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Light under Arctic sea ice in observations and earth system models
Lebrun, M.; Vancoppenolle, M.; Madec, G.; Babin, M.; Bécu, G.; Lourenço, A.; Nomura, D.; Vivier, F.; Delille, B. (2023). Light under Arctic sea ice in observations and earth system models. JGR: Oceans 128(3): e2021JC018161. https://dx.doi.org/10.1029/2021JC018161
In: Journal of Geophysical Research-Oceans. AMER GEOPHYSICAL UNION: Washington. ISSN 2169-9275; e-ISSN 2169-9291, meer
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| Trefwoord |
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| Author keywords |
sea ice; optics; modeling |
| Auteurs | | Top |
- Lebrun, M.
- Vancoppenolle, M., meer
- Madec, G.
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- Babin, M.
- Bécu, G.
- Lourenço, A.
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- Nomura, D.
- Vivier, F.
- Delille, B., meer
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| Abstract |
The intensity and spectrum of light under Arctic sea ice, key to the energy budget and primary productivity of the Arctic Ocean, are tedious to observe. Earth System Models (ESMs) are instrumental in understanding the large-scale properties and impacts of under-ice light. To date, however, ESM parameterizations of radiative transfer have been evaluated with a few observations only. From observational programs conducted over the past decade at four locations in the Northern Hemisphere sea ice zone, 349 observational records of under-ice light and coincident environmental characteristics were compiled. This data set was used to evaluate seven ESM parameterizations. Snow depth, melt pond presence and, to some extent, ice thickness explain the observed variance in light intensity, in agreement with previous work. The effects of Chlorophyll-a are also detected, with rather low intensity. The spectral distribution of under-ice light largely differs from typical open ocean spectra but weakly varies among the 349 records except for a weak effect of snow depth on the blue light contribution. Most parameterizations considered reproduce variations in under-ice light intensity. Large errors remain for individual records, on average by a factor of ∼3, however. Skill largely improves if more predictors are considered (snow and ponds in particular). Residual errors are attributed to missing physics in the parametrizations, inconsistencies in the model-observation comparison protocol, and measurement errors. We provide recommendations to improve the representation of light under sea ice in the ice-ocean model NEMO, which may also apply to other ESMs and help improve next-generation ESMs. |
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