From 8678ce7dd0453cd0a0ad7cd68224ff676745bab5 Mon Sep 17 00:00:00 2001 From: Daan Date: Thu, 15 Apr 2021 15:51:37 +0200 Subject: [PATCH] Fix divergence computation + a typo --- 02_mitgcm.ipynb | 238 +++++++++++++++++++++--------------------------- 1 file changed, 106 insertions(+), 132 deletions(-) diff --git a/02_mitgcm.ipynb b/02_mitgcm.ipynb index e28b6ec..e7093fa 100644 --- a/02_mitgcm.ipynb +++ b/02_mitgcm.ipynb @@ -39,7 +39,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -436,7 +436,7 @@ " Conventions: CF-1.6\n", " title: netCDF wrapper of MITgcm MDS binary data\n", " source: MITgcm\n", - " history: Created by calling `open_mdsdataset(extra_metadata=None, ll...
  • Conventions :
    CF-1.6
    title :
    netCDF wrapper of MITgcm MDS binary data
    source :
    MITgcm
    history :
    Created by calling `open_mdsdataset(extra_metadata=None, llc_method='smallchunks', nz=None, ny=None, nx=None, default_dtype=None, ignore_unknown_vars=False, chunks=None, endian='>', swap_dims=None, grid_vars_to_coords=True, geometry='sphericalpolar', calendar='gregorian', ref_date=None, delta_t=1, read_grid=True, prefix=None, iters='all', grid_dir=None, data_dir='./global_oce_latlon/')`
  • " ], "text/plain": [ "\n", @@ -785,7 +785,7 @@ " history: Created by calling `open_mdsdataset(extra_metadata=None, ll..." ] }, - "execution_count": 3, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -818,27 +818,27 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "\n", + "T Axis (not periodic, boundary=None):\n", + " * center time\n", + "X Axis (periodic, boundary=None):\n", + " * center XC --> left\n", + " * left XG --> center\n", "Z Axis (not periodic, boundary=None):\n", " * center Z --> left\n", " * left Zl --> center\n", - "T Axis (not periodic, boundary=None):\n", - " * center time\n", "Y Axis (periodic, boundary=None):\n", " * center YC --> left\n", - " * left YG --> center\n", - "X Axis (periodic, boundary=None):\n", - " * center XC --> left\n", - " * left XG --> center" + " * left YG --> center" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -865,33 +865,16 @@ "$$ \\frac{\\partial u}{\\partial x} + \\frac{\\partial v}{\\partial y} $$\n", "\n", "\n", - "In discrete form, using [MITgcm notation](http://mitgcm.org/public/r2_manual/latest/online_documents/node50.html), the formula for the C-grid is\n", + "In discrete form, using [MITgcm notation](https://mitgcm.readthedocs.io/en/latest/algorithm/algorithm.html#horizontal-divergence), the formula for the divergence on C-grid is\n", "\n", - "$$ ( \\delta_i \\Delta y_g \\Delta r_f h_w u + \\delta_j \\Delta x_g \\Delta r_f h_s v ) / A_c$$\n", + "$$ \\frac{1}{A_c h_c} ( \\delta_i \\Delta y_g h_w u + \\delta_j \\Delta x_g h_s v ) $$\n", "\n", - "First we calculate the volume transports in each direction:" + "The `UVEL`, `dyG` and `hFacW` DataArrays are defined on the U-points, which are on the left points of the X-axis (`XG`), while the `VVEL`, `dxG` and `hFacS` DataArrays are defined on V-points, which are the left point of the Y -axis (`YG`)." ] }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "u_transport = ds.UVEL * ds.dyG * ds.hFacW * ds.drF\n", - "v_transport = ds.VVEL * ds.dxG * ds.hFacS * ds.drF" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `u_transport` DataArray is on the left point of the X axis, while the `v_transport` DataArray is on the left point of the Y axis." - ] - }, - { - "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -914,8 +897,27 @@ } ], "source": [ - "display(u_transport.dims)\n", - "display(v_transport.dims)" + "display(ds.UVEL.dims)\n", + "display(ds.VVEL.dims)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True\n", + "True\n" + ] + } + ], + "source": [ + "print(ds.UVEL.dims[2:] == ds.dyG.dims == ds.hFacW.dims[1:])\n", + "print(ds.VVEL.dims[2:] == ds.dxG.dims == ds.hFacS.dims[1:])" ] }, { @@ -927,7 +929,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -936,13 +938,13 @@ "('time', 'Z', 'YC', 'XC')" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "div_uv = (grid.diff(u_transport, 'X') + grid.diff(v_transport, 'Y')) / ds.rA\n", + "div_uv = (grid.diff(ds.UVEL * ds.dyG * ds.hFacW, 'X') + grid.diff(ds.VVEL * ds.dxG * ds.hFacS, 'Y')) / (ds.rA * ds.hFacC)\n", "div_uv.dims" ] }, @@ -955,22 +957,22 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
    " ] @@ -999,12 +1001,12 @@ "\n", "$$ \\zeta = (- \\delta_j \\Delta x_c u + \\delta_i \\Delta y_c v ) / A_\\zeta \\ . $$\n", "\n", - "In xgcm, we calculate this quanity as" + "In xgcm, we calculate this quantity as" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -1408,7 +1410,7 @@ " * Z (Z) float32 -25.0 -85.0 -170.0 ... -3.575e+03 -4.19e+03 -4.855e+03\n", " * YG (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n", " * XG (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0\n", - " rAz (YG, XG) float32 3.433e+10 3.433e+10 ... 4.783e+10 4.783e+10
  • " ], "text/plain": [ "\n", @@ -1524,7 +1526,7 @@ " rAz (YG, XG) float32 3.433e+10 3.433e+10 ... 4.783e+10 4.783e+10" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -1545,16 +1547,16 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, @@ -1586,16 +1588,16 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, @@ -1636,16 +1638,16 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, @@ -1682,7 +1684,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -2057,7 +2059,7 @@ "Coordinates:\n", " * time (time) timedelta64[ns] 11:00:00\n", " * YG (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n", - " * XG (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0
  • " ], "text/plain": [ "\n", @@ -2104,7 +2106,7 @@ " * XG (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -2125,16 +2127,16 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, @@ -2164,16 +2166,16 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, @@ -2206,16 +2208,16 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, @@ -2236,34 +2238,6 @@ "ke = 0.5*(grid.interp((ds.UVEL*ds.hFacW)**2, 'X') + grid.interp((ds.VVEL*ds.hFacS)**2, 'Y'))\n", "ke[0,0].where(ds.maskC[0]).plot()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": {