A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

Zhang, Yu; Pan, Ming; Sheffield, Justin; Siemann, Amanda L.; Fisher, Colby K.; Liang, Miaoling; Beck, Hylke E.; Wanders, Niko; MacCracken, Rosalyn F.; Houser, Paul R.; Zhou, Tian; Lettenmaier, Dennis P.; Pinker, Rachel T.; Bytheway, Janice; Kummerow, Christian D.; Wood, Eric F.

doi:10.5194/hess-22-241-2018

Articles | Volume 22, issue 1

https://doi.org/10.5194/hess-22-241-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Observations and modeling of land surface water and energy...

https://doi.org/10.5194/hess-22-241-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 22, issue 1

Research article

|

12 Jan 2018

Research article |

| 12 Jan 2018

A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

Yu Zhang, Ming Pan, Justin Sheffield, Amanda L. Siemann, Colby K. Fisher, Miaoling Liang, Hylke E. Beck, Niko Wanders, Rosalyn F. MacCracken, Paul R. Houser, Tian Zhou, Dennis P. Lettenmaier, Rachel T. Pinker, Janice Bytheway, Christian D. Kummerow, and Eric F. Wood

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XML: 177
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BibTeX: 150
EndNote: 218

Views and downloads (calculated since 18 Apr 2017)

Month	HTML	PDF	XML	Total
Apr 2017	300	74	4	378
May 2017	199	40	9	248
Jun 2017	62	25	7	94
Jul 2017	29	12	1	42
Aug 2017	26	9	1	36
Sep 2017	33	15	1	49
Oct 2017	26	14	0	40
Nov 2017	18	10	0	28
Dec 2017	21	20	1	42
Jan 2018	351	146	8	505
Feb 2018	84	29	4	117
Mar 2018	44	50	4	98
Apr 2018	38	18	2	58
May 2018	37	20	1	58
Jun 2018	43	22	2	67
Jul 2018	27	18	1	46
Aug 2018	60	35	1	96
Sep 2018	50	19	0	69
Oct 2018	49	39	3	91
Nov 2018	27	25	1	53
Dec 2018	22	14	2	38
Jan 2019	25	17	1	43
Feb 2019	12	8	0	20
Mar 2019	16	14	1	31
Apr 2019	28	21	2	51
May 2019	33	14	0	47
Jun 2019	39	17	3	59
Jul 2019	34	14	1	49
Aug 2019	22	18	0	40
Sep 2019	22	17	0	39
Oct 2019	37	18	1	56
Nov 2019	23	11	0	34
Dec 2019	28	14	2	44
Jan 2020	32	8	3	43
Feb 2020	31	9	0	40
Mar 2020	26	10	0	36
Apr 2020	10	15	1	26
May 2020	19	7	1	27
Jun 2020	22	13	1	36
Jul 2020	42	17	2	61
Aug 2020	15	12	1	28
Sep 2020	30	10	1	41
Oct 2020	31	12	1	44
Nov 2020	25	10	0	35
Dec 2020	23	15	1	39
Jan 2021	29	15	0	44
Feb 2021	35	16	2	53
Mar 2021	27	13	0	40
Apr 2021	33	9	0	42
May 2021	30	13	3	46
Jun 2021	21	10	0	31
Jul 2021	28	16	0	44
Aug 2021	35	33	1	69
Sep 2021	20	15	1	36
Oct 2021	29	37	0	66
Nov 2021	37	32	1	70
Dec 2021	38	21	1	60
Jan 2022	22	14	0	36
Feb 2022	16	10	1	27
Mar 2022	29	16	1	46
Apr 2022	53	10	1	64
May 2022	30	10	1	41
Jun 2022	30	15	3	48
Jul 2022	42	11	0	53
Aug 2022	73	6	0	79
Sep 2022	39	14	1	54
Oct 2022	39	12	3	54
Nov 2022	64	20	0	84
Dec 2022	65	14	3	82
Jan 2023	69	25	0	94
Feb 2023	61	11	1	73
Mar 2023	63	21	5	89
Apr 2023	41	17	2	60
May 2023	30	16	0	46
Jun 2023	40	13	2	55
Jul 2023	38	9	3	50
Aug 2023	41	14	2	57
Sep 2023	46	10	1	57
Oct 2023	42	13	2	57
Nov 2023	29	5	1	35
Dec 2023	38	15	2	55
Jan 2024	46	19	1	66
Feb 2024	48	26	2	76
Mar 2024	48	12	2	62
Apr 2024	47	16	1	64
May 2024	59	17	0	76
Jun 2024	91	12	4	107
Jul 2024	62	12	10	84
Aug 2024	69	8	9	86
Sep 2024	31	16	4	51
Oct 2024	48	11	1	60
Nov 2024	35	23	4	62
Dec 2024	31	8	1	40
Jan 2025	36	19	0	55
Feb 2025	43	18	0	61
Mar 2025	40	15	2	57
Apr 2025	52	21	4	77
May 2025	56	17	0	73
Jun 2025	88	28	0	116
Jul 2025	70	21	3	94
Aug 2025	64	15	3	82
Sep 2025	98	20	2	120
Oct 2025	64	32	1	97
Nov 2025	66	26	3	95

Cumulative views and downloads (calculated since 18 Apr 2017)

Month	HTML	PDF	XML	Total
Apr 2017	300	74	4	378
May 2017	199	40	9	248
Jun 2017	62	25	7	94
Jul 2017	29	12	1	42
Aug 2017	26	9	1	36
Sep 2017	33	15	1	49
Oct 2017	26	14	0	40
Nov 2017	18	10	0	28
Dec 2017	21	20	1	42
Jan 2018	351	146	8	505
Feb 2018	84	29	4	117
Mar 2018	44	50	4	98
Apr 2018	38	18	2	58
May 2018	37	20	1	58
Jun 2018	43	22	2	67
Jul 2018	27	18	1	46
Aug 2018	60	35	1	96
Sep 2018	50	19	0	69
Oct 2018	49	39	3	91
Nov 2018	27	25	1	53
Dec 2018	22	14	2	38
Jan 2019	25	17	1	43
Feb 2019	12	8	0	20
Mar 2019	16	14	1	31
Apr 2019	28	21	2	51
May 2019	33	14	0	47
Jun 2019	39	17	3	59
Jul 2019	34	14	1	49
Aug 2019	22	18	0	40
Sep 2019	22	17	0	39
Oct 2019	37	18	1	56
Nov 2019	23	11	0	34
Dec 2019	28	14	2	44
Jan 2020	32	8	3	43
Feb 2020	31	9	0	40
Mar 2020	26	10	0	36
Apr 2020	10	15	1	26
May 2020	19	7	1	27
Jun 2020	22	13	1	36
Jul 2020	42	17	2	61
Aug 2020	15	12	1	28
Sep 2020	30	10	1	41
Oct 2020	31	12	1	44
Nov 2020	25	10	0	35
Dec 2020	23	15	1	39
Jan 2021	29	15	0	44
Feb 2021	35	16	2	53
Mar 2021	27	13	0	40
Apr 2021	33	9	0	42
May 2021	30	13	3	46
Jun 2021	21	10	0	31
Jul 2021	28	16	0	44
Aug 2021	35	33	1	69
Sep 2021	20	15	1	36
Oct 2021	29	37	0	66
Nov 2021	37	32	1	70
Dec 2021	38	21	1	60
Jan 2022	22	14	0	36
Feb 2022	16	10	1	27
Mar 2022	29	16	1	46
Apr 2022	53	10	1	64
May 2022	30	10	1	41
Jun 2022	30	15	3	48
Jul 2022	42	11	0	53
Aug 2022	73	6	0	79
Sep 2022	39	14	1	54
Oct 2022	39	12	3	54
Nov 2022	64	20	0	84
Dec 2022	65	14	3	82
Jan 2023	69	25	0	94
Feb 2023	61	11	1	73
Mar 2023	63	21	5	89
Apr 2023	41	17	2	60
May 2023	30	16	0	46
Jun 2023	40	13	2	55
Jul 2023	38	9	3	50
Aug 2023	41	14	2	57
Sep 2023	46	10	1	57
Oct 2023	42	13	2	57
Nov 2023	29	5	1	35
Dec 2023	38	15	2	55
Jan 2024	46	19	1	66
Feb 2024	48	26	2	76
Mar 2024	48	12	2	62
Apr 2024	47	16	1	64
May 2024	59	17	0	76
Jun 2024	91	12	4	107
Jul 2024	62	12	10	84
Aug 2024	69	8	9	86
Sep 2024	31	16	4	51
Oct 2024	48	11	1	60
Nov 2024	35	23	4	62
Dec 2024	31	8	1	40
Jan 2025	36	19	0	55
Feb 2025	43	18	0	61
Mar 2025	40	15	2	57
Apr 2025	52	21	4	77
May 2025	56	17	0	73
Jun 2025	88	28	0	116
Jul 2025	70	21	3	94
Aug 2025	64	15	3	82
Sep 2025	98	20	2	120
Oct 2025	64	32	1	97
Nov 2025	66	26	3	95

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Total article views: 6,980 (including HTML, PDF, and XML) Thereof 6,683 with geography defined and 297 with unknown origin.

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Short summary

A global data record for all four terrestrial water budget variables (precipitation, evapotranspiration, runoff, and total water storage change) at 0.5° resolution and monthly scale for the period of 1984–2010 is developed by optimally merging a series of remote sensing products, in situ measurements, land surface model outputs, and atmospheric reanalysis estimates and enforcing the mass balance of water. Initial validations show the data record is reliable for climate related analysis.


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