Address review comments on hazard tutorial

Author: l-pierini

doc/user-guide/climada_hazard_Hazard.ipynb

@@ -7,16 +7,15 @@
     "# Hazard class\n",
     "\n",
     "## What is a hazard?\n",
-    "A hazard describes weather events such as storms, floods, droughts, or heat waves, both in terms of probability of occurrence as well as physical intensity.\n",
+    "A hazard describes climate and weather extremes such as storms, floods, droughts, or heat waves, in terms of events which have a physical intensity and a probability (in the frequentist sense) of occurrence. Each hazard event is represented by a geographical map of intensity expressed in a given unit (e.g., flood depth in meters, wind speed in m/s, or heat wave duration in number of days).\n",
     "\n",
     "## How are hazards embedded in the CLIMADA architecture?\n",
     "Hazards are defined by the base class `Hazard` which gathers the required attributes that enable the impact computation (such as centroids, frequency per event, and intensity per event and centroid), and common methods such as readers and visualization functions. \n",
     "\n",
     "Each hazard class collects observational data or model simulations and transforms them, if necessary, in order to construct a coherent event database. \n",
-    "Stochastic realizations can be generated by accounting for the frequency and key intensity characteristics (such as local water depth for floods or gust speed for storms) of the input events, producing a probabilistic ensemble for each.\n",
-    "CLIMADA provides therefore an event-based probabilistic approach which does not assume a-priori probability distributions. Note that one can also reduce the probabilistic approach to a deterministic approach (e.g., story-line or forecasting) by defining the frequency to be 1.\n",
+    "For certain hazards, dedicated subclasses exist, such as `TropicalCyclones` (see tutorial [TropCyclone](climada_hazard_TropCyclone.ipynb)), `Wildfires`, or `RiverFlood` which collect observational data or model simulations and transform them, if necessary, into a CLIMADA `Hazard` object.  Most of these data models are found in the [climada petals](https://climada-petals.readthedocs.io/en/latest/tutorial/hazard.html) repository. However, these specific classes are designed for targeted purposes and are not general data models; therefore, users should rely on appropriate external hazard data sources whenever possible.\n",
     "\n",
-    "Different hazards rely on different data sources, such as observational datasets (e.g., inventories or satellite images) or model simulations (e.g., synthetic tropical cyclone tracks). Similarly, the methods used to compute hazard attributes and generate a stochastic event ensemble depend on the hazard type. This information is defined in the corresponding Hazard-derived class (e.g. `TropCylcone` for tropical cyclones, explained in the tutorial [TropCyclone](climada_hazard_TropCyclone.ipynb))\n",
+    "CLIMADA provides an event-based probabilistic approach which does not assume a-priori probability distributions. Note that one can also reduce the probabilistic approach to a deterministic approach (e.g., story-line or forecasting) by defining the frequency to be 1. Consequently, the hazard representation can encompass probabilistic event sets, single events, storylines, climate-model or observational time series.\n",
     "\n",
     "When high-quality data or models describing hazard intensity and frequency are available for a specific region, they can be directly imported into the platform via the reader functions. This allows the hazard-modelling step of the risk analysis to be skipped (either partially or entirely), and enables seamless integration of CLIMADA with external data sources. Note that since the `Hazard` class is not an abstract class, any hazard that is not defined in CLIMADA can still be used by providing the `Hazard` attributes.\n",
     "\n",