Sensitivity of the Arctic freshwater content and transport to model resolution

Fuentes‐Franco, Ramón; Köenigk, Torben

doi:10.1007/s00382-019-04735-y

Cited by 11 publications

(10 citation statements)

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“…We do not find any resolution dependency of the correlation between freshwater exports and convection in the Labrador Sea. This result is in contrast to a recent study from Fuentes Franco and Koenigk (2019) where they analyzed a set of HadGEM3-GC2 simulations at different resolutions and found larger correlations with increased resolution. non-eddying to eddy-present and eddy-rich".…”

Section: The Impact Of Arctic Freshwater and Sea Ice Exports On The Variability Of Deep Convectioncontrasting

confidence: 99%

“…Recent studies found that the increased resolution in the HighResMIP models improved many aspects of the ocean including temperature and salinity biases (Gutjahr et al 2019), the northward ocean heat transport (Grist et al 2018), sea ice in the Atlantic sector of the Arctic Ocean (Docquier et al 2019(Docquier et al , 2020, the position of the North Atlantic Current (Sein et al 2018) as well as Arctic freshwater exports (Fuentes Franco and Koenigk 2019), all of them with the potential to improve the representation of Labrador Sea convection.…”

Section: Introductionmentioning

confidence: 99%

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Deep mixed ocean volume in the Labrador Sea in HighResMIP models

et al. 2021

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Simulations from seven global coupled climate models performed at high and standard resolution as part of the high resolution model intercomparison project (HighResMIP) are analyzed to study deep ocean mixing in the Labrador Sea and the impact of increased horizontal resolution. The representation of convection varies strongly among models. Compared to observations from ARGO-floats and the EN4 data set, most models substantially overestimate deep convection in the Labrador Sea. In four out of five models, all four using the NEMO-ocean model, increasing the ocean resolution from 1° to 1/4° leads to increased deep mixing in the Labrador Sea. Increasing the atmospheric resolution has a smaller effect than increasing the ocean resolution. Simulated convection in the Labrador Sea is mainly governed by the release of heat from the ocean to the atmosphere and by the vertical stratification of the water masses in the Labrador Sea in late autumn. Models with stronger sub-polar gyre circulation have generally higher surface salinity in the Labrador Sea and a deeper convection. While the high-resolution models show more realistic ocean stratification in the Labrador Sea than the standard resolution models, they generally overestimate the convection. The results indicate that the representation of sub-grid scale mixing processes might be imperfect in the models and contribute to the biases in deep convection. Since in more than half of the models, the Labrador Sea convection is important for the Atlantic Meridional Overturning Circulation (AMOC), this raises questions about the future behavior of the AMOC in the models.

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Section: The Impact Of Arctic Freshwater and Sea Ice Exports On The Variability Of Deep Convectioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deep mixed ocean volume in the Labrador Sea in HighResMIP models

et al. 2021

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“…The liquid FWC calculation quantifies the vertically integrated salinity anomaly from a particular reference salinity (Sref), which in this case is 34.8 psu indicated by the mean of the Arctic Ocean and commonly used in other studies [7][8][9]. Following Carmack et al [10], Fuentes-Franco et al [11], and Dewey et al [12], we calculate integrated liquid FWC (m) from salinity measurements and estimations using the equation:…”

Section: Observations and Modelsmentioning

confidence: 99%

Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

2021

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Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean.

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“…The third type of error resides in the deficiency of CMIP models to physically describe the dynamical processes in the Arctic Ocean. For example, model resolution can impact the spatial pattern of liquid freshwater in the Arctic Ocean (Fuentes‐Franco & Koenigk, 2019; Q. Wang, Wekerle, Danilov, Wang, & Jung, 2018). Model uncertainty could be also due to important yet missing processes in the model.…”

Section: Discussionmentioning

confidence: 99%

Arctic Ocean Freshwater in CMIP6 Coupled Models

Wang

et al. 2022

Earth's Future

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In this study we assessed the representation of the sea surface salinity (SSS) and liquid freshwater content (LFWC) of the Arctic Ocean in the historical simulation of 31 CMIP6 models with comparison to 39 Coupled Model Intercomparison Project phase 5 (CMIP5) models, and investigated the projected changes in Arctic liquid and solid freshwater content and freshwater budget in scenarios with two different shared socioeconomic pathways (SSP2‐4.5 and SSP5‐8.5). No significant improvement was found in the SSS and LFWC simulation from CMIP5 to CMIP6, given the large model spreads in both CMIP phases. The overestimation of LFWC continues to be a common bias in CMIP6. In the historical simulation, the multi‐model mean river runoff, net precipitation, Bering Strait and Barents Sea Opening (BSO) freshwater transports are 2,928 ± 1,068, 1,839 ± 3,424, 2,538 ± 1,009, and −636 ± 553 km3/year, respectively. In the last decade of the 21st century, CMIP6 MMM projects these budget terms to rise to 4,346 ± 1,484 km3/year (3,678 ± 1,255 km3/year), 3,866 ± 2,935 km3/year (3,145 ± 2,651 km3/year), 2,631 ± 1,119 km3/year (2,649 ± 1,141 km3/year) and 1,033 ± 1,496 km3/year (449 ± 1,222 km3/year) under SSP5‐8.5 (SSP2‐4.5). Arctic sea ice is expected to continue declining in the future, and sea ice meltwater flux is likely to decrease to about zero in the mid‐21st century under both SSP2‐4.5 and SSP5‐8.5 scenarios. Liquid freshwater exiting Fram and Davis straits will be higher in the future, and the Fram Strait export will remain larger. The Arctic Ocean is projected to hold a total of 160,300 ± 62,330 km3 (141,590 ± 50,310 km3) liquid freshwater under SSP5‐8.5 (SSP2‐4.5) by 2100, about 60% (40%) more than its historical climatology.

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Sensitivity of the Arctic freshwater content and transport to model resolution

Cited by 11 publications

References 50 publications

Deep mixed ocean volume in the Labrador Sea in HighResMIP models

Deep mixed ocean volume in the Labrador Sea in HighResMIP models

Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

Arctic Ocean Freshwater in CMIP6 Coupled Models

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