Journal cover Journal topic
The Cryosphere An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 4.713
IF 5-year value: 4.927
IF 5-year
CiteScore value: 8.0
SNIP value: 1.425
IPP value: 4.65
SJR value: 2.353
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
h5-index value: 53
Volume 6, issue 2
The Cryosphere, 6, 431–446, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
The Cryosphere, 6, 431–446, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 03 Apr 2012

Research article | 03 Apr 2012

Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network

A. Rösel2,1, L. Kaleschke1, and G. Birnbaum3 A. Rösel et al.
  • 1Institute of Oceanography, University of Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
  • 2Max Planck Institute for Comparative and International Private Law, Mittelweg 187, 20148 Hamburg, Germany
  • 3Alfred Wegener Institute for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany

Abstract. Melt ponds on sea ice strongly reduce the surface albedo and accelerate the decay of Arctic sea ice. Due to different spectral properties of snow, ice, and water, the fractional coverage of these distinct surface types can be derived from multispectral sensors like the Moderate Resolution Image Spectroradiometer (MODIS) using a spectral unmixing algorithm. The unmixing was implemented using a multilayer perceptron to reduce computational costs.

Arctic-wide melt pond fractions and sea ice concentrations are derived from the level 3 MODIS surface reflectance product. The validation of the MODIS melt pond data set was conducted with aerial photos from the MELTEX campaign 2008 in the Beaufort Sea, data sets from the National Snow and Ice Data Center (NSIDC) for 2000 and 2001 from four sites spread over the entire Arctic, and with ship observations from the trans-Arctic HOTRAX cruise in 2005. The root-mean-square errors range from 3.8 % for the comparison with HOTRAX data, over 10.7 % for the comparison with NSIDC data, to 10.3 % and 11.4 % for the comparison with MELTEX data, with coefficient of determination ranging from R2=0.28 to R2=0.45. The mean annual cycle of the melt pond fraction per grid cell for the entire Arctic shows a strong increase in June, reaching a maximum of 15 % by the end of June. The zonal mean of melt pond fractions indicates a dependence of the temporal development of melt ponds on the geographical latitude, and has its maximum in mid-July at latitudes between 80° and 88° N.

Furthermore, the MODIS results are used to estimate the influence of melt ponds on retrievals of sea ice concentrations from passive microwave data. Results from a case study comparing sea ice concentrations from ARTIST Sea Ice-, NASA Team 2-, and Bootstrap-algorithms with MODIS sea ice concentrations indicate an underestimation of around 40 % for sea ice concentrations retrieved with microwave algorithms.

Publications Copernicus