Paul Hezel

Projected decline in spring snow depth on Arctic sea ice caused by progressively later autumn open ocean freeze-up this century

We present the first analysis of snow depth on Arctic sea ice in the Coupled Model Intercomparison Project 5 (CMIP5) because of its importance for sea ice thermodynamics and ringed seal (Phoca hispida) habitat. Snow depths in April on Arctic sea ice decrease over the 21st century in RCP2.6, RCP4.5, and RCP8.5 scenarios. The chief cause is loss of sea ice area in autumn and, to a lesser extent, winter. By the end of the 21st century in the RCP8.5 scenario, snowfall accumulation is delayed by about three months compared to the late 20th century in the multi-model mean. Mean April snow depth north of 70°N declines from about 28 cm to 16 cm. Precipitation increases as expected in a warmer climate, but much of this increase in the Arctic occurs as rainfall. The seasonality of snowfall rate grows, with increasing rates in winter and decreasing rates in summer and autumn, but the cumulative snowfall from September to April does not change. Ringed seals depend on spring snow cover on Arctic sea ice to create subnivean birth lairs. The area with snow depths above 20 cm — a threshold needed for ringed seals to build snow caves — declines by 70%.

New Arctic sea ice draft data from submarines

Arctic sea ice thickness data from 17 newly processed submarine cruises covering over 49,000 kilometers of cruise track have now been added to the archive at the National Snow and Ice Data Center (NSIDC). This addition increases the archive by 68%, to a total of over 120,000 kilometers of track from 37 U.S. Navy and 2 Royal Navy submarine cruises. The data are actually of ice draft, the submerged portion of floating sea ice, which is about 89% of ice thickness. Declines in Arctic sea ice extent and thickness in recent decades make this an invaluable data set for research into Arctic climate variations [e.g., Tucker et al., 2001], for testing sea ice models [e.g., Rothrock et al., 2003; Miller et al., 2005], and for intercomparison with measurements of thickness by other methods [e.g., Laxon et al., 2003].

What is the Trajectory of Arctic Sea Ice

We consider the trajectory in phase space of the Arctic sea ice thickness distribution, in which each dimension or component is the time series of sea ice area for a given ice thickness bin. We analyze the trajectory as determined by output from an ice-ocean model, finding that the first two principal components account for 98% of the variance. Simplifying the ice thickness distribution into thin ice, thick ice, and open water, we construct a simple empirical linear model that converges to a stable annual cycle from any initial state. When we include a quadratic nonlinearity to simulate a crude ice-albedo feedback, the model exhibits two stable states, one with perennial ice and one with ice-free summers, resembling the projections of some climate models for the late 21st century. We discuss the interplay between external forcing, internal dynamics, and “tipping points” in the decline of Arctic sea ice.