Advancing seasonal predictions of Arctic sea ice
Satellite observations of sea ice thickness provide an opportunity to improve seasonal predictions of Arctic sea ice cover.
Arctic sea ice grows and melts each year with the seasons, reaching its low point in September. Summer sea ice cover has shrunk significantly over the past thirty years, although variation from year to year means that the downward trend is not uniform. Arctic sea ice plays a critical role in regulating weather and climate in and beyond the region. Sea ice decline activates a feedback loop in the climate system: as highly reflective ice cover shrinks, darker ocean waters that absorb more of the sun’s energy are exposed. Earth’s surface warms further, driving further ice melt, and so on, affecting global climate and Earth’s energy balance. Impacts include potential influence on Arctic and mid-latitude weather, and many human-related effects such as increased vulnerability of Alaskan coastal communities to erosion and storm surge, shifting habitats for Arctic wildlife that support subsistence livelihoods, opening of shipping routes across the Arctic, and new opportunities for resource extraction industries.
The combination of Arctic sea ice decline, its far-reaching implications for weather and climate, and its importance for diverse stakeholders has fueled an emerging research focus on predicting sea ice extent at monthly or longer timescales. In the context of overall decline, summer sea ice cover varies from year to year. Using satellite observations of current conditions, current models can predict annual changes in sea ice extent up to six months ahead of time with some skill, depending on the initial month and model used. Researchers seek to understand which physical mechanisms and supporting observations could improve forecast accuracy and extend forecast lead times. Sea ice thickness, because of its persistence on seasonal time scales, is one potential source of predictive skill for summer sea ice extent. Newer satellite observations of sea ice thickness across the Arctic provide an opportunity to improve model predictions by using better measurements of thickness as inputs into seasonal forecast models.
Researchers found that annual sea ice volume anomalies (departures from average) tend to grow over the summer months, driven by the relationship between sea ice thickness and its ability to reflect sunlight (known as the ice-albedo feedback) . Sea ice thickness affects ice concentration, melt onset date, snow coverage, and ice thickness distribution, all of which influence how much energy the surface absorbs from the sun. Declines in sea ice thickness increase the amount of energy that the surface absorbs, driving a feedback loop of further warming and further declines in ice thickness. Similar summertime growth occurs in greater than average volume anomalies as well. This phenomenon highlights the importance of using accurate sea ice volume data as an input to seasonal sea ice prediction models and global climate models that project future climate change, and in accurately representing these dynamics in both types of models.
This research was supported by NOAA’s Climate Variability and Predictability program and used data from NASA and the NOAA National Center for Environmental Prediction