Abstract. The presence of melt ponds on the Arctic sea ice strongly affects the energy balance of the Arctic Ocean in summer. It affects albedo as well as transmittance through the sea ice, which has consequences on the heat balance and mass balance of sea ice. An algorithm to retrieve melt pond fraction and sea ice albedo (Zege et al., 2014) from the MEdium Resolution Imaging Spectrometer (MERIS) data is validated against aerial, ship borne and in situ campaign data. The result show the best correlation for landfast and multiyear ice of high ice concentrations (albedo: R = 0.92, RMS = 0.068, melt pond fraction: R = 0.6, RMS = 0.065). The correlation for lower ice concentrations, subpixel ice floes, blue ice and wet ice is lower due to complicated surface conditions and ice drift. Combining all aerial observations gives a mean albedo RMS equal to 0.089 and a mean melt pond fraction RMS equal to 0.22. The in situ melt pond fraction correlation is R = 0.72 with an RMS = 0.14. Ship cruise data might be affected by documentation of varying accuracy within the ASPeCT protocol, which is the reason for discrepancy between the satellite value and observed value: mean R = 0.21, mean RMS = 0.16. An additional dynamic spatial cloud filter for MERIS over snow and ice has been developed to assist with the validation on swath data. The case studies and trend analysis for the whole MERIS period (2002–2011) show pronounced and reasonable spatial features of melt pond fractions and sea ice albedo. The most prominent feature is the melt onset shifting towards spring (starting already in weeks 3 and 4 of June) within the multiyear ice area, north to the Queen Elizabeth Islands and North Greenland.

ABSTRACT. Changing Arctic sea-ice extent and melt season duration, and increasing economic interest in the Arctic have prompted the need for enhanced marine ecosystem studies and improvements to dynamical and forecast models. Sea-ice melt pond fraction f p has been shown to be correlated with the September minimum ice extent due to its impact on ice albedo and heat uptake. Ice forecasts should benefit from knowledge of f p as melt ponds form several months in advance of ice retreat. This study goes further back by examining the potential to predict f p during winter using backscatter data from the commonly available Sentinel-1 synthetic aperture radar. An object-based image analysis links the winter and spring thermodynamic states of first-year and multiyear sea-ice types. Strong correlations between winter backscatter and spring f p , detected from high-resolution visible to near infrared imagery, are observed, and models for the retrieval of f p from Sentinel-1 data are provided (r 2 ≥ 0.72).The models utilize HH polarization channel backscatter that is routinely acquired over the Arctic from the two-satellite Sentinel-1 constellation mission, as well as other past, current and future SAR missions operating in the same C-band frequency. Predicted f p is generally representative of major ice types firstyear ice and multiyear ice during the stage in seasonal melt pond evolution where f p is closely related to spatial variations in ice topography.