Towards a compound-event-oriented climate model  evaluation: a decomposition of the underlying biases  in multivariate fire and heat stress hazards

Villalobos-Herrera, Roberto; Bevacqua, Emanuele; Ribeiro, Andreia F. S.; Auld, Graeme; Crocetti, Laura; Mircheva, Bilyana; Ha, Minh; Zscheischler, Jakob; De Michele, Carlo

doi:10.5194/nhess-21-1867-2021

Articles | Volume 21, issue 6

https://doi.org/10.5194/nhess-21-1867-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Understanding compound weather and climate events and related...

https://doi.org/10.5194/nhess-21-1867-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 6

Research article

|

17 Jun 2021

Research article |

| 17 Jun 2021

Towards a compound-event-oriented climate model evaluation: a decomposition of the underlying biases in multivariate fire and heat stress hazards

Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele

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Dec 2020	106	28	2	136
Jan 2021	92	25	0	117
Feb 2021	69	18	1	88
Mar 2021	28	19	0	47
Apr 2021	37	6	0	43
May 2021	45	16	0	61
Jun 2021	338	72	3	413
Jul 2021	151	43	1	195
Aug 2021	50	29	0	79
Sep 2021	79	34	1	114
Oct 2021	77	74	1	152
Nov 2021	79	57	3	139
Dec 2021	53	28	1	82
Jan 2022	49	21	1	71
Feb 2022	35	19	1	55
Mar 2022	38	16	0	54
Apr 2022	51	12	1	64
May 2022	31	11	1	43
Jun 2022	30	5	1	36
Jul 2022	35	12	0	47
Aug 2022	61	12	2	75
Sep 2022	55	10	1	66
Oct 2022	41	13	2	56
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Dec 2022	38	14	1	53
Jan 2023	34	21	1	56
Feb 2023	31	21	1	53
Mar 2023	35	20	3	58
Apr 2023	39	14	1	54
May 2023	17	10	3	30
Jun 2023	32	11	1	44
Jul 2023	26	14	3	43
Aug 2023	37	13	2	52
Sep 2023	42	11	1	54
Oct 2023	46	24	2	72
Nov 2023	14	10	0	24
Dec 2023	26	8	0	34
Jan 2024	50	12	1	63
Feb 2024	20	22	3	45
Mar 2024	25	6	3	34
Apr 2024	35	20	3	58
May 2024	29	8	1	38
Jun 2024	58	18	3	79
Jul 2024	38	9	1	48
Aug 2024	41	11	3	55
Sep 2024	57	11	3	71
Oct 2024	41	7	1	49
Nov 2024	24	6	3	33
Dec 2024	23	7	0	30
Jan 2025	47	13	0	60
Feb 2025	38	5	1	44
Mar 2025	33	10	1	44
Apr 2025	49	12	2	63
May 2025	41	12	1	54
Jun 2025	52	13	0	65
Jul 2025	32	12	3	47
Aug 2025	44	7	1	52
Sep 2025	55	14	2	71
Oct 2025	55	27	3	85
Nov 2025	8	8	2	18

Cumulative views and downloads (calculated since 23 Nov 2020)

Month	HTML	PDF	XML	Total
Nov 2020	263	80	5	348
Dec 2020	106	28	2	136
Jan 2021	92	25	0	117
Feb 2021	69	18	1	88
Mar 2021	28	19	0	47
Apr 2021	37	6	0	43
May 2021	45	16	0	61
Jun 2021	338	72	3	413
Jul 2021	151	43	1	195
Aug 2021	50	29	0	79
Sep 2021	79	34	1	114
Oct 2021	77	74	1	152
Nov 2021	79	57	3	139
Dec 2021	53	28	1	82
Jan 2022	49	21	1	71
Feb 2022	35	19	1	55
Mar 2022	38	16	0	54
Apr 2022	51	12	1	64
May 2022	31	11	1	43
Jun 2022	30	5	1	36
Jul 2022	35	12	0	47
Aug 2022	61	12	2	75
Sep 2022	55	10	1	66
Oct 2022	41	13	2	56
Nov 2022	38	7	0	45
Dec 2022	38	14	1	53
Jan 2023	34	21	1	56
Feb 2023	31	21	1	53
Mar 2023	35	20	3	58
Apr 2023	39	14	1	54
May 2023	17	10	3	30
Jun 2023	32	11	1	44
Jul 2023	26	14	3	43
Aug 2023	37	13	2	52
Sep 2023	42	11	1	54
Oct 2023	46	24	2	72
Nov 2023	14	10	0	24
Dec 2023	26	8	0	34
Jan 2024	50	12	1	63
Feb 2024	20	22	3	45
Mar 2024	25	6	3	34
Apr 2024	35	20	3	58
May 2024	29	8	1	38
Jun 2024	58	18	3	79
Jul 2024	38	9	1	48
Aug 2024	41	11	3	55
Sep 2024	57	11	3	71
Oct 2024	41	7	1	49
Nov 2024	24	6	3	33
Dec 2024	23	7	0	30
Jan 2025	47	13	0	60
Feb 2025	38	5	1	44
Mar 2025	33	10	1	44
Apr 2025	49	12	2	63
May 2025	41	12	1	54
Jun 2025	52	13	0	65
Jul 2025	32	12	3	47
Aug 2025	44	7	1	52
Sep 2025	55	14	2	71
Oct 2025	55	27	3	85
Nov 2025	8	8	2	18

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Short summary

Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity as examples, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.


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