Vertical flow in the Southern Ocean estimated from individual moorings

In this study, we demonstrate that oceanic vertical velocities can be estimated from individual mooring measurements, even for non-stationary flow. This result is obtained under three assumptions: i. weak diffusion (Péclet number ≫1), ii. weak friction (Reynolds number ≫1), and iii. small inertial terms (Rossby number ≪1). The theoretical framework is applied to a set of 4 moorings located in the Southern Ocean. For this site, the diagnosed vertical velocities are highly variable in time, their standard deviation being one-to-two orders of magnitude greater than their mean. We demonstrate that the time-averaged vertical velocities are largely induced by geostrophic flow, and can be estimated from the time-averaged density and horizontal velocities. This suggests that local time-mean vertical velocities are primarily forced by the time-mean ocean dynamics, rather than by e.g. transient eddies or internal waves. We also show that, in the context of these four moorings, the time-mean vertical flow is consistent with stratified Taylor column dynamics in the presence of a topographic obstacle

The rogue nature of hiatuses in a global warming climate

The nature of rogue events is their unlikelihood and the recent unpredicted decade-long slowdown in surface warming, the so-called hiatus, may be such an event. However, given decadal variability in climate, global surface temperatures were never expected to increase monotonically with increasing radiative forcing. Here surface air temperature from 20 climate models is analyzed to estimate the historical and future likelihood of hiatuses and “surges” (faster than expected warming), showing that the global hiatus of the early 21st century was extremely unlikely. A novel analysis of future climate scenarios suggests that hiatuses will almost vanish and surges will strongly intensify by 2100 under a “business as usual” scenario. For “CO2 stabilisation” scenarios, hiatus, and surge characteristics revert to typical 1940s values. These results suggest to study the hiatus of the early 21st century and future reoccurrences as rogue events, at the limit of the variability of current climate modelling capability

Detectability of an AMOC decline in current and projected climate changes

Determining whether the Atlantic Meridional Overturning Circulation (AMOC)'s transport is in decline is challenging due to the short duration of continuous observations. To estimate how many years are needed to detect a decline, we conduct a simulation study using synthetic data that mimics an AMOC time series. The time series' characteristics are reproduced using the trend, variance, and autocorrelation coefficient of the AMOC strength at 26.5°N from 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) models under the RCP8.5 future scenario, and from RAPID observations (2004–2018). Our results suggest that the 14‐year RAPID length has just entered the lower limits of the trend's “detection window” based on synthetic data generated using CMIP5 trends and variability (14–42 years; median urn:x-wiley:grl:media:grl61393:grl61393-math-0001 24 years), but twice the length is required for detectability based on RAPID variability (29–67 years; median urn:x-wiley:grl:media:grl61393:grl61393-math-0002 43 years). The annual RAPID trend is currently not statistically significant (−0.11 Sv yr−1, p > 0.05)

Insights into decadal North Atlantic sea surface temperature and ocean heat content variability from an eddy-permitting coupled climate model

An ocean mixed layer heat budget methodology is used to investigate the physical processes determining subpolar North Atlantic (SPNA) sea surface temperature (SST) and ocean heat content (OHC) variability on decadal-multidecadal timescales using the state-of-the-art climate model HadGEM3-GC2. New elements include development of an equation for evolution of anomalous SST for interannual and longer timescales in a form analogous to that for OHC, parameterization of the diffusive heat flux at the base of the mixed layer and analysis of a composite AMOC event. Contributions to OHC and SST variability from two sources are evaluated i) net ocean-atmosphere heat flux and ii) all other processes, including advection, diffusion and entrainment for SST. Anomalies in OHC tendency propagate anticlockwise around the SPNA on multidecadal timescales with a clear relationship to the phase of the Atlantic meridional overturning circulation (AMOC). AMOC anomalies lead SST tendencies which in turn lead OHC tendencies in both the eastern and western SPNA. OHC and SST variations in the SPNA on decadal timescales are dominated by AMOC variability because it controls variability of advection which is shown to be the dominant term in the OHC budget. Lags between OHC and SST is traced to differences between the advection term for OHC and the advection-entrainment term for SST. The new results have implications for interpretation of variations in Atlantic heat uptake in the CMIP6 climate model assessment

Variational methods

International audienceThis contribution presents derivative-based methods for local sensitivity analysis, called Variational Sensitivity Analysis (VSA). If one defines an output called the response function, its sensitivity to inputs variations around a nominal value can be studied using derivative (gradient) information. The main issue of VSA is then to provide an efficient way of computing gradients. This contribution first presents the theoretical grounds of VSA: framework and problem statement, tangent and adjoint methods. Then it covers pratical means to compute derivatives, from naive to more sophisticated approaches, discussing their various 2 merits. Finally, applications of VSA are reviewed and some examples are presented, covering various applications fields: oceanography, glaciology, meteorology

Reconstructing extreme AMOC events through nudging of the ocean surface: a perfect model approach

While the Atlantic Meridional Overturning Circulation (AMOC) is thought to be a crucial component of the North Atlantic climate, past changes in its strength are challenging to quantify, and only limited information is available. In this study, we use a perfect model approach with the IPSL-CM5A-LR model to assess the performance of several surface nudging techniques in reconstructing the variability of the AMOC. Special attention is given to the reproducibility of an extreme positive AMOC peak from a preindustrial control simulation. Nudging includes standard relaxation techniques towards the sea surface temperature and salinity anomalies of this target control simulation, and/or the prescription of the wind-stress fields. Surface nudging approaches using standard fixed restoring terms succeed in reproducing most of the target AMOC variability, including the timing of the extreme event, but systematically underestimate its amplitude. A detailed analysis of the AMOC variability mechanisms reveals that the underestimation of the extreme AMOC maximum comes from a deficit in the formation of the dense water masses in the main convection region, located south of Iceland in the model. This issue is largely corrected after introducing a novel surface nudging approach, which uses a varying restoring coefficient that is proportional to the simulated mixed layer depth, which, in essence, keeps the restoring time scale constant. This new technique substantially improves water mass transformation in the regions of convection, and in particular, the formation of the densest waters, which are key for the representation of the AMOC extreme. It is therefore a promising strategy that may help to better constrain the AMOC variability and other ocean features in the models. As this restoring technique only uses surface data, for which better and longer observations are available, it opens up opportunities for improved reconstructions of the AMOC over the last few decades

Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordThe decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.J.A.S. and R.B. were funded by the Natural Environment Research Council (NE/P006760/1). C.D. acknowledges the National Science Foundation (NSF), which sponsors the National Center for Atmospheric Research. D.M.S. was supported by the Met Office Hadley Centre Climate Programme (GA01101) and the APPLICATE project, which is funded by the European Union’s Horizon 2020 programme. X.Z. was supported by the NSF (ARC#1023592). P.J.K. and K.E.M. were supported by the Canadian Sea Ice and Snow Evolution Network, which is funded by the Natural Science and Engineering Research Council of Canada. T.O. was funded by Environment and Climate Change Canada (GCXE17S038). L.S. was supported by the National Oceanic and Atmospheric Administration’s Climate Program Office