{
 "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": 67,
   "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('\\u03bcmol 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('\\u03bcmol N 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.png', bbox_inches='tight',dpi=1000,transparent=False)\n",
    "\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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