Using Arctic ice mass balance buoys for evaluation of modelled ice energy fluxes
<p>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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-10-01
|
| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/13/4845/2020/gmd-13-4845-2020.pdf |
| Summary: | <p>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.</p>
<p>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.</p> |
|---|---|
| ISSN: | 1991-959X 1991-9603 |