Sea-ice extent and its trend provide limited metrics of model performance

We examine how the evaluation of modelled sea-ice coverage against reality is affected by uncertainties in the retrieval of sea-ice coverage from satellite, by the usage of sea-ice extent to overcome these uncertainties, and by internal variability. We find that for Arctic summer sea ice, model biases in sea-ice extent can be qualitatively different from biases in sea-ice area. This is because about half of the CMIP5 models and satellite retrievals based on the Bootstrap and the ASI algorithm show a compact ice cover in summer with large areas of high-concentration sea ice, while the other half of the CMIP5 models and satellite retrievals based on the NASA Team algorithm show a loose ice cover. For the Arctic winter sea-ice cover, differences in grid geometry can cause synthetic biases in sea-ice extent that are larger than the observational uncertainty. Comparing the uncertainty arising directly from the satellite retrievals with those that arise from internal variability, we find that the latter by far dominates the uncertainty estimate for trends in sea-ice extent and area: most of the differences between modelled and observed trends can simply be explained by internal variability. For absolute sea-ice area and sea-ice extent, however, internal variability cannot explain the difference between model and observations for about half the CMIP5 models that we analyse here. All models that we examined have regional biases, as expressed by the root-mean-square error in concentration, that are larger than the differences between individual satellite algorithms

Insights on past and future sea-ice evolution from combining observations and models

We discuss the current understanding of past and future sea-ice evolution as inferred from combining model simulations and observations. In such combined analysis, the models allow us to enhance our understanding behind the observed evolution of sea ice, while the observations allow us to assess how realistically the models represent the processes that govern sea-ice evolution in the real world. Combined, observations and models thus provide robust insights into the functioning of sea ice in the Earth's climate system, and can inform policy decisions related to the future evolution of the ice cover. We find that models and observations agree well on the sensitivity of Arctic sea ice to global warming and on the main drivers for the observed retreat. In contrast, a robust reduction of the uncertainty range of future sea-ice evolution remains difficult, in particular since the observational record is often too short to robustly examine the impact of internal variability on model biases. Process-based model evaluation and model evaluation based on seasonal-prediction systems provide promising ways to overcome these limitations

Observations reveal external driver for Arctic sea-ice retreat

The very low summer extent of Arctic sea ice that has been observed in recent years is often casually interpreted as an early-warning sign of anthropogenic global warming. For examining the validity of this claim, previously IPCC model simulations have been used. Here, we focus on the available observational record to examine if this record allows us to identify either internal variability, self-acceleration, or a specific external forcing as the main driver for the observed sea-ice retreat. We find that the available observations are sufficient to virtually exclude internal variability and self-acceleration as an explanation for the observed long-term trend, clustering, and magnitude of recent sea-ice minima. Instead, the recent retreat is well described by the superposition of an externally forced linear trend and internal variability. For the externally forced trend, we find a physically plausible strong correlation only with increasing atmospheric CO2 concentration. Our results hence show that the observed evolution of Arctic sea-ice extent is consistent with the claim that virtually certainly the impact of an anthropogenic climate change is observable in Arctic sea ice already today

Changing state of Arctic sea ice across all seasons

The decline in the floating sea ice cover in the Arctic is one of the most striking manifestations of climate change. In this review, we examine this ongoing loss of Arctic sea ice across all seasons. Our analysis is based on satellite retrievals, atmospheric reanalysis, climate-model simulations and a literature review. We find that relative to the 1981-2010 reference period, recent anomalies in spring and winter sea ice coverage have been more significant than any observed drop in summer sea ice extent (SIE) throughout the satellite period. For example, the SIE in May and November 2016 was almost four standard deviations below the reference SIE in these months. Decadal ice loss during winter months has accelerated from -2.4%/decade from 1979 to 1999 to-3.4%/decade from 2000 onwards. We also examine regional ice loss and find that for any given region, the seasonal ice loss is larger the closer that region is to the seasonal outer edge of the ice cover. Finally, across all months, we identify a robust linear relationship between pan-Arctic SIE and total anthropogenic CO2 emissions. The annual cycle of Arctic sea ice loss per ton of CO2 emissions ranges from slightly above 1 m(2) throughout winter to more than 3 m(2) throughout summer. Based on a linear extrapolation of these trends, we find the Arctic Ocean will become sea-ice free throughout August and September for an additional 800 +/- 300 Gt of CO2 emissions, while it becomes ice free from July to October for an additional 1400 +/- 300Gt of CO2 emissions

A non-destructive method for measuring the salinity and solid fraction of growing sea ice in situ

We describe an instrument developed to make in situ measurements of salinity and solid-fraction profiles in growing sea ice. The vertical resolution of the measurements is up to a few millimeters, with a temporal resolution of up to fractions of a second. The technique is based on impedance measurements between platinum wires around which sea ice grows. Data obtained using this instrument in laboratory experiments are in good agreement with theoretical predictions. In a field test in the Arctic, the bulk salinity of growing sea ice has been measured in situ throughout the whole depth of the ice layer. The data are compared with bulk salinities obtained from ice cores, and confirm the general understanding that the bulk salinity in ice-core studies is significantly underestimated in the lower parts of the cores. The approach can also be used in other glaciological applications and for general studies of two-phase, two-component porous media

Anthropogenic influence on recent circulation-driven Antarctic sea-ice changes

Observations reveal an increase of Antarctic sea ice over the past three decades, yet global climate models tend to simulate a sea-ice decrease for that period. Here, we combine observations with model experiments (MPI-ESM) to investigate causes for this discrepancy and for the observed sea-ice increase. Based on observations and atmospheric reanalysis, we show that on multi-decadal time scales Antarctic sea-ice changes are linked to intensified meridional winds that are caused by a zonally asymmetric lowering of the high-latitude surface pressure. In our simulations, this surface-pressure lowering is a response to a combination of anthropogenic stratospheric ozone depletion and greenhouse gas increase. Combining these two lines of argument, we infer a possible anthropogenic influence on the observed sea-ice changes. However, similar to other models, MPI-ESM simulates a surface-pressure response that is rather zonally symmetric, which explains why the simulated sea-ice response differs from observations

On the origin of discrepancies between observed and simulated memory of Arctic Sea ice

To investigate the inherent predictability of sea ice and its representation in climate models, we compare the seasonal-to-interannual memory of Arctic sea ice as given by lagged correlations of sea-ice area anomalies in large model ensembles (Max Planck Institute Grand Ensemble and Coupled Model Intercomparison Project phase 6) and multiple observational products. We find that state-of-the-art climate models significantly overestimate the memory of pan-Arctic sea-ice area from the summer months into the following year. This cannot be explained by internal variability. We further show that the observed summer memory can be disentangled regionally into a reemergence of positive correlations in the perennial ice zone and negative correlations in the seasonal ice zone; the latter giving rise to the discrepancy between observations and model simulations. These findings could explain some of the predictability gap between potential and operational forecast skill of Arctic sea-ice area identified in previous studies