Light Under Arctic Sea Ice in Observations and Earth System Models. Issue 3 (2nd March 2023)

• Record Type: Journal Article
• Authors: Lebrun, Marion; Vancoppenolle, Martin; Madec, Gurvan; Babin, Marcel; Becu, Guislain; Lourenço, Antonio; Nomura, Daiki; Vivier, Frederic; Delille, Bruno
• Is Part Of: Journal of geophysical research. Volume 128:Issue 3(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-03-02
• Subjects: sea ice -- optics -- modeling; Oceanography -- Periodicals; 551.4605
• DOI: 10.1029/2021JC018161
• Languages: English
• ISSNs: 2169-9275

Abstract

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. Plain Language Summary: The Arctic sea ice cover has rapidly decreased over the last four decades, and Earth System Models (ESMs) project a complete decay of summer Arctic sea ice in the coming decades. As a result, phytoplankton, micro‐algae growing and drifting within seawater, experience increased light supply, favorable to photosynthesis. Phytoplankton is central to the Arctic marine ecosystem, because of its role as a carbon source to the whole food chain. However, there is low confidence in the capacity of models to project Arctic phytoplankton. This is because of large difficulties in simulating nutrient and light supply mechanisms, stemming from limits in basic understanding. Here we gather and analyze a large database of observations of the sea ice environment from the Northern Hemisphere. Snow depth and melt ponds emerge as key drivers of the under‐ice light climate. We also evaluate and improve a calculation method for light intensity and color used in several ESMs, and largely improve agreement with observations as compared with reference. Our results will contribute to lower uncertainties in light climate under sea ice in future ESM projections. Key Points: Snow depth, melt ponds, ice thickness, Chlorophyll‐a in sea ice, influence under‐ice light intensity and spectral distribution Seasonal variations in light intensity under sea ice are reproduced by Earth System Model parameterizations informed by observed environmental conditions Large uncertainties stem from measurement errors, missing physics in the parameterizations, and inconsistent comparison protocol