Euro‐Atlantic regimes are typically identified using either the latitude of the North Atlantic jet or clustering algorithms in the phase space of 500‐hPa geopotential (Z500). However, while robust ...trimodality is visibly apparent in jet latitude indices, Z500 clusters require highly sensitive significance tests to distinguish them from autocorrelated noise. This leads to considerable decadal variability in regime patterns, confounding many potential applications. A clear‐cut choice of the optimal number of regimes is also hard to justify. We argue that the jet speed, a near‐Gaussian distribution projecting strongly onto the Z500 field, is the source of these difficulties. Once its influence is removed, the phase space becomes visibly non‐Gaussian, and clustering algorithms easily recover three regimes, closely corresponding to the jet latitude modes. Further analysis supports the existence of two additional blocking regimes, corresponding to a tilted and split jet. All five regimes are approximately stationary across the twentieth century.
Plain Language Summary
Weather over the North Atlantic region during winter is highly variable, with shifts in the jet stream and anticyclonic blocks both having large impacts on western Europe. A common way of thinking about this variability is in terms of movement between persistent large‐scale weather patterns termed regimes. However, settling on an optimal and consistent set of regime patterns has proved very challenging. We show that by removing the influence of jet speed from the geopotential height field, it is much easier to identify stable regime patterns, which well describe observations. These patterns include both jet dynamics and blocked states, forming a bridge between previous studies that looked for regimes in either the jet latitude or geopotential height in isolation.
Key Points
The approximately Gaussian jet speed serves to obscure non‐Gaussian regime structure in the phase space of geopotential height
If this influence is removed, the regime structure becomes significantly more robust and stable across the entire twentieth century
We find a new paradigm of three main regimes that can be consistently extended to five regimes, capturing both jet latitude and blocking patterns
Recently, much attention has been devoted to better understand the internal modes of variability of the climate system. This is particularly important in mid-latitude regions like the North-Atlantic, ...which is characterized by a large natural variability and is intrinsically difficult to predict. A suitable framework for studying the modes of variability of the atmospheric circulation is to look for recurrent patterns, commonly referred to as Weather Regimes. Each regime is characterized by a specific large-scale atmospheric circulation pattern, thus influencing regional weather and extremes over Europe. The focus of the present paper is the study of the Euro-Atlantic wintertime Weather Regimes in the climate models participating to the PRIMAVERA project. We analyse here the set of coupled historical simulations (hist-1950), which have been performed both at standard and increased resolution, following the HighresMIP protocol. The models’ performance in reproducing the observed Weather Regimes is assessed in terms of different metrics, focussing on systematic biases and on the impact of resolution. We also analyse the connection of the Weather Regimes with the Jet Stream latitude and blocking frequency over the North-Atlantic sector. We find that—for most models—the regime patterns are better represented in the higher resolution version, for all regimes but the NAO-. On the other side, no clear impact of resolution is seen on the regime frequency of occurrence and persistence. Also, for most models, the regimes tend to be more tightly clustered in the increased resolution simulations, more closely resembling the observed ones. However, the horizontal resolution is not the only factor determining the model performance, and we find some evidence that biases in the SSTs and mean geopotential field might also play a role.
The impact of the stochastic schemes Stochastically Perturbed Parametrisation Tendencies (SPPT) and Stochastic Kinetic Energy Backscatter Scheme (SKEBS) on the representation of interannual ...variability in the Asian summer monsoon is examined in the coupled climate model CCSM4. The Webster–Yang index, measuring anomalies of a specified wind-shear index in the monsoon region, is used as a metric for monsoon strength, and is used to analyse the output of three model integrations: one deterministic, one with SPPT, and one with SKEBS. Both schemes show improved variability, which we trace back to improvements in the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). SPPT improves the representation of ENSO and through teleconnections thereby the monsoon, supporting previous work on the benefits of this scheme on the model climate. SKEBS also improves monsoon variability by way of improving the representation of the IOD, in particular by breaking an overly strong coupling to ENSO.
There is growing evidence that the atmospheric dynamics of the Euro‐Atlantic sector during winter is driven in part by the presence of quasi‐persistent regimes. However, general circulation models ...typically struggle to simulate these with, for example, an overly weakly persistent blocking regime. Previous studies have showed that increased horizontal resolution can improve the regime structure of a model but have so far only considered a single model with only one ensemble member at each resolution, leaving open the possibility that this may be either coincidental or model dependent. We show that the improvement in regime structure due to increased resolution is robust across multiple models with multiple ensemble members. However, while the high‐resolution models have notably more tightly clustered data, other aspects of the regimes may not necessarily improve and are also subject to a large amount of sampling variability that typically requires at least three ensemble members to surmount.
Key Points
Climate models have difficulty representing Euro‐Atlantic regime structure correctly
Increasing horizontal resolution improves the significance of regime clustering across multiple models
Spatial patterns and persistence levels of regimes do not necessarily improve with increased resolution
Stochastic schemes, designed to represent unresolved subgrid‐scale variability, are frequently used in short and medium‐range weather forecasts, where they are found to improve several aspects of the ...model. In recent years, the impact of stochastic physics has also been found to be beneficial for the model's long‐term climate. In this paper, we demonstrate for the first time that the inclusion of a stochastic physics scheme can notably affect a model's projection of global warming, as well as its historical climatological global temperature. Specifically, we find that when including the “stochastically perturbed parametrization tendencies” (SPPT) scheme in the fully coupled climate model EC‐Earth v3.1, the predicted level of global warming between 1850 and 2100 is reduced by 10% under an RCP8.5 forcing scenario. We link this reduction in climate sensitivity to a change in the cloud feedbacks with SPPT. In particular, the scheme appears to reduce the positive low cloud cover feedback and increase the negative cloud optical feedback. A key role is played by a robust, rapid increase in cloud liquid water with SPPT, which we speculate is due to the scheme's nonlinear interaction with condensation.
Plain Language Summary
Accurate estimates of the extent of global warming by 2100 are crucial for determining effective climate policies. However, large uncertainties still remain, due in large part to uncertainties in the response of clouds to global warming. Model uncertainties arise largely from the need to crudely estimate the effects of processes too small to represent perfectly (given the limits of current computing power). “Stochastic schemes” aim to represent such errors, thereby, potentially, improving climate models. Indeed, many such improvements have been found over the last decade. In this paper, we show that the inclusion of such a scheme in one particular climate model has the effect of reducing the projected global warming by 10%. We link this to the scheme having changed the response of clouds to global warming. A potential consequence of this result is that carefully calibrated stochastic schemes could, by representing model errors, improve the accuracy of global warming projections.
Key Points
The inclusion of a stochastic scheme reduces climate sensitivity in a general circulation model
This reduction, of around 10%, is linked to changes in cloud cover and cloud optical depth feedbacks
Well‐calibrated stochastic schemes may give more accurate global warming projections
Even the most advanced climate models struggle to reproduce the observed wintertime circulation of the atmosphere over the North Atlantic and western Europe. During winter, the large-scale motions of ...this particularly challenging region are dominated by eddy-driven and highly non-linear flows, whose low-frequency variability is often studied from the perspective of regimes – a small number of qualitatively distinct atmospheric states. Poor representation of regimes associated with persistent atmospheric blocking events, or variations in jet latitude, degrades the ability of models to correctly simulate extreme events. In this paper we leverage a recently developed hybrid approach – which combines both jet and geopotential height data – to assess the representation of regimes in 8400 years of historical climate simulations drawn from the Coupled Model Intercomparison Project (CMIP) experiments, CMIP5, CMIP6, and HighResMIP. We show that these geopotential-jet regimes are particularly suited to the analysis of climate data, with considerable reductions in sampling variability compared to classical regime approaches. We find that CMIP6 has a considerably improved spatial regime structure, and a more trimodal eddy-driven jet, relative to CMIP5, but it still struggles with under-persistent regimes and too little European blocking when compared to reanalysis. Reduced regime persistence can be understood, at least in part, as a result of jets that are too fast and eddy feedbacks on the jet stream that are too weak – structural errors that do not noticeably improve in higher-resolution models.
The extent to which interannual variability in Arctic sea ice influences the mid-latitude circulation has been extensively debated. While observational data support the existence of a teleconnection ...between November sea ice in the Barents–Kara region and the subsequent winter North Atlantic Oscillation, climate models do not consistently reproduce such a link, with only very weak inter-model consensus. We show, using the EC-Earth3 climate model, that while an ensemble of coupled EC-Earth3 simulations shows no evidence of such a teleconnection, the inclusion of stochastic parameterizations to the ocean and sea ice component results in the emergence of a robust teleconnection comparable in magnitude to that observed. While the exact mechanisms causing this remain unclear, we argue that it can be accounted for by an improved ice–ocean–atmosphere coupling due to the stochastic perturbations, which aim to represent the effect of unresolved ice and ocean variability. In particular, the weak inter-model consensus may to a large extent be due to model biases in surface coupling, with stochastic parameterizations being one possible remedy.
It has been demonstrated that decadal variations in the North Atlantic Oscillation (NAO) can be predicted by current forecast models. While Atlantic Multidecadal Variability (AMV) in sea surface ...temperatures (SSTs) has been hypothesised as the source of this skill, the validity of this hypothesis and the pathways involved remain unclear. We show, using reanalysis and data from two forecast models, that the decadal predictability of the NAO can be entirely accounted for by the predictability of decadal variations in the speed of the North Atlantic eddy-driven jet, with no predictability of decadal variations in the jet latitude. The sub-polar North Atlantic (SPNA) is identified as the only obvious common source of an SST-based signal across the models and reanalysis, and the predictability of the jet speed is shown to be consistent with a forcing from the SPNA visible already within a single season. The pathway is argued to be tropospheric in nature, with the SPNA-associated heating extending up to the mid-troposphere, which alters the meridional temperature gradient around the climatological jet core. The relative roles of anthropogenic aerosol emissions and the Atlantic Meridional Overturning Circulation (AMOC) at generating predictable SPNA variability are also discussed. The analysis is extensively supported by the novel use of a set of seasonal hindcasts spanning the 20th century and forced with prescribed SSTs.
PDF
