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Several cost-efficient, high-resolution modeling approaches are applied to simulations of the Southern Ocean in past, present, and future climates. The results are compared with an ensemble of medium-resolution, eddy-present simulations and evaluated based on their ability to reproduce observed mesoscale activity and to reveal a response to climate change distinct from natural variability. The high-resolution simulations reproduce the observed magnitude of Southern Ocean eddy kinetic energy (EKE) well, but differences remain in local magnitudes and the spatial distribution of EKE. The coarser, eddy-present ensemble simulates a similar pattern of EKE but underrepresents observed levels by 50 %. Five years of simulated data in each time period is found to produce consistent results when evaluating mean conditions and assessing change in the region as a whole. At 1 °C of warming, the high-resolution simulations produce no change in overall EKE, in contrast to the increase projected by the eddy-permitting ensemble and despite full ensemble agreement. At 4 °C of warming, both datasets produce consistent levels of EKE rise in relative terms, although not absolute magnitudes, as well as an increase in EKE variability. Simulated EKE rise is concentrated where flow interacts with topographic features in regions already known to be eddy-rich. Regional EKE change in the high-resolution simulations is consistent with changes seen in at least four of five eddy-permitting ensemble members at 1 °C of warming, and all ensemble members at 4 °C. However, substantial noise would make these changes difficult to distinguish from natural variability without an ensemble.

This sixth World Ocean Review (WOR) focuses on the Arctic and the Antarctic – two regions which are, in a very real sense, polar opposites, with some of the world’s most extreme conditions. Besides presenting a wealth of facts and figures about the history and exploration of the polar regions, WOR 6 builds a deeper awareness of their key role for life on our planet. It highlights the changes that can be observed in their flora and fauna and analyses the already dramatic impacts of global warming on these extremely fragile regions.

Poster Code: Fri_214_OS-4_1872 Iceberg calving is an important component of the mass balance of the Antarctic Ice Sheet, with recent estimates of ∼1300 Gt/year being on the same level as ice shelf basal melting. The iceberg mass is usually assumed to be evenly divided between giant icebergs (length >10km) and smaller ones, with some estimates even preferring giant icebergs (as high as 89%). However, it is still unclear what the best way is to include giant icebergs into model estimates of the Southern Ocean freshwater cycle. Here, we estimate the iceberg meltwater input from a simulation of present-day Antarctic icebergs and compare it to the balance between precipitation and evaporation (P-E) and sea-ice production rates. For the first time, an iceberg model is initialized with a set of nearly 7000 satellite-observed iceberg positions and sizes. It reproduces typical drift patterns for a large spectrum of size classes, including typical routes taken by giant icebergs. The associated meltwater input is generally on the order of 5–20% of the P-E balance in large areas of the Southern Ocean, especially around the coast, with local maxima even exceeding P-E. Furthermore, the freshwater flux from melting icebergs is on the order of 5–20% of coastal sea ice production rates and, thus, partly compensates the effect of brine rejection in the annual mean. Iceberg melting is also the largest vector of freshwater input from frozen ice along (and northward of) the sea-ice edge.

OS-4b - Sea ice modeling and prediction: Sea ice process understanding Climate models struggle to capture observed Antarctic sea-ice extent trends, which has critical consequences for sea-ice projections. To tackle this, it is often suggested to develop models at high spatial resolution. In this study we focus on the September sea-ice extent in prototype simulations for the “High Resolution Model Intercomparison Project” (HighResMIP). Scenario simulations (RCP8.5) are performed with the AWI Climate Model (AWI-CM) at “high-resolution” in both ocean and atmosphere (HR) and “low-resolution” (LR) under the same protocol. Compared to LR, HR predicts a much weaker warming signal around Antarctica in austral winter for the end of this century (2070-2099) relative to 1976-2005. This may partly be explained by the different sea-ice mean states in LR and HR. However, we also observe increased extent variability and strongly reduced rates of sea-ice decrease. Specifically, HR shows polynya-like features in the Weddell Sea in the pre-satellite era, followed by a stable September sea-ice extent until ~2050. “Mixed-resolution” runs (HR ocean with LR atmosphere, and vice versa) attribute this difference in trends and variability to the HR ocean, independent of the atmospheric resolution. Considering the observed stable Antarctic September sea-ice extent and the recent return of the Weddell polynya, we will discuss possible common mechanisms and implications for other modelling centres participating in HighResMIP.

Atmosphere-ocean coupling is of major importance for numerical climate models. Systematic errors in surface flux computations affect both components simultaneously. As an example, surface flux variations caused by (sub-)mesoscale oceanic features and their impact on the atmospheric circulation are generally underrepresented in current models. In the case of coupled climate models, atmospheric sub-grid scale information is in fact available at the surface, as part of it is typically resolved by the oceanic model component. We present a stochastic scheme that couples resolved spatial ocean (and ice) variability, previously not visible to the atmospheric model. Consequently, the resulting SST perturbations of the stochastic scheme are based on resolved dynamics, displaying a pronounced seasonality and realistic magnitude. We apply the stochastic coupling method in the AWI Climate Model, a new multi-resolution climate model with an ocean component (FESOM) supporting unstructured triangular grids. Our specific setup features a high ocean-to-atmosphere resolution ratio in the tropics, with grid point ratios of about 60:1 (less than 25km to about 200km). Compared to the default deterministic coupling, changes are largest in the tropics, leading to an improved distribution of convective precipitation, and reductions of prominent biases of up to 50%. The scheme does not rely on a simultaneous increase of resolution in the atmospheric component, saving computational resources. The results are also of interest to other modeling centres employing high ocean-to-atmosphere resolution ratios, as the coupling scheme could be implemented relatively easily as an additional coupling option, without a change to the model code. (Oral in AS5.6/BG4.14/CL5.09/OS1.14 - Recent Developments in Numerical Earth System Modelling)

This talk will give an overview about the ocean model developments at the Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research, and summarise example applications made possible by using a novel numerical core. The Finite Element Sea Ice-Ocean Model (FESOM1.4) supports multi-resolution triangular grids and has already been used in many studies in the last decade, with a focus on Arctic and Antarctic sea ice, global ocean circulation, and the impact of locally eddy-resolving resolution. In a coupled climate configuration with ECHAM6, the model now also participates in the 6th phase of the Coupled Model Intercomparison Project (CMIP) and in a number of endorsed MIPs like HighResMIP. The change of the dynamical core to a finite volume formulation speeds up the successor model FESOM2 by a factor of 3. In combination with its nearly linear scalability characteristics that retain a short time-to-solution even for extremely large ocean grids, this extends the range of possible applications dramatically. A recent accomplishment is a prototype single-executable coupled configuration of IFS-spectral and FESOM2. This configuration will allow to test the sensitivity of ECMWF’s medium-to-seasonal-range forecasts to the choice of the ocean model formulation, both in terms of computational scalability and possible added value due to locally eddy-resolving surface fields.

While in atmosphere models it is already common to define objective metrics to investigate how well an atmospheric model performs compared to observations, this is not too common for ocean models. Here we define a simple metrics encompassing the 3D structure of bias and absolute error to estimate the performance of ocean models and we apply it to the historical CMIP5 simulations from 1950 to 2005. Ocean model 3D temperature and salinity fields are compared to the PHC climatology for the major ocean basins. For each 3D grid point of the PHC dataset bias and absolute error of the model climatology are calculated and then volume- averaged over each ocean basin. An average CMIP5 model error is calculated for each ocean basin and used as a reference when investigating a particular model - similarly as has been done for the atmosphere by Reichler and Kim (2008) for CMIP3 models. Ocean surface temperature is generally reasonably well simulated by CMIP5 models and mean absolute errors amount to around 1 K which is comparable to the interannual variability. But in 500 to 1000 m - depending on the ocean basin and on the model - mean absolute errors of up to 4 K are detected which clearly exceed the interannual variability of generally below 1 K. For salinity mean absolute errors are in all levels clearly higher than the interannual variability. For example at the surface the mean absolute error amounts to up to 1 psu while the interannual variability is below 0.2 psu. Even if investigating biases which allows for cancelling out of errors within a basin instead of the mean absolute error this statement still holds in many cases. This means that there is a lot of scope for improvement of the simulation of the vertical structure of the ocean.

Ocean model biases such as the North West corner cold bias connected to the location of the Gulf Stream path, the warm bias in upwelling zones, the warm bias in the Southern Ocean, and model drift like the deep ocean warm bias which tends to peak in around 800 to 1000 m depth in the Atlantic Ocean are issues common among state-of-the-art ocean models. These issues are often amplified when the ocean model is coupled to an atmosphere model to perform climate simulations. Furthermore, unrealistic freezing of the Labrador Sea is an issue in various climate models. With the unstructured mesh approach in our Finite Element Sea ice Ocean Model (FESOM) we are able to systematically investigate the benefits of local refinement of the ocean model grid both in an uncoupled set-up (sea-ice ocean only) as well as in a fully coupled climate model (atmosphere- land-sea ice-ocean). While the horizontal ocean model resolution is 25 km on average in the finer grids, we refine the grids in some key areas to up to 5 km. Therefore we can explicitly resolve ocean eddies and simulate eddy-mean flow interactions in these key areas. The atmosphere-land component of our AWI-CM (Alfred Wegener Institute Climate Model) is ECHAM6-JSBACH developed at the Max-Planck-Institute for Meteorology in Hamburg, Germany. Here we present results of century-long uncoupled and coupled simulations on ocean model grids with different local refinements while keeping the atmosphere resolution constant in the coupled simulations. Results indicate that high horizontal resolutions in key regions such as the Gulf Stream / North Atlantic Current area or the Agulhas Stream can reduce biases such as the North West corner cold bias and the deep ocean model drift.

The recently established AWI Climate Model (AWI-CM), a coupled configuration of the Finite Element Sea Ice-Ocean Model (FESOM) with the atmospheric model ECHAM6, uses a novel multi-resolution approach: Its ocean component builds on a finite element dynamical core supporting unstructured triangular surface grids, allowing to distribute the grid points in a flexible manner. This allows to concentrate resolution in dynamically important regions, with a continuous transition zone to the coarser resolution in other areas. The model is an ideal tool to study the influence of explicit resolution of smaller scales in dedicated experiments. The unique – spatially seamless – approach might also be of benefit when it comes to temporally seamless prediction, bridging the gap between numerical weather prediction and climate models. A first benchmark set-up of AWI-CM with moderate resolution in the atmosphere (T63) and 25km in key ocean areas, e.g. around the equator, achieved a similar overall simulation performance in a long control simulation compared to well-established CMIP5 models. In particular, the (isotropically) increased equatorial resolution considerably increased the realism of TIW activity and ENSO-related variability compared to standard resolutions. The potential of AWI-CM is further exploited within the EU project PRIMAVERA in the HighResMIP of CMIP6, where we plan to contribute simulations with eddy-resolving resolutions (1/12° or 9-10 km) in key areas of the global ocean, such as the Gulf Stream-North Atlantic Current region, the Agulhas retroflection zone, or the Arctic basin. First simulations show distinct improvements with respect to the development of deep temperature and salinity biases in the North Atlantic Ocean and an overall improvement of surface biases. At even higher resolutions of 4.5 km locally in the Arctic, linear kinematic features emerge in the simulated sea ice distribution with potentially strong impacts on air-sea fluxes in the coupled system. Although the tested set-ups are computationally very demanding (with numbers of grid points comparable to a regular 0.25° grid), the throughput is high at about 8 simulated years per day because of high scalability. In addition, we are about to finish the development of a finite volume version of the ocean model code (FESOM 2). It is already faster than the original FESOM version by a factor of two to three, which will further enlarge the set of computationally feasible applications.

The recently established AWI Climate Model (AWI-CM), a coupled configuration of the Finite Element Sea Ice-Ocean Model (FESOM) with the atmospheric model ECHAM6, uses a novel multi-resolution approach: Its ocean component builds on a finite element dynamical core supporting unstructured triangular surface grids, allowing to distribute the grid points in a flexible manner. This allows to concentrate resolution in dynamically important regions, with a continuous transition zone to the coarser resolution in other areas. The model is an ideal tool to study the influence of explicit resolution of smaller scales in dedicated experiments. The unique – spatially seamless – approach might also be of benefit when it comes to temporally seamless prediction, bridging the gap between numerical weather prediction and climate models. A first benchmark set-up of AWI-CM with moderate resolution in the atmosphere (T63) and 25km in key ocean areas, e.g. around the equator, achieved a similar overall simulation performance in a long control simulation compared to well-established CMIP5 models. In particular, the (isotropically) increased equatorial resolution considerably increased the realism of TIW activity and ENSO-related variability compared to standard resolutions. The potential of AWI-CM is further exploited within the EU project PRIMAVERA in the HighResMIP of CMIP6, where we plan to contribute simulations with eddy-resolving resolutions (1/12° or 9-10 km) in key areas of the global ocean, such as the Gulf Stream-North Atlantic Current region, the Agulhas retroflection zone, or the Arctic basin. First simulations show distinct improvements with respect to the development of deep temperature and salinity biases in the North Atlantic Ocean and an overall improvement of surface biases. At even higher resolutions of 4.5 km locally in the Arctic, linear kinematic features emerge in the simulated sea ice distribution with potentially strong impacts on air-sea fluxes in the coupled system. Although the tested set-ups are computationally very demanding (with numbers of grid points comparable to a regular 0.25° grid), the throughput is high at about 8 simulated years per day because of high scalability. In addition, we are about to finish the development of a finite volume version of the ocean model code (FESOM 2). It is already faster than the original FESOM version by a factor of two to three, which will further enlarge the set of computationally feasible applications.

Climate models are used in a variety of applications: for the understanding of the interactions between different components of the climate system, for seasonal and decadal predictions, and for climate projections based on possible scenarios for future emissions. The current generation of climate models uses structured-mesh methods for the spatial discretization of both the atmosphere and the ocean. Typical biases with respect to observations may partly be connected to systematic errors arising from these traditional discretization methods. The goals of this thesis are (i) to develop a new global climate model with a multi-resolution sea ice-ocean component (FESOM) based on unstructured meshes coupled to an interactive atmospheric component (ECHAM6), (ii) a careful validation against observational data and other models, and (iii) the application of this new model to scientific questions for which the multi-resolution approach is particularly well suited. The multi-resolution approach allows to increase the spatial resolution locally in ocean regions of particular interest, e.g. at coastlines or near deep-water production sites, and to study the influence of small-scale processes on the global climate system and their interactions with the atmosphere. The first part of this thesis deals with the coupling of the existing models ECHAM6 and FESOM which was a fundamental task in the course of this dissertation. The physics of the turbulent exchange of moisture, momentum, and heat at the atmosphere-ocean interface is described in detail. Due to the different geometrical representation of the land-sea distribution in the models, the conservation of net fluxes between the models has to be guaranteed and one particular solution is given. As a next step, the mean climate state of a long control run with ECHAM6-FESOM forced with present-day (1990) greenhouse gas and aerosol concentrations is analyzed. The simulated mean climate compares favorably to observations - with typical biases known from other models at that resolution - and is even slightly better than the average over five well-established models according to objective performance indices. A similar result is found for the simulated variability, in particular atmospheric teleconnection patterns and spatio-temporal variability patterns in the ocean. An examination of strong cooling trends in global mean surface temperature in the present-day control run allows to attribute the observed "hiatus period" to natural variability of the climate system that is able to temporarily mask the externally forced warming trend. The potential of unstructured-mesh methods for global climate modeling is illustrated via two simulations with ECHAM6-FESOM that differ only in the spatial resolution in the equatorial belt. An increased resolution in the ocean leads, inter alia, to a better simulation of the narrow equatorial current systems and a reduced cold bias in the western tropical Pacific. Connected to this are improvements in the simulation of the El Nino--Southern Oscillation phenomenon. Future setups with ECHAM6-FESOM will apply strongly increased resolution in other key areas of the ocean, e.g. in the Arctic or in the Gulfstream and North Atlantic current regions. These setups will allow to study the importance of different key regions in the global climate system as well as their role in causing typical systematic errors encountered in the current generation of climate models.

The transient climate response (TCR) is 20% higher in the Alfred Wegener Institute Climate Model (AWI‐CM) compared to the Max Planck Institute Earth System Model (MPI‐ESM) whereas the equilibrium climate sensitivity (ECS) is by up to 10% higher in AWI‐CM. These results are largely independent of the two considered model resolutions for each model. The two coupled CMIP6 models share the same atmosphere‐land component ECHAM6.3 developed at the Max Planck Institute for Meteorology (MPI‐M). However, ECHAM6.3 is coupled to two different ocean models, namely the MPIOM sea ice‐ocean model developed at MPI‐M and the FESOM sea ice‐ocean model developed at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI). A reason for the different TCR is related to ocean heat uptake in response to greenhouse gas forcing. Specifically, AWI‐CM simulations show stronger surface heating than MPI‐ESM simulations while the latter accumulate more heat in the deeper ocean. The vertically integrated ocean heat content is increasing slower in AWI‐CM model configurations compared to MPI‐ESM model configurations in the high latitudes. Weaker vertical mixing in AWI‐CM model configurations compared to MPI‐ESM model configurations seems to be key for these differences. The strongest difference in vertical ocean mixing occurs inside the Weddell and Ross Gyres and the northern North Atlantic. Over the North Atlantic, these differences materialize in a lack of a warming hole in AWI‐CM model configurations and the presence of a warming hole in MPI‐ESM model configurations. All these differences occur largely independent of the considered model resolutions., Plain Language Summary: The transient climate response (TCR) describes how strongly near‐surface temperatures warm in response to gradually increasing greenhouse‐gas levels. Here we investigate the role of the ocean which takes up heat and thereby delays the surface warming. Two models of the Coupled Model Intercomparison Project Phase 6 (CMIP6), the Alfred Wegener Institute Climate Model (AWI‐CM) and the Max Planck Institute Earth System Model (MPI‐ESM), which use the same atmosphere model but different ocean models are selected for this study. In AWI‐CM the upper ocean layers heat faster than in MPI‐ESM, while the opposite is true for the deep ocean. As a consequence, the TCR is 20% stronger in AWI‐CM compared to MPI‐ESM. We find that weaker vertical ocean mixing in AWI‐CM compared to MPI‐ESM, especially over the northern North Atlantic and the Weddell and Ross Gyres, is key for these differences. Our findings corroborate the importance of realistic ocean mixing in climate models when it comes to getting the strength and timing of climate change right., Key Points: The transient climate response in two coupled models with the same atmosphere but different ocean components differs by 20%. The upper (deeper) ocean heats faster (slower) in AWI‐CM compared to MPI‐ESM, independent of model resolution. Vertical mixing in the northern North Atlantic and the Weddell and Ross Gyres appears to be key for these differences., Bundesministerium für Bildung und Forschung (BMBF) http://dx.doi.org/10.13039/501100002347, German Climate Computing Centre (DKRZ), Federal Ministry of Education and Research of Germany, Helmholtz Association http://dx.doi.org/10.13039/501100009318, https://esgf-data.dkrz.de/projects/cmip6-dkrz/