{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 3 NPGO Paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import netCDF4 as nc\n",
    "import matplotlib.pyplot as plt\n",
    "from salishsea_tools import bio_tools as bt, places\n",
    "import xarray as xr\n",
    "import os\n",
    "import glob\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SST -- data are from CentralSoG_SST_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_SST=[ 6.41475627,  6.48755541,  7.4785702 ,  9.25347408, 12.63790333,\n",
    "       15.98057834, 18.54948443, 19.06939349, 15.93989528, 12.02364599,\n",
    "        9.0698088 ,  6.8426298 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_SST_SEM=[0.21721438, 0.33888804, 0.33143871, 0.15566903, 0.06565611,\n",
    "       0.28891357, 0.22434856, 0.30571173, 0.24001654, 0.23185627,\n",
    "       0.14982848, 0.25240781]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_SST=[ 6.54155677,  6.32416194,  7.75323583, 10.39172893, 14.8838251 ,\n",
    "       17.22590977, 19.5343776 , 19.48116382, 16.07562534, 12.52031955,\n",
    "        9.00751125,  7.22206359]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_SST_SEM=[0.10085818, 0.4890846 , 0.37887922, 0.15664109, 0.40595597,\n",
    "       0.20241134, 0.40119105, 0.67801848, 0.50271186, 0.33871933,\n",
    "       0.18173575, 0.33064517]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_SST=[ 9.78365537, 10.22426138,  9.4735278 ,  9.67848561]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_SST=[11.72465165, 11.13348375, 10.47916834, 10.70108273]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_SST=[17.50388524, 17.87908419, 18.36135449, 17.72161776]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_SST=[17.94220457, 19.22289418, 19.45471819, 18.36878465]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Salinity -- data are from CentralSoG_SSS_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Sal= [25.50095144, 24.93931884, 25.66983048, 24.71296806, 18.50090254,\n",
    "       13.74989501, 15.83386163, 18.77032177, 22.11775614, 23.80291518,\n",
    "       23.92629601, 24.63696603]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Sal_SEM=[0.25090128, 0.34827499, 0.22707056, 0.53063788, 1.29902834,\n",
    "       1.59029185, 2.24347327, 0.97587449, 0.3152079 , 0.52615727,\n",
    "       0.41454268, 0.26008036]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Sal=[24.16407734, 24.02108627, 23.46290609, 21.96345317, 15.89424179,\n",
    "       14.72397722, 16.48597299, 19.74857647, 22.7618917 , 23.66667069,\n",
    "       22.93491948, 23.81730112]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Sal_SEM=[0.8826463 , 0.99281972, 0.94991001, 0.90580449, 1.61168061,\n",
    "       1.24163564, 1.76138473, 1.28528857, 0.81950455, 0.49974175,\n",
    "       0.69538148, 1.10459364]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_Sal=[23.34870235, 23.97076454, 21.99257067, 22.53289721]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_Sal=[18.47972066, 20.29101052, 22.52859016, 20.46148007]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_Sal=[18.59444785, 18.55219596, 14.78432114, 12.54113959]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_Sal=[20.58331684, 16.97778168, 16.03245907, 14.35114464]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Halocline Strength -- data are from CentralSoG_Halocline_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Halo= [0.36154052, 0.49809309, 0.35279773, 0.59444239, 2.17599837,\n",
    "       2.83692228, 2.06920697, 1.88577881, 1.31863951, 0.84843678,\n",
    "       0.58477922, 0.50166281]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Halo_SEM=[0.0425931 , 0.06372294, 0.0536515 , 0.10031701, 0.37381109,\n",
    "       0.46136078, 0.39131849, 0.18637298, 0.09991184, 0.06102145,\n",
    "       0.08902362, 0.0766228]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Halo=[0.60806095, 0.64845463, 0.75646377, 1.24462616, 2.71714942,\n",
    "       2.62485502, 2.29233551, 1.82686781, 1.266163  , 0.91992592,\n",
    "       1.10688201, 0.64399621]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Halo_SEM=[0.10139684, 0.21724346, 0.11031644, 0.11941914, 0.33992397,\n",
    "       0.31827148, 0.46300932, 0.33271079, 0.15843871, 0.11012063,\n",
    "       0.17339882, 0.12728148]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_Halo=[1.02274943, 0.78320406, 1.33834988, 1.02001461]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_Halo=[1.787881  , 1.68205798, 1.24675077, 1.57429606]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_Halo=[1.76022024, 1.88017547, 2.33848005, 3.07700164]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_Halo=[1.3562591 , 2.24361753, 2.58961049, 2.80259067]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### PAR -- data are from CentralSoG_SurfacePAR_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_PAR= [12.04400661, 23.23528714, 36.51879487, 54.5113959 , 76.02100952,\n",
    "       87.81722026, 99.97068933, 86.76086059, 61.21366767, 31.11335206,\n",
    "       15.38539501, 10.86040996]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_PAR_SEM=[0.98927229, 0.80121518, 2.21281148, 2.65062751, 4.36595316,\n",
    "       6.5682177 , 3.54313251, 2.28383506, 2.1619708 , 1.18555839,\n",
    "       0.89343873, 1.10119006]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_PAR=[12.32470128, 26.11127048, 45.67482302, 63.15013291, 91.98044567,\n",
    "       93.73015807, 98.88877244, 82.78904517, 55.05779156, 33.1923411 ,\n",
    "       18.17157652,  9.76882253]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_PAR_SEM=[1.47123463, 0.57532029, 3.05257932, 2.50705727, 4.39118173,\n",
    "       5.75917672, 2.30639185, 2.69061531, 2.1721261 , 0.98056129,\n",
    "       1.51775549, 0.60773262]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_PAR=[61.90657111, 52.45042499, 52.51039674, 55.86754087]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_PAR=[66.25929667, 68.03363515, 68.91267142, 64.53493222]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_PAR=[91.57734924, 97.41059098, 94.13498441, 82.94210228]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_PAR=[94.68697684, 93.73494871, 92.82362585, 85.96508285]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wind -- data are from HRDPSWinds_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Wind= [5.503117561340332, 5.190681457519531, 5.546851634979248, 4.699765205383301, 4.319005012512207, 4.160552978515625, 4.251698970794678, 4.14553689956665, 4.074483394622803, 4.822423458099365, 5.530994415283203, 5.60904598236084]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Wind_SEM=[0.2716546654701233, 0.3555466830730438, 0.3046501874923706, 0.3556775450706482, 0.13578826189041138, 0.07550367712974548, 0.2988617420196533, 0.17373867332935333, 0.12545664608478546, 0.018483856692910194, 0.17944231629371643, 0.45889315009117126]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Wind=[5.133814334869385, 4.842380046844482, 3.766061544418335, 4.423320770263672, 3.550428867340088, 4.039124488830566, 3.807666540145874, 3.829700469970703, 4.08309268951416, 4.191368103027344, 4.611095428466797, 5.599612236022949]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Wind_SEM=[0.6975691318511963, 0.7239692807197571, 0.24488499760627747, 0.2416556030511856, 0.17904892563819885, 0.24562996625900269, 0.24054600298404694, 0.2916531264781952, 0.2151043862104416, 0.1926278918981552, 0.35777175426483154, 0.44312936067581177]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_Wind=[5.546851634979248, 4.699765205383301, 4.319005012512207]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_Wind=[3.766061544418335, 4.423320770263672, 3.550428867340088]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_Wind=[4.160552978515625, 4.251698970794678, 4.14553689956665]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_Wind=[4.039124488830566, 3.807666540145874, 3.829700469970703]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fraser River Flow -- data are from FraserRiverFlow_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_FR= [991.5 ,  983.25,  979.  , 1024.  , 1077.  , 1012.5 ,  979.5 ,\n",
    "        977.  ,  985.75, 1018.5 , 1066.25, 1114.  , 1071.  , 1102.5 ,\n",
    "       1125.  , 1145.  , 1126.25, 1029.25,  952.  ,  929.5 ,  914.  ,\n",
    "        883.  ,  883.  ,  899.75,  910.75,  913.5 ,  920.75,  928.5 ,\n",
    "        941.  ,  922.  ,  901.75,  895.5 ,  910.5 ,  914.  ,  945.  ,\n",
    "        966.  ,  960.75,  956.25,  934.75,  920.5 ,  910.5 ,  900.25,\n",
    "        907.5 ,  925.25,  937.75,  935.25,  912.  ,  905.  ,  894.75,\n",
    "        877.75,  857.25,  847.25,  864.75,  848.75,  850.  ,  840.75,\n",
    "        814.5 ,  810.5 ,  824.  ,  816.5 ,  836.75,  835.5 ,  832.5 ,\n",
    "        851.75,  874.25,  865.5 ,  859.5 ,  859.25,  865.  ,  878.25,\n",
    "        896.25,  900.75,  894.75,  888.5 ,  905.75,  924.25,  911.5 ,\n",
    "        919.25,  921.  ,  916.75,  920.  ,  916.  ,  917.25,  925.  ,\n",
    "        928.75,  944.75,  974.5 , 1024.5 , 1056.25, 1132.5 , 1159.5 ,\n",
    "       1154.75, 1111.  , 1119.75, 1106.25, 1104.25, 1081.  , 1099.  ,\n",
    "       1100.25, 1109.  , 1139.75, 1162.25, 1187.5 , 1231.5 , 1275.75,\n",
    "       1397.5 , 1497.5 , 1610.  , 1672.5 , 1777.5 , 1895.  , 2002.5 ,\n",
    "       2102.5 , 2212.5 , 2307.5 , 2387.5 , 2452.5 , 2557.5 , 2697.5 ,\n",
    "       2952.5 , 3150.  , 3280.  , 3315.  , 3355.  , 3460.  , 3520.  ,\n",
    "       3560.  , 3607.5 , 3632.5 , 3687.5 , 3752.5 , 3850.  , 3960.  ,\n",
    "       4250.  , 4480.  , 4645.  , 4842.5 , 5117.5 , 5562.5 , 6075.  ,\n",
    "       6472.5 , 6757.5 , 6907.5 , 7037.5 , 7170.  , 7245.  , 7260.  ,\n",
    "       7285.  , 7352.5 , 7442.5 , 7487.5 , 7552.5 , 7667.5 , 7755.  ,\n",
    "       7580.  , 7530.  , 7627.5 , 7705.  , 7670.  , 7670.  , 7795.  ,\n",
    "       8002.5 , 7987.5 , 7855.  , 7740.  , 7587.5 , 7560.  , 7695.  ,\n",
    "       7895.  , 7742.5 , 7637.5 , 7717.5 , 7985.  , 8127.5 , 8080.  ,\n",
    "       7945.  , 7850.  , 7952.5 , 7982.5 , 7932.5 , 7785.  , 7562.5 ,\n",
    "       7507.5 , 7575.  , 7562.5 , 7422.5 , 7297.5 , 7267.5 , 7200.  ,\n",
    "       7102.5 , 6985.  , 7025.  , 7115.  , 7112.5 , 6925.  , 6660.  ,\n",
    "       6432.5 , 6280.  , 6225.  , 6100.  , 5907.5 , 5745.  , 5642.5 ,\n",
    "       5542.5 , 5542.5 , 5515.  , 5402.5 , 5242.5 , 5092.5 , 4947.5 ,\n",
    "       4827.5 , 4712.5 , 4635.  , 4597.5 , 4552.5 , 4500.  , 4417.5 ,\n",
    "       4245.  , 4062.5 , 3952.5 , 3872.5 , 3825.  , 3777.5 , 3690.  ,\n",
    "       3622.5 , 3547.5 , 3537.5 , 3492.5 , 3360.  , 3265.  , 3227.5 ,\n",
    "       3177.5 , 3152.5 , 3130.  , 3100.  , 3105.  , 3190.  , 3277.5 ,\n",
    "       3210.  , 3050.  , 2947.5 , 2882.5 , 2770.  , 2730.  , 2712.5 ,\n",
    "       2715.  , 2657.5 , 2577.5 , 2522.5 , 2457.5 , 2382.5 , 2360.  ,\n",
    "       2320.  , 2235.  , 2137.5 , 2085.  , 2032.5 , 1995.  , 1982.5 ,\n",
    "       1995.  , 1957.5 , 1952.5 , 1957.5 , 1917.5 , 1850.  , 1787.5 ,\n",
    "       1780.  , 1770.  , 1917.5 , 2197.5 , 2210.  , 2202.5 , 2175.  ,\n",
    "       2175.  , 2170.  , 2127.5 , 2045.  , 2065.  , 1970.  , 1967.5 ,\n",
    "       1890.  , 1822.5 , 1817.5 , 1802.5 , 1792.5 , 1717.5 , 1660.  ,\n",
    "       1655.  , 1737.5 , 1730.  , 1750.  , 1750.  , 1825.  , 1777.5 ,\n",
    "       1730.  , 1782.5 , 1815.  , 1795.  , 1750.  , 1707.5 , 1680.  ,\n",
    "       1657.5 , 1677.5 , 1695.  , 1682.5 , 1662.5 , 1587.5 , 1567.5 ,\n",
    "       1597.5 , 1640.  , 1612.5 , 1625.  , 1630.  , 1630.  , 1627.5 ,\n",
    "       1582.5 , 1647.5 , 1720.  , 1670.  , 1655.  , 1652.5 , 1642.5 ,\n",
    "       1637.5 , 1580.  , 1502.5 , 1415.  , 1350.  , 1285.  , 1245.  ,\n",
    "       1232.5 , 1382.5 , 1364.5 , 1335.  , 1315.  , 1320.  , 1357.5 ,\n",
    "       1337.5 , 1310.  , 1272.5 , 1247.5 , 1205.  , 1181.  , 1165.  ,\n",
    "       1160.  , 1170.  , 1222.5 , 1242.5 , 1192.5 , 1177.5 , 1122.5 ,\n",
    "       1047.5 , 1004.75,  976.5 ,  943.5 ,  922.5 ,  920.25,  939.75,\n",
    "        994.5 ,  969.75,  955.75,  954.  ,  995.75, 1014.75,  989.25,\n",
    "        982.75]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_FR_Index=[ 1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
    "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,\n",
    "        27,  28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,\n",
    "        40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,\n",
    "        53,  54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,  65,\n",
    "        66,  67,  68,  69,  70,  71,  72,  73,  74,  75,  76,  77,  78,\n",
    "        79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,  90,  91,\n",
    "        92,  93,  94,  95,  96,  97,  98,  99, 100, 101, 102, 103, 104,\n",
    "       105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117,\n",
    "       118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130,\n",
    "       131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143,\n",
    "       144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156,\n",
    "       157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169,\n",
    "       170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182,\n",
    "       183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,\n",
    "       196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208,\n",
    "       209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221,\n",
    "       222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234,\n",
    "       235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247,\n",
    "       248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260,\n",
    "       261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,\n",
    "       274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286,\n",
    "       287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299,\n",
    "       300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312,\n",
    "       313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325,\n",
    "       326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338,\n",
    "       339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351,\n",
    "       352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364,\n",
    "       365]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "#NPGO_C_FR_SEM=[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_FR=[1060.  , 1038.  , 1075.75, 1198.  , 1151.25, 1149.  , 1139.75,\n",
    "       1166.75, 1140.  , 1137.5 , 1135.  , 1116.5 , 1089.25, 1015.5 ,\n",
    "        988.25, 1001.25,  969.25, 1027.75, 1049.25, 1021.25, 1051.75,\n",
    "       1068.  , 1085.25, 1197.25, 1218.25, 1183.75, 1166.25, 1184.25,\n",
    "       1221.5 , 1288.25, 1318.75, 1714.  , 1476.25, 1362.25, 1263.25,\n",
    "       1195.75, 1314.5 , 1371.75, 1309.5 , 1213.5 , 1171.75, 1136.5 ,\n",
    "       1105.  , 1114.25, 1154.75, 1171.75, 1194.25, 1209.5 , 1225.25,\n",
    "       1215.  , 1191.  , 1161.5 , 1141.5 , 1127.75, 1119.  , 1105.25,\n",
    "       1074.75, 1055.5 , 1041.25, 1030.75, 1018.25,  995.5 ,  976.  ,\n",
    "        947.5 ,  942.  ,  940.  ,  941.  ,  944.  ,  936.25,  929.75,\n",
    "        956.  ,  984.  , 1073.  , 1151.5 , 1215.25, 1284.  , 1332.75,\n",
    "       1340.75, 1315.75, 1330.25, 1339.  , 1393.25, 1433.  , 1431.75,\n",
    "       1448.75, 1462.75, 1562.75, 1683.5 , 1964.  , 2157.  , 2218.  ,\n",
    "       2250.  , 2281.  , 2223.75, 2142.  , 2092.5 , 2069.75, 2058.5 ,\n",
    "       2046.5 , 2052.75, 2099.25, 2095.  , 2092.5 , 2112.5 , 2092.5 ,\n",
    "       2052.5 , 2085.  , 2095.  , 2247.5 , 2387.5 , 2582.5 , 2770.  ,\n",
    "       2957.5 , 3205.  , 3547.5 , 3775.  , 3880.  , 3992.5 , 4037.5 ,\n",
    "       4090.  , 4262.5 , 4352.5 , 4392.5 , 4495.  , 4595.  , 4745.  ,\n",
    "       4915.  , 4990.  , 5100.  , 5227.5 , 5442.5 , 5742.5 , 6022.5 ,\n",
    "       6295.  , 6555.  , 6697.5 , 6840.  , 6992.5 , 7100.  , 7245.  ,\n",
    "       7360.  , 7452.5 , 7615.  , 7787.5 , 7897.5 , 7980.  , 8030.  ,\n",
    "       8067.5 , 8100.  , 8080.  , 7992.5 , 7927.5 , 7730.  , 7685.  ,\n",
    "       7707.5 , 7682.5 , 7605.  , 7400.  , 7112.5 , 6835.  , 6597.5 ,\n",
    "       6425.  , 6325.  , 6175.  , 6025.  , 5967.5 , 6017.5 , 6070.  ,\n",
    "       6067.5 , 6145.  , 6130.  , 6072.5 , 6077.5 , 6117.5 , 6165.  ,\n",
    "       6200.  , 6182.5 , 6165.  , 6227.5 , 6297.5 , 6262.5 , 6102.5 ,\n",
    "       5997.5 , 5932.5 , 5842.5 , 5897.5 , 6040.  , 6060.  , 5982.5 ,\n",
    "       5790.  , 5587.5 , 5485.  , 5392.5 , 5285.  , 5235.  , 5207.5 ,\n",
    "       5140.  , 5032.5 , 4880.  , 4777.5 , 4852.5 , 4965.  , 4977.5 ,\n",
    "       4875.  , 4762.5 , 4702.5 , 4570.  , 4460.  , 4410.  , 4350.  ,\n",
    "       4217.5 , 4102.5 , 4002.5 , 3925.  , 3857.5 , 3805.  , 3780.  ,\n",
    "       3777.5 , 3732.5 , 3632.5 , 3497.5 , 3390.  , 3330.  , 3255.  ,\n",
    "       3187.5 , 3080.  , 3000.  , 2937.5 , 2915.  , 2850.  , 2805.  ,\n",
    "       2802.5 , 2787.5 , 2785.  , 2732.5 , 2635.  , 2550.  , 2505.  ,\n",
    "       2462.5 , 2432.5 , 2382.5 , 2360.  , 2312.5 , 2282.5 , 2235.  ,\n",
    "       2167.5 , 2160.  , 2170.  , 2187.5 , 2240.  , 2230.  , 2147.5 ,\n",
    "       2070.  , 2077.5 , 2105.  , 2127.5 , 2130.  , 2125.  , 2130.  ,\n",
    "       2140.  , 2197.5 , 2182.5 , 2195.  , 2150.  , 2112.5 , 2177.5 ,\n",
    "       2172.5 , 2287.5 , 2352.5 , 2350.  , 2362.5 , 2430.  , 2432.5 ,\n",
    "       2370.  , 2292.5 , 2242.5 , 2150.  , 2062.5 , 2005.  , 1952.5 ,\n",
    "       1925.  , 1882.5 , 1940.  , 2095.  , 2080.  , 2072.5 , 2257.5 ,\n",
    "       2417.5 , 2377.5 , 2270.  , 2182.5 , 2137.5 , 2125.  , 2082.5 ,\n",
    "       2027.5 , 1987.5 , 1922.5 , 1912.5 , 1910.  , 1880.  , 1977.5 ,\n",
    "       2005.  , 1930.  , 1947.5 , 2000.  , 2237.5 , 2212.5 , 2227.5 ,\n",
    "       2250.  , 2475.  , 2710.  , 2765.  , 2652.5 , 2520.  , 2517.5 ,\n",
    "       2622.5 , 2602.5 , 2410.  , 2250.  , 2140.  , 2192.5 , 2180.  ,\n",
    "       2225.  , 2255.  , 2220.  , 2100.  , 1992.5 , 1917.5 , 1835.  ,\n",
    "       1835.  , 1985.  , 1890.  , 1749.75, 1631.75, 1552.  , 1483.5 ,\n",
    "       1471.75, 1502.5 , 1497.5 , 1465.  , 1485.  , 1542.5 , 1612.5 ,\n",
    "       1550.  , 1515.  , 1532.5 , 1537.5 , 1525.  , 1485.  , 1442.5 ,\n",
    "       1425.  , 1402.5 , 1382.5 , 1422.5 , 1435.  , 1400.  , 1357.5 ,\n",
    "       1312.5 , 1272.5 , 1220.  , 1180.  , 1163.  , 1184.5 , 1197.5 ,\n",
    "       1160.25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_FR_Index=[ 1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,  13,\n",
    "        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,\n",
    "        27,  28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,\n",
    "        40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,\n",
    "        53,  54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,  65,\n",
    "        66,  67,  68,  69,  70,  71,  72,  73,  74,  75,  76,  77,  78,\n",
    "        79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,  90,  91,\n",
    "        92,  93,  94,  95,  96,  97,  98,  99, 100, 101, 102, 103, 104,\n",
    "       105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117,\n",
    "       118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130,\n",
    "       131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143,\n",
    "       144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156,\n",
    "       157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169,\n",
    "       170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182,\n",
    "       183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,\n",
    "       196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208,\n",
    "       209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221,\n",
    "       222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234,\n",
    "       235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247,\n",
    "       248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260,\n",
    "       261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273,\n",
    "       274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286,\n",
    "       287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299,\n",
    "       300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312,\n",
    "       313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325,\n",
    "       326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338,\n",
    "       339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351,\n",
    "       352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364,\n",
    "       365]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_FR=[836.75,  835.5 ,  832.5 ,  851.75,  874.25,  865.5 ,  859.5 ,\n",
    "        859.25,  865.  ,  878.25,  896.25,  900.75,  894.75,  888.5 ,\n",
    "        905.75,  924.25,  911.5 ,  919.25,  921.  ,  916.75,  920.  ,\n",
    "        916.  ,  917.25,  925.  ,  928.75,  944.75,  974.5 , 1024.5 ,\n",
    "       1056.25, 1132.5 , 1159.5 , 1154.75, 1111.  , 1119.75, 1106.25,\n",
    "       1104.25, 1081.  , 1099.  , 1100.25, 1109.  , 1139.75, 1162.25,\n",
    "       1187.5 , 1231.5 , 1275.75, 1397.5 , 1497.5 , 1610.  , 1672.5 ,\n",
    "       1777.5 , 1895.  , 2002.5 , 2102.5 , 2212.5 , 2307.5 , 2387.5 ,\n",
    "       2452.5 , 2557.5 , 2697.5 , 2952.5 , 3150.  , 3280.  , 3315.  ,\n",
    "       3355.  , 3460.  , 3520.  , 3560.  , 3607.5 , 3632.5 , 3687.5 ,\n",
    "       3752.5 , 3850.  , 3960.  , 4250.  , 4480.  , 4645.  , 4842.5 ,\n",
    "       5117.5 , 5562.5 , 6075.  , 6472.5 , 6757.5 , 6907.5 , 7037.5 ,\n",
    "       7170.  , 7245.  , 7260.  , 7285.  , 7352.5 , 7442.5 , 7487.5 ,\n",
    "       7552.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_FR=[1018.25,  995.5 ,  976.  ,  947.5 ,  942.  ,  940.  ,  941.  ,\n",
    "        944.  ,  936.25,  929.75,  956.  ,  984.  , 1073.  , 1151.5 ,\n",
    "       1215.25, 1284.  , 1332.75, 1340.75, 1315.75, 1330.25, 1339.  ,\n",
    "       1393.25, 1433.  , 1431.75, 1448.75, 1462.75, 1562.75, 1683.5 ,\n",
    "       1964.  , 2157.  , 2218.  , 2250.  , 2281.  , 2223.75, 2142.  ,\n",
    "       2092.5 , 2069.75, 2058.5 , 2046.5 , 2052.75, 2099.25, 2095.  ,\n",
    "       2092.5 , 2112.5 , 2092.5 , 2052.5 , 2085.  , 2095.  , 2247.5 ,\n",
    "       2387.5 , 2582.5 , 2770.  , 2957.5 , 3205.  , 3547.5 , 3775.  ,\n",
    "       3880.  , 3992.5 , 4037.5 , 4090.  , 4262.5 , 4352.5 , 4392.5 ,\n",
    "       4495.  , 4595.  , 4745.  , 4915.  , 4990.  , 5100.  , 5227.5 ,\n",
    "       5442.5 , 5742.5 , 6022.5 , 6295.  , 6555.  , 6697.5 , 6840.  ,\n",
    "       6992.5 , 7100.  , 7245.  , 7360.  , 7452.5 , 7615.  , 7787.5 ,\n",
    "       7897.5 , 7980.  , 8030.  , 8067.5 , 8100.  , 8080.  , 7992.5 ,\n",
    "       7927.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_FR=[7667.5, 7755. , 7580. , 7530. , 7627.5, 7705. , 7670. , 7670. ,\n",
    "       7795. , 8002.5, 7987.5, 7855. , 7740. , 7587.5, 7560. , 7695. ,\n",
    "       7895. , 7742.5, 7637.5, 7717.5, 7985. , 8127.5, 8080. , 7945. ,\n",
    "       7850. , 7952.5, 7982.5, 7932.5, 7785. , 7562.5, 7507.5, 7575. ,\n",
    "       7562.5, 7422.5, 7297.5, 7267.5, 7200. , 7102.5, 6985. , 7025. ,\n",
    "       7115. , 7112.5, 6925. , 6660. , 6432.5, 6280. , 6225. , 6100. ,\n",
    "       5907.5, 5745. , 5642.5, 5542.5, 5542.5, 5515. , 5402.5, 5242.5,\n",
    "       5092.5, 4947.5, 4827.5, 4712.5, 4635.]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_FR=[7730. , 7685. , 7707.5, 7682.5, 7605. , 7400. , 7112.5, 6835. ,\n",
    "       6597.5, 6425. , 6325. , 6175. , 6025. , 5967.5, 6017.5, 6070. ,\n",
    "       6067.5, 6145. , 6130. , 6072.5, 6077.5, 6117.5, 6165. , 6200. ,\n",
    "       6182.5, 6165. , 6227.5, 6297.5, 6262.5, 6102.5, 5997.5, 5932.5,\n",
    "       5842.5, 5897.5, 6040. , 6060. , 5982.5, 5790. , 5587.5, 5485. ,\n",
    "       5392.5, 5285. , 5235. , 5207.5, 5140. , 5032.5, 4880. , 4777.5,\n",
    "       4852.5, 4965. , 4977.5, 4875. , 4762.5, 4702.5, 4570. , 4460. ,\n",
    "       4410. , 4350. , 4217.5, 4102.5, 4002.5, 3925. , 3857.5, 3805. ,\n",
    "       3780. , 3777.5, 3732.5, 3632.5, 3497.5, 3390. , 3330. , 3255. ,\n",
    "       3187.5, 3080. , 3000. , 2937.5, 2915. , 2850. , 2805. , 2802.5,\n",
    "       2787.5, 2785. , 2732.5, 2635. , 2550. , 2505. , 2462.5, 2432.5,\n",
    "       2382.5, 2360. , 2312.5, 2282.5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nitrate -- data are from CentralSoG_0-10mNitrate_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_N= [24.3980628 , 23.67905457, 22.59146629, 14.48463374,  5.38950038,\n",
    "        2.51176774,  1.97124377,  3.54658716,  8.74831538, 17.18580439,\n",
    "       21.6594439 , 23.57027296]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_N_SEM=[0.11667523, 0.11190603, 0.20137107, 1.23414193, 0.51169805,\n",
    "       0.58081648, 0.51456234, 0.5983553 , 0.45166945, 0.24010748,\n",
    "       0.22360953, 0.1472202]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_N=[22.82788288, 22.19948811, 16.63627192,  6.90341105,  3.57964221,\n",
    "        1.85326166,  1.53406205,  2.710954  ,  9.13413621, 16.421376  ,\n",
    "       20.70562188, 22.49668357]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_N_SEM=[0.36677255, 0.25092139, 0.68853362, 0.50627303, 0.44464386,\n",
    "       0.24919049, 0.63251747, 1.03646634, 0.85953584, 0.45853951,\n",
    "       0.25025754, 0.12691501]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_N=[12.46289449, 13.83035024, 16.02460427, 14.30295155]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_N=[7.57758729, 8.8820203 , 9.86462511, 9.83486753]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_N=[3.48006453, 3.20434749, 1.67761007, 2.34410947]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_N=[3.69164181, 1.13548262, 1.43987888, 1.86403363]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Silicon -- data are from CentralSoG_0-10mSilicon_Data.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Si= [49.32323968, 50.37285438, 49.70968201, 34.4677553 , 12.64501118,\n",
    "       12.50659466, 17.0418997 , 19.41833774, 26.0765079 , 35.45568785,\n",
    "       43.45061737, 47.87295499]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Si_SEM=[0.41073373, 0.50735594, 0.36454512, 2.70717051, 2.41409781,\n",
    "       1.4875741 , 2.96242003, 4.76044281, 3.73065234, 2.24611888,\n",
    "       1.19261423, 0.90892549]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Si=[48.15701592, 49.07171776, 41.72099818, 17.42549544,  8.36526166,\n",
    "       15.26847673, 21.98395522, 27.37391357, 33.72818989, 39.00032263,\n",
    "       43.47364324, 46.34268646]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Si_SEM=[0.2275976 , 0.33726364, 1.34646478, 1.47386724, 0.67683366,\n",
    "       0.9930824 , 2.5463565 , 2.47506929, 2.05869284, 1.55110053,\n",
    "       0.78331193, 0.5134743]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_Si=[28.15483335, 29.61777566, 37.88429131, 33.43969765]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_Si=[19.10670492, 22.81162635, 21.68596449, 26.41137794]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_Si=[8.64361296, 10.58562337, 19.52603833, 26.5338348]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_Si=[15.81506055, 21.94194099, 20.0092991 , 28.40216005]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x1500 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(8,2,figsize=(10, 15),gridspec_kw={'width_ratios': [4, 1]})\n",
    "bbox = {'boxstyle': 'round', 'facecolor': 'w', 'alpha': 0.9}\n",
    "cmap = plt.get_cmap('tab10')\n",
    "palette = [cmap(0), cmap(0.2), 'k', cmap(0.1), cmap(0.3)]\n",
    "xticks=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov',\"Dec\"]\n",
    "border = 0.25\n",
    "\n",
    "fig.tight_layout(pad=2.5)\n",
    "c='k'\n",
    "\n",
    "### SST\n",
    "\n",
    "ax[0,0].errorbar(xticks, NPGO_C_SST, yerr= NPGO_C_SST_SEM, capsize=3,label='NPGO+ cold',linewidth=2)\n",
    "ax[0,0].errorbar(xticks, NPGO_W_SST,yerr= NPGO_W_SST_SEM, capsize=3,linestyle='--',label='NPGO- warm',color='r',linewidth=2)\n",
    "ax[0,0].set_title('Sea Surface Temperature',fontsize=14)\n",
    "ax[0,0].legend(frameon=False,fontsize=12,loc=2)\n",
    "ax[0,0].set_ylim(5,25)\n",
    "ax[0,0].set_ylabel('Degrees C',fontsize=12)\n",
    "ax[0,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[0,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[0,0].set_xticklabels([])\n",
    "ax[0,0].text(-.4, 26.5, '(a)', fontsize=12,  color='k')\n",
    "\n",
    "#ax[0,1].bp1 = color_boxplot(Spring_C_SST, 'royalblue', [1])\n",
    "ax[0,1].boxplot(Spring_C_SST,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[0,1].boxplot(Spring_W_SST,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[0,1].boxplot(Summer_C_SST,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[0,1].boxplot(Summer_W_SST,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[0,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[0,1].set_ylim(5,25)\n",
    "ax[0,1].set_ylabel('', fontsize=12)\n",
    "ax[0,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[0,1].yaxis.set_tick_params(labelsize=12)\n",
    "#ax.legend([bp1[\"boxes\"], bp2[\"boxes\"], ['A', 'B'], loc='upper right')\n",
    "## To indicate significance\n",
    "ax[0,1].plot([1,1, 1.5, 1.5], [13, 14.25, 14.25, 13], linewidth=1, color='k')\n",
    "ax[0,1].text(1.25, 13.5, \"*\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[0,1].plot([2.5,2.5, 3, 3], [20.75, 22, 22, 20.75], linewidth=1, color='k')\n",
    "ax[0,1].text(2.75, 22, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "\n",
    "### SSS\n",
    "\n",
    "ax[1,0].errorbar(xticks, NPGO_C_Sal, yerr= NPGO_C_Sal_SEM, capsize=3,label='NPGO+ coldest',linewidth=2)\n",
    "ax[1,0].errorbar(xticks, NPGO_W_Sal,yerr= NPGO_W_Sal_SEM, capsize=3,linestyle='--',label='NPGO- warmest',color='r',linewidth=2)\n",
    "ax[1,0].set_title('Sea Surface Salinity',fontsize=14)\n",
    "ax[1,0].legend((),frameon=False)\n",
    "ax[1,0].set_ylim(5,30)\n",
    "ax[1,0].set_ylabel('g/kg',fontsize=12)\n",
    "ax[1,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[1,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[1,0].set_xticklabels([])\n",
    "ax[1,0].text(-.4, 32, '(b)', fontsize=12,  color='k')\n",
    "\n",
    "\n",
    "ax[1,1].boxplot(Spring_C_Sal,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[1,1].boxplot(Spring_W_Sal,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[1,1].boxplot(Summer_C_Sal,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[1,1].boxplot(Summer_W_Sal,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[1,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[1,1].set_ylim(5,30)\n",
    "ax[1,1].set_ylabel('',fontsize=12)\n",
    "ax[1,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[1,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[1,1].plot([1,1, 1.5, 1.5], [25.25, 26.75, 26.75, 25.25], linewidth=1, color='k')\n",
    "ax[1,1].text(1.25, 26, \"*\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[1,1].plot([2.5,2.5, 3, 3], [22.25, 23.75, 23.75, 22.25], linewidth=1, color='k')\n",
    "ax[1,1].text(2.75, 23.75, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "\n",
    "\n",
    "### Halocline Strength\n",
    "ax[2,0].errorbar(xticks, NPGO_C_Halo, yerr= NPGO_C_Halo_SEM, capsize=3,label='NPGO+ coldest',linewidth=2)\n",
    "ax[2,0].errorbar(xticks, NPGO_W_Halo,yerr= NPGO_W_Halo_SEM, capsize=3,linestyle='--',label='NPGO- warmest',color='r',linewidth=2)\n",
    "ax[2,0].set_title('Halocline Strength',fontsize=14)\n",
    "ax[2,0].legend((),frameon=False,loc=1)\n",
    "ax[2,0].set_ylim(0,4)\n",
    "ax[2,0].set_ylabel('g/kg m$^{-1}$',fontsize=12)\n",
    "#ax.invert_yaxis()\n",
    "ax[2,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[2,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[2,0].set_xticklabels([])\n",
    "ax[2,0].text(-.4, 4.3, '(c)', fontsize=12,  color='k')\n",
    "\n",
    "ax[2,1].boxplot(Spring_C_Halo,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[2,1].boxplot(Spring_W_Halo,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[2,1].boxplot(Summer_C_Halo,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[2,1].boxplot(Summer_W_Halo,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[2,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[2,1].set_ylim(0,4)\n",
    "ax[2,1].set_ylabel('',fontsize=12)\n",
    "ax[2,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[2,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[2,1].plot([1,1, 1.5, 1.5], [2, 2.24, 2.24, 2], linewidth=1, color='k')\n",
    "ax[2,1].text(1.25, 2.1, \"*\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[2,1].plot([2.5,2.5, 3, 3], [3.25, 3.49, 3.49, 3.25], linewidth=1, color='k')\n",
    "ax[2,1].text(2.75, 3.5, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "\n",
    "### Surface PAR\n",
    "\n",
    "ax[3,0].errorbar(xticks, NPGO_C_PAR, yerr= NPGO_C_PAR_SEM, capsize=3,label='NPGO+ coldest',linewidth=2)\n",
    "ax[3,0].errorbar(xticks, NPGO_W_PAR,yerr= NPGO_W_PAR_SEM, capsize=3,linestyle='--',label='NPGO- warmest',color='r',linewidth=2)\n",
    "ax[3,0].set_title('Surface PAR',fontsize=14)\n",
    "ax[3,0].legend((),frameon=False)\n",
    "ax[3,0].set_ylim(0,125)\n",
    "ax[3,0].set_ylabel('uE/m$^{2}$/s',fontsize=12)\n",
    "ax[3,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[3,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[3,0].set_xticklabels([])\n",
    "ax[3,0].text(-.4, 133, '(d)', fontsize=12,  color='k')\n",
    "\n",
    "\n",
    "ax[3,1].boxplot(Spring_C_PAR,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[3,1].boxplot(Spring_W_PAR,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[3,1].boxplot(Summer_C_PAR,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[3,1].boxplot(Summer_W_PAR,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[3,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[3,1].set_ylim(0,125)\n",
    "ax[3,1].set_ylabel('',fontsize=12)\n",
    "ax[3,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[3,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[3,1].plot([1,1, 1.5, 1.5], [72.5, 80, 80, 72.5], linewidth=1, color='k')\n",
    "ax[3,1].text(1.25, 78, \"**\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[3,1].plot([2.5,2.5, 3, 3], [102.5, 110, 110, 102.5], linewidth=1, color='k')\n",
    "ax[3,1].text(2.75, 110, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "\n",
    "### Wind Speed\n",
    "\n",
    "\n",
    "ax[4,0].errorbar(xticks, NPGO_C_Wind, yerr= NPGO_C_Wind_SEM, capsize=3,label='NPGO+ coldest',linewidth=2)\n",
    "ax[4,0].errorbar(xticks, NPGO_W_Wind,yerr= NPGO_W_Wind_SEM, capsize=3,linestyle='--',label='NPGO- warmest',color='r',linewidth=2)\n",
    "ax[4,0].set_title('Wind Speed',fontsize=14)  #(with 2015)\n",
    "ax[4,0].legend((),frameon=False)\n",
    "ax[4,0].set_ylim(2,7)\n",
    "ax[4,0].set_ylabel('m s$^{-1}$',fontsize=12)\n",
    "ax[4,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[4,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[4,0].set_xticklabels([])\n",
    "ax[4,0].text(-.4, 7.3, '(e)', fontsize=12,  color='k')\n",
    "\n",
    "\n",
    "ax[4,1].boxplot(Spring_C_Wind,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[4,1].boxplot(Spring_W_Wind,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[4,1].boxplot(Summer_C_Wind,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[4,1].boxplot(Summer_W_Wind,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[4,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[4,1].set_ylim(2,7)\n",
    "ax[4,1].set_ylabel('')\n",
    "ax[4,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[4,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[4,1].plot([1,1, 1.5, 1.5], [5.75, 6, 6, 5.75], linewidth=1, color='k')\n",
    "ax[4,1].text(1.25, 6, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "ax[4,1].plot([2.5,2.5, 3, 3], [4.5, 4.75, 4.75, 4.5], linewidth=1, color='k')\n",
    "ax[4,1].text(2.75, 4.55, \"*\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "\n",
    "\n",
    "### Fraser River Flow\n",
    "\n",
    "ax[5,0].plot(NPGO_C_FR_Index,NPGO_C_FR, linestyle='-',label='Cold Years',linewidth=2);\n",
    "ax[5,0].plot(NPGO_W_FR_Index,NPGO_W_FR, color='r',linestyle='--',label='Warm Years',linewidth=2);\n",
    "ax[5,0].set_title('Fraser River Flow',fontsize=14)\n",
    "ax[5,0].legend((),frameon=False,bbox_to_anchor=(1, 1))\n",
    "ax[5,0].set_ylim(0,10000)\n",
    "ax[5,0].set_ylabel('m$^{3}$ s$^{-1}$',fontsize=12)\n",
    "#ax.set_xlabel('Day of Year',fontsize=14)\n",
    "ax[5,0].set_xlim(0,365)\n",
    "ax[5,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[5,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[5,0].set_xticks([1,32,60,91,121,152,182,213,244,274,305,335])\n",
    "#ax.set_xticklabels(['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'],fontsize=12)\n",
    "ax[5,0].set_xticklabels([])\n",
    "ax[5,0].text(4, 10600, '(f)', fontsize=12,  color='k')\n",
    "\n",
    "\n",
    "ax[5,1].boxplot(Spring_C_FR,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[5,1].boxplot(Spring_W_FR,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[5,1].boxplot(Summer_C_FR,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[5,1].boxplot(Summer_W_FR,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[5,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[5,1].set_ylim(0,10000)\n",
    "ax[5,1].set_ylabel('',fontsize=12)\n",
    "ax[5,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[5,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[5,1].plot([1,1, 1.5, 1.5], [8500, 9100, 9100, 8500], linewidth=1, color='k')\n",
    "ax[5,1].text(1.25, 8700, \"*\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[5,1].plot([2.5,2.5, 3, 3], [8400, 9000, 9000, 8400], linewidth=1, color='k')\n",
    "ax[5,1].text(2.75, 8600, \"**\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "\n",
    "\n",
    "\n",
    "## Nitrate\n",
    "\n",
    "ax[6,0].errorbar(xticks, NPGO_C_N, yerr= NPGO_C_N_SEM, capsize=3,label='NPGO+ coldest',linewidth=2)\n",
    "ax[6,0].errorbar(xticks, NPGO_W_N,yerr= NPGO_W_N_SEM, capsize=3,linestyle='--',label='NPGO- warmest',color='r',linewidth=2)\n",
    "ax[6,0].set_title('Depth Averaged Nitrate (0-10 m)',fontsize=14)\n",
    "ax[6,0].legend((),frameon=False)\n",
    "ax[6,0].set_ylim(0,30)\n",
    "ax[6,0].set_ylabel('mmol N m$^{-3}$',fontsize=12)\n",
    "ax[6,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[6,0].yaxis.set_tick_params(labelsize=12)\n",
    "ax[6,0].set_xticklabels([])\n",
    "ax[6,0].text(-.4, 32, '(g)', fontsize=12,  color='k')\n",
    "\n",
    "\n",
    "ax[6,1].boxplot(Spring_C_N,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[6,1].boxplot(Spring_W_N,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[6,1].boxplot(Summer_C_N,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[6,1].boxplot(Summer_W_N,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[6,1].set(xticks=[1.25,2.75], xticklabels=['',''])\n",
    "ax[6,1].set_ylim(0,30)\n",
    "ax[6,1].set_ylabel('',fontsize=12)\n",
    "ax[6,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[6,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[6,1].plot([1,1, 1.5, 1.5], [18, 19.8, 19.8, 18], linewidth=1, color='k')\n",
    "ax[6,1].text(1.25, 19, \"**\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[6,1].plot([2.5,2.5, 3, 3], [6, 7.8, 7.8, 6], linewidth=1, color='k')\n",
    "ax[6,1].text(2.75, 8, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "\n",
    "\n",
    "## Silicon\n",
    "ax[7,0].errorbar(xticks, NPGO_C_Si, yerr= NPGO_C_Si_SEM, capsize=3,label='NPGO+ coldest',linewidth=2)\n",
    "ax[7,0].errorbar(xticks, NPGO_W_Si,yerr= NPGO_W_Si_SEM, capsize=3,linestyle='--',label='NPGO- warmest',color='r',linewidth=2)\n",
    "ax[7,0].set_title('Depth Averaged Silicon (0-10 m)',fontsize=14)\n",
    "ax[7,0].legend((),frameon=False)\n",
    "ax[7,0].set_ylim(0,60)\n",
    "ax[7,0].set_ylabel('mmol Si m$^{-3}$',fontsize=12)\n",
    "ax[7,0].xaxis.set_tick_params(labelsize=12)\n",
    "ax[7,0].yaxis.set_tick_params(labelsize=12)\n",
    "#ax.set_xticklabels([])\n",
    "ax[7,0].text(-.4, 63, '(h)', fontsize=12,  color='k')\n",
    "\n",
    "ax[7,1].boxplot(Spring_C_Si,positions=[1], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[7,1].boxplot(Spring_W_Si,positions=[1.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[7,1].boxplot(Summer_C_Si,positions=[2.5], patch_artist=True,showmeans=False,boxprops=dict(facecolor='royalblue',color='royalblue'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[7,1].boxplot(Summer_W_Si,positions=[3], patch_artist=True,showmeans=False,boxprops=dict(facecolor='r',color='r'),capprops=dict(color=c),whiskerprops=dict(color=c),flierprops=dict(color=c, markeredgecolor=c),\\\n",
    "                medianprops=dict(color=c),widths=0.4)\n",
    "ax[7,1].set(xticks=[1.25,2.75], xticklabels=['Spring','Summer'])\n",
    "ax[7,1].set_ylim(0,60)\n",
    "ax[7,1].set_ylabel('',fontsize=12)\n",
    "ax[7,1].xaxis.set_tick_params(labelsize=12)\n",
    "ax[7,1].yaxis.set_tick_params(labelsize=12)\n",
    "## To indicate significance\n",
    "ax[7,1].plot([1,1, 1.5, 1.5], [42, 45.6, 45.6, 42], linewidth=1, color='k')\n",
    "ax[7,1].text(1.25, 45, \"*\", ha='center', va='bottom', color='k',fontsize=12)\n",
    "ax[7,1].plot([2.5,2.5, 3, 3], [35, 38.6, 38.6, 35], linewidth=1, color='k')\n",
    "ax[7,1].text(2.75, 38.5, \"NS\", ha='center', va='bottom', color='k',fontsize=9)\n",
    "\n",
    "\n",
    "#plt.savefig('Fig4_Drivers_revised.png', bbox_inches='tight',dpi=1000,transparent=False)\n",
    "\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (py39)",
   "language": "python",
   "name": "py39"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}