Winter interactions between weather regimes and marine surface in the North Atlantic European region

Abstract

[1] This study aims at understanding the winter marine surface/atmosphere interactions in the North Atlantic European (NAE) region on intraseasonal timescales. The CNRMOM1d ocean model coupled with the GELATO3 sea ice model is forced with the ERA40 surface fluxes over the 1959 -2001 period. Composites of the simulated Sea Surface Temperature (SST) and sea ice concentration anomalies associated with each weather regime are computed. These are then prescribed to the ARPEGE Atmosphere General Circulation Model. We show that the interaction with the marine surface induces a negative feedback on the persistence of the NAO -regime, favours the transition from the Zonal regime toward the Atlantic Ridge regime and destabilizes the transition from the Blocking regime toward the Atlantic Ridge regime. Citation:

Major Changes in Extreme Dust Events Dynamics Over the Arabian Peninsula During 2003–2017 Driven by Atmospheric Conditions

“…(ii) Severe widespread prolonged dust events are triggered and maintained by persistent synoptic circulations (e.g., Beegum et al., 2018; Dumka et al., 2019; Hamidi et al., 2017, 2014; Houssos et al., 2015; Knippertz & Fink, 2006; Knippertz & Stuut, 2014; Shao et al., 2010; Solomos et al., 2017). A synoptic circulation should sustain at least 3 days to reach its persistent nature (e.g., Guemas et al., 2010, 2009; Kyselý & Domonkos, 2006; Miller et al., 2020). All the identified dust events in our study are widespread in nature and affect most of the Arabian Peninsula and its surrounding regions.…”

A review on Arctic sea‐ice predictability and prediction on seasonal to decadal time‐scales

“…The shrinking sea ice also contributes to the polar temperature amplification (Manabe and Stouffer, 1980; Ingram et al , 1989; Serreze et al , 2009; Kumar et al , 2010; Screen and Simmonds, 2010). Furthermore, sensitivity of the atmosphere to extreme sea‐ice anomalies (Smith et al , 2003; Chiang et al , 2004; Magnusdottir et al , 2004; Guemas and Salas‐Mélia, 2008b) and more realistic anomalies (Alexander et al , 2004; Deser et al , 2007; Guemas et al , 2009; Balmaseda et al , 2010) have been highlighted using general circulation models (GCMs). The rapid sea‐ice decline could favour an increase in autumn/winter snowfall over Siberia, northern Canada and Alaska (Deser et al , 2010), snow cover (Deser et al , 2010; Cohen et al , 2012; Liu et al , 2012), a polar stratospheric cooling (Screen et al , 2013), a weakening of the midlatitude jet (Francis et al , 2009; Francis and Vavrus, 2012), and an increase in the frequency of cold Northern Hemisphere midlatitude winter events (Honda et al , 2009; Petoukhov and Semenov, 2010; Cohen et al , 2012; Liu et al , 2012; Yang and Christensen, 2012).…”

Dynamical prediction of Arctic sea ice modes of variability

“…Weather regimes are examples of such flow regimes that are manifested as particular atmospheric conditions on a regional scale with time scales roughly on the range of 10-100 days (Reinhold and Pierrehumbert 1982;Barnston and Livezey 1987;Vautard and Legras 1988;Ghil and Robertson 2002). The application of the concept of weather regimes in the analysis of mid-and high-latitude 1 3 synoptic systems has provided us with a deeper understanding of intrinsic climate variability (Molteni et al 1990;Michelangeli et al 1995;Cassou et al 2004;Guemas et al 2009), with potential benefits to weather and climate prediction capability (Mo and Ghil 1988;Brankovic and Molteni 1997;Cassou 2008;Riddle et al 2013) and possibly to longterm climate change (Corti et al 1999).…”