Storms drive outgassing of CO2 in the subpolar Southern Ocean

The subpolar Southern Ocean is a critical region where CO2 outgassing influences the global mean air-sea CO2 flux (FCO2). However, the processes controlling the outgassing remain elusive. We show, using a multi-glider dataset combining FCO2 and ocean turbulence, that the air-sea gradient of CO2 (∆pCO2) is modulated by synoptic storm-driven ocean variability (20 µatm, 1–10 days) through two processes. Ekman transport explains 60% of the variability, and entrainment drives strong episodic CO2 outgassing events of 2–4 mol m−2 yr−1. Extrapolation across the subpolar Southern Ocean using a process model shows how ocean fronts spatially modulate synoptic variability in ∆pCO2 (6 µatm2 average) and how spatial variations in stratification influence synoptic entrainment of deeper carbon into the mixed layer (3.5 mol m−2 yr−1 average). These results not only constrain aliased-driven uncertainties in FCO2 but also the effects of synoptic variability on slower seasonal or longer ocean physics-carbon dynamics.

Atlantic Ocean Variability and European Alps Winter Precipitation

Winter precipitation (snowpack) in the European Alps provides a critical source of freshwater to major river basins such as the Danube, Rhine, and Po. Previous research identified Atlantic Ocean variability and hydrologic responses in the European Alps. The research presented here evaluates Atlantic Sea Surface Temperatures (SSTs) and European Alps winter precipitation variability using Singular Value Decomposition. Regions in the north and mid-Atlantic from the SSTs were identified as being tele-connected with winter precipitation in the European Alps. Indices were generated for these Atlantic SST regions to use in prediction of precipitation. Regression and non-parametric models were developed using the indices as predictors and winter precipitation as the predictand for twenty-one alpine precipitation stations in Austria, Germany, and Italy. The proposed framework identified three regions in the European Alps in which model skill ranged from excellent (West Region–Po River Basin), to good (East Region) to poor (Central Region). A novel approach for forecasting future winter precipitation utilizing future projections of Atlantic SSTs predicts increased winter precipitation until ~2040, followed by decreased winter precipitation until ~2070, and then followed by increasing winter precipitation until ~2100.

On the Importance of High-Resolution in Large-Scale Ocean Models

Eddying global ocean models are now routinely used for ocean prediction, and the value-added of a better representation of the observed ocean variability and western boundary currents at that resolution is currently being evaluated in climate models. This overview article begins with a brief summary of the impact on ocean model biases of resolving eddies in several global ocean-sea ice numerical simulations. Then, a series of North and Equatorial Atlantic configurations are used to show that an increase of the horizontal resolution from eddy-resolving to submesoscale-enabled together with the inclusion of high-resolution bathymetry and tides significantly improve the models’ abilities to represent the observed ocean variability and western boundary currents. However, the computational cost of these simulations is extremely large, and for these simulations to become routine, close collaborations with computer scientists are essential to ensure that numerical codes can take full advantage of the latest computing architecture.

The Impact of the Mesoscale Ocean Variability on the Estimation of Tidal Harmonic Constants Based on Satellite Altimeter Data in the South China Sea

The estimation accuracy of tidal harmonic constants is of great significance to maritime traffic and port construction. However, due to the long sampling period of satellite altimeters, tidal signals alias the mesoscale ocean frequencies. As a result, the harmonic analysis is affected by mesoscale environmental noise. In this study, the influence of the mesoscale ocean variability (MOV) on the estimation of tidal harmonic constants was quantified by analyzing 25 years of altimeter data from the Topex/Poseidon (T/P) and Jason satellites in the South China Sea (SCS). The results indicated that the absolute amplitude differences (AADs) of the eight major tidal constituents before and after the mesoscale variability correction (MVC) were generally within 10 mm, and most were within 6 mm. For the relative impact, M2, O1, and K1 were not obviously affected by the MOV because of their large amplitudes, and the AADs generally accounted for less than ±10% of the amplitudes. As a tidal constituent with amplitude less than 2 cm in the SCS, the amplitude of K2 was significantly affected by the MOV, with the ratios of the AADs to its own amplitudes ranging from −64.79% to 95.99% in space. In terms of phase, the K2 tide was most affected by the MOV: 63% of the data points before and after correction were over ±5°, and the maximum and minimum values were 86.46° and −176.27°, respectively. The absolute phase differences of other tidal constituents before and after the MVC were generally concentrated within ±5°. The impact of the MOV on the evolution of tidal amplitudes in the SCS was also explored. It was found that the MOV can cause pseudo-rapid temporal variations of tidal amplitudes in some regions of the SCS.

Imprint of chaotic ocean variability on transports in the southwestern Pacific at interannual timescales

The southwestern Pacific Ocean sits at a bifurcation where southern subtropical waters are redistributed equatorward and poleward by different ocean currents. The processes governing the interannual variability of these currents are not completely understood. This issue is investigated using a probabilistic modeling strategy that allows disentangling the atmospherically forced deterministic ocean variability and the chaotic intrinsic ocean variability. A large ensemble of 50 simulations performed with the same ocean general circulation model (OGCM) driven by the same realistic atmospheric forcing and only differing by a small initial perturbation is analyzed over 1980–2015. Our results show that, in the southwestern Pacific, the interannual variability of the transports is strongly dominated by chaotic ocean variability south of 20∘ S. In the tropics, while the interannual variability of transports and eddy kinetic energy modulation are largely deterministic and explained by the El Niño–Southern Oscillation (ENSO), ocean nonlinear processes still explain 10 % to 20 % of their interannual variance at large scale. Regions of strong chaotic variance generally coincide with regions of high mesoscale activity, suggesting that a spontaneous inverse cascade is at work from the mesoscale toward lower frequencies and larger scales. The spatiotemporal features of the low-frequency oceanic chaotic variability are complex but spatially coherent within certain regions. In the Subtropical Countercurrent area, they appear as interannually varying, zonally elongated alternating current structures, while in the EAC (East Australian Current) region, they are eddy-shaped. Given this strong imprint of large-scale chaotic oceanic fluctuations, our results question the attribution of interannual variability to the atmospheric forcing in the region from pointwise observations and one-member simulations.

Understanding intrinsic ocean variability by suppressing regional stochastic variability

<p>Intrinsic ocean variability is essential for climate prediction because it is less sensitive to stochastic process, but it is very difficult to be identified due to internal climate variability. Here we use regional interactive ensemble applied on ocean-atmosphere interface (RIE-OA) to suppress atmosphere stochastic variability and to reveal intrinsic variability as well as to understand climate dynamic across multiple timescales. Five atmosphere general circulation models (AGCM) are coupled to an ocean general circulation model (OGCM) over the North Atlantic basin (20<sup>o</sup>N to Denmark Strait and Greenland-Scotland ridge). The OGCM interacts with fluxes from a selected AGCM globally except over the North Atlantic basin where the OGCM interacts with the ensemble averaged fluxes from the five AGCMs. The five AGCMs, on the other hand, feel the same ocean states. Hence, the atmosphere stochastic variability impacting the ocean is one-fifth weaker than stand-alone configuration (control case). This leads to reduction of the local climate variability, such as Atlantic Multidecadal Variability, but should not reduce intrinsic variability. Comparing control cases and RIE-OA case, we found the intrinsic ocean variability, a narrow-banded low-frequency (about 8 to 20 years) signal over the North Atlantic Subtropical Gyre, is not influenced by the weakened stochastic variability. More details will be discussed.</p>

Imprint of intrinsic ocean variability on ocean heat content and thermosteric sea level over 2005-2015

<p>Ocean warming accounts for more than 90% of the net Earth energy imbalance. As oceans warm, sea level is rising due to the expansion of seawater. Therefore, estimating ocean heat content (OHC) and thermosteric sea level (TSL) appears of great importance to assess the impact of the on-going global warming.  Different research groups have estimated such climate variables for years now and even routinely (Boyer et al., 2016). These climate variables are derived from in situ temperature measurement at different depths with uneven spatial coverage. Two main sources of uncertainties are attributed to the evolving technology of temperature probes and to the uneven spatio-temporal distribution of in situ measurements (Boyer et al., 2016). A large ensemble of forced eddy-permitting ocean simulations revealed the existence of another uncertainty of regional OHC trend estimates (Sérazin et al 2017): a substantial intrinsic variability emerging from oceanic nonlinearities generates random multi decadal trends, which can mask its atmospherically-forced counterpart. This intrinsic variability can also leave a large imprint on regional sea level trends over the altimetry period (Llovel et al., 2018; Penduff et al., 2019). Less attention has been paid for estimating the imprint of such intrinsic ocean variability in OHC and TSL change associated with the uneven spatial coverage of in situ records. In this study, we investigate the imprint of ocean intrinsic variability and of the uneven distribution of in situ records on OHC and TLS change, by taking advantage of this large ensemble simulation. To do so, we extract synthetic in situ temperature profiles from the simulations in space, time and depth. We then interpolate these synthetic profiles using ISAS (Gaillard et al. 2016) to estimate both the imprint of intrinsic ocean variability and the uneven distribution of in situ data to OHC change and TSL change from 2005 to 2015.</p>

Characterisation of the chaotic variability of the regional sea level and its components over 1993-2015 at interannual time scales

<p>Satellite altimetry data have revealed a global mean sea level rise of 3.1 mm/yr since 1993 with large regional sea level trend variability. These remote data highlight complex structures especially in strongly eddying regions. A recent study showed that over 38% of the global ocean area, the chaotic variability that spontaneously emerges from the ocean may hinder the attribution to the atmospheric forcing of regional sea level trends from 1993 to 2015. This study aims at complementing this work by first focusing on the atmospherically-forced and chaotic contributions of regional sea level interannual variability and its components (steric and manometric sea level interannual variability). A global ¼° ocean/sea-ice 50-member ensemble simulation is considered to disentangle the imprints of the atmospheric forcing and of the chaotic ocean variability over 1993-2015. The atmospherically-forced and chaotic interannual variabilities of sea level mainly have a steric origin , except in coastal areas. The chaotic part of the interannual variability of sea level and its components is stronger in the Pacific and Atlantic oceans than in the Indian ocean. The chaotic part of the interannual variability of sea level and of its steric component exceeds 20% over 48% of the global ocean area; this fractional area reduces to 26% for the manometric component. As the chaotic part of the regional sea level interannual variability has a substantial imprint, this study then interested in quantifying the periods when it becomes dominant over the atmospherically-forced contribution. This is assessed using spectral analysis on the ensemble simulation in the frequency domain for the sea level and its steric and manometric components over the global ocean as well as in some basins of interest. This enables us to better characterise and quantify the chaotic ocean variability contribution to regional sea level changes and its components.</p>