You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Global data set of protection levels for riverine and coastal flood, based on the [FLOPROS database] (https://nhess.copernicus.org/articles/16/1049/2016/). For each of coastal and riverine inundation, the dataset provides for every location a minimum ("min") and maximum ("max") protection, specified as a return period in years; the min and max reflects in uncertainty in the protection level. The return period indicates that the location is protected against flood events with that return period (e.g. 100 years indicates that the location is protected against 1-in-100 year flood events). Finding the equivalent flood depth protection level additionally requires a flood depth indicator data set.
1
+
Global data set of protection levels for riverine and coastal flood, based on the [FLOPROS database] (<https://nhess.copernicus.org/articles/16/1049/2016/>). For each of coastal and riverine inundation, the dataset provides for every location a minimum ("min") and maximum ("max") protection, specified as a return period in years; the min and max reflects in uncertainty in the protection level. The return period indicates that the location is protected against flood events with that return period (e.g. 100 years indicates that the location is protected against 1-in-100 year flood events). Finding the equivalent flood depth protection level additionally requires a flood depth indicator data set.
Sparks, N., Toumi, R. The Imperial College Storm Model (IRIS) Dataset. *Sci Data***11**, 424 (2024). <https://doi.org/10.1038/s41597-024-03250-y>
1
+
Sparks, N., Toumi, R. The Imperial College Storm Model (IRIS) Dataset. _Sci Data_**11**, 424 (2024). <https://doi.org/10.1038/s41597-024-03250-y>
2
2
3
3
## The Imperial College Storm Model (IRIS) Dataset - Scientific Data
4
+
4
5
Assessing tropical cyclone risk on a global scale given the infrequency of landfalling tropical cyclones and the short period of reliable observations remains a challenge. Synthetic tropical cyclone datasets can help overcome these problems. Here we present a new global dataset created by IRIS, the ImpeRIal college Storm Model. IRIS is novel because, unlike other synthetic TC models, it only simulates the decay from the point of lifetime maximum intensity. This minimises the bias in the dataset. It takes input from 42 years of observed tropical cyclones and creates a 10,000 year synthetic dataset which is then validated against the observations. IRIS captures important statistical characteristics of the observed data. The return periods of the landfall maximum wind speed (1 minute sustained in m/s) are realistic globally. Climate model projections are used to adjust the life-time maximum intensity.
5
6
6
-
***Disclaimer***: There have been many improvements on the dataset. Contact Professor Toumi from the Imperial College London for improved data.
7
+
**_Disclaimer_**: There have been many improvements on the dataset. Contact Professor Toumi from the Imperial College London for improved data.
Copy file name to clipboardExpand all lines: src/hazard/onboard/wisc_european_winter_storm.md
+1-2Lines changed: 1 addition & 2 deletions
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -1,7 +1,6 @@
1
-
2
1
Maximum 10 metre 3 second gust peak wind speed (note 3 second average; by default physrisk wind speeds are 1 minute average) for different return periods, inferred from the Copernicus WISC European storm event set. This allows events and return period maps to be used consistently.
0 commit comments