{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "*This notebook contains material from [Controlling Natural Watersheds](https://jckantor.github.io/Controlling-Natural-Watersheds);\n", "content is available [on Github](https://github.com/jckantor/Controlling-Natural-Watersheds.git).*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "< [Global Historical Climatology Network](http://nbviewer.jupyter.org/github/jckantor/Controlling-Natural-Watersheds/blob/master/notebooks/A.11-Global_Historical_Climatology_Network.ipynb) | [Contents](toc.ipynb) | [ENSO](http://nbviewer.jupyter.org/github/jckantor/Controlling-Natural-Watersheds/blob/master/notebooks/A.13-ENSO.ipynb) >
"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"# Precipitation at International Falls 1970-2010"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"* Load Precipitation Data for International Falls\n",
"* Comparison of 1970-1999 to 2000-2010\n",
"* Correlation of Precipitation and Rainy River Flow"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Initialize Notebook"
]
},
{
"cell_type": "code",
"execution_count": 217,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"# Display graphics inline with the notebook\n",
"%matplotlib inline\n",
"\n",
"# Standard Python modules\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import os\n",
"import datetime\n",
"\n",
"# use seaborn for statistical plotting\n",
"import seaborn as sns\n",
"sns.set_context('talk')\n",
"\n",
"# Data directory\n",
"dir = '../data/'\n",
"img = '../images'"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"## Load Precipitation Data for International Falls"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"Precipitation data for International Falls was obtained from the Global Historical Climatology network and stored as a Pandas data series in `./data/KINL.pkl` in standard metric units of mm. In the following cell reads the data series"
]
},
{
"cell_type": "code",
"execution_count": 218,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [],
"source": [
"KINL = pd.read_pickle(dir+'KINL.pkl')\n",
"KINL = KINL['1970':'2010']"
]
},
{
"cell_type": "markdown",
"metadata": {
"deletable": true,
"editable": true
},
"source": [
"### Annual Precipitation"
]
},
{
"cell_type": "code",
"execution_count": 219,
"metadata": {
"collapsed": false,
"deletable": true,
"editable": true
},
"outputs": [
{
"data": {
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ERCKgok1EREQkArpO2yAX2/euiYiIDFYq2kRERESq1MyLDWt6VERERCQCKtpEREREIqDp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\n9ca1aq5641o1V71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"text/plain": [
" "
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}