A new approach to classification of 40 years of Antarctic sea ice concentration data

Paul Wachter,Fabian Reiser,Jucundus Jacobeit,Peter Friedl

doi:10.1002/joc.6874

Abstract

AbstractIn this paper, we present a characterization of Antarctic sea ice based on the classification of annual sea ice concentration (SIC) data from 1979 to 2018. A clustering algorithm was applied to provide a climatological description of significant annual cycles of SIC and their spatial distribution around the Southern Ocean. Based on these classification results, we investigate the variability of SIC cycles on decadal and inter‐annual time scales. First, we discuss significant spatial shifts of SIC cycles during 1979–1998 and 1999–2018. In the Weddell Sea and in large parts of the Ross Sea, we observed higher SIC during the summer season, and an extension of sea ice cover in winter compared to the long‐term average. Second, we introduce the Climatological Sea Ice Anomaly Index (CSIAI), which is an annual measure for year‐round sea ice anomalies of the Southern Ocean and its regional sub‐sectors. By relating selected years of significant sea ice conditions (1981, 2007 and 2014) with atmospheric influences, we demonstrate that the CSIAI is very useful for assessing inter‐annular Antarctic SIC variability. Positive and negative sea ice anomalies can be qualitatively explained by atmospheric circulation anomalies in the years 1981 and 2007. However, in 2014, the year with the largest observed sea ice extent in our time series, we found that this positive sea ice anomaly was surprisingly not associated with a stationary and inter‐seasonally persistent pattern of circulation anomaly. This suggests that sub‐seasonal to seasonal circulation anomalies and ocean‐related processes favoured the formation of the sea ice maximum in 2014. With this study we provide additional information on the long‐term annual SIC variability around Antarctica. Furthermore, our classification approach and its results have potential for application in the evaluation of sea ice model results.

Highlights

Sea ice plays an important role in the global climate system because it acts as an insulator and prevents the ocean from losing heat and moisture, during winter, to the atmosphere (Maykut, 1982)
Our approach consisted of pre-processing the sea ice concentration (SIC) dataset, comprised of both a temporal interpolation (Figure 1) and a first evaluation of long-term sea ice cover (Figure 2)
The 10 identified annual sea ice classes, in combination with the spatial assignment to individual pixels and years of the original dataset, enabled the classification of an Antarctic sea ice climatology based on 40 years of passive microwave remote sensing data (Figure 3)

Summary

| INTRODUCTION

Sea ice plays an important role in the global climate system because it acts as an insulator and prevents the ocean from losing heat and moisture, during winter, to the atmosphere (Maykut, 1982). Turner et al (2009) showed that ozone depletion caused a deepening of the Amundsen low, which resulted in increased SIE in the Ross Sea. Most of the studies mentioned above used SIC and SIE derived from satellite passive microwave data for long-term trend analysis of Antarctic sea ice or to investigate individual, seasonal sea ice anomaly events. Since the sea ice classes identified in this study represent significant annual SIC cycles, changes in spatial distribution patterns are clear indications of climatically relevant trends in Antarctic sea ice. Our classification-based consideration of entire annual cycles reduces the influence of short-term SIC fluctuations and focuses on climatologically relevant annual anomalies and long-term trends. The nonparametric Mann–Whitney U test is preferred, rather than the two-tailed t test or Welch test

| RESULTS

Findings

| SUMMARY AND OUTLOOK