Abstract
Abstract. Arctic sea ice experiences a dramatic annual cycle, and seasonal ice loss and growth can be characterized by various metrics: melt onset, breakup, opening, freeze onset, freeze-up, and closing. By evaluating a range of seasonal sea ice metrics, CMIP6 sea ice simulations can be evaluated in more detail than by using traditional metrics alone, such as sea ice area. We show that models capture the observed asymmetry in seasonal sea ice transitions, with spring ice loss taking about 1–2 months longer than fall ice growth. The largest impacts of internal variability are seen in the inflow regions for melt and freeze onset dates, but all metrics show pan-Arctic model spreads exceeding the internal variability range, indicating the contribution of model differences. Through climate model evaluation in the context of both observations and internal variability, we show that biases in seasonal transition dates can compensate for other unrealistic aspects of simulated sea ice. In some models, this leads to September sea ice areas in agreement with observations for the wrong reasons.
Highlights
Metrics of seasonality have been underutilized in evaluating sea ice in climate models due to a lack of long-term observational products, the required daily model output, and the complexities in defining seasonal Arctic sea ice transitions
There are multiple possible variables for diagnosing melt and freeze onset, such as surface temperature, thermodynamic ice growth, and snowmelt, and the choice of variable has been shown to impact which processes are captured by the dates as well as their comparability to satellite data (Smith and Jahn, 2019). Another strategy for defining seasonal sea ice transitions is to create metrics based on ice concentration, a variable that has good spatial and temporal satellite data coverage since satellite-observed ice concentration is derived from passive microwave brightness temperatures (Comiso et al, 1997)
Seasonal sea ice transitions can be characterized by various metrics, and each metric represents a distinct stage of sea ice loss or gain
Summary
Metrics of seasonality have been underutilized in evaluating sea ice in climate models due to a lack of long-term observational products, the required daily model output, and the complexities in defining seasonal Arctic sea ice transitions. New process-based metrics for model evaluation are much needed; the spread between climate model projections of sea ice area has been on the order of mil-
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