{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "# **Chapter 3** \n", "**ATMOS 5340: Environmental Programming and Statistics** \n", "**John Horel **\n", "\n", "Evaluation of persistence forecasts of total seasonal snow at Alta based on snow totals each month earlier during the season or from the previous season" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# these are python modules used in the program\n", "import numpy as np\n", "import pandas as pd\n", "from pandas import Series, DataFrame\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alta snowfall\n", "https://utahavalanchecenter.org/alta-monthly-snowfall\n", "\n", "\n", "Look in the `data` folder at the called `alta_snow.csv`\n", "\n", "Open the `alta_snow.csv` file see the column contents and the units.\n", "\n", "- The 0th column is the Year at Season End\n", "- The 1st-6th column are the total snowfall during each month from November to April (in inches)\n", "- The 7th column is the Nov-Apr total snowfall (inches)\n", "\n", "\n", "Begins in the 1946 season and ends in 2022" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | NOV | \n", "DEC | \n", "JAN | \n", "FEB | \n", "MAR | \n", "APR | \n", "TOTAL | \n", "
---|---|---|---|---|---|---|---|
Ending Year | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
1946 | \n", "276.860 | \n", "210.820 | \n", "214.630 | \n", "127.00 | \n", "175.260 | \n", "140.970 | \n", "1145.540 | \n", "
1947 | \n", "175.260 | \n", "160.020 | \n", "154.940 | \n", "134.62 | \n", "172.720 | \n", "152.400 | \n", "949.960 | \n", "
1948 | \n", "299.720 | \n", "203.200 | \n", "116.840 | \n", "167.64 | \n", "419.100 | \n", "187.960 | \n", "1394.460 | \n", "
1949 | \n", "180.340 | \n", "406.400 | \n", "335.280 | \n", "147.32 | \n", "246.380 | \n", "12.700 | \n", "1328.420 | \n", "
1950 | \n", "99.060 | \n", "347.980 | \n", "337.820 | \n", "86.36 | \n", "276.860 | \n", "63.500 | \n", "1211.580 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
2018 | \n", "38.100 | \n", "109.220 | \n", "130.810 | \n", "167.64 | \n", "179.070 | \n", "106.680 | \n", "731.520 | \n", "
2019 | \n", "116.840 | \n", "144.780 | \n", "215.900 | \n", "309.88 | \n", "254.000 | \n", "161.290 | \n", "1206.500 | \n", "
2020 | \n", "224.790 | \n", "166.370 | \n", "297.180 | \n", "184.15 | \n", "121.920 | \n", "63.500 | \n", "1056.640 | \n", "
2021 | \n", "129.540 | \n", "129.540 | \n", "126.492 | \n", "314.96 | \n", "134.620 | \n", "114.300 | \n", "949.960 | \n", "
2022 | \n", "42.926 | \n", "276.098 | \n", "54.102 | \n", "52.07 | \n", "143.002 | \n", "149.098 | \n", "717.296 | \n", "
77 rows × 7 columns
\n", "