<p>We investigate the seasonal predictability of the two dominant atmospheric teleconnections associated with the North Atlantic Jet: the Summer North Atlantic Oscillation (SNAO) and East Atlantic Pattern (EAP). We go beyond standard forecast practices by combining an ensemble predictions system with a machine learning approach. Specifically, we combine on the one hand a 30-member hindcast ensemble initialised every May between 1902 and 2008 in the Max Planck Institute Earth System Model in mixed resolution (MPI-ESM-MR), with on the other hand a neural network-based classifier Self-Organising Maps (SOM) in the ERA-20C reanalysis. We use the SOM to identify a sub-ensemble in which simulated North Atlantic sea surface temperatures (SST) at the initialisation of the prediction system (i.e. April) are linked to atmospheric modes.</p><p>While we find for summer climate at 3-4 months lead time only limited predictive skill in the ensemble mean of MPI-ESM-MR, we find significant predictive skill over many areas in the SOM-based sub-ensemble. Our results suggest that the predictive skill of European summer temperatures can be linked to the predictive skill of SNAO and EAP, which stems in turn from the &#8211; with skill predictable - temperature gradient between subpolar and subtropical gyres. We also demonstrate the predictive skill is time dependent, with high skill over the late half of the time series (1955 - 2008) and low skill in the early period (1902 - 1954).</p>
Abstract. 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 (SSTA) a season ahead. We consider the physical mechanism proposed by Duchez et al. (2016a) and test the dependence of SST predictive skill in initialised hindcasts on the phase of AMOC at 26° N. We use initialised simulations with the MPI-ESM-MR seasonal prediction system. First, we use the assimilation experiment between 1979–2014 to confirm that the AMOC leads a SSTA dipole pattern in the tropical and subtropical North Atlantic, with 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. We find higher SST hindcast skill at 2–4 months lead time for SSTA composites based on the AMOC phase for February, May and November start dates. Our method shows major benefit for May start dates, where mean summer SST hindcast skill over the subtropics increase by a factor of 2, reaching up to 80 % agreement with ERA-Interim SST.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.