Adding Narrative Text and Cleaning Repo (#23)

* Add Alex's Videos to edited.ipynb

* Add Melt Rate section to edited.ipynb

* Icing and Cleaning

* Cleaning

* More Cleaning, rm ipynb checkpoints

* rename edited.ipynb -> SnowFlow.ipynb

* rm OpenTopography API Key file

* Add Dingman citation from Carlos

additional_notebooks/MeltRate.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ecc44fa4-6561-49ee-83c2-738b02743ca9",
+   "metadata": {},
+   "source": [
+    "## Section #1: Generating Melt Rate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f43efbd7-3868-4082-895d-6e887d85a55f",
+   "metadata": {},
+   "source": [
+    "#### Goal: Calculate melt rate in mm/hr to use in the Overland Flow Model. \n",
+    "In this section of the SnowFlow notebook, we we determine the melt rate of a hypothetical snow layer atop the Heil Ranch area which makes up the Geer Canyon watershed near Boulder Colorado, USA.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "354142e0-cfdb-4cae-bad0-6ffe8a7fbce1",
+   "metadata": {},
+   "source": [
+    "First, double check in the upper right-hand corner of the notebook to ensure that your kernel is either \"CSDMS\" or \"Ivy\".\n",
+    "We will also need to import the numpy library to complete this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "b6863af5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98cce2b4-095b-4af4-963c-49bde3719aae",
+   "metadata": {},
+   "source": [
+    "We will start by defining three scenarios for melting. Generally, the degree-day-factor ($DDF$) for snow melt is about $3-5$ $\\frac {millimeters} {Day*Kelvin}$. \n",
+    "\n",
+    "$$ MeltRate = DDF * Temperature $$\n",
+    "\n",
+    "We will use 3 temperatures to generate three scenarios for $DDF$ : 0.5, 4, and 10 $^\\circ$$C$.\n",
+    "\n",
+    "We will start by creating a column vector with computed $DDF$ as values (dimensions of this vector will be 3-by-1)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ce0b898-6615-428e-b60c-de0ea7581811",
+   "metadata": {},
+   "source": [
+    "First, start by creating a numpy array called Temperature with the temperature values of 0.5, 4, and 10 $^\\circ$$C$. Then, convert the vector into Kelvin."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "438e83f6-e062-4b42-ac4f-cee69e152af0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ab9be93-9b8d-4ba2-8617-53e00e9fc8e0",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "    <summary>👉 <b>Click to see solution</b></summary>\n",
+    "\n",
+    "```python\n",
+    "Temperature = np.array([0.5,4,10]) #Celsius\n",
+    "Temperature = Temperature + 273 #Kelvin\n",
+    "```\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ad060ed1-848b-4cdf-a2d3-0d230a055b14",
+   "metadata": {},
+   "source": [
+    "Now, we need to define our $DDF$ variable, and convert it to units of $^\\circ$$C$. For this notebook, we will use $DDF = 4$ \n",
+    "\n",
+    "Keep in mind, the units of $DDF$ are $\\frac {millimeters} {Day*Kelvin}$, so you also need to convert the value to units of $\\frac {millimeters} {Hours*Kelvin}$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7f371272-4920-49b0-8e9d-0b04a4b1505a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "35a25607-027a-4f05-8afb-c4332c617b5e",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "    <summary>👉 <b>Click to see solution</b></summary>\n",
+    "\n",
+    "```python\n",
+    "DDF = 4 #daily\n",
+    "DDF = DDF/24 #hourly\n",
+    "```\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ad3f1b44-d958-4570-93c3-82d26674c076",
+   "metadata": {},
+   "source": [
+    "\n",
+    "Next, we will calculate the $MeltRate$ for each of the three scenarios and place their values in an array called Melt. \n",
+    "\n",
+    "The equation is as follow: $MeltRate = DDF * Temperature$."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "82155be9-33b7-4a86-b4d1-7a648faef3a9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dddfa559-13f5-4e0a-88a3-3ec3257325a2",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "    <summary>👉 <b>Click to see solution</b></summary>\n",
+    "\n",
+    "```python\n",
+    "Melt = DDF * Temperature\n",
+    "```\n",
+    "</details>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f70636b2-e02c-4afd-9287-26b76bb4d22b",
+   "metadata": {},
+   "source": [
+    "Now, we will round the numbers in the Melt array to three decimal points. Print the array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cd6a38b3-7230-404c-91c1-eed405477f21",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "903b2021-3cc8-4119-992e-6c024d935dca",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "    <summary>👉 <b>Click to see solution</b></summary>\n",
+    "\n",
+    "```python\n",
+    "np.round(Melt, 3)\n",
+    "```\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c9a1350-ab09-4c78-a068-89cb31ebe641",
+   "metadata": {},
+   "source": [
+    "At this point, we have computed melt rates for our three scenaiors via several seperate lines of code. However, this can also be done with a function called $Melt$.\n",
+    "First, you will need to define the function $Melt$ to take an input temperature in units of $^\\circ$$C$. The same lines of code used above can be used below for our function. However, you can condense the lines of code to be more pythonic."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4dd9910-dbf4-400b-9b3c-fd752af4f6a9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2eeda5c5-5e0d-46d2-9ad6-0b071eed6bf7",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "    <summary>👉 <b>Click to see solution</b></summary>\n",
+    "\n",
+    "```python\n",
+    "def Melt(Temperature):\n",
+    "    Temperature = Temperature + 273 # Conversion to Kelvin\n",
+    "    DDF = 4/24 #Conversion to hourly rate\n",
+    "    Melt = DDF * Temperature\n",
+    "    np.round(Melt, 3)\n",
+    "    return(Melt)\n",
+    "```\n",
+    "</details>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "32105cd4-d551-4691-9de7-ce2110c61cf9",
+   "metadata": {},
+   "source": [
+    "Now try running the $Melt$ function with a temperature of $0.5$ $^\\circ$$C$. The function should return the a value equal to the first value in the Melt array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "92b3fa04-fac5-4d6b-89cd-3df465268240",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "83c54dbb-0474-4806-98bb-ea99d7e80749",
+   "metadata": {},
+   "source": [
+    "<details>\n",
+    "    <summary>👉 <b>Click to see solution</b></summary>\n",
+    "\n",
+    "```python\n",
+    "Melt(0.5)\n",
+    "```\n",
+    "</details>"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "CSDMS",
+   "language": "python",
+   "name": "csdms-2023"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
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+   "pygments_lexer": "ipython3",
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+}