We provide an updated analysis of instrumental Greenland monthly temperature data to 2019, focusing mainly on coastal stations but also analysing ice‐sheet records from Swiss Camp and Summit. Significant summer (winter) coastal warming of ~1.7 (4.4)°C occurred from 1991–2019, but since 2001 overall temperature trends are generally flat and insignificant due to a cooling pattern over the last 6–7 years. Inland and coastal stations show broadly similar temperature trends for summer. Greenland temperature changes are more strongly correlated with Greenland Blocking than with North Atlantic Oscillation changes. In quantifying the association between Greenland coastal temperatures and Greenland Ice Sheet (GrIS) mass‐balance changes, we show a stronger link of temperatures with total mass balance rather than surface mass balance. Based on Greenland coastal temperatures and modelled mass balance for the 1972–2018 period, each 1°C of summer warming corresponds to ~(91) 116 Gt·yr⁻¹ of GrIS (surface) mass loss and a 26 Gt·yr⁻¹ increase in solid ice discharge. Given an estimated 4.0–6.6°C of further Greenland summer warming according to the regional model MAR projections run under CMIP6 future climate projections (SSP5‐8.5 scenario), and assuming that ice‐dynamical losses and ice sheet topography stay similar to the recent past, linear extrapolation gives a corresponding GrIS global sea‐level rise (SLR) contribution of ~10.0–12.6 cm by 2100, compared with the 8–27 cm (mean 15 cm) “likely” model projection range reported by IPCC in 2019 (SPM.B1.2). However, our estimate represents a lower limit for future GrIS change since fixed dynamical mass losses and amplified melt arising from both melt‐albedo and melt‐elevation positive feedbacks are not taken into account here.

Recent studies note a significant increase in high-pressure blocking over the Greenland region (Greenland Blocking Index, GBI) in summer since the 1990s. Such a general circulation change, indicated by a negative trend in the North Atlantic Oscillation (NAO) index, is generally highlighted as a major driver of recent surface melt records observed on the Greenland Ice Sheet (GrIS). Here we compare reanalysis-based GBI records with those from the Coupled Model Intercomparison Project 5 (CMIP5) suite of global climate models over 1950–2100. We find that the recent summer GBI increase lies well outside the range of modelled past reconstructions and future GBI projections (RCP4.5 and RCP8.5). The models consistently project a future decrease in GBI (linked to an increase in NAO), which highlights a likely key deficiency of current climate models if the recently observed circulation changes continue to persist. Given well-established connections between atmospheric pressure over the Greenland region and air temperature and precipitation extremes downstream, e.g. over northwest Europe, this brings into question the accuracy of simulated North Atlantic jet stream changes and resulting climatological anomalies over densely populated regions of northern Europe as well as of future projections of GrIS mass balance produced using global and regional climate models.

Sudden stratospheric warmings (SSWs) can have major impact on surface wintertime weather, especially at mid‐high latitudes. We do not yet have a complete understanding of why some of these events influence our weather more than others, but one factor may be the dynamical nature of the SSW; whether it involves a split or a displacement of the polar vortex, and one way to explore this is through comprehensive climate models. Here, we analyze the stratospheric dynamics of SSWs within models from the sixth Coupled Model Intercomparison Project (CMIP6). All CMIP6 models simulate SSWs to some degree, although we find a persistent bias in the relative underrepresentation of split vortex events. When comparing with CMIP5 models, large biases persist despite significant model improvements in resolution and in representing atmospheric processes. We show that the simulated displacement frequency is strongly related to climatological lower stratospheric eddy heat flux. The split frequency, on the other hand, is not related to lower stratospheric eddy heat flux, but is strongly related to both the vortex geometry (aspect ratio) and lower stratospheric zonal winds. This suggests that those models with a large positive bias in zonal winds may inhibit the propagation of zonal wavenumber 2 planetary waves from the troposphere, which are associated with split events. Our results suggest how future model development may address these longstanding biases.

We present a homogenized Greenland blocking index (GBI) daily record from 1851 to 2015, therefore significantly extending our previously published monthly/seasonal GBI analysis. This new time series is analysed for evidence of changes in extreme events, and we investigate the underlying thermodynamic and dynamic precursors. We compare occurrences and changes in extreme events between our GBI record and a recently published, temporally similar daily North Atlantic Oscillation (NAO) series, and use this comparison to test dynamic meteorology hypotheses relating negative NAO to Greenland blocking. We also compare daily GBI changes and extreme events with long‐running indices of England and Wales temperature and precipitation, to assess potential downstream effects of Greenland blocking on UK extreme weather events and climate change. In this extended analysis we show that there have been sustained periods of positive GBI during 1870–1900 and from the late 1990s to present. A clustering of extreme high GBI events since 2000 is not consistently reflected by a similar grouping of extreme low NAO events. Case studies of North Atlantic atmospheric circulation changes linked with extreme high and low daily GBI episodes are used to shed light on potential linkages between Greenland blocking and jet‐stream changes. Particularly noteworthy is a clustering of extreme high GBI events during mid‐October in 4 out of 5 years during 2002–2006, which we investigate from both cryospheric and dynamic meteorology perspectives. Supporting evidence suggests that these autumn extreme GBI episodes may have been influenced by regional sea‐ice anomalies off west Greenland but were probably largely forced by increases in Rossby‐wave train activity originating from the tropical Pacific. However, more generally our results indicate that high GBI winter anomalies are co‐located with sea‐ice anomalies, while there seems to be minimal influence of sea‐ice anomalies on the recent significant increase in summer GBI.

We investigate factors influencing European winter (DJFM) air temperatures for the period 1979–2015 with the focus on changes during the recent period of rapid Arctic warming (1998–2015). We employ meteorological reanalyses analysed with a combination of correlation analysis, two pattern clustering techniques, and back‐trajectory airmass identification. In all five selected European regions, severe cold winter events lasting at least 4 days are significantly correlated with warm Arctic episodes. Relationships during opposite conditions of warm Europe/cold Arctic are also significant. Correlations have become consistently stronger since 1998. Large‐scale pattern analysis reveals that cold spells are associated with the negative phase of the North Atlantic Oscillation (NAO‐) and the positive phase of the Scandinavian (SCA+) pattern, which in turn are correlated with the divergence of dry‐static energy transport. Warm European extremes are associated with opposite phases of these patterns and the convergence of latent heat transport. Airmass trajectory analysis is consistent with these findings, as airmasses associated with extreme cold events typically originate over continents, while warm events tend to occur with prevailing maritime airmasses. Despite Arctic‐wide warming, significant cooling has occurred in northeastern Europe owing to a decrease in adiabatic subsidence heating in airmasses arriving from the southeast, along with increased occurrence of circulation patterns favouring low temperature advection. These dynamic effects dominated over the increased mean temperature of most circulation patterns. Lagged correlation analysis reveals that SCA‐ and NAO+ are typically preceded by cold Arctic anomalies during the previous 2–3 months, which may aid seasonal forecasting.