diff --git a/Pipfile b/Pipfile
index 80141836..567b8974 100644
--- a/Pipfile
+++ b/Pipfile
@@ -6,7 +6,7 @@ name = "pypi"
 [packages]
 affine = "==2.3.0"
 numpy = "==1.22.0"
-pydantic = "==1.9.0"
+pydantic = "==2.4.2"
 python-dotenv = "==0.19.2"
 requests = "==2.27.1"
 scipy = "==1.7.3"
diff --git a/Pipfile.lock b/Pipfile.lock
index 4d880f73..5990ab1f 100644
--- a/Pipfile.lock
+++ b/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "34b11e3f01fe2bbc75a5d9c500e3a20a6e07fb300186698b9b8a64c2da20e660"
+            "sha256": "173c9dd806cde686f53d8da71d5ebe54009d37bfa0d70e7c7279b31f33fa78ba"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -26,103 +26,104 @@
         },
         "aiobotocore": {
             "hashes": [
-                "sha256:00fd7f43cc0484d8ed274fd0be492aa16a7fea679dbea96a602bb722ca4c2d22"
+                "sha256:00fd7f43cc0484d8ed274fd0be492aa16a7fea679dbea96a602bb722ca4c2d22",
+                "sha256:132a7ccae3bbd35d44dce84a0f4bd77cdac8653f676575afba10ce4879605836"
             ],
             "markers": "python_version >= '3.6'",
             "version": "==2.1.2"
         },
         "aiohttp": {
             "hashes": [
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             "markers": "python_version >= '3.6'",
-            "version": "==3.8.4"
+            "version": "==3.8.6"
         },
         "aioitertools": {
             "hashes": [
@@ -140,6 +141,14 @@
             "markers": "python_version >= '3.7'",
             "version": "==1.3.1"
         },
+        "annotated-types": {
+            "hashes": [
+                "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43",
+                "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"
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+            "version": "==0.6.0"
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                 "sha256:4aa4b9b649f85e3fcb343363d97564aa1fb62e249677f2e18a96765145cc0f6e"
@@ -148,19 +157,19 @@
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-            "version": "==4.0.2"
+            "markers": "python_version >= '3.7'",
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-            "version": "==22.2.0"
+            "markers": "python_version >= '3.7'",
+            "version": "==23.1.0"
         },
         "botocore": {
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@@ -172,11 +181,11 @@
         },
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@@ -262,101 +271,80 @@
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-            "version": "==1.3.3"
+            "markers": "python_version >= '3.8'",
+            "version": "==1.4.0"
         },
         "fsspec": {
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@@ -376,11 +364,11 @@
         },
         "importlib-metadata": {
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+            "version": "==6.8.0"
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@@ -536,26 +524,31 @@
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@@ -583,6 +576,7 @@
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@@ -666,48 +660,129 @@
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@@ -723,6 +798,7 @@
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@@ -731,6 +807,7 @@
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@@ -739,6 +816,7 @@
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@@ -774,15 +852,16 @@
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@@ -794,19 +873,19 @@
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@@ -975,80 +1054,79 @@
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+            "markers": "python_version >= '3.8'",
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-            "version": "==8.1.3"
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@@ -1060,34 +1138,35 @@
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@@ -1095,6 +1174,7 @@
                 "sha256:f84c2818376e66cf843d497486ea8fed8700b340f308f076c6fb1229dff318b6"
             ],
             "index": "pypi",
+            "markers": "python_full_version >= '3.8.0'",
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@@ -1107,35 +1187,37 @@
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@@ -1147,129 +1229,140 @@
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+                "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34",
+                "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43",
+                "sha256:c8098ddcc2a85b61647b2590f825f3db38891662cfc2fc776415143f599bb859",
+                "sha256:d2b04aac4d386b172d5b9692e2d2da8de7bfb6c387fa4f801fbf6fb2e6ba4673",
+                "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54",
+                "sha256:d858aa552c999bc8a8d57426ed01e40bef403cd8ccdd0fc5f6f04a00414cac2a",
+                "sha256:e7d73685e87afe9f3b36c799222440d6cf362062f78be1013661b00c5c6f678b",
+                "sha256:f003ed9ad21d6a4713f0a9b5a7a0a79e08dd0f221aff4525a2be4c346ee60aab",
+                "sha256:f22ac1c3cac4dbc50079e965eba2c1058622631e526bd9afd45fedd49ba781fa",
+                "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c",
+                "sha256:fca0e3a251908a499833aa292323f32437106001d436eca0e6e7833256674585",
+                "sha256:fd1592b3fdf65fff2ad0004b5e363300ef59ced41c2e6b3a99d4089fa8c5435d",
+                "sha256:fd66fc5d0da6d9815ba2cebeb4205f95818ff4b79c3ebe268e75d961704af52f"
             ],
             "markers": "python_version >= '3.6'",
-            "version": "==6.0"
+            "version": "==6.0.1"
         },
         "setuptools": {
             "hashes": [
-                "sha256:257de92a9d50a60b8e22abfcbb771571fde0dbf3ec234463212027a4eeecbe9a",
-                "sha256:e728ca814a823bf7bf60162daf9db95b93d532948c4c0bea762ce62f60189078"
+                "sha256:4ac1475276d2f1c48684874089fefcd83bd7162ddaafb81fac866ba0db282a87",
+                "sha256:b454a35605876da60632df1a60f736524eb73cc47bbc9f3f1ef1b644de74fd2a"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==67.6.1"
+            "markers": "python_version >= '3.8'",
+            "version": "==68.2.2"
         },
         "tomli": {
             "hashes": [
@@ -1281,27 +1374,28 @@
         },
         "tox": {
             "hashes": [
-                "sha256:6fa4dbd933d0e335b5392c81e9cd467630119b3669705dbad47814a93b6c9586",
-                "sha256:cd88e41aef9c71f0ba02b6d7939f102760b192b63458fbe04dbbaed82f7bf5f5"
+                "sha256:5039f68276461fae6a9452a3b2c7295798f00a0e92edcd9a3b78ba1a73577951",
+                "sha256:599af5e5bb0cad0148ac1558a0b66f8fff219ef88363483b8d92a81e4246f28f"
             ],
             "index": "pypi",
-            "version": "==4.4.11"
+            "markers": "python_version >= '3.8'",
+            "version": "==4.11.3"
         },
         "typing-extensions": {
             "hashes": [
-                "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb",
-                "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"
+                "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0",
+                "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"
             ],
-            "markers": "python_version >= '3.7'",
-            "version": "==4.5.0"
+            "markers": "python_version >= '3.8'",
+            "version": "==4.8.0"
         },
         "virtualenv": {
             "hashes": [
-                "sha256:31712f8f2a17bd06234fa97fdf19609e789dd4e3e4bf108c3da71d710651adbc",
-                "sha256:f50e3e60f990a0757c9b68333c9fdaa72d7188caa417f96af9e52407831a3b68"
+                "sha256:b80039f280f4919c77b30f1c23294ae357c4c8701042086e3fc005963e4e537b",
+                "sha256:e8361967f6da6fbdf1426483bfe9fca8287c242ac0bc30429905721cefbff752"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==20.21.0"
+            "version": "==20.24.5"
         }
     }
 }
diff --git a/notebooks/vulnerability_onboarding/Wind/Table_A2_Impact_Function_Slope.csv b/notebooks/vulnerability_onboarding/Wind/Table_A2_Impact_Function_Slope.csv
new file mode 100644
index 00000000..c6ff7ec6
--- /dev/null
+++ b/notebooks/vulnerability_onboarding/Wind/Table_A2_Impact_Function_Slope.csv
@@ -0,0 +1,12 @@
+region,nb_countries,nb_events,vhalf_a,vhalf_b,vhalf_c,rmsf_a,rmsf_b,rmsf_c,tdr_a,tdr_b,tdr_c
+NA1,21,73,74.7,59.6,66.3,11.8,9.8,10.3,0.68,1.44,1
+NA2,2,43,74.7,86,89.2,9.5,8.7,8.7,2.11,1.16,1
+NI,6,31,74.7,58.7,70.8,7.8,6,7.2,0.85,2.03,1
+OC,11,48,74.7,49.7,64.1,22.5,14.7,17.7,0.6,2.31,1
+SI,2,19,74.7,46.8,52.4,20.1,8.6,9.1,0.2,1.8,1
+WP1,4,43,74.7,56.7,66.4,15.2,11.3,12.6,0.62,2.05,1
+WP2,1,83,74.7,84.7,188.4,38.2,36.7,104.9,25.89,16.44,1
+WP3,1,69,74.7,80.2,112.8,15.2,14.8,20.5,5.32,3.83,1
+WP4,5,64,74.7,135.6,190.5,73.8,35.9,43.8,35.56,3.35,1
+Combined,53,473,74.7,–,–,22.2,16.8,24.4,4.69,2.15,1
+Global calibration,53,473,74.7,73.4,110.1,22.2,22.2,33.1,4.69,4.84,1
\ No newline at end of file
diff --git a/notebooks/vulnerability_onboarding/Wind/Table_S2_V_half_individual_fitting_per_event.csv b/notebooks/vulnerability_onboarding/Wind/Table_S2_V_half_individual_fitting_per_event.csv
new file mode 100644
index 00000000..36399467
--- /dev/null
+++ b/notebooks/vulnerability_onboarding/Wind/Table_S2_V_half_individual_fitting_per_event.csv
@@ -0,0 +1,474 @@
+EM_ID,ibtracsID,v_half_fitted [m/s],country,country_id,region,year,Reported_Damage [USD],reference_year,Normalized_Reported_Damage [USD],Simulated_Damage [USD],log_ratio,unique_ID
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\ No newline at end of file
diff --git a/notebooks/vulnerability_onboarding/Wind/onboard.ipynb b/notebooks/vulnerability_onboarding/Wind/onboard.ipynb
new file mode 100644
index 00000000..82a7d285
--- /dev/null
+++ b/notebooks/vulnerability_onboarding/Wind/onboard.ipynb
@@ -0,0 +1,266 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Regional tropical cyclone impact functions\n",
+    "\n",
+    "### CITATION\n",
+    "Eberenz S, Lüthi S, Bresch DN. Regional tropical cyclone impact functions for globally consistent risk assessments. Natural Hazards and Earth System Sciences. 2021 Jan 29;21(1):393-415.\n",
+    "\n",
+    "### LINK\n",
+    "https://nhess.copernicus.org/articles/21/393/2021/\n",
+    "\n",
+    "### NOTES\n",
+    "The data is used to provide a 'generic asset' vulnerability distribution. The fitted results are copied into Table_A2_Impact_Function_Slope.csv. \n",
+    "(a) the global default impact function (uncalibrated), (b) calibrated by optimizing RMSF, and (c) calibrated by optimizing TDR. The regions NA1 to WP4 are defined in Table A1. The row “combined” summarizes results for all regions combined based on the regionalized calibration; the row “global calibration” is based on one unified global calibration based on all matched TC 473 events. RMSF: root-mean-squared fraction; TDR: total damage ratio.\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['NA1' 'NA2' 'NI' 'OC' 'SI' 'WP1' 'WP2' 'WP3' 'WP4' 'Combined'\n",
+      " 'Global calibration']\n",
+      "['59.6' '86' '58.7' '49.7' '46.8' '56.7' '84.7' '80.2' '135.6' '–' '73.4']\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv('Table_A2_Impact_Function_Slope.csv')\n",
+    "region = df[\"region\"].to_numpy()\n",
+    "vhalf = df[\"vhalf_b\"].to_numpy()\n",
+    "\n",
+    "\n",
+    "print(region)\n",
+    "print(vhalf)\n",
+    "#df = pd.read_csv('Table_S2_V_half_individual_fitting_per_event.csv')\n",
+    "#vhalf = df.where(df.region == \"WP2\").vhalf_fitted\n",
+    "#region = df[\"region\"].to_numpy()\n",
+    "#vhalf = df[\"vhalf_fitted\"].to_numpy()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([170., 103.,  61.,  36.,  34.,  10.,   8.,  15.,   8.,  28.]),\n",
+       " array([ 25.8 ,  55.79,  85.78, 115.77, 145.76, 175.75, 205.74, 235.73,\n",
+       "        265.72, 295.71, 325.7 ]),\n",
+       " <BarContainer object of 10 artists>)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "v_half = df[\"v_half_fitted [m/s]\"]  #df[df.region == \"WP2\"][\"v_half_fitted [m/s]\"]\n",
+    "\n",
+    "import matplotlib.pyplot as plot\n",
+    "plot.hist(v_half)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "103.40930232558141\n",
+      "[ 45.1 130.6]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(v_half.mean())\n",
+    "import numpy as np\n",
+    "print(np.quantile(v_half, [0.25, 0.75]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x149f14b50>]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "def vul(v, v_half):\n",
+    "    v_thresh = 25.7\n",
+    "    #v_half = 135.6 # wp4 74.7 135.6 190.5\n",
+    "    vn = np.where(v > v_thresh, v - v_thresh, 0) / (v_half - v_thresh)\n",
+    "    f = vn**3 / (1 + vn**3)\n",
+    "    return f\n",
+    "\n",
+    "v = np.arange(0, 90, 10)\n",
+    "fig, ax = plt.subplots() \n",
+    "#for item in v_half.to_numpy():\n",
+    "#    ax.plot(v, vul(v, item))\n",
+    "ax.plot(v, vul(v, 74.7))\n",
+    "ax.plot(v, vul(v, 190.5))\n",
+    "ax.plot(v, vul(v, 135.6))\n",
+    "#ax.plot(v, vul(v, 100))\n",
+    "#ax.plot(v, vul(v, 220))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([175.,  51.,  28.,  19.,  13.,  17.,  19.,  17.,  37.,  97.]),\n",
+       " array([0.00149235, 0.10134311, 0.20119387, 0.30104464, 0.4008954 ,\n",
+       "        0.50074616, 0.60059692, 0.70044769, 0.80029845, 0.90014921,\n",
+       "        0.99999998]),\n",
+       " <BarContainer object of 10 artists>)"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist([vul(60, item) for item in v_half.to_numpy()])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0       39.2\n",
+       "1      106.8\n",
+       "2       58.4\n",
+       "3       70.1\n",
+       "4       37.6\n",
+       "       ...  \n",
+       "468     58.9\n",
+       "469    270.0\n",
+       "470    325.7\n",
+       "471    285.9\n",
+       "472     44.1\n",
+       "Name: v_half_fitted [m/s], Length: 473, dtype: float64"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "v_half"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "physrisk-og59E7IU",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.13"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/setup.cfg b/setup.cfg
index 8e01c761..45bdad45 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -24,7 +24,7 @@ install_requires =
     numba==0.56.4
     numpy==1.22.0
     pillow==9.4.0
-    pydantic==1.9.0
+    pydantic==2.4.2
     python-dotenv==0.19.2
     requests==2.27.1
     scipy==1.7.3
diff --git a/src/physrisk/api/v1/common.py b/src/physrisk/api/v1/common.py
index ff3f4ed2..c31574cc 100644
--- a/src/physrisk/api/v1/common.py
+++ b/src/physrisk/api/v1/common.py
@@ -33,8 +33,8 @@ class Asset(BaseModel):
     asset_class: str = Field(
         description="name of asset class; corresponds to physrisk class names, e.g. PowerGeneratingAsset"
     )
-    type: Optional[str] = Field(description="Type of the asset <level_1>/<level_2>/<level_3>")
-    location: Optional[str]
+    type: Optional[str] = Field(None, description="Type of the asset <level_1>/<level_2>/<level_3>")
+    location: Optional[str] = None
     latitude: float = Field(description="Latitude in degrees")
     longitude: float = Field(description="Longitude in degrees")
 
diff --git a/src/physrisk/api/v1/exposure_req_resp.py b/src/physrisk/api/v1/exposure_req_resp.py
index ac549e71..29d7d037 100644
--- a/src/physrisk/api/v1/exposure_req_resp.py
+++ b/src/physrisk/api/v1/exposure_req_resp.py
@@ -10,7 +10,9 @@ class AssetExposureRequest(BaseModel):
     """Impact calculation request."""
 
     assets: Assets
-    calc_settings: CalcSettings = Field(default_factory=CalcSettings, description="Interpolation method.")
+    calc_settings: CalcSettings = Field(
+        default_factory=CalcSettings, description="Interpolation method."  # type:ignore
+    )
     scenario: str = Field("rcp8p5", description="Name of scenario ('rcp8p5')")
     year: int = Field(
         2050,
diff --git a/src/physrisk/api/v1/hazard_data.py b/src/physrisk/api/v1/hazard_data.py
index cd2e7210..4f2ba548 100644
--- a/src/physrisk/api/v1/hazard_data.py
+++ b/src/physrisk/api/v1/hazard_data.py
@@ -59,7 +59,7 @@ class Scenario(BaseModel):
 
     id: str
     years: List[int]
-    periods: Optional[List[Period]]
+    # periods: Optional[List[Period]]
 
 
 def expanded(item: str, key: str, param: str):
@@ -89,7 +89,7 @@ class HazardResource(BaseModel):
     description: str = Field(
         description="Brief description in mark down of the indicator and model that generated the indicator."
     )
-    map: Optional[MapInfo] = Field(description="Optional information used for display of the indicator in a map.")
+    map: Optional[MapInfo] = Field(None, description="Optional information used for display of the indicator in a map.")
     scenarios: List[Scenario] = Field(description="Climate change scenarios for which the indicator is available.")
     units: str = Field(description="Units of the hazard indicator.")
 
@@ -112,13 +112,13 @@ def expand_resource(
     resource: HazardResource, keys: List[str], params: Dict[str, List[str]]
 ) -> Iterable[HazardResource]:
     if len(keys) == 0:
-        yield resource.copy(deep=True, update={"params": {}})
+        yield resource.model_copy(deep=True, update={"params": {}})
     else:
         keys = keys.copy()
         key = keys.pop()
         for item in expand_resource(resource, keys, params):
             for param in params[key]:
-                yield item.copy(
+                yield item.model_copy(
                     deep=True,
                     update={
                         "indicator_id": expand(item.indicator_id, key, param),
@@ -128,7 +128,7 @@ def expand_resource(
                         "map": None
                         if item.map is None
                         else (
-                            item.map.copy(
+                            item.map.model_copy(
                                 deep=True,
                                 update={"path": expand(item.map.path if item.map.path is not None else "", key, param)},
                             )
@@ -148,9 +148,9 @@ class InventorySource(Flag):
 
 
 class HazardAvailabilityRequest(BaseModel):
-    types: Optional[List[str]]  # e.g. ["RiverineInundation"]
+    types: Optional[List[str]] = []  # e.g. ["RiverineInundation"]
     sources: Optional[List[str]] = Field(
-        description="Sources of inventory, can be 'embedded', 'hazard' or 'hazard_test'."
+        None, description="Sources of inventory, can be 'embedded', 'hazard' or 'hazard_test'."
     )
 
 
@@ -171,11 +171,11 @@ class HazardDataRequestItem(BaseModel):
     longitudes: List[float]
     latitudes: List[float]
     request_item_id: str
-    hazard_type: Optional[str]  # e.g. RiverineInundation
-    event_type: Optional[str]  # e.g. RiverineInundation; deprecated: use hazard_type
+    hazard_type: Optional[str] = None  # e.g. RiverineInundation
+    event_type: Optional[str] = None  # e.g. RiverineInundation; deprecated: use hazard_type
     indicator_id: str
-    indicator_model_gcm: Optional[str]
-    path: Optional[str]
+    indicator_model_gcm: Optional[str] = ""
+    path: Optional[str] = None
     scenario: str  # e.g. rcp8p5
     year: int
 
@@ -188,7 +188,7 @@ class HazardDataRequest(BaseHazardRequest):
 class HazardDataResponseItem(BaseModel):
     intensity_curve_set: List[IntensityCurve]
     request_item_id: str
-    event_type: str
+    event_type: Optional[str]
     model: str
     scenario: str
     year: int
diff --git a/src/physrisk/api/v1/impact_req_resp.py b/src/physrisk/api/v1/impact_req_resp.py
index 957420e6..592444ab 100644
--- a/src/physrisk/api/v1/impact_req_resp.py
+++ b/src/physrisk/api/v1/impact_req_resp.py
@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import List, Optional
+from typing import Dict, List, Optional
 
 from pydantic import BaseModel, Field
 
@@ -14,7 +14,9 @@ class AssetImpactRequest(BaseModel):
     """Impact calculation request."""
 
     assets: Assets
-    calc_settings: CalcSettings = Field(default_factory=CalcSettings, description="Interpolation method.")
+    calc_settings: CalcSettings = Field(
+        default_factory=CalcSettings, description="Interpolation method."  # type:ignore
+    )
     include_asset_level: bool = Field(True, description="If true, include asset-level impacts.")
     include_measures: bool = Field(True, description="If true, include measures.")
     include_calc_details: bool = Field(True, description="If true, include impact calculation details.")
@@ -25,32 +27,73 @@ class AssetImpactRequest(BaseModel):
     )
 
 
-# region Response
+class Category(int, Enum):
+    NODATA = 0
+    LOW = 1
+    MEDIUM = 2
+    HIGH = 3
+    REDFLAG = 4
+
+
+class RiskMeasureDefinition(BaseModel):
+    measure_id: str = Field(None, description="Identifier for the risk measure.")
+    label: str = Field(
+        "<short description of the measure, e.g. fractional loss for 1-in-100 year event.",
+        description="Value of the score.",
+    )
+    description: str
+
+
+class RiskScoreValue(BaseModel):
+    value: Category = Field("", description="Value of the score: red, amber, green, nodata.")
+    label: str = Field(
+        "", description="Short description of value, e.g. material increase in loss for 1-in-100 year event."
+    )
+    description: str = Field(
+        "",
+        description="Full description of value including criteria, \
+        e.g. change in fractional loss from 1-in-100 year event is greater than 10%.",
+    )
+
+
+class ScoreBasedRiskMeasureDefinition(BaseModel, frozen=True):
+    hazard_types: List[str] = Field([], description="Defines the hazards that the measure is used for.")
+    values: List[RiskScoreValue] = Field([], description="Defines the set of values that the score can take.")
+    child_measure_ids: List[str] = Field(
+        [], description="The identifiers of the risk measures used to calculate the score."
+    )
+
+    # should be sufficient to pass frozen=True, but does not seem to work (pydantic docs says feature in beta)
+    def __hash__(self):
+        return id(self)
+
+
+class RiskMeasureKey(BaseModel):
+    hazard_type: str
+    scenario_id: str
+    year: str
+    measure_id: str
 
 
-class Category(str, Enum):
-    NODATA = "NODATA"
-    LOW = "LOW"
-    MEDIUM = "MEDIUM"
-    HIGH = "HIGH"
-    REDFLAG = "REDFLAG"
+class RiskMeasuresForAssets(BaseModel):
+    key: RiskMeasureKey
+    scores: List[int] = Field(None, description="Identifier for the risk measure.")
+    measures_0: List[float]
+    measures_1: Optional[List[float]]
 
 
-class Indicator(BaseModel):
-    value: float
-    label: str
+class ScoreBasedRiskMeasureSetDefinition(BaseModel):
+    measure_set_id: str
+    asset_measure_ids_for_hazard: Dict[str, List[str]]
+    score_definitions: Optional[Dict[str, ScoreBasedRiskMeasureDefinition]]
 
 
-class RiskMeasureResult(BaseModel):
-    """Provides a risk category based on one or more risk indicators.
-    A risk indicator is a quantity derived from one or more vulnerability models,
-    e.g. the change in 1-in-100 year damage or disruption.
-    """
+class RiskMeasures(BaseModel):
+    """Risk measures"""
 
-    category: Category = Field(description="Result category.")
-    cat_defn: str = Field(description="Definition of the category for the particular indicator.")
-    indicators: List[Indicator]
-    summary: str = Field(description="Summary of the indicator.")
+    measures_for_assets: List[RiskMeasuresForAssets]
+    score_based_measure_set_defn: ScoreBasedRiskMeasureSetDefinition
+    measures_definitions: Optional[List[RiskMeasureDefinition]]
 
 
 class AcuteHazardCalculationDetails(BaseModel):
@@ -61,19 +104,19 @@ class AcuteHazardCalculationDetails(BaseModel):
     vulnerability_distribution: VulnerabilityDistrib
 
 
-class AssetSingleHazardImpact(BaseModel):
+class AssetSingleImpact(BaseModel):
     """Impact at level of single asset and single type of hazard."""
 
-    hazard_type: str = Field("", description="Type of the hazard.")
-    impact_type: str = Field(
+    hazard_type: Optional[str] = Field("", description="Type of the hazard.")
+    impact_type: Optional[str] = Field(
         "damage",
         description="""'damage' or 'disruption'. Whether the impact is fractional damage to the asset
-        ('damage') or disruption to the annual economic benefit obtained from the asset ('disruption'), expressed as
+        ('damage') or disruption to an operation, expressed as
         fractional decrease to an equivalent cash amount.""",
     )
-    risk_measure: Optional[RiskMeasureResult]
-    impact_distribution: Distribution
-    impact_exceedance: ExceedanceCurve
+    year: Optional[str] = None
+    impact_distribution: Optional[Distribution]
+    impact_exceedance: Optional[ExceedanceCurve]
     impact_mean: float
     impact_std_deviation: float
     calc_details: Optional[AcuteHazardCalculationDetails] = Field(
@@ -93,13 +136,11 @@ class AssetLevelImpact(BaseModel):
         description="""Asset identifier; will appear if provided in the request
         otherwise order of assets in response is identical to order of assets in request.""",
     )
-    impacts: List[AssetSingleHazardImpact] = Field([], description="Impacts for each hazard type.")
+    impacts: List[AssetSingleImpact] = Field([], description="Impacts for each hazard type.")
 
 
 class AssetImpactResponse(BaseModel):
     """Response to impact request."""
 
-    asset_impacts: List[AssetLevelImpact]
-
-
-# endregion
+    asset_impacts: Optional[List[AssetLevelImpact]] = None
+    risk_measures: Optional[RiskMeasures] = None
diff --git a/src/physrisk/data/inventory.py b/src/physrisk/data/inventory.py
index 4615d869..f4ab6246 100644
--- a/src/physrisk/data/inventory.py
+++ b/src/physrisk/data/inventory.py
@@ -6,7 +6,7 @@
 from collections import defaultdict
 from typing import DefaultDict, Dict, Iterable, List, Tuple
 
-from pydantic import parse_obj_as
+from pydantic import TypeAdapter, parse_obj_as
 
 import physrisk.data.colormap_provider as colormap_provider
 import physrisk.data.static.hazard
@@ -50,7 +50,7 @@ class EmbeddedInventory(Inventory):
 
     def __init__(self):
         with importlib.resources.open_text(physrisk.data.static.hazard, "inventory.json") as f:
-            models = parse_obj_as(HazardModels, json.load(f)).resources
+            models = TypeAdapter(HazardModels).validate_python(json.load(f)).resources
             expanded_models = expand(models)
             super().__init__(expanded_models)
 
diff --git a/src/physrisk/data/inventory_reader.py b/src/physrisk/data/inventory_reader.py
index 8d044143..cffb0987 100644
--- a/src/physrisk/data/inventory_reader.py
+++ b/src/physrisk/data/inventory_reader.py
@@ -4,7 +4,7 @@
 
 import s3fs
 from fsspec import AbstractFileSystem
-from pydantic import BaseModel, parse_obj_as
+from pydantic import BaseModel, TypeAdapter
 
 from physrisk.api.v1.hazard_data import HazardResource
 
@@ -48,7 +48,7 @@ def read(self, path: str) -> List[HazardResource]:
         if not self._fs.exists(self._full_path(path)):
             return []
         json_str = self.read_json(path)
-        models = parse_obj_as(HazardModels, json.loads(json_str)).resources
+        models = TypeAdapter(HazardModels).validate_python(json.loads(json_str)).resources
         return models
 
     def read_description_markdown(self, paths: List[str]) -> Dict[str, str]:
@@ -73,7 +73,7 @@ def append(self, path: str, hazard_models: Iterable[HazardResource]):
         for model in hazard_models:
             combined[model.key()] = model
         models = HazardModels(resources=list(combined.values()))
-        json_str = json.dumps(models.dict())
+        json_str = json.dumps(models.model_dump())
         with self._fs.open(self._full_path(path), "w") as f:
             f.write(json_str)
 
diff --git a/src/physrisk/hazard_models/core_hazards.py b/src/physrisk/hazard_models/core_hazards.py
index 72697b90..d398bbcc 100644
--- a/src/physrisk/hazard_models/core_hazards.py
+++ b/src/physrisk/hazard_models/core_hazards.py
@@ -17,11 +17,14 @@ def first(self):
     def match(self, hint: HazardDataHint):
         return next(r for r in self.resources if r.path == hint.path)
 
-    def with_model_gcm(self, gcm):
+    def with_group_id(self, group_id: str):
+        return ResourceSubset(r for r in self.resources if r.group_id == group_id)
+
+    def with_model_gcm(self, gcm: str):
         return ResourceSubset(r for r in self.resources if r.indicator_model_gcm == gcm)
 
-    def with_model_id(self, gcm):
-        return ResourceSubset(r for r in self.resources if r.indicator_model_id == gcm)
+    def with_model_id(self, model_id: str):
+        return ResourceSubset(r for r in self.resources if r.indicator_model_id == model_id)
 
 
 class ResourceSelector(Protocol):
@@ -58,7 +61,7 @@ def source_paths(self) -> Dict[type, SourcePath]:
             )
         return source_paths
 
-    def _add_selector(self, hazard_type: type, indicator_id: str, selector: ResourceSelector):
+    def add_selector(self, hazard_type: type, indicator_id: str, selector: ResourceSelector):
         self._selectors[ResourceSelectorKey(hazard_type, indicator_id)] = selector
 
     def _get_resource_source_path(self, hazard_type: str):
@@ -90,10 +93,10 @@ class CoreInventorySourcePaths(InventorySourcePaths):
     def __init__(self, inventory: Inventory):
         super().__init__(inventory)
         for indicator_id in ["mean_work_loss/low", "mean_work_loss/medium", "mean_work_loss/high"]:
-            self._add_selector(ChronicHeat, indicator_id, self._select_chronic_heat)
-        self._add_selector(ChronicHeat, "mean/degree/days/above/32c", self._select_chronic_heat)
-        self._add_selector(RiverineInundation, "flood_depth", self._select_riverine_inundation)
-        self._add_selector(CoastalInundation, "flood_depth", self._select_coastal_inundation)
+            self.add_selector(ChronicHeat, indicator_id, self._select_chronic_heat)
+        self.add_selector(ChronicHeat, "mean/degree/days/above/32c", self._select_chronic_heat)
+        self.add_selector(RiverineInundation, "flood_depth", self._select_riverine_inundation)
+        self.add_selector(CoastalInundation, "flood_depth", self._select_coastal_inundation)
 
     def resources_with(self, *, hazard_type: type, indicator_id: str):
         return ResourceSubset(self._inventory.resources_by_type_id[(hazard_type.__name__, indicator_id)])
@@ -146,5 +149,9 @@ def cmip6_scenario_to_rcp(scenario: str):
         return scenario
 
 
+def get_default_source_path_provider(inventory: Inventory = EmbeddedInventory()):
+    return CoreInventorySourcePaths(inventory)
+
+
 def get_default_source_paths(inventory: Inventory = EmbeddedInventory()):
     return CoreInventorySourcePaths(inventory).source_paths()
diff --git a/src/physrisk/kernel/calculation.py b/src/physrisk/kernel/calculation.py
index 4fa679c8..46789da5 100644
--- a/src/physrisk/kernel/calculation.py
+++ b/src/physrisk/kernel/calculation.py
@@ -29,7 +29,10 @@ def get_default_vulnerability_models() -> Dict[type, Sequence[VulnerabilityModel
     """Get default exposure/vulnerability models for different asset types."""
     return {
         PowerGeneratingAsset: [pgam.InundationModel()],
-        RealEstateAsset: [RealEstateCoastalInundationModel(), RealEstateRiverineInundationModel()],
+        RealEstateAsset: [
+            RealEstateCoastalInundationModel(),
+            RealEstateRiverineInundationModel(),
+        ],
         IndustrialActivity: [ChronicHeatGZNModel()],
         ThermalPowerGeneratingAsset: [
             ThermalPowerGenerationCoastalInundationModel(),
diff --git a/src/physrisk/kernel/hazards.py b/src/physrisk/kernel/hazards.py
index 2bdb350b..e5799663 100644
--- a/src/physrisk/kernel/hazards.py
+++ b/src/physrisk/kernel/hazards.py
@@ -1,3 +1,4 @@
+import inspect
 import sys
 from enum import Enum
 from typing import cast
@@ -34,6 +35,11 @@ class ChronicHeat(Hazard):
     pass
 
 
+class ChronicWind(Hazard):
+    kind = HazardKind.chronic
+    pass
+
+
 class CombinedInundation(Hazard):
     kind = HazardKind.chronic
     pass
@@ -69,5 +75,11 @@ class Wind(Hazard):
     pass
 
 
+def all_hazards():
+    return [
+        obj for _, obj in inspect.getmembers(sys.modules[__name__]) if inspect.isclass(obj) and issubclass(obj, Hazard)
+    ]
+
+
 def hazard_class(name: str):
     return getattr(sys.modules[__name__], name)
diff --git a/src/physrisk/kernel/risk.py b/src/physrisk/kernel/risk.py
index 27e1ef78..30ca1ef3 100644
--- a/src/physrisk/kernel/risk.py
+++ b/src/physrisk/kernel/risk.py
@@ -1,8 +1,10 @@
-from typing import Dict, List, NamedTuple, Optional, Protocol, Sequence, Tuple
+from dataclasses import dataclass
+from typing import Dict, List, NamedTuple, Optional, Protocol, Sequence, Set, Tuple, Type, Union
 
-from physrisk.api.v1.impact_req_resp import RiskMeasureResult
+from physrisk.api.v1.impact_req_resp import Category, ScoreBasedRiskMeasureDefinition
 from physrisk.kernel.assets import Asset
 from physrisk.kernel.hazard_model import HazardModel
+from physrisk.kernel.hazards import Hazard, all_hazards
 from physrisk.kernel.impact import AssetImpactResult, calculate_impacts
 from physrisk.kernel.impact_distrib import ImpactDistrib
 from physrisk.kernel.vulnerability_model import VulnerabilityModelBase
@@ -63,11 +65,21 @@ class MeasureKey(NamedTuple):
     hazard_type: type
 
 
+@dataclass
+class Measure:
+    score: Category
+    measure_0: float
+    definition: ScoreBasedRiskMeasureDefinition  # reference to single instance of ScoreBasedRiskMeasureDefinition
+
+
 class RiskMeasureCalculator(Protocol):
-    def calc_measure(self, hazard_type: type, base_impact: ImpactDistrib, impact: ImpactDistrib) -> RiskMeasureResult:
+    def calc_measure(self, hazard_type: type, base_impact: ImpactDistrib, impact: ImpactDistrib) -> Measure:
+        ...
+
+    def get_definition(self, hazard_type: type) -> ScoreBasedRiskMeasureDefinition:
         ...
 
-    def supported_hazards(self) -> List[type]:
+    def supported_hazards(self) -> Set[type]:
         ...
 
 
@@ -78,6 +90,14 @@ def __init__(
         vulnerability_models: Dict[type, Sequence[VulnerabilityModelBase]],
         measure_calculators: Dict[type, RiskMeasureCalculator],
     ):
+        """Risk model that calculates risk measures at the asset level for a sequence
+        of assets.
+
+        Args:
+            hazard_model (HazardModel): The hazard model.
+            vulnerability_models (Dict[type, Sequence[VulnerabilityModelBase]]): Vulnerability models for asset types.
+            measure_calculators (Dict[type, RiskMeasureCalculator]): Risk measure calculators for asset types.
+        """
         super().__init__(hazard_model, vulnerability_models)
         self._measure_calculators = measure_calculators
 
@@ -85,9 +105,44 @@ def calculate_impacts(self, assets: Sequence[Asset], prosp_scens: Sequence[str],
         impacts = self._calculate_all_impacts(assets, prosp_scens, years)
         return impacts
 
+    def populate_measure_definitions(
+        self, assets: Sequence[Asset]
+    ) -> Tuple[Dict[Type[Hazard], List[str]], Dict[ScoreBasedRiskMeasureDefinition, str]]:
+        hazards = all_hazards()
+        # the identifiers of the score-based risk measures used for each asset, for each hazard type
+        measure_ids_for_hazard: Dict[Type[Hazard], List[str]] = {}
+        # one
+        calcs_by_asset = [self._measure_calculators.get(type(asset), None) for asset in assets]
+        used_calcs = {c for c in calcs_by_asset if c is not None}
+        # get all measures
+        measure_id_lookup = {
+            cal: f"measure_{i}"
+            for (i, cal) in enumerate(
+                set(
+                    item
+                    for item in (
+                        cal.get_definition(hazard_type=hazard_type) for hazard_type in hazards for cal in used_calcs
+                    )
+                    if item is not None
+                )
+            )
+        }
+
+        def get_measure_id(measure_calc: Union[RiskMeasureCalculator, None], hazard_type: type):
+            if measure_calc is None:
+                return "na"
+            measure = measure_calc.get_definition(hazard_type=hazard_type)
+            return measure_id_lookup[measure] if measure is not None else "na"
+
+        for hazard_type in hazards:
+            measure_ids = [get_measure_id(calc, hazard_type) for calc in calcs_by_asset]
+            measure_ids_for_hazard[hazard_type] = measure_ids
+        return measure_ids_for_hazard, measure_id_lookup
+
     def calculate_risk_measures(self, assets: Sequence[Asset], prosp_scens: Sequence[str], years: Sequence[int]):
         impacts = self._calculate_all_impacts(assets, prosp_scens, years)
-        measures: Dict[MeasureKey, RiskMeasureResult] = {}
+        measures: Dict[MeasureKey, Measure] = {}
+
         for asset in assets:
             if type(asset) not in self._measure_calculators:
                 continue
@@ -102,5 +157,5 @@ def calculate_risk_measures(self, assets: Sequence[Asset], prosp_scens: Sequence
                             impact = scenario_impacts[key].impact
                             risk_ind = measure_calc.calc_measure(hazard_type, base_impact, impact)
                             measures[MeasureKey(asset, prosp_scen, year, hazard_type)] = risk_ind
-                            # if the fractional loss is material and materially increases
+
         return impacts, measures
diff --git a/src/physrisk/kernel/vulnerability_model.py b/src/physrisk/kernel/vulnerability_model.py
index e7a768d2..e458c642 100644
--- a/src/physrisk/kernel/vulnerability_model.py
+++ b/src/physrisk/kernel/vulnerability_model.py
@@ -1,7 +1,7 @@
 import importlib.resources
 import json
 from abc import ABC, abstractmethod
-from typing import Iterable, List, Optional, Protocol, Tuple, Union
+from typing import Iterable, List, Optional, Protocol, Sequence, Tuple, Union
 
 import numpy as np
 from scipy import stats
@@ -171,6 +171,7 @@ def get_distributions(
             self.hazard_type,
             intensity_bin_edges,
             self.impact_bin_edges,
+            # np.eye(8, 11)
             self.get_impact_curve(intensity_bin_centres, asset).to_prob_matrix(self.impact_bin_edges),
         )
 
@@ -226,29 +227,41 @@ def beta_distrib(mean, std, scaling_factor):
 
 
 class DeterministicVulnerabilityModel(VulnerabilityModelAcuteBase):
-    """A vulnerability model that requires only specification of a damage/disruption curve.
-    This simple model contains no uncertainty around damage/disruption."""
-
+  
     def __init__(
         self,
         *,
-        event_type: type,
-        intensities,
-        impacts,
-        indicator_id="",
+        hazard_type: type,
+        damage_curve_intensities: Sequence[float],
+        damage_curve_impacts: Sequence[float],
+        indicator_id: str,
         buffer_zone: Optional[HazardDataBufferZone] = None,
     ):
-        self.event_type = event_type
-        self.intensities = intensities
-        self.impacts = impacts
-        self.indicator_id = indicator_id
+        """A vulnerability model that requires only specification of a damage/disruption curve.
+        This simple model contains no uncertainty around damage/disruption. The damage curve is passed via the
+        constructor. The edges of the (hazard) intensity bins are determined by the granularity of
+        the hazard data itself. The impact bin edges are inferred from the intensity bin edges, by
+        looking up the impact corresponding to the hazard indicator intensity from the damage curve.
+
+            Args:
+                event_type (type): _description_
+                damage_curve_intensities (Sequence[float]): Intensities
+                (i.e. hazard indicator values) of the damage/disruption (aka impact) curve.
+                damage_curve_impacts (Sequence[float]): Fractional damage to asset/disruption
+                to operation resulting from a hazard of the corresponding intensity.
+                indicator_id (str): ID of the hazard indicator to which this applies. Defaults to "".
+                buffer_zone (Optional[HazardDataBufferZone]): Delimitation of the area for the hazard data.
+        """
+        super().__init__(indicator_id=indicator_id, hazard_type=hazard_type)
+        self.damage_curve_intensities = damage_curve_intensities
+        self.damage_curve_impacts = damage_curve_impacts
         self.buffer_zone = buffer_zone
 
     def get_data_requests(
         self, asset: Asset, *, scenario: str, year: int
     ) -> Union[HazardDataRequest, Iterable[HazardDataRequest]]:
         return HazardDataRequest(
-            self.event_type,
+            self.hazard_type,
             asset.longitude,
             asset.latitude,
             scenario=scenario,
@@ -266,10 +279,14 @@ def get_distributions(
         intensity_curve = ExceedanceCurve(1.0 / event_data.return_periods, event_data.intensities)
         intensity_bin_edges, probs = intensity_curve.get_probability_bins()
 
-        impact_bins_edges = np.interp(intensity_bin_edges, self.intensities, self.impacts)
+        # look up the impact bin edges
+        impact_bins_edges = np.interp(intensity_bin_edges, self.damage_curve_intensities, self.damage_curve_impacts)
 
+        # the vulnerability distribution probabilities are an identity matrix:
+        # we assume that if the intensity falls within a certain bin then the impacts *will* fall within the
+        # bin where the edges are obtained by applying the damage curve to the intensity bin edges.
         vul = VulnerabilityDistrib(
-            type(self.event_type), intensity_bin_edges, impact_bins_edges, np.eye(len(impact_bins_edges) - 1)
+            type(self.hazard_type), intensity_bin_edges, impact_bins_edges, np.eye(len(impact_bins_edges) - 1)
         )
-        event = HazardEventDistrib(type(self.event_type), intensity_bin_edges, probs)
+        event = HazardEventDistrib(type(self.hazard_type), intensity_bin_edges, probs)
         return vul, event
diff --git a/src/physrisk/requests.py b/src/physrisk/requests.py
index 2717202a..2a560aa1 100644
--- a/src/physrisk/requests.py
+++ b/src/physrisk/requests.py
@@ -2,7 +2,7 @@
 import json
 from importlib import import_module
 from pathlib import PosixPath
-from typing import Any, Dict, List, Optional, cast
+from typing import Any, Dict, List, Optional, Sequence, Type, cast
 
 import numpy as np
 
@@ -16,7 +16,8 @@
 from physrisk.data.zarr_reader import ZarrReader
 from physrisk.hazard_models.core_hazards import get_default_source_paths
 from physrisk.kernel.exposure import JupterExposureMeasure, calculate_exposures
-from physrisk.kernel.risk import AssetLevelRiskModel, BatchId, MeasureKey
+from physrisk.kernel.hazards import all_hazards
+from physrisk.kernel.risk import AssetLevelRiskModel, BatchId, Measure, MeasureKey
 
 from .api.v1.hazard_data import (
     HazardAvailabilityRequest,
@@ -35,7 +36,12 @@
     AssetImpactResponse,
     AssetLevelImpact,
     Assets,
-    AssetSingleHazardImpact,
+    AssetSingleImpact,
+    RiskMeasureKey,
+    RiskMeasures,
+    RiskMeasuresForAssets,
+    ScoreBasedRiskMeasureDefinition,
+    ScoreBasedRiskMeasureSetDefinition,
 )
 from .data.image_creator import ImageCreator
 from .data.inventory import EmbeddedInventory, Inventory
@@ -66,16 +72,18 @@ def __init__(
     def get(self, *, request_id, request_dict):
         if request_id == "get_hazard_data":
             request = HazardDataRequest(**request_dict)
-            return json.dumps(_get_hazard_data(request, hazard_model=self.hazard_model).dict())  # , allow_nan=False)
+            return json.dumps(
+                _get_hazard_data(request, hazard_model=self.hazard_model).model_dump()
+            )  # , allow_nan=False)
         elif request_id == "get_hazard_data_availability":
             request = HazardAvailabilityRequest(**request_dict)
-            return json.dumps(_get_hazard_data_availability(request, self.inventory, self.colormaps).dict())
+            return json.dumps(_get_hazard_data_availability(request, self.inventory, self.colormaps).model_dump())
         elif request_id == "get_hazard_data_description":
             request = HazardDescriptionRequest(**request_dict)
             return json.dumps(_get_hazard_data_description(request).dict())
         elif request_id == "get_asset_exposure":
             request = AssetExposureRequest(**request_dict)
-            return json.dumps(_get_asset_exposures(request, self.hazard_model).dict(exclude_none=True))
+            return json.dumps(_get_asset_exposures(request, self.hazard_model).model_dump(exclude_none=True))
         elif request_id == "get_asset_impact":
             request = AssetImpactRequest(**request_dict)
             return dumps(_get_asset_impacts(request, self.hazard_model).dict())
@@ -205,9 +213,9 @@ def _get_hazard_data(request: HazardDataRequest, hazard_model: HazardModel):
         intensity_curves = [
             IntensityCurve(intensities=list(resp.intensities), return_periods=list(resp.return_periods))
             if isinstance(resp, hmHazardEventDataResponse)
-            else IntensityCurve(intensities=[resp.parameter], return_periods=[])
+            else IntensityCurve(intensities=[float(resp.parameter)], return_periods=[])
             if isinstance(resp, HazardParameterDataResponse)
-            else None
+            else IntensityCurve(intensities=[], return_periods=[])
             for resp in resps
         ]
         response.items.append(
@@ -271,18 +279,17 @@ def _get_asset_impacts(request: AssetImpactRequest, hazard_model: HazardModel):
     years = [request.year]
     if request.include_measures:
         batch_impacts, measures = risk_model.calculate_risk_measures(assets, scenarios, years)
+        measure_ids_for_asset, definitions = risk_model.populate_measure_definitions(assets)
+        risk_measures = _create_risk_measures(measures, measure_ids_for_asset, definitions, assets, scenarios, years)
     else:
         batch_impacts = risk_model.calculate_impacts(assets, scenarios, years)
-        measures = None
+        risk_measures = None
 
-    # results = calculate_impacts(
-    #    assets, hazard_model, vulnerability_models, scenario=request.scenario, year=request.year
-    # )
     results = batch_impacts[BatchId(scenarios[0], years[0])]
 
     # note that this does rely on ordering of dictionary (post 3.6)
-    impacts: Dict[Asset, List[AssetSingleHazardImpact]] = {}
-    for (asset, hazard_type), v in results.items():
+    impacts: Dict[Asset, List[AssetSingleImpact]] = {}
+    for (asset, _), v in results.items():
         # calculation details
         if v.event is not None and v.vulnerability is not None:
             hazard_exceedance = v.event.to_exceedance_curve()
@@ -302,11 +309,9 @@ def _get_asset_impacts(request: AssetImpactRequest, hazard_model: HazardModel):
             )
 
         impact_exceedance = v.impact.to_exceedance_curve()
-        measure_key = MeasureKey(asset, scenarios[0], years[0], v.impact.hazard_type)
-        hazard_impacts = AssetSingleHazardImpact(
+        hazard_impacts = AssetSingleImpact(
             hazard_type=v.impact.hazard_type.__name__,
             impact_type=v.impact.impact_type.name,
-            risk_measure=None if measures is None or measure_key not in measures else measures[measure_key],
             impact_exceedance=ExceedanceCurve(
                 values=impact_exceedance.values, exceed_probabilities=impact_exceedance.probs
             ),
@@ -320,7 +325,64 @@ def _get_asset_impacts(request: AssetImpactRequest, hazard_model: HazardModel):
 
     asset_impacts = [AssetLevelImpact(asset_id="", impacts=a) for a in impacts.values()]
 
-    return AssetImpactResponse(asset_impacts=asset_impacts)
+    return AssetImpactResponse(asset_impacts=asset_impacts, risk_measures=risk_measures)
+
+
+def _create_risk_measures(
+    measures: Dict[MeasureKey, Measure],
+    measure_ids_for_asset: Dict[Type[Hazard], List[str]],
+    definitions: Dict[ScoreBasedRiskMeasureDefinition, str],
+    assets: List[Asset],
+    scenarios: Sequence[str],
+    years: Sequence[int],
+) -> RiskMeasures:
+    """Prepare RiskMeasures object for (JSON) output from measure results.
+
+    Args:
+        measures (Dict[MeasureKey, Measure]): The score-based risk measures.
+        measure_ids_for_asset (Dict[Type[Hazard], List[str]]): IDs of the score-based risk measures
+            for each asset.
+        definitions (Dict[ScoreBasedRiskMeasureDefinition, str]): Map of the score-based risk measures
+            definitions to ID.
+        assets (List[Asset]): Assets.
+        scenarios (Sequence[str]): Scenario IDs.
+        years (Sequence[int]): Years.
+
+    Returns:
+        RiskMeasures: Output for writing to JSON.
+    """
+    hazard_types = all_hazards()
+    measure_set_id = "measure_set_1"
+    measures_for_assets: List[RiskMeasuresForAssets] = []
+    for hazard_type in hazard_types:
+        for scenario_id in scenarios:
+            for year in years:
+                # we calculate and tag results for each scenario, year and hazard
+                score_key = RiskMeasureKey(
+                    hazard_type=hazard_type.__name__, scenario_id=scenario_id, year=str(year), measure_id=measure_set_id
+                )
+                scores = [-1] * len(assets)
+                measures_0 = [float("nan")] * len(assets)
+                for i, asset in enumerate(assets):
+                    # look up result using the MeasureKey:
+                    measure_key = MeasureKey(asset=asset, prosp_scen=scenario_id, year=year, hazard_type=hazard_type)
+                    measure = measures.get(measure_key, None)
+                    if measure is not None:
+                        scores[i] = measure.score
+                        measures_0[i] = measure.measure_0
+                measures_for_assets.append(
+                    RiskMeasuresForAssets(key=score_key, scores=scores, measures_0=measures_0, measures_1=None)
+                )
+    score_based_measure_set_defn = ScoreBasedRiskMeasureSetDefinition(
+        measure_set_id=measure_set_id,
+        asset_measure_ids_for_hazard={k.__name__: v for k, v in measure_ids_for_asset.items()},
+        score_definitions={v: k for (k, v) in definitions.items()},
+    )
+    return RiskMeasures(
+        measures_for_assets=measures_for_assets,
+        score_based_measure_set_defn=score_based_measure_set_defn,
+        measures_definitions=None,
+    )
 
 
 def _get_example_portfolios() -> List[Assets]:
diff --git a/src/physrisk/risk_models/risk_models.py b/src/physrisk/risk_models/risk_models.py
index ee56da87..f66b511c 100644
--- a/src/physrisk/risk_models/risk_models.py
+++ b/src/physrisk/risk_models/risk_models.py
@@ -1,9 +1,9 @@
-from typing import List
+from typing import Set
 
-from physrisk.api.v1.impact_req_resp import Category, Indicator, RiskMeasureResult
-from physrisk.kernel.hazards import CoastalInundation, Hazard, HazardKind, RiverineInundation
+from physrisk.api.v1.impact_req_resp import Category, RiskScoreValue, ScoreBasedRiskMeasureDefinition
+from physrisk.kernel.hazards import CoastalInundation, RiverineInundation, Wind
 from physrisk.kernel.impact_distrib import ImpactDistrib
-from physrisk.kernel.risk import RiskMeasureCalculator
+from physrisk.kernel.risk import Measure, RiskMeasureCalculator
 
 
 class RealEstateToyRiskMeasures(RiskMeasureCalculator):
@@ -11,41 +11,75 @@ class RealEstateToyRiskMeasures(RiskMeasureCalculator):
 
     def __init__(self):
         self.model_summary = {"*Toy* model for real estate risk assessment."}
-        self._category_defns = {
-            Category.NODATA: "No information.",
-            Category.LOW: "Marginal impact on real estate valuation very unlikely under RCP 8.5.",
-            Category.MEDIUM: "Material marginal impact on real estate valuation unlikely under RCP 8.5.",
-            Category.HIGH: "Material marginal impact on real estate valuation possible under RCP 8.5.",
-            Category.REDFLAG: "Material marginal impact on real estate valuation likely under RCP 8.5 "
-            "with possible impact on availability of insurance.",
+        self.return_period = 100.0  # criteria based on 1 in 100-year flood or cyclone events
+        self.measure_thresholds = {
+            Category.REDFLAG: 0.3,
+            Category.HIGH: 0.1,
+            Category.MEDIUM: 0.05,
         }
+        definition = ScoreBasedRiskMeasureDefinition(
+            hazard_types=[RiverineInundation.__name__, CoastalInundation.__name__],
+            values=[
+                RiskScoreValue(
+                    value=Category.REDFLAG,
+                    label="Material marginal impact on valuation very likely.",
+                    description=self._description(Category.REDFLAG),
+                ),
+                RiskScoreValue(
+                    value=Category.HIGH,
+                    label="Material marginal impact on valuation likely.",
+                    description=self._description(Category.HIGH),
+                ),
+                RiskScoreValue(
+                    value=Category.MEDIUM,
+                    label="Marginal impact on valuation possible.",
+                    description=self._description(Category.MEDIUM),
+                ),
+                RiskScoreValue(
+                    value=Category.LOW,
+                    label="Marginal impact on valuation very unlikely.",
+                    description=self._description(Category.LOW),
+                ),
+                RiskScoreValue(value=Category.NODATA, label="No data.", description="No data."),
+            ],
+            child_measure_ids=["annual_loss_{return_period:0.0f}year"],
+        )
+        self.measure_definitions = [definition]
+        self._definition_lookup = {RiverineInundation: definition, CoastalInundation: definition}
 
-    def calc_measure(self, hazard_type: type, base_impact: ImpactDistrib, impact: ImpactDistrib) -> RiskMeasureResult:
-        if Hazard.kind(base_impact.hazard_type) == HazardKind.acute:
-            return_period = 100.0  # criterion based on 1 in 100-year flood events
-            histo_loss = base_impact.to_exceedance_curve().get_value(1.0 / return_period)
-            future_loss = impact.to_exceedance_curve().get_value(1.0 / return_period)
-            loss_increase = future_loss - histo_loss
-
-            if loss_increase > 0.3:
-                category = Category.REDFLAG
-            elif loss_increase > 0.1:
-                category = Category.HIGH
-            elif loss_increase > 0.05:
-                category = Category.MEDIUM
-            else:
-                category = Category.LOW
-
-            summary = (
-                f"Projected 1-in-{return_period:0.0f} year annual loss "
-                f"increases by {loss_increase*100:0.0f}% of asset value over historical baseline. "
+    def _description(self, category: Category):
+        return (
+            (
+                f"Projected 1-in-{self.return_period:0.0f} year annual loss "
+                f"increases by less than {self.measure_thresholds[Category.MEDIUM]*100:0.0f}% of asset value "
+                f"over historical baseline."
             )
-            cat_defn = self._category_defns[category]
-            indicator = Indicator(value=loss_increase, label=f"{loss_increase * 100:0.0f}%")
+            if category == Category.LOW
+            else (
+                f"Projected 1-in-{self.return_period:0.0f} year annual loss "
+                f"increases by at least {self.measure_thresholds[category]*100:0.0f}% of asset value over "
+                f"historical baseline."
+            )
+        )
+
+    def calc_measure(self, hazard_type: type, base_impact: ImpactDistrib, impact: ImpactDistrib) -> Measure:
+        return_period = 100.0  # criterion based on 1 in 100-year flood events
+        histo_loss = base_impact.to_exceedance_curve().get_value(1.0 / return_period)
+        future_loss = impact.to_exceedance_curve().get_value(1.0 / return_period)
+        loss_increase = future_loss - histo_loss
 
-            return RiskMeasureResult(category=category, cat_defn=cat_defn, indicators=[indicator], summary=summary)
+        if loss_increase > self.measure_thresholds[Category.REDFLAG]:
+            score = Category.REDFLAG
+        elif loss_increase > self.measure_thresholds[Category.HIGH]:
+            score = Category.HIGH
+        elif loss_increase > self.measure_thresholds[Category.MEDIUM]:
+            score = Category.MEDIUM
         else:
-            raise NotImplementedError()
+            score = Category.LOW
+        return Measure(score=score, measure_0=loss_increase, definition=self.get_definition(hazard_type))
+
+    def get_definition(self, hazard_type: type):
+        return self._definition_lookup.get(hazard_type, None)
 
-    def supported_hazards(self) -> List[type]:
-        return [RiverineInundation, CoastalInundation]
+    def supported_hazards(self) -> Set[type]:
+        return set([RiverineInundation, CoastalInundation, Wind])
diff --git a/src/physrisk/vulnerability_models/real_estate_models.py b/src/physrisk/vulnerability_models/real_estate_models.py
index e0f9b3bb..8e1f5b9c 100644
--- a/src/physrisk/vulnerability_models/real_estate_models.py
+++ b/src/physrisk/vulnerability_models/real_estate_models.py
@@ -9,8 +9,13 @@
 from physrisk.kernel.vulnerability_matrix_provider import VulnMatrixProvider
 from physrisk.kernel.vulnerability_model import VulnerabilityModel
 
-from ..kernel.hazards import CoastalInundation, RiverineInundation
-from ..kernel.vulnerability_model import applies_to_events, checked_beta_distrib, get_vulnerability_curves_from_resource
+from ..kernel.hazards import CoastalInundation, RiverineInundation, Wind
+from ..kernel.vulnerability_model import (
+    DeterministicVulnerabilityModel,
+    applies_to_events,
+    checked_beta_distrib,
+    get_vulnerability_curves_from_resource,
+)
 
 
 class RealEstateInundationModel(VulnerabilityModel):
@@ -123,3 +128,37 @@ def __init__(
             resource=resource,
             impact_bin_edges=impact_bin_edges,
         )
+
+
+class GenericTropicalCycloneModel(DeterministicVulnerabilityModel):
+    def __init__(self):
+        """A very simple generic tropical cyclone vulnerability model."""
+        v_half = 74.7  # m/s
+        intensities = np.arange(0, 100, 10)
+        impacts = self.wind_damage(intensities, v_half)
+        super().__init__(
+            hazard_type=Wind,
+            damage_curve_intensities=intensities,
+            damage_curve_impacts=impacts,
+            indicator_id="max_speed",
+        )
+
+    def wind_damage(self, v: np.ndarray, v_half: float):
+        """Calculates damage based on functional form of
+        Emanuel K. Global warming effects on US hurricane damage. Weather, Climate, and Society. 2011 Oct 1;3(4):261-8.
+        Using a threshold speed of 25.7 m/s.
+        A review of the origin of parameters is available in
+        Eberenz S, Lüthi S, Bresch DN. Regional tropical cyclone impact functions for
+        globally consistent risk assessments.
+        Natural Hazards and Earth System Sciences. 2021 Jan 29;21(1):393-415.
+        which also provides suggested region-specific variations.
+        Args:
+            v (np.ndarray[float]): Wind speeds at which to calculate the fractional damage.
+            v_half (float): The 'v_half' function parameter.
+
+        Returns:
+            np.ndarray[float]: Fractional damage.
+        """
+        v_thresh = 25.7  # m/s
+        vn = np.where(v > v_thresh, v - v_thresh, 0) / (v_half - v_thresh)
+        return vn**3 / (1 + vn**3)
diff --git a/src/test/api/test_data_requests.py b/src/test/api/test_data_requests.py
index 7aee8fab..56a7b906 100644
--- a/src/test/api/test_data_requests.py
+++ b/src/test/api/test_data_requests.py
@@ -1,4 +1,3 @@
-import json
 import unittest
 from test.api.container import TestContainer
 from test.base_test import TestWithCredentials
@@ -131,6 +130,13 @@ def test_zarr_reading_live(self):
         container = Container()
         requester = container.requester()
 
+        import json
+        from zipfile import ZipFile
+
+        with ZipFile("src/test/api/test_lat_lons.json.zip") as z:
+            with z.open("test_lat_lons.json") as f:
+                data = json.loads(f.read())
+
         request1 = {
             "items": [
                 {
@@ -145,6 +151,20 @@ def test_zarr_reading_live(self):
             ],
         }
 
+        request1 = {
+            "items": [
+                {
+                    "request_item_id": "test_inundation",
+                    "event_type": "ChronicHeat",
+                    "longitudes": data["longitudes"],
+                    "latitudes": data["latitudes"],
+                    "year": 2030,
+                    "scenario": "ssp585",
+                    "indicator_id": "mean_work_loss/high",
+                }
+            ],
+        }
+
         response_floor = requester.get(request_id="get_hazard_data", request_dict=request1)
         request1["interpolation"] = "linear"  # type: ignore
         response_linear = requester.get(request_id="get_hazard_data", request_dict=request1)
diff --git a/src/test/api/test_impact_requests.py b/src/test/api/test_impact_requests.py
index 49489243..6f0024d9 100644
--- a/src/test/api/test_impact_requests.py
+++ b/src/test/api/test_impact_requests.py
@@ -96,4 +96,6 @@ def test_example_portfolios(self):
             container = Container()
             requester = container.requester()
             response = requester.get(request_id="get_asset_impact", request_dict=request_dict)
+            with open("out.json", "w") as f:
+                f.write(response)
             assert response is not None
diff --git a/src/test/api/test_lat_lons.json.zip b/src/test/api/test_lat_lons.json.zip
new file mode 100644
index 00000000..a8529d3d
Binary files /dev/null and b/src/test/api/test_lat_lons.json.zip differ
diff --git a/src/test/kernel/test_exposure.py b/src/test/kernel/test_exposure.py
index 49facf16..98dbdec3 100644
--- a/src/test/kernel/test_exposure.py
+++ b/src/test/kernel/test_exposure.py
@@ -36,7 +36,7 @@ def test_jupiter_exposure_service(self):
             ]
         )
         request = AssetExposureRequest(assets=assets_api, scenario="ssp585", year=2050)
-        response = requester.get(request_id="get_asset_exposure", request_dict=request.dict())
+        response = requester.get(request_id="get_asset_exposure", request_dict=request.model_dump())
         result = AssetExposureResponse(**json.loads(response)).items[0]
         expected = dict((k.__name__, v) for (k, v) in expected.items())
         for key in result.exposures.keys():
diff --git a/src/test/kernel/test_live_services.py b/src/test/kernel/test_live_services.py
new file mode 100644
index 00000000..f4adab07
--- /dev/null
+++ b/src/test/kernel/test_live_services.py
@@ -0,0 +1,21 @@
+import pytest
+import requests
+
+# url = "https://physrisk-api2-sandbox.apps.odh-cl1.apps.os-climate.org"
+url = "http://127.0.0.1:5000"
+
+
+@pytest.mark.skip("only as example")
+def test_live_exposure():
+    request = {
+        "assets": {
+            "items": [
+                {"asset_class": "Asset", "type": None, "location": None, "latitude": 34.556, "longitude": 69.4787}
+            ]
+        },
+        "calc_settings": {"hazard_interp": "floor"},
+        "scenario": "ssp585",
+        "year": 2050,
+    }
+    result = requests.post(url + "/api/get_asset_exposure", json=request)
+    print(result.json())
diff --git a/src/test/models/test_wind_models.py b/src/test/models/test_wind_models.py
new file mode 100644
index 00000000..4909331a
--- /dev/null
+++ b/src/test/models/test_wind_models.py
@@ -0,0 +1,93 @@
+import test.data.hazard_model_store as hms
+
+import numpy as np
+
+from physrisk.data.pregenerated_hazard_model import ZarrHazardModel
+from physrisk.hazard_models.core_hazards import ResourceSubset, get_default_source_path_provider
+from physrisk.kernel.assets import RealEstateAsset
+from physrisk.kernel.hazards import Wind
+from physrisk.kernel.impact import calculate_impacts
+from physrisk.vulnerability_models.real_estate_models import GenericTropicalCycloneModel
+
+
+def test_wind_real_estate_model():
+    scenario = "rcp8p5"
+    year = 2080
+    # mock some IRIS data for the calculation:
+    store, root = hms.zarr_memory_store()
+    return_periods = [
+        10.0,
+        20.0,
+        30.0,
+        40.0,
+        50.0,
+        60.0,
+        70.0,
+        80.0,
+        90.0,
+        100.0,
+        200.0,
+        300.0,
+        400.0,
+        500.0,
+        600.0,
+        700.0,
+        800.0,
+        900.0,
+        1000.0,
+    ]
+    intensity = np.array(
+        [
+            37.279999,
+            44.756248,
+            48.712502,
+            51.685001,
+            53.520000,
+            55.230000,
+            56.302502,
+            57.336250,
+            58.452499,
+            59.283749,
+            63.312500,
+            65.482498,
+            66.352501,
+            67.220001,
+            67.767502,
+            68.117500,
+            68.372498,
+            69.127502,
+            70.897499,
+        ]
+    )
+    shape, transform = hms.shape_transform_21600_43200(return_periods=return_periods)
+    path = f"wind/iris/v1/max_speed_{scenario}_{year}".format(scenario=scenario, year=year)
+    hms.add_curves(
+        root, hms.TestData.longitudes, hms.TestData.latitudes, path, shape, intensity, return_periods, transform
+    )
+
+    provider = get_default_source_path_provider()
+
+    def select_iris_osc(candidates: ResourceSubset, scenario: str, year: int, hint=None):
+        return candidates.with_group_id("iris_osc").first()
+
+    # specify use of IRIS (OSC contribution)
+    provider.add_selector(Wind, "max_speed", select_iris_osc)
+
+    hazard_model = ZarrHazardModel(source_paths=provider.source_paths(), store=store)
+    assets = [
+        RealEstateAsset(lat, lon, location="Asia", type="Buildings/Industrial")
+        for lon, lat in zip(hms.TestData.longitudes[0:1], hms.TestData.latitudes[0:1])
+    ]
+    vulnerability_models = {RealEstateAsset: [GenericTropicalCycloneModel()]}
+    results = calculate_impacts(assets, hazard_model, vulnerability_models, scenario=scenario, year=year)
+    # check calculation
+    cum_probs = 1.0 / np.array(return_periods)
+    probs = cum_probs[:-1] - cum_probs[1:]
+    model = GenericTropicalCycloneModel()
+    edges = np.interp(intensity, model.damage_curve_intensities, model.damage_curve_impacts)
+    centres = (edges[1:] + edges[:-1]) / 2
+    mean_check = np.sum(probs * centres)
+
+    impact_distrib = results[(assets[0], Wind)].impact
+    mean_impact = impact_distrib.mean_impact()
+    np.testing.assert_allclose(mean_impact, mean_check)
diff --git a/src/test/risk_models/test_risk_models.py b/src/test/risk_models/test_risk_models.py
index 75068321..be3e1ad5 100644
--- a/src/test/risk_models/test_risk_models.py
+++ b/src/test/risk_models/test_risk_models.py
@@ -5,18 +5,18 @@
 
 import numpy as np
 
+from physrisk.api.v1.impact_req_resp import RiskMeasureKey
 from physrisk.data.pregenerated_hazard_model import ZarrHazardModel
 from physrisk.hazard_models.core_hazards import get_default_source_paths
 from physrisk.kernel.assets import RealEstateAsset
 from physrisk.kernel.calculation import get_default_vulnerability_models
 from physrisk.kernel.hazards import CoastalInundation, RiverineInundation
 from physrisk.kernel.risk import AssetLevelRiskModel, MeasureKey
+from physrisk.requests import _create_risk_measures
 from physrisk.risk_models.risk_models import RealEstateToyRiskMeasures
 
 
 class TestRiskModels(unittest.TestCase):
-    """Tests RealEstateInundationModel."""
-
     def test_risk_indicator_model(self):
         source_paths = get_default_source_paths()
         scenarios = ["rcp8p5"]
@@ -50,8 +50,33 @@ def sp_coastal(scenario, year):
             for lon, lat in zip(TestData.longitudes[0:1], TestData.latitudes[0:1])
         ]
 
+        assets = [
+            RealEstateAsset(TestData.latitudes[0], TestData.longitudes[0], location="Asia", type="Buildings/Industrial")
+            for i in range(2)
+        ]
+
         model = AssetLevelRiskModel(
             hazard_model, get_default_vulnerability_models(), {RealEstateAsset: RealEstateToyRiskMeasures()}
         )
-        impacts, measures = model.calculate_risk_measures(assets, prosp_scens=scenarios, years=years)
-        print(measures[MeasureKey(assets[0], scenarios[0], years[0], RiverineInundation)])
+        measure_ids_for_asset, definitions = model.populate_measure_definitions(assets)
+        _, measures = model.calculate_risk_measures(assets, prosp_scens=scenarios, years=years)
+
+        # how to get a score using the MeasureKey
+        measure = measures[MeasureKey(assets[0], scenarios[0], years[0], RiverineInundation)]
+        score = measure.score
+        measure_0 = measure.measure_0
+
+        # packing up the risk measures, e.g. for JSON transmission:
+        risk_measures = _create_risk_measures(measures, measure_ids_for_asset, definitions, assets, scenarios, years)
+        # we still have a key, but no asset:
+        key = RiskMeasureKey(
+            hazard_type="RiverineInundation",
+            scenario_id=scenarios[0],
+            year=str(years[0]),
+            measure_id=risk_measures.score_based_measure_set_defn.measure_set_id,
+        )
+        item = next(m for m in risk_measures.measures_for_assets if m.key == key)
+        score2 = item.scores[0]
+        measure_0_2 = item.measures_0[0]
+        assert score == score2
+        assert measure_0 == measure_0_2