04 Jan 2021

04 Jan 2021

Review status: this preprint is currently under review for the journal TC.

An improved sea ice detection algorithm using MODIS: application as a new European sea ice extent indicator

Joan A. Parera-Portell1,a, Raquel Ubach1, and Charles Gignac2 Joan A. Parera-Portell et al.
  • 1Department of Geography, Univesitat Autònoma de Barcelona, Barcelona, Spain
  • 2TENOR laboratory, Institut National de la Recherche Scientifique - Centre Eau Terre Environnement, Quebec City, Canada
  • anow at: Instituto Andaluz de Geofísica, Universidad de Granada, Granada, Spain

Abstract. The continued loss of sea ice in the Northern Hemisphere due to global warming poses a threat on biota and human activities, evidencing the necessity of efficient sea ice monitoring tools. Aiming at the creation of an improved European sea ice extent indicator, the IceMap250 algorithm has been reworked to generate improved sea ice extent maps at 500 m resolution at nadir. Changes in the classification approach and a new method to correct artefacts arising from the MODIS cloud mask allow the enlargement of the mapped area, the reduction of potential error sources and a qualitative improvement of the resulting maps, while systematically achieving accuracies above 90 %. Monthly sea ice extent maps have been derived using a new synthesis method which acts as an additional error filter. Our results, covering the months of maximum (March) and minimum (September) sea ice extent during two decades (from 2000 to 2019), are a proof of the algorithm's applicability as an indicator, illustrating the sea ice decline in the European regional seas. We observed no significant trends in the Baltic (−2.75 ± 2.05 × 103 km2 yr−1) although, on the contrary, the European Arctic seas display clear negative trends both in March (−27.98 ± 6.01 × 103 km2 yr−1) and September (−16.47 ± 5.66 × 103 km2 yr−1). Such trends indicate that the sea ice cover in March and September is shrinking at a rate of ∼9 % and ∼13 % per decade, respectively, even though the sea ice extent loss is comparatively ∼70 % greater in March. Therefore, according to the trends and without taking into account the variability of the sea ice cover, the loss of sea ice extent over two decades in the study area would be comparable to the area of continental France in the case of the March maximum, and to that of Finland in the case of the September minimum.

Joan A. Parera-Portell et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2020-333', Anonymous Referee #1, 27 Jan 2021
    • AC1: 'Reply on RC1', Joan Antoni Parera Portell, 11 Feb 2021
  • RC2: 'Comment on tc-2020-333', Anonymous Referee #2, 02 Feb 2021
    • AC2: 'Reply on RC2', Joan Antoni Parera Portell, 11 Feb 2021

Joan A. Parera-Portell et al.

Data sets

IceMap500 European maximum and minimum sea ice extent maps (2000-2019) Joan A. Parera-Portell and Raquel Ubach

Joan A. Parera-Portell et al.


Total article views: 464 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
344 108 12 464 8 5
  • HTML: 344
  • PDF: 108
  • XML: 12
  • Total: 464
  • BibTeX: 8
  • EndNote: 5
Views and downloads (calculated since 04 Jan 2021)
Cumulative views and downloads (calculated since 04 Jan 2021)

Viewed (geographical distribution)

Total article views: 429 (including HTML, PDF, and XML) Thereof 424 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
Latest update: 19 Apr 2021
Short summary
We describe a new method to automatically map sea ice at a resolution of 500 m using data acquired by the MODIS sensor. The strength of this method is that it uses a single sensor, it achieves a high accuracy and it is capable of attenuating some unwanted resolution-breaking effects. Our resulting March and September monthly maps clearly show the loss of sea ice in the European Arctic during the 2000–2019 period, and prove that our method might be used as a reliable sea ice monitoring tool.