Abstract
Abstract. A new method of sea ice model evaluation is demonstrated. Data from the network of Arctic ice mass balance buoys (IMBs) are used to estimate distributions of vertical energy fluxes over sea ice in two densely sampled regions – the North Pole and Beaufort Sea. The resulting dataset captures seasonal variability in sea ice energy fluxes well, and it captures spatial variability to a lesser extent. The dataset is used to evaluate a coupled climate model, HadGEM2-ES (Hadley Centre Global Environment Model, version 2, Earth System), in the two regions. The evaluation shows HadGEM2-ES to simulate too much top melting in summer and too much basal conduction in winter. These results are consistent with a previous study of sea ice state and surface radiation in this model, increasing confidence in the IMB-based evaluation. In addition, the IMB-based evaluation suggests an additional important cause for excessive winter ice growth in HadGEM2-ES, a lack of sea ice heat capacity, which was not detectable in the earlier study. Uncertainty in the IMB fluxes caused by imperfect knowledge of ice salinity, snow density and other physical constants is quantified (as is inaccuracy due to imperfect sampling of ice thickness) and in most cases is found to be small relative to the model biases discussed. Hence the IMB-based evaluation is shown to be a valuable tool with which to analyse sea ice models and, by extension, better understand the large spread in coupled model simulations of the present-day ice state. Reducing this spread is a key task both in understanding the current rapid decline in Arctic sea ice and in constraining projections of future Arctic sea ice change.
Highlights
Evaluation of sea ice simulations using metrics based on sea ice extent (e.g. Stroeve et al, 2012; Wang and Overland, 2012) is known to be an imperfect method of assessing models (Notz, 2015)
Around 500 estimates of monthly mean top melt, top conduction, basal conduction and ocean heat flux have been estimated from data measured by the Arctic ice mass balance buoys (IMBs) network, with the number of estimates available for each month ranging from 25 to 59
The flux biases are consistent with an evaluation of the sea ice simulation of HadGEM2-ES that identified an overamplified seasonal cycle in ice thickness, with model ice growth and melt biased high in winter and summer respectively, as well as a high model bias in net SW radiation in June, a low bias in net LW radiation throughout the winter, and a low model bias in ice thickness in autumn and early winter
Summary
Evaluation of sea ice simulations using metrics based on sea ice extent (e.g. Stroeve et al, 2012; Wang and Overland, 2012) is known to be an imperfect method of assessing models (Notz, 2015). Sea ice volume, evaluated for CMIP5 by Stroeve et al (2014) and Shu et al (2015), is less sensitive to internal variability (Olonscheck and Notz, 2018) but is driven by multiple complex processes and so is susceptible to compensating errors These issues hinder understanding of the very large spread in modelled present-day sea ice simulations. Mean fluxes of top melt, top conduction, basal conduction and ocean heat flux are calculated from temperature and elevation data obtained from 104 IMBs released between 1993 and 2015; the resulting observational dataset and the code used in its production are published alongside this study, with references given in the Code availability and Data availability sections below This dataset is used to evaluate the sea ice in a coupled climate model (HadGEM2-ES, part of the CMIP5 ensemble) in two densely sampled regions of the Arctic, the North Pole and the Beaufort Sea. Modelled and IMB-measured fluxes are restricted to each region in turn: distributions of fluxes in each month are compared and likely model biases identified.
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