{
 "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= [5.255556106567383, 4.943120002746582 ,5.280871868133545, 4.541804313659668, 4.1618571281433105, 4.005492687225342, 4.127147674560547 ,4.005497932434082 ,4.025290012359619, 4.468635082244873, 5.065437316894531, 5.1902337074279785]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_C_Wind_SEM=[0.22892044484615326, 0.23120790719985962, 0.19691279530525208 ,0.45478391647338867, 0.13002191483974457, 0.12630566954612732, 0.38189953565597534, 0.2072964608669281 ,0.23421116173267365, 0.2180320769548416, 0.26443806290626526, 0.5637392401695251]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Wind=[4.4879350662231445 ,4.2724103927612305 ,3.360086679458618 ,3.922926187515259, 3.1792898178100586, 3.588247537612915, 3.384995937347412, 3.394467830657959, 3.5997471809387207, 3.6979005336761475, 4.087904453277588, 4.875214576721191]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "NPGO_W_Wind_SEM=[0.595543622970581, 0.614099383354187, 0.2084141969680786 ,0.1963309645652771, 0.1585114598274231, 0.19811184704303741 ,0.1936599761247635, 0.2502512037754059, 0.17527444660663605, 0.1652664840221405, 0.3087571859359741, 0.3759503662586212]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_C_Wind=[5.280871868133545, 4.541804313659668, 4.1618571281433105]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "Spring_W_Wind=[3.360086679458618, 3.922926187515259, 3.1792898178100586]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_C_Wind=[4.005492687225342, 4.127147674560547, 4.005497932434082]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "Summer_W_Wind=[3.588247537612915, 3.384995937347412, 3.394467830657959]"
   ]
  },
  {
   "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",
    "\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",
    "\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",
    "\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",
    "\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(2,6)\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, 6.3, '(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(2,6)\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",
    "\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",
    "\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",
    "\n",
    "\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",
    "\n",
    "#plt.savefig('Fig3a_SSTboxplots.png', bbox_inches='tight',dpi=1000,transparent=True)\n",
    "\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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