Deliverable No. 2.5 Final report on model developments and their evaluation in coupled mode
In such a remote and harsh environment as the Arctic, the monitoring of essential climate variables is expensive and, therefore, sporadic. In turn, satellites provide observations constrained to the surface. Also, because of technical restrictions, satellites cannot sample, at least not year-round,...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Report |
| Language: | English |
| Published: |
Zenodo
2021
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5281/zenodo.4916933 https://zenodo.org/record/4916933 |
| Summary: | In such a remote and harsh environment as the Arctic, the monitoring of essential climate variables is expensive and, therefore, sporadic. In turn, satellites provide observations constrained to the surface. Also, because of technical restrictions, satellites cannot sample, at least not year-round, a set of essential variables, such as the sea ice thickness. To overcome this difficulty, numerical models are key tools for studying and predicting the Arctic weather and climate. Numerical models aim at reproducing the interactions between different climate components such as the land, atmosphere, ocean, and sea ice. Such interactions are complex and described with non-linear functions. This is one reason numerical models are in constant improvement. The primary goals of Work Package 2 are to promote improvements in numerical models and establish the impact of these improvements on model results, both for the study of the Arctic climate and numerical weather prediction. This deliverable presents a set of model enhancements that are implemented and tested in fully coupled models (AWI-CM1, HadGEM3-GC3.1, EC-Earth3 PRIMAVERA, and ECMWF IFS CY45R1) and forced-mode (NEMO3.6-LIM3 and GELATO). All model developments aim to improve the representation of physical processes that take place in the sea ice or snow. These consist of a better representation of the turbulent exchanges of heat and momentum between the atmosphere and sea ice (form drag), a description of the melt ponds that appear on the sea ice surface during the melt season (melt ponds), a parameterization which takes into account the effect of the sea ice attached to the shore and ocean floor (landfast ice), a scheme which accounts for the size of the floes that form the sea ice cover (floe size distribution), and an improved representation of the snow both over land and sea ice (multilayer snow scheme). We assess the benefit of the model developments based on the following five aspects: (i) changes in various components of the Arctic surface energy budget, (ii) changes in the transfer of momentum from the atmosphere to the ocean, (iii) the overall realism of the simulated climate system, (iv) effects on the Arctic Ocean circulation, and (v) changes in the Arctic climate sensitivity. Common results emerged from the form drag experiments: increased sea ice drift speed in the marginal ice zone, a general decrease in ice thickness, and a marginal decrease of ice concentration at the ice edge in summer. The form drag parameterization improved the large-scale atmospheric and ocean-driven ocean circulation. The melt pond parameterization shows a clear impact on the albedo and sea ice variability and reinforces that a reduced sea ice regime in the Arctic impacts the large-scale, density-driven ocean circulation. The multilayer snow scheme makes the models more sensitive to the surface thermodynamic forcing than the control run with a single layer of snow and shows a more realistic albedo. In numerical weather prediction, the multilayer scheme leads to an improved prediction of the 2-m temperature diurnal cycle over land. Over sea ice, the new scheme reduces large positive biases of outgoing longwave radiation. Fast ice developments lead to more realistic sea ice conditions supported by evidence from observational data. Parameterization of floe size distribution reveals sea ice growth caused by large ice floes in the marginal ice zone during summer. |
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