Sensitivity of winter North Atlantic-European climate to resolved atmosphere and ocean dynamics

Northern Hemisphere western boundary currents, like the Gulf Stream, are key regions for cyclogenesis affecting large-scale atmospheric circulation. Recent observations and model simulations with high-temporal and -spatial resolution have provided evidence that the associated ocean fronts locally affect troposphere dynamics. A coherent view of how this affects the mean climate and its variability is, however, lacking. In particular the separate role of resolved ocean and atmosphere dynamics in shaping the atmospheric circulation is still largely unknown. Here we demonstrate for the first time, by using coupled seasonal forecast experiments at different resolutions, that resolving meso-scale oceanic variability in the Gulf Stream region strongly affects mid-latitude interannual atmospheric variability, including the North Atlantic Oscillation. Its impact on climatology, however, is minor. Increasing atmosphere resolution to meso-scale, on the other hand, strongly affects mean climate but moderately its variability. We also find that regional predictability relies on adequately resolving small-scale atmospheric processes, while resolving small-scale oceanic processes acts as an unpredictable source of noise, except for the North Atlantic storm-track where the forcing of the atmosphere translates into skillful predictions

Dominant Modes of Variability in the South Atlantic: A Study with a Hierarchy of Ocean-Atmosphere Models.

Abstract Using an atmosphere model of intermediate complexity and a hierarchy of ocean models, the dominant modes of interannual and decadal variability in the South Atlantic Ocean are studied. The atmosphere Simplified Parameterizations Primitive Equation Dynamics (SPEEDY) model has T30L7 resolution. The physical package consists of a set of simplified physical parameterization schemes, based on the same principles adopted in the schemes of state-of-the-art AGCMs. It is at least an order of magnitude faster, whereas the quality of the simulated climate compares well with those models. The hierarchy of ocean models consists of simple mixed layer models with an increasing number of physical processes involved such as Ekman transport, wind-induced mixing, and wind-driven barotropic transport. Finally, the atmosphere model is coupled to a regional version of the Miami Isopycnal Coordinate Ocean Model (MICOM) covering the South Atlantic with a horizontal resolution of 1° and 16 vertical layers. The coupled modes of mean sea level pressure and sea surface temperature simulated by SPEEDY–MICOM strongly resemble the modes as analyzed from the NCEP–NCAR reanalysis, indicating that this model configuration possesses the required physical mechanisms for generating these modes of variability. Using the ocean model hierarchy the authors were able to show that turbulent heat fluxes, Ekman transport, and wind-induced mixing contribute to the generation of the dominant modes of coupled SST variability. The different roles of these terms in generating these modes are analyzed. Variations in the wind-driven barotropic transport mainly seem to affect the SST variability in the Brazil–Malvinas confluence zone. The spectra of the mixed layer models appeared to be too red in comparison with the fully coupled SPEEDY–MICOM model due to the too strong coupling between SST and surface air temperatures (SATs), resulting from the inability to advect and subduct SST anomalies by the mixed layer models. In SPEEDY–MICOM anomalies in the southeastern corner of the South Atlantic are subducted and advected toward the north Brazilian coast on a time scale of about 6 yr

Land–Atmosphere coupling sensitivity to GCMs resolution: a multimodel assessment of local and remote processes in the Sahel hot spot

Land–atmosphere interactions are often interpreted as local effects, whereby the soil state drives local atmospheric conditions and feedbacks originate. However, nonlocal mechanisms can significantly modulate land–atmosphere exchanges and coupling. We make use of GCMs at different resolutions (low ~1° and high ~0.25°) to separate the two contributions to coupling: better represented local processes versus the influence of improved large-scale circulation. We use a two-legged metric, complemented by a process-based assessment of four CMIP6 GCMs. Our results show that weakening, strengthening, and relocation of coupling hot spots occur at high resolution globally. The northward expansion of the Sahel hot spot, driven by nonlocal mechanisms, is the most notable change. The African easterly jet’s horizontal wind shear is enhanced in JJA due to better resolved orography at high resolution. This effect, combined with enhanced easterly moisture flux, favors the development of African easterly waves over the Sahel. More precipitation and soil moisture recharge produce strengthening of the coupling, where evapotranspiration remains controlled by soil moisture, and weakening where evapotranspiration depends on atmospheric demand. In SON, the atmospheric influence is weaker, but soil memory helps to maintain the coupling between soil moisture and evapotranspiration and the relocation of the hot spot at high resolution. The multimodel agreement provides robust evidence that atmospheric dynamics determines the onset of land–atmosphere interactions, while the soil state modulates their duration. Comparison of precipitation, soil moisture, and evapotranspiration against satellite data reveals that the enhanced moistening at high resolution significantly reduces model biases, supporting the realism of the hot-spot relocation

The Bjerknes feedback in the tropical Atlantic in CMIP5 models

Coupled state-of-the-art general circulation models still perform relatively poorly in simulating tropical Atlantic (TA) climate. To investigate whether lack of air–sea interaction might be responsible for their biases, we investigate the Bjerknes feedback (BF) in the TA, the driver of the dominant interannual variability in that region. First, we analyse this mechanism from reanalysis data. Then, we compare our findings to model output from the Coupled Model Intercomparison Project Phase 5. The feedback is subdivided into three components. The first one consists of the influence of eastern equatorial sea surface temperature anomalies (SST’) on zonal wind stress anomalies ((Formula presented.)’) in the western basin. The second component is the influence of wind stress anomalies in the western TA on eastern equatorial oceanic heat content anomalies (HC’). The third component is the local response of overlying SST’ to HC’ in the eastern TA. All three components are shown to be present in ERA-Interim and ORAS4 reanalysis by correlating the two variables of each component with each other. The obtained patterns are compared to the ones from model output via pattern correlation per component. While the models display errors in the annual cycles of SST, (Formula presented.), and HC, as well as in the seasonality of the feedback, the impact of SST’ on wind stress and the impact of wind stress on HC’ are simulated relatively well by most of the models. This is especially the case when correcting for the error in seasonality. The third component of the BF, the impact of HC’ on SST’ in the eastern part of the basin, deviates from what we find in reanalysis. We find an influence of HC anomalies on overlying SSTs in the eastern equatorial TA, but it is weaker than in the reanalysis and it is not strongly confined to the equator. Longitude–depth cross sections of equatorial temperature variance and correlation between subsurface temperature anomalies and SST’ in the cold tongue region show that flawed simulation and slow adjustment of the subsurface ocean are responsible for this.</p