#x27;,\n",
+       "               &#x27;1959-02-01&#x27;, &#x27;1959-02-08&#x27;, &#x27;1959-02-15&#x27;, &#x27;1959-02-22&#x27;,\n",
+       "               &#x27;1959-03-01&#x27;, &#x27;1959-03-08&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2021-10-31&#x27;, &#x27;2021-11-07&#x27;, &#x27;2021-11-14&#x27;, &#x27;2021-11-21&#x27;,\n",
+       "               &#x27;2021-11-28&#x27;, &#x27;2021-12-05&#x27;, &#x27;2021-12-12&#x27;, &#x27;2021-12-19&#x27;,\n",
+       "               &#x27;2021-12-26&#x27;, &#x27;2022-01-02&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=3288, freq=&#x27;W-SUN&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-89f29540-59e9-4d85-861e-e8cafaf57503' class='xr-section-summary-in' type='checkbox'  checked><label for='section-89f29540-59e9-4d85-861e-e8cafaf57503' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.2.1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Jun 14 17:26:04 2023: cdo remapbil,/Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/grid_5.txt /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_2deg_Pacific_175_240E_25_50N_newgrid.nc /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_5deg_Pacific_175_240E_25_50N_newgrid.nc\n",
+       "Wed Jun 14 17:25:22 2023: cdo -setgrid,/Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/grid.txt /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_2deg_Pacific_175_240E_25_50N.nc /Users/semv/surfdrive/Scripts/escience/s2spy/tests/test_rgdr/test_data/sst_daily_1950-2021_2deg_Pacific_175_240E_25_50N_newgrid.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.2.0 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (longitude: 13, latitude: 5, time: 3288)\n",
+       "Coordinates:\n",
+       "  * longitude  (longitude) float64 177.5 182.5 187.5 192.5 ... 227.5 232.5 237.5\n",
+       "  * latitude   (latitude) float64 47.5 42.5 37.5 32.5 27.5\n",
+       "  * time       (time) datetime64[ns] 1959-01-04 1959-01-11 ... 2022-01-02\n",
+       "Data variables:\n",
+       "    sst        (time, latitude, longitude) float32 277.7 277.9 ... 291.9 291.5\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.1 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Wed Jun 14 17:26:04 2023: cdo remapbil,/Users/semv/surfdriv...\n",
+       "    CDO:          Climate Data Operators version 2.2.0 (https://mpimet.mpg.de..."
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# create weekly data\n",
+    "data_weekly = data.resample(time='W').mean()\n",
+    "data_weekly"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "preprocessor = preprocess.Preprocessor(\n",
+    "    rolling_window_size=5,\n",
+    "    timescale=\"weekly\",\n",
+    "    detrend=\"linear\",\n",
+    "    subtract_climatology=True,\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "preprocessor.fit(data_weekly)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fa88945d240>]"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "preprocessor.climatology[\"sst\"].isel(latitude=0, longitude=0).plot()"
+   ]
   }
  ],
  "metadata": {
diff --git a/pyproject.toml b/pyproject.toml
index 1f4241b..ca1bf35 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ dynamic = ["version"]
 description = "python package for s2s forecasts with ai"
 readme = "README.md"
 license = "Apache-2.0"
-requires-python = ">=3.8,<3.11"
+requires-python = ">3.8,<3.11"
 authors = [
   {email = "y.liu@esciencecenter.nl"},
   {name = "Yang Liu, Bart Schilperoort, Peter Kalverla, Jannes van Ingen, Sem Vijverberg"}
@@ -30,7 +30,6 @@ classifiers = [
     "License :: OSI Approved :: Apache Software License",
     "Natural Language :: English",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
 ]
diff --git a/s2spy/preprocess.py b/s2spy/preprocess.py
index 71b91eb..8f50fbc 100644
--- a/s2spy/preprocess.py
+++ b/s2spy/preprocess.py
@@ -1,4 +1,6 @@
 """Preprocessor for s2spy workflow."""
+import warnings
+from typing import Literal
 from typing import Tuple
 from typing import Union
 import numpy as np
@@ -61,9 +63,39 @@ def _subtract_trend(data: Union[xr.DataArray, xr.Dataset], method: str, trend: d
     raise NotImplementedError
 
 
-def _get_climatology(data: Union[xr.Dataset, xr.DataArray]):
+def _get_climatology(
+    data: Union[xr.Dataset, xr.DataArray],
+    timescale: Literal["monthly", "weekly", "daily"],
+):
     """Calculate the climatology of timeseries data."""
-    return data.groupby("time.dayofyear").mean("time")
+    _check_data_resolution_match(data, timescale)
+    if timescale == "monthly":
+        climatology = data.groupby("time.month").mean("time")
+    elif timescale == "weekly":
+        climatology = data.groupby(data["time"].dt.isocalendar().week).mean("time")
+    elif timescale == "daily":
+        climatology = data.groupby("time.dayofyear").mean("time")
+    else:
+        raise ValueError("Given timescale is not supported.")
+
+    return climatology
+
+
+def _subtract_climatology(
+    data: Union[xr.Dataset, xr.DataArray],
+    timescale: Literal["monthly", "weekly", "daily"],
+    climatology: Union[xr.Dataset, xr.DataArray],
+):
+    if timescale == "monthly":
+        deseasonalized = data.groupby("time.month") - climatology
+    elif timescale == "weekly":
+        deseasonalized = data.groupby(data["time"].dt.isocalendar().week) - climatology
+    elif timescale == "daily":
+        deseasonalized = data.groupby("time.dayofyear") - climatology
+    else:
+        raise ValueError("Given timescale is not supported.")
+
+    return deseasonalized
 
 
 def _check_input_data(data: Union[xr.DataArray, xr.Dataset]):
@@ -88,12 +120,56 @@ def _check_input_data(data: Union[xr.DataArray, xr.Dataset]):
         )
 
 
+def _check_temporal_resolution(
+    timescale: Literal["monthly", "weekly", "daily"]
+) -> Literal["monthly", "weekly", "daily"]:
+    support_temporal_resolution = ["monthly", "weekly", "daily"]
+    if timescale not in support_temporal_resolution:
+        raise ValueError(
+            "Given temporal resoltuion is not supported."
+            "Please choose from 'monthly', 'weekly', 'daily'."
+        )
+    return timescale
+
+
+def _check_data_resolution_match(
+    data: Union[xr.DataArray, xr.Dataset],
+    timescale: Literal["monthly", "weekly", "daily"],
+):
+    """Check if the temporal resolution of input is the same as given timescale."""
+    timescale_dict = {
+        "monthly": np.timedelta64(1, "M"),
+        "weekly": np.timedelta64(1, "W"),
+        "daily": np.timedelta64(1, "D"),
+    }
+    time_intervals = np.diff(data["time"].to_numpy())
+    temporal_resolution = np.median(time_intervals).astype("timedelta64[D]")
+    if timescale == "monthly":
+        temporal_resolution = temporal_resolution.astype(int)
+        min_days, max_days = (28, 31)
+        if not max_days >= temporal_resolution >= min_days:
+            warnings.warn(
+                "The temporal resolution of data does not completely match "
+                "the target timescale. Please check your input data.",
+                stacklevel=1,
+            )
+
+    elif timescale in timescale_dict:
+        if timescale_dict[timescale].astype("timedelta64[D]") != temporal_resolution:
+            warnings.warn(
+                "The temporal resolution of data does not completely match "
+                "the target timescale. Please check your input data.",
+                stacklevel=1,
+            )
+
+
 class Preprocessor:
     """Preprocessor for s2s data."""
 
-    def __init__(
+    def __init__(  # noqa: PLR0913
         self,
         rolling_window_size: Union[int, None],
+        timescale: Literal["monthly", "weekly", "daily"],
         rolling_min_periods: int = 1,
         subtract_climatology: bool = True,
         detrend: Union[str, None] = "linear",
@@ -121,11 +197,14 @@ def __init__(
                 climatology of the data. Defaults to True.
             detrend (optional): Which method to use for detrending. Currently the only method
                 supported is "linear". If you want to skip detrending, set this to None.
+            timescale: Temporal resolution of input data.
         """
         self._window_size = rolling_window_size
         self._min_periods = rolling_min_periods
         self._detrend = detrend
         self._subtract_climatology = subtract_climatology
+        if subtract_climatology:
+            self._timescale = _check_temporal_resolution(timescale)
 
         self._climatology: Union[xr.DataArray, xr.Dataset]
         self._trend: dict
@@ -149,15 +228,16 @@ def fit(self, data: Union[xr.DataArray, xr.Dataset]) -> None:
             data_rolling = data
 
         if self._subtract_climatology:
-            self._climatology = _get_climatology(data_rolling)
+            self._climatology = _get_climatology(data_rolling, self._timescale)
 
         if self._detrend is not None:
-            self._trend = _get_trend(
-                data_rolling.groupby("time.dayofyear") - self._climatology
-                if self._subtract_climatology
-                else data_rolling,
-                self._detrend,
-            )
+            if self._subtract_climatology:
+                deseasonalized = _subtract_climatology(
+                    data_rolling, self._timescale, self._climatology
+                )
+                self._trend = _get_trend(deseasonalized, self._detrend)
+            else:
+                self._trend = _get_trend(data_rolling, self._detrend)
 
         self._is_fit = True
 
@@ -179,7 +259,7 @@ def transform(
             )
 
         if self._subtract_climatology:
-            d = data.groupby("time.dayofyear") - self._climatology
+            d = _subtract_climatology(data, self._timescale, self._climatology)
         else:
             d = data
 


Test patch:
diff --git a/tests/test_preprocess.py b/tests/test_preprocess.py
index 99364eb..6e0c610 100644
--- a/tests/test_preprocess.py
+++ b/tests/test_preprocess.py
@@ -1,5 +1,4 @@
-"""Tests for the s2spy.preprocess module.
-"""
+"""Tests for the s2spy.preprocess module."""
 import numpy as np
 import pytest
 import scipy.signal
@@ -55,14 +54,47 @@ def test_get_and_subtract_linear_trend(self, raw_field):
         result = preprocess._subtract_trend(raw_field, "linear", trend)
         np.testing.assert_array_almost_equal(result["sst"], expected["sst"])
 
-    def test_get_climatology(self, raw_field):
-        result = preprocess._get_climatology(raw_field)
+    def test_check_temporal_resolution(self):
+        with pytest.raises(ValueError):
+            preprocess._check_temporal_resolution("hourly")  # type: ignore
+
+    def test_get_climatology_daily(self, raw_field):
+        result = preprocess._get_climatology(raw_field, timescale="daily")
         expected = (
             raw_field["sst"].sel(time=slice("2010-01-01", "2010-12-31")).data
             + raw_field["sst"].sel(time=slice("2011-01-01", "2011-12-31")).data
         ) / 2
         np.testing.assert_array_almost_equal(result["sst"], expected)
 
+    def test_get_climatology_weekly(self, raw_field):
+        raw_field_weekly = raw_field.resample(time="W").mean()
+        result = preprocess._get_climatology(raw_field_weekly, timescale="weekly")
+        # need to consider the actual calendar week number for the expected climatology
+        raw_field_weekly["time"] = raw_field_weekly["time"].dt.isocalendar().week
+        expected = raw_field_weekly.groupby("time").mean()
+        np.testing.assert_array_almost_equal(result["sst"], expected["sst"])
+
+    def test_get_climatology_monthly(self, raw_field):
+        raw_field_monthly = raw_field.resample(time="M").mean()
+        result = preprocess._get_climatology(raw_field_monthly, timescale="monthly")
+        expected = (
+            raw_field_monthly["sst"].sel(time=slice("2010-01-01", "2010-12-31")).data
+            + raw_field_monthly["sst"].sel(time=slice("2011-01-01", "2011-12-31")).data
+        ) / 2
+        np.testing.assert_array_almost_equal(result["sst"], expected)
+
+    def test_get_climatology_wrong_timescale(self, raw_field):
+        with pytest.raises(ValueError):
+            preprocess._get_climatology(raw_field, timescale="hourly")  # type: ignore
+
+    @pytest.mark.parametrize("timescale", ("weekly", "monthly"))
+    def test_check_data_resolution_mismatch(self, raw_field, timescale):
+        with pytest.warns(UserWarning):
+            preprocess._check_data_resolution_match(raw_field, timescale)
+
+    def test_check_data_resolution_match(self, raw_field):
+        preprocess._check_data_resolution_match(raw_field, "daily")
+
 
 class TestPreprocessor:
     """Test preprocessor."""
@@ -71,6 +103,7 @@ class TestPreprocessor:
     def preprocessor(self):
         prep = preprocess.Preprocessor(
             rolling_window_size=25,
+            timescale="daily",
             detrend="linear",
             subtract_climatology=True,
         )
@@ -80,6 +113,7 @@ def preprocessor(self):
     def preprocessor_no_rolling(self, request):
         prep = preprocess.Preprocessor(
             rolling_window_size=request.param,
+            timescale="monthly",
             detrend=None,
             subtract_climatology=True,
         )
@@ -89,6 +123,7 @@ def preprocessor_no_rolling(self, request):
     def preprocessor_no_climatology(self):
         prep = preprocess.Preprocessor(
             rolling_window_size=25,
+            timescale="daily",
             detrend="linear",
             subtract_climatology=False,
         )
@@ -98,6 +133,7 @@ def preprocessor_no_climatology(self):
     def preprocessor_no_detrend(self):
         prep = preprocess.Preprocessor(
             rolling_window_size=25,
+            timescale="daily",
             detrend=None,
             subtract_climatology=True,
         )
@@ -116,6 +152,7 @@ def raw_field(self):
     def test_init(self):
         prep = preprocess.Preprocessor(
             rolling_window_size=25,
+            timescale="weekly",
             detrend="linear",
             subtract_climatology=True,
         )
@@ -130,7 +167,7 @@ def test_fit(self, preprocessor, raw_field):
     def test_fit_no_rolling(self, preprocessor_no_rolling, raw_field):
         preprocessor_no_rolling.fit(raw_field)
         assert preprocessor_no_rolling.climatology == preprocess._get_climatology(
-            raw_field
+            raw_field, timescale="daily"
         )
 
     def test_transform(self, preprocessor, raw_field):
@@ -163,6 +200,7 @@ def test_fit_and_transform_no_detrend(self, preprocessor_no_detrend, raw_field):
     def test_fit_and_transform_no_climatology_and_detrend(self, raw_field):
         prep = preprocess.Preprocessor(
             rolling_window_size=10,
+            timescale="daily",
             detrend=None,
             subtract_climatology=False,
         )