Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation

McMahon, T. A.; Peel, M. C.; Karoly, D. J.

doi:10.5194/hess-19-361-2015

Articles | Volume 19, issue 1

https://doi.org/10.5194/hess-19-361-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-19-361-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 19, issue 1

Research article

|

21 Jan 2015

Research article |

| 21 Jan 2015

Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation

T. A. McMahon, M. C. Peel, and D. J. Karoly

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Total article views: 5,195 (including HTML, PDF, and XML)

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Views and downloads (calculated since 05 May 2014)

Month	HTML	PDF	XML	Total
May 2014	161	141	0	302
Jun 2014	24	33	1	58
Jul 2014	24	27	0	51
Aug 2014	14	14	0	28
Sep 2014	18	13	3	34
Oct 2014	16	11	0	27
Nov 2014	14	15	2	31
Dec 2014	10	12	1	23
Jan 2015	45	34	2	81
Feb 2015	39	37	2	78
Mar 2015	52	25	1	78
Apr 2015	79	21	1	101
May 2015	63	25	1	89
Jun 2015	94	23	0	117
Jul 2015	63	24	2	89
Aug 2015	10	19	0	29
Sep 2015	8	24	14	46
Oct 2015	18	22	17	57
Nov 2015	30	27	1	58
Dec 2015	12	31	2	45
Jan 2016	32	17	0	49
Feb 2016	21	11	2	34
Mar 2016	16	14	0	30
Apr 2016	11	18	0	29
May 2016	9	19	0	28
Jun 2016	6	8	0	14
Jul 2016	8	11	1	20
Aug 2016	8	3	1	12
Sep 2016	7	1	0	8
Oct 2016	19	6	1	26
Nov 2016	16	6	1	23
Dec 2016	7	7	1	15
Jan 2017	16	2	0	18
Feb 2017	12	3	1	16
Mar 2017	20	6	3	29
Apr 2017	23	7	0	30
May 2017	24	7	0	31
Jun 2017	24	9	2	35
Jul 2017	16	10	0	26
Aug 2017	7	23	0	30
Sep 2017	9	8	0	17
Oct 2017	6	6	0	12
Nov 2017	12	22	0	34
Dec 2017	18	22	0	40
Jan 2018	4	2	0	6
Feb 2018	8	7	1	16
Mar 2018	10	6	0	16
Apr 2018	11	6	0	17
May 2018	11	6	0	17
Jun 2018	3	10	1	14
Jul 2018	3	10	0	13
Aug 2018	15	17	0	32
Sep 2018	18	8	0	26
Oct 2018	16	8	0	24
Nov 2018	14	9	0	23
Dec 2018	9	8	0	17
Jan 2019	3	5	0	8
Feb 2019	6	7	0	13
Mar 2019	6	5	0	11
Apr 2019	7	6	0	13
May 2019	12	9	0	21
Jun 2019	10	5	0	15
Jul 2019	7	6	0	13
Aug 2019	10	9	0	19
Sep 2019	10	6	0	16
Oct 2019	11	11	1	23
Nov 2019	8	4	0	12
Dec 2019	9	8	1	18
Jan 2020	10	7	1	18
Feb 2020	11	6	0	17
Mar 2020	6	6	0	12
Apr 2020	7	8	0	15
May 2020	7	6	0	13
Jun 2020	13	7	0	20
Jul 2020	25	25	8	58
Aug 2020	13	11	7	31
Sep 2020	14	7	0	21
Oct 2020	8	8	0	16
Nov 2020	15	5	0	20
Dec 2020	16	14	0	30
Jan 2021	23	16	0	39
Feb 2021	19	7	0	26
Mar 2021	16	8	0	24
Apr 2021	12	17	0	29
May 2021	13	8	0	21
Jun 2021	8	10	0	18
Jul 2021	7	14	0	21
Aug 2021	6	17	0	23
Sep 2021	11	13	0	24
Oct 2021	13	31	0	44
Nov 2021	19	24	0	43
Dec 2021	17	9	0	26
Jan 2022	16	15	0	31
Feb 2022	13	7	2	22
Mar 2022	13	12	0	25
Apr 2022	15	4	0	19
May 2022	17	10	1	28
Jun 2022	12	7	2	21
Jul 2022	10	5	0	15
Aug 2022	19	5	0	24
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Oct 2022	19	11	3	33
Nov 2022	10	19	0	29
Dec 2022	13	3	0	16
Jan 2023	27	20	4	51
Feb 2023	21	8	0	29
Mar 2023	20	20	1	41
Apr 2023	15	7	1	23
May 2023	9	15	0	24
Jun 2023	11	6	1	18
Jul 2023	21	6	2	29
Aug 2023	36	10	2	48
Sep 2023	116	12	1	129
Oct 2023	227	6	3	236
Nov 2023	200	5	0	205
Dec 2023	23	7	2	32
Jan 2024	17	8	1	26
Feb 2024	7	16	2	25
Mar 2024	11	16	6	33
Apr 2024	29	6	8	43
May 2024	20	12	5	37
Jun 2024	23	9	2	34
Jul 2024	20	13	2	35
Aug 2024	43	6	1	50
Sep 2024	14	8	0	22
Oct 2024	24	10	0	34
Nov 2024	22	10	1	33
Dec 2024	16	10	2	28
Jan 2025	30	6	0	36
Feb 2025	34	12	2	48
Mar 2025	35	18	3	56
Apr 2025	24	13	0	37
May 2025	32	9	1	42
Jun 2025	69	12	2	83
Jul 2025	29	32	0	61
Aug 2025	29	15	1	45
Sep 2025	66	15	2	83
Oct 2025	22	19	1	42
Nov 2025	40	31	2	73

Cumulative views and downloads (calculated since 05 May 2014)

Month	HTML	PDF	XML	Total
May 2014	161	141	0	302
Jun 2014	24	33	1	58
Jul 2014	24	27	0	51
Aug 2014	14	14	0	28
Sep 2014	18	13	3	34
Oct 2014	16	11	0	27
Nov 2014	14	15	2	31
Dec 2014	10	12	1	23
Jan 2015	45	34	2	81
Feb 2015	39	37	2	78
Mar 2015	52	25	1	78
Apr 2015	79	21	1	101
May 2015	63	25	1	89
Jun 2015	94	23	0	117
Jul 2015	63	24	2	89
Aug 2015	10	19	0	29
Sep 2015	8	24	14	46
Oct 2015	18	22	17	57
Nov 2015	30	27	1	58
Dec 2015	12	31	2	45
Jan 2016	32	17	0	49
Feb 2016	21	11	2	34
Mar 2016	16	14	0	30
Apr 2016	11	18	0	29
May 2016	9	19	0	28
Jun 2016	6	8	0	14
Jul 2016	8	11	1	20
Aug 2016	8	3	1	12
Sep 2016	7	1	0	8
Oct 2016	19	6	1	26
Nov 2016	16	6	1	23
Dec 2016	7	7	1	15
Jan 2017	16	2	0	18
Feb 2017	12	3	1	16
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Apr 2017	23	7	0	30
May 2017	24	7	0	31
Jun 2017	24	9	2	35
Jul 2017	16	10	0	26
Aug 2017	7	23	0	30
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Nov 2017	12	22	0	34
Dec 2017	18	22	0	40
Jan 2018	4	2	0	6
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Apr 2018	11	6	0	17
May 2018	11	6	0	17
Jun 2018	3	10	1	14
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Aug 2018	15	17	0	32
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Oct 2018	16	8	0	24
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Jan 2022	16	15	0	31
Feb 2022	13	7	2	22
Mar 2022	13	12	0	25
Apr 2022	15	4	0	19
May 2022	17	10	1	28
Jun 2022	12	7	2	21
Jul 2022	10	5	0	15
Aug 2022	19	5	0	24
Sep 2022	13	8	0	21
Oct 2022	19	11	3	33
Nov 2022	10	19	0	29
Dec 2022	13	3	0	16
Jan 2023	27	20	4	51
Feb 2023	21	8	0	29
Mar 2023	20	20	1	41
Apr 2023	15	7	1	23
May 2023	9	15	0	24
Jun 2023	11	6	1	18
Jul 2023	21	6	2	29
Aug 2023	36	10	2	48
Sep 2023	116	12	1	129
Oct 2023	227	6	3	236
Nov 2023	200	5	0	205
Dec 2023	23	7	2	32
Jan 2024	17	8	1	26
Feb 2024	7	16	2	25
Mar 2024	11	16	6	33
Apr 2024	29	6	8	43
May 2024	20	12	5	37
Jun 2024	23	9	2	34
Jul 2024	20	13	2	35
Aug 2024	43	6	1	50
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Oct 2024	24	10	0	34
Nov 2024	22	10	1	33
Dec 2024	16	10	2	28
Jan 2025	30	6	0	36
Feb 2025	34	12	2	48
Mar 2025	35	18	3	56
Apr 2025	24	13	0	37
May 2025	32	9	1	42
Jun 2025	69	12	2	83
Jul 2025	29	32	0	61
Aug 2025	29	15	1	45
Sep 2025	66	15	2	83
Oct 2025	22	19	1	42
Nov 2025	40	31	2	73

Latest update: 27 Nov 2025

Short summary

Here we assess GCM performance from a hydrologic perspective. We identify five better performing CMIP3 GCMs that reproduce grid-scale climatological statistics of observed precipitation and temperature over global land regions for future hydrologic simulation. GCM performance in reproducing observed mean and standard deviation of annual precipitation, mean annual temperature and mean monthly precipitation and temperature was assessed and ranked, and five better performing GCMs were identified.