{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "### Figure 3 \n", "(a) and (b) show the time series of $\\Delta C_{land}$ and $\\Delta C_{ocean}$\n", "\n", "(c) and (d) show the time series of feedback ratios $\\lambda_{A/R}$ and $\\lambda_{OAE}$\n", "\n", "(e) shows the feedback ratios averaged over 2040 to 2060 and the theoretical values" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import copy\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import netCDF4 as nc\n", "import pandas as pd\n", "import sys\n", "import importlib\n", "import my_io\n", "importlib.reload(my_io)\n", "from my_io import Figure1\n", "OAE_STOP = False\n", "ppm2GtCO2 = 2.124/0.272912\n", "fontsize = 18\n", "def ens_values(df_list,var_name):\n", " '''\n", " df_list: a list of DataFrame\n", " '''\n", " yrstart = 2015\n", " diff_realizaions = [] # (nreal,nyear)\n", " for ireal in range(len(df_list)):\n", " diff_realizaions.append([])\n", " for iyear in range(yrstart,2100):\n", " for ireal in range(len(df_list)):\n", " diff_realizaions[ireal].append(df_list[ireal][var_name].loc[iyear]) \n", " diff_realizaions = np.array(diff_realizaions)\n", " ens_mean = np.average(diff_realizaions,axis=0)\n", " ens_min = np.min(diff_realizaions,axis=0)\n", " ens_max = np.max(diff_realizaions,axis=0)\n", " ens_stddev = np.std(diff_realizaions,axis=0)\n", " yrindex = np.array(range(yrstart,2100)) \n", " df_ens = pd.DataFrame(data=ens_max - ens_min, index=yrindex, columns=['ens_range'])\n", " df_ens['ens_mean'] = ens_mean\n", " df_ens['ens_min'] = ens_min\n", " df_ens['ens_max'] = ens_max\n", " return df_ens\n", "def cOcean_from_fgco2(df,yrstart):\n", " cOcean = []\n", " for year in range(yrstart,2100):\n", " cOcean.append(df['fgco2'].loc[yrstart:year].sum())\n", " cOcean = np.array(cOcean)\n", " cOcean = pd.DataFrame(data=cOcean, index=range(yrstart,2100), columns=['cOcean'])\n", " cOcean.index.name = 'year'\n", " return cOcean" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "feedback_ratio_limit = [-30,10]\n", "try:\n", " del fig\n", "except:\n", " pass\n", "fig = plt.figure(figsize=(14,9),layout=\"constrained\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### cLand and cOcean of A/R and OAE of all available models" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ACCESS-ESM1-5 C0\n", "CESM2 C1\n", "CanESM5 C2\n", "FOCI C3\n", "MIROC-ES2L C4\n", "MPI-ESM1-2-LR C5\n", "NorESM2-LM C6\n", "UKESM1-0-LL C7\n" ] } ], "source": [ "model_list = ['ACCESS-ESM1-5', 'CESM2', 'CanESM5', \n", " 'FOCI', 'MIROC-ES2L', 'MPI-ESM1-2-LR',\n", " 'NorESM2-LM','UKESM1-0-LL']\n", "color_list = []\n", "for imodel in range(len(model_list)):\n", " color_list.append('C'+str(imodel))\n", " print(model_list[imodel],color_list[imodel])" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "105.58006905726563\n", "0.7848661510247531\n", "106.93174226414061\n", "0.794914283752795\n", "107.6625099853594\n", "0.8003466996790911\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "'''\n", "(a) diff in cLand/cOcean of A/R (all models, FOCI + MPI-ESM + LUMIP)\n", "'''\n", "import matplotlib.patches as mpatches\n", "ax = fig.add_subplot(321)\n", "handles = []\n", "for imodel in range(len(model_list)):\n", " # for legend\n", " patch = mpatches.Patch(color=color_list[imodel], label=model_list[imodel])\n", " handles.append(patch) \n", " #######\n", " if model_list[imodel] in ['NorESM2-LM']:\n", " continue\n", " elif model_list[imodel]=='MPI-ESM1-2-LR':\n", " ############## cLand\n", " var_name, exp = 'cLand', 'BOTH' \n", " fig1 = Figure1(var_name,exp)\n", " fig1.read_MPIESM()\n", " df_ens = ens_values([fig1.dflist[3][0]-fig1.dflist[2][0],\n", " fig1.dflist[3][1]-fig1.dflist[2][1],\n", " fig1.dflist[3][2]-fig1.dflist[2][2]],'cLand')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'-',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ###### cOcean\n", " var_name, exp = 'fgco2', 'BOTH' \n", " fig1 = Figure1(var_name,exp)\n", " fig1.read_MPIESM()\n", " cOcean = []\n", " for iexp in range(4):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " if iexp in [0,2,3]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " if iexp in [1]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2020)) \n", " cOcean[iexp][ireal] = cOcean[iexp][ireal] + cOcean[0][ireal].loc[2019]\n", " cOcean[iexp][ireal] = pd.concat([cOcean[iexp][ireal], cOcean[0][ireal].loc[2015:2019]]).sort_values('year')\n", " for ireal in range(3):\n", " d_cOcean_OAE_2099 = (cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean']).loc[2099]\n", " print(d_cOcean_OAE_2099)\n", " print(f'{d_cOcean_OAE_2099/(0.14*80*12.0107)}')\n", " df_ens = ens_values([cOcean[3][0]-cOcean[2][0],\n", " cOcean[3][1]-cOcean[2][1],\n", " cOcean[3][2]-cOcean[2][2],],'cOcean')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'--',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ########## FOCI\n", " elif model_list[imodel]=='FOCI':\n", " ############# cLand\n", " var_name, exp = 'cLand', 'BOTH' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_FOCI()\n", " # fig1.read_MPIESM()\n", "# for ireal in range(3):\n", " # ax.plot(fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'--',color='C1',label='cLand (OAE)')\n", "# ax.plot(fig1.dflist[2][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'-.',color=color_list[imodel],label='cLand (A/R)')\n", " df_ens = ens_values([fig1.dflist[2][0]-fig1.dflist[0][0],\n", " fig1.dflist[2][1]-fig1.dflist[0][1],\n", " fig1.dflist[2][2]-fig1.dflist[0][2]],'cLand')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'-',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ###### cOcean\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " for ireal in range(3):\n", " d_cOcean_OAE_2099 = (cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean']).loc[2099]\n", " df_ens = ens_values([cOcean[2][0]-cOcean[0][0],\n", " cOcean[2][1]-cOcean[0][1],\n", " cOcean[2][2]-cOcean[0][2],],'cOcean')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'--',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ############### ACCESS\n", " elif model_list[imodel]=='ACCESS-ESM1-5':\n", " ### cLand\n", " fig1=Figure1('cLand','foo')\n", " fig1.read_ACCESS_ensemble(debug=True)\n", " foo = []\n", " for ireal in range(10):\n", " foo.append(fig1.dflist[1][ireal]-fig1.dflist[0][ireal])\n", " df_ens = ens_values(foo,'cLand')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'-',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ### cOcean\n", " fig1 = Figure1('fgco2','foo')\n", " fig1.read_ACCESS_ensemble(debug=True)\n", " cOcean = []\n", " for iexp in [0,1]:\n", " cOcean.append([])\n", " for ireal in range(10):\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " foo = []\n", " for ireal in range(10):\n", " foo.append(cOcean[1][ireal]-cOcean[0][ireal])\n", " df_ens = ens_values(foo,'cOcean')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'--',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ############ rest of the models\n", " else:\n", " var_name, exp = 'cLand', 'AFF' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_model(model_list[imodel])\n", " for ireal in range(1):\n", " # ax.plot(fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'--',color='C1',label='cLand (OAE)')\n", " ax.plot(fig1.dflist[2][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'-',color=color_list[imodel],label=model_list[imodel])\n", " ######\n", " var_name, exp = 'fgco2', 'AFF' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_model(model_list[imodel])\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(1):\n", " if iexp==1:\n", " pass\n", " else:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " for ireal in range(1):\n", " # ax.plot(range(2015,2100),cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'-',color='C1',label='cOcean (OAE)')\n", " ax.plot(range(2015,2100),cOcean[2][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'--',color='C'+str(imodel),label=model_list[imodel])\n", "ax.grid()\n", "ax.tick_params(labelsize=fontsize)\n", "# handles, labels = ax.get_legend_handles_labels()\n", "# ax.legend([handles[0],handles[3]],[labels[0],labels[3]],loc = 'best', fontsize=fontsize)\n", "# ax.legend(loc = 'best', fontsize=fontsize)\n", "ax.set_title('(a) $\\Delta C_{land}$ and $\\Delta C_{ocean}$ (A/R-REF)',fontsize=18)\n", "ax.set_ylabel('PgC', fontsize = 18)\n", "ax.set_ylim([-25,120])\n", "######\n", "# subplot legend for dashed and solid lines\n", "from matplotlib.lines import Line2D\n", "line_solid = Line2D([], [], color='black', linestyle='--', linewidth=2, label='$C_{ocean}$')\n", "line_dashed = Line2D([], [], color='black', linestyle='-', linewidth=2, label='$C_{land}$')\n", "ax.legend(handles=[line_solid, line_dashed], loc='upper left',fontsize=fontsize)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(-25.0, 120.0)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "'''\n", "(b) diff in cLand/cOcean of OAE (all models, FOCI + MPI-ESM + CDRMIP)\n", "'''\n", "import matplotlib.patches as mpatches\n", "ax = fig.add_subplot(322)\n", "handles = []\n", "for imodel in range(len(model_list)):\n", " # for legend\n", " patch = mpatches.Patch(color=color_list[imodel], label=model_list[imodel])\n", " handles.append(patch) \n", " #######\n", " if model_list[imodel] in ['ACCESS-ESM1-5', 'CESM2', 'CanESM5', 'MIROC-ES2L']:\n", " continue\n", " ####### MPI-ESM\n", " elif model_list[imodel]=='MPI-ESM1-2-LR':\n", " #### MPI-ESM cLand\n", " var_name, exp = 'cLand', 'BOTH' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_MPIESM()\n", "# for ireal in range(3):\n", "# ax.plot(fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'--',color=color_list[imodel])\n", " df_ens = ens_values([fig1.dflist[1][0]-fig1.dflist[0][0],\n", " fig1.dflist[1][1]-fig1.dflist[0][1],\n", " fig1.dflist[1][2]-fig1.dflist[0][2]],'cLand')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'-',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ######## MPI-ESM cOcean\n", " var_name, exp = 'fgco2', 'BOTH' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_MPIESM()\n", " cOcean = []\n", " for iexp in range(4):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " if iexp in [0,2,3]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " if iexp in [1]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2020)) \n", " cOcean[iexp][ireal] = cOcean[iexp][ireal] + cOcean[0][ireal].loc[2019]\n", " cOcean[iexp][ireal] = pd.concat([cOcean[iexp][ireal], cOcean[0][ireal].loc[2015:2019]]).sort_values('year')\n", "# for ireal in range(3):\n", "# ax.plot(range(2015,2100),cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'-',color=color_list[imodel],label='OAE')\n", " df_ens = ens_values([cOcean[1][0]-cOcean[0][0],\n", " cOcean[1][1]-cOcean[0][1],\n", " cOcean[1][2]-cOcean[0][2],],'cOcean')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'--',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ### FOCI\n", " elif model_list[imodel]=='FOCI':\n", " ###### FOCI cLand\n", " var_name, exp = 'cLand', 'BOTH' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_FOCI()\n", "# for ireal in range(3):\n", "# ax.plot(fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'--',color=color_list[imodel],label='cLand (OAE)')\n", "# ax.plot(fig1.dflist[2][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'--',color=color_list[imodel],label='cLand (A/R)')\n", " df_ens = ens_values([fig1.dflist[1][0]-fig1.dflist[0][0],\n", " fig1.dflist[1][1]-fig1.dflist[0][1],\n", " fig1.dflist[1][2]-fig1.dflist[0][2],],'cLand')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'-',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ######## FOCI cOcean\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " for ireal in range(3):\n", "# ax.plot(range(2015,2100),cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'-',color=color_list[imodel],label='cOcean (OAE)')\n", " d_cOcean_OAE_2099 = (cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean']).loc[2099]\n", "# print(d_cOcean_OAE_2099)\n", "# print(f'{d_cOcean_OAE_2099/(0.14*80*12.0107)}')\n", "# ax.plot(range(2015,2100),cOcean[2][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'-',color=color_list[imodel],label='cOcean (A/R)')\n", " df_ens = ens_values([cOcean[1][0]-cOcean[0][0],\n", " cOcean[1][1]-cOcean[0][1],\n", " cOcean[1][2]-cOcean[0][2],],'cOcean')\n", " ax.plot(range(2015,2100),df_ens['ens_mean'],'--',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", " ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ######## NorESM\n", "# elif model_list[imodel]=='NorESM2-LM':\n", "# ### NorESM cLand\n", "# fig1=Figure1('cLand','foo')\n", "# fig1.read_NorESM_ensemble(debug=True)\n", "# df_ens = ens_values([fig1.dflist[1][0]-fig1.dflist[0][0],\n", "# fig1.dflist[1][1]-fig1.dflist[0][0],\n", "# fig1.dflist[1][2]-fig1.dflist[0][0]],'cLand')\n", "# ax.plot(range(2015,2100),df_ens['ens_mean'],'-',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", "# ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", "# ### NorESM cOcean\n", "# fig1=Figure1('fgco2','foo')\n", "# fig1.read_NorESM_ensemble(debug=True)\n", "# cOcean = []\n", "# for iexp in [0,1]:\n", "# cOcean.append([])\n", "# for ireal in range(3):\n", "# if iexp == 0:\n", "# cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", "# break\n", "# if iexp == 1:\n", "# cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", "# df_ens = ens_values([cOcean[1][0]-cOcean[0][0],\n", "# cOcean[1][1]-cOcean[0][0],\n", "# cOcean[1][2]-cOcean[0][0]],'cOcean')\n", "# ax.plot(range(2015,2100),df_ens['ens_mean'],'--',linewidth=1.5,color=color_list[imodel],label=model_list[imodel])\n", "# ax.fill_between(range(2015,2100), df_ens['ens_min'], df_ens['ens_max'] ,alpha=0.2, facecolor=color_list[imodel])\n", " ############### rest of the models\n", " else:\n", " #### other models cLand\n", " var_name, exp = 'cLand', 'OAE' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_model(model_list[imodel])\n", " for ireal in range(1):\n", " ax.plot(fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand'],'-',color=color_list[imodel],label='cLand (OAE)')\n", " ##### other models cOcean\n", " var_name, exp = 'fgco2', 'OAE' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_model(model_list[imodel])\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(1):\n", " if iexp in [0]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " if iexp in [1]:\n", " if model_list[imodel]in['UKESM1-0-LL']:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2020)) \n", " cOcean[iexp][ireal] = cOcean[iexp][ireal] + cOcean[0][ireal].loc[2019]\n", " cOcean[iexp][ireal] = pd.concat([cOcean[iexp][ireal], cOcean[0][ireal].loc[2015:2019]]).sort_values('year')\n", " else:\n", " # NorESM ocn-alk starts also from 2015\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " for ireal in range(1):\n", " ax.plot(range(2015,2100),cOcean[1][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'--',color=color_list[imodel],label='cOcean (OAE)')\n", "# ax.plot(range(2015,2100),cOcean[2][ireal]['cOcean']-cOcean[0][ireal]['cOcean'],'-',color='C'+str(imodel),label=model_list[imodel])\n", "ax.grid()\n", "ax.tick_params(labelsize=fontsize)\n", "# handles, labels = ax.get_legend_handles_labels()\n", "# ax.legend([handles[0],handles[3]],[labels[0],labels[3]],loc = 'best', fontsize=fontsize)\n", "# ax.legend(loc = 'best', fontsize=fontsize)\n", "ax.set_title('(b) $\\Delta C_{land}$ and $\\Delta C_{ocean}$ (OAE-REF)',fontsize=18)\n", "ax.set_ylabel('PgC', fontsize = 18)\n", "ax.set_ylim([-25,120])\n", "######\n", "# subplot legend for dashed and solid lines\n", "# from matplotlib.lines import Line2D\n", "# line_solid = Line2D([], [], color='black', linestyle='-', linewidth=2, label='cOcean')\n", "# line_dashed = Line2D([], [], color='black', linestyle='--', linewidth=2, label='cLand')\n", "# ax.legend(handles=[line_solid, line_dashed], loc='upper left',fontsize=fontsize)\n", "#####\n", "# from matplotlib.lines import Line2D\n", "# style_list = ['--','-']\n", "# lines = [Line2D([0], [0], color='k', linewidth=2, linestyle=style) for style in style_list]\n", "# labels = ['cLand','cOcean']\n", "# ax.legend(handles=lines, labels=labels, loc='best',fontsize=18)\n", "# ax.legend(loc='best',fontsize=18)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ACCESS-ESM1-5 feedback ratio A/R (r0): -11.7\n", "ACCESS-ESM1-5 feedback ratio A/R (r1): -12.6\n", "ACCESS-ESM1-5 feedback ratio A/R (r2): -13.1\n", "ACCESS-ESM1-5 feedback ratio A/R (r3): -20.2\n", "ACCESS-ESM1-5 feedback ratio A/R (r4): -16.3\n", "ACCESS-ESM1-5 feedback ratio A/R (r5): -15.2\n", "ACCESS-ESM1-5 feedback ratio A/R (r6): -16.6\n", "ACCESS-ESM1-5 feedback ratio A/R (r7): -10.6\n", "ACCESS-ESM1-5 feedback ratio A/R (r8): -15.4\n", "ACCESS-ESM1-5 feedback ratio A/R (r9): -18.1\n", "ACCESS-ESM1-5 feedback ratio A/R (ensmean): -15.0\n", "CESM2 feedback ratio A/R: -14.1\n", "CanESM5 feedback ratio A/R: -25.3\n", "FOCI feedback ratio A/R (r0): -18.4\n", "FOCI feedback ratio A/R (r1): -14.2\n", "FOCI feedback ratio A/R (r2): -17.1\n", "FOCI feedback ratio A/R (ensmean): -16.6\n", "MIROC-ES2L feedback ratio A/R: -13.4\n", "MPI-ESM1-2-LR feedback ratio A/R (r0): -14.6\n", "MPI-ESM1-2-LR feedback ratio A/R (r1): -14.1\n", "MPI-ESM1-2-LR feedback ratio A/R (r2): -17.2\n", "MPI-ESM feedback ratio A/R (ensmean): -15.3\n", "UKESM1-0-LL feedback ratio A/R: -14.1\n", "--- lambda_AR\n", "len(lambda) 7\n", "mean=-15.9, std=4.3\n", "--- cLand_AR\n", "len(lambda) 7\n", "mean=30.9, std=8.3\n", "--- cOcean_AR\n", "len(lambda) 7\n", "mean=-4.8, std=1.5\n" ] } ], "source": [ "'''\n", "(c) A/R feedback ratio of other models (CDRMIP)\n", "Note: OAE runs of NorESM starts from 2015!\n", "'''\n", "\n", "ax = fig.add_subplot(323)\n", "######\n", "lambda_AR_list = []\n", "d_cLand_AR_list = []\n", "d_cOcean_AR_list = []\n", "for imodel in range(len(model_list)):\n", " if model_list[imodel] in ['NorESM2-LM']:\n", " lambda_AR_list.append(0)\n", " continue\n", " if model_list[imodel]=='FOCI':\n", " var_name, exp = 'cLand', 'BOTH' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_FOCI()\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " feedback_ratio_OAE, feedback_ratio_AR = [], []\n", " for ireal in range(3):\n", " d_cLand_OAE = fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_OAE = cOcean[1][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " d_cLand_AR = fig1.dflist[2][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_AR = cOcean[2][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " # calculate feedback ratio from 2020 because d_cOcean is zero until 2020 for OAE runs\n", " feedback_ratio_OAE.append(d_cLand_OAE.loc[2020:] / d_cOcean_OAE.loc[2020:])\n", " feedback_ratio_AR.append(d_cOcean_AR.loc[2020:] / d_cLand_AR.loc[2020:])\n", " print(f'{model_list[imodel]} feedback ratio A/R (r{ireal}): {feedback_ratio_AR[-1][-60:-39].mean()*100:.1f}')\n", " if ireal == 0:\n", " d_cLand_AR_list.append(d_cLand_AR[-60:-39].mean())\n", " d_cOcean_AR_list.append(d_cOcean_AR[-60:-39].mean())\n", " feedback_ratio_OAE_FOCI, feedback_ratio_AR_FOCI = np.array(feedback_ratio_OAE) * 100., np.array(feedback_ratio_AR) * 100. # to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_AR_FOCI,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel],label='A/R') \n", " ax.fill_between(range(2025,2100),np.min(feedback_ratio_AR_FOCI,axis=0)[-75:],np.max(feedback_ratio_AR_FOCI,axis=0)[-75:],alpha=0.2, facecolor=color_list[imodel])\n", " print(f'FOCI feedback ratio A/R (ensmean): {np.average(feedback_ratio_AR_FOCI,axis=0)[-60:-39].mean():.1f}')\n", " # add the first member to list, later for calculating multi-model mean \n", " lambda_AR_list.append(feedback_ratio_AR_FOCI[0][-60:-39].mean()) \n", " ####### MPI-ESM\n", " elif model_list[imodel]=='MPI-ESM1-2-LR':\n", " fig1=Figure1('fgco2','BOTH')\n", " fig1.read_MPIESM()\n", " cOcean = []\n", " for iexp in range(4):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " if iexp in [0,2,3]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " if iexp in [1]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2020))\n", " cOcean[iexp][ireal] = cOcean[iexp][ireal] + cOcean[0][ireal].loc[2019]\n", " cOcean[iexp][ireal] = pd.concat([cOcean[iexp][ireal], cOcean[0][ireal].loc[2015:2019]]).sort_values('year')\n", " # ######\n", " feedback_ratio_OAE, feedback_ratio_AR = [], []\n", " fig1=Figure1('cLand','BOTH')\n", " fig1.read_MPIESM()\n", " for ireal in range(3):\n", " d_cLand_OAE = fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_OAE = cOcean[1][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " d_cLand_AR = fig1.dflist[3][ireal]['cLand']-fig1.dflist[2][ireal]['cLand']\n", " d_cOcean_AR = cOcean[3][ireal]['cOcean'] - cOcean[2][ireal]['cOcean']\n", " # calculate feedback ratio from 2020 because d_cOcean is zero until 2020 for OAE runs\n", " feedback_ratio_OAE.append(d_cLand_OAE.loc[2020:] / d_cOcean_OAE.loc[2020:])\n", " feedback_ratio_AR.append(d_cOcean_AR.loc[2020:] / d_cLand_AR.loc[2020:])\n", " print(f'{model_list[imodel]} feedback ratio A/R (r{ireal}): {feedback_ratio_AR[-1][-60:-39].mean()*100:.1f}')\n", " if ireal == 0:\n", " d_cLand_AR_list.append(d_cLand_AR[-60:-39].mean())\n", " d_cOcean_AR_list.append(d_cOcean_AR[-60:-39].mean())\n", " feedback_ratio_OAE_MPIESM, feedback_ratio_AR_MPIESM = np.array(feedback_ratio_OAE) * 100., np.array(feedback_ratio_AR) * 100. # to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_AR_MPIESM,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel])\n", " ax.fill_between(range(2025,2100),np.min(feedback_ratio_AR_MPIESM,axis=0)[-75:],np.max(feedback_ratio_AR_MPIESM,axis=0)[-75:],alpha=0.2, facecolor=color_list[imodel]) \n", " print(f'MPI-ESM feedback ratio A/R (ensmean): {np.average(feedback_ratio_AR_MPIESM,axis=0)[-60:-39].mean():.1f}')\n", " # add the first member to list, later for calculating multi-model mean \n", " lambda_AR_list.append(feedback_ratio_AR_MPIESM[0][-60:-39].mean()) \n", " ###### ACCESS\n", " elif model_list[imodel]=='ACCESS-ESM1-5':\n", " fig1=Figure1('fgco2','foo')\n", " fig1.read_ACCESS_ensemble(debug=True)\n", " fig1 = Figure1('fgco2','foo')\n", " fig1.read_ACCESS_ensemble(debug=True)\n", " cOcean = []\n", " for iexp in [0,1]:\n", " cOcean.append([])\n", " for ireal in range(10):\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " feedback_ratio_OAE, feedback_ratio_AR = [], []\n", " fig1=Figure1('cLand','foo')\n", " fig1.read_ACCESS_ensemble(debug=True)\n", " for ireal in range(10):\n", " d_cLand_AR = fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_AR = cOcean[1][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " feedback_ratio_AR.append(d_cOcean_AR.loc[2020:] / d_cLand_AR.loc[2020:])\n", " print(f'{model_list[imodel]} feedback ratio A/R (r{ireal}): {feedback_ratio_AR[-1][-60:-39].mean()*100:.1f}')\n", " if ireal == 0:\n", " d_cLand_AR_list.append(d_cLand_AR[-60:-39].mean())\n", " d_cOcean_AR_list.append(d_cOcean_AR[-60:-39].mean())\n", " feedback_ratio_AR_ACCESS = np.array(feedback_ratio_AR) * 100. # multiply by 100 to convert to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_AR_ACCESS,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel])\n", " ax.fill_between(range(2025,2100),np.min(feedback_ratio_AR_ACCESS,axis=0)[-75:],\n", " np.max(feedback_ratio_AR_ACCESS,axis=0)[-75:],alpha=0.2, facecolor=color_list[imodel])\n", " print(f'{model_list[imodel]} feedback ratio A/R (ensmean): {np.average(feedback_ratio_AR_ACCESS,axis=0)[-60:-39].mean():.1f}')\n", " # add the first member to list, later for calculating multi-model mean \n", " lambda_AR_list.append(feedback_ratio_AR_ACCESS[0][-60:-39].mean()) \n", " ##################### \n", " else:\n", " fig1=Figure1('fgco2','AFF')\n", " fig1.read_model(model_list[imodel])\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(1):\n", " if iexp==1:\n", " cOcean[iexp].append([])\n", " else:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", "\n", " # ######\n", " feedback_ratio_OAE, feedback_ratio_AR = [], []\n", " fig1=Figure1('cLand','AFF')\n", " fig1.read_model(model_list[imodel])\n", " for ireal in range(1):\n", " d_cLand_AR = fig1.dflist[2][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_AR = cOcean[2][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " # calculate feedback ratio from 2020 because d_cOcean is zero until 2020 for OAE runs\n", " feedback_ratio_AR.append(d_cOcean_AR.loc[2020:] / d_cLand_AR.loc[2020:])\n", " if ireal == 0:\n", " d_cLand_AR_list.append(d_cLand_AR[-60:-39].mean())\n", " d_cOcean_AR_list.append(d_cOcean_AR[-60:-39].mean())\n", " feedback_ratio_AR = np.array(feedback_ratio_AR) * 100. # multyply by 100 to convert from unitless to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_AR,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel])\n", " print(f'{model_list[imodel]} feedback ratio A/R: {np.average(feedback_ratio_AR,axis=0)[-60:-39].mean():.1f}')\n", " lambda_AR_list.append(np.average(feedback_ratio_AR,axis=0)[-60:-39].mean())\n", "ax.grid()\n", "ax.set_ylabel('%', fontsize = 18)\n", "ax.set_xticks([2025, 2040, 2060, 2080, 2100])\n", "ax.set_xticklabels([2025, 2040, 2060, 2080, 2100])\n", "ax.tick_params(labelsize=fontsize)\n", "ax.set_title('(c) Carbon cycle feedback ratio $\\lambda_{A/R}$',fontsize=18)\n", "ax.set_ylim(feedback_ratio_limit)\n", "####\n", "foo = []\n", "for bar in lambda_AR_list:\n", " if bar != 0:\n", " foo.append(bar)\n", "print('--- lambda_AR')\n", "print(f'len(lambda) {len(foo)}')\n", "print(f'mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "####\n", "foo = []\n", "for bar in d_cLand_AR_list:\n", " if bar != 0:\n", " foo.append(bar)\n", "print('--- cLand_AR')\n", "print(f'len(lambda) {len(foo)}')\n", "print(f'mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "####\n", "foo = []\n", "for bar in d_cOcean_AR_list:\n", " if bar != 0:\n", " foo.append(bar)\n", "print('--- cOcean_AR')\n", "print(f'len(lambda) {len(foo)}')\n", "print(f'mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "FOCI feedback ratio OAE (r0): -21.0\n", "FOCI feedback ratio OAE (r1): -11.5\n", "FOCI feedback ratio OAE (r2): -15.1\n", "FOCI feedback ratio OAE (ensmean): -15.9\n", "MPI-ESM1-2-LR feedback ratio OAE (r0): -4.0\n", "MPI-ESM1-2-LR feedback ratio OAE (r1): -16.6\n", "MPI-ESM1-2-LR feedback ratio OAE (r2): -7.5\n", "MPI-ESM feedback ratio OAE (ensmean): -9.4\n", "NorESM2-LM feedback ratio OAE: -14.8\n", "UKESM1-0-LL feedback ratio OAE: -12.1\n", "--- lambda_OAE\n", "len(lambda) 4\n", "mean=-13.0, std=2.5\n", "--- d_cLand_OAE\n", "len(lambda) 4\n", "mean=-4.7, std=2.0\n", "--- d_cOcean_OAE\n", "len(lambda) 4\n", "mean=34.8, std=0.6\n" ] } ], "source": [ "'''\n", "(d) OAE feedback ratio of all models (CDRMIP)\n", "OAE runs of UKESM starts from 2020!\n", "'''\n", "ax = fig.add_subplot(324)\n", "######\n", "lambda_OAE_list = []\n", "d_cLand_OAE_list = []\n", "d_cOcean_OAE_list = []\n", "for imodel in range(len(model_list)):\n", " if model_list[imodel] in ['ACCESS-ESM1-5', 'CESM2', 'CanESM5', 'MIROC-ES2L']:\n", " lambda_OAE_list.append(0)\n", " continue\n", " if model_list[imodel]=='FOCI':\n", " var_name, exp = 'cLand', 'BOTH' \n", " fig1=Figure1(var_name,exp)\n", " fig1.read_FOCI()\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " feedback_ratio_OAE = []\n", " for ireal in range(3):\n", " d_cLand_OAE = fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_OAE = cOcean[1][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " d_cLand_AR = fig1.dflist[2][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_AR = cOcean[2][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " # calculate feedback ratio from 2020 because d_cOcean is zero until 2020 for OAE runs\n", " feedback_ratio_OAE.append(d_cLand_OAE.loc[2020:] / d_cOcean_OAE.loc[2020:])\n", " print(f'{model_list[imodel]} feedback ratio OAE (r{ireal}): {feedback_ratio_OAE[-1][-60:-39].mean()*100:.1f}')\n", " if ireal == 0:\n", " d_cLand_OAE_list.append(d_cLand_OAE[-60:-39].mean())\n", " d_cOcean_OAE_list.append(d_cOcean_OAE[-60:-39].mean())\n", " feedback_ratio_OAE_FOCI = np.array(feedback_ratio_OAE) * 100. # to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_OAE_FOCI,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel],label='OAE')\n", " ax.fill_between(range(2025,2100),np.min(feedback_ratio_OAE_FOCI,axis=0)[-75:],np.max(feedback_ratio_OAE_FOCI,axis=0)[-75:],alpha=0.2, facecolor=color_list[imodel])\n", " print(f'FOCI feedback ratio OAE (ensmean): {np.average(feedback_ratio_OAE_FOCI,axis=0)[-60:-39].mean():.1f}')\n", " lambda_OAE_list.append(np.average(feedback_ratio_OAE_FOCI,axis=0)[-60:-39].mean())\n", " elif model_list[imodel]=='MPI-ESM1-2-LR':\n", " \n", " fig1=Figure1('fgco2','BOTH')\n", " fig1.read_MPIESM()\n", " cOcean = []\n", " for iexp in range(4):\n", " cOcean.append([])\n", " for ireal in range(3):\n", " if iexp in [0,2,3]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " if iexp in [1]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2020))\n", " cOcean[iexp][ireal] = cOcean[iexp][ireal] + cOcean[0][ireal].loc[2019]\n", " cOcean[iexp][ireal] = pd.concat([cOcean[iexp][ireal], cOcean[0][ireal].loc[2015:2019]]).sort_values('year')\n", " # ######\n", " feedback_ratio_OAE = []\n", " fig1=Figure1('cLand','BOTH')\n", " fig1.read_MPIESM()\n", " for ireal in range(3):\n", " d_cLand_OAE = fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_OAE = cOcean[1][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " d_cLand_AR = fig1.dflist[3][ireal]['cLand']-fig1.dflist[2][ireal]['cLand']\n", " d_cOcean_AR = cOcean[3][ireal]['cOcean'] - cOcean[2][ireal]['cOcean']\n", " # calculate feedback ratio from 2020 becaused_cOcean is zero until 2020 for OAE runs\n", " feedback_ratio_OAE.append(d_cLand_OAE.loc[2020:] / d_cOcean_OAE.loc[2020:])\n", " print(f'{model_list[imodel]} feedback ratio OAE (r{ireal}): {feedback_ratio_OAE[-1][-60:-39].mean()*100:.1f}')\n", " if ireal == 0:\n", " d_cLand_OAE_list.append(d_cLand_OAE[-60:-39].mean())\n", " d_cOcean_OAE_list.append(d_cOcean_OAE[-60:-39].mean())\n", " feedback_ratio_OAE_MPIESM = np.array(feedback_ratio_OAE) * 100. # to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_OAE_MPIESM,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel],label='OAE')\n", " ax.fill_between(range(2025,2100),np.min(feedback_ratio_OAE_MPIESM,axis=0)[-75:],np.max(feedback_ratio_OAE_MPIESM,axis=0)[-75:],\n", " alpha=0.2,facecolor=color_list[imodel])\n", " print(f'MPI-ESM feedback ratio OAE (ensmean): {np.average(feedback_ratio_OAE_MPIESM,axis=0)[-60:-39].mean():.1f}')\n", " lambda_OAE_list.append(np.average(feedback_ratio_OAE_MPIESM,axis=0)[-60:-39].mean())\n", " else:\n", " fig1=Figure1('fgco2','OAE')\n", " fig1.read_model(model_list[imodel])\n", " cOcean = []\n", " for iexp in range(3):\n", " cOcean.append([])\n", " for ireal in range(1):\n", " if iexp in [0]:\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " if iexp in [1]:\n", " if model_list[imodel]=='UKESM1-0-LL':\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2020))\n", " cOcean[iexp][ireal] = cOcean[iexp][ireal] + cOcean[0][ireal].loc[2019]\n", " cOcean[iexp][ireal] = pd.concat([cOcean[iexp][ireal], cOcean[0][ireal].loc[2015:2019]]).sort_values('year')\n", " elif model_list[imodel]=='NorESM2-LM':\n", " cOcean[iexp].append(cOcean_from_fgco2(fig1.dflist[iexp][ireal],2015))\n", " feedback_ratio_OAE = []\n", " fig1=Figure1('cLand','OAE')\n", " fig1.read_model(model_list[imodel])\n", " for ireal in range(1):\n", " d_cLand_OAE = fig1.dflist[1][ireal]['cLand']-fig1.dflist[0][ireal]['cLand']\n", " d_cOcean_OAE = cOcean[1][ireal]['cOcean'] - cOcean[0][ireal]['cOcean']\n", " # calculate feedback ratio from 2020 because d_cOcean is zero until 2020 for OAE runs\n", " feedback_ratio_OAE.append(d_cLand_OAE.loc[2020:] / d_cOcean_OAE.loc[2020:])\n", " ax.plot(feedback_ratio_OAE[-1][-75:]*100.,'--',linewidth=1,color=color_list[imodel])\n", " if ireal == 0:\n", " d_cLand_OAE_list.append(d_cLand_OAE[-60:-39].mean())\n", " d_cOcean_OAE_list.append(d_cOcean_OAE[-60:-39].mean())\n", " feedback_ratio_OAE = np.array(feedback_ratio_OAE) * 100. # to percentage\n", " ax.plot(range(2025,2100),np.average(feedback_ratio_OAE,axis=0)[-75:],'-',linewidth=1.5,color=color_list[imodel],label='OAE')\n", " print(f'{model_list[imodel]} feedback ratio OAE: {np.average(feedback_ratio_OAE,axis=0)[-60:-39].mean():.1f}')\n", " lambda_OAE_list.append(np.average(feedback_ratio_OAE,axis=0)[-60:-39].mean())\n", "ax.grid()\n", "ax.set_ylabel('%', fontsize = 18)\n", "ax.set_xticks([2025, 2040, 2060, 2080, 2100])\n", "ax.set_xticklabels([2025, 2040, 2060, 2080, 2100])\n", "ax.tick_params(labelsize=fontsize)\n", "ax.set_title('(d) Carbon cycle feedback ratio $\\lambda_{OAE}$',fontsize=18)\n", "ax.set_ylim(feedback_ratio_limit)\n", "#######\n", "foo = []\n", "for bar in lambda_OAE_list:\n", " if bar != 0:\n", " foo.append(bar)\n", "print('--- lambda_OAE')\n", "print(f'len(lambda) {len(foo)}')\n", "print(f'mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "#######\n", "foo = []\n", "for bar in d_cLand_OAE_list:\n", " if bar != 0:\n", " foo.append(bar)\n", "print('--- d_cLand_OAE')\n", "print(f'len(lambda) {len(foo)}')\n", "print(f'mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "#######\n", "foo = []\n", "for bar in d_cOcean_OAE_list:\n", " if bar != 0:\n", " foo.append(bar)\n", "print('--- d_cOcean_OAE')\n", "print(f'len(lambda) {len(foo)}')\n", "print(f'mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "'''\n", "(e) comparing feedback ratios\n", "'''\n", "ax = fig.add_subplot(325)\n", "# incorporate Table 1\n", "lambda_AR_theo_4x = [-26.616185834154027,-23.18052744372935,-23.69298287390421,0,-22.960520775578384,-23.90033909512007,-24.774695226066793,-23.393045143429678]\n", "lambda_OAE_theo_4x = [-10.711631662793994,-26.41489574976597,-39.7253330168976,0,-27.77288378785428,-24.347405962452434,-26.458134978422375,-18.218499852339725]\n", "lambda_AR_theo_2x = [-31.398857138214954,-27.523245379577126,-28.019632577033065,0,-27.228266479860828,-27.54672380778056,-28.158522530527147,-27.73055504767143]\n", "lambda_OAE_theo_2x = [-23.70798183629439,-29.27959261492038,-39.05293882765925,0,-34.4091966240245,-33.602443435192164,-28.83460691820848,-27.049385610535193]\n", "# lambda_AR = [-11.7,-14.1,-25.3,-16.6,-13.4,-15.3,0,-14.1]\n", "# lambda_OAE = [0,0,0,-15.9,0,-9.4,-14.8,-12.1]\n", "msize = 8\n", "for imodel in range(8):\n", " if lambda_AR_theo_4x[imodel]!=0:\n", " ax.plot(lambda_AR_theo_4x[imodel],1,'o',markersize=msize,color=color_list[imodel])\n", " if lambda_OAE_theo_4x[imodel]!=0:\n", " ax.plot(lambda_OAE_theo_4x[imodel],2,'o',markersize=msize,color=color_list[imodel])\n", " if lambda_AR_theo_2x[imodel]!=0:\n", " ax.plot(lambda_AR_theo_2x[imodel],1,'o',markersize=msize,color=color_list[imodel],fillstyle='top')\n", " if lambda_OAE_theo_2x[imodel]!=0:\n", " ax.plot(lambda_OAE_theo_2x[imodel],2,'o',markersize=msize,color=color_list[imodel],fillstyle='top')\n", " if lambda_AR_list[imodel]!=0:\n", " if model_list[imodel]=='MPI-ESM1-2-LR':\n", " asymmetric_error = [[np.average(feedback_ratio_AR_MPIESM,axis=0)[-60:-39].mean()-np.average(feedback_ratio_AR_MPIESM,axis=0)[-60:-39].min()],\n", " [np.average(feedback_ratio_AR_MPIESM,axis=0)[-60:-39].max()-np.average(feedback_ratio_AR_MPIESM,axis=0)[-60:-39].mean()]]\n", " ax.errorbar(lambda_AR_list[imodel], 3.1, xerr=asymmetric_error, fmt='o',\n", " ecolor=color_list[imodel],markerfacecolor=color_list[imodel],\n", " markeredgecolor=color_list[imodel],\n", " markersize=msize)\n", " elif model_list[imodel]=='FOCI':\n", " asymmetric_error = [[np.average(feedback_ratio_AR_FOCI,axis=0)[-60:-39].mean()-np.average(feedback_ratio_AR_FOCI,axis=0)[-60:-39].min()],\n", " [np.average(feedback_ratio_AR_FOCI,axis=0)[-60:-39].max()-np.average(feedback_ratio_AR_FOCI,axis=0)[-60:-39].mean()]]\n", " ax.errorbar(lambda_AR_list[imodel], 2.9, xerr=asymmetric_error, fmt='o',\n", " ecolor=color_list[imodel],markerfacecolor=color_list[imodel],\n", " markeredgecolor=color_list[imodel],\n", " markersize=msize)\n", " elif model_list[imodel]=='ACCESS-ESM1-5':\n", " asymmetric_error = [[np.average(feedback_ratio_AR_ACCESS,axis=0)[-60:-39].mean()-np.average(feedback_ratio_AR_ACCESS,axis=0)[-60:-39].min()],\n", " [np.average(feedback_ratio_AR_ACCESS,axis=0)[-60:-39].max()-np.average(feedback_ratio_AR_ACCESS,axis=0)[-60:-39].mean()]]\n", " ax.errorbar(lambda_AR_list[imodel], 3.2, xerr=asymmetric_error, fmt='o',\n", " ecolor=color_list[imodel],markerfacecolor=color_list[imodel],\n", " markeredgecolor=color_list[imodel],\n", " markersize=msize)\n", " else:\n", " ax.plot(lambda_AR_list[imodel],3,'o',markersize=msize,color=color_list[imodel])\n", " if lambda_OAE_list[imodel]!=0:\n", " if model_list[imodel]=='MPI-ESM1-2-LR':\n", " asymmetric_error = [[np.average(feedback_ratio_OAE_MPIESM,axis=0)[-60:-39].mean()-np.average(feedback_ratio_OAE_MPIESM,axis=0)[-60:-39].min()],\n", " [np.average(feedback_ratio_OAE_MPIESM,axis=0)[-60:-39].max()-np.average(feedback_ratio_OAE_MPIESM,axis=0)[-60:-39].mean()]]\n", " ax.errorbar(lambda_OAE_list[imodel], 4.1, xerr=asymmetric_error, fmt='o',\n", " ecolor=color_list[imodel],markerfacecolor=color_list[imodel],\n", " markeredgecolor=color_list[imodel],\n", " markersize=msize)\n", " elif model_list[imodel]=='FOCI':\n", " asymmetric_error = [[np.average(feedback_ratio_OAE_FOCI,axis=0)[-60:-39].mean()-np.average(feedback_ratio_OAE_FOCI,axis=0)[-60:-39].min()],\n", " [np.average(feedback_ratio_OAE_FOCI,axis=0)[-60:-39].max()-np.average(feedback_ratio_OAE_FOCI,axis=0)[-60:-39].mean()]]\n", " ax.errorbar(lambda_OAE_list[imodel], 3.9, xerr=asymmetric_error, fmt='o',\n", " ecolor=color_list[imodel],markerfacecolor=color_list[imodel],\n", " markeredgecolor=color_list[imodel],\n", " markersize=msize)\n", " else:\n", " ax.plot(lambda_OAE_list[imodel],4,'o',markersize=msize,color=color_list[imodel])\n", "ax.hlines(y=[1.5,2.5,3.5],xmin=-40,xmax=0,linewidth=1,linestyles='--',color='k')\n", "ax.set_title('(e) Comparison of carbon cycle feedback ratios',fontsize=18)\n", "ax.set_xlabel('%', fontsize = 18)\n", "ax.grid(visible=True,axis='x')\n", "ax.tick_params(labelsize=fontsize)\n", "ax.set_ylim([0.5,4.5])\n", "ax.set_xlim([-40,0])\n", "ax.set_yticks([1,2,3,4])\n", "# ax.set_yticklabels([r'$\\lambda^{theo}_{A/R}',r'\\lambda_{A/R}$'])\n", "ax.set_yticklabels(['','','',''])\n", "ann = ax.annotate('$\\lambda_{A/R}^{theo}$',xy=(-44,1),fontsize=18,ha='left',annotation_clip=False)\n", "ann2 = ax.annotate('$\\lambda_{OAE}^{theo}$',xy=(-44,2),fontsize=18,ha='left',annotation_clip=False)\n", "ann2 = ax.annotate('$\\lambda_{A/R}$',xy=(-44,3),fontsize=18,ha='left',annotation_clip=False)\n", "ann2 = ax.annotate('$\\lambda_{OAE}$',xy=(-44,4),fontsize=18,ha='left',annotation_clip=False)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "lambda_AR_theo_4x mean=-24.1, std=1.2\n", "lambda_OAE_theo_4x mean=-24.8, std=8.3\n", "lambda_AR_theo_2x mean=-28.2, std=1.3\n", "lambda_OAE_theo_2x mean=-30.8, std=4.8\n" ] } ], "source": [ "foo = []\n", "for bar in lambda_AR_theo_4x:\n", " if bar != 0:\n", " foo.append(bar)\n", "print(f'lambda_AR_theo_4x mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "###############\n", "foo = []\n", "for bar in lambda_OAE_theo_4x:\n", " if bar != 0:\n", " foo.append(bar)\n", "print(f'lambda_OAE_theo_4x mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "foo = []\n", "for bar in lambda_AR_theo_2x:\n", " if bar != 0:\n", " foo.append(bar)\n", "print(f'lambda_AR_theo_2x mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "foo = []\n", "for bar in lambda_OAE_theo_2x:\n", " if bar != 0:\n", " foo.append(bar)\n", "print(f'lambda_OAE_theo_2x mean={np.array(foo).mean():.1f}, std={np.array(foo).std():.1f}')\n", "#####" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# fig.legend(handles=handles, loc='outside lower center',fontsize=fontsize,ncol=4)\n", "fig.legend(handles=handles, loc='outside lower center',fontsize=fontsize,ncol=4,bbox_to_anchor=(0.5, -0.12))\n", "# fig.tight_layout()\n", "# fig.subplots_adjust(right=0.78)\n", "fig" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "co2sys", "language": "python", "name": "co2sys" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 4 }