Coupled subseasonal forecast systems with dynamical sea ice have the potential of
providing important predictive information in polar regions. Here, we evaluate the ability of …

In this study, the potential for sea ice concentration prediction using machine‐learning
methods is investigated. Three different sea ice prediction models are compared: one high …

Forecasts of sea ice evolution in the Arctic region for several months ahead can be of
considerable socioeconomic value for a diverse range of marine sectors and for local …

The ice edge is a simple quantity in the form of a line that can be derived from a spatially
varying sea ice concentration field. Due to its long history and relevance for operations in the …

Reliable short-term sea ice forecasts are needed to support maritime operations in polar
regions. While sea ice forecasts produced by physically based models still have limited …

Abstract The International Verification Methods Workshop was held online in November
2020 and included sessions on physical error characterization using process diagnostics …

In this study, the subseasonal Antarctic sea ice edge prediction skill of the Copernicus
Climate Change Service (C3S) and Subseasonal to Seasonal (S2S) projects was evaluated …

In response to a growing demand for improved sea‐ice forecast guidance at shorter
timescales and higher spatial resolutions, this study investigates the predictive skill of daily …

Accelerated loss of the sea‐ice cover and increased human activities in the Arctic
emphasize the need for skillful prediction of sea‐ice conditions at subseasonal to seasonal …

In this study, sea ice edge derived from three passive microwave (PM) algorithms, ARTIST
sea ice (ASI), enhanced NASA Team 2 (NT2), and Bootstrap (BT), are compared to those …