Articles | Volume 15, issue 1
Model experiment description paper
11 Jan 2022
Model experiment description paper |  | 11 Jan 2022

Modeling reservoir surface temperatures for regional and global climate models: a multi-model study on the inflow and level variation effects

Manuel C. Almeida, Yurii Shevchuk, Georgiy Kirillin, Pedro M. M. Soares, Rita M. Cardoso, José P. Matos, Ricardo M. Rebelo, António C. Rodrigues, and Pedro S. Coelho


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-64', Anonymous Referee #1, 19 Aug 2021
    • AC1: 'Reply on RC1', Manuel Almeida, 21 Sep 2021
  • RC2: 'Comment on gmd-2021-64', Anonymous Referee #2, 22 Aug 2021
    • AC2: 'Reply on RC2', Manuel Almeida, 21 Sep 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Manuel Almeida on behalf of the Authors (21 Sep 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (18 Oct 2021) by Richard Mills
RR by Anonymous Referee #2 (27 Oct 2021)
ED: Publish as is (02 Dec 2021) by Richard Mills
AR by Manuel Almeida on behalf of the Authors (03 Dec 2021)  Author's response   Manuscript 
Short summary
In this study, we have evaluated the importance of the input of energy conveyed by river inflows into lakes and reservoirs when modeling surface water energy fluxes. Our results suggest that there is a strong correlation between water residence time and the surface water temperature prediction error and that the combined use of process-based physical models and machine-learning models will considerably improve the modeling of air–lake heat and moisture fluxes.