Julianna Carvalho-Oliveira, Leonard Borchert, Aurélie Duchez, Mikhail Dobrynin and Johanna Baehr
The temperature of the sea surface is known to have an influence on weather and climate, including tropical cyclones. Predicting sea temperature variation in advance therefore has many benefits, however the mechanisms behind this variation are unclear. This study analyses how ocean circulation can be used to help predict sea temperatures up to 6 months in advance. The team found that circulation has the greatest discernible effect on sea temperatures 2-4 months later and has a stronger effect in more recent years. Accounting for circulation strength does improve sea surface temperature simulations, but only in the summer months. Knowing this, strategic use of circulation data could help us improve our seasonal simulations of sea surface temperature, potentially improving our predictions of some extreme weather events.
Sea Surface Temperature (SST) is known to have a large influence on the weather and on climate trends on a seasonal timescale (a few months ahead). SST anomalies in tropical oceans have been linked to tropical cyclones and heatwaves, influencing their frequency and their intensity. SST variations can also affect marine resources such as fish stocks. These all have socio-economic importance, therefore predicting their changes could have many benefits. Unfortunately, the mechanisms behind SST variations are not well understood, limiting how well we can predict seasonal SST anomalies. The large-scale circulation of water currents around the Atlantic (Atlantic Meridional Overturning Circulation, AMOC) is an important driver of seasonal predictability for SSTs, however its strength is variable in itself. This paper examines to what extent the AMOC influences SST predictability in the tropical and extra-tropical Atlantic Ocean. This could improve our predictions of SST variability and its influence on local climate, potentially giving more warning of extreme weather events.
The team found that AMOC strength at 26° N was a good indicator of seasonal SST anomaly patterns. A strong AMOC moves warm water northwards, leading to warmer northerly SSTs and cooler readings in the tropics. When the AMOC is weak this effect is reduced, leading to warmer tropical SSTs. This AMOC-SST correlation was most noticeable 2-4 months later but is sensitive to the length of time being studied. The effect was stronger in spring and summer, and over 2004-2014 than for the whole simulation back to 1979. Regarding SST predictability, the skill of retrospective climate model simulations (hindcasts) was improved when considering data on AMOC strength but only over the summer months. Various factors prevent an increase in hindcast skill in other months of the year. This is an important new finding, showing that knowledge of AMOC strength can improve the predictability of SSTs, but only in certain circumstances. When used with caution, this could help us improve our forecasts of SST and its effects on climate and weather events.
This study used retrospective climate predictions, known as hindcasts, generated by the MPI-ESM-MR climate model. One simulation ran from Jan 1979 to Dec 2014 and was used to assess the long-term dependence of SSTs on AMOC variability. A 30-member hindcast ensemble was used to evaluate how well SST anomalies can be predicted depending on the AMOC strength. This ensemble was initialised every February, May, August and November between 1982 and 2014 and ran for six months each time. The 30 members of this ensemble use the same climate model but use slightly different initial conditions to capture the uncertainty of observational data.
These findings suggest a possible useful mechanism for improving our seasonal forecasts of SSTs and, consequently, their influence on extreme weather events such as tropical cyclones. This could improve efforts to prepare for such events in the months prior, reducing their impact.
We investigate the impact of the strength of the Atlantic Meridional Overturning Circulation (AMOC) at 26∘ N on the prediction of North Atlantic sea surface temperature anomalies (SSTAs) a season ahead. We test the dependence of sea surface temperate (SST) predictive skill in initialised hindcasts on the phase of the AMOC at 26∘N, invoking a seesaw mechanism driven by AMOC fluctuations, with positive SSTAs north of 26∘ N and negative SSTAs south of 26∘ N after a strong AMOC and vice versa. We use initialised simulations with the MPI-ESM-MR (where MR is mixed resolution) seasonal prediction system. First, we use an assimilation experiment between 1979–2014 to confirm that the AMOC leads a SSTA dipole pattern in the tropical and subtropical North Atlantic, with the strongest AMOC fingerprints after 2–4 months. Going beyond previous studies, we find that the AMOC fingerprint has a seasonal dependence and is sensitive to the length of the observational window used, i.e. stronger over the last decade than for the entire time series back to 1979. We then use a set of ensemble hindcast simulations with 30 members, starting each February, May, August and November between 1982 and 2014. We compare the changes in skill between composites based on the AMOC phase a month prior to each start date to simulations without considering the AMOC phase and find subtle influence of the AMOC mechanism on seasonal SST prediction skill. We find higher subtropical SST hindcast skill at a 2–4-month lead time for June–July–August (JJA) SSTA composites based on the AMOC phase at May start dates than for the full time period. In other regions and seasons, we find a negligible impact of the AMOC seesaw mechanism on seasonal SST predictions due to atmospheric influence, calling for caution when considering such a mechanism. Our method shows that, for May start dates following strong AMOC phases, summer SST hindcast skill over the subtropics increases significantly compared to that of weak AMOC phases. This suggests that in the assessment of SST skill for a season ahead an eye should be kept on the initial AMOC state.