Tipping points in overturning circulation mediated by ocean mixing and the configuration and magnitude of the hydrological cycle: A simple model

The current configuration of the ocean overturning involves upwelling predominantly in the Southern Ocean and sinking predominantly in the Atlantic basin. The reasons for this remain unclear, as both models and paleoclimatic observations suggest that sinking can sometimes occur in the Pacific. We present a six-box model of the overturning in which temperature, salinity and low-latitude pycnocline depths are allowed to vary prognostically in both the Atlantic and Pacific. The overturning is driven by temperature, winds, and mixing and modulated by the hydrological cycle. In each basin there are three possible flow regimes, depending on whether low-latitude water flowing into northern surface boxes is transformed into dense deep water, somewhat lighter intermediate water, or light water that is returned at the surface. The resulting model combines insights from a number of previous studies and allows for nine possible global flow regimes. For the modern ocean, we find that although the interbasin atmospheric freshwater flux suppresses Pacific sinking, the equator-to-pole flux enhances it. When atmospheric temperatures are held fixed, seven possible flow regimes can be accessed by changing the amplitude and configuration of the modern hydrological cycle . North Pacific overturning can strengthen with either increases or decreases in the hydrological cycle, as well as under reversal of the interbasin freshwater flux. Tipping-point behavior of both transient and equilibrium states is modulated by parameters such as the poorly constrained lateral diffusive mixing. If hydrological cycle amplitude is varied consistently with global temperature, northern polar amplification is necessary for the Atlantic overturning to collapseComment: 38 pages, 10 figures, Submitted to Journal of Physical Oceanograph

Using Artificial Intelligence to aid Scientific Discovery of Climate Tipping Points

We propose a hybrid Artificial Intelligence (AI) climate modeling approach that enables climate modelers in scientific discovery using a climate-targeted simulation methodology based on a novel combination of deep neural networks and mathematical methods for modeling dynamical systems. The simulations are grounded by a neuro-symbolic language that both enables question answering of what is learned by the AI methods and provides a means of explainability. We describe how this methodology can be applied to the discovery of climate tipping points and, in particular, the collapse of the Atlantic Meridional Overturning Circulation (AMOC). We show how this methodology is able to predict AMOC collapse with a high degree of accuracy using a surrogate climate model for ocean interaction. We also show preliminary results of neuro-symbolic method performance when translating between natural language questions and symbolically learned representations. Our AI methodology shows promising early results, potentially enabling faster climate tipping point related research that would otherwise be computationally infeasible.Comment: This is the preprint of work presented at the 2022 AAAI Fall Symposium Series, Third Symposium on Knowledge-Guided ML, November 202

Spatial heterogeneity of wind forcing: application to artificial reef functioning influenced by the circulation in the Bay of Marseilles, France.

, DOI = 10.1016/j.crvi.2006.04.002International audienceIn the frame of the largest French project of artificial production reefs, initiated by the city of Marseilles in 2001, the present study aimed at describing the hydrodynamic pattern of the coastal area considered, by the use of a 3D numerical modelling. Results were local wind statistics, bottom current fields and drifting particle maps. The knowledge of the hydrodynamic connexions between particle (such as larvae) sources or targeted areas linked to the reefs, allows us to explain the success or failure of the reefs' colonizing. Moreover, the study confirms the wind spatial variability and demonstrates the error resulting from the use of an average but locally absent wind direction

Spatial Heterogeneity of Artificial Reefs Functioning according to Wind-Induced Lagrangian Circulation.

International audienceIn the scope of the program "Récifs Prado" for artificial reef immersion in the Bay of Marseilles (southern France), we adapted the fine resolution (100 m) of the 3D numerical model POM (Princeton Ocean Model) to compute the typical patterns of the wind induced circulation within the bay. In addition, we derived from those results the lagrangian trajectories of planktonic particles drifting over periods of 3 days, both from natural habitats to colonize the reefs, and inversely from the reefs to enrich peripheral ecosystems. Results emphasized the high spatial heterogeneity of the reefs functioning at short scales. First, reefs were submitted to a general southward particle flux, being colonized from the northern bay and then impacting the southern bay 50% and 40% of the time, respectively. Second, adjacent reefs frequently showed contrasted impacts, with fluxes simultaneously oriented offshore or inshore, in opposite directions. Third, at the top of reefs particles were released both southward and northward 32% and 8.6% of the time, respectively, when at the bottom of reefs particles were only released southward 40% of the time

Isopycnal mixing by mesoscale eddies significantly impacts oceanic anthropogenic carbon uptake

Anthropogenic carbon dioxide uptake varies across Earth System Models for reasons that have remained obscure. When varied within a single model, the lateral eddy mixing coefficient ARedi produces a range of uptake similar to the modeled range. The highest uptake, resulting from a simulation with a constant ARedi of 2400 m2/s, simulates 15% more historical carbon uptake than a model with ARedi = 400 m2/s. A sudden doubling in carbon dioxide produces a 21% range in carbon uptake across the models. Two spatially dependent representations of ARedi produce uptake that lies in the middle of the range of constant values despite predicting very large values in the subtropical gyres. One-dimensional diffusive models of the type used for integrated assessments can be fit to the simulations, with ARedi accounting for a substantial fraction of the effective vertical diffusion. Such models, however, mask significant regional changes in stratification and biological carbon storage

Transient response of the Southern Ocean to changing ozone:Regional responses and physical mechanisms

The impact of changing ozone on the climate of the Southern Ocean is evaluated using an ensemble of coupled climate model simulations. By imposing a step change from 1860 to 2000 conditions, response functions associated with this change are estimated. The physical processes that drive this response are different across time periods and locations, as is the sign of the response itself. Initial cooling in the Pacific sector is driven not only by the increased winds pushing cold water northward, but also by the southward shift of storms associated with the jet stream. This shift drives both an increase in cloudiness (resulting in less absorption of solar radiation) and an increase in net freshwater flux to the ocean (resulting in a decrease in surface salinity that cuts off mixing of warm water from below). A subsurface increase in temperature associated with this reduction in mixing then upwells along the Antarctic coast, producing a subsequent warming. Similar changes in convective activity occur in the Weddell Sea but are offset in time. Changes in sea ice concentration also play a role in modulating solar heating of the ocean near the continent. The time scale for the initial cooling is much longer than that seen in NCAR CCSM3.5, possibly reflecting differences in natural convective variability between that model (which has essentially no Southern Ocean deep convection) and the one used here (which has a large and possibly unrealistically regular mode of convection) or to differences in cloud feedbacks or in the location of the anomalous winds. </jats:p

Bottom Topography Mapping via Nonlinear Data Assimilation

A variational data assimilation method is described for bottom topography mapping in rivers and estuaries using remotely sensed observations of water surface currents. The velocity field and bottom topography are related by the vertically integrated momentum and continuity equations, leading to a nonlinear inverse problem for bottom topography, which is solved using a Picard iteration strategy combined with a nonlinear line search. An illustration of the method is shown for Haverstraw Bay, in the Hudson River, where the known bottom topography is well reconstructed. Once the topography has been estimated, currents and water levels may be forecast. The method makes feasible 1) the estimation of bottom topography in regions where in situ data collection may be impossible, dangerous, or expensive, and 2) the calibration of barotropic shallow-water models via control of the bottom topography