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

D Notz

doi:10.5194/tc-8-229-2014

Abstract

Abstract. 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.

Highlights

The evaluation of climate-model simulations against reality is important both to build confidence in future projections from these models and to understand and improve their possible shortcomings
Since our focus here is on sea-ice extent vs. sea-ice area, it is important to understand the cause for the different agreement between these two measures for the satellite algorithms
Examining the frequency distribution of summer sea-ice concentration in the CMIP5 model simulations, we find that these simulations can be divided into two groups

Summary

Introduction

The evaluation of climate-model simulations against reality is important both to build confidence in future projections from these models and to understand and improve their possible shortcomings. Two quantities must be known: first, the real evolution of the variable that is to be evaluated, and second, the degree to which one can expect agreement between simulation and reality in light of the internal variability of the climate system In this contribution we examine how the evaluation of modelled sea-ice coverage is affected by the incomplete knowledge of both quantities and by the standard approach that is taken to overcome this incomplete knowledge. Because of wide-spread cloud coverage, most often the passive microwave signature of the ocean surface as retrieved from satellites is used to derive the most likely sea-ice concentration in a specific area This passive microwave signature is, strongly affected by meltwater at the ice surface and by surface temperature, wind speed, humidity and other atmospheric properties. Because of these influencing factors, different retrieval algorithms result in different estimates of sea-ice concentration in a particular area (see, for example, Comiso et al, 1997; Kwok, 2002; Meier, 2005; Andersen et al, 2007)

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