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Over recent years there have been concomitant advances in the development of stratosphere-resolving numerical models, our understanding of stratosphere–troposphere interaction, and the extension of long-range forecasts to explicitly include the stratosphere. These advances are now allowing for new and improved capability in long-range prediction. We present an overview of this development and show how the inclusion of the stratosphere in forecast systems aids monthly, seasonal, and annual-to-decadal climate predictions and multidecadal projections. We end with an outlook towards the future and identify areas of improvement that could\ud further benefit these rapidly evolving predictions.

The impact of the Arctic stratospheric polar vortex on persistent weather regimes over North America is so far under-explored. Here we show the relationship between four wintertime North American weather regimes and the stratospheric vortex strength using reanalysis data. We find that the strength of the vortex significantly affects the behavior of the regimes. Whilst a regime associated with Greenland blocking is strongly favored following weak vortex events, it is not the primary regime associated with a widespread, elevated risk of extreme cold in North America. Instead, we find that the regime most strongly associated with widespread extremely cold weather does not show a strong dependency on the strength of the lower-stratospheric zonal-mean zonal winds. We also suggest that stratospheric vortex morphology may be particularly important for cold air outbreaks during this regime.

The stratosphere can have a signi_cant impact on winter surface weather on subseasonal to seasonal (S2S) timescales. This study evaluates the ability of current operational S2S prediction systems to capture two important links between the stratosphere and tropo sphere: (1) changes in probabilistic prediction skill in the extratropical stratosphere by precursors in the tropics and the extratropical troposphere and (2) changes in surface predictability in the extratropics after stratospheric weak and strong vortex events. Prob abilistic skill exists for stratospheric events when including extratropical tropospheric precursors over the North Paci_c and Eurasia, though only a limited set of models captures the Eurasian precursors. Tropical teleconnections such as the Madden‐Julian Oscillation, the Quasi‐Biennial Oscillation, and El Nin~o Southern Oscillation increase the probabilistic skill of the polar vortex strength, though these are only captured by a limited set of models. At the surface, predictability is increased over the USA, Russia, and the Middle East for weak vortex events, but not for Europe, and the change in predictability is smaller for strong vortex events for all prediction systems. Prediction systems with poorly resolved stratospheric processes represent this skill to a lesser degree. Altogether, the analyses indicate that correctly simulating stratospheric variability and stratosphere‐troposphere dynamical coupling are critical elements for skillful S2S wintertime predictions.

The stratosphere has been identified as an important source of predictability for a range of processes on subseasonal to seasonal (S2S) timescales. Knowledge about S2S predictability within the stratosphere is however still limited. This study evaluates to what extent predictability in the extratropical stratosphere exists in hindcasts of operational prediction systems in the S2S database. The stratosphere is found to exhibit extended predictability as compared to the troposphere. Prediction systems with higher stratospheric skill tend to also exhibit higher skill in the troposphere. The analysis also includes an assessment of the predictability for stratospheric events, including early and mid‐winter sudden stratospheric warming (SSW) events, strong vortex events, and extreme heat flux events for the Northern Hemisphere, and final warming events for both hemispheres. Strong vortex events and final warming events exhibit higher levels of predictability as compared to SSW events. In general, skill is limited to the deterministic range of one to two weeks. High‐top prediction systems overall exhibit higher stratospheric prediction skill as compared to their low‐top counterparts, pointing to the important role of stratospheric representation in S2S prediction models.

Uncertainty information in natural hazard forecasts is increasingly being explicitly\ud communicated. This study was designed to determine whether different ways of\ud communicating uncertainty graphically affects decisions and interpretations of forecasts and whether expertise was a factor in decisions and interpretations from forecasts explicitly showing uncertainty. In a hypothetical decision-making task regarding ice thickness and shipping, 138 experts and non-experts received ice-thickness forecasts in four different presentations expressing uncertainty: worded probability, spaghetti plot, fan plot, and box plot. These forecasts contained no measures of central tendency. There was no consistent difference in decision or best-guess forecast (deterministic ice thickness forecast based on the forecast representation) between the different forecast representations. However, participants interpreted different amounts of uncertainty across the different forecast representations. Experts made significantly more economically rational decisions than non-experts, interpreted lower best-guess forecasts, and inferred significantly more uncertainty than nonexperts. These results suggest that care be taken in choosing how uncertainty is represented in forecasts, especially between expert and non-expert audiences.

Renewable electricity is a key enabling step in the decarbonisation of energy. Europe is at the forefront of renewable deployment and this has dramatically increased the weather-sensitivity of the continent’s power systems. Despite the importance of weather to energy systems, and widespread interest from both academia and industry, the meteorological drivers of European power systems remain difficult to identify and poorly understood. \ud \ud This study presents a new and generally applicable approach, Targeted Circulation Types (TCTs). TCTs, in contrast to standard meteorological weather-regime or circulation-typing schemes, convolve the weather-sensitivity of an impacted system of interest (in this case, the electricity system) with the intrinsic structures of the atmospheric circulation to identify its meteorological drivers. A new 38-year reconstruction of daily electricity demand and renewable supply across Europe is used to identify the winter time large-scale circulation patterns of most interest to the European electricity grid. TCTs provide greater explanatory power for power system variability and extremes compared to standard meteorological typing. Two new pairs of atmospheric patterns are highlighted, both of which have marked and extensive impacts on the European power system. The first pair resembles the meridional surface pressure dipole of the North Atlantic Oscillation but shifted eastward into Europe and noticeably strengthened, while the second pair is weaker and corresponds to surface pressure anomalies over central southern and eastern Europe. While these gross qualitative patterns are robust features of the present European power systems, the detailed circulation structures are strongly affected by the amount and location of renewables installed.

The teleconnection from the Madden-Julian Oscillation (MJO) provides a source of subseasonal variability and predictability to the North Atlantic-European (NAE) region. The El Niño-Southern Oscillation (ENSO) modulates the seasonal mean state, through which the MJO and its teleconnection pattern propagates; however, its impact on this teleconnection to the NAE region has not been investigated. Here we find a robust dependence of the teleconnections from the MJO to NAE weather regimes on the phase of ENSO. We show that the MJO to NAO+ regime tropospheric teleconnection is strongly enhanced during El Niño years, via enhanced Rossby wave activity, and suppressed during La Niña. Conversely the MJO to NAO− regime stratospheric teleconnection is enhanced during La Niña years, and suppressed during El Niño. This dependence on the background state has strong implications for subseasonal predictability, including interannual variations in subseasonal predictive skill.

Renewable electricity is a key enabling step in the decarbonisation of energy. Europe is at the forefront of renewable deployment and this has dramatically increased the weather-sensitivity of the continent’s power systems. Despite the importance of weather to energy systems, and widespread interest from both academia and industry, the meteorological drivers of European power systems remain difficult to identify and poorly understood. This study presents a new and generally applicable approach, Targeted Circulation Types (TCTs). TCTs, in contrast to standard meteorological weather-regime or circulation-typing schemes, convolve the weather-sensitivity of an impacted system of interest (in this case, the electricity system) with the intrinsic structures of the atmospheric circulation to identify its meteorological drivers. A new 38-year reconstruction of daily electricity demand and renewable supply across Europe is used to identify the winter time large-scale circulation patterns of most interest to the European electricity grid. TCTs provide greater explanatory power for power system variability and extremes compared to standard meteorological typing. Two new pairs of atmospheric patterns are highlighted, both of which have marked and extensive impacts on the European power system. The first pair resembles the meridional surface pressure dipole of the North Atlantic Oscillation but shifted eastward into Europe and noticeably strengthened, while the second pair is weaker and corresponds to surface pressure anomalies over central southern and eastern Europe. While these gross qualitative patterns are robust features of the present European power systems, the detailed circulation structures are strongly affected by the amount and location of renewables installed.

Gravity waves are an important part of the momentum budget of the atmosphere. Despite this, parameterizations of gravity wave spectra in atmospheric models are poorly constrained. Gravity waves are formed by jet streams, flow over topography and convection, all of which produce pressure perturbations as they propagate over the Earth’s surface, detectable by microbarometer arrays used for sensing infrasound. In this study, observations of gravity waves between 2007 and 2011 at an infrasound station in the Ivory Coast, West Africa are combined with meteorological data to calculate parameters such as intrinsic phase speed and wavenumber. Through spectral analysis, the seasonal and daily variations in all gravity wave parameters are examined. The gravity wave back azimuth varies with the migration of the Inter-Tropical Convergence Zone, a region of intense convection, supporting previous studies. Daily variations in gravity wave arrivals at the station can be linked to two distinct convective cycles over the land and ocean. This was achieved by combining the gravity wave parameters with lightning strikes detected by the Met Office’s Arrival Time Difference lightning detection system. Noise generated by turbulence in the middle of the day was found to attenuate smaller pressure amplitude gravity waves, artificially amplifying the daily variations in some gravity wave parameters. Detection of daily and seasonal variations in gravity wave parameters has the potential be used to improve the representation of gravity wave spectra in atmospheric models.

Stratospheric sulfate aerosol injection (SAI) has been proposed as a way to geoengineer climate. While swift global mean surface cooling is generally expected from tropical SAI, the regional impacts of such perturbation on near‐surface air temperature (SAT) are projected to be spatially inhomogeneous. By using existing simulations from the Geoengineering Model Intercomparison Project G4 scenario, where 5 Tg/year of sulfur dioxide (SO2) is injected into the tropical stratosphere to offset some of the warming in a midrange representative greenhouse gas concentration pathway (RCP4.5) between 2020 and 2070, we examine the regional detectability of the SAI surface cooling effect and attempt to find the best spatial scale for potential SAI monitoring. We use optimal fingerprint detection and attribution techniques to estimate the time horizon over which the SAI surface cooling effect would be detected after implementation in 2020 on subglobal scales, ranging from the near‐global in situ observational coverage down to subcontinental regions. We show that using the spatiotemporal SAT pattern across the Northern and Southern extratropics and the Tropics, and across the Northern and Southern Hemispheres, as well as averaging SATs over the whole globe robustly result in successful SAI detection within 10 years of geoengineering implementation in a majority of the included plausible geoengineering realizations. However, detecting the SAI effect on SAT within the first decade of implementation would be more challenging on subcontinental scales.

Stratospheric sulfate aerosol injection (SAI) has been proposed as a way to geo-engineer climate. Whilst swift global-mean surface cooling is generally expected from tropical SAI, the regional impacts of such perturbation on near-surface air temperature (SAT) are projected to be spatially inhomogeneous. By using existing simulations from the Geoengineering Model Intercomparison Project (GeoMIP) G4 scenario, where 5 Tg yr-1 of sulfur dioxide (SO2) is injected into the tropical stratosphere to offset some of the warming in a mid-range representative greenhouse gas concentration pathway (RCP4.5) between 2020 and 2070, we examine the regional detectability of the SAI surface cooling effect, and attempt to find the best spatial scale for potential SAI monitoring. We use optimal fingerprint detection and attribution techniques to estimate the time horizon over which the SAI surface cooling effect would be detected after implementation in 2020 on sub-global scales, ranging from the near-global in situ observational coverage down to sub-continental regions. We show that using the spatio-temporal SAT pattern across the Northern and Southern extra-tropics and the Tropics, and across the Northern and Southern Hemispheres, as well as averaging SATs over the whole globe robustly result in successful SAI detection within 10 years of geoengineering implementation in a majority of the included plausible geoengineering realizations. However, detecting the SAI effect on SAT within the first decade of implementation would be more challenging on sub-continental scales.