An official website of the United States government
Abstract Models struggle to accurately simulate observed sea ice thickness changes, which could be partially due to inadequate representation of thermodynamic processes. We analyzed co‐located winter observations of the Arctic sea ice from the Multidisciplinary Drifting Observatory for the Study of the Arctic Climate for evaluating and improving thermodynamic processes in sea ice models, aiming to enable more accurate predictions of the warming climate system. We model the sea ice and snow heat conduction for observed transects forced by realistic boundary conditions to understand the impact of the non‐resolved meter‐scale snow and sea ice thickness heterogeneity on horizontal heat conduction. Neglecting horizontal processes causes underestimating the conductive heat flux of 10% or more. Furthermore, comparing model results to independent temperature observations reveals a ∼5 K surface temperature overestimation over ice thinner than 1 m, attributed to shortcomings in parameterizing surface turbulent and radiative fluxes rather than the conduction. Assessing the model deficiencies and parameterizing these unresolved processes is required for improved sea ice representation.
more »
« less
Effects of Increasing the Category Resolution of the Sea Ice Thickness Distribution in a Coupled Climate Model on Arctic and Antarctic Sea Ice Mean State
Abstract Many modern sea ice models used in global climate models represent the subgrid‐scale heterogeneity in sea ice thickness with an ice thickness distribution (ITD), which improves model realism by representing the significant impact of the high spatial heterogeneity of sea ice thickness on thermodynamic and dynamic processes. Most models default to five thickness categories. However, little has been done to explore the effects of the resolution of this distribution (number of categories) on sea‐ice feedbacks in a coupled model framework and resulting representation of the sea ice mean state. Here, we explore this using sensitivity experiments in CESM2 with the standard 5 ice thickness categories and 15 ice thickness categories. Increasing the resolution of the ITD in a run with preindustrial climate forcing results in substantially thicker Arctic sea ice year‐round. Analyses show that this is a result of the ITD influence on ice strength. With 15 ITD categories, weaker ice occurs for the same average thickness, resulting in a higher fraction of ridged sea ice. In contrast, the higher resolution of thin ice categories results in enhanced heat conduction and bottom growth and leads to only somewhat increased winter Antarctic sea ice volume. The spatial resolution of the ICESat‐2 satellite mission provides a new opportunity to compare model outputs with observations of seasonal evolution of the ITD in the Arctic (ICESat‐2; 2018–2021). Comparisons highlight significant differences from the ITD modeled with both runs over this period, likely pointing to underlying issues contributing to the representation of average thickness.
more »
« less
- PAR ID:
- 10373012
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Oceans
- Volume:
- 127
- Issue:
- 10
- ISSN:
- 2169-9275
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Abstract. Ocean–sea-ice coupled models constrained by various observations provide different ice thickness estimates in the Antarctic. We evaluatecontemporary monthly ice thickness from four reanalyses in the Weddell Sea: the German contribution of the project Estimating the Circulation and Climate ofthe Ocean Version 2 (GECCO2), the Southern Ocean State Estimate (SOSE), the Ensemble Kalman Filter system based on the Nucleus for European Modelling of the Ocean (NEMO-EnKF) and the Global Ice–Ocean Modeling and Assimilation System (GIOMAS). The evaluation is performed againstreference satellite and in situ observations from ICESat-1, Envisat, upward-looking sonars and visual ship-based sea-ice observations. Compared withICESat-1, NEMO-EnKF has the highest correlation coefficient (CC) of 0.54 and lowest root mean square error (RMSE) of 0.44 m. Compared within situ observations, SOSE has the highest CC of 0.77 and lowest RMSE of 0.72 m. All reanalyses underestimate ice thickness near the coast ofthe western Weddell Sea with respect to ICESat-1 and in situ observations even though these observational estimates may be biased low. GECCO2 andNEMO-EnKF reproduce the seasonal variation in first-year ice thickness reasonably well in the eastern Weddell Sea. In contrast, GIOMAS ice thicknessperforms best in the central Weddell Sea, while SOSE ice thickness agrees most with the observations from the southern coast of the Weddell Sea. Inaddition, only NEMO-EnKF can reproduce the seasonal evolution of the large-scale spatial distribution of ice thickness, characterized by the thickice shifting from the southwestern and western Weddell Sea in summer to the western and northwestern Weddell Sea in spring. We infer that the thickice distribution is correlated with its better simulation of northward ice motion in the western Weddell Sea. These results demonstrate thepossibilities and limitations of using current sea-ice reanalysis for understanding the recent variability of sea-ice volume in the Antarctic.more » « less
-
Arctic sea ice growth in response to synoptic- and large-scale atmospheric forcing from CMIP5 modelsnull (Ed.)We explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing. The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate.more » « less
-
Sea ice thickness is a key parameter in the polar climate and ecosystem. Thermodynamic and dynamic processes alter the sea ice thickness. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provided a unique opportunity to study seasonal sea ice thickness changes of the same sea ice. We analyzed 11 large-scale (∼50 km) airborne electromagnetic sea thickness and surface roughness surveys from October 2019 to September 2020. Data from ice mass balance and position buoys provided additional information. We found that thermodynamic growth and decay dominated the seasonal cycle with a total mean sea ice thickness increase of 1.4 m (October 2019 to June 2020) and decay of 1.2 m (June 2020 to September 2020). Ice dynamics and deformation-related processes, such as thin ice formation in leads and subsequent ridging, broadened the ice thickness distribution and contributed 30% to the increase in mean thickness. These processes caused a 1-month delay between maximum thermodynamic sea ice thickness and maximum mean ice thickness. The airborne EM measurements bridged the scales from local floe-scale measurements to Arctic-wide satellite observations and model grid cells. The spatial differences in mean sea ice thickness between the Central Observatory (<10 km) of MOSAiC and the Distributed Network (<50 km) were negligible in fall and only 0.2 m in late winter, but the relative abundance of thin and thick ice varied. One unexpected outcome was the large dynamic thickening in a regime where divergence prevailed on average in the western Nansen Basin in spring. We suggest that the large dynamic thickening was due to the mobile, unconsolidated sea ice pack and periodic, sub-daily motion. We demonstrate that this Lagrangian sea ice thickness data set is well suited for validating the existing redistribution theory in sea ice models. Our comprehensive description of seasonal changes of the sea ice thickness distribution is valuable for interpreting MOSAiC time series across disciplines and can be used as a reference to advance sea ice thickness modeling.more » « less
-
Vertical heat conduction through young ice is a major source of wintertime sea ice growth in the Arctic. However, field observations indicate that young ice preferentially accumulates wind-blown snow, resulting in greater snow thickness on young ice than would be expected from precipitation alone, and hence greater snow thickness on young ice than climate models represent. As snow has a low thermal conductivity, this additional snow thickness due to redistribution will reduce the actual heat conduction. We present new observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate Expedition which show that young ice rapidly accumulates a snow thickness of 2.5–8 cm, when wind-blown snow is available from the nearby mature ice. By applying a simple redistribution scheme and heat flux model to simulated conditions from the Community Earth System Model 2.0, we suggest that neglecting this snow redistribution onto young ice could result in the potential overestimation of conductive heat flux—and hence ice growth rates—by 3–8% on average in the Arctic in the winter in the absence of climate feedbacks. The impacts of snow redistribution are highest in the springtime and in coastal regions.more » « less
