implemented changes suggested by Sarah

Author: ValentinGebhart

doc/tutorial/climada_util_local_exceedance_values.ipynb

@@ -14,7 +14,7 @@
    "source": [
     "This tutorial presents methods available for `Hazard` and `Impact` objects, to compute local exceedance values and local return periods. In particular, the available methods compute local exceedance intensities (`Hazard.local_exceedance_intensity`) and local exceedance impacts (`Impact.local_exceedance_impact`) for user-defined return periods, and local return periods for user-defined threshold values (`Hazard.local_return_period` or `Impact.local_return_period`).\n",
     "\n",
-    "We first explain the methods functionality and options using a mock Hazard object such that the computation can be easily followed. Further below, we apply the methods to more real Hazard and Impact objects. If you are already familiar with local exceedance values and return values, you can directly jump to the section about [Method comparison for a real Hazard object](#real-hazard-object)."
+    "We first explain the methods functionality and options using a mock Hazard object such that the computation can be easily followed. Further below, we apply the methods to realistic Hazard and Impact objects. If you are already familiar with local exceedance values and return values, you can directly jump to the section about [Method comparison for a realistic Hazard object](#method-comparison-for-a-realistic-hazard-object)."
    ]
   },
   {
@@ -30,7 +30,7 @@
    "source": [
     "### Define a mock Hazard object\n",
     "\n",
-    "We define a simple mock TC Hazard object with which we will demonstrate the methods and their different parameter choices. The Hazard object consists of two events and has a spatial extend of four centroids, A, B, C and D. The first event has a (estimated) frequency of 9 times every 100years, and the second even has a (estimated) frequency of once every 100years. The two events have the following spatial intensity pattern (in unit m/s)\n",
+    "We define a simple mock TC Hazard object with which we will demonstrate the methods and their different parameter choices. The Hazard object consists of two events and has a spatial extent of four centroids, A, B, C and D. The first event has a (estimated) frequency of 9 times every 100years, and the second even has a (estimated) frequency of once every 100years. The two events have the following spatial intensity pattern (in unit m/s)\n",
     "| event_id | centroid A | centroid B | centroid C | centroid D |\n",
     "| ---:     | ---:       | ---:       | ---:       | ---:       |\n",
     "| 1        | 0          | 0          | 10         | 50         |\n",
@@ -100,7 +100,7 @@
     "\n",
     "Given the information of the Hazard object, which hazard intensity do we expect at each centroid to reoccur at a given return period? For instance, we could ask which intensity to expect every 5, 30, and 150 years. This question is addressed by the method `Hazard.local_exceedance_intensity()` which we will explain in the following, including different parameter settings one can choose from.\n",
     "\n",
-    "To compute which intensity to expect at a centroid for a given return period, we have to infer from the Hazard object how often different intensities are exceeded. To do so, we sort the events according to their intensity at the centroid, and then, for each intensity, sum the frequencies of the events that exceed this intensity. This resulting cumulative frequency for each intensity then yields the intensitiy's return period as one over the cumulative frequency. Finally, as we see below, the return periods for new intensities have to be inter- and extrapolated from the Hazard objects data.\n",
+    "To compute which intensity to expect at a centroid for a given return period, we have to infer from the Hazard object how often different intensities are exceeded. To do so, we sort the events according to their intensity at the centroid, and then, for each intensity, sum the frequencies of the events that exceed this intensity. This resulting cumulative frequency for each intensity then yields the intensity's return period as one over the cumulative frequency. Finally, as we see below, the return periods for new intensities have to be inter- and extrapolated from the Hazard objects data.\n",
     "\n",
     "**Examplary calculation for centroid D**\n",
     "\n",
@@ -326,7 +326,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Method comparison for a real Hazard object\n",
+    "## Method comparison for a realistic Hazard object\n",
     "\n",
     "We now showcase the different settings for `Hazard.local_exceedance_intensity()` with a real example (historic tropical cyclones in Florida from 1990 to 2004). First, we read in the hazard object.\n"
    ]