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
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Total article views: 1,898 (including HTML, PDF, and XML)
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Viewed (geographical distribution)
Total article views: 2,988 (including HTML, PDF, and XML)
Thereof 2,414 with geography defined
and 574 with unknown origin.
Total article views: 1,898 (including HTML, PDF, and XML)
Thereof 1,620 with geography defined
and 278 with unknown origin.
Total article views: 1,090 (including HTML, PDF, and XML)
Thereof 794 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...