State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Center for Global Change and Water Cycle, Hohai University, Nanjing 210098, China
Laboratoire Météorologie Dynamique du CNRS, IPSL, CNRS, Paris, 91128, France
Institute of Industrial Science, University of Tokyo, Tokyo, 153-8505, Japan
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Center for Global Change and Water Cycle, Hohai University, Nanjing 210098, China
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Center for Global Change and Water Cycle, Hohai University, Nanjing 210098, China
Viewed
Total article views: 2,707 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,937
726
44
2,707
36
45
HTML: 1,937
PDF: 726
XML: 44
Total: 2,707
BibTeX: 36
EndNote: 45
Views and downloads (calculated since 05 Feb 2019)
Cumulative views and downloads
(calculated since 05 Feb 2019)
Total article views: 1,633 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,186
416
31
1,633
24
34
HTML: 1,186
PDF: 416
XML: 31
Total: 1,633
BibTeX: 24
EndNote: 34
Views and downloads (calculated since 23 Apr 2020)
Cumulative views and downloads
(calculated since 23 Apr 2020)
Total article views: 1,074 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
751
310
13
1,074
12
11
HTML: 751
PDF: 310
XML: 13
Total: 1,074
BibTeX: 12
EndNote: 11
Views and downloads (calculated since 05 Feb 2019)
Cumulative views and downloads
(calculated since 05 Feb 2019)
Viewed (geographical distribution)
Total article views: 2,707 (including HTML, PDF, and XML)
Thereof 2,143 with geography defined
and 564 with unknown origin.
Total article views: 1,633 (including HTML, PDF, and XML)
Thereof 1,365 with geography defined
and 268 with unknown origin.
Total article views: 1,074 (including HTML, PDF, and XML)
Thereof 778 with geography defined
and 296 with unknown origin.
This article proposes a new estimation approach for assessing the uncertainty with multiple datasets by fully considering all variations in temporal and spatial dimensions. Comparisons demonstrate that classical metrics may underestimate the uncertainties among datasets due to an averaging process in their algorithms. This new approach is particularly suitable for overall assessment of multiple climatic products, but can be easily applied to other spatiotemporal products in related fields.
This article proposes a new estimation approach for assessing the uncertainty with multiple...
