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:https://doi.org/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

Download

Final revised paper (published on 12 Jan 2018)
Supplement to the final revised paper
Preprint (discussion started on 18 Apr 2017)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Comment on 'A Climate Data Record (CDR) for the global terrestrial water budget: 1984-2010'', Anonymous Referee #1, 20 May 2017
- AC1: 'RC1', Ming Pan, 22 Aug 2017
RC2: 'Comment on "A Climate Data Record (CDR) for the global terrestrial water budget: 1984-2010"', Anonymous Referee #2, 30 May 2017
- AC2: 'RC2', Ming Pan, 22 Aug 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to revisions (further review by Editor and Referees) (11 Sep 2017) by Reed Maxwell

AR by Ming Pan on behalf of the Authors (12 Sep 2017) Author's response Manuscript

ED: Referee Nomination & Report Request started (25 Sep 2017) by Reed Maxwell

RR by Anonymous Referee #1 (27 Oct 2017)

Suggestions for revision or reasons for rejection

This is the second review of ‘A Climate Data Record (CDR) for the global terrestrial water budget: 1984-2010’. I thank the authors for their response to reviewer questions and comments and for their revisions to the manuscript. A few minor points still remain to be clarified, however. These are detailed below.

Section 2.2.1, page 8-9: I thank the authors for their explanation in their response to the question about the use of “optimal” to describe the merging technique. Based on this, it seems that it is perhaps more accurate to qualify this “optimality” as constrained by or conditional on limited data availability rather than being the optimal approach. A few minor edits, consistent with the authors’ response to R1-Comment 2, in the abstract and section 2.2.1 would clarify this point.

Page 9, Lines 31-32: It would be helpful here to state that the assumed 10% error in VIC runoff is based on the authors’ experience and judgment “given there is no global grid level (0.5 degree in this study) runoff observations to quantify the error.”

Page 11, lines 25-30: I recognize the difficulty in accounting for groundwater extraction and management globally. As the authors note, there are regions (California Central Valley, US High Plains, Iran, etc) where historic regional storage declines challenge the assumption of zero long term TWSC. For completeness, a explanation of the consequences of this assumption on the CDR results for these areas, either in section 3.2 or in the discussion in section 5, seems warranted.

Page 13, line 22: In response to R1-comment 12, the authors state that the filtering out of basins with non-significant correlations “was done in order to remove those basins such as Indus and Senegal which might have incorrect observational data.” This was not immediately apparent from the explanation on page 13 of the revised manuscript – please edit to include this point for clarity.

Page 16, lines 8-12 and Figure S7: I thank the authors for the additional text and plots addressing the question of inter-annual variability in the CDR. However, this section is a little unclear. Please define SPI and provide more detail in the Figure S7 caption to indicate what is shown in the plots (i.e which parts are from the CDR?)

Figures – general: The number of figures in the main manuscript makes the main point of this manuscript less clear. Some of the figures could be moved to the supplemental information to better emphasize the results of the study. For example, the data product comparisons (Figures 2-10) could be limited to just continental (or river basin) plots and the remainder moved to the SI.

Figure 2: The caption references TMPART but this seems inconsistent. Should it instead reference the CSU dataset?

Figure 11: Please provide a more descriptive caption to accompany this flowchart.

Hide

ED: Publish subject to minor revisions (review by editor) (27 Oct 2017) by Reed Maxwell

AR by Ming Pan on behalf of the Authors (06 Nov 2017) Author's response Manuscript

ED: Publish as is (09 Nov 2017) by Reed Maxwell

AR by Ming Pan on behalf of the Authors (11 Nov 2017)

Download

The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.

Article (4684 KB)
Full-text XML

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.