Variability along the Atlantic water pathway in the forced Norwegian Earth System Model

The growing attention on mechanisms that can provide predictability on interannual-to-decadal time scales, makes it necessary to identify how well climate models represent such mechanisms. In this study we use a high (0.25° horizontal grid) and a medium (1°) resolution version of a forced global ocean-sea ice model, utilising the Norwegian Earth System Model, to assess the impact of increased ocean resolution. Our target is the simulation of temperature and salinity anomalies along the pathway of warm Atlantic water in the subpolar North Atlantic and the Nordic Seas. Although the high resolution version has larger biases in general at the ocean surface, the poleward propagation of thermohaline anomalies is better resolved in this version, i.e., the time for an anomaly to travel northward is more similar to observation based estimates. The extent of these anomalies can be rather large in both model versions, as also seen in observations, e.g., stretching from Scotland to northern Norway. The easternmost branch into the Nordic and Barents Seas, carrying warm Atlantic water, is also improved by higher resolution, both in terms of mean heat transport and variability in thermohaline properties. A more detailed assessment of the link between the North Atlantic Ocean circulation and the thermohaline anomalies at the entrance of the Nordic Seas reveals that the high resolution is more consistent with mechanisms that are previously published. This suggests better dynamics and variability in the subpolar region and the Nordic Seas in the high resolution compared to the medium resolution. This is most likely due a better representation of the mean circulation in the studied region when using higher resolution. As the poleward propagation of ocean heat anomalies is considered to be a key source of climate predictability, we recommend that similar methodology presented herein should be performed on coupled climate models that are used for climate prediction.publishedVersio

Causes of the large warm bias in the Angola–Benguela Frontal Zone in the Norwegian Earth System Model

We have investigated the causes of the sea surface temperature (SST) bias in the Angola–Benguela Frontal Zone (ABFZ) of the southeastern Atlantic Ocean simulated by the Norwegian Earth System Model (NorESM). Similar to other coupled-models, NorESM has a warm SST bias in the ABFZ of up to 8 °C in the annual mean. Our analysis of NorESM reveals that a cyclonic surface wind bias over the ABFZ drives a locally excessively strong southward (0.05 m/s (relative to observation)) Angola Current displacing the ABFZ southward. A series of uncoupled stand-alone atmosphere and ocean model simulations are performed to investigate the cause of the coupled model bias. The stand-alone atmosphere model driven with observed SST exhibits a similar cyclonic surface circulation bias; while the stand-alone ocean model forced with the reanalysis data produces a warm SST in the ABFZ with a magnitude approximately half of that in the coupled NorESM simulation. An additional uncoupled sensitivity experiment shows that the atmospheric model’s local negative surface wind curl generates anomalously strong Angola Current at the ocean surface. Consequently, this contributes to the warm SST bias in the ABFZ by 2 °C (compared to the reanalysis forced simulation). There is no evidence that local air-sea feedbacks among wind stress curl, SST, and sea level pressure (SLP) affect the ABFZ SST bias. Turbulent surface heat flux differences between coupled and uncoupled experiments explain the remaining 2 °C warm SST bias in NorESM. Ocean circulation, upwelling and turbulent heat flux errors all modulate the intensity and the seasonality of the ABFZ errors.publishedVersio

Evaluation of NorESM-OC (versions 1 and 1.2), the ocean carbon-cycle stand-alone configuration of the Norwegian Earth System Model (NorESM1)

Idealised and hindcast simulations performed with the stand-alone ocean carbon-cycle configuration of the Norwegian Earth System Model (NorESM-OC) are described and evaluated. We present simulation results of two different model versions at different grid resolutions and using two different atmospheric forcing data sets. Model version NorESM-OC1 corresponds to the version that is included in the fully coupled model NorESM-ME1, which participated in CMIP5. The main update between NorESM-OC1 and NorESM-OC1.2 is the addition of two new options for the treatment of sinking particles. We find that using a constant sinking speed, which has been the standard in NorESM's ocean carbon cycle module HAMOCC (HAMburg Ocean Carbon Cycle model) does not transport enough particulate organic carbon (POC) into the deep ocean below approximately 2000 m depth. The two newly implemented parameterisations, a particle aggregation scheme with prognostic sinking speed, and a simpler scheme prescribing a linear increase of sinking speed with depth, provide better agreement with observed POC fluxes. Additionally, reduced deep ocean biases of oxygen and remineralised phosphate indicate a better performance of the new parameterisations. For model version 1.2, a re-tuning of the ecosystem parameterisation has been performed, which (i) reduces previously too high primary production in high latitudes, (ii) consequently improves model results for surface nutrients, and (iii) reduces alkalinity and dissolved inorganic carbon biases at low latitudes. We use hindcast simulations with prescribed observed and constant (pre-industrial) atmospheric CO2 concentrations to derive the past and contemporary ocean carbon sink. For the period 1990–1999 we find an average ocean carbon uptake ranging from 2.01 to 2.58 Pg C yr-1 depending on model version, grid resolution and atmospheric forcing data set

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean- sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean-sea-ice models (JRA55-do).We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean-ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean-sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80% of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP- 2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP- 2. For example, the sea surface temperatures of the OMIP- 2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating processlevel responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean-sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework

Evaluation of global ocean–sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)

We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.This research has been supported by the Integrated Research Program for Advancing Climate Models (TOUGOU) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan (grant nos. JPMXD0717935457 and JPMXD0717935561), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) (grant no. 274762653), the Helmholtz Climate Initiative REKLIM (Regional Climate Change) and European Union's Horizon 2020 Research & Innovation program (grant nos. 727862 and 800154), the Research Council of Norway (EVA (grant no. 229771) and INES (grant no. 270061)), the US National Science Foundation (NSF) (grant no. 1852977), the National Natural Science Foundation of China (grant nos. 41931183 and 41976026), NOAA's Science Collaboration Program and administered by UCAR's Cooperative Programs for the Advancement of Earth System Science (CPAESS) (grant nos. NA16NWS4620043 and NA18NWS4620043B), and NOAA (grant no. NA18OAR4320123).Peer ReviewedPostprint (published version

Copernicus Ocean State Report, issue 6

The 6th issue of the Copernicus OSR incorporates a large range of topics for the blue, white and green ocean for all European regional seas, and the global ocean over 1993–2020 with a special focus on 2020

Development and Applications of Second-Order Turbulence Closures for Mixing in Overflows

Mixing between overflows and ambient water masses is a crucial problem of deep-water formation in the down-welling branch of the meridional overturning circulation of the ocean. In this dissertation work, performance of second-order turbulence closures in reproducing mixing of overflows is investigated within both hydrostatic and non-hydrostatic models. First, a 2D non-hydrostatic model is developed to simulate the Red Sea overflow in the northern channel. The model results are compared to the Red Sea Outflow Experiment. It is found that the experiments without sub-grid scale models cannot reproduce the basic structure of the overflow. The k-ε model yields unrealistically thick bottom layer (BL) and interfacial layer (IL). A new technique so-called very large eddy simulation (VLES) which allows the use of k-ε model in non-hydrostatic models is also employed. It is found that VLES results the most realistic reproduction of the observations. Furthermore, the non-hydrostatic model is improved by introducing laterally average terms, so the model can simulate the constrictions not only in the z-direction but also in the y-direction. Observational data from the Bosphorus Strait is employed to test the spatially average 2D non-hydrostatic model (SAM) in a realistic application. The simulations from SAM with a simple Smagorinsky type closure appear to be excessively diffusive and noisy. We show that SAM can benefit significantly from VLES turbulence closures. Second, the performance of different second-order turbulence closures is extensively tested in a hydrostatic model. Four different two-equation turbulence closures (k-&epsilon, k-&omega, Mellor-Yamada 2.5 (MY2.5) and a modified version of k- &epsilon) and K-Profile Parameterization (KPP) are selected for the comparison of 3D numerical simulations of the Red Sea overflow. All two-equation turbulence models are able to capture the vertical structure of the Red Sea overflow consisting of the BL and IL. MY2.5 with Galperin stability functions produce the largest salinity deviations from the observations along two sections across the overflow and the modified k-&epsilon exhibits the smallest deviations. The rest of the closures fall in between, showing deviations similar to one another. Four different closures (k- &epsilon, k-&omega, MY2.5KC and KPP) are also employed to simulate the Mediterranean outflow. The numerical results are compared with observational data obtained in the 1988 Gulf of Cadiz Expedition. The simulations with two-equation closures reproduce the observed properties of the overflow quite well, especially the evolution of temperature and salinity profiles. The vertically integrated turbulent salt flux displays that the overflow goes under significant mixing outside the west edge of the Strait of Gibraltar. The volume transport and water properties of the outflow are modified significantly in the first 50 km after the overflow exits the strait. The k-&epsilon and k-&omega cases show the best agreement with the observations. Finally, the interaction between the Red Sea overflow and Gulf of Aden (GOA) eddies has been investigated. It is found that the overflow is mainly transported by the undercurrent at the west side of the gulf. The transport of the overflow is episodic depending strength and location of GOA eddies. The most crucial finding is that the Red Sea overflow leaves the Gulf of Aden in patches rather than one steady current. Multiple GOA eddies induce lateral stirring, thus diapycnal mixing of the Red Sea outflow.</p

Diagnosing and Understanding the AMOC Biases in NorESM

We investigate the Atlantic Meridional Overturning Circulation (AMOC) in the Norwegian Earth System Model (NorESM) featuring isopycnal ocean component (MICOM). The Coupled Model Intercomparison Phase 5 (CMIP5) NorESM historical simulations showed a decline of the AMOC after 1980 concurring with the recent observations from RAPID-MOCHA program. The NorESM future projections predict reduction of the AMOC with 12 to 30% under different warming (RCP2.6-RCP8.5) scenarios. In the CMIP5 model intercomparison project, the NorESM ocean component demonstrated an intense AMOC and took place in the upper end of the AMOC magnitudes model range. The NorESM AMOC strength was found to be sensitive to oceanic grid resolution and whether coupled or uncoupled configuration is used. However, the AMOC tends to be on the strong side in all configurations. In order to find the causes of this vigorous AMOC we carried out a careful diagnostics of the AMOC and explored possible relationship to the model biases found in the Atlantic thermohaline structure, and water mass formation. Several processes has been investigated to understand further their connection and significance to the AMOC strength and variability: 1) The North Atlantic Mode Waters Formation (STMW and SPMW); 2) The Labrador Sea Water Mass formation and variability. Furthermore, the AMOC sensitivity to sub-grid scale physical parameterizations such as isopycnal eddy mixing and the impact of model resolution on the representation of overflows is examined

Tracing the Imprint of River Runoff Variability on Arctic Water Mass Transformation

The Arctic Ocean receives a net freshwater input from land and from the atmosphere. This flux of freshwater, along with net surface heat loss, acts to transform the water mass properties of inflowing Atlantic and Pacific waters. In this study, model simulations are used to quantify the Arctic water mass transformation in salinity and temperature space, and its explained variance due to variability in the largest freshwater source to the Arctic: river runoff. This explained variance is quantified using a novel tool, the seasonal climate response function, which describes the magnitude and time scale of adjustment to a runoff perturbation at monthly resolution. Using this method, the transient response of Arctic water mass transformation is reconstructed over time scales ranging from several months to a decade. Model simulations with variable runoff indicate a significant explained model variance of several terms contributing to salinity transformation, including diffusion, the formation and melt of sea ice, and a possibly model‐dependent surface salinity‐restoring term. Most notably, an increase in river runoff strengthens the diffusion of salt and heat, which ultimately leads to an increase in the advective salt and heat import into the Arctic. These results provide evidence for the potential predictability of the Arctic system based on variability in river runoff

Tracing the Imprint of River Runoff Variability on Arctic Water Mass Transformation

The Arctic Ocean receives a net freshwater input from land and from the atmosphere. This flux of freshwater, along with net surface heat loss, acts to transform the water mass properties of inflowing Atlantic and Pacific waters. In this study, model simulations are used to quantify the Arctic water mass transformation in salinity and temperature space, and its explained variance due to variability in the largest freshwater source to the Arctic: river runoff. This explained variance is quantified using a novel tool, the seasonal climate response function, which describes the magnitude and time scale of adjustment to a runoff perturbation at monthly resolution. Using this method, the transient response of Arctic water mass transformation is reconstructed over time scales ranging from several months to a decade. Model simulations with variable runoff indicate a significant explained model variance of several terms contributing to salinity transformation, including diffusion, the formation and melt of sea ice, and a possibly model-dependent surface salinity-restoring term. Most notably, an increase in river runoff strengthens the diffusion of salt and heat, which ultimately leads to an increase in the advective salt and heat import into the Arctic. These results provide evidence for the potential predictability of the Arctic system based on variability in river runoff