Towards a global impact-based forecasting  model for tropical cyclones

Kooshki Forooshani, Mersedeh; van den Homberg, Marc; Kalimeri, Kyriaki; Kaltenbrunner, Andreas; Mejova, Yelena; Milano, Leonardo; Ndirangu, Pauline; Paolotti, Daniela; Teklesadik, Aklilu; Turner, Monica L.

doi:https://doi.org/10.5194/nhess-24-309-2024

Articles | Volume 24, issue 1

https://doi.org/10.5194/nhess-24-309-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Reducing the impacts of natural hazards through forecast-based...

https://doi.org/10.5194/nhess-24-309-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 1

Research article

|

01 Feb 2024

Research article |

| 01 Feb 2024

Towards a global impact-based forecasting model for tropical cyclones

Mersedeh Kooshki Forooshani, Marc van den Homberg, Kyriaki Kalimeri, Andreas Kaltenbrunner, Yelena Mejova, Leonardo Milano, Pauline Ndirangu, Daniela Paolotti, Aklilu Teklesadik, and Monica L. Turner

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Sep 2023	57	20	3	80
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Nov 2023	123	31	9	163
Dec 2023	46	30	4	80
Jan 2024	57	45	3	105
Feb 2024	434	59	8	501
Mar 2024	189	15	2	206
Apr 2024	141	18	5	164
May 2024	140	20	2	162
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Cumulative views and downloads (calculated since 29 Sep 2023)

Month	HTML	PDF	XML	Total
Sep 2023	57	20	3	80
Oct 2023	241	84	18	343
Nov 2023	123	31	9	163
Dec 2023	46	30	4	80
Jan 2024	57	45	3	105
Feb 2024	434	59	8	501
Mar 2024	189	15	2	206
Apr 2024	141	18	5	164
May 2024	140	20	2	162
Jun 2024	138	12	2	152
Jul 2024	131	15	8	154
Aug 2024	113	12	6	131
Sep 2024	113	21	8	142
Oct 2024	118	11	4	133
Nov 2024	42	1	0	43

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Short summary

We improve an existing impact forecasting model for the Philippines by transforming the target variable (percentage of damaged houses) to a fine grid, using only features which are globally available. We show that our two-stage model conserves the performance of the original and even has the potential to introduce savings in anticipatory action resources. Such model generalizability is important in increasing the applicability of such tools around the world.