{ "cells": [ { "cell_type": "markdown", "id": "d42fc115-6798-4af5-8150-ad1f078fefcc", "metadata": { "tags": [] }, "source": [ "# Example: Cross-contour transport\n", "\n", "## WARNING: This notebook currently only works with analysis3-23.04 or earlier!!! See issue #327 for details.\n", "\n", "This notebook uses the `cosima_cookbook` to calculate transport across an arbitrary contour. We do this by first creating the contour, such as sea surface height, and extracting the coordinates using `matplotlib`'s `Path` class. We then create some masks to indicate which direction is across the contour at each position along the contour. We then load the transport data and compute the transport, resulting in data with dimensions depth and along contour index. \n", "\n", "Computation times shown used conda environment `analysis3-22.07` on the large compute size on NCI's ARE.\n", "\n", "**Note:** updated 4Sep23 to modify the calculation of the transport masks to include cases where the contour borders a grid cell on three sides. Previously these options were not included in the calculation and thus there was missing transport.\n", "\n", "**Alert:** After including the additional cases the contour number doesn't always monotonically increase along the contour. At the moment, the two indices that are set at the same time are adjacent numbers, whereas if you were following the contour you'd expect their numbers to be 2 apart with the other coordinate in between.\n", "\n", "First, we load useful packages:" ] }, { "cell_type": "code", "execution_count": 1, "id": "9317acde-1a95-41f7-a7a7-ab60f9a33540", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import cosima_cookbook as cc\n", "import matplotlib.pyplot as plt\n", "import netCDF4 as nc\n", "import xarray as xr\n", "import numpy as np\n", "\n", "from dask.distributed import Client" ] }, { "cell_type": "code", "execution_count": 2, "id": "789a9952-1884-4633-aa20-60c05cce513b", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "client = Client()\n", "client" ] }, { "cell_type": "markdown", "id": "0fc07fcc-6e1d-40c0-be5b-c887266a20c7", "metadata": {}, "source": [ "#### Choose database" ] }, { "cell_type": "code", "execution_count": 3, "id": "142873eb-d834-40c2-aa5c-7b8f750f83d0", "metadata": {}, "outputs": [], "source": [ "session = cc.database.create_session()" ] }, { "cell_type": "markdown", "id": "de04e5ed-ee85-48ff-9628-abd3e6d8ea7b", "metadata": {}, "source": [ "#### Choose experiment" ] }, { "cell_type": "code", "execution_count": 4, "id": "eed34fea-7cdd-4439-9668-3f543b9a4766", "metadata": {}, "outputs": [], "source": [ "experiment = '01deg_jra55v13_ryf9091'" ] }, { "cell_type": "markdown", "id": "63761ef6-84b9-4c3b-9f99-9f90cb878e49", "metadata": {}, "source": [ "#### Choose a latitude range so the contour fits in the range, but there is not too much extra space. Extra space slows down the computation." ] }, { "cell_type": "code", "execution_count": 5, "id": "900d12f3-548f-4854-8686-5dc9f3d037c7", "metadata": {}, "outputs": [], "source": [ "lat_range = slice(-64.99, -47)" ] }, { "cell_type": "markdown", "id": "2ed43746-1772-4db8-be15-19accc9907ab", "metadata": {}, "source": [ "#### We must make sure that this latitude range is so that the t-cells are always south and west of the u-cells.\n", "\n", "This is important because the meridional and zonal transports occur on different grids to each other. We can check this by loading the `u`-cell and `t`-cell coordinates. \n", "\n", "We choose this convention so that later on when we create `numpy` grids of where the contour is and in what direction the contour goes." ] }, { "cell_type": "code", "execution_count": 6, "id": "ab5a694c-b2a2-4f1d-9366-9a9facbf3fe5", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 10.9 s, sys: 2.41 s, total: 13.3 s\n", "Wall time: 1min 5s\n" ] } ], "source": [ "%%time\n", "\n", "yt_ocean = cc.querying.getvar(experiment, 'yt_ocean', session, n=1)\n", "yt_ocean = yt_ocean.sel(yt_ocean = lat_range)\n", "\n", "xt_ocean = cc.querying.getvar(experiment, 'xt_ocean', session, n=1)\n", "\n", "yu_ocean = cc.querying.getvar(experiment, 'yu_ocean', session, n=1)\n", "yu_ocean = yu_ocean.sel(yu_ocean = lat_range)\n", "\n", "xu_ocean = cc.querying.getvar(experiment, 'xu_ocean', session, n=1)" ] }, { "cell_type": "code", "execution_count": 7, "id": "577743fb-7cd1-4a43-b4f2-8dcef92aaaac", "metadata": {}, "outputs": [], "source": [ "if len(yt_ocean) != len(yu_ocean):\n", " print('help! y different size')\n", "\n", "if yt_ocean.min('yt_ocean')> yu_ocean.min('yu_ocean'):\n", " print('help! wrong order')\n", "\n", "if len(xt_ocean) != len(xu_ocean):\n", " print('help! x different size')\n", "\n", "if xt_ocean.min('xt_ocean')> xu_ocean.min('xu_ocean'):\n", " print('help! x wrong order')" ] }, { "cell_type": "markdown", "id": "207b7d83-c992-4b5f-896c-44cc7ff291c2", "metadata": {}, "source": [ "#### Load quantity we want a contour of, e.g. SSH averaged over a year" ] }, { "cell_type": "code", "execution_count": 8, "id": "21118fd1-2274-444d-80c2-30bf6cc55ce1", "metadata": {}, "outputs": [], "source": [ "start_time = '2170-01-01'\n", "end_time = '2170-12-31'\n", "time_slice = slice(start_time, end_time)\n", "ssh = cc.querying.getvar(experiment,'sea_level', session, start_time = start_time, end_time = end_time)\n", "\n", "# select one year and latitude range\n", "ssh = ssh.sel(yt_ocean = lat_range, time = time_slice)\n", "\n", "# weighted time-mean by month length\n", "days_in_month = ssh.time.dt.days_in_month\n", "days_in_year = 365\n", "ssh_mean = (ssh * days_in_month / days_in_year).sum('time')" ] }, { "cell_type": "markdown", "id": "fd55d0ea-ab7e-412c-9b23-687c809036b6", "metadata": {}, "source": [ "#### Choose your desired contour value" ] }, { "cell_type": "code", "execution_count": 9, "id": "2cc4a6dc-393b-45e7-923a-f543f681344c", "metadata": {}, "outputs": [], "source": [ "contour_depth = -1.20" ] }, { "cell_type": "markdown", "id": "e2d63199-9ae5-42d1-ba6c-aac55f9d88e4", "metadata": {}, "source": [ "Plot your data (always good idea `:)`)" ] }, { "cell_type": "code", "execution_count": 10, "id": "c000a8da-6309-4d9b-a6e6-f2f4518a2de9", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize = (10, 4))\n", "\n", "ssh_mean.plot(extend='both', cbar_kwargs={'label': \"SSH [m]\"})\n", "ssh_mean.plot.contour(levels = [contour_depth], colors = 'k', linestyles = '-')\n", "plt.title('Sea surface height (m)');" ] }, { "cell_type": "code", "execution_count": 11, "id": "e2ca6843-4f28-4b5b-805f-99f858cf482e", "metadata": {}, "outputs": [], "source": [ "h = ssh_mean.load()\n", "\n", "# Fill in land with zeros:\n", "h = h.fillna(0)" ] }, { "cell_type": "code", "execution_count": 12, "id": "1a1ca948-228b-4e97-a3e7-874932ece34e", "metadata": {}, "outputs": [], "source": [ "# Contour is on t-grid (we assume ACCESS-OM2 B grid transports)\n", "grid_sel = 't'\n", "x_var = xt_ocean\n", "y_var = yt_ocean" ] }, { "cell_type": "markdown", "id": "3a480d78-04dc-4558-b735-53c34ce6e792", "metadata": { "tags": [] }, "source": [ "#### Select the contour \n", "If there are multiple contours satisfying this contour level, change the `count` in the `if` statement below until desired contour is highlighted red. Counting starts from the south west. For example, if we chose `count == 1` the Antarctic Peninsula would instead be selected, rather than the circumpolar contour." ] }, { "cell_type": "code", "execution_count": 13, "id": "76fbe005-ed16-43d3-b443-a16819602fac", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize = (10, 4))\n", "count = 0\n", "x_contour = []\n", "y_contour = []\n", "\n", "# Create the contour:\n", "sc = plt.contour(h, levels=[contour_depth])\n", "for collection in sc.collections:\n", " for path in collection.get_paths():\n", " count += 1\n", " if count == 2:\n", " # Write down the lat/lon indices\n", " for ii in range(np.size(path.vertices[:,0])):\n", " x_contour.append(int(np.round(path.vertices[ii][0])))\n", " y_contour.append(int(np.round(path.vertices[ii][1])))\n", "\n", "plt.scatter(x_contour, y_contour, s=5, alpha=0.5, color='tomato');" ] }, { "cell_type": "markdown", "id": "93a49bfe-6d4f-449d-8746-c2203f53ccca", "metadata": {}, "source": [ "#### Processing\n", "Now process these coordinates to make sure there are no double ups." ] }, { "cell_type": "code", "execution_count": 14, "id": "bdb41806-ce8d-447b-825c-9020ffe6b276", "metadata": {}, "outputs": [], "source": [ "# Difference between two neighbouring indices\n", "diff_x_contour = np.diff(x_contour)\n", "diff_y_contour = np.diff(y_contour)\n", "\n", "# Get a list with the indices of duplicates\n", "diff_ind = []\n", "for ii in range(len(diff_x_contour)):\n", " if (diff_x_contour[ii]==0) and (diff_y_contour[ii]==0):\n", " diff_ind.append(ii)" ] }, { "cell_type": "code", "execution_count": 15, "id": "5ecb5141-0e70-4dd7-b209-db2f260994bb", "metadata": {}, "outputs": [], "source": [ "# Now remove the indices (start from the end so the indices don't shift)\n", "for ii in range(len(diff_ind)):\n", " index = diff_ind[::-1][ii]\n", " del x_contour[index]\n", " del y_contour[index]" ] }, { "cell_type": "code", "execution_count": 16, "id": "a95b0816-b795-4242-968f-58cfb86e85c6", "metadata": {}, "outputs": [], "source": [ "h_contour = np.zeros(len(x_contour))\n", "\n", "for ii in range(len(h_contour)):\n", " h_contour[ii] = h[y_contour[ii], x_contour[ii]]" ] }, { "cell_type": "markdown", "id": "5649659b-7642-4c6e-a3bf-f1987b5de567", "metadata": {}, "source": [ "Due to the discrete grid, the values on our contour are not exactly the same. We check this makes sense -- if this plot is blank, then something has gone wrong." ] }, { "cell_type": "code", "execution_count": 17, "id": "910fea81-3d88-4c41-84d1-1ef8bcefeb52", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10, 5))\n", "\n", "plt.plot(h_contour, 'o', markersize=1)\n", "plt.axhline(contour_depth, color='k', linewidth=0.5);" ] }, { "cell_type": "markdown", "id": "3804fd5e-d48d-4f42-a06d-732207405f1a", "metadata": {}, "source": [ "#### Get lat and lon along the contour" ] }, { "cell_type": "code", "execution_count": 18, "id": "c78519e6-0b37-4b9a-bf38-518da3e66f25", "metadata": {}, "outputs": [], "source": [ "lat_along_contour = np.zeros((len(x_contour)))\n", "lon_along_contour = np.zeros((len(x_contour)))\n", "\n", "for ii in range(len(h_contour)):\n", " lon_along_contour[ii] = x_var[x_contour[ii]]\n", " lat_along_contour[ii] = y_var[y_contour[ii]]" ] }, { "cell_type": "markdown", "id": "ee26c68e-1ad5-4f65-8e34-49235d18aa52", "metadata": {}, "source": [ "#### Repeat the leftmost point at the end of the array. \n", "\n", "(Required for masking contour above and below)" ] }, { "cell_type": "code", "execution_count": 19, "id": "fd86bf32-0a0d-485a-8abb-49e05db24bed", "metadata": {}, "outputs": [], "source": [ "lat_along_contour = np.append(lat_along_contour, lat_along_contour[0])\n", "lon_along_contour = np.append(lon_along_contour, lon_along_contour[0])" ] }, { "cell_type": "code", "execution_count": 20, "id": "a345555f-6878-433a-8a9e-78e8785ecd16", "metadata": {}, "outputs": [], "source": [ "# Number of grid points on the contour\n", "num_points = len(lat_along_contour)" ] }, { "cell_type": "markdown", "id": "7d1b090a-3a2f-41ae-8d40-4baef6daceab", "metadata": {}, "source": [ "#### Now we number the points along the contour" ] }, { "cell_type": "code", "execution_count": 21, "id": "dce023e5-a888-4bd4-87a1-9725cc306628", "metadata": {}, "outputs": [], "source": [ "contour_mask_numbered = np.zeros_like(lon_along_contour)\n", "\n", "for ii in range(num_points-1):\n", " lat1 = lat_along_contour[ii]\n", " lat2 = lat_along_contour[ii+1]\n", " lon1 = lon_along_contour[ii]\n", " lon2 = lon_along_contour[ii+1]\n", " contour_mask_numbered[ii] = ii" ] }, { "cell_type": "code", "execution_count": 22, "id": "a6a007ad-69ed-4897-b6ab-7e3d0ad258d1", "metadata": {}, "outputs": [], "source": [ "contour_mask = h*0\n", "\n", "for ii in range(num_points-1):\n", " contour_mask[y_contour[ii], x_contour[ii]] = contour_mask_numbered[ii]+1" ] }, { "cell_type": "code", "execution_count": 23, "id": "b84dab94-95a5-4846-8002-c101c79199e4", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1, figsize=(16, 8))\n", "contour_mask.plot(extend='both');" ] }, { "cell_type": "markdown", "id": "bb5e92d4-df73-418d-a6fc-5f48c71c33d8", "metadata": {}, "source": [ "#### Create mask\n", "Now we create a mask below contour so that the direction of the contour can be determined" ] }, { "cell_type": "markdown", "id": "cb067e62-6dfe-4a40-8961-cf95e405ddfe", "metadata": {}, "source": [ "**Remark on computational inefficiency**\n", "\n", "Note that creating masks with nested `for` loops is very inefficient. We should probably use boolean masks (just compare the entire array with `mask_value`), and [`DataArray.shift()`](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.shift.html) or [`DataArray.roll()`](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.roll.html) from each of the directions to generate the masks without using loops.\n", "\n", "See discussion in: https://github.com/COSIMA/cosima-recipes/issues/179" ] }, { "cell_type": "code", "execution_count": 24, "id": "e77f5ab9-6322-46b9-99ac-f76c20218e1d", "metadata": {}, "outputs": [], "source": [ "mask_value = -1000\n", "contour_mask_numbered = contour_mask\n", "\n", "# fill in points to south of contour:\n", "contour_masked_above = np.copy(contour_mask_numbered)\n", "contour_masked_above[-1, 0] = mask_value\n", "\n", "# from top left:\n", "for ii in range(len(contour_mask.xt_ocean)-1):\n", " for jj in range(len(contour_mask.yt_ocean))[::-1][:-1]:\n", " if contour_masked_above[jj, ii] == mask_value:\n", " if contour_masked_above[jj-1, ii] == 0:\n", " contour_masked_above[jj-1, ii] = mask_value\n", " if contour_masked_above[jj, ii+1] == 0:\n", " contour_masked_above[jj, ii+1] = mask_value\n", "\n", "#from top right:\n", "for ii in range(len(contour_mask.xt_ocean))[::-1][:-1]:\n", " for jj in range(len(contour_mask.yt_ocean))[::-1][:-1]:\n", " if contour_masked_above[jj, ii] == mask_value:\n", " if contour_masked_above[jj-1, ii] == 0:\n", " contour_masked_above[jj-1, ii] = mask_value\n", " if contour_masked_above[jj, ii-1] == 0:\n", " contour_masked_above[jj, ii-1] = mask_value\n", "\n", "# from bottom right:\n", "for ii in range(len(contour_mask.xt_ocean))[::-1][:-1]:\n", " for jj in range(len(contour_mask.yt_ocean)-1):\n", " if contour_masked_above[jj, ii] == mask_value:\n", " if contour_masked_above[jj+1, ii] == 0:\n", " contour_masked_above[jj+1, ii] = mask_value\n", " if contour_masked_above[jj, ii-1] == 0:\n", " contour_masked_above[jj, ii-1] = mask_value\n", "\n", "#from bottom left:\n", "for ii in range(len(contour_mask.xt_ocean)-1):\n", " for jj in range(len(contour_mask.yt_ocean)-1):\n", " if contour_masked_above[jj, ii] == mask_value:\n", " if contour_masked_above[jj+1, ii] == 0:\n", " contour_masked_above[jj+1, ii] = mask_value\n", " if contour_masked_above[jj, ii+1] == 0:\n", " contour_masked_above[jj, ii+1] = mask_value" ] }, { "cell_type": "code", "execution_count": 25, "id": "fd9d5bcb-7cb4-4fa5-b054-5941c848edb1", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1, figsize=(16, 8))\n", "\n", "plt.pcolormesh(contour_mask.xt_ocean, contour_mask.yt_ocean, contour_masked_above)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "id": "e6dd6197-21ab-4635-851c-17cb20759200", "metadata": {}, "source": [ "South of the contour, values have been filled in to be -100, and it is thus a different colour in the plot.\n", "\n", "#### Direction of cross-contour transport\n", "Now we can use the mask south of the contour to determine whether the transport across the contour should be north, east, south or west (the grid is made of discrete square(ish) shaped cells). This is done by looping through the contour points and determining in which directions there are zeros (above contour) and -100 (below contour). This means the orientation of the contour can be determined. This is saved as `mask_x_transport`, which has -1 and +1 in a 2D (x and y) array where the contour has eastward transport, and `mask_y_transport` which as -1 and +1 for coordinates with northward transport. All other positions in the array are 0. This means that multiplying the northward transport `ty_trans` by the `mask_y_transport` gives all the northward transport across the contour, and zeros everywhere else (e.g. where contour goes upwards and cross-contour transport is thus eastward)." ] }, { "cell_type": "code", "execution_count": 26, "id": "44a8c118-640e-44c2-89c2-55f4e5bf1b7a", "metadata": {}, "outputs": [], "source": [ "mask_x_transport = np.zeros_like(contour_mask_numbered)\n", "mask_y_transport = np.zeros_like(contour_mask_numbered)\n", "\n", "mask_y_transport_numbered = np.zeros_like(contour_mask_numbered)\n", "mask_x_transport_numbered = np.zeros_like(contour_mask_numbered)\n", "\n", "# make halos:\n", "shape = contour_masked_above.shape\n", "contour_masked_above_halo = np.zeros((shape[0], shape[1]+2))\n", "contour_masked_above_halo[:, 0] = contour_masked_above[:, -1]\n", "contour_masked_above_halo[:, 1:-1] = contour_masked_above\n", "contour_masked_above_halo[:, -1] = contour_masked_above[:, 0]\n", "\n", "new_number_count = 1\n", "for mask_loc in range(1, int(np.max(contour_mask_numbered))+1):\n", " #if mask_loc%100 == 0:\n", " # print('mask for x/y transport at point '+str(mask_loc))\n", " index_i = np.where(contour_mask_numbered==mask_loc)[1]\n", " index_j = np.where(contour_mask_numbered==mask_loc)[0]\n", " # if point above is towards Antarctica and point below is away from Antarctica:\n", " # take transport grid point to north of t grid:\n", " if (contour_masked_above[index_j+1, index_i]==0) and (contour_masked_above[index_j-1, index_i]!=0):\n", " mask_y_transport[index_j, index_i] = -1\n", " # important to do \n", " mask_y_transport_numbered[index_j, index_i] = new_number_count\n", " new_number_count += 1\n", " # if point below is towards Antarctica and point above is away from Antarctica:\n", " # take transport grid point to south of t grid:\n", " elif (contour_masked_above[index_j-1, index_i]==0) and (contour_masked_above[index_j+1, index_i]!=0):\n", " mask_y_transport[index_j-1, index_i] = 1\n", " mask_y_transport_numbered[index_j-1, index_i] = new_number_count\n", " new_number_count += 1\n", " # if point below and point above are BOTH towards Antarctica:\n", " # take transport grid point to south of t grid:\n", " elif (contour_masked_above[index_j-1, index_i]==0) and (contour_masked_above[index_j+1, index_i]==0):\n", " mask_y_transport[index_j-1, index_i] = 1\n", " mask_y_transport[index_j, index_i] = -1 \n", " mask_y_transport_numbered[index_j-1, index_i] = new_number_count\n", " mask_y_transport_numbered[index_j, index_i] = new_number_count+1\n", " new_number_count += 2\n", " # if point to right is towards Antarctica and point to left is away from Antarctica:\n", " # zonal indices increased by 1 due to halos\n", " # take transport grid point on right of t grid:\n", " if (contour_masked_above_halo[index_j, index_i+2]==0) and (contour_masked_above_halo[index_j, index_i]!=0):\n", " mask_x_transport[index_j, index_i] = -1\n", " mask_x_transport_numbered[index_j, index_i] = new_number_count\n", " new_number_count += 1\n", " # if point to left is towards Antarctica and point to right is away from Antarctica:\n", " # take transport grid point on left of t grid:\n", " elif (contour_masked_above_halo[index_j, index_i]==0) and (contour_masked_above_halo[index_j, index_i+2]!=0):\n", " mask_x_transport[index_j, index_i-1] = 1\n", " mask_x_transport_numbered[index_j, index_i-1] = new_number_count\n", " new_number_count += 1\n", " # if point to left and right BOTH toward Antarctica\n", " elif (contour_masked_above_halo[index_j, index_i]==0) and (contour_masked_above_halo[index_j, index_i+2]==0):\n", " mask_x_transport[index_j, index_i-1] = 1\n", " mask_x_transport[index_j, index_i] = -1 \n", " mask_x_transport_numbered[index_j, index_i-1] = new_number_count\n", " mask_x_transport_numbered[index_j, index_i] = new_number_count+1\n", " new_number_count += 2" ] }, { "cell_type": "code", "execution_count": 27, "id": "bd99120e-ff5a-423e-a9af-cf8bbf8082f6", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1, figsize=(16, 8))\n", "\n", "plt.pcolormesh(contour_mask.xt_ocean, contour_mask.yt_ocean, mask_x_transport)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "id": "553a6c80-bc24-4301-a1a7-d85351d3a745", "metadata": {}, "source": [ "As can be seen, in `mask_x_transport` there is yellow (+1) where eastward transport crosses the contour, and (-1) where westward transport crosses the contour (in the net northward direction). There are zeros everywhere else.\n", "\n", "### We now have the coordinates of the contours, and whether the x or y transport is needed to calculate cross-contour transport. \n", "\n", "We now proceed to calculate transports across the contour" ] }, { "cell_type": "code", "execution_count": 28, "id": "e60e7a18-e049-496e-9077-c7758372ab56", "metadata": {}, "outputs": [], "source": [ "# Convert contour masks to data arrays, so we can multiply them later.\n", "# We need to ensure the lat lon coordinates correspond to the actual data location:\n", "# The y masks are used for ty_trans, so like vhrho this should have dimensions (yu_ocean, xt_ocean).\n", "# The x masks are used for tx_trans, so like uhrho this should have dimensions (yt_ocean, xu_ocean).\n", "# However the actual name will always be simply y_ocean/x_ocean irrespective of the variable\n", "# to make concatenation of transports in both direction and sorting possible.\n", "\n", "mask_x_transport = xr.DataArray(mask_x_transport, coords = [yt_ocean, xu_ocean], dims = ['y_ocean','x_ocean'])\n", "mask_y_transport = xr.DataArray(mask_y_transport, coords = [yu_ocean, xt_ocean], dims = ['y_ocean','x_ocean'])\n", "mask_x_transport_numbered = xr.DataArray(mask_x_transport_numbered, coords = [yt_ocean, xu_ocean], dims = ['y_ocean','x_ocean'])\n", "mask_y_transport_numbered = xr.DataArray(mask_y_transport_numbered, coords = [yu_ocean, xt_ocean], dims = ['y_ocean','x_ocean'])" ] }, { "cell_type": "markdown", "id": "f8993961-df9c-489c-91ad-2f5681ecc191", "metadata": {}, "source": [ "And plot just to confirm that we didn't mess up anything." ] }, { "cell_type": "code", "execution_count": 29, "id": "439dc694-1436-4843-85c4-25f6853b02e9", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1, figsize=(16, 8))\n", "\n", "mask_x_transport.plot(cmap=\"viridis\");" ] }, { "cell_type": "markdown", "id": "c1ab1a6e-266d-4f80-ab20-5f581d3b7f41", "metadata": {}, "source": [ "#### Stack contour data into 1D" ] }, { "cell_type": "code", "execution_count": 30, "id": "a8538013-8bd3-4cc8-804a-528ae89d6c37", "metadata": {}, "outputs": [], "source": [ "# Create the contour order data-array. Note that in this procedure the x-grid counts have x-grid\n", "# dimensions and the y-grid counts have y-grid dimensions, but these are implicit, the dimension \n", "# *names* are kept general across the counts, the generic y_ocean, x_ocean, so that concatening works\n", "# but we dont double up with numerous counts for one lat/lon point.\n", "\n", "# stack contour data into 1d:\n", "mask_x_numbered_1d = mask_x_transport_numbered.stack(contour_index = ['y_ocean', 'x_ocean'])\n", "mask_x_numbered_1d = mask_x_numbered_1d.where(mask_x_numbered_1d > 0, drop = True)\n", "\n", "mask_y_numbered_1d = mask_y_transport_numbered.stack(contour_index = ['y_ocean', 'x_ocean'])\n", "mask_y_numbered_1d = mask_y_numbered_1d.where(mask_y_numbered_1d > 0, drop = True)\n", "\n", "contour_ordering = xr.concat((mask_x_numbered_1d, mask_y_numbered_1d), dim = 'contour_index')\n", "contour_ordering = contour_ordering.sortby(contour_ordering)\n", "contour_index_array = np.arange(1, len(contour_ordering)+1)" ] }, { "cell_type": "markdown", "id": "d36cca6d-84cd-4dfe-850c-487636b41323", "metadata": {}, "source": [ "#### Load transports `tx_trans` and `ty_trans`" ] }, { "cell_type": "code", "execution_count": 31, "id": "c8043e3a-d4b2-4ee7-969d-db569336e4be", "metadata": {}, "outputs": [], "source": [ "ty_trans = cc.querying.getvar(experiment, 'ty_trans', session, start_time = start_time, end_time = end_time)\n", "ty_trans = ty_trans.sel(yu_ocean = lat_range, time = time_slice)\n", "\n", "tx_trans = cc.querying.getvar(experiment, 'tx_trans', session, start_time = start_time, end_time = end_time)\n", "tx_trans = tx_trans.sel(yt_ocean = lat_range, time = time_slice)\n", "\n", "ty_trans = ty_trans.rename({'yu_ocean': 'y_ocean', 'xt_ocean': 'x_ocean'})\n", "tx_trans = tx_trans.rename({'yt_ocean': 'y_ocean', 'xu_ocean': 'x_ocean'})" ] }, { "cell_type": "markdown", "id": "208e23fc-ec56-4ae7-806d-d2f945cc392d", "metadata": {}, "source": [ "#### Take time average" ] }, { "cell_type": "code", "execution_count": 32, "id": "c9d42b7d-967a-4d47-bac2-e664032f6ecb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 25.8 s, sys: 3.52 s, total: 29.4 s\n", "Wall time: 55 s\n" ] } ], "source": [ "%%time\n", "# weighed time mean by month length\n", "days_in_month = ssh.time.dt.days_in_month\n", "days_in_year = 365\n", "\n", "tx_trans = (tx_trans * days_in_month / days_in_year).sum('time')\n", "tx_trans = tx_trans.load()\n", "\n", "ty_trans = (ty_trans * days_in_month / days_in_year).sum('time')\n", "ty_trans = ty_trans.load()" ] }, { "cell_type": "markdown", "id": "37fc7c2c-ddf3-4862-a76b-b081cc2d5ea0", "metadata": {}, "source": [ "#### Convert from mass transport to volume transport" ] }, { "cell_type": "code", "execution_count": 33, "id": "7f0b74fb-b530-4dbb-94ba-5b40f5b2803e", "metadata": {}, "outputs": [], "source": [ "ρ0 = 1035 # kg/m^3\n", "\n", "ty_trans = ty_trans * mask_y_transport / ρ0 # convert to Sv\n", "tx_trans = tx_trans * mask_x_transport / ρ0 # convert to Sv" ] }, { "cell_type": "markdown", "id": "47009061-ee3d-4de3-b169-973581c2d278", "metadata": {}, "source": [ "#### Extract transport values along contour" ] }, { "cell_type": "code", "execution_count": 34, "id": "e7cb043a-e3c2-4fb1-9dd6-82e2f92ba645", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 4 s, sys: 219 ms, total: 4.22 s\n", "Wall time: 4.17 s\n" ] } ], "source": [ "%%time\n", "## We could also loop in time if we didn't want the time average. Initialise a data array and fill in data by looping in time.\n", "\n", "# stack transports into 1d and drop any points not on contour:\n", "x_transport_1d = tx_trans.stack(contour_index = ['y_ocean', 'x_ocean'])\n", "x_transport_1d = x_transport_1d.where(mask_x_numbered_1d>0, drop = True)\n", "y_transport_1d = ty_trans.stack(contour_index = ['y_ocean', 'x_ocean'])\n", "y_transport_1d = y_transport_1d.where(mask_y_numbered_1d>0, drop = True)\n", "\n", "# combine all points on contour:\n", "vol_trans_across_contour = xr.concat((x_transport_1d, y_transport_1d), dim = 'contour_index')\n", "vol_trans_across_contour = vol_trans_across_contour.sortby(contour_ordering)\n", "vol_trans_across_contour.coords['contour_index'] = contour_index_array\n", "vol_trans_across_contour = vol_trans_across_contour.load()" ] }, { "cell_type": "code", "execution_count": 35, "id": "6b0aba54-80b5-4812-9c70-e2963137db41", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize = (10, 4))\n", "\n", "vol_trans_across_contour.sum('st_ocean').cumsum('contour_index').plot()\n", "ax.set_ylabel('Cumulative transport across contour');" ] }, { "cell_type": "markdown", "id": "31dbe819-cfec-476a-96b9-7543226c9f55", "metadata": {}, "source": [ "#### Finally, we can extract the coordinates of the contour index, and the distance, for a more meaningful $x$ axis." ] }, { "cell_type": "code", "execution_count": 36, "id": "f726f72d-baeb-4230-9e6e-988245694331", "metadata": {}, "outputs": [], "source": [ "contour_ordering = xr.concat((mask_x_numbered_1d,mask_y_numbered_1d), dim = 'contour_index')\n", "contour_ordering = contour_ordering.sortby(contour_ordering)\n", "\n", "# get lat and lon along contour, useful for plotting later:\n", "lat_along_contour = contour_ordering.y_ocean\n", "lon_along_contour = contour_ordering.x_ocean\n", "\n", "contour_index_array = np.arange(1, len(contour_ordering)+1)\n", "\n", "# don't need the multi-index anymore, replace with contour count and save\n", "lat_along_contour.coords['contour_index'] = contour_index_array\n", "lon_along_contour.coords['contour_index'] = contour_index_array" ] }, { "cell_type": "markdown", "id": "36138ca9-c0ed-415e-a595-bec99e2e248c", "metadata": {}, "source": [ "#### Code to extract distance in between contour coordinates, using length of diagonal if there is a bend.\n", "Loop through the contour, determining if diagonal is required or not, and save the distance along each segment. Then, cumulatively sum the distances along each segment to get the distance from the first point.\n", "\n", "If there is a bend in the contour, then half the diagonal distance is added to each side to avoid artifically inflating the along-contour distance metric, according to this diagram:\n", "\n", "\"drawing\"" ] }, { "cell_type": "code", "execution_count": 37, "id": "05958ea6-d747-4dff-868e-529930e7a0cb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 305 ms, sys: 39.4 ms, total: 345 ms\n", "Wall time: 923 ms\n" ] } ], "source": [ "%%time\n", "dxu = cc.querying.getvar(experiment, 'dxu', session, ncfile = 'ocean_grid.nc', n=1)\n", "dxu = dxu.sel(yu_ocean = lat_range)\n", "\n", "dyt = cc.querying.getvar(experiment, 'dyt', session, ncfile = 'ocean_grid.nc', n=1)\n", "dyt = dyt.sel(yt_ocean = lat_range)\n", "\n", "num_points = len(lat_along_contour)" ] }, { "cell_type": "code", "execution_count": 38, "id": "616aad75-af80-44bf-8bf3-c591035cd469", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 5min 13s, sys: 17.9 s, total: 5min 31s\n", "Wall time: 10min 9s\n" ] } ], "source": [ "%%time\n", "# if there is a bend in the contour, add the distance using the half-length of the diagonal\n", "# instead of the sum of 2 edges, to be more representative.\n", "distance_along_contour = np.zeros((num_points))\n", "\n", "x_indices = np.sort(mask_x_transport_numbered.values[mask_x_transport_numbered.values>0])\n", "y_indices = np.sort(mask_y_transport_numbered.values[mask_y_transport_numbered.values>0])\n", "\n", "skip = False\n", "# note dxu and dyt do not vary in x, so we can just take the first value (as long as there is no land there,\n", "# which for this latitude range there is not. If using a different latitude range, choose an x value that is\n", "# not a nan/land for the entire latitude range\n", "dxu = dxu.isel(xu_ocean = 0)\n", "dyt = dyt.isel(xt_ocean = 0)\n", "\n", "for count in range(1, num_points):\n", " if skip == True:\n", " skip = False\n", " continue\n", " if count in y_indices:\n", " if count + 1 in y_indices:\n", " # note dxu and dyt do not vary in x:\n", " jj = np.where(mask_y_transport_numbered==count)[0]\n", " distance_along_contour[count-1] = (dxu[jj])[0]\n", " else:\n", " jj0 = np.where(mask_y_transport_numbered==count)[0]\n", " jj1 = np.where(mask_x_transport_numbered==count+1)[0]\n", " half_diagonal_distance = 0.5 * np.sqrt((dxu[jj0])[0]**2 + (dyt[jj1])[0]**2)\n", " distance_along_contour[count-1] = half_diagonal_distance\n", " distance_along_contour[count] = half_diagonal_distance\n", " # skip to next count:\n", " skip = True\n", "\n", " # count in x_indices:\n", " else:\n", " if count + 1 in x_indices:\n", " jj = np.where(mask_x_transport_numbered==count)[0]\n", " distance_along_contour[count-1] = (dyt[jj])[0]\n", " else:\n", " jj0 = np.where(mask_x_transport_numbered==count)[0]\n", " jj1 = np.where(mask_y_transport_numbered==count+1)[0]\n", " half_diagonal_distance = 0.5 * np.sqrt((dyt[jj0])[0]**2 + (dxu[jj1])[0]**2)\n", " distance_along_contour[count-1] = half_diagonal_distance\n", " distance_along_contour[count] = half_diagonal_distance\n", " # skip to next count:\n", " skip = True\n", "\n", "# fix last value:\n", "if distance_along_contour[-1] == 0:\n", " count = count + 1\n", " if count in y_indices:\n", " jj = np.where(mask_y_transport_numbered==count)[0]\n", " distance_along_contour[-1] = (dxu[jj])[0]\n", " else:\n", " jj = np.where(mask_x_transport_numbered==count)[0]\n", " distance_along_contour[-1] = (dyt[jj])[0]\n", "\n", "# units are 10^3 km:\n", "distance_along_contour = np.cumsum(distance_along_contour) / 1e3 / 1e3" ] }, { "cell_type": "markdown", "id": "ccb11faa-8ed7-4677-9827-9bc0d869f733", "metadata": { "tags": [] }, "source": [ "#### Select the indices for axis labels of specific longitudes, so we can plot transport vs distance but have longitude labels instead of length" ] }, { "cell_type": "code", "execution_count": 39, "id": "c31b7d6b-b0ce-427a-b4ef-7097326a9d0b", "metadata": {}, "outputs": [], "source": [ "distance_indices = np.zeros(8)\n", "\n", "for i in np.arange(100, len(lon_along_contour.values)):\n", " if (distance_indices[1]==0):\n", " if (lon_along_contour.values[i]>-240):\n", " distance_indices[1] = lon_along_contour.contour_index.values[i]\n", " if (distance_indices[2]==0):\n", " if (lon_along_contour.values[i]>-180):\n", " distance_indices[2] = lon_along_contour.contour_index.values[i]\n", " if (distance_indices[3]==0):\n", " if (lon_along_contour.values[i]>-120):\n", " distance_indices[3] = lon_along_contour.contour_index.values[i]\n", " if (distance_indices[4]==0):\n", " if lon_along_contour.values[i]>-60:\n", " distance_indices[4] = lon_along_contour.contour_index.values[i]\n", " if (distance_indices[5]==0):\n", " if (lon_along_contour.values[i]>0):\n", " distance_indices[5] = lon_along_contour.contour_index.values[i]\n", " if (distance_indices[6]==0):\n", " if (lon_along_contour.values[i]>60):\n", " distance_indices[6] = lon_along_contour.contour_index.values[i]\n", "\n", "distance_indices[7] = len(lon_along_contour.contour_index.values)-1" ] }, { "cell_type": "markdown", "id": "e819790e-c2f5-4bc7-970f-a3eb4338871d", "metadata": {}, "source": [ "#### Plot cumulative transport against distance along the contour." ] }, { "cell_type": "code", "execution_count": 40, "id": "5c992571-c6fd-48d9-92e2-481c813c3424", "metadata": {}, "outputs": [], "source": [ "depth_to_integrate = 500 # m" ] }, { "cell_type": "code", "execution_count": 41, "id": "58dec990-919e-4ec7-8ff4-cc18e763a527", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(nrows = 2, figsize = (10, 8))\n", "\n", "axes[0].plot(distance_along_contour, (1e-6 * vol_trans_across_contour.sel(st_ocean = slice(0, depth_to_integrate)).sum('st_ocean').cumsum('contour_index')))\n", "\n", "axes[0].set_ylabel('Cumulative transport (Sv)')\n", "axes[0].set_xlabel('Distance from 80$^\\circ$E (10$^3$ km)')\n", "axes[0].set_xlim(0, distance_along_contour[-1])\n", "axes[0].set_title(f'Cumulative transport across SSH={contour_depth} m in top {depth_to_integrate} m depth')\n", "\n", "axes[1].plot(distance_along_contour, (1e-6 * vol_trans_across_contour.sel(st_ocean = slice(0, depth_to_integrate)).sum('st_ocean').cumsum('contour_index')))\n", "\n", "axes[1].set_xticks(distance_along_contour[distance_indices.astype(int)[:-1]])\n", "axes[1].set_xticklabels(('80$^\\circ$E', '120$^\\circ$E', '180$^\\circ$W', '120$^\\circ$W', '60$^\\circ$W', '0$^\\circ$', '60$^\\circ$E'))\n", "axes[1].set_xlim(0, distance_along_contour[-1])\n", "\n", "axes[1].set_xlabel('Longitude coordinates along contour')\n", "axes[1].set_ylabel('Cumulative transport (Sv)');" ] }, { "cell_type": "markdown", "id": "e266f75a-8f16-4a20-aaf5-24ff8464b1c3", "metadata": {}, "source": [ "We can see that there is a net northward transport across the Antarctic Circumpolar Current in the top 500m - this is the Ekman wind-driven transport. We could then choose to extract the density (or salt and temperature) along this same path, do this by interpolating density to the north and eastern edge of t-cells. Then we could bin the transports in each depth level into the corresponding density, to determine the transport across the contour in density space. An example of this calculation can be found in https://github.com/claireyung/Topographic_Hotspots_Upwelling-Paper_Code/blob/main/Analysis_Code/Save_and_bin_along_contours.ipynb. " ] }, { "cell_type": "code", "execution_count": null, "id": "d47d6e63-e147-4c7f-876a-b2057ec59d4a", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python [conda env:analysis3-22.07]", "language": "python", "name": "conda-env-analysis3-22.07-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.15" } }, "nbformat": 4, "nbformat_minor": 5 }