Polynyas are of high research interest since these features are areas of extensive new ice formation. The calculation of accurate ice-production values requires the knowledge of polynya area and thin-ice thickness distribution. These two variables can be derived by remote sensing data. However, a cross-validation study of various remote sensing data sets indicates that the spatial resolution issue is essential for the retrieval of accurate thin-ice thickness distribution. Thus, high-resolution remote sensing data must be used. MODIS thermal-infrared data with a spatial resolution of 1 km × 1 km is appropriate for the retrieval of thin-ice thickness distribution within the polynya.
The algorithm to derive thermal-infrared thin-ice thickness is improved to state-of-the-art parameterizations. The mean absolute error of thin-ice thickness is ±4.7 cm for ice below 20 cm of thickness. The thin-ice thickness maps lack full coverage due to the restriction of the algorithm to cloud-free and nighttime data. Therefore, a compositing method is applied to compute daily thin-ice thickness maps. These maps cover on average 70 % of the Laptev Sea polynya.
In order to fill the remaining gaps a combined remote sensing – model approach is developed to provide a consistent time series of high-resolution thin-ice thickness maps. This data set is valuable for the retrieval of accurate ice production within polynyas