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Accurate forecasts of the ocean state and the estimation of forecast uncertainties are crucial when it comes to providing skilful seasonal predictions. In this study we analyse the predictive skill and reliability of the ocean component in a seasonal forecasting system. Furthermore, we assess the effects of accounting for model and observational uncertainties. Ensemble forcasts are carried out with an updated version of the ECMWF seasonal forecasting model System 4, with a forecast length of ten months, initialized every May between 1981 and 2010. We find that, for essential quantities such as sea surface temperature and upper ocean 300 m heat content, the ocean forecasts are generally underdispersive and skilful beyond the first month mainly in the Tropics and parts of the North Atlantic. The reference reanalysis used for the forecast evaluation considerably affects diagnostics of forecast skill and reliability, throughout the entire ten-month forecasts but mostly during the first three months. Accounting for parametrization uncertainty by implementing stochastic parametrization perturbations has a positive impact on both reliability (from month 3 onwards) as well as forecast skill (from month 8 onwards). Skill improvements extend also to atmospheric variables such as 2 m temperature, mostly in the extratropical Pacific but also over the midlatitudes of the Americas. Hence, while model uncertainty impacts the skill of seasonal forecasts, observational uncertainty impacts our assessment of that skill. Future ocean model development should therefore aim not only to reduce model errors but to simultaneously assess and estimate uncertainties.

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.

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)

International audience; The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and future climate to model resolution and stochastic parameterisation. The EC-Earth Earth system model is used to explore the impact of stochastic physics in a large ensemble of 30-year climate integrations at five different atmospheric horizontal resolutions (from 125 up to 16 km). The project includes more than 120 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), together with coupled transient runs (1850-2100). A total of 20.4 million core hours have been used, made available from a single year grant from PRACE (the Partnership for Advanced Computing in Europe), and close to 1.5 PB of output data have been produced on SuperMUC IBM Petascale System at the Leibniz Supercomputing Centre (LRZ) in Garching, Germany. About 140 TB of post-processed data are stored on the CINECA supercomputing centre archives and are freely accessible to the community thanks to an EUDAT data pilot project. This paper presents the technical and scientific set-up of the experiments, including the details on the forcing used for the simulations performed, defining the SPHINX v1.0 protocol. In addition, an overview of preliminary results is given. An improvement in the simulation of Euro-Atlantic atmospheric blocking following resolution increase is observed. It is also shown that including stochastic parameterisation in the low-resolution runs helps to improve some aspects of the tropical climate - specifically the Madden-Julian Oscillation and the tropical rainfall variability. These findings show the importance of representing the impact of small-scale processes on the large-scale climate variability either explicitly (with high-resolution simulations) or stochastically (in low-resolution simulations).

This dissertation deals with the representation of uncertainties in sea ice modelling, especially within the sea ice dynamics. An important term of the momentum balance for computing the evolution of sea ice drift is the viscous-plastic sea ice rheology. It describes the deformation of sea ice under convergent drift. In this context, an ice strength parameter determines the internal ice strength, which counteracts plastic deformation and hence piling up of sea ice. Uncertainties in the choice of the parameter are simulated in this study by application of symmetric perturbation schemes. Temporal as well as spatial correlations are included in the generation of continuously applied stochastic perturbations. The parameter perturbations are implemented in an ocean-sea ice and in a coupled atmosphere-ocean-sea ice model. Results show that including these uncertainty estimates leads to a change in the mean sea ice distribution, especially in the Arctic. A randomly reduced ice strength parameter results in a relative acceleration of sea ice drift under convergence, which cannot be reverted by a randomly increased ice strength in the subsequent course of the simulation. This is caused by the highly nonlinear formulation of the sea ice rheology and results in a general acceleration of sea ice owing to the symmetric perturbations. As a result, the amount of thick, ridged sea ice in regions of predominantly convergent drift is increased. In the Arctic this increase accumulates slowly, but continuously over decades. Antarctic sea ice on the other hand exhibits relatively small changes in the mean sea ice distribution. In the coupled atmosphere-ocean-sea ice model ice strength perturbations lead to increased drift as well, although the impact on the sea ice thickness distribution is reduced. The reason are coupled feedback mechanisms, which counteract a general thickness increase. Finally, ensemble simulations are conducted with the coupled model in the context of sea ice predictions. Comparing ensembles with parameter perturbations and ensembles with atmospheric initial condition perturbations shows that the inclusion of model uncertainty leads to increased ensemble spread for the sea ice distribution of the central Arctic during the first weeks of the simulation. This has important implications for uncertainty estimations in data assimilation and forecasts for the polar regions.

Icebergs are commonly ignored in current general circulation models despite their connections to ocean stratification, phytoplankton growth and redistribution of freshwater in the Southern Ocean. On the way to fully including icebergs in ocean circulation models, we present FESOM-IB, the high resolution Finite Element Sea Ice - Ocean Model (FESOM) enhanced by an IceBerg drift and decay module developed at AWI Bremerhaven. By solving the momentum equations for iceberg drift, the iceberg trajectory is computed from an evaluation of the FESOM ice/ocean velocity fields and sea surface height at every time step. Icebergs are assumed to be cubical-shaped and treated as Lagrangian point masses having properties such as length, width and height. Simple diagnostic equations for computing the melt rates of icebergs are applied and iceberg dimensions are adjusted accordingly. Therefore the numerical method's stability for the solution of the momentum equations has to be independent from iceberg size. Our numerical procedure proved to be stable across the full range of iceberg classes; small to giant icebergs may be modelled. We present a 3-year simulation of 308 artifical icebergs from 4 different size classes started at 77 circum-Antarctic locations. Melt rates as well as the components of iceberg momentum balance are quantified and the influence of iceberg size on the drift patterns is discussed. In our simulation giant icebergs tend to stay close to the Antarctic coast. They drift westwards in the coastal current and may only leave it at well-defined bifurcation points in the Weddell Sea, the Ross Sea and over the Kerguelen Plateau. In contrast, smaller icebergs show an off-shore drift component early in their lives. Independent of the iceberg size, the dominant iceberg velocity component is changed into eastward as soon as icebergs reach the ACC.

In this study we demonstrate the potential of a kinetic energy backscatter scheme for use in global ocean simulations. Ocean models commonly employ (bi)harmonic eddy viscosities causing excessive dissipation of kinetic energy in eddy-permitting simulations. Overdissipation not only affects the smallest resolved scales but also the generation of eddies through baroclinic instabilities, impacting the entire wave number spectrum. The backscatter scheme returns part of this overdissipated energy back into the resolved flow. We employ backscatter in the FESOM2 multiresolution ocean model with a quasi-uniform 1/4° mesh. In multidecadal ocean simulations, backscatter increases eddy activity by a factor 2 or more, moving the simulation closer to observational estimates of sea surface height variability. Moreover, mean sea surface height, temperature, and salinity biases are reduced. This amounts to a globally averaged bias reduction of around 10% for each field, which is even larger in the Antarctic Circumpolar Current. However, in some regions such as the coastal Kuroshio, backscatter leads to a slight overenergizing of the flow and, in the Antarctic, to an unrealistic reduction of sea ice. Some of the bias increases can be reduced by a retuning of the model, and we suggest related adjustments to the backscatter scheme. The backscatter simulation is about 2.5 times as expensive as a simulation without backscatter. Most of the increased cost is due to a halving of the time step to accommodate higher simulated velocities.