{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Exemplary time series" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import xarray as xr\n", "import scipy.signal as sig\n", "import matplotlib.pyplot as plt\n", "\n", "from matplotlib.collections import LineCollection\n", "from matplotlib.colors import BoundaryNorm, ListedColormap\n", "\n", "plt.rc('xtick', labelsize=8)\n", "plt.rc('ytick', labelsize=8)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/gxfs_work/geomar/smomw379/miniconda3/envs/py3_mhw/lib/python3.12/site-packages/distributed/node.py:182: UserWarning: Port 8787 is already in use.\n", "Perhaps you already have a cluster running?\n", "Hosting the HTTP server on port 33073 instead\n", " warnings.warn(\n" ] } ], "source": [ "import dask, dask_jobqueue \n", "import dask.distributed as dask_distributed\n", "\n", "cluster = dask_jobqueue.SLURMCluster(\n", " # Dask worker size\n", " cores=32, memory='80GB',\n", " processes=4, # Dask workers per job\n", " # SLURM job script things\n", " queue='base', walltime='03:00:00',\n", " # Dask worker network and temporary\n", " interface='ib0', local_directory='./dask_jobqueue_logs'\n", " )\n", "\n", "client = dask_distributed.Client(cluster)\n", "cluster.scale(jobs=1)\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " JOBID PARTITION NAME USER ST TIME NODES NODELIST(REASON)\n", " 17345954 base dask-wor smomw379 R 7:30 1 nesh-srp198\n", " 17345914 base dask-wor smomw379 R 17:04 1 nesh-clk501\n" ] } ], "source": [ "!squeue -u smomw379" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Client-52b4afc9-6df5-11f0-ba89-74563c5ee57c

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Connection method: Cluster objectCluster type: dask_jobqueue.SLURMCluster
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Cluster Info

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SLURMCluster

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e207d8f4

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Scheduler

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\n", " Comm: tcp://172.18.4.21:41271\n", " \n", " Workers: 4\n", "
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Worker: SLURMCluster-0-0

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Worker: SLURMCluster-0-1

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Worker: SLURMCluster-0-2

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Worker: SLURMCluster-0-3

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" ], "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "client" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "## exemplary grid point\n", "ys = 500\n", "xs = 750" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "## domain \n", "if xs+250 > 2500:\n", " x0 = np.arange(xs,1442)\n", "else:\n", " x0 = np.arange(xs,xs+250)\n", "\n", "if ys+250 > 2500:\n", " y0 = np.arange(ys,1021)\n", "else:\n", " y0 = np.arange(ys,ys+250)\n", "\n", "# time\n", "yr0=1980 # first year\n", "yr1=2022 # last year (included)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## temperature anomalies" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def fixed(temp_load):\n", " ## use raw timeseries\n", " temp = temp_load - temp_load.mean('time')\n", " return temp\n", "\n", "def detrend(temp_load):\n", " ## remove linear trend\n", " temp = xr.DataArray(sig.detrend(temp_load, axis=0)\n", " ).rename('votemper').rename({'dim_0':'time'}\n", " ).assign_coords({'time':dsT.time_counter.values})\n", " return temp\n", "\n", "def non_linear(temp_load):\n", " ## remove moving average\n", " N_window = 20*365 # window size \n", " ind_min = int(N_window/2) #first valid index (that uses the full window)\n", " ind_max = lt-int(N_window/2) #last valid index\n", " # running mean (boxcar)\n", " temp_rolling = np.zeros(temp_load.shape)\n", " temp_rolling = temp_load.rolling({'time':N_window},center=True).mean()\n", " # increase the window size gradually from first timestep to first timestep that can use the full window \n", " for tt in range(0,ind_min):\n", " temp_rolling[tt] = temp_load[0:ind_min+tt].mean('time')\n", " for tt in range(ind_max+1,lt):\n", " temp_rolling[tt] = temp_load[int(ind_max-(N_window/2+(tt-ind_max+1))):lt].mean('time')\n", "\n", " temp = (temp_load - temp_rolling).compute()\n", "\n", " return temp\n", "\n", "def WMO(temp_load):\n", " ## use raw timeseries (1991-2020)\n", " temp = temp_load - temp_load.sel(time=slice('1980','2009')).mean('time')\n", " return temp" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "z0=30" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "## load the temperature for the cutout region\n", "EXP = 'VIKING20X.L46-KFS003'\n", "path = f'/gxfs_work/geomar/smomw379/DATA/{EXP}/TMP/votemper_BASE_30/'\n", "dsT = xr.open_mfdataset(path+f'{EXP}_1d_*0101_*1231_votemper' +\n", " f'_{x0.min()}-{x0.max()}_{y0.min()}-{y0.max()}-{z0}.nc').isel(x=245,y=182)\n", "\n", "temp_load = dsT.votemper.rename({'time_counter':'time'}).load()\n", "\n", "lt = len(temp_load)\n", "\n", "EXP = 'VIKING20X.L46-KFS003-6th'\n", "path = f'/gxfs_work/geomar/smomw379/DATA/{EXP}/TMP/votemper_BASE_30/'\n", "dsT = xr.open_mfdataset(path+f'{EXP}_1d_*0101_*1231_votemper' +\n", " f'_{x0.min()}-{x0.max()}_{y0.min()}-{y0.max()}-{z0}.nc').isel(x=245,y=182)\n", "\n", "temp_load_6 = dsT.votemper.rename({'time_counter':'time'}).load()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "temp_non_linear = non_linear(temp_load)\n", "temp_fixed = fixed(temp_load)\n", "temp_detrend = detrend(temp_load)\n", "temp_WMO = WMO(temp_load)\n", "\n", "temp6_non_linear = non_linear(temp_load_6)\n", "temp6_fixed = fixed(temp_load_6)\n", "temp6_detrend = detrend(temp_load_6)\n", "temp6_WMO = WMO(temp_load_6)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## calculate climatologies" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "def daily_clim(doy, temp, tsel): \n", "\n", " ## for each day of the year get list of indices from full timeseries \n", " doys = np.arange(doy-5,doy+6) # Hobday et al. (2016): take +- 5 days\n", "\n", " doys[doys<1] = 366 + doys[doys<1] # include last/first days of year at beginning/end of year\n", " doys[doys>366] = doys[doys>366] - 366\n", " # get the indices in a sorted array\n", " ind_doy = np.array([])\n", " for xx in range(0,11):\n", " ind_doy = np.append(ind_doy, np.where(dsT.time_counter.sel(time_counter=tsel).dt.dayofyear == doys[xx])[0])\n", " ind_doy = np.sort(ind_doy).astype(int)\n", "\n", " ## temperature at doy from all years\n", " T_doy = temp.isel(time=ind_doy)\n", "\n", " ## average temperature for doy\n", " T_clim = T_doy.mean('time').compute()\n", "\n", " ## standard deviation temperature for doy\n", " T_std = T_doy.std('time').compute()\n", "\n", " return T_clim, T_std" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "## 1st cycle\n", "T_clim_fixed = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T_std_fixed = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "T_clim_non_linear = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T_std_non_linear = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "T_clim_detrend = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T_std_detrend = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "T_clim_WMO = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T_std_WMO = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "\n", "for doy in range(0,366):\n", " T_clim_fixed[doy], T_std_fixed[doy] = daily_clim(doy,temp_fixed, tsel=slice('1980','2022'))\n", " T_clim_non_linear[doy], T_std_non_linear[doy] = daily_clim(doy,temp_non_linear, tsel=slice('1980','2022'))\n", " T_clim_detrend[doy], T_std_detrend[doy] = daily_clim(doy,temp_detrend, tsel=slice('1980','2022'))\n", " T_clim_WMO[doy], T_std_WMO[doy] = daily_clim(doy,temp_WMO, tsel=slice('1980','2009'))\n", "\n", "\n", "\n", "## 6th cycle\n", "T6_clim_fixed = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T6_std_fixed = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "T6_clim_non_linear = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T6_std_non_linear = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "T6_clim_detrend = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T6_std_detrend = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "T6_clim_WMO = xr.DataArray(np.zeros((366))).rename('seas').rename({'dim_0':'doy'})\n", "T6_std_WMO = xr.DataArray(np.zeros((366))).rename('std').rename({'dim_0':'doy'})\n", "\n", "\n", "for doy in range(0,366):\n", " T6_clim_fixed[doy], T6_std_fixed[doy] = daily_clim(doy,temp6_fixed,tsel=slice('1980','2022'))\n", " T6_clim_non_linear[doy], T6_std_non_linear[doy] = daily_clim(doy,temp6_non_linear,tsel=slice('1980','2022'))\n", " T6_clim_detrend[doy], T6_std_detrend[doy] = daily_clim(doy,temp6_detrend,tsel=slice('1980','2022'))\n", " T6_clim_WMO[doy], T6_std_WMO[doy] = daily_clim(doy,temp6_WMO,tsel=slice('1980','2009'))" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "#### 1st cycle\n", "## fixed\n", "thresh_raw = (T_clim_fixed + 1.28*T_std_fixed).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh_fixed = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "# non - linear\n", "thresh_raw = (T_clim_non_linear + 1.28*T_std_non_linear).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh_non_linear = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "# non - linear\n", "thresh_raw = (T_clim_detrend + 1.28*T_std_detrend).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh_detrend = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "# WMO\n", "thresh_raw = (T_clim_WMO + 1.28*T_std_WMO).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh_WMO = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "#### 6th cycle\n", "## fixed\n", "thresh_raw = (T6_clim_fixed + 1.28*T6_std_fixed).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh6_fixed = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "# non - linear\n", "thresh_raw = (T6_clim_non_linear + 1.28*T6_std_non_linear).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh6_non_linear = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "# non - linear\n", "thresh_raw = (T6_clim_detrend + 1.28*T6_std_detrend).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh6_detrend = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n", "\n", "# WMO\n", "thresh_raw = (T6_clim_WMO + 1.28*T6_std_WMO).compute()\n", "thresh_ext = xr.DataArray(np.tile(thresh_raw,3)).rename('thresh').rename({'dim_0':'doy'})\n", "thresh6_WMO = thresh_ext.rolling({'doy':31}, center=True).mean()[366:366+366].assign_coords({'doy':np.arange(1,367)}).compute()\n" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "## anomaly relative to threshold\n", "\n", "T_ano_fixed = (temp_fixed.groupby('time.dayofyear') - thresh_fixed.rename({'doy':'dayofyear'})).compute()\n", "T_ano_detrend = (temp_detrend.groupby('time.dayofyear') - thresh_detrend.rename({'doy':'dayofyear'})).compute()\n", "T_ano_non_linear = (temp_non_linear.groupby('time.dayofyear') - thresh_non_linear.rename({'doy':'dayofyear'})).compute()\n", "T_ano_WMO = (temp_WMO.groupby('time.dayofyear') - thresh_WMO.rename({'doy':'dayofyear'})).compute()\n", "\n", "\n", "T6_ano_fixed = (temp6_fixed.groupby('time.dayofyear') - thresh6_fixed.rename({'doy':'dayofyear'})).compute()\n", "T6_ano_detrend = (temp6_detrend.groupby('time.dayofyear') - thresh6_detrend.rename({'doy':'dayofyear'})).compute()\n", "T6_ano_non_linear = (temp6_non_linear.groupby('time.dayofyear') - thresh6_non_linear.rename({'doy':'dayofyear'})).compute()\n", "T6_ano_WMO = (temp6_WMO.groupby('time.dayofyear') - thresh6_WMO.rename({'doy':'dayofyear'})).compute()\n" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "## add globally averaged temperature\n", "path = '/gxfs_work/geomar/smomw379/DATA/VIKING20X.L46-KFS003/globmean/'\n", "dsT_glob = xr.open_mfdataset(path + 'VIKING20X.L46-KFS003_1m_*0101_*1231_globmeanT.nc').rename({'gdept':'deptht'}).squeeze()\n", "dsT_glob = dsT_glob.sel(time_counter=slice('1980','2022'))\n", "\n", "path = '/gxfs_work/geomar/smomw355/model_data/ocean-only/VIKING20X.L46-KFS003-6th/nemo/derived/'\n", "dsT_glob6 = xr.open_mfdataset(path+'VIKING20X.L46-KFS003-6th_1m_*0101_*1231_globmeanT.nc').squeeze()\n", "dsT_glob6 = dsT_glob6.sel(time_counter=slice('1980','2022'))" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "time = temp_load.time" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "def coloured_line(temp, axI):\n", " ax = axI.twiny(); ax.set_yticks([]), ax.set_xticks([])\n", " points = np.array([time.astype(float), temp]).T.reshape(-1, 1, 2)\n", " segments = np.concatenate([points[:-1], points[1:]], axis=1)\n", "\n", " # Use a boundary norm instead\n", " cmap = ListedColormap(['cornflowerblue','r'])\n", " norm = BoundaryNorm([-1, 0, 1], cmap.N)\n", "\n", " lc = LineCollection(segments, cmap=cmap, norm=norm)\n", " lc.set_array(temp)\n", " lc.set_linewidth(1.5)\n", " line = ax.add_collection(lc)\n", " ax.set_ylim(-0.4, 0.25)\n", " ax.set_xlim(time.astype(float)[0],time.astype(float)[-1])\n" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(7.5,7))\n", "ax0 = fig.add_axes([0.08,0.78,0.39,0.18]); axX = fig.add_axes([0.53,0.78,0.39,0.18])\n", "\n", "ax1 = fig.add_subplot([0.08,0.54,0.39,0.18]); axA = fig.add_axes([0.53,0.54,0.39,0.18])\n", "ax2 = fig.add_subplot([0.08,0.3,0.39,0.18]); axB = fig.add_axes([0.53,0.3,0.39,0.18])\n", "ax4 = fig.add_subplot([0.08,0.06,0.39,0.18]); axD = fig.add_axes([0.53,0.06,0.39,0.18])\n", "\n", "##\n", "ax0.contourf(dsT_glob.time_counter, -dsT_glob.deptht,\n", " (dsT_glob.mean_votemper - dsT_glob.mean_votemper.mean('time_counter')).transpose(),\n", " cmap='RdBu_r', levels=np.arange(-0.08,0.085,0.005), extend='both')\n", "\n", "\n", "ax0.hlines(-100,dsT_glob.time_counter[0], dsT_glob.time_counter[-1], colors='grey', linestyles='--')\n", "ax0.hlines(-1000,dsT_glob.time_counter[0], dsT_glob.time_counter[-1], colors='grey', linestyles='--')\n", "ax0.hlines(-2200,dsT_glob.time_counter[0], dsT_glob.time_counter[-1], colors='grey', linestyles='--')\n", "\n", "ax0.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "ax0.set_ylim(-2500,0)\n", "ax0.set_yticks(np.arange(-2500,1,500))\n", "ax0.set_yticklabels(np.arange(2500,-1,-500))\n", "ax0.set_title('a) Globally averaged temperature (1st cycle)', fontsize=8, loc='left')\n", "ax0.set_ylabel('Depth [m]', fontsize=8)\n", "\n", "##\n", "ctf1 = axX.contourf(dsT_glob6.time_counter, -dsT_glob6.deptht,\n", " (dsT_glob6.mean_votemper - dsT_glob6.mean_votemper.mean('time_counter')).transpose(),\n", " cmap='RdBu_r', levels=np.arange(-0.08,0.085,0.005), extend='both')\n", "\n", "axX.hlines(-100,dsT_glob.time_counter[0], dsT_glob.time_counter[-1], colors='grey', linestyles='--')\n", "axX.hlines(-1000,dsT_glob.time_counter[0], dsT_glob.time_counter[-1], colors='grey', linestyles='--')\n", "axX.hlines(-2200,dsT_glob.time_counter[0], dsT_glob.time_counter[-1], colors='grey', linestyles='--')\n", "\n", "axX.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "axX.set_ylim(-2500,0)\n", "axX.set_yticks(np.arange(-2500,1,500))\n", "axX.set_yticklabels(np.arange(2500,-1,-500))\n", "axX.set_title('b) Globally averaged temperature (6th cycle)', fontsize=8, loc='left')\n", "\n", "##\n", "coloured_line(T_ano_fixed, ax1)\n", "\n", "ax1.plot(time, np.zeros(len(time)), color='dimgrey', linestyle='--', zorder=15)\n", "ax1.set_title(r'c) Fixed$_{43yr}$ baseline (1st cycle)', loc='left', fontsize=8, pad=4)\n", "ax1.set_ylim(-0.4,0.4)\n", "ax1.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "ax1.set_ylabel('Temp. anomaly [°C]', fontsize=8)\n", "ax1.set_yticks(np.arange(-0.4,0.41,0.2))\n", "\n", "##\n", "coloured_line(T_ano_detrend, ax2)\n", "\n", "ax2.plot(time, np.zeros(len(time)), color='dimgrey', linestyle='--', zorder=15)\n", "ax2.set_title('e) Detrended baseline (1st cycle)', loc='left', fontsize=8, pad=4)\n", "ax2.set_ylim(-0.4,0.4)\n", "ax2.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "ax2.set_ylabel('Temp. anomaly [°C]', fontsize=8)\n", "ax2.set_yticks(np.arange(-0.4,0.41,0.2))\n", "\n", "##\n", "coloured_line(T_ano_WMO, ax4)\n", "\n", "ax4.plot(time, np.zeros(len(time)), color='dimgrey', linestyle='--', zorder=15)\n", "ax4.set_title('g) Fixed$_{30yr}$ baseline (1st cycle)', loc='left', fontsize=8, pad=4)\n", "ax4.set_xlabel('Year', fontsize=8)\n", "ax4.set_ylim(-0.4,0.4)\n", "ax4.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "ax4.set_ylabel('Temp. anomaly [°C]', fontsize=8)\n", "ax4.set_yticks(np.arange(-0.4,0.41,0.2))\n", "\n", "##\n", "coloured_line(T6_ano_fixed, axA)\n", "\n", "axA.plot(time, np.zeros(len(time)), color='dimgrey', linestyle='--', zorder=15)\n", "axA.set_title('d) Fixed$_{43yr}$ baseline (6th cycle)', loc='left', fontsize=8, pad=4)\n", "axA.set_ylim(-0.4,0.4)\n", "axA.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "axA.set_yticks(np.arange(-0.4,0.41,0.2))\n", "\n", "##\n", "coloured_line(T6_ano_detrend, axB)\n", "\n", "axB.plot(time, np.zeros(len(time)), color='dimgrey', linestyle='--', zorder=15)\n", "axB.set_title('f) Detrended baseline (6th cycle)', loc='left', fontsize=8, pad=4)\n", "axB.set_ylim(-0.4,0.4)\n", "axB.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "axB.set_yticks(np.arange(-0.4,0.41,0.2))\n", "\n", "##\n", "coloured_line(T6_ano_WMO, axD)\n", "\n", "axD.plot(time, np.zeros(len(time)), color='dimgrey', linestyle='--', zorder=15)\n", "axD.set_xlabel('Year', fontsize=8)\n", "axD.set_title('h) Fixed$_{30yr}$ baseline (6th cycle)', loc='left', fontsize=8,pad=4)\n", "axD.set_ylim(-0.4,0.4)\n", "axD.set_xlim(np.datetime64('1980-01-01'), np.datetime64('2021-12-31'))\n", "axD.set_yticks(np.arange(-0.4,0.41,0.2))\n", "\n", "## colorbar \n", "axcb = fig.add_axes([0.525,0.78,0.48,0.18], frameon=False); axcb.set_xticks([]); axcb.set_yticks([]);\n", "cb = plt.colorbar(ctf1, ax=[axcb], orientation='vertical') \n", "cb.set_label('[°C]', y=1.15, labelpad=-25, fontsize=8, rotation=0)\n", "\n", "plt.savefig('Baseline_temp-tseries.png', dpi=300)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Save data for publication" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "## variable attributes\n", "T6_ano_WMO.attrs['long_name'] = 'Temperature anomaly relative to MHW threshold (6th-cycle)'\n", "T6_ano_WMO.attrs['units'] = 'degC'\n", "T6_ano_detrend.attrs['long_name'] = 'Temperature anomaly relative to MHW threshold (6th-cycle)'\n", "T6_ano_detrend.attrs['units'] = 'degC'\n", "T6_ano_fixed.attrs['long_name'] = 'Temperature anomaly relative to MHW threshold (6th-cycle)'\n", "T6_ano_fixed.attrs['units'] = 'degC'\n", "\n", "T_ano_fixed.attrs['long_name'] = 'Temperature anomaly relative to MHW threshold (1st-cycle)'\n", "T_ano_fixed.attrs['units'] = 'degC'\n", "T_ano_detrend.attrs['long_name'] = 'Temperature anomaly relative to MHW threshold (1st-cycle)'\n", "T_ano_detrend.attrs['units'] = 'degC'\n", "T_ano_WMO.attrs['long_name'] = 'Temperature anomaly relative to MHW threshold (1st-cycle)'\n", "T_ano_WMO.attrs['units'] = 'degC'" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "T_glob_mean = dsT_glob.mean_votemper\n", "T_glob_mean.attrs['long_name'] = 'Global mean temperature (1st-cycle)'\n", "\n", "T6_glob_mean = dsT_glob6.mean_votemper\n", "T6_glob_mean.attrs['long_name'] = 'Global mean temperature (6th-cycle)'" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "## create output dataset\n", "ds_out = xr.Dataset(data_vars={'T6_ano_fixed30yr':T6_ano_WMO.compute(), 'T6_ano_detrend':T6_ano_detrend.compute(), 'T6_ano_fixed43yr':T6_ano_fixed.compute(), \n", " 'T_ano_fixed43yr':T_ano_fixed.compute(), 'T_ano_detrend':T_ano_detrend.compute(), 'T_ano_fixed30yr':T_ano_WMO.compute(),\n", " 'T_glob_mean':T_glob_mean.compute(),'T6_glob_mean':T6_glob_mean.compute()\n", " })" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "## set global attributes\n", "ds_out.attrs['title'] = 'Temperature anomalies global and example grid point'\n", "ds_out.attrs['institution'] = 'GEOMAR Helmholtz Centre for Ocean Research Kiel'\n", "ds_out.attrs['creator_name'] = 'Tobias Schulzki'\n", "ds_out.attrs['creator_email'] = 'tschulzki@geomar.de'\n", "ds_out.attrs['creator_url'] = 'orcid.org/0000-0002-3480-8492'\n", "ds_out.attrs['license'] = 'CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en)'\n", "ds_out.attrs['keywords'] = 'Temperature, marine heatwaves, VIKING20X, numerical model'\n", "ds_out.attrs['summary'] = 'Created in 2_Baseline_tseries.ipynb'\n", "ds_out.attrs['cdm_data_type'] = 'grid'\n", "ds_out.attrs['processing_level'] = 'Level 4 (numerical simulation output)'\n", "ds_out.attrs['source'] = 'VIKING20X'\n", "ds_out.attrs['pi'] = 'Tobias Schulzki'\n", "ds_out.attrs['pi_contact'] = 'tschulzki@geomar.de'\n", "ds_out.attrs['pi_url'] = 'orcid.org/0000-0002-3480-8492'\n", "ds_out.attrs['institution_id'] = 'https://ror.org/02h2x0161'\n", "ds_out.attrs['research_devision'] = 'Ocean Circulation and Climate Dynamics'\n", "ds_out.attrs['research_unit'] = 'Ocean Dynamics'\n", "ds_out.attrs['project'] = 'iAtlantic, METAscales'\n", "ds_out.attrs['date_created'] = '2025-07-31'\n", "ds_out.attrs['date_modified'] = '2025-07-31'\n", "ds_out.attrs['publisher_name'] = 'GEOMAR Helmholtz Centre for Ocean Research Kiel'\n", "ds_out.attrs['publisher_email'] = 'datamanagement@geomar.de'\n", "ds_out.attrs['naming_authority'] = 'de.geomar'" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "outpath = '/gxfs_work/geomar/smomw379/Publications/Schulzki2025_MHWs/DATA/'\n", "ds_out.to_netcdf(outpath+'Schulzki_et_al_2025_Figure02.nc')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "py3_mhw", "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": "3.12.0" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }