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The Los Alamos Sea Ice Model (CICE) is used by several Earth system models where sea ice boundary conditions are not necessary, given their global scope. However, regional and local implementations of sea ice models require boundary conditions describing the time changes of the sea ice and snow being exchanged across the boundaries of the model domain. The physical detail of these boundary conditions regarding, for example, the usage of different sea ice thickness categories or the vertical resolution of thermodynamic properties, must be considered when matching them with the requirements of the sea ice model. Available satellite products do not include all required data. Therefore, the most straightforward way of getting sea ice boundary conditions is from a larger-scale model. The main goal of our study is to describe and evaluate the implementation of time-varying sea ice boundaries in the CICE model using two regional coupled ocean–sea ice models, both covering a large part of the Barents Sea and areas around Svalbard: the Barents-2.5 km, implemented at the Norwegian Meteorological Institute (MET), and the Svalbard 4 km (S4K) model, implemented at the Norwegian Polar Institute (NPI). We use the TOPAZ4 model and a Pan-Arctic 4 km resolution model (A4) to generate the boundary conditions for the sea ice and the ocean. The Barents-2.5 km model is MET’s main forecasting model for ocean state and sea ice in the Barents Sea. The S4K model covers a similar domain but it is used mainly for research purposes. Obtained results show significant improvements in the performance of the Barents-2.5 km model after the implementation of the time-varying boundary conditions. The performance of the S4K model in terms of sea ice and snow thickness is comparable to that of the TOPAZ4 system but with more accurate results regarding the oceanic component because of using ocean boundary conditions from the A4 model. The implementation of time-varying boundary conditions described in this study is similar regardless of the CICE versions used in different models. The main challenge remains the handling of data from larger models before its usage as boundary conditions for regional/local sea ice models, since mismatches between available model products from the former and specific requirements of the latter are expected, implying case-specific approaches and different assumptions. Ideally, model setups should be as similar as possible to allow a smoother transition from larger to smaller domains. Implementation and evaluation of open boundary conditions for sea ice in a regional coupled ocean (ROMS) and sea ice (CICE) modeling system

This is chapter 1 of the State of Environmental Science in Svalbard (SESS) report 2020 (https://sios-svalbard.org/SESS_Issue3). Situated in the Arctic and in a region with relatively pristine conditions, Svalbard is a very important and interdisciplinary observational supersite for the Arctic. In this SESS report, we investigate how representative Svalbard is for the Arctic region as a whole using data from numerical simulations with climate models. In our study comparing model predictions of how temperature, precipitation, and sea-ice extent develop over time, we found that the changes in Svalbard resemble those in the Arctic as a whole, both during the warming period of the past few decades and during projected future climate change. However, some important differences were found (see Highlights). Predicting and characterising climate change in Svalbard will be increasingly important in the 21st century as changes in near-surface air temperature, precipitation and sea-ice extent seem to occur at an extremely high pace in Svalbard, even higher than in the rest of the Arctic. Closer collaboration between experimentalists, observationalists, and the modelling community could help us understand the mechanisms underlying differences between observed and modelled climate changes. SIOS is in a unique position to coordinate and facilitate such collaborative research. &nbsp

We consider possible changes in the future climate of wind speed (WS), significant wave height (SWH) and storm surge residual (SSR) for a region covering the Northern Seas. Our results are based on an analysis of changes in the response derived with regional atmosphere, wave, and storm surge models run for two time periods 1961–1990 and 2071–2100. Available for the study were atmospheric downscalings of the Hadley Centre’s SRES A2 and B2 scenarios, the Max-Planck Institute’s SRES B2 scenario and the Bjerknes Centre’s SRES A1B scenario. The most important statistically significant findings are, first, a decrease in WS south of Iceland accompanied by a decrease of about 4–6% in SWH. Secondly, there is an increase in the eastern North Sea that continues into the Skagerrak. Along the North Sea east coast and in the Skagerrak the annual 99-percentiles of SWH and SSR increase 6–8% and 8–10%, respectively, and these results are robust across the various choices in global models and emission scenarios. Finally, there is an increase in the annual 99-percentiles of all variables west of the British Isles.

Climate responses to aerosol forcing at present-day and doubled CO2-levels are studied based on equilibrium simulations with the CCM-Oslo atmospheric GCM coupled to a slab ocean. Aerosols interact on-line with meteorology through life-cycling of sulphate and black carbon (BC), and tables for aerosol optics and CCN activation. Anthropogenic aerosols counteract the warming by CO2 through a negative radiative forcing dominated by the indirect effect. Anthropogenic aerosols reduce precipitation by 4%, while CO2 doubling gives a 5% increase, mainly through enhanced convective activity, including a narrower ITCZ. Globally, the aerosol cooling is insensitive to CO2, and the effects of CO2 doubling are insensitive to aerosols. Hence, global climate responses to these sources of forcing are almost additive, although sulphate and BC burdens are slightly increased due to reduced stratiform precipitation over major anthropogenic source regions and a modified ITCZ. Regionally, positive cloud feedbacks give up to 5 K stronger aerosol cooling at present-day CO2 than after CO2 doubling. Aerosol emissions projected for year-2100 (SRES A2) strongly increase BC and change the sign of the direct effect. This results in a 0.3 K warming and 0.1% increase in precipitation compared to the year 2000, thus enhancing the global warming by greenhouse gases.

The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2) and shares with CESM2 the computer code infrastructure and many Earth system model components. However, NorESM2 employs entirely different ocean and ocean biogeochemistry models. The atmosphere component of NorESM2 (CAM-Nor) includes a different module for aerosol physics and chemistry, including interactions with cloud and radiation; additionally, CAM-Nor includes improvements in the formulation of local dry and moist energy conservation, in local and global angular momentum conservation, and in the computations for deep convection and air–sea fluxes. The surface components of NorESM2 have minor changes in the albedo calculations and to land and sea-ice models. We present results from simulations with NorESM2 that were carried out for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Two versions of the model are used: one with lower (∼ 2∘) atmosphere–land resolution and one with medium (∼ 1∘) atmosphere–land resolution. The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2are assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. Compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 appears less sensitive to greenhouse gas forcing than its predecessors, with an estimated equilibrium climate sensitivity of 2.5 K in both resolutions on a 150-year time frame; however, this estimate increases with the time window and the climate sensitivity at equilibration is much higher. We also consider the model response to future scenarios as defined by selected Shared Socioeconomic Pathways (SSPs) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM-MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactory evolution of recent sea-ice area. In NorESM2-LM, an ice-free Arctic Ocean is only avoided in the SSP1-2.6 scenario.

The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2) and shares with CESM2 the computer code infrastructure and many Earth system model components. However, NorESM2 employs entirely different ocean and ocean biogeochemistry models. The atmosphere component of NorESM2 (CAM-Nor) includes a different module for aerosol physics and chemistry, including interactions with cloud and radiation; additionally, CAM-Nor includes improvements in the formulation of local dry and moist energy conservation, in local and global angular momentum conservation, and in the computations for deep convection and air–sea fluxes. The surface components of NorESM2 have minor changes in the albedo calculations and to land and sea-ice models. We present results from simulations with NorESM2 that were carried out for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Two versions of the model are used: one with lower (∼ 2∘) atmosphere–land resolution and one with medium (∼ 1∘) atmosphere–land resolution. The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2 are assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. Compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 appears less sensitive to greenhouse gas forcing than its predecessors, with an estimated equilibrium climate sensitivity of 2.5 K in both resolutions on a 150-year time frame; however, this estimate increases with the time window and the climate sensitivity at equilibration is much higher. We also consider the model response to future scenarios as defined by selected Shared Socioeconomic Pathways (SSPs) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM-MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactory evolution of recent sea-ice area. In NorESM2-LM, an ice-free Arctic Ocean is only avoided in the SSP1-2.6 scenario.