Articles | Volume 16, issue 17
Model evaluation paper
31 Aug 2023
Model evaluation paper |  | 31 Aug 2023

Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations

Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-47', Anonymous Referee #1, 11 Apr 2023
    • AC1: 'Reply on RC1', Adam Pasik, 07 Jun 2023
  • RC2: 'Comment on egusphere-2023-47', Anonymous Referee #2, 01 May 2023
    • AC2: 'Reply on RC2', Adam Pasik, 07 Jun 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Adam Pasik on behalf of the Authors (28 Jun 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (30 Jun 2023) by Hisashi Sato
RR by Anonymous Referee #2 (28 Jul 2023)
ED: Publish as is (30 Jul 2023) by Hisashi Sato
AR by Alexander Gruber on behalf of the Authors (31 Jul 2023)  Manuscript 

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

Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.