Two+ decades (2000-2023) of pan Arctic meltpond fraction data

Abstract

Melt ponds are influencing the Arctic energy budget as they strongly reduce the surface albedo of sea ice. It is therefore highly important to monitor their temporal and spatial evolution. Here we build on the work of Rösel and Kaleschke (2012) to extend their time series of Moderate Resolution Image Spectroradiometer (MODIS) melt pond estimates to the present. To do so we make use of a spectral unmixing algorithm implemented via a neural network to reduce computational costs. The results will be compared to classification results of helicopter borne camera data acquired during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Furthermore, we will apply classification results from the Modular Aerial Camera System (MACS) newly employed on AWI's research aircrafts to validate the MODIS results on a larger scale. The derived time series of 23 years meltpond data will be carefully analyzed for any trends, both in the temporal and spatial domain and might be of interest to better parametrize sea ice models.