Super Residual Circulation : A New Perspective on Ocean Vertical Heat Transport

Ocean circulation and mixing regulate Earth's climate by moving heat vertically within the ocean. We present a new formalism to diagnose the role of ocean circulation and diabatic processes in setting vertical heat transport in ocean models. In this formalism we use temperature tendencies, rather than explicit vertical velocities, to diagnose circulation. Using quasi-steady-state simulations from the Australian Community Climate and Earth-System Simulator Ocean Model (ACCESS-OM2), we diagnose a diathermal overturning circulation in temperature-depth space. Furthermore, projection of tendencies due to diabatic processes onto this coordinate permits us to represent these as apparent overturning circulations. Our framework permits us to extend the concept of "Super Residual Transport,'' which combines mean and eddy advection terms with subgridscale isopycnal mixing due to mesoscale eddies but excludes small-scale threedimensional turbulent mixing effect, to construct a new overturning circulation-the "Super Residual Circulation'' (SRC). We find that in the coarse-resolution version of ACCESS-OM2 (nominally 1 degrees horizontal resolution) the SRC is dominated by an similar to 11-Sv (1 Sv [10(6) m(3) s(-1)) circulation that transports heat upward. The SRC's upward heat transport is;2 times as large in a finer-horizontal-resolution (0.1 degrees) version of ACCESS, suggesting that a differing balance of super-residual and parameterized small-scale processes may emerge as eddies are resolved. Our analysis adds new insight into superresidual processes, because the SRC elucidates the pathways in temperature and depth space along which water mass transformation occurs.Peer reviewe

Subpolar Southern Ocean response to changes in the surface momentum, heat, and freshwater fluxes under 2xCO2

The Antarctic subpolar Southern Ocean (sSO) has fundamental climate importance. Antarctic Bottom Water (AABW) originates in the sSO and supplies the lower limb of the meridional overturning circulation (MOC), occupying 36% of ocean volume. Climate models struggle to represent continental shelf processes that form AABW. We explore sources of persistent model biases by examining response of the sSO to perturbations in surface forcing in a global ocean–sea ice model (ACCESS-OM2) that forms AABW both on shelf and in open ocean. The sSO response to individual and combined perturbations of surface heat, freshwater, and momentum fluxes follows the WCRP CMIP6 FAFMIP-protocol. Wind perturbation (i.e., a poleward shift and intensification of the westerlies) is dominant, enhancing AABW formation and accelerating the global MOC. This occurs through upwelling of warm waters and inhibition of sea ice growth during winter, which triggers large open water polynya (OWP) events with associated deep convection. These events occur in the Weddell and Ross Seas and their variability is associated with availability of heat at midocean depths. These OWPs cease when the heat reservoir is depleted. Effects of surface warming and freshening only partially compensate changes from increasing winds on ocean stratification and depletion of AABW formation. These results indicate that overly convective models, such ACCESS-OM2, can respond to CO2-perturbed scenarios by forming too much AABW in OWP, which might not hold in models without OWPs. This might contribute to the large intermodel spread thermosteric sea level projections, being relevant to the interpretation of future projections by current climate models.Peer reviewe

Challenges and Prospects in Ocean Circulation Models

We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations

What causes the spread of model projections of ocean dynamic sea-level change in response to greenhouse gas forcing?

Sea levels of different atmosphere-ocean general circulation models (AOGCMs) respond to climate change forcing in different ways, representing a crucial uncertainty in climate change research. We isolate the role of the ocean dynamics in setting the spatial pattern of dynamic sea-level (zeta) change by forcing several AOGCMs with prescribed identical heat, momentum (wind) and freshwater flux perturbations. This method produces a zeta projection spread comparable in magnitude to the spread that results from greenhouse gas forcing, indicating that the differences in ocean model formulation are the cause, rather than diversity in surface flux change. The heat flux change drives most of the global pattern of zeta change, while the momentum and water flux changes cause locally confined features. North Atlantic heat uptake causes large temperature and salinity driven density changes, altering local ocean transport and zeta. The spread between AOGCMs here is caused largely by differences in their regional transport adjustment, which redistributes heat that was already in the ocean prior to perturbation. The geographic details of the zeta change in the North Atlantic are diverse across models, but the underlying dynamic change is similar. In contrast, the heat absorbed by the Southern Ocean does not strongly alter the vertically coherent circulation. The Arctic zeta change is dissimilar across models, owing to differences in passive heat uptake and circulation change. Only the Arctic is strongly affected by nonlinear interactions between the three air-sea flux changes, and these are model specific.Peer reviewe

Challenges and Prospects in Ocean Circulation Models

We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.Peer reviewe

Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning

In this paper, we present the current state-of-the-art of decision making (DM) and machine learning (ML) and bridge the two research domains to create an integrated approach of complex problem solving based on human and computational agents. We present a novel classification of ML, emphasizing the human-in-the-loop in interactive ML (iML) and more specific on collaborative interactive ML (ciML), which we understand as a deep integrated version of iML, where humans and algorithms work hand in hand to solve complex problems. Both humans and computers have specific strengths and weaknesses and integrating humans into machine learning processes might be a very efficient way for tackling problems. This approach bears immense research potential for various domains, e.g., in health informatics or in industrial applications. We outline open questions and name future challenges that have to be addressed by the research community to enable the use of collaborative interactive machine learning for problem solving in a large scale

ACCESS-OM2 v1.0: a global ocean-sea ice model at three resolutions

We introduce ACCESS-OM2, a new version of the ocean–sea ice model of the Australian Community Climate and Earth System Simulator. ACCESS-OM2 is driven by a prescribed atmosphere (JRA55-do) but has been designed to form the ocean–sea ice component of the fully coupled (atmosphere–land–ocean–sea ice) ACCESS-CM2 model. Importantly, the model is available at three different horizontal resolutions: a coarse resolution (nominally 1∘ horizontal grid spacing), an eddy-permitting resolution (nominally 0.25∘), and an eddy-rich resolution (0.1∘ with 75 vertical levels); the eddy-rich model is designed to be incorporated into the Bluelink operational ocean prediction and reanalysis system. The different resolutions have been developed simultaneously, both to allow for testing at lower resolutions and to permit comparison across resolutions. In this paper, the model is introduced and the individual components are documented. The model performance is evaluated across the three different resolutions, highlighting the relative advantages and disadvantages of running ocean–sea ice models at higher resolution. We find that higher resolution is an advantage in resolving flow through small straits, the structure of western boundary currents, and the abyssal overturning cell but that there is scope for improvements in sub-grid-scale parameterizations at the highest resolution

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

Human and Machine Learning

In this paper, we consider learning by human beings and machines in the light of Herbert Simon’s pioneering contributions to the theory of Human Problem Solving. Using board games of perfect information as a paradigm, we explore differences in human and machine learning in complex strategic environments. In doing so, we contrast theories of learning in classical game theory with computational game theory proposed by Simon. Among theories that invoke computation, we make a further distinction between computable and computational or machine learning theories. We argue that the modern machine learning algorithms, although impressive in terms of their performance, do not necessarily shed enough light on human learning. Instead, they seem to take us further away from Simon’s lifelong quest to understand the mechanics of actual human behaviour