Damage functions for climate-related hazards: unification and uncertainty analysis

Prahl, Boris F.; Rybski, Diego; Boettle, Markus; Kropp, Jürgen P.

doi:10.5194/nhess-16-1189-2016

Articles | Volume 16, issue 5

https://doi.org/10.5194/nhess-16-1189-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/nhess-16-1189-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 16, issue 5

Research article

|

25 May 2016

Research article |

| 25 May 2016

Damage functions for climate-related hazards: unification and uncertainty analysis

Boris F. Prahl, Diego Rybski, Markus Boettle, and Jürgen P. Kropp

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Total article views: 6,645 (including HTML, PDF, and XML)

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2,387	3,831	427	6,645	827	151	164

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XML: 427
Total: 6,645
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BibTeX: 151
EndNote: 164

Views and downloads (calculated since 12 Nov 2015)

Month	HTML	PDF	XML	Total
Nov 2015	100	64	3	167
Dec 2015	37	53	1	91
Jan 2016	27	12	0	39
Feb 2016	37	12	2	51
Mar 2016	15	11	0	26
Apr 2016	10	8	0	18
May 2016	152	65	0	217
Jun 2016	40	17	2	59
Jul 2016	26	13	2	41
Aug 2016	21	6	2	29
Sep 2016	27	10	11	48
Oct 2016	14	7	5	26
Nov 2016	13	13	4	30
Dec 2016	16	16	0	32
Jan 2017	14	37	6	57
Feb 2017	13	32	4	49
Mar 2017	28	35	11	74
Apr 2017	23	37	5	65
May 2017	28	22	8	58
Jun 2017	21	21	6	48
Jul 2017	16	22	4	42
Aug 2017	12	25	6	43
Sep 2017	24	25	2	51
Oct 2017	8	16	0	24
Nov 2017	19	20	4	43
Dec 2017	15	30	7	52
Jan 2018	24	25	4	53
Feb 2018	14	17	1	32
Mar 2018	13	29	2	44
Apr 2018	12	23	2	37
May 2018	8	7	0	15
Jun 2018	11	22	1	34
Jul 2018	19	25	2	46
Aug 2018	18	15	1	34
Sep 2018	10	14	4	28
Oct 2018	23	23	3	49
Nov 2018	16	15	3	34
Dec 2018	14	10	12	36
Jan 2019	11	7	7	25
Feb 2019	8	8	0	16
Mar 2019	10	16	5	31
Apr 2019	6	8	1	15
May 2019	11	8	1	20
Jun 2019	13	13	2	28
Jul 2019	9	8	3	20
Aug 2019	7	7	4	18
Sep 2019	6	12	23	41
Oct 2019	15	10	24	49
Nov 2019	6	5	7	18
Dec 2019	9	12	1	22
Jan 2020	8	17	4	29
Feb 2020	7	6	0	13
Mar 2020	15	10	1	26
Apr 2020	6	9	5	20
May 2020	5	12	7	24
Jun 2020	18	11	5	34
Jul 2020	36	28	21	85
Aug 2020	13	13	47	73
Sep 2020	13	9	13	35
Oct 2020	14	13	0	27
Nov 2020	11	13	0	24
Dec 2020	10	12	4	26
Jan 2021	20	14	6	40
Feb 2021	9	10	3	22
Mar 2021	7	14	3	24
Apr 2021	5	13	6	24
May 2021	4	9	6	19
Jun 2021	6	10	1	17
Jul 2021	11	18	1	30
Aug 2021	5	18	0	23
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Nov 2021	8	39	2	49
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Jan 2022	14	31	6	51
Feb 2022	13	44	2	59
Mar 2022	7	40	0	47
Apr 2022	24	22	3	49
May 2022	12	23	4	39
Jun 2022	36	27	2	65
Jul 2022	5	18	0	23
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Sep 2022	8	35	0	43
Oct 2022	43	23	0	66
Nov 2022	12	22	1	35
Dec 2022	9	41	0	50
Jan 2023	22	24	1	47
Feb 2023	20	47	2	69
Mar 2023	28	46	1	75
Apr 2023	9	45	1	55
May 2023	32	47	3	82
Jun 2023	44	38	0	82
Jul 2023	15	47	1	63
Aug 2023	14	39	2	55
Sep 2023	20	46	0	66
Oct 2023	17	63	0	80
Nov 2023	15	40	1	56
Dec 2023	12	60	1	73
Jan 2024	17	52	0	69
Feb 2024	20	78	0	98
Mar 2024	15	76	3	94
Apr 2024	38	84	5	127
May 2024	19	76	3	98
Jun 2024	25	64	4	93
Jul 2024	34	61	3	98
Aug 2024	30	41	4	75
Sep 2024	20	50	3	73
Oct 2024	22	96	1	119
Nov 2024	11	95	0	106
Dec 2024	8	70	1	79
Jan 2025	21	66	0	87
Feb 2025	39	89	1	129
Mar 2025	23	81	6	110
Apr 2025	22	59	1	82
May 2025	29	64	1	94
Jun 2025	52	61	0	113
Jul 2025	45	72	3	120
Aug 2025	30	38	0	68
Sep 2025	33	48	2	83
Oct 2025	34	66	1	101
Nov 2025	38	75	3	116
Dec 2025	7	12	0	19

Cumulative views and downloads (calculated since 12 Nov 2015)

Month	HTML	PDF	XML	Total
Nov 2015	100	64	3	167
Dec 2015	37	53	1	91
Jan 2016	27	12	0	39
Feb 2016	37	12	2	51
Mar 2016	15	11	0	26
Apr 2016	10	8	0	18
May 2016	152	65	0	217
Jun 2016	40	17	2	59
Jul 2016	26	13	2	41
Aug 2016	21	6	2	29
Sep 2016	27	10	11	48
Oct 2016	14	7	5	26
Nov 2016	13	13	4	30
Dec 2016	16	16	0	32
Jan 2017	14	37	6	57
Feb 2017	13	32	4	49
Mar 2017	28	35	11	74
Apr 2017	23	37	5	65
May 2017	28	22	8	58
Jun 2017	21	21	6	48
Jul 2017	16	22	4	42
Aug 2017	12	25	6	43
Sep 2017	24	25	2	51
Oct 2017	8	16	0	24
Nov 2017	19	20	4	43
Dec 2017	15	30	7	52
Jan 2018	24	25	4	53
Feb 2018	14	17	1	32
Mar 2018	13	29	2	44
Apr 2018	12	23	2	37
May 2018	8	7	0	15
Jun 2018	11	22	1	34
Jul 2018	19	25	2	46
Aug 2018	18	15	1	34
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Oct 2018	23	23	3	49
Nov 2018	16	15	3	34
Dec 2018	14	10	12	36
Jan 2019	11	7	7	25
Feb 2019	8	8	0	16
Mar 2019	10	16	5	31
Apr 2019	6	8	1	15
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Jun 2019	13	13	2	28
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Aug 2019	7	7	4	18
Sep 2019	6	12	23	41
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Nov 2019	6	5	7	18
Dec 2019	9	12	1	22
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Feb 2020	7	6	0	13
Mar 2020	15	10	1	26
Apr 2020	6	9	5	20
May 2020	5	12	7	24
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Jul 2020	36	28	21	85
Aug 2020	13	13	47	73
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Oct 2020	14	13	0	27
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Dec 2020	10	12	4	26
Jan 2021	20	14	6	40
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Mar 2021	7	14	3	24
Apr 2021	5	13	6	24
May 2021	4	9	6	19
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Nov 2021	8	39	2	49
Dec 2021	12	27	4	43
Jan 2022	14	31	6	51
Feb 2022	13	44	2	59
Mar 2022	7	40	0	47
Apr 2022	24	22	3	49
May 2022	12	23	4	39
Jun 2022	36	27	2	65
Jul 2022	5	18	0	23
Aug 2022	16	30	3	49
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Oct 2022	43	23	0	66
Nov 2022	12	22	1	35
Dec 2022	9	41	0	50
Jan 2023	22	24	1	47
Feb 2023	20	47	2	69
Mar 2023	28	46	1	75
Apr 2023	9	45	1	55
May 2023	32	47	3	82
Jun 2023	44	38	0	82
Jul 2023	15	47	1	63
Aug 2023	14	39	2	55
Sep 2023	20	46	0	66
Oct 2023	17	63	0	80
Nov 2023	15	40	1	56
Dec 2023	12	60	1	73
Jan 2024	17	52	0	69
Feb 2024	20	78	0	98
Mar 2024	15	76	3	94
Apr 2024	38	84	5	127
May 2024	19	76	3	98
Jun 2024	25	64	4	93
Jul 2024	34	61	3	98
Aug 2024	30	41	4	75
Sep 2024	20	50	3	73
Oct 2024	22	96	1	119
Nov 2024	11	95	0	106
Dec 2024	8	70	1	79
Jan 2025	21	66	0	87
Feb 2025	39	89	1	129
Mar 2025	23	81	6	110
Apr 2025	22	59	1	82
May 2025	29	64	1	94
Jun 2025	52	61	0	113
Jul 2025	45	72	3	120
Aug 2025	30	38	0	68
Sep 2025	33	48	2	83
Oct 2025	34	66	1	101
Nov 2025	38	75	3	116
Dec 2025	7	12	0	19

Latest update: 06 Dec 2025

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Short summary

Damage functions are an essential tool for vulnerability assessment and the quantification of disaster loss. They are often tailored to specific hazards and regions, which complicates knowledge transfer between different hazards and places. In our work, we unify approaches for climate-related hazards, e.g. for storms and coastal floods. A unified damage function is embedded in an uncertainty framework, where we identify the dominating sources of uncertainty on local and regional scales.