{ "cells": [ { "cell_type": "markdown", "id": "d5a466a9-0be2-48ea-8648-49ad2c97a359", "metadata": {}, "source": [ "# Calculate pairwise distances between a contour and grid cells\n", "\n", "In this notebook, we will demonstrate how to calculate the distance from every grid cell to the nearest grid cell along a contour. We will demonstrate this by computing the distance from each grid cell in a data array to the sea ice edge. We will use monthly sea ice concentration from ACCESS-OM2-01 over the Southern Ocean to perform these calculations. \n", " \n", "*Useful definitions* \n", "**Nearest neighbour**: Refers to the search of the point within a predetermined set of points that is located closest (spatially) to a given point. In order words, what grid cell along the sea ice edge is closest to a grid cell with coordinates `i`, `j`. \n", "**Sea ice edge**: Refers to the northernmost grid cell where sea ice concentration is $10\\%$ or above." ] }, { "cell_type": "markdown", "id": "3df39598-3b8d-4fae-956d-f50399f3aaaf", "metadata": {}, "source": [ "## Loading modules" ] }, { "cell_type": "code", "execution_count": 1, "id": "5d591a48-9911-4c59-a8ee-481d883777cc", "metadata": { "tags": [] }, "outputs": [], "source": [ "import intake\n", "\n", "import xarray as xr\n", "import numpy as np\n", "import datetime as dt\n", "\n", "from sklearn.neighbors import BallTree\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "f95ceb03-d722-49c3-b4cb-71bd9e0b1304", "metadata": {}, "source": [ "## Creating a session in the COSIMA cookbook" ] }, { "cell_type": "code", "execution_count": 2, "id": "5076a238-0d66-4c10-8f95-b6de4824a47a", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.08/lib/python3.11/site-packages/distributed/node.py:187: UserWarning: Port 8787 is already in use.\n", "Perhaps you already have a cluster running?\n", "Hosting the HTTP server on port 40215 instead\n", " warnings.warn(\n" ] }, { "data": { "text/html": [ "
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Client

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Client-11a12ea0-78c7-11f0-b090-00000190fe80

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Connection method: Cluster objectCluster type: distributed.LocalCluster
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Cluster Info

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LocalCluster

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a7eb649a

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Status: runningUsing processes: True
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Scheduler Info

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Scheduler

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Scheduler-e6339785-e211-400b-a595-8b9a94a16f66

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\n", " Comm: tcp://127.0.0.1:41361\n", " \n", " Workers: 0 \n", "
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Workers

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Worker: 0

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\n", " Comm: tcp://127.0.0.1:40045\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/33431/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:35547\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-7bhsctb_\n", "
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Worker: 1

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\n", " Comm: tcp://127.0.0.1:33119\n", " \n", " Total threads: 1\n", "
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\n", " Nanny: tcp://127.0.0.1:43023\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-gzvtdyw8\n", "
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Worker: 2

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\n", " Comm: tcp://127.0.0.1:42199\n", " \n", " Total threads: 1\n", "
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\n", " Nanny: tcp://127.0.0.1:35095\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-uysktptr\n", "
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Worker: 3

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\n", " Comm: tcp://127.0.0.1:33931\n", " \n", " Total threads: 1\n", "
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\n", " Nanny: tcp://127.0.0.1:36735\n", "
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Worker: 4

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\n", " Nanny: tcp://127.0.0.1:34231\n", "
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Worker: 5

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\n", " Nanny: tcp://127.0.0.1:41883\n", "
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Worker: 6

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Worker: 7

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Worker: 8

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Worker: 9

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Worker: 10

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Worker: 11

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Worker: 12

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Worker: 13

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Worker: 14

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Worker: 15

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Worker: 16

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Worker: 17

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Worker: 18

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\n", " Nanny: tcp://127.0.0.1:44323\n", "
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Worker: 19

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\n", " Comm: tcp://127.0.0.1:36663\n", " \n", " Total threads: 1\n", "
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\n", " Nanny: tcp://127.0.0.1:38475\n", "
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Worker: 20

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\n", " Comm: tcp://127.0.0.1:43095\n", " \n", " Total threads: 1\n", "
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\n", " Nanny: tcp://127.0.0.1:43131\n", "
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Worker: 21

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\n", " Comm: tcp://127.0.0.1:46681\n", " \n", " Total threads: 1\n", "
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\n", " Nanny: tcp://127.0.0.1:32793\n", "
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Worker: 22

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\n", " Comm: tcp://127.0.0.1:37005\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/33183/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:36819\n", "
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Worker: 23

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\n", " Comm: tcp://127.0.0.1:43127\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/44245/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:38975\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-gele627d\n", "
\n", "
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Worker: 24

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:41509\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/42241/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:44757\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-1py6y26r\n", "
\n", "
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Worker: 25

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:35813\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/45665/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:36579\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-2gu9i9n6\n", "
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Worker: 26

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:39211\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/46623/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:38141\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-5np3mjh3\n", "
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Worker: 27

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:38071\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/36319/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:46819\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-d3yc6l3e\n", "
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Worker: 28

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\n", " Comm: tcp://127.0.0.1:34385\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/35777/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:43557\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-rh2nfpgn\n", "
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Worker: 29

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\n", " Comm: tcp://127.0.0.1:35273\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/36781/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:33359\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-9t1om534\n", "
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Worker: 30

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\n", " Comm: tcp://127.0.0.1:33687\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/44689/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:41341\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-ne09e0hn\n", "
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Worker: 31

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\n", " Comm: tcp://127.0.0.1:35689\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/45031/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:37793\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-187i7zou\n", "
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Worker: 32

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\n", " Comm: tcp://127.0.0.1:39099\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/37901/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:42365\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-v5ud9242\n", "
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Worker: 33

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\n", " Comm: tcp://127.0.0.1:32803\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/42059/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:38909\n", "
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Worker: 34

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\n", " Comm: tcp://127.0.0.1:37453\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/33303/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:40469\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-66aqd0_z\n", "
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Worker: 35

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\n", " Comm: tcp://127.0.0.1:35525\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/32813/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:33757\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-ysm8p6tp\n", "
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Worker: 36

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\n", " Comm: tcp://127.0.0.1:39883\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/41081/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:44353\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-t87hxad5\n", "
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Worker: 37

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\n", " Comm: tcp://127.0.0.1:43855\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/41485/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:42413\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-bizqkrji\n", "
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Worker: 38

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\n", " Comm: tcp://127.0.0.1:39319\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/40739/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:38777\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-l3w3sa26\n", "
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Worker: 39

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\n", " Comm: tcp://127.0.0.1:44159\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/36889/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:45509\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-h2q6hwsj\n", "
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Worker: 40

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\n", " Comm: tcp://127.0.0.1:40803\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/36863/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:39947\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-zgngwsuw\n", "
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Worker: 41

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\n", " Comm: tcp://127.0.0.1:43281\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/39743/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:32915\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-iu3d1d9p\n", "
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Worker: 42

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:40897\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/35627/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:37289\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-x6_y5afk\n", "
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Worker: 43

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:46033\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/43335/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:46287\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-a45b0je2\n", "
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Worker: 44

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:37835\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/34499/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:42865\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-0syf_wud\n", "
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Worker: 45

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\n", " Comm: tcp://127.0.0.1:39061\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/35489/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:41353\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-aaoj4quq\n", "
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Worker: 46

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:46777\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/35247/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:41841\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-4hvnt4h1\n", "
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Worker: 47

\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "\n", "
\n", " Comm: tcp://127.0.0.1:36635\n", " \n", " Total threads: 1\n", "
\n", " Dashboard: /proxy/36453/status\n", " \n", " Memory: 3.93 GiB\n", "
\n", " Nanny: tcp://127.0.0.1:34097\n", "
\n", " Local directory: /jobfs/147046130.gadi-pbs/dask-scratch-space/worker-x1xw29_w\n", "
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" ], "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from dask.distributed import Client\n", "client = Client(threads_per_worker = 1)\n", "client" ] }, { "cell_type": "markdown", "id": "c45e1335-cd0b-4773-9e8f-4df654d38aa8", "metadata": {}, "source": [ "## Accessing ACCESS-OM2-01 data\n", "\n", "First we load the ACCESS-NRI default intake catalog." ] }, { "cell_type": "code", "execution_count": 3, "id": "06213890-26f2-4f14-871f-523078d6c9a5", "metadata": {}, "outputs": [], "source": [ "catalog = intake.cat.access_nri" ] }, { "cell_type": "markdown", "id": "50cbd6c4-b6ed-437a-8b82-37751cd66e6b", "metadata": {}, "source": [ "We use monthly sea ice outputs. Here, we load only two months of sea ice data." ] }, { "cell_type": "code", "execution_count": 4, "id": "b1de38e7-862a-4974-9a64-0b1046391571", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.08/lib/python3.11/site-packages/intake_esm/core.py:301: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", " records = grouped.get_group(internal_key).to_dict(orient='records')\n" ] }, { "data": { "text/html": [ "
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<xarray.DataArray 'aice_m' (time: 3, nj: 2700, ni: 3600)> Size: 117MB\n",
       "dask.array<getitem, shape=(3, 2700, 3600), dtype=float32, chunksize=(1, 2700, 3600), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 24B 1978-01-01 1978-02-01 1978-03-01\n",
       "    TLON     (nj, ni) float32 39MB dask.array<chunksize=(2700, 3600), meta=np.ndarray>\n",
       "    TLAT     (nj, ni) float32 39MB dask.array<chunksize=(2700, 3600), meta=np.ndarray>\n",
       "    ULON     (nj, ni) float32 39MB dask.array<chunksize=(2700, 3600), meta=np.ndarray>\n",
       "    ULAT     (nj, ni) float32 39MB dask.array<chunksize=(2700, 3600), meta=np.ndarray>\n",
       "Dimensions without coordinates: nj, ni\n",
       "Attributes:\n",
       "    units:          1\n",
       "    long_name:      ice area  (aggregate)\n",
       "    cell_measures:  area: tarea\n",
       "    cell_methods:   time: mean\n",
       "    time_rep:       averaged
" ], "text/plain": [ " Size: 117MB\n", "dask.array\n", "Coordinates:\n", " * time (time) datetime64[ns] 24B 1978-01-01 1978-02-01 1978-03-01\n", " TLON (nj, ni) float32 39MB dask.array\n", " TLAT (nj, ni) float32 39MB dask.array\n", " ULON (nj, ni) float32 39MB dask.array\n", " ULAT (nj, ni) float32 39MB dask.array\n", "Dimensions without coordinates: nj, ni\n", "Attributes:\n", " units: 1\n", " long_name: ice area (aggregate)\n", " cell_measures: area: tarea\n", " cell_methods: time: mean\n", " time_rep: averaged" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cat_subset = catalog['01deg_jra55v140_iaf_cycle4']\n", "ds = cat_subset.search(variable='aice_m',file_id='seaIce.1mon.d2:2.nc:5.ni:3600.nj:2700'\n", ").to_dask(\n", " xarray_combine_by_coords_kwargs=dict(compat=\"override\",\n", " data_vars=\"minimal\",\n", " coords=\"minimal\"),\n", " xarray_open_kwargs={\"chunks\" : \"auto\"},\n", ")\n", "\n", "var_ice = ds['aice_m']\n", "var_ice = var_ice.sel(time=slice('1978-01', '1978-03'))\n", "var_ice" ] }, { "cell_type": "markdown", "id": "ce17902e-7eae-4a71-aa8a-94703a1bb4ad", "metadata": {}, "source": [ "The sea ice outputs need some processing before we can start our calculations. You can check this [example](../02-Easy-Recipes/Sea_Ice_Coordinates.ipynb) for a guide on how to load and plot sea ice data. \n \nWe will follow these processing steps:\n1. Correct time dimension values by subtracting 12 hours,\n2. Attach the ocean model grid so we can calculate distances." ] }, { "cell_type": "code", "execution_count": 5, "id": "5f3c2530-9225-4b59-ba62-22f374698b00", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.08/lib/python3.11/site-packages/intake_esm/core.py:301: FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n", " records = grouped.get_group(internal_key).to_dict(orient='records')\n" ] }, { "data": { "text/html": [ "
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<xarray.DataArray 'aice_m' (time: 3, yt_ocean: 713, xt_ocean: 3600)> Size: 31MB\n",
       "dask.array<getitem, shape=(3, 713, 3600), dtype=float32, chunksize=(1, 713, 3600), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "    TLON      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "    TLAT      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "    ULON      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "    ULAT      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "  * time      (time) datetime64[ns] 24B 1977-12-31T12:00:00 ... 1978-02-28T12...\n",
       "  * xt_ocean  (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95\n",
       "  * yt_ocean  (yt_ocean) float64 6kB -79.97 -79.93 -79.88 ... -45.11 -45.04\n",
       "Attributes:\n",
       "    units:          1\n",
       "    long_name:      ice area  (aggregate)\n",
       "    cell_measures:  area: tarea\n",
       "    cell_methods:   time: mean\n",
       "    time_rep:       averaged
" ], "text/plain": [ " Size: 31MB\n", "dask.array\n", "Coordinates:\n", " TLON (yt_ocean, xt_ocean) float32 10MB dask.array\n", " TLAT (yt_ocean, xt_ocean) float32 10MB dask.array\n", " ULON (yt_ocean, xt_ocean) float32 10MB dask.array\n", " ULAT (yt_ocean, xt_ocean) float32 10MB dask.array\n", " * time (time) datetime64[ns] 24B 1977-12-31T12:00:00 ... 1978-02-28T12...\n", " * xt_ocean (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95\n", " * yt_ocean (yt_ocean) float64 6kB -79.97 -79.93 -79.88 ... -45.11 -45.04\n", "Attributes:\n", " units: 1\n", " long_name: ice area (aggregate)\n", " cell_measures: area: tarea\n", " cell_methods: time: mean\n", " time_rep: averaged" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Loading area_t to get ocean grid\n", "var_search = catalog['01deg_jra55v140_iaf_cycle4'].search(variable='area_t')\n", "var_search = var_search.search(path=var_search.df['path'][0])\n", "ds = var_search.to_dask(xarray_open_kwargs={\"chunks\": \"auto\"})\n", "area_t = ds['area_t']\n", "\n", "# Apply time correction so data appears in the middle (12:00) of the day rather than at the beginning of the day (00:00)\n", "var_ice['time'] = var_ice.time.to_pandas() - dt.timedelta(hours = 12)\n", "\n", "# Change coordinates so they match ocean dimensions \n", "var_ice.coords['ni'] = area_t['xt_ocean'].values\n", "var_ice.coords['nj'] = area_t['yt_ocean'].values\n", "\n", "# Rename coordinate variables so they match ocean data\n", "var_ice = var_ice.rename(({'ni': 'xt_ocean', 'nj': 'yt_ocean'}))\n", "\n", "# Subsetting data for the Southern Ocean\n", "var_ice = var_ice.sel(yt_ocean = slice(-80, -45))\n", "var_ice" ] }, { "cell_type": "markdown", "id": "f1c80d3d-fcea-4ced-b637-ea9e4bcbe701", "metadata": {}, "source": [ "## Finding sea ice edge\n", "The sea ice edge is the defined as the northernmost areas where sea ice concentration (SIC) is over $10\\%$. This is a multistep process:\n", "\n", "1. Identify cells where $\\text{SIC} >= 0.1$, classifying them with a value of 1;\n", "2. Calculate the cumulative sum along latitude;\n", "3. Apply mask to constrain to only cells with $\\text{SIC} >= 0.1$;\n", "4. Choose the maximum for each longitude.\n", "\n", "We'll demonstrate this process over the first timestep of data." ] }, { "cell_type": "code", "execution_count": 6, "id": "06538e50-5575-4e5a-906e-1604f0ab7275", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "is_ice = var_ice.isel(time=0) >= 0.1\n", "cumulative_ice = is_ice.cumsum(dim='yt_ocean')\n", "ice_edge = (cumulative_ice == cumulative_ice.max('yt_ocean')) * is_ice\n", "\n", "ice_edge.plot()" ] }, { "cell_type": "markdown", "id": "ae74ff21-3795-4e80-ae7c-5d1fb9819bb2", "metadata": {}, "source": [ "### Checking results in relation to SIC data" ] }, { "cell_type": "code", "execution_count": 7, "id": "1ff776bb-82ac-41cb-8b32-8f6cd40ce82b", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "var_ice.where(var_ice >= 0.1).isel(time=0).plot()\n", "ice_edge.plot.contour(colors=[\"red\"])" ] }, { "cell_type": "markdown", "id": "508d16c8-31e8-45a8-9572-7266d84a7caf", "metadata": {}, "source": [ "Above we plotted only cells with SIC greater or equal to 0.1. The red line represents the sea ice edge we identified in the previous step. We can be satisfied that we identified the sea ice edge correctly." ] }, { "cell_type": "markdown", "id": "298b40ce-44e2-491a-9a20-20c5075686ed", "metadata": {}, "source": [ "## Getting coordinate pairs for our entire grid\n", "We will use the latitude and longitude values in our data to create coordinate pairs. We only need to get this information once if we are calculating distances from the same grid. " ] }, { "cell_type": "code", "execution_count": 8, "id": "304d6a4b-11bd-4fd9-ab78-f113014a0fd1", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array([[ -79.96816911, -279.95 ],\n", " [ -79.96816911, -279.85 ],\n", " [ -79.96816911, -279.75 ],\n", " ...,\n", " [ -45.03607147, 79.75 ],\n", " [ -45.03607147, 79.85 ],\n", " [ -45.03607147, 79.95 ]])" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grid_x, grid_y = np.meshgrid(\n", " var_ice.xt_ocean.values,\n", " var_ice.yt_ocean.values,\n", ")\n", "\n", "# Changing shape so there are two values per row\n", "grid_coords = np.vstack([grid_y.flat, grid_x.flat]).T\n", "grid_coords" ] }, { "cell_type": "markdown", "id": "83cb7c8c-d921-4cc5-a1b8-b472a420457f", "metadata": {}, "source": [ "## Getting coordinate pairs for sea ice edge\n", "We will find the index for the sea ice edge so we can identify the latitude at which the sea ice edge occurs. This will be combined with all longitude values to create the coordinate pairs for the sea ice edge. \n", " \n", "Note that this step has to be done once for every time step as the sea ice edge changes over time." ] }, { "cell_type": "code", "execution_count": 9, "id": "86cf7d0e-cc59-459e-9ecb-2a1e4f5a0fd7", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array([[ -61.84325357, -279.95 ],\n", " [ -61.84325357, -279.85 ],\n", " [ -61.84325357, -279.75 ],\n", " ...,\n", " [ -61.60640174, 79.75 ],\n", " [ -61.65391774, 79.85 ],\n", " [ -61.84325357, 79.95 ]])" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Getting the indices for cell with maximum value along yt_ocean dimension\n", "ice_yt = ice_edge.yt_ocean[ice_edge.argmax(dim='yt_ocean')]\n", "ice_coords = np.vstack([ice_yt, ice_edge.xt_ocean]).T\n", "ice_coords" ] }, { "cell_type": "markdown", "id": "dace170b-eefc-4377-9bbf-4c6d78fdd500", "metadata": {}, "source": [ "## Using Nearest Neighbours algorithm to calculate distance to closest sea ice edge cell\n", "\n", "We will build a data structure called [BallTree](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.BallTree.html#sklearn.neighbors.BallTree) for our calculations, from the points comprising the sea ice edge. This structure allows us to efficiently query the nearest point within the sea ice edge set to any arbitrary point, according to some kind of metric. Because we're on a sphere, we use the [haversine (great circle) distance](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.haversine_distances.html), which also requires that we transform coordinates from degrees to radians. `scikit-learn` also offers a [KDTree](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KDTree.html) for a similar purpose, but this doesn't support the haversine distance as a metric, so we opt for the ball tree instead.\n", "\n", "The advantage of using a data structure like a ball tree is that we trade off slightly more time and memory to construct the tree for more efficient querying. This makes it feasible to query the closest sea ice edge cell to every point on the grid, which may otherwise have excessive time and/or memory requirements for a brute force approach." ] }, { "cell_type": "code", "execution_count": 10, "id": "09edbc2f-c5a0-48fc-bbdd-2b13da68ce69", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 6.5 ms, sys: 0 ns, total: 6.5 ms\n", "Wall time: 5.71 ms\n" ] } ], "source": [ "%%time\n", "\n", "# First we set up our Ball Tree. Coordinates must be given in radians.\n", "ball_tree = BallTree(np.deg2rad(ice_coords), metric='haversine')" ] }, { "cell_type": "code", "execution_count": 11, "id": "b39e0332-8172-493a-8dbc-c4e716432980", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 30.4 s, sys: 2.57 s, total: 33 s\n", "Wall time: 22.1 s\n" ] } ], "source": [ "%%time\n", "\n", "# The nearest neighbour calculation will give two outputs: distances and indices\n", "# We only need the distances for now, so ignore the second output\n", "distances_radians, _ = ball_tree.query(np.deg2rad(grid_coords), return_distance=True)" ] }, { "cell_type": "markdown", "id": "7b60acd8-9860-4cf0-a614-1c0724700bd0", "metadata": {}, "source": [ "## Transforming distance from radians to kilometers\n", "\n", "Because the haversine distance operates in terms of radians only, we will need to multiply by the resulting distances by Earth's radius to get distances in radians. We will also reshape the results so it matches our original grid." ] }, { "cell_type": "code", "execution_count": 12, "id": "ee5eb05a-8e86-4423-859f-366a4a4e067e", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.DataArray (yt_ocean: 713, xt_ocean: 3600)> Size: 21MB\n",
       "array([[ 805.00144028,  803.19226827,  801.38249999, ...,  810.42536522,\n",
       "         808.61799012,  806.81001469],\n",
       "       [ 806.69292563,  804.88000362,  803.06648432, ...,  812.12809432,\n",
       "         810.31697234,  808.50524899],\n",
       "       [ 808.40803346,  806.59143086,  804.77423025, ...,  813.85423949,\n",
       "         812.03943914,  810.22403667],\n",
       "       ...,\n",
       "       [1607.76336769, 1606.55053756, 1605.36467069, ..., 1611.56299844,\n",
       "        1610.26966326, 1609.00309777],\n",
       "       [1615.51041181, 1614.30178279, 1613.12003095, ..., 1619.29692977,\n",
       "        1618.0080497 , 1616.74585538],\n",
       "       [1623.26793377, 1622.06347241, 1620.88580274, ..., 1627.04144284,\n",
       "        1625.75698268, 1624.4991249 ]])\n",
       "Coordinates:\n",
       "  * yt_ocean  (yt_ocean) float64 6kB -79.97 -79.93 -79.88 ... -45.11 -45.04\n",
       "  * xt_ocean  (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95
" ], "text/plain": [ " Size: 21MB\n", "array([[ 805.00144028, 803.19226827, 801.38249999, ..., 810.42536522,\n", " 808.61799012, 806.81001469],\n", " [ 806.69292563, 804.88000362, 803.06648432, ..., 812.12809432,\n", " 810.31697234, 808.50524899],\n", " [ 808.40803346, 806.59143086, 804.77423025, ..., 813.85423949,\n", " 812.03943914, 810.22403667],\n", " ...,\n", " [1607.76336769, 1606.55053756, 1605.36467069, ..., 1611.56299844,\n", " 1610.26966326, 1609.00309777],\n", " [1615.51041181, 1614.30178279, 1613.12003095, ..., 1619.29692977,\n", " 1618.0080497 , 1616.74585538],\n", " [1623.26793377, 1622.06347241, 1620.88580274, ..., 1627.04144284,\n", " 1625.75698268, 1624.4991249 ]])\n", "Coordinates:\n", " * yt_ocean (yt_ocean) float64 6kB -79.97 -79.93 -79.88 ... -45.11 -45.04\n", " * xt_ocean (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "distances_km = distances_radians * 6371\n", "\n", "distances_t0 = xr.DataArray(\n", " data=distances_km.reshape(var_ice.yt_ocean.size, -1),\n", " dims=['yt_ocean', 'xt_ocean'],\n", " coords={'yt_ocean': var_ice.yt_ocean, 'xt_ocean': var_ice.xt_ocean}\n", ")\n", "\n", "distances_t0" ] }, { "cell_type": "markdown", "id": "a84eef60-4d30-4510-9a77-d4cd22a972b0", "metadata": {}, "source": [ "## Turning results into data array\n", "We will also apply a mask to our results, so we will only keep values for cells where SIC was greater or equal to 0.1." ] }, { "cell_type": "code", "execution_count": 13, "id": "a1a74720-552f-4dec-85cb-8bb4eea1b895", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.08/lib/python3.11/site-packages/distributed/client.py:3363: UserWarning: Sending large graph of size 20.73 MiB.\n", "This may cause some slowdown.\n", "Consider loading the data with Dask directly\n", " or using futures or delayed objects to embed the data into the graph without repetition.\n", "See also https://docs.dask.org/en/stable/best-practices.html#load-data-with-dask for more information.\n", " warnings.warn(\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "distances_t0.where(is_ice).plot()" ] }, { "cell_type": "markdown", "id": "7f1dad1e-e835-4685-be38-9f0eb36f662f", "metadata": {}, "source": [ "## Calculating results for other time steps\n", "\n", "We can wrap this up into a function to calculate distances for a given timestep. This function returns the ice mask as a second value, so that we can make the plots in the same format as demonstrated so far." ] }, { "cell_type": "code", "execution_count": 14, "id": "f2de3cdc-351c-4b73-8786-57b71c436915", "metadata": { "tags": [] }, "outputs": [], "source": [ "def ice_edge_distances(ice_ds):\n", " x, y = np.meshgrid(np.deg2rad(var_ice.xt_ocean.values),\n", " np.deg2rad(var_ice.yt_ocean.values))\n", " grid_coords = np.vstack([y.flat, x.flat]).T\n", " \n", " is_ice = ice_ds >= 0.1\n", " cumulative_ice = is_ice.cumsum(dim='yt_ocean')\n", " ice_edge = (cumulative_ice == cumulative_ice.max('yt_ocean')) * is_ice\n", " \n", " ice_yt = ice_edge.yt_ocean[ice_edge.argmax(dim='yt_ocean')]\n", " ice_coords = np.vstack([ice_yt, ice_edge.xt_ocean]).T\n", " \n", " ball_tree = BallTree(np.deg2rad(ice_coords), metric='haversine')\n", " distances_radians, _ = ball_tree.query(grid_coords, return_distance=True)\n", " \n", " distances_km = distances_radians * 6371\n", " distances = xr.DataArray(\n", " data=distances_km.reshape(ice_ds.yt_ocean.size, -1),\n", " dims=['yt_ocean', 'xt_ocean'],\n", " coords={'yt_ocean': ice_ds.yt_ocean, 'xt_ocean': ice_ds.xt_ocean},\n", " name='ice_edge_distance'\n", " )\n", " \n", " return distances, is_ice" ] }, { "cell_type": "code", "execution_count": 15, "id": "d14e67c2-d1c8-4ba3-9d75-2aae21d2ebf0", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.08/lib/python3.11/site-packages/distributed/client.py:3363: UserWarning: Sending large graph of size 20.73 MiB.\n", "This may cause some slowdown.\n", "Consider loading the data with Dask directly\n", " or using futures or delayed objects to embed the data into the graph without repetition.\n", "See also https://docs.dask.org/en/stable/best-practices.html#load-data-with-dask for more information.\n", " warnings.warn(\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "distances_t1, mask = ice_edge_distances(var_ice.isel(time=1))\n", "\n", "distances_t1.where(mask).plot()" ] }, { "cell_type": "markdown", "id": "c6442376-de87-4bb3-bc07-4f6e448f8763", "metadata": {}, "source": [ "## Stacking results into one data array" ] }, { "cell_type": "code", "execution_count": 16, "id": "916f236d-6607-4812-a658-64ca364296ac", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "
<xarray.DataArray (time: 2, yt_ocean: 713, xt_ocean: 3600)> Size: 41MB\n",
       "dask.array<concatenate, shape=(2, 713, 3600), dtype=float64, chunksize=(1, 713, 3600), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * yt_ocean  (yt_ocean) float64 6kB -79.97 -79.93 -79.88 ... -45.11 -45.04\n",
       "  * xt_ocean  (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95\n",
       "    TLON      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "    TLAT      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "    ULON      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "    ULAT      (yt_ocean, xt_ocean) float32 10MB dask.array<chunksize=(713, 3600), meta=np.ndarray>\n",
       "  * time      (time) datetime64[ns] 16B 1977-12-31T12:00:00 1978-01-31T12:00:00
" ], "text/plain": [ " Size: 41MB\n", "dask.array\n", "Coordinates:\n", " * yt_ocean (yt_ocean) float64 6kB -79.97 -79.93 -79.88 ... -45.11 -45.04\n", " * xt_ocean (xt_ocean) float64 29kB -279.9 -279.8 -279.7 ... 79.75 79.85 79.95\n", " TLON (yt_ocean, xt_ocean) float32 10MB dask.array\n", " TLAT (yt_ocean, xt_ocean) float32 10MB dask.array\n", " ULON (yt_ocean, xt_ocean) float32 10MB dask.array\n", " ULAT (yt_ocean, xt_ocean) float32 10MB dask.array\n", " * time (time) datetime64[ns] 16B 1977-12-31T12:00:00 1978-01-31T12:00:00" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dist_ice = xr.concat([distances_t0.where(is_ice), distances_t1.where(mask)], dim='time')\n", "dist_ice" ] }, { "cell_type": "code", "execution_count": 17, "id": "6b9c254a-dc1c-4d7e-9c78-18bc2099d936", "metadata": { "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/g/data/xp65/public/apps/med_conda/envs/analysis3-25.08/lib/python3.11/site-packages/distributed/client.py:3363: UserWarning: Sending large graph of size 40.32 MiB.\n", "This may cause some slowdown.\n", "Consider loading the data with Dask directly\n", " or using futures or delayed objects to embed the data into the graph without repetition.\n", "See also https://docs.dask.org/en/stable/best-practices.html#load-data-with-dask for more information.\n", " warnings.warn(\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dist_ice.plot(col='time')" ] }, { "cell_type": "markdown", "id": "d0057e34-7fc6-469c-a850-1b07f2da8239", "metadata": {}, "source": [ "We are done! We should be able to follow the same workflow to calculate distances to any line/point of your interest." ] }, { "cell_type": "code", "execution_count": 18, "id": "b3d128e2-e3fc-4f1b-be87-38066338e6fb", "metadata": {}, "outputs": [], "source": [ "client.close()" ] } ], "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": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 5 }