Articles | Volume 16, issue 16
Methods for assessment of models
18 Aug 2023
Methods for assessment of models |  | 18 Aug 2023

Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll

Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-849', Lester Kwiatkowski, 05 Dec 2022
  • RC2: 'Comment on egusphere-2022-849', Marcello Vichi, 05 Feb 2023
  • AC1: 'Comment on egusphere-2022-849', Bror Jonsson, 22 Mar 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Bror Jonsson on behalf of the Authors (19 Apr 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (20 Apr 2023) by Andrew Yool
AR by Bror Jonsson on behalf of the Authors (05 May 2023)
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.