Use new source of T2 data

0_prepare_data.ipynb

@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 2,
    "id": "7b2a7f44-b0cb-4471-a0c6-e56da23caf86",
    "metadata": {},
    "outputs": [],
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "36b9f49e-32e6-4544-a9d3-f6a8ba49d867",
    "metadata": {},
    "outputs": [],
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "78a4350c-59fb-479a-b7cd-e2bf9b996d36",
    "metadata": {},
    "outputs": [],
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "53cb9cc3-0e56-4da4-920b-2f071a0846fb",
    "metadata": {},
    "outputs": [],
@@ -89,32 +89,53 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "0e4d0268-208f-45c7-bb0a-b5e8d3c7c1f7",
+   "execution_count": 10,
+   "id": "87860fa8-0a9c-4304-9c3c-94561c3e966c",
    "metadata": {},
    "outputs": [],
    "source": [
     "# air temperature at the height of 2 m with the shape\n",
-    "# (number of days, number of latitudes, number of longitudes)\n",
-    "\n",
-    "# contains temperature values depending on (d, lat, lon)\n",
-    "\n",
+    "# (number of days, number of hours, number of latitudes, number of longitudes)\n",
+    "# contains temperature values depending on (d, h, lat, lon)\n",
     "#   d (axis 0) is the number of a day starting with 0 and ending with 5113\n",
     "#              every third day is taken\n",
-    "# d = 0 corresponds to 1 Jan 1980, d = 5113 corresponds to 30 Dec 2021\n",
+    "#              d = 0 corresponds to 1 Jan 1980, \n",
+    "#              d = 5113 corresponds to 30 Dec 2021\n",
     "#              d = 4991 corresponds to 29 Dec 2020\n",
     "#              (we will restrict our attention to 1980–2020)\n",
-    "\n",
+    "#   h (axis 1) is the hour of the day (an integer in [0, 24])\n",
+    "#              the values corresponding to h = 0 and h = 24 are the same\n",
     "# lat (axis 2) describes the latitude (an integer in [0, 179]) \n",
-    "\n",
     "# lon (axis 3) describes the longitude (an integer in [0, 359])\n",
     "\n",
-    "wrf_T2_data = np.load(f\"{src_path}/T2-MAP-FULL.npy\")[:wrf_N_days]"
+    "wrf_T2_data = np.load(f\"{src_path}/WRF-T2-MAP.npy\")[:wrf_N_days]\n",
+    "wrf_T2_data_DAYxLAT = wrf_T2_data.mean(axis=(1, 3))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
+   "id": "1124d9f9-95d9-4c02-8176-82b9c0331d34",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(4992, 180)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wrf_T2_data_DAYxLAT.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
    "id": "ec569ffd-93c2-4490-8ba1-69af4fab8f23",
    "metadata": {},
    "outputs": [],
@@ -129,11 +150,32 @@
     "    ]\n",
     "\n",
     "    # putting values at specific month into averaged array\n",
-    "    wrf_mon_T2[:, month_idx] = wrf_mean_T2[monthly_indicies].mean(axis=0)\n",
+    "    wrf_mon_T2[:, month_idx] = wrf_T2_data_DAYxLAT[monthly_indicies].mean(axis=0)-273.15\n",
     "\n",
     "np.save(f\"./data/WRF/WRF_T2_LATxMON.npy\",wrf_mon_T2)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "b480c05f-4b06-4d33-9527-dbe2655ed251",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "27.894258059212177"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "wrf_mon_T2.max()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "46d4f093-a420-42c7-b885-a8409d9d8ee4",