diff --git a/‎doc/tutorial/climada_hazard_entity_Crop.ipynb‎
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@@ -9,7 +9,9 @@
     "\n",
     "## Summary\n",
     "\n",
-    "This tutorial gives an overview of the modules in CLIMADA used to compute climate related risks to crop production on a 0.5° grid. The risk calculation is based on yearly crop yield as simulated by global gridded crop models (GGCMs) that are forced with climate variables such as temperature and water availability provided from climate model output or re-analysis data. To integrate this data into the CLIMADA logic, yearly crop yield relative to an historical mean is treated as a *hazard* (class *RelativeCropyield*). As an exposure, any kind of absolute yearly crop production can be provided. As a default, we estimate the exposure from a mean simulated crop yield normalized per country with crop statistics. This module currently supports four crop types (rice, wheat, soy, maize), each divided in full irrigation and no irrigation."
+    "This tutorial gives an overview of the modules in CLIMADA used to compute climate related risks to crop production on a 0.5° grid. The risk calculation is based on yearly crop yield as simulated by global gridded crop models (GGCMs) that are forced with climate variables such as temperature and water availability provided from climate model output or re-analysis data. To integrate this data into the CLIMADA logic, yearly crop yield relative to an historical mean is treated as a *hazard* (class *RelativeCropyield*).\n",
+    "\n",
+    "As an exposure, any kind of absolute yearly crop production can be provided (e.g. as tonnes per year or monetary value). As a default, we estimate the exposure from a mean simulated crop yield normalized per country with crop statistics. This module currently supports four crop types (rice, wheat, soy, maize), each divided in full irrigation and no irrigation."
    ]
   },
   {
@@ -27,12 +29,16 @@
     "\n",
     "The two classes *RelativeCropyield(Hazard)* and *CropProduction(Exposure)* can be combined to calculate climate impacts on crop production based on simulations data from global gridded crop models (GGCMs) within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, https://www.isimip.org/) as well as statistics from the Food and Agriculture Organization of the United Nations (FAO, http://www.fao.org/faostat/en/#home).\n",
     "\n",
+    "\n",
     "A relative crop yield (RC) hazard is generated by the class *RelativeCropyield(Hazard)* that extracts crop yield data simulated by global gridded crop models (GGCMs) within ISIMIP. The GGCMs are forced with the output from climate models (e.g. in ISIMIP2b, ISIMIP3b) or re-analyis data (ISIMIP2a, ISIMIP3a). The driving climate variables for crop yield are temoperature, water availability, CO2 concentrations, and nitrogen availability.\n",
     "\n",
+    "\n",
     "From ISIMIP, a variety of model runs with yearly crop yield data on a spatial resolution of 0.5° x 0.5° are available. Each run is based on one GGCM forced by a climate model output or re-analysis data. Runs are available for different crop types, model combinations, historical climate and future climate scenarios, and other model parameters. Additionally, land use data required for *CropProduction(Exposure)* is available from the ISIMIP input data.\n",
     "\n",
+    "\n",
     "*Hazard intensity* is defined as yearly crop yield relative to a historical mean simulated with the same model combination. Each model year represents one event in the hazard instance. The required data sets are available from https://esg.pik-potsdam.de/search/isimip/ (choose *Variable = yield* for crop yield and *landuse-15crops* for land use data).\n",
     "\n",
+    "\n",
     "In this tutorial we show how a *RelativeCropyield* and a *CropProduction* instance can be initiated and translated into socio-economic impacts in the form of (yearly) crop production losses / gains in tonnes or USD."
    ]
   },