From 4c89ed27841eb71c369602453d4165adc83764bb Mon Sep 17 00:00:00 2001 From: "Navid C. Constantinou" Date: Fri, 4 Oct 2024 14:29:22 +1000 Subject: [PATCH] fix tripole --- .../Apply_function_to_every_gridpoint.ipynb | 929 +++++++++++++----- 1 file changed, 700 insertions(+), 229 deletions(-) diff --git a/Recipes/Apply_function_to_every_gridpoint.ipynb b/Recipes/Apply_function_to_every_gridpoint.ipynb index 27cabac8..4c5eda7f 100644 --- a/Recipes/Apply_function_to_every_gridpoint.ipynb +++ b/Recipes/Apply_function_to_every_gridpoint.ipynb @@ -46,8 +46,9 @@ "import xarray as xr\n", "import numpy as np\n", "import scipy.stats\n", + "import cartopy.crs as ccrs\n", "import intake\n", - "cat = intake.cat.access_nri" + "catalog = intake.cat.access_nri" ] }, { @@ -63,7 +64,7 @@ "
\n", "
\n", "

Client

\n", - "

Client-99754ea3-8203-11ef-90ec-000001adfe80

\n", + "

Client-c07d9f81-8207-11ef-99aa-000001adfe80

\n", " \n", "\n", " \n", @@ -98,7 +99,7 @@ " \n", "
\n", "

LocalCluster

\n", - "

02966292

\n", + "

079f76c6

\n", "
\n", " \n", "
\n", @@ -135,11 +136,11 @@ "
\n", "
\n", "

Scheduler

\n", - "

Scheduler-7be50f08-de22-4731-85fa-38250fb5d679

\n", + "

Scheduler-17648e8b-c006-4d22-83f9-d8440e29bd2b

\n", " \n", " \n", " \n", "
\n", - " Comm: tcp://127.0.0.1:43997\n", + " Comm: tcp://127.0.0.1:35663\n", " \n", " Workers: 48\n", @@ -181,7 +182,7 @@ " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -226,7 +227,7 @@ "
\n", - " Comm: tcp://127.0.0.1:35103\n", + " Comm: tcp://127.0.0.1:37715\n", " \n", " Total threads: 1\n", @@ -189,7 +190,7 @@ "
\n", - " Dashboard: /proxy/38311/status\n", + " Dashboard: /proxy/44669/status\n", " \n", " Memory: 0 B\n", @@ -197,13 +198,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:42615\n", + " Nanny: tcp://127.0.0.1:35785\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-p9_htlzn\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-gt4j48wq\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -271,7 +272,7 @@ "
\n", - " Comm: tcp://127.0.0.1:43811\n", + " Comm: tcp://127.0.0.1:32881\n", " \n", " Total threads: 1\n", @@ -234,7 +235,7 @@ "
\n", - " Dashboard: /proxy/38427/status\n", + " Dashboard: /proxy/41371/status\n", " \n", " Memory: 0 B\n", @@ -242,13 +243,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:33837\n", + " Nanny: tcp://127.0.0.1:39537\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-3xvzvj8q\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-2msnrca0\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -316,7 +317,7 @@ "
\n", - " Comm: tcp://127.0.0.1:46305\n", + " Comm: tcp://127.0.0.1:37867\n", " \n", " Total threads: 1\n", @@ -279,7 +280,7 @@ "
\n", - " Dashboard: /proxy/36681/status\n", + " Dashboard: /proxy/41029/status\n", " \n", " Memory: 0 B\n", @@ -287,13 +288,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:36727\n", + " Nanny: tcp://127.0.0.1:41519\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-7zmenml_\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-2r4b2mvb\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -361,7 +362,7 @@ "
\n", - " Comm: tcp://127.0.0.1:44279\n", + " Comm: tcp://127.0.0.1:39653\n", " \n", " Total threads: 1\n", @@ -324,7 +325,7 @@ "
\n", - " Dashboard: /proxy/37695/status\n", + " Dashboard: /proxy/45289/status\n", " \n", " Memory: 0 B\n", @@ -332,13 +333,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:45305\n", + " Nanny: tcp://127.0.0.1:40867\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-yyu0ctvo\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-bg2ksfi4\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -406,7 +407,7 @@ "
\n", - " Comm: tcp://127.0.0.1:40177\n", + " Comm: tcp://127.0.0.1:45411\n", " \n", " Total threads: 1\n", @@ -369,7 +370,7 @@ "
\n", - " Dashboard: /proxy/40043/status\n", + " Dashboard: /proxy/41823/status\n", " \n", " Memory: 0 B\n", @@ -377,13 +378,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:41541\n", + " Nanny: tcp://127.0.0.1:34091\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-9bvarjq8\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-46008wu1\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -451,7 +452,7 @@ "
\n", - " Comm: tcp://127.0.0.1:33725\n", + " Comm: tcp://127.0.0.1:44789\n", " \n", " Total threads: 1\n", @@ -414,7 +415,7 @@ "
\n", - " Dashboard: /proxy/38195/status\n", + " Dashboard: /proxy/40261/status\n", " \n", " Memory: 0 B\n", @@ -422,13 +423,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:37363\n", + " Nanny: tcp://127.0.0.1:34987\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-flh_8is1\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-guwrezef\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -496,7 +497,7 @@ "
\n", - " Comm: tcp://127.0.0.1:33807\n", + " Comm: tcp://127.0.0.1:37825\n", " \n", " Total threads: 1\n", @@ -459,7 +460,7 @@ "
\n", - " Dashboard: /proxy/46243/status\n", + " Dashboard: /proxy/34001/status\n", " \n", " Memory: 0 B\n", @@ -467,13 +468,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:41537\n", + " Nanny: tcp://127.0.0.1:34281\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-lca4r0q7\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-15opc7ob\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -541,7 +542,7 @@ "
\n", - " Comm: tcp://127.0.0.1:33471\n", + " Comm: tcp://127.0.0.1:34959\n", " \n", " Total threads: 1\n", @@ -504,7 +505,7 @@ "
\n", - " Dashboard: /proxy/37735/status\n", + " Dashboard: /proxy/36273/status\n", " \n", " Memory: 0 B\n", @@ -512,13 +513,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:34171\n", + " Nanny: tcp://127.0.0.1:37891\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-rklup1gt\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-iechw5o3\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -586,7 +587,7 @@ "
\n", - " Comm: tcp://127.0.0.1:40939\n", + " Comm: tcp://127.0.0.1:41343\n", " \n", " Total threads: 1\n", @@ -549,7 +550,7 @@ "
\n", - " Dashboard: /proxy/38073/status\n", + " Dashboard: /proxy/43897/status\n", " \n", " Memory: 0 B\n", @@ -557,13 +558,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:33569\n", + " Nanny: tcp://127.0.0.1:41113\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-bf_vgp4k\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-nfec_bh8\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -631,7 +632,7 @@ "
\n", - " Comm: tcp://127.0.0.1:35795\n", + " Comm: tcp://127.0.0.1:32835\n", " \n", " Total threads: 1\n", @@ -594,7 +595,7 @@ "
\n", - " Dashboard: /proxy/36181/status\n", + " Dashboard: /proxy/38471/status\n", " \n", " Memory: 0 B\n", @@ -602,13 +603,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:35543\n", + " Nanny: tcp://127.0.0.1:41115\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-bt8crafk\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-qmxevv3r\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -676,7 +677,7 @@ "
\n", - " Comm: tcp://127.0.0.1:36029\n", + " Comm: tcp://127.0.0.1:43481\n", " \n", " Total threads: 1\n", @@ -639,7 +640,7 @@ "
\n", - " Dashboard: /proxy/37333/status\n", + " Dashboard: /proxy/45391/status\n", " \n", " Memory: 0 B\n", @@ -647,13 +648,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:42905\n", + " Nanny: tcp://127.0.0.1:34843\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-0f5_3lqo\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-or3t7xxb\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -721,7 +722,7 @@ "
\n", - " Comm: tcp://127.0.0.1:37131\n", + " Comm: tcp://127.0.0.1:43313\n", " \n", " Total threads: 1\n", @@ -684,7 +685,7 @@ "
\n", - " Dashboard: /proxy/41095/status\n", + " Dashboard: /proxy/40727/status\n", " \n", " Memory: 0 B\n", @@ -692,13 +693,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:46255\n", + " Nanny: tcp://127.0.0.1:39047\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-n2vtyaj2\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-mvm6y070\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -766,7 +767,7 @@ "
\n", - " Comm: tcp://127.0.0.1:40829\n", + " Comm: tcp://127.0.0.1:39739\n", " \n", " Total threads: 1\n", @@ -729,7 +730,7 @@ "
\n", - " Dashboard: /proxy/39091/status\n", + " Dashboard: /proxy/35913/status\n", " \n", " Memory: 0 B\n", @@ -737,13 +738,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:35323\n", + " Nanny: tcp://127.0.0.1:37225\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-vcaqwy2a\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-j7qd0kpr\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -811,7 +812,7 @@ "
\n", - " Comm: tcp://127.0.0.1:46131\n", + " Comm: tcp://127.0.0.1:40891\n", " \n", " Total threads: 1\n", @@ -774,7 +775,7 @@ "
\n", - " Dashboard: /proxy/38685/status\n", + " Dashboard: /proxy/40431/status\n", " \n", " Memory: 0 B\n", @@ -782,13 +783,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:33915\n", + " Nanny: tcp://127.0.0.1:40985\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-j01emtrx\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-z7y8fovn\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -856,7 +857,7 @@ "
\n", - " Comm: tcp://127.0.0.1:43159\n", + " Comm: tcp://127.0.0.1:43749\n", " \n", " Total threads: 1\n", @@ -819,7 +820,7 @@ "
\n", - " Dashboard: /proxy/40425/status\n", + " Dashboard: /proxy/42187/status\n", " \n", " Memory: 0 B\n", @@ -827,13 +828,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:44219\n", + " Nanny: tcp://127.0.0.1:38917\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-bas8smc9\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-hs25rcxb\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -901,7 +902,7 @@ "
\n", - " Comm: tcp://127.0.0.1:35083\n", + " Comm: tcp://127.0.0.1:35245\n", " \n", " Total threads: 1\n", @@ -864,7 +865,7 @@ "
\n", - " Dashboard: /proxy/45101/status\n", + " Dashboard: /proxy/43609/status\n", " \n", " Memory: 0 B\n", @@ -872,13 +873,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:34271\n", + " Nanny: tcp://127.0.0.1:36331\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-mbslqki3\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-m982hhmu\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -946,7 +947,7 @@ "
\n", - " Comm: tcp://127.0.0.1:37407\n", + " Comm: tcp://127.0.0.1:41155\n", " \n", " Total threads: 1\n", @@ -909,7 +910,7 @@ "
\n", - " Dashboard: /proxy/45141/status\n", + " Dashboard: /proxy/42205/status\n", " \n", " Memory: 0 B\n", @@ -917,13 +918,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:45335\n", + " Nanny: tcp://127.0.0.1:36329\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-yp2wc3lp\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-llzw63ag\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -991,7 +992,7 @@ "
\n", - " Comm: tcp://127.0.0.1:36793\n", + " Comm: tcp://127.0.0.1:39049\n", " \n", " Total threads: 1\n", @@ -954,7 +955,7 @@ "
\n", - " Dashboard: /proxy/40441/status\n", + " Dashboard: /proxy/40893/status\n", " \n", " Memory: 0 B\n", @@ -962,13 +963,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:34733\n", + " Nanny: tcp://127.0.0.1:40521\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-01rqb3wg\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-ht__ndt1\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1036,7 +1037,7 @@ "
\n", - " Comm: tcp://127.0.0.1:33389\n", + " Comm: tcp://127.0.0.1:44663\n", " \n", " Total threads: 1\n", @@ -999,7 +1000,7 @@ "
\n", - " Dashboard: /proxy/36105/status\n", + " Dashboard: /proxy/32799/status\n", " \n", " Memory: 0 B\n", @@ -1007,13 +1008,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:43009\n", + " Nanny: tcp://127.0.0.1:46077\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-499khvzy\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-9v9qs7hf\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1081,7 +1082,7 @@ "
\n", - " Comm: tcp://127.0.0.1:32811\n", + " Comm: tcp://127.0.0.1:45639\n", " \n", " Total threads: 1\n", @@ -1044,7 +1045,7 @@ "
\n", - " Dashboard: /proxy/39777/status\n", + " Dashboard: /proxy/39191/status\n", " \n", " Memory: 0 B\n", @@ -1052,13 +1053,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:37425\n", + " Nanny: tcp://127.0.0.1:44051\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-fwfr27a7\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-evn_hg_d\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1126,7 +1127,7 @@ "
\n", - " Comm: tcp://127.0.0.1:34293\n", + " Comm: tcp://127.0.0.1:33631\n", " \n", " Total threads: 1\n", @@ -1089,7 +1090,7 @@ "
\n", - " Dashboard: /proxy/33357/status\n", + " Dashboard: /proxy/44117/status\n", " \n", " Memory: 0 B\n", @@ -1097,13 +1098,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:44321\n", + " Nanny: tcp://127.0.0.1:41425\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-t_st9bhk\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-xh7jep_f\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1171,7 +1172,7 @@ "
\n", - " Comm: tcp://127.0.0.1:44227\n", + " Comm: tcp://127.0.0.1:45915\n", " \n", " Total threads: 1\n", @@ -1134,7 +1135,7 @@ "
\n", - " Dashboard: /proxy/34505/status\n", + " Dashboard: /proxy/37301/status\n", " \n", " Memory: 0 B\n", @@ -1142,13 +1143,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:44655\n", + " Nanny: tcp://127.0.0.1:35953\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-7wp958gv\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-97xqxpp2\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1216,7 +1217,7 @@ "
\n", - " Comm: tcp://127.0.0.1:34895\n", + " Comm: tcp://127.0.0.1:42037\n", " \n", " Total threads: 1\n", @@ -1179,7 +1180,7 @@ "
\n", - " Dashboard: /proxy/37595/status\n", + " Dashboard: /proxy/36571/status\n", " \n", " Memory: 0 B\n", @@ -1187,13 +1188,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:35421\n", + " Nanny: tcp://127.0.0.1:46039\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-e3g8s5v9\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-0pju21oy\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1261,7 +1262,7 @@ "
\n", - " Comm: tcp://127.0.0.1:42133\n", + " Comm: tcp://127.0.0.1:42687\n", " \n", " Total threads: 1\n", @@ -1224,7 +1225,7 @@ "
\n", - " Dashboard: /proxy/43929/status\n", + " Dashboard: /proxy/35489/status\n", " \n", " Memory: 0 B\n", @@ -1232,13 +1233,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:43113\n", + " Nanny: tcp://127.0.0.1:43559\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-ruiu8dmf\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-_pz0cw0g\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1306,7 +1307,7 @@ "
\n", - " Comm: tcp://127.0.0.1:43613\n", + " Comm: tcp://127.0.0.1:44457\n", " \n", " Total threads: 1\n", @@ -1269,7 +1270,7 @@ "
\n", - " Dashboard: /proxy/34839/status\n", + " Dashboard: /proxy/32831/status\n", " \n", " Memory: 0 B\n", @@ -1277,13 +1278,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:39337\n", + " Nanny: tcp://127.0.0.1:36785\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-l8kgpqje\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-q0kcg5tm\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1351,7 +1352,7 @@ "
\n", - " Comm: tcp://127.0.0.1:44715\n", + " Comm: tcp://127.0.0.1:44037\n", " \n", " Total threads: 1\n", @@ -1314,7 +1315,7 @@ "
\n", - " Dashboard: /proxy/46159/status\n", + " Dashboard: /proxy/36473/status\n", " \n", " Memory: 0 B\n", @@ -1322,13 +1323,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:45007\n", + " Nanny: tcp://127.0.0.1:40497\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-rnhhxrsp\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-g1tj8325\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1396,7 +1397,7 @@ "
\n", - " Comm: tcp://127.0.0.1:36953\n", + " Comm: tcp://127.0.0.1:32787\n", " \n", " Total threads: 1\n", @@ -1359,7 +1360,7 @@ "
\n", - " Dashboard: /proxy/39165/status\n", + " Dashboard: /proxy/40355/status\n", " \n", " Memory: 0 B\n", @@ -1367,13 +1368,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:37381\n", + " Nanny: tcp://127.0.0.1:41453\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-aiyzznsa\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-zel265fq\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1441,7 +1442,7 @@ "
\n", - " Comm: tcp://127.0.0.1:37791\n", + " Comm: tcp://127.0.0.1:43611\n", " \n", " Total threads: 1\n", @@ -1404,7 +1405,7 @@ "
\n", - " Dashboard: /proxy/34631/status\n", + " Dashboard: /proxy/40989/status\n", " \n", " Memory: 0 B\n", @@ -1412,13 +1413,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:42877\n", + " Nanny: tcp://127.0.0.1:36305\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-8pasuemn\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-2vc82qu4\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1486,7 +1487,7 @@ "
\n", - " Comm: tcp://127.0.0.1:34095\n", + " Comm: tcp://127.0.0.1:35155\n", " \n", " Total threads: 1\n", @@ -1449,7 +1450,7 @@ "
\n", - " Dashboard: /proxy/44331/status\n", + " Dashboard: /proxy/43237/status\n", " \n", " Memory: 0 B\n", @@ -1457,13 +1458,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:40919\n", + " Nanny: tcp://127.0.0.1:32901\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-p7rdwugq\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-hkgdw9y9\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1531,7 +1532,7 @@ "
\n", - " Comm: tcp://127.0.0.1:41287\n", + " Comm: tcp://127.0.0.1:34867\n", " \n", " Total threads: 1\n", @@ -1494,7 +1495,7 @@ "
\n", - " Dashboard: /proxy/44461/status\n", + " Dashboard: /proxy/35095/status\n", " \n", " Memory: 0 B\n", @@ -1502,13 +1503,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:40835\n", + " Nanny: tcp://127.0.0.1:46721\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-mquzw4pc\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-8ux3c6kk\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1576,7 +1577,7 @@ "
\n", - " Comm: tcp://127.0.0.1:33963\n", + " Comm: tcp://127.0.0.1:35947\n", " \n", " Total threads: 1\n", @@ -1539,7 +1540,7 @@ "
\n", - " Dashboard: /proxy/38061/status\n", + " Dashboard: /proxy/46305/status\n", " \n", " Memory: 0 B\n", @@ -1547,13 +1548,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:42291\n", + " Nanny: tcp://127.0.0.1:46547\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-8x6scvui\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-07etaj27\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1621,7 +1622,7 @@ "
\n", - " Comm: tcp://127.0.0.1:38741\n", + " Comm: tcp://127.0.0.1:42651\n", " \n", " Total threads: 1\n", @@ -1584,7 +1585,7 @@ "
\n", - " Dashboard: /proxy/43031/status\n", + " Dashboard: /proxy/45251/status\n", " \n", " Memory: 0 B\n", @@ -1592,13 +1593,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:45537\n", + " Nanny: tcp://127.0.0.1:42409\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-qgl1yqa4\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-hvu4d16y\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1666,7 +1667,7 @@ "
\n", - " Comm: tcp://127.0.0.1:34023\n", + " Comm: tcp://127.0.0.1:33015\n", " \n", " Total threads: 1\n", @@ -1629,7 +1630,7 @@ "
\n", - " Dashboard: /proxy/38391/status\n", + " Dashboard: /proxy/37769/status\n", " \n", " Memory: 0 B\n", @@ -1637,13 +1638,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:41055\n", + " Nanny: tcp://127.0.0.1:46435\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-oppnp1h9\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-euwaaplp\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1711,7 +1712,7 @@ "
\n", - " Comm: tcp://127.0.0.1:41495\n", + " Comm: tcp://127.0.0.1:46581\n", " \n", " Total threads: 1\n", @@ -1674,7 +1675,7 @@ "
\n", - " Dashboard: /proxy/45403/status\n", + " Dashboard: /proxy/46669/status\n", " \n", " Memory: 0 B\n", @@ -1682,13 +1683,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:36083\n", + " Nanny: tcp://127.0.0.1:34623\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-u5nk0i6v\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-fd5x6q8b\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1756,7 +1757,7 @@ "
\n", - " Comm: tcp://127.0.0.1:38491\n", + " Comm: tcp://127.0.0.1:34861\n", " \n", " Total threads: 1\n", @@ -1719,7 +1720,7 @@ "
\n", - " Dashboard: /proxy/41895/status\n", + " Dashboard: /proxy/44459/status\n", " \n", " Memory: 0 B\n", @@ -1727,13 +1728,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:43913\n", + " Nanny: tcp://127.0.0.1:38641\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-k_u74xdn\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-gl37dal0\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1801,7 +1802,7 @@ "
\n", - " Comm: tcp://127.0.0.1:37289\n", + " Comm: tcp://127.0.0.1:43107\n", " \n", " Total threads: 1\n", @@ -1764,7 +1765,7 @@ "
\n", - " Dashboard: /proxy/45073/status\n", + " Dashboard: /proxy/36175/status\n", " \n", " Memory: 0 B\n", @@ -1772,13 +1773,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:38297\n", + " Nanny: tcp://127.0.0.1:46843\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-cza1drap\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-8waprgwb\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1846,7 +1847,7 @@ "
\n", - " Comm: tcp://127.0.0.1:38181\n", + " Comm: tcp://127.0.0.1:42559\n", " \n", " Total threads: 1\n", @@ -1809,7 +1810,7 @@ "
\n", - " Dashboard: /proxy/43175/status\n", + " Dashboard: /proxy/37495/status\n", " \n", " Memory: 0 B\n", @@ -1817,13 +1818,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:33995\n", + " Nanny: tcp://127.0.0.1:33841\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-_2y8cpin\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-ci4arahq\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1891,7 +1892,7 @@ "
\n", - " Comm: tcp://127.0.0.1:37841\n", + " Comm: tcp://127.0.0.1:44337\n", " \n", " Total threads: 1\n", @@ -1854,7 +1855,7 @@ "
\n", - " Dashboard: /proxy/38615/status\n", + " Dashboard: /proxy/37197/status\n", " \n", " Memory: 0 B\n", @@ -1862,13 +1863,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:36617\n", + " Nanny: tcp://127.0.0.1:44949\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-ck_dn52_\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-oaqn_sqn\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1936,7 +1937,7 @@ "
\n", - " Comm: tcp://127.0.0.1:37175\n", + " Comm: tcp://127.0.0.1:44023\n", " \n", " Total threads: 1\n", @@ -1899,7 +1900,7 @@ "
\n", - " Dashboard: /proxy/45069/status\n", + " Dashboard: /proxy/42029/status\n", " \n", " Memory: 0 B\n", @@ -1907,13 +1908,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:46225\n", + " Nanny: tcp://127.0.0.1:38731\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-l2l7emzc\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-_lej3rzu\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -1981,7 +1982,7 @@ "
\n", - " Comm: tcp://127.0.0.1:32801\n", + " Comm: tcp://127.0.0.1:41611\n", " \n", " Total threads: 1\n", @@ -1944,7 +1945,7 @@ "
\n", - " Dashboard: /proxy/38841/status\n", + " Dashboard: /proxy/43283/status\n", " \n", " Memory: 0 B\n", @@ -1952,13 +1953,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:38869\n", + " Nanny: tcp://127.0.0.1:35387\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-xufmaoop\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-kqqf83i6\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2026,7 +2027,7 @@ "
\n", - " Comm: tcp://127.0.0.1:34295\n", + " Comm: tcp://127.0.0.1:45835\n", " \n", " Total threads: 1\n", @@ -1989,7 +1990,7 @@ "
\n", - " Dashboard: /proxy/36097/status\n", + " Dashboard: /proxy/32959/status\n", " \n", " Memory: 0 B\n", @@ -1997,13 +1998,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:45359\n", + " Nanny: tcp://127.0.0.1:34925\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-75q7srmw\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-xx2cisgd\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2071,7 +2072,7 @@ "
\n", - " Comm: tcp://127.0.0.1:42393\n", + " Comm: tcp://127.0.0.1:41785\n", " \n", " Total threads: 1\n", @@ -2034,7 +2035,7 @@ "
\n", - " Dashboard: /proxy/37311/status\n", + " Dashboard: /proxy/44317/status\n", " \n", " Memory: 0 B\n", @@ -2042,13 +2043,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:36507\n", + " Nanny: tcp://127.0.0.1:40949\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-c78thjkw\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-sy8iipu1\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2116,7 +2117,7 @@ "
\n", - " Comm: tcp://127.0.0.1:39679\n", + " Comm: tcp://127.0.0.1:34363\n", " \n", " Total threads: 1\n", @@ -2079,7 +2080,7 @@ "
\n", - " Dashboard: /proxy/39787/status\n", + " Dashboard: /proxy/45161/status\n", " \n", " Memory: 0 B\n", @@ -2087,13 +2088,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:38385\n", + " Nanny: tcp://127.0.0.1:39795\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-hr4wredq\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-3dkpfhsc\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2161,7 +2162,7 @@ "
\n", - " Comm: tcp://127.0.0.1:43847\n", + " Comm: tcp://127.0.0.1:46215\n", " \n", " Total threads: 1\n", @@ -2124,7 +2125,7 @@ "
\n", - " Dashboard: /proxy/36153/status\n", + " Dashboard: /proxy/40665/status\n", " \n", " Memory: 0 B\n", @@ -2132,13 +2133,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:37713\n", + " Nanny: tcp://127.0.0.1:43837\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-25clcjhx\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-0wcv4hfc\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2206,7 +2207,7 @@ "
\n", - " Comm: tcp://127.0.0.1:45295\n", + " Comm: tcp://127.0.0.1:41671\n", " \n", " Total threads: 1\n", @@ -2169,7 +2170,7 @@ "
\n", - " Dashboard: /proxy/38853/status\n", + " Dashboard: /proxy/42979/status\n", " \n", " Memory: 0 B\n", @@ -2177,13 +2178,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:44225\n", + " Nanny: tcp://127.0.0.1:35759\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-33k_1z6x\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-x_o60uqr\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2251,7 +2252,7 @@ "
\n", - " Comm: tcp://127.0.0.1:46191\n", + " Comm: tcp://127.0.0.1:34885\n", " \n", " Total threads: 1\n", @@ -2214,7 +2215,7 @@ "
\n", - " Dashboard: /proxy/36859/status\n", + " Dashboard: /proxy/38773/status\n", " \n", " Memory: 0 B\n", @@ -2222,13 +2223,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:43475\n", + " Nanny: tcp://127.0.0.1:42795\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-gd0tuixy\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-mc87qnke\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2296,7 +2297,7 @@ "
\n", - " Comm: tcp://127.0.0.1:44223\n", + " Comm: tcp://127.0.0.1:44357\n", " \n", " Total threads: 1\n", @@ -2259,7 +2260,7 @@ "
\n", - " Dashboard: /proxy/35053/status\n", + " Dashboard: /proxy/36337/status\n", " \n", " Memory: 0 B\n", @@ -2267,13 +2268,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:38039\n", + " Nanny: tcp://127.0.0.1:44301\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-exb9jp4z\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-gd2dowuz\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", @@ -2345,7 +2346,7 @@ "" ], "text/plain": [ - "" + "" ] }, "execution_count": 2, @@ -2761,11 +2762,11 @@ " intake_esm_attrs:filename: ocean_month.nc\n", " intake_esm_attrs:file_id: ocean_month\n", " intake_esm_attrs:_data_format_: netcdf\n", - " intake_esm_dataset_key: ocean_month.1mon
\n", - " Comm: tcp://127.0.0.1:32967\n", + " Comm: tcp://127.0.0.1:45973\n", " \n", " Total threads: 1\n", @@ -2304,7 +2305,7 @@ "
\n", - " Dashboard: /proxy/36879/status\n", + " Dashboard: /proxy/36235/status\n", " \n", " Memory: 0 B\n", @@ -2312,13 +2313,13 @@ "
\n", - " Nanny: tcp://127.0.0.1:40347\n", + " Nanny: tcp://127.0.0.1:46107\n", "
\n", - " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-c59faq4c\n", + " Local directory: /jobfs/126166311.gadi-pbs/dask-scratch-space/worker-9vhw_awp\n", "
\n", + " dtype='datetime64[ns]')
    • sst
      (time, yt_ocean, xt_ocean)
      float32
      dask.array<chunksize=(1, 216, 240), meta=np.ndarray>
      long_name :
      Potential temperature
      units :
      K
      valid_range :
      [-10. 500.]
      cell_methods :
      time: mean
      time_avg_info :
      average_T1,average_T2,average_DT
      standard_name :
      sea_surface_temperature
    • \n", " \n", "
    \n", " \n", @@ -2897,12 +2898,12 @@ "\n", " \n", " \n", - "
    • xt_ocean
      PandasIndex
      PandasIndex(Index([-279.875, -279.625, -279.375, -279.125, -278.875, -278.625, -278.375,\n",
+       "
    • xt_ocean
      PandasIndex
      PandasIndex(Index([-279.875, -279.625, -279.375, -279.125, -278.875, -278.625, -278.375,\n",
        "       -278.125, -277.875, -277.625,\n",
        "       ...\n",
        "         77.625,   77.875,   78.125,   78.375,   78.625,   78.875,   79.125,\n",
        "         79.375,   79.625,   79.875],\n",
-       "      dtype='float64', name='xt_ocean', length=1440))
    • yt_ocean
      PandasIndex
      PandasIndex(Index([ -81.0770008338366,  -80.9714022446317,  -80.8658036554268,\n",
+       "      dtype='float64', name='xt_ocean', length=1440))
    • yt_ocean
      PandasIndex
      PandasIndex(Index([ -81.0770008338366,  -80.9714022446317,  -80.8658036554268,\n",
        "        -80.7602050662219,   -80.654606477017,  -80.5490078878121,\n",
        "        -80.4434092986072, -80.33781070940229, -80.23221212019739,\n",
        "       -80.12661353099249,\n",
@@ -2911,7 +2912,7 @@
        "        89.31369079182024,  89.41928938102512,  89.52488797023008,\n",
        "          89.630486559435,  89.73608514863992,  89.84168373784476,\n",
        "        89.94728232704986],\n",
-       "      dtype='float64', name='yt_ocean', length=1080))
    • time
      PandasIndex
      PandasIndex(DatetimeIndex(['1958-01-14 12:00:00', '1958-02-13 00:00:00',\n",
+       "      dtype='float64', name='yt_ocean', length=1080))
    • time
      PandasIndex
      PandasIndex(DatetimeIndex(['1958-01-14 12:00:00', '1958-02-13 00:00:00',\n",
        "               '1958-03-14 12:00:00', '1958-04-14 00:00:00',\n",
        "               '1958-05-14 12:00:00', '1958-06-14 00:00:00',\n",
        "               '1958-07-14 12:00:00', '1958-08-14 12:00:00',\n",
@@ -2922,7 +2923,7 @@
        "               '2018-07-14 12:00:00', '2018-08-14 12:00:00',\n",
        "               '2018-09-14 00:00:00', '2018-10-14 12:00:00',\n",
        "               '2018-11-14 00:00:00', '2018-12-14 12:00:00'],\n",
-       "              dtype='datetime64[ns]', name='time', length=732, freq=None))
  • filename :
    ocean_month.nc
    title :
    ACCESS-OM2
    grid_type :
    mosaic
    grid_tile :
    1
    intake_esm_vars :
    ['sst']
    intake_esm_attrs:realm :
    ocean
    intake_esm_attrs:variable :
    pbot_t,patm_t,rho_dzt,dht,sea_level,sea_level_sq,pot_temp,temp,sst,sst_sq,bottom_temp,salt,sss,sss_sq,bottom_salt,age_global,mld,mld_max,mld_min,mld_sq,psiu,psiv,bv_freq,buoyfreq2_wt,hblt_max,pot_rho_0,pot_rho_2,rho,eta_t,u,v,wt,tx_trans,ty_trans,tz_trans,tx_trans_gm,ty_trans_gm,tx_trans_submeso,ty_trans_submeso,tx_trans_rho,ty_trans_rho,tx_trans_rho_gm,ty_trans_rho_gm,tx_trans_nrho_submeso,ty_trans_nrho_submeso,tx_trans_int_z,ty_trans_int_z,temp_xflux_adv_int_z,temp_yflux_adv_int_z,temp_yflux_gm_int_z,temp_xflux_gm_int_z,temp_xflux_ndiffuse_int_z,temp_yflux_ndiffuse_int_z,temp_yflux_submeso_int_z,temp_xflux_submeso_int_z,lprec,fprec,evap,runoff,melt,pme_river,wfimelt,wfiform,pme_net,sfc_salt_flux_ice,sfc_salt_flux_runoff,sfc_salt_flux_restore,sfc_salt_flux_coupler,sfc_hflux_from_water_prec,sfc_hflux_from_water_evap,sfc_hflux_from_runoff,fprec_melt_heat,frazil_3d_int_z,lw_heat,evap_heat,sens_heat,swflx,sw_heat,mh_flux,liceht,net_sfc_heating,temp_rivermix,sfc_hflux_coupler,sfc_hflux_pme,tau_x,tau_y,bmf_u,bmf_v,vert_pv,usq,vsq,bih_fric_u,bih_fric_v,u_dot_grad_vert_pv,ekman_we,eta_nonbouss,surface_pot_temp_max,surface_pot_temp_min,average_T1,average_T2,average_DT,time_bounds
    intake_esm_attrs:frequency :
    1mon
    intake_esm_attrs:variable_long_name :
    bottom pressure on T cells [Boussinesq (volume conserving) model],applied pressure on T cells,t-cell rho*thickness,t-cell thickness,effective sea level (eta_t + patm/(rho0*g)) on T cells,square of effective sea level (eta_t + patm/(rho0*g)) on T cells,Potential temperature,Conservative temperature,Potential temperature,squared Potential temperature,Conservative temperature,Practical Salinity,Practical Salinity,squared Practical Salinity,Practical Salinity,Age (global),mixed layer depth determined by density criteria,mixed layer depth determined by density criteria,mixed layer depth determined by density criteria,squared mixed layer depth determined by density criteria,quasi-barotropic strmfcn psiu (compatible with tx_trans),quasi-barotropic strmfcn psiv (compatible with ty_trans),buoy freq at T-cell centre for use in neutral physics,Squared buoyancy frequency at T-cell bottom,T-cell boundary layer depth from KPP,potential density referenced to 0 dbar,potential density referenced to 2000 dbar,in situ density,surface height on T cells [Boussinesq (volume conserving) model],i-current,j-current,dia-surface velocity T-points,T-cell i-mass transport,T-cell j-mass transport,T-cell k-mass transport,T-cell mass i-transport from GM,T-cell mass j-transport from GM,T-cell mass i-transport from submesoscale param,T-cell mass j-transport from submesoscale param,T-cell i-mass transport on pot_rho,T-cell j-mass transport on pot_rho,T-cell i-mass transport from GM on pot_rho,T-cell j-mass transport from GM on pot_rho,T-cell i-mass transport from submesoscale param on neutral rho,T-cell j-mass transport from submesoscale param on neutral rho,T-cell i-mass transport vertically summed,T-cell j-mass transport vertically summed,z-integral of cp*rho*dyt*u*temp,z-integral of cp*rho*dxt*v*temp,z-integral cp*gm_yflux*dyt*rho_dzt*temp,z-integral cp*gm_xflux*dyt*rho_dzt*temp,z-integral cp*ndiffuse_xflux*dyt*rho_dzt*temp,z-integral cp*ndiffuse_yflux*dxt*rho_dzt*temp,z-integral cp*submeso_yflux*dxt*rho_dzt*temp,z-integral cp*submeso_xflux*dyt*rho_dzt*temp,liquid precip (including ice melt/form) into ocean (>0 enters ocean),snow falling onto ocean (>0 enters ocean),mass flux from evaporation/condensation (>0 enters ocean),mass flux of liquid river runoff entering ocean,water flux transferred with sea ice form/melt (>0 enters ocean),mass flux of precip-evap+river via sbc (liquid, frozen, evaporation),water into ocean due to ice melt (>0 enters ocean),water out of ocean due to ice form (>0 enters ocean),precip-evap into ocean (total w/ restore + normalize),sfc_salt_flux_ice,sfc_salt_flux_runoff,sfc_salt_flux_restore: flux from restoring term,sfc_salt_flux_coupler: flux from the coupler,heat flux from precip transfer of water across ocean surface,heat flux from evap transfer of water across ocean surface,heat flux (relative to 0C) from liquid river runoff,heat flux to melt frozen precip (<0 cools ocean),Vertical sum of ocn frazil heat flux over time step,longwave flux into ocean (<0 cools ocean),latent heat flux into ocean (<0 cools ocean),sensible heat into ocean (<0 cools ocean),shortwave flux into ocean (>0 heats ocean),penetrative shortwave heating,heat into ocean due to melting ice (>0 heats ocean),heat into ocean due to land ice discharge-melt (>0 heats ocean),surface ocean heat flux coming through coupler and mass transfer,cp*rivermix*rho_dzt*temp,surface heat flux coming through coupler,heat flux (relative to 0C) from pme transfer of water across ocean surface,i-directed wind stress forcing u-velocity,j-directed wind stress forcing v-velocity,Bottom u-stress via bottom drag,Bottom v-stress via bottom drag,vertical piece of Ertel PV: (f+zeta)*N^2,i-current,j-current,Thickness and rho wghtd horz bih frict on u-zonal,Thickness and rho wghtd horz bih frict on v-merid,3d velocity dot product with 3d gradient of vertical piece of Ertel PV: u.grad((f+zeta)*N^2),Ekman vertical velocity averaged to wt-point,surface height including steric contribution,Potential temperature,Potential temperature,Start time for average period,End time for average period,Length of average period,time axis boundaries
    intake_esm_attrs:variable_standard_name :
    sea_water_pressure_at_sea_floor,sea_water_pressure_at_sea_water_surface,sea_water_mass_per_unit_area,cell_thickness,sea_surface_height_above_geoid,square_of_sea_surface_height_above_geoid,sea_water_potential_temperature,sea_water_conservative_temperature,sea_surface_temperature,square_of_sea_surface_temperature,,sea_water_salinity,sea_surface_salinity,square_of_sea_surface_salinity,,sea_water_age_since_surface_contact,ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_mixed_layer_thickness_defined_by_sigma_t,square_of_ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_barotropic_mass_streamfunction,,,,ocean_mixed_layer_thickness_defined_by_mixing_scheme,sea_water_potential_density,,,,sea_water_x_velocity,sea_water_y_velocity,,ocean_mass_x_transport,ocean_mass_y_transport,upward_ocean_mass_transport,,,,,,,,,,,,,,,,,,,,,rainfall_flux,snowfall_flux,water_evaporation_flux,water_flux_into_sea_water_from_rivers,water_flux_into_sea_water_due_to_sea_ice_thermodynamics,water_flux_into_sea_water,icemelt_flux,iceform_flux,,downward_sea_ice_basal_salt_flux,salt_flux_into_sea_water_from_rivers,,,temperature_flux_due_to_rainfall_expressed_as_heat_flux_into_sea_water,temperature_flux_due_to_evaporation_expressed_as_heat_flux_into_sea_water,temperature_flux_due_to_runoff_expressed_as_heat_flux_into_sea_water,heat_flux_into_sea_water_due_to_snow_thermodynamics,,surface_net_downward_longwave_flux,surface_downward_latent_heat_flux,surface_downward_sensible_heat_flux,surface_net_downward_shortwave_flux,downwelling_shortwave_flux_in_sea_water,mh_flux,liceht_flux,,,,,surface_downward_x_stress,surface_downward_y_stress,,,,sea_water_x_velocity,sea_water_y_velocity,,,,,,sea_surface_temperature,sea_surface_temperature,,,,
    intake_esm_attrs:variable_cell_methods :
    time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: min,time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean_pow(02),time: mean_pow(02),time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: min,,,,
    intake_esm_attrs:variable_units :
    dbar,Pa,(kg/m^3)*m,m,meter,m^2,K,K,K,squared K,deg_C,psu,psu,squared psu,psu,yr,m,m,m,m^2,kg/s,kg/s,1/s,1/s^2,m,kg/m^3,kg/m^3,kg/m^3,meter,m/sec,m/sec,m/sec,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,Watts,Watts,Watt,Watt,Watt,Watt,Watt,Watt,(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),kg/(m^2*sec),kg/(m^2*sec),kg/(m^2*sec),kg/(m^2*sec),Watts/m^2,Watts/m^2,Watts/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,(W/m^2),(W/m^2),Watts/m^2,Watt/m^2,Watts/m^2,Watts/m^2,N/m^2,N/m^2,N/m^2,N/m^2,1/sec^3,m/sec,m/sec,(kg/m^3)*(m^2/s^2),(kg/m^3)*(m^2/s^2),1/sec^4,m/s,meter,K,K,days since 0001-01-01 00:00:00,days since 0001-01-01 00:00:00,days,days
    intake_esm_attrs:filename :
    ocean_month.nc
    intake_esm_attrs:file_id :
    ocean_month
    intake_esm_attrs:_data_format_ :
    netcdf
    intake_esm_dataset_key :
    ocean_month.1mon
    • " + " dtype='datetime64[ns]', name='time', length=732, freq=None))
  • filename :
    ocean_month.nc
    title :
    ACCESS-OM2
    grid_type :
    mosaic
    grid_tile :
    1
    intake_esm_vars :
    ['sst']
    intake_esm_attrs:realm :
    ocean
    intake_esm_attrs:variable :
    pbot_t,patm_t,rho_dzt,dht,sea_level,sea_level_sq,pot_temp,temp,sst,sst_sq,bottom_temp,salt,sss,sss_sq,bottom_salt,age_global,mld,mld_max,mld_min,mld_sq,psiu,psiv,bv_freq,buoyfreq2_wt,hblt_max,pot_rho_0,pot_rho_2,rho,eta_t,u,v,wt,tx_trans,ty_trans,tz_trans,tx_trans_gm,ty_trans_gm,tx_trans_submeso,ty_trans_submeso,tx_trans_rho,ty_trans_rho,tx_trans_rho_gm,ty_trans_rho_gm,tx_trans_nrho_submeso,ty_trans_nrho_submeso,tx_trans_int_z,ty_trans_int_z,temp_xflux_adv_int_z,temp_yflux_adv_int_z,temp_yflux_gm_int_z,temp_xflux_gm_int_z,temp_xflux_ndiffuse_int_z,temp_yflux_ndiffuse_int_z,temp_yflux_submeso_int_z,temp_xflux_submeso_int_z,lprec,fprec,evap,runoff,melt,pme_river,wfimelt,wfiform,pme_net,sfc_salt_flux_ice,sfc_salt_flux_runoff,sfc_salt_flux_restore,sfc_salt_flux_coupler,sfc_hflux_from_water_prec,sfc_hflux_from_water_evap,sfc_hflux_from_runoff,fprec_melt_heat,frazil_3d_int_z,lw_heat,evap_heat,sens_heat,swflx,sw_heat,mh_flux,liceht,net_sfc_heating,temp_rivermix,sfc_hflux_coupler,sfc_hflux_pme,tau_x,tau_y,bmf_u,bmf_v,vert_pv,usq,vsq,bih_fric_u,bih_fric_v,u_dot_grad_vert_pv,ekman_we,eta_nonbouss,surface_pot_temp_max,surface_pot_temp_min,average_T1,average_T2,average_DT,time_bounds
    intake_esm_attrs:frequency :
    1mon
    intake_esm_attrs:variable_long_name :
    bottom pressure on T cells [Boussinesq (volume conserving) model],applied pressure on T cells,t-cell rho*thickness,t-cell thickness,effective sea level (eta_t + patm/(rho0*g)) on T cells,square of effective sea level (eta_t + patm/(rho0*g)) on T cells,Potential temperature,Conservative temperature,Potential temperature,squared Potential temperature,Conservative temperature,Practical Salinity,Practical Salinity,squared Practical Salinity,Practical Salinity,Age (global),mixed layer depth determined by density criteria,mixed layer depth determined by density criteria,mixed layer depth determined by density criteria,squared mixed layer depth determined by density criteria,quasi-barotropic strmfcn psiu (compatible with tx_trans),quasi-barotropic strmfcn psiv (compatible with ty_trans),buoy freq at T-cell centre for use in neutral physics,Squared buoyancy frequency at T-cell bottom,T-cell boundary layer depth from KPP,potential density referenced to 0 dbar,potential density referenced to 2000 dbar,in situ density,surface height on T cells [Boussinesq (volume conserving) model],i-current,j-current,dia-surface velocity T-points,T-cell i-mass transport,T-cell j-mass transport,T-cell k-mass transport,T-cell mass i-transport from GM,T-cell mass j-transport from GM,T-cell mass i-transport from submesoscale param,T-cell mass j-transport from submesoscale param,T-cell i-mass transport on pot_rho,T-cell j-mass transport on pot_rho,T-cell i-mass transport from GM on pot_rho,T-cell j-mass transport from GM on pot_rho,T-cell i-mass transport from submesoscale param on neutral rho,T-cell j-mass transport from submesoscale param on neutral rho,T-cell i-mass transport vertically summed,T-cell j-mass transport vertically summed,z-integral of cp*rho*dyt*u*temp,z-integral of cp*rho*dxt*v*temp,z-integral cp*gm_yflux*dyt*rho_dzt*temp,z-integral cp*gm_xflux*dyt*rho_dzt*temp,z-integral cp*ndiffuse_xflux*dyt*rho_dzt*temp,z-integral cp*ndiffuse_yflux*dxt*rho_dzt*temp,z-integral cp*submeso_yflux*dxt*rho_dzt*temp,z-integral cp*submeso_xflux*dyt*rho_dzt*temp,liquid precip (including ice melt/form) into ocean (>0 enters ocean),snow falling onto ocean (>0 enters ocean),mass flux from evaporation/condensation (>0 enters ocean),mass flux of liquid river runoff entering ocean,water flux transferred with sea ice form/melt (>0 enters ocean),mass flux of precip-evap+river via sbc (liquid, frozen, evaporation),water into ocean due to ice melt (>0 enters ocean),water out of ocean due to ice form (>0 enters ocean),precip-evap into ocean (total w/ restore + normalize),sfc_salt_flux_ice,sfc_salt_flux_runoff,sfc_salt_flux_restore: flux from restoring term,sfc_salt_flux_coupler: flux from the coupler,heat flux from precip transfer of water across ocean surface,heat flux from evap transfer of water across ocean surface,heat flux (relative to 0C) from liquid river runoff,heat flux to melt frozen precip (<0 cools ocean),Vertical sum of ocn frazil heat flux over time step,longwave flux into ocean (<0 cools ocean),latent heat flux into ocean (<0 cools ocean),sensible heat into ocean (<0 cools ocean),shortwave flux into ocean (>0 heats ocean),penetrative shortwave heating,heat into ocean due to melting ice (>0 heats ocean),heat into ocean due to land ice discharge-melt (>0 heats ocean),surface ocean heat flux coming through coupler and mass transfer,cp*rivermix*rho_dzt*temp,surface heat flux coming through coupler,heat flux (relative to 0C) from pme transfer of water across ocean surface,i-directed wind stress forcing u-velocity,j-directed wind stress forcing v-velocity,Bottom u-stress via bottom drag,Bottom v-stress via bottom drag,vertical piece of Ertel PV: (f+zeta)*N^2,i-current,j-current,Thickness and rho wghtd horz bih frict on u-zonal,Thickness and rho wghtd horz bih frict on v-merid,3d velocity dot product with 3d gradient of vertical piece of Ertel PV: u.grad((f+zeta)*N^2),Ekman vertical velocity averaged to wt-point,surface height including steric contribution,Potential temperature,Potential temperature,Start time for average period,End time for average period,Length of average period,time axis boundaries
    intake_esm_attrs:variable_standard_name :
    sea_water_pressure_at_sea_floor,sea_water_pressure_at_sea_water_surface,sea_water_mass_per_unit_area,cell_thickness,sea_surface_height_above_geoid,square_of_sea_surface_height_above_geoid,sea_water_potential_temperature,sea_water_conservative_temperature,sea_surface_temperature,square_of_sea_surface_temperature,,sea_water_salinity,sea_surface_salinity,square_of_sea_surface_salinity,,sea_water_age_since_surface_contact,ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_mixed_layer_thickness_defined_by_sigma_t,square_of_ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_barotropic_mass_streamfunction,,,,ocean_mixed_layer_thickness_defined_by_mixing_scheme,sea_water_potential_density,,,,sea_water_x_velocity,sea_water_y_velocity,,ocean_mass_x_transport,ocean_mass_y_transport,upward_ocean_mass_transport,,,,,,,,,,,,,,,,,,,,,rainfall_flux,snowfall_flux,water_evaporation_flux,water_flux_into_sea_water_from_rivers,water_flux_into_sea_water_due_to_sea_ice_thermodynamics,water_flux_into_sea_water,icemelt_flux,iceform_flux,,downward_sea_ice_basal_salt_flux,salt_flux_into_sea_water_from_rivers,,,temperature_flux_due_to_rainfall_expressed_as_heat_flux_into_sea_water,temperature_flux_due_to_evaporation_expressed_as_heat_flux_into_sea_water,temperature_flux_due_to_runoff_expressed_as_heat_flux_into_sea_water,heat_flux_into_sea_water_due_to_snow_thermodynamics,,surface_net_downward_longwave_flux,surface_downward_latent_heat_flux,surface_downward_sensible_heat_flux,surface_net_downward_shortwave_flux,downwelling_shortwave_flux_in_sea_water,mh_flux,liceht_flux,,,,,surface_downward_x_stress,surface_downward_y_stress,,,,sea_water_x_velocity,sea_water_y_velocity,,,,,,sea_surface_temperature,sea_surface_temperature,,,,
    intake_esm_attrs:variable_cell_methods :
    time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: min,time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean_pow(02),time: mean_pow(02),time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: min,,,,
    intake_esm_attrs:variable_units :
    dbar,Pa,(kg/m^3)*m,m,meter,m^2,K,K,K,squared K,deg_C,psu,psu,squared psu,psu,yr,m,m,m,m^2,kg/s,kg/s,1/s,1/s^2,m,kg/m^3,kg/m^3,kg/m^3,meter,m/sec,m/sec,m/sec,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,Watts,Watts,Watt,Watt,Watt,Watt,Watt,Watt,(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),kg/(m^2*sec),kg/(m^2*sec),kg/(m^2*sec),kg/(m^2*sec),Watts/m^2,Watts/m^2,Watts/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,(W/m^2),(W/m^2),Watts/m^2,Watt/m^2,Watts/m^2,Watts/m^2,N/m^2,N/m^2,N/m^2,N/m^2,1/sec^3,m/sec,m/sec,(kg/m^3)*(m^2/s^2),(kg/m^3)*(m^2/s^2),1/sec^4,m/s,meter,K,K,days since 0001-01-01 00:00:00,days since 0001-01-01 00:00:00,days,days
    intake_esm_attrs:filename :
    ocean_month.nc
    intake_esm_attrs:file_id :
    ocean_month
    intake_esm_attrs:_data_format_ :
    netcdf
    intake_esm_dataset_key :
    ocean_month.1mon
    • " ], "text/plain": [ " Size: 5GB\n", @@ -2956,7 +2957,7 @@ ], "source": [ "experiment = '025deg_jra55_iaf_omip2_cycle6'\n", - "sst = cat[experiment].search(frequency=\"1mon\", variable=\"sst\").to_dask()\n", + "sst = catalog[experiment].search(frequency=\"1mon\", variable=\"sst\").to_dask()\n", "sst" ] }, @@ -2965,7 +2966,7 @@ "id": "2a578cd9-ae55-4d7b-8477-c2d463a7973a", "metadata": {}, "source": [ - "Rechunk so that there is only one chunk in time dimension, used by the linear regression." + "Rechunk so that there is only one chunk in the time dimension that will be used the linear regression." ] }, { @@ -3362,11 +3363,11 @@ " intake_esm_attrs:filename: ocean_month.nc\n", " intake_esm_attrs:file_id: ocean_month\n", " intake_esm_attrs:_data_format_: netcdf\n", - " intake_esm_dataset_key: ocean_month.1mon
  • filename :
    ocean_month.nc
    title :
    ACCESS-OM2
    grid_type :
    mosaic
    grid_tile :
    1
    intake_esm_vars :
    ['sst']
    intake_esm_attrs:realm :
    ocean
    intake_esm_attrs:variable :
    pbot_t,patm_t,rho_dzt,dht,sea_level,sea_level_sq,pot_temp,temp,sst,sst_sq,bottom_temp,salt,sss,sss_sq,bottom_salt,age_global,mld,mld_max,mld_min,mld_sq,psiu,psiv,bv_freq,buoyfreq2_wt,hblt_max,pot_rho_0,pot_rho_2,rho,eta_t,u,v,wt,tx_trans,ty_trans,tz_trans,tx_trans_gm,ty_trans_gm,tx_trans_submeso,ty_trans_submeso,tx_trans_rho,ty_trans_rho,tx_trans_rho_gm,ty_trans_rho_gm,tx_trans_nrho_submeso,ty_trans_nrho_submeso,tx_trans_int_z,ty_trans_int_z,temp_xflux_adv_int_z,temp_yflux_adv_int_z,temp_yflux_gm_int_z,temp_xflux_gm_int_z,temp_xflux_ndiffuse_int_z,temp_yflux_ndiffuse_int_z,temp_yflux_submeso_int_z,temp_xflux_submeso_int_z,lprec,fprec,evap,runoff,melt,pme_river,wfimelt,wfiform,pme_net,sfc_salt_flux_ice,sfc_salt_flux_runoff,sfc_salt_flux_restore,sfc_salt_flux_coupler,sfc_hflux_from_water_prec,sfc_hflux_from_water_evap,sfc_hflux_from_runoff,fprec_melt_heat,frazil_3d_int_z,lw_heat,evap_heat,sens_heat,swflx,sw_heat,mh_flux,liceht,net_sfc_heating,temp_rivermix,sfc_hflux_coupler,sfc_hflux_pme,tau_x,tau_y,bmf_u,bmf_v,vert_pv,usq,vsq,bih_fric_u,bih_fric_v,u_dot_grad_vert_pv,ekman_we,eta_nonbouss,surface_pot_temp_max,surface_pot_temp_min,average_T1,average_T2,average_DT,time_bounds
    intake_esm_attrs:frequency :
    1mon
    intake_esm_attrs:variable_long_name :
    bottom pressure on T cells [Boussinesq (volume conserving) model],applied pressure on T cells,t-cell rho*thickness,t-cell thickness,effective sea level (eta_t + patm/(rho0*g)) on T cells,square of effective sea level (eta_t + patm/(rho0*g)) on T cells,Potential temperature,Conservative temperature,Potential temperature,squared Potential temperature,Conservative temperature,Practical Salinity,Practical Salinity,squared Practical Salinity,Practical Salinity,Age (global),mixed layer depth determined by density criteria,mixed layer depth determined by density criteria,mixed layer depth determined by density criteria,squared mixed layer depth determined by density criteria,quasi-barotropic strmfcn psiu (compatible with tx_trans),quasi-barotropic strmfcn psiv (compatible with ty_trans),buoy freq at T-cell centre for use in neutral physics,Squared buoyancy frequency at T-cell bottom,T-cell boundary layer depth from KPP,potential density referenced to 0 dbar,potential density referenced to 2000 dbar,in situ density,surface height on T cells [Boussinesq (volume conserving) model],i-current,j-current,dia-surface velocity T-points,T-cell i-mass transport,T-cell j-mass transport,T-cell k-mass transport,T-cell mass i-transport from GM,T-cell mass j-transport from GM,T-cell mass i-transport from submesoscale param,T-cell mass j-transport from submesoscale param,T-cell i-mass transport on pot_rho,T-cell j-mass transport on pot_rho,T-cell i-mass transport from GM on pot_rho,T-cell j-mass transport from GM on pot_rho,T-cell i-mass transport from submesoscale param on neutral rho,T-cell j-mass transport from submesoscale param on neutral rho,T-cell i-mass transport vertically summed,T-cell j-mass transport vertically summed,z-integral of cp*rho*dyt*u*temp,z-integral of cp*rho*dxt*v*temp,z-integral cp*gm_yflux*dyt*rho_dzt*temp,z-integral cp*gm_xflux*dyt*rho_dzt*temp,z-integral cp*ndiffuse_xflux*dyt*rho_dzt*temp,z-integral cp*ndiffuse_yflux*dxt*rho_dzt*temp,z-integral cp*submeso_yflux*dxt*rho_dzt*temp,z-integral cp*submeso_xflux*dyt*rho_dzt*temp,liquid precip (including ice melt/form) into ocean (>0 enters ocean),snow falling onto ocean (>0 enters ocean),mass flux from evaporation/condensation (>0 enters ocean),mass flux of liquid river runoff entering ocean,water flux transferred with sea ice form/melt (>0 enters ocean),mass flux of precip-evap+river via sbc (liquid, frozen, evaporation),water into ocean due to ice melt (>0 enters ocean),water out of ocean due to ice form (>0 enters ocean),precip-evap into ocean (total w/ restore + normalize),sfc_salt_flux_ice,sfc_salt_flux_runoff,sfc_salt_flux_restore: flux from restoring term,sfc_salt_flux_coupler: flux from the coupler,heat flux from precip transfer of water across ocean surface,heat flux from evap transfer of water across ocean surface,heat flux (relative to 0C) from liquid river runoff,heat flux to melt frozen precip (<0 cools ocean),Vertical sum of ocn frazil heat flux over time step,longwave flux into ocean (<0 cools ocean),latent heat flux into ocean (<0 cools ocean),sensible heat into ocean (<0 cools ocean),shortwave flux into ocean (>0 heats ocean),penetrative shortwave heating,heat into ocean due to melting ice (>0 heats ocean),heat into ocean due to land ice discharge-melt (>0 heats ocean),surface ocean heat flux coming through coupler and mass transfer,cp*rivermix*rho_dzt*temp,surface heat flux coming through coupler,heat flux (relative to 0C) from pme transfer of water across ocean surface,i-directed wind stress forcing u-velocity,j-directed wind stress forcing v-velocity,Bottom u-stress via bottom drag,Bottom v-stress via bottom drag,vertical piece of Ertel PV: (f+zeta)*N^2,i-current,j-current,Thickness and rho wghtd horz bih frict on u-zonal,Thickness and rho wghtd horz bih frict on v-merid,3d velocity dot product with 3d gradient of vertical piece of Ertel PV: u.grad((f+zeta)*N^2),Ekman vertical velocity averaged to wt-point,surface height including steric contribution,Potential temperature,Potential temperature,Start time for average period,End time for average period,Length of average period,time axis boundaries
    intake_esm_attrs:variable_standard_name :
    sea_water_pressure_at_sea_floor,sea_water_pressure_at_sea_water_surface,sea_water_mass_per_unit_area,cell_thickness,sea_surface_height_above_geoid,square_of_sea_surface_height_above_geoid,sea_water_potential_temperature,sea_water_conservative_temperature,sea_surface_temperature,square_of_sea_surface_temperature,,sea_water_salinity,sea_surface_salinity,square_of_sea_surface_salinity,,sea_water_age_since_surface_contact,ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_mixed_layer_thickness_defined_by_sigma_t,square_of_ocean_mixed_layer_thickness_defined_by_sigma_t,ocean_barotropic_mass_streamfunction,,,,ocean_mixed_layer_thickness_defined_by_mixing_scheme,sea_water_potential_density,,,,sea_water_x_velocity,sea_water_y_velocity,,ocean_mass_x_transport,ocean_mass_y_transport,upward_ocean_mass_transport,,,,,,,,,,,,,,,,,,,,,rainfall_flux,snowfall_flux,water_evaporation_flux,water_flux_into_sea_water_from_rivers,water_flux_into_sea_water_due_to_sea_ice_thermodynamics,water_flux_into_sea_water,icemelt_flux,iceform_flux,,downward_sea_ice_basal_salt_flux,salt_flux_into_sea_water_from_rivers,,,temperature_flux_due_to_rainfall_expressed_as_heat_flux_into_sea_water,temperature_flux_due_to_evaporation_expressed_as_heat_flux_into_sea_water,temperature_flux_due_to_runoff_expressed_as_heat_flux_into_sea_water,heat_flux_into_sea_water_due_to_snow_thermodynamics,,surface_net_downward_longwave_flux,surface_downward_latent_heat_flux,surface_downward_sensible_heat_flux,surface_net_downward_shortwave_flux,downwelling_shortwave_flux_in_sea_water,mh_flux,liceht_flux,,,,,surface_downward_x_stress,surface_downward_y_stress,,,,sea_water_x_velocity,sea_water_y_velocity,,,,,,sea_surface_temperature,sea_surface_temperature,,,,
    intake_esm_attrs:variable_cell_methods :
    time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: min,time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean,time: mean_pow(02),time: mean_pow(02),time: mean,time: mean,time: mean,time: mean,time: mean,time: max,time: min,,,,
    intake_esm_attrs:variable_units :
    dbar,Pa,(kg/m^3)*m,m,meter,m^2,K,K,K,squared K,deg_C,psu,psu,squared psu,psu,yr,m,m,m,m^2,kg/s,kg/s,1/s,1/s^2,m,kg/m^3,kg/m^3,kg/m^3,meter,m/sec,m/sec,m/sec,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,kg/s,Watts,Watts,Watt,Watt,Watt,Watt,Watt,Watt,(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),(kg/m^3)*(m/sec),kg/(m^2*sec),kg/(m^2*sec),kg/(m^2*sec),kg/(m^2*sec),Watts/m^2,Watts/m^2,Watts/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,W/m^2,(W/m^2),(W/m^2),Watts/m^2,Watt/m^2,Watts/m^2,Watts/m^2,N/m^2,N/m^2,N/m^2,N/m^2,1/sec^3,m/sec,m/sec,(kg/m^3)*(m^2/s^2),(kg/m^3)*(m^2/s^2),1/sec^4,m/s,meter,K,K,days since 0001-01-01 00:00:00,days since 0001-01-01 00:00:00,days,days
    intake_esm_attrs:filename :
    ocean_month.nc
    intake_esm_attrs:file_id :
    ocean_month
    intake_esm_attrs:_data_format_ :
    netcdf
    intake_esm_dataset_key :
    ocean_month.1mon
    • " ], "text/plain": [ " Size: 5GB\n", @@ -3952,7 +3953,7 @@ "Coordinates:\n", " * xt_ocean (xt_ocean) float64 12kB -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n", " * yt_ocean (yt_ocean) float64 9kB -81.08 -80.97 -80.87 ... 89.74 89.84 89.95\n", - "Dimensions without coordinates: stat_type" + " dtype='float64', name='yt_ocean', length=1080))
    • " ], "text/plain": [ " Size: 25MB\n", @@ -4120,10 +4121,437 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "58dd2ab9-b505-4885-bed5-37567a403fc4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 31.5 s, sys: 3.98 s, total: 35.5 s\n", + "Wall time: 1min 6s\n" + ] + }, + { + "data": { + "text/html": [ + "
    \n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
    <xarray.DataArray (yt_ocean: 1080, xt_ocean: 1440)> Size: 12MB\n",
+       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
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+       "Coordinates:\n",
+       "  * xt_ocean  (xt_ocean) float64 12kB -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n",
+       "  * yt_ocean  (yt_ocean) float64 9kB -81.08 -80.97 -80.87 ... 89.74 89.84 89.95
    " + ], + "text/plain": [ + " Size: 12MB\n", + "array([[nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " ...,\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan],\n", + " [nan, nan, nan, ..., nan, nan, nan]])\n", + "Coordinates:\n", + " * xt_ocean (xt_ocean) float64 12kB -279.9 -279.6 -279.4 ... 79.38 79.62 79.88\n", + " * yt_ocean (yt_ocean) float64 9kB -81.08 -80.97 -80.87 ... 89.74 89.84 89.95" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "%%time \n", "stats.load()\n", @@ -4131,6 +4559,7 @@ "# Put data back into some more useful variable names\n", "sst_trend = stats.sel(stat_type=0)\n", "p_value = stats.sel(stat_type=1)\n", + "\n", "sst_trend" ] }, @@ -4139,25 +4568,67 @@ "id": "437d4d93-c95a-4606-a483-c5409ac37619", "metadata": {}, "source": [ - "Plot the calculated slope, stippling all regions that are significant at $p<0.05$." + "Plot the calculated slope, stippling all regions that are significant at $p<0.05$. Before we plot we need to load the unmasked coordinates and attach them to the dataarray otherwise regions neal the poles will be distorted (see )." ] }, { "cell_type": "code", - "execution_count": null, - "id": "539a6348-94b0-491c-94bf-a55ca72a25bd", + "execution_count": 10, + "id": "836b90e1-6089-4b74-b73a-ad98f8eac1cf", "metadata": {}, "outputs": [], "source": [ - "sst_trend.plot(cbar_kwargs={'label': '°C/yr'})\n", - "plt.contourf(p_value.xt_ocean, p_value.yt_ocean, p_value,\n", - " levels=(0, 0.05), colors='None', hatches=('...',))\n", - "plt.title('ACCESS-OM2-025 SST trend')" + "geolon_t = xr.open_dataset(\"/g/data/ik11/grids/ocean_grid_025.nc\").geolon_t\n", + "geolat_t = xr.open_dataset(\"/g/data/ik11/grids/ocean_grid_025.nc\").geolat_t\n", + "\n", + "sst_trend = sst_trend.assign_coords({\"geolon_t\": geolon_t, \"geolat_t\": geolat_t})\n", + "p_value = p_value.assign_coords({\"geolon_t\": geolon_t, \"geolat_t\": geolat_t})" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "539a6348-94b0-491c-94bf-a55ca72a25bd", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 4))\n", + "\n", + "ax = plt.axes(projection=ccrs.Robinson())\n", + "\n", + "ax.coastlines(resolution=\"50m\")\n", + "ax.gridlines(draw_labels=False)\n", + "\n", + "sst_trend.plot(ax=ax,\n", + " x=\"geolon_t\",\n", + " y=\"geolat_t\",\n", + " transform=ccrs.PlateCarree(),\n", + " cbar_kwargs={'label': '°C/yr',\n", + " 'extend': 'both'})\n", + "\n", + "plt.contourf(p_value.geolon_t, p_value.geolat_t, p_value,\n", + " levels=(0, 0.05),\n", + " colors='None',\n", + " hatches=('...',),\n", + " transform=ccrs.PlateCarree())\n", + "\n", + "plt.title('ACCESS-OM2-025 SST trend');" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "f27843df", "metadata": {}, "outputs": [],