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It is well established that El Niño–Southern Oscillation (ENSO) impacts the North Atlantic–European (NAE) climate, with the strongest influence in winter. In late winter, the ENSO signal travels via both tropospheric and stratospheric pathways to the NAE sector and often projects onto the North Atlantic Oscillation. However, this signal does not strengthen gradually during winter, and some studies have suggested that the ENSO signal is different between early and late winter and that the teleconnections involved in the early winter subperiod are not well understood. In this study, we investigate the ENSO teleconnection to NAE in early winter (November–December) and characterize the possible mechanisms involved in that teleconnection. To do so, observations, reanalysis data and the output of different types of model simulations have been used. We show that the intraseasonal winter shift of the NAE response to ENSO is detected for both El Niño and La Niña and is significant in both observations and initialized predictions, but it is not reproduced by free-running Coupled Model Intercomparison Project phase 5 (CMIP5) models. The teleconnection is established through the troposphere in early winter and is related to ENSO effects over the Gulf of Mexico and Caribbean Sea that appear in rainfall and reach the NAE region. CMIP5 model biases in equatorial Pacific ENSO sea surface temperature patterns and strength appear to explain the lack of signal in the Gulf of Mexico and Caribbean Sea and, hence, their inability to reproduce the intraseasonal shift of the ENSO signal over Europe.

In winter 2013/14 a succession of storms hit the UK leading to record rainfall and flooding in many regions including south east England. In the Thames river valley there was widespread flooding, with clean-up costs of over £1 billion. There was no observational precedent for this level of rainfall. Here we present analysis of a large ensemble of high-resolution initialised climate simulations to show that this event could have been anticipated, and that in the current climate there remains a high chance of exceeding the observed record monthly rainfall totals in many regions of the UK. In south east England there is a 7% chance of exceeding the current rainfall record in at least one month in any given winter. Expanding our analysis to some other regions of England and Wales the risk increases to a 34% chance of breaking a regional record somewhere each winter. A succession of storms during the 2013–2014 winter led to record flooding in the UK. Here, the authors use high-resolution climate simulations to show that this event could have been anticipated and that there remains a high chance of exceeding observed record monthly rainfall totals in many parts of the UK.

A state-of-the-art climate model shows that radiative forcing due to anthropogenic and volcanic aerosols explains the variability in sea surface temperature of the North Atlantic between 1950 and 2005. Influence of anthropogenic aerosols on climate Changes in North Atlantic sea surface temperatures (SSTs) have profound impacts on the climate of much of the globe. Multidecadal variability in Atlantic SST has long been thought to be governed by internal ocean dynamics, but here Booth et al . present evidence that human-generated aerosols — predominantly from fossil-fuel and biomass burning — were a prime driver of twentieth-century North Atlantic climate variability. Using a sophisticated Earth system climate model, they show that from 1860 to 2005, anthropogenic aerosol emissions strongly influenced Atlantic multidecadal SST variability and therefore the climate processes and events linked to Atlantic SSTs, such as drought and tropical cyclones. Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean 1 . These links are extensive, influencing a range of climate processes such as hurricane activity 2 and African Sahel 3 , 4 , 5 and Amazonian 5 droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations 6 , 7 , 8 , 9 , 10 . A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures 11 , 12 , but climate models have so far failed to reproduce these interactions 6 , 9 and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860–2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910–1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol–cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol–cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions.

The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.

The North Atlantic Oscillation profoundly influences European and North American winter weather. Dynamical model predictions now exhibit skill in prediction of the winter North Atlantic Oscillation more than one year in advance. The winter North Atlantic Oscillation is the primary mode of atmospheric variability in the North Atlantic region and has a profound influence on European and North American winter climate. Until recently, seasonal variability of the North Atlantic Oscillation was thought to be largely driven by chaotic and inherently unpredictable processes 1 , 2 . However, latest generation seasonal forecasting systems have demonstrated significant skill in predicting the North Atlantic Oscillation when initialized a month before the onset of winter 3 , 4 , 5 . Here we extend skilful dynamical model predictions to more than a year ahead. The skill increases greatly with ensemble size due to a spuriously small signal-to-noise ratio in the model, and consequently larger ensembles are projected to further increase the skill in predicting the North Atlantic Oscillation. We identify two sources of skill for second-winter forecasts of the North Atlantic Oscillation: climate variability in the tropical Pacific region and predictable effects of solar forcing on the stratospheric polar vortex strength. We also identify model biases in Arctic sea ice that, if reduced, may further increase skill. Our results open possibilities for a range of new climate services, including for the transport 6 , 7 , energy, water management 8 and insurance sectors.

The global warming slowdown has been attributed to the negative phase of the Pacific Decadal Oscillation. Modelling work simulates this negative phase in response to anthropogenic aerosols, indicating that external forcings may influence natural cycles. The rate of global mean surface temperature (GMST) warming has slowed this century despite the increasing concentrations of greenhouse gases. Climate model experiments 1 , 2 , 3 , 4 show that this slowdown was largely driven by a negative phase of the Pacific Decadal Oscillation (PDO), with a smaller external contribution from solar variability, and volcanic and anthropogenic aerosols 5 , 6 . The prevailing view is that this negative PDO occurred through internal variability 7 , 8 , 9 , 10 , 11 . However, here we show that coupled models from the Fifth Coupled Model Intercomparison Project robustly simulate a negative PDO in response to anthropogenic aerosols implying a potentially important role for external human influences. The recovery from the eruption of Mount Pinatubo in 1991 also contributed to the slowdown in GMST trends. Our results suggest that a slowdown in GMST trends could have been predicted in advance, and that future reduction of anthropogenic aerosol emissions, particularly from China, would promote a positive PDO and increased GMST trends over the coming years. Furthermore, the overestimation of the magnitude of recent warming by models is substantially reduced by using detection and attribution analysis to rescale their response to external factors, especially cooling following volcanic eruptions. Improved understanding of external influences on climate is therefore crucial to constrain near-term climate predictions.

An influence of solar irradiance variations on Earth’s surface climate has been repeatedly suggested. Simulations with a climate model driven by satellite measurements of solar ultraviolet irradiance show an atmospheric response to the solar minimum that resembles the negative phase of the North Atlantic Oscillation. An influence of solar irradiance variations on Earth’s surface climate has been repeatedly suggested, based on correlations between solar variability and meteorological variables 1 . Specifically, weaker westerly winds have been observed in winters with a less active sun, for example at the minimum phase of the 11-year sunspot cycle 2 , 3 , 4 . With some possible exceptions 5 , 6 , it has proved difficult for climate models to consistently reproduce this signal 7 , 8 . Spectral Irradiance Monitor satellite measurements indicate that variations in solar ultraviolet irradiance may be larger than previously thought 9 . Here we drive an ocean–atmosphere climate model with ultraviolet irradiance variations based on these observations. We find that the model responds to the solar minimum with patterns in surface pressure and temperature that resemble the negative phase of the North Atlantic or Arctic Oscillation, of similar magnitude to observations. In our model, the anomalies descend through the depth of the extratropical winter atmosphere. If the updated measurements of solar ultraviolet irradiance are correct, low solar activity, as observed during recent years, drives cold winters in northern Europe and the United States, and mild winters over southern Europe and Canada, with little direct change in globally averaged temperature. Given the quasiregularity of the 11-year solar cycle, our findings may help improve decadal climate predictions for highly populated extratropical regions.

Subtropical East Asia (STEA) experienced a historic flood in the summer of 2020, and historic drought and heatwaves in the summer of 2022. Previous studies emphasized the role of western Pacific subtropical high (WPSH), but there is a paradox that the contrasting climate extremes over STEA in 2020 and 2022 are both associated with anomalously strong WPSH. Given that local vertical motion has a dominant control on precipitation variability, here we investigate the mechanism for the variability of vertical motion in STEA. In most extratropical regions of the Northern Hemisphere, ascent (descent) motion aligns with southerly (northerly) flow in the troposphere due to the northward tilting isentropic surfaces. However, isentropic surfaces tilt eastwards over STEA in the summer due to the existence of a strong warm center over the Tibetan Plateau (TP). Thus, the ascent motion over the STEA is insensitive to the strength of southerly flow related to the intensity of the WPSH but sensitive to the strength of westerly flow related to the meridional shift of subtropical jet. The notably strong WPSH in 2020 and 2022 increased water vapor transport into STEA but had little impact on atmospheric vertical motion. However, the East Asian subtropical jet displaced southwards (northwards) in the summer of 2020 (2022), leading to anomalous westerly (easterly) flows in the mid-upper troposphere from TP to STEA on the jet’s southern flank, prompting anomalous ascent (descent) motion in STEA that contributed to the flood (drought) conditions in 2020 (2022). Our results highlight the essential role of anomalous zonal flow in generating surface climate extremes over STEA in the summer because of its strong control of vertical motion.

There is a well-established relationship between the El Niño-Southern Oscillation (ENSO) and summer climate over South Africa. ENSO predictability has formed the basis for seasonal forecasting efforts in the region. However, prediction skill over South Africa is not as high as in some other ENSO-dominated regions and there have been notable forecast failures during ENSO events. Here we examine near-term predictions of South African summer climate from two modelling centres and find evidence of a useful level of prediction skill but with an ENSO teleconnection that is weak in amplitude. We describe a Pacific-to-southern Africa wavetrain in the extratropical westerlies, which is a robust feature of the reanalysis and the modelling systems, and which plays a role in the transmission of the ENSO signal to South Africa. Further, we find that a failure of the ENSO teleconnection with South Africa is accompanied by a distortion of the wave over the South Atlantic, manifesting as a change in phase and/or position. This supports the idea that the wavetrain is a key component of the teleconnection.

Sudden stratospheric warmings (SSWs) strongly impact tropospheric weather, yet their accurate prediction remains a significant challenge. This study investigates the predictability of SSWs in the Whole Atmosphere Community Climate Model with different vertical resolutions. Results show that SSW onset can be successfully captured up to 5 days in advance with 70 vertical layers, notably shorter than ∼10‐day lead time achieved by operational models. In contrast, when vertical layers are increased to 138, the lead time can be extended to 10 days, with the improvement attributed to better prediction of planetary wave vertical propagation and the resultant wave‐mean flow interactions. Further analysis reveals that the SSW predictability is more sensitive to the vertical resolution between 0.1 and 100 hPa than in the troposphere or mesosphere and beyond. This study demonstrates that enhancing vertical resolution alone can substantially improve SSW prediction skill, despite using coarse horizontal resolution (∼1°) and simplified initialization.