cice_grid_valiation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6c12bc09-4fe2-41ee-abe2-9c2a3e4eace9",
   "metadata": {},
   "source": [
    "Use the new cice grid scripts and compare it to the old results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9e68dc25-ad27-4288-9182-c474a477b57d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:23.784342Z",
     "iopub.status.busy": "2024-03-08T04:27:23.783231Z",
     "iopub.status.idle": "2024-03-08T04:27:27.792975Z",
     "shell.execute_reply": "2024-03-08T04:27:27.792175Z",
     "shell.execute_reply.started": "2024-03-08T04:27:23.784284Z"
    }
   },
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "daae67c0-1e0d-4314-8432-72eb005f3be4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:27.794288Z",
     "iopub.status.busy": "2024-03-08T04:27:27.793998Z",
     "iopub.status.idle": "2024-03-08T04:27:27.797938Z",
     "shell.execute_reply": "2024-03-08T04:27:27.797266Z",
     "shell.execute_reply.started": "2024-03-08T04:27:27.794268Z"
    }
   },
   "outputs": [],
   "source": [
    "_script_path = '/g/data/tm70/as2285/om3-scripts/grid_generation/Gen_CICE_grid.py'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "081c2690-8bcf-498c-bfea-d7ad006ecec1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:27.798591Z",
     "iopub.status.busy": "2024-03-08T04:27:27.798430Z",
     "iopub.status.idle": "2024-03-08T04:27:27.806061Z",
     "shell.execute_reply": "2024-03-08T04:27:27.805408Z",
     "shell.execute_reply.started": "2024-03-08T04:27:27.798575Z"
    }
   },
   "outputs": [],
   "source": [
    "_data_dir = '/g/data/ik11/inputs/access-om2/input_20200530/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4985bfe6-40d5-4fad-b833-7d9ae4cfd82e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:27.807321Z",
     "iopub.status.busy": "2024-03-08T04:27:27.807116Z",
     "iopub.status.idle": "2024-03-08T04:27:27.818107Z",
     "shell.execute_reply": "2024-03-08T04:27:27.817270Z",
     "shell.execute_reply.started": "2024-03-08T04:27:27.807300Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/g/data/tm70/as2285/om3-scripts/grid_generation\n"
     ]
    }
   ],
   "source": [
    "cd /g/data/tm70/as2285/om3-scripts/grid_generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6fe121d6-5515-4ab2-80c4-60a22c5a045e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:27.819205Z",
     "iopub.status.busy": "2024-03-08T04:27:27.818947Z",
     "iopub.status.idle": "2024-03-08T04:27:27.822901Z",
     "shell.execute_reply": "2024-03-08T04:27:27.822133Z",
     "shell.execute_reply.started": "2024-03-08T04:27:27.819178Z"
    }
   },
   "outputs": [],
   "source": [
    "res = ['1deg', '025deg', '01deg']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "278b706b-70df-4aaa-9cbb-80e2473b8c6a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:21:55.262693Z",
     "iopub.status.busy": "2024-03-08T04:21:55.261632Z",
     "iopub.status.idle": "2024-03-08T04:22:18.336806Z",
     "shell.execute_reply": "2024-03-08T04:22:18.334832Z",
     "shell.execute_reply.started": "2024-03-08T04:21:55.262640Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3.0\n",
      "NetCDF file created successfully.\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! python3 {_script_path} {_data_dir}/mom_{res[0]}/ocean_hgrid.nc grid_{res[0]}.nc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4ed8aab4-c58a-4380-895e-bf5418878f1a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:22:18.343475Z",
     "iopub.status.busy": "2024-03-08T04:22:18.342530Z",
     "iopub.status.idle": "2024-03-08T04:22:35.582919Z",
     "shell.execute_reply": "2024-03-08T04:22:35.581165Z",
     "shell.execute_reply.started": "2024-03-08T04:22:18.343419Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3.0\n",
      "NetCDF file created successfully.\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! python3 {_script_path} {_data_dir}/mom_{res[1]}/ocean_hgrid.nc grid_{res[1]}.nc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "18db72ad-8c6a-47b4-abcd-afba4ed28e09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:22:35.587869Z",
     "iopub.status.busy": "2024-03-08T04:22:35.586947Z",
     "iopub.status.idle": "2024-03-08T04:23:10.061223Z",
     "shell.execute_reply": "2024-03-08T04:23:10.059759Z",
     "shell.execute_reply.started": "2024-03-08T04:22:35.587814Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3.0\n",
      "NetCDF file created successfully.\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! python3 {_script_path} {_data_dir}/mom_{res[2]}/ocean_hgrid.nc grid_{res[2]}.nc"
   ]
  },
  {
   "cell_type": "raw",
   "id": "8e17427a-d30e-4a85-83e3-8b0f6a0e0d74",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-07T03:41:41.716635Z",
     "iopub.status.busy": "2024-03-07T03:41:41.715839Z",
     "iopub.status.idle": "2024-03-07T03:41:41.739999Z",
     "shell.execute_reply": "2024-03-07T03:41:41.738838Z",
     "shell.execute_reply.started": "2024-03-07T03:41:41.716566Z"
    }
   },
   "source": [
    "mom_grid = xr.open_dataset(f'{_data_dir}/mom_{iRes}/ocean_hgrid.nc')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fdc09cd-4d78-4846-abcc-3ea51774fdfb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T03:55:19.854846Z",
     "iopub.status.busy": "2024-03-08T03:55:19.854431Z",
     "iopub.status.idle": "2024-03-08T03:55:19.862377Z",
     "shell.execute_reply": "2024-03-08T03:55:19.861511Z",
     "shell.execute_reply.started": "2024-03-08T03:55:19.854809Z"
    }
   },
   "source": [
    "Let set our tolerance to 2e-6 as precision of float32 is 1e.6:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c9c5d695-2a7b-432e-9c53-539477a9c1bd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:23:10.067150Z",
     "iopub.status.busy": "2024-03-08T04:23:10.066070Z",
     "iopub.status.idle": "2024-03-08T04:23:10.075453Z",
     "shell.execute_reply": "2024-03-08T04:23:10.074472Z",
     "shell.execute_reply.started": "2024-03-08T04:23:10.067085Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "finfo(resolution=1e-06, min=-3.4028235e+38, max=3.4028235e+38, dtype=float32)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.finfo(np.float32)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce83e733-da52-4211-9a05-0c2366d67e4b",
   "metadata": {},
   "source": [
    "Plot all the differences in all vars and resolutions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "91128fe7-9864-474a-9677-47264e8240f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:29:45.510599Z",
     "iopub.status.busy": "2024-03-08T04:29:45.509864Z",
     "iopub.status.idle": "2024-03-08T04:31:11.995163Z",
     "shell.execute_reply": "2024-03-08T04:31:11.994273Z",
     "shell.execute_reply.started": "2024-03-08T04:29:45.510541Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1deg\n",
      "new vars not in old?\n",
      "set()\n",
      "missing vars in new?\n",
      "{'hun', 'hue', 'lonu_bonds', 'latt_bonds', 'latu_bonds', 'lont_bonds'}\n",
      "025deg\n",
      "new vars not in old?\n",
      "set()\n",
      "missing vars in new?\n",
      "set()\n",
      "01deg\n",
      "new vars not in old?\n",
      "set()\n",
      "missing vars in new?\n",
      "{'clon_t', 'clon_u', 'clat_u', 'clat_t'}\n"
     ]
    },
    {
     "data": {
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/2W7/sccem/e+970ZN25cjjzyyPzgBz/Ir3/963z/+9/fbn/yKgBA1/NtBgAolQ3plQ01vI5wQ816pjvZvK5na2trRowYUd2/cuXKanV9S0tL1q9fn1WrVrWrTlq5cmUmTZpUbfPHP/5xi/7/9Kc/bVGl/1JNTU1pamrqlLEAnUslPZRIV1XSp8Zr0he165vGc/rpp+eWW27JXXfdlTe84Q3bbTtixIiMHj06jz32WBJ5FQB6KudXG4OzCwAA8DJjxoxJS0tLFixYUN23fv36LFy4sHpCc/z48enbt2+7NitWrMjDDz9cbTNx4sS0tbXlgQceqLa5//7709bWVm0DNBaT9FAelV7ej3RfRVHktNNOy7e//e3ccccdGTNmzCs+5umnn87y5curF5nKqwAA5aWSHgAolaKoZGNRu9KkooZ901jWrFmT3/zmN9Xby5Yty5IlSzJkyJDsvvvumTFjRmbPnp2xY8dm7NixmT17dnbZZZccd9xxSZLm5uaceOKJOfPMM7PbbrtlyJAhOeuss7LvvvtmypQpSZK99torhx9+eE466aR87WtfS5J84hOfyBFHHJE999yz/oMGdppJQSiPrno/9qrxuvG9rElPkk9+8pO54YYb8j//8z8ZNGhQdX345ubmDBgwIGvWrMmsWbPywQ9+MCNGjMjvfve7nHvuuRk6dGg+8IEPVNvKqwDQ8zi/2hhM0gMA0CP99Kc/zSGHHFK9PXPmzCTJ8ccfn3nz5uXss8/O2rVrc+qpp2bVqlWZMGFCbrvttgwaNKj6mEsuuSR9+vTJMccck7Vr1+bQQw/NvHnz0rt372qb66+/PmeccUamTp2aJDnqqKMyd+7cOo0S6Gy9+vXt6kMA/qpXP6e16L4uv/zyJMnkyZPb7b/66qtzwgknpHfv3nnooYdy7bXX5plnnsmIESNyyCGH5KabbpJXAQAagG8zAECpbEglG1K7qzFr2TeNZfLkySmKbS/6WqlUMmvWrMyaNWubbfr375/LLrssl1122TbbDBkyJNddd93OHCpQIr1U0kNpdNX7sXelxmvSi6sk282pSTJgwID88Ic/fMV+5FUA6HmcX20Mzi4AAADADrImPZSH9yMAANCoVNIDAKWyoeiVDUXtTrhu2H5BCgBsl0lBKI+uej/2rvGa9LXsGwCA7s/51cbg7AIAAADsoIqfu4fSqFS8HwEAgMbk2wwAUCobU/n/s/f/cVrXdb74/7hmkAENRpFgYBcRWzMLaz1QCGViGkqrZnpWy43Vs2Z6/LWIHjdyd0NPwS1PKScpSz8e8Wf6vZ2yHyeXxFUpj5hIUup6WDtRYDGRhjNqBjrX+/sHOacRRJyZ98x1zdzvt9vrdnPe1+t6Xa/X1OU8fb7ez/cr1TSU2LpXmfSVr3wlkyZNyrBhwzJlypT88Ic/3Gn/FStWZMqUKRk2bFj222+/fPWrX33NvrfddlsqlUqOP/74bs0NgL6jkh5qR/9V0pffAACgu+RX64PsAgDA67j99tszd+7cXHLJJXnkkUdy6KGHZvbs2Vm/fv0O+69bty4f+tCHcuihh+aRRx7Jpz/96Zx//vn5xje+sV3fX/7yl7noooty6KGHlr0MAHpB41CnxkGt8H0EAID6IL+6PZv0AEBN6Uil9PZGXXHFFTn99NPziU98IgceeGAWL16cCRMm5Oqrr95h/69+9avZZ599snjx4hx44IH5xCc+kb/7u7/LF77wha5r7ejI3/zN3+TSSy/Nfvvt163fFwB9y+PuoXZUGvqn5PyVM+nLbAAA0F3yq/VBdgEAGJTa29u7tC1btuyw39atW7N69erMmjWry/VZs2blgQce2OF7Vq5cuV3/o446Kg8//HBeeumlzmuXXXZZ3vzmN+f000/v4WoA6Csedw+1w/cRAAD6j/xqz/ivGQCgpnQUDaW3JJkwYUKam5s726JFi3Y4n6effjodHR0ZO3Zsl+tjx45Na2vrDt/T2tq6w/4vv/xynn766STJ//7f/zvXXXddrr322p7+ygDoQzYFoXb01/exoVIpvQEAQHfJr9YHh3cBAIPShg0bMnLkyM6fm5qadtq/8qpkaVEU2117vf6vXH/uuefy8Y9/PNdee21Gjx79RqcOQD/yuHuoHZWK7yMAAPQX+dWesUkPANSUaiqpduNcozcyfpKMHDmySxD5WkaPHp3Gxsbt7urctGnTdndzvqKlpWWH/YcMGZK99947jz/+eH7xi1/k2GOP/X/zqlaTJEOGDMnatWvzlre85Q2tC4C+0Th0t/6eAvBHDf30faw0VlJpKC9e3VmiEgAAXo/8an3kV91yDACwE0OHDs2UKVOyfPnyLteXL1+eGTNm7PA906dP367/XXfdlalTp2a33XbL2972tjz66KNZs2ZNZzvuuONy+OGHZ82aNZkwYUJp6wGgZzzuHmqH7yMAANQ++dUdU0kPANSUahrSUeJ9hNUUb/g98+bNy5w5czJ16tRMnz4911xzTdavX5+zzjorSTJ//vz86le/yo033pgkOeuss7JkyZLMmzcvZ5xxRlauXJnrrrsuX//615Mkw4YNy+TJk7t8xp577pkk210HoLZ43D3Ujv76PjY0VtJQYiW9M+kBAOgJ+dX6yK/apAcAeB0nn3xynnnmmVx22WXZuHFjJk+enDvvvDMTJ05MkmzcuDHr16/v7D9p0qTceeedueCCC/LlL38548ePz5e+9KWceOKJ/bUEAHqJyl2oHb6PAABQH+RXt2eTHgBgF5x99tk5++yzd/ja0qVLt7t22GGH5cc//vEuj7+jMQCoPTYFoXaUeS48AADQu+RXu7JJDwDUlI6iIR1FeRsgHcUbfxwTALzC4+6hdvTb97GxodzProhXAQDoPvnV+iC7AAAAALuo0tDY31MA/sj3EQAAqFcq6QGAmlJNQ6ol3kdYjTs9AegBm4JQO/rp+1hpqKTSWN6j9ivxGH8AALpPfrU+qKQHAACAXeVx91A7fB8BAIA6pZIeAKgpHUUlHUV51UNljg3AwFfZbWh/TwH4o/76PjY0VtJQYiV9g0p6AAB6QH61PrjlGAAAAHaVx91D7VBJDwAA1CmV9ABATelIQzpKvI+ww5lJAPRApaHBXxKoEZV+2qSvNDSU+tmVwr9lAADoPvnV+uCWYwAAANhVKumhdlR8HwEAgPqkkh4AqCnVoiHVorz7CKsqkwDoCZv0UDv66fvoTHoAAGqZ/Gp9UEkPAAAAu6i/Hq8NbM/3EQAAqFcq6QGAmuLMJABqmkp6qB399H2sNFZSKbGSvqKSHgCAHpBfrQ9uOQYAAIBdZZMeaodKegAAoE6ppAcAako1SUdRXvVQtbSRARgMKo026aFW9Nf3cVslfXk3CFRErAAA9ID8an1wyzEAAADsKpW7UDt8HwEAgDqlkh4AqCnVNKRa4n2EZY4NwCDgcfdQO/rp+9jQWElDiWfSNziTHgCAHpBfrQ9+iwAAALCLKjbpoWb4PgIAAPVKJT0AUFM6ioZ0FOXdR1jm2AAMAh6vDbWj0j/fx0qlkkpDedXulapKegAAuk9+tT74LQIAAMAuUrkLtcP3EQAAqFcq6QGAmlJNJdUSz+Esc2wABgGbglA7+unJFg2NDWloLO+zG1QmAQDQA/Kr9UHUDwAAALvK4+6hdvg+AgAAdUolPQBQU5yZBEAtqzSqpIda0V/fx0pjJZXGEs+kL1QmAQDQffKr9cFvEQAAAHaVx91D7fB9BAAA6pRKegCgpnSkIR0l3kdY5tgADAI2BaF29NP3USU9AAC1TH61PvTrb3HRokV597vfnREjRmTMmDE5/vjjs3bt2i59TjvttFQqlS7tkEMO6dJny5YtOe+88zJ69OjsscceOe644/LUU0/15VIAAAAYBCrOwIaa4fsIAADUq379r5kVK1bknHPOyYMPPpjly5fn5ZdfzqxZs/LCCy906Xf00Udn48aNne3OO+/s8vrcuXNzxx135Lbbbsv999+f559/Psccc0w6Ojr6cjkAQC+oFpXSGwB0m0p6qB2V/vk+NjQ2lN4AAKC75FfrQ78+7n7ZsmVdfr7++uszZsyYrF69Ou9///s7rzc1NaWlpWWHY7S1teW6667LTTfdlCOPPDJJcvPNN2fChAm5++67c9RRR5W3AAAAAAaXis0zqBkVyUEAAKA+1dSZ9G1tbUmSUaNGdbl+3333ZcyYMdlzzz1z2GGH5XOf+1zGjBmTJFm9enVeeumlzJo1q7P/+PHjM3ny5DzwwAM73KTfsmVLtmzZ0vlze3t7GcsBALqhWvKZSVVnJgHQEzbpoXb01/ex5DPpozIJAIAekF+tDzXzWyyKIvPmzcv73ve+TJ48ufP67Nmzc8stt+See+7JF7/4xaxatSof+MAHOjfZW1tbM3To0Oy1115dxhs7dmxaW1t3+FmLFi1Kc3NzZ5swYUJ5CwMAAGDAKGzSQ83wfQQAAOpVzVTSn3vuufnpT3+a+++/v8v1k08+ufOfJ0+enKlTp2bixIn53ve+lxNOOOE1xyuKIpXXeOzZ/PnzM2/evM6f29vbbdQDQI2oFg2pFiXe6Vni2AAMAjYFoXb00/exoVJJQ0N51e4NHuMPAEAPyK/Wh5r4LZ533nn5zne+k3vvvTd//ud/vtO+48aNy8SJE/Pkk08mSVpaWrJ169Zs3ry5S79NmzZl7NixOxyjqakpI0eO7NIAAADgddk8g9rh+wgAANSpft2kL4oi5557br75zW/mnnvuyaRJk173Pc8880w2bNiQcePGJUmmTJmS3XbbLcuXL+/ss3Hjxjz22GOZMWNGaXMHAMrRkUrpDQAAuqvS2FB6AwCA7pJfrQ/9GvWfc845ufnmm3PrrbdmxIgRaW1tTWtra1588cUkyfPPP5+LLrooK1euzC9+8Yvcd999OfbYYzN69Oh85CMfSZI0Nzfn9NNPz4UXXph//dd/zSOPPJKPf/zjOeigg3LkkUf25/IAAAAYaBpsnkHN8H1Mkvz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      "text/plain": [
       "<Figure size 2500x8000 with 60 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(25,80))\n",
    "\n",
    "for i,iRes in enumerate(res):\n",
    "\n",
    "    old_cice_grid = xr.open_dataset(f'{_data_dir}/cice_{iRes}/grid.nc')\n",
    "    new_cice_grid = xr.open_dataset(f'grid_{iRes}.nc')\n",
    "\n",
    "    print(iRes)\n",
    "    print(\"new vars not in old?\")\n",
    "    print(set(new_cice_grid.data_vars).difference(old_cice_grid.data_vars))\n",
    "    print(\"missing vars in new?\")\n",
    "    print(set(old_cice_grid.data_vars).difference(new_cice_grid.data_vars))\n",
    "    \n",
    "    for j,jVar in enumerate(new_cice_grid.data_vars):\n",
    "        \n",
    "        plt.subplot(\n",
    "            len(new_cice_grid.data_vars),\n",
    "            len(res),\n",
    "            i+(j*len(res))+1\n",
    "        )\n",
    "        \n",
    "                \n",
    "        anom = (new_cice_grid[jVar]-old_cice_grid[jVar])\n",
    "\n",
    "        anom = anom.where(abs(anom)>2e-6)\n",
    "        \n",
    "        if (jVar in (['ulat','ulon','tlat','tlon'])):\n",
    "            anom = np.rad2deg(anom)        \n",
    "            anom.plot(vmin=-1, vmax=1, cmap='coolwarm')\n",
    "        else:\n",
    "            anom.plot()\n",
    "\n",
    "        \n",
    "        plt.title(jVar)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "950c2a53-f3ec-4849-87b9-05b2007bf578",
   "metadata": {},
   "source": [
    "More detail on 0.1 degree ulat/ulon and angle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "687baac0-9dcd-450b-97ee-93711295c30c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:24:39.999314Z",
     "iopub.status.busy": "2024-03-08T04:24:39.998987Z",
     "iopub.status.idle": "2024-03-08T04:24:49.483239Z",
     "shell.execute_reply": "2024-03-08T04:24:49.482505Z",
     "shell.execute_reply.started": "2024-03-08T04:24:39.999282Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14f6f445e440>"
      ]
     },
     "execution_count": 35,
     "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": [
    "np.rad2deg((new_cice_grid-old_cice_grid).ulat).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "52d85abe-a5ac-4eea-901a-fb381b640d6d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:24:49.484192Z",
     "iopub.status.busy": "2024-03-08T04:24:49.484013Z",
     "iopub.status.idle": "2024-03-08T04:24:58.941306Z",
     "shell.execute_reply": "2024-03-08T04:24:58.940613Z",
     "shell.execute_reply.started": "2024-03-08T04:24:49.484174Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14f6f431e020>"
      ]
     },
     "execution_count": 36,
     "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": [
    "np.rad2deg((new_cice_grid-old_cice_grid).ulon).plot(vmin=-1, vmax=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9e6ed413-6cc5-46d2-87b6-9262183ce1ea",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:33:40.113396Z",
     "iopub.status.busy": "2024-03-08T04:33:40.112329Z",
     "iopub.status.idle": "2024-03-08T04:34:46.811274Z",
     "shell.execute_reply": "2024-03-08T04:34:46.810567Z",
     "shell.execute_reply.started": "2024-03-08T04:33:40.113341Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x149b7692bdc0>"
      ]
     },
     "execution_count": 12,
     "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": [
    "plt.pcolor(new_cice_grid.angleT.values-old_cice_grid.angleT.values)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "13d1d74c-717f-400e-99c6-7194b45d2cd7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2228947e-1dbe-4079-99a0-dce467d35df0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5be3ec30-1925-441c-8762-a9a908bd7a1c",
   "metadata": {},
   "source": [
    "what is going on with 0.25 deg angle?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "abe34ba4-a082-40fd-b1f3-513e147b2347",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:33.755883Z",
     "iopub.status.busy": "2024-03-08T04:27:33.754760Z",
     "iopub.status.idle": "2024-03-08T04:27:46.420617Z",
     "shell.execute_reply": "2024-03-08T04:27:46.419444Z",
     "shell.execute_reply.started": "2024-03-08T04:27:33.755830Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.3.0\n"
     ]
    }
   ],
   "source": [
    "old_cice_grid = xr.open_dataset(f'{_data_dir}/cice_025deg/grid.nc')\n",
    "new_cice_grid = xr.open_dataset(f'grid_025deg.nc')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e3fddab-0f89-4cc5-b21c-5a86b98219ee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:10:58.130942Z",
     "iopub.status.busy": "2024-03-08T04:10:58.128716Z",
     "iopub.status.idle": "2024-03-08T04:10:58.140627Z",
     "shell.execute_reply": "2024-03-08T04:10:58.139204Z",
     "shell.execute_reply.started": "2024-03-08T04:10:58.130880Z"
    }
   },
   "source": [
    "Looks to be the same problem as ulat / ulon, x is offset by 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "92340e2b-8bbc-4de4-a4c2-bb716ea84563",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-08T04:27:46.422542Z",
     "iopub.status.busy": "2024-03-08T04:27:46.422266Z",
     "iopub.status.idle": "2024-03-08T04:27:57.235566Z",
     "shell.execute_reply": "2024-03-08T04:27:57.234865Z",
     "shell.execute_reply.started": "2024-03-08T04:27:46.422512Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x149febe5e950>"
      ]
     },
     "execution_count": 7,
     "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": [
    "plt.pcolor(new_cice_grid.angle[:,:-1].values-old_cice_grid.angle[:,1:].values)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "161f0b21-0d95-4ea2-82e3-6bce40673e8e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}