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The upper reaches of the Yangtze River Basin (UYRB) are famous for their hydropower generation and water resources in China, relying greatly on precipitation. The UYRB summer precipitation has decreased since the early 2000s and has been exposed to a particularly dry period in the most recent two decades. By analyzing the long‐term variability from the beginning of the 20th Century, we found that the precipitation exhibits a profound periodic interdecadal variation, with a significant cycle of 30–50 years. The interdecadal variability of precipitation is shown to be significantly modulated by both the Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), exerting their impact through related circulation anomalies. Moreover, the periodical nature of the UYRB precipitation variation and its correlation with AMO/PDO suggest that the UYRB might enter a wet period in the forthcoming decade, i.e. rich in hydroelectric resources but a high risk of flood. [ABSTRACT FROM AUTHOR]

Global mean near surface temperature change is the key metric by which our warming climate is monitored and for which international climate policy is set. At the end of each year the Met Office issues a global mean temperature forecast for the coming year. Following on from the new record in 2023, we predict that 2024 will likely (76% chance) be a new record year with a 1‐in‐3 chance of exceeding 1.5°C above pre‐industrial. Whilst a one‐year temporary exceedance of 1.5°C would not constitute a breach of the Paris Agreement target, our forecast highlights how close we are now to this. Our 2024 forecast is primarily driven by the strong warming trend of +0.2°C/decade (1981–2023) and secondly by the lagged warming effect of a strong tropical Pacific El Niño event. We highlight that 2023 itself was significantly warmer than the Met Office DePreSys3 forecast, with much of this additional observed warming coming from the southern hemisphere, the cause of which requires further understanding. [ABSTRACT FROM AUTHOR]

Using a large ensemble of initialised retrospective forecasts (hindcasts) from a seasonal prediction system, we explore various statistics relating to sudden stratospheric warmings (SSWs). Observations show that SSWs occur at a similar frequency during both El Niño and La Niña northern hemisphere winters. This is contrary to expectation, as the stronger stratospheric polar vortex associated with La Niña years might be expected to result in fewer of these extreme breakdowns. Here we show that this similar frequency may have occurred by chance due to the limited sample of years in the observational record. We also show that in these hindcasts, winters with two SSWs, a rare event in the observational record, on average have an increased surface impact. Multiple SSW events occur at a lower rate than expected if events were independent but somewhat surprisingly, our analysis also indicates a risk, albeit small, of winters with three or more SSWs, as yet an unseen event. [ABSTRACT FROM AUTHOR]

The United Kingdom is committed to substantially increasing offshore wind capacity in its drive to decarbonise electricity production and achieve net zero. If low wind episodes—or 'wind drought' events—occur during high energy demand periods, energy security may be threatened without alternative supply. The challenge of managing the variability of wind power will increase into the future as its share in the energy mix increases. This study focuses attention on the North Sea as a centre of current and planned offshore wind resource, and on the winter season, given the occurrence of weather patterns that risk security of supply. We use a large climate model ensemble, providing a dataset an order of magnitude larger than the reanalysis‐based observations, to better sample wind drought events. This leads to a more robust estimate of their frequency and persistence and their dynamical teleconnections compared with the observational record. We define week‐long wind drought events, based on a 20th percentile threshold in 10 m wind speed, during which wind power is estimated to be around half that in a typical week of winter. Wind drought events of up to two consecutive weeks have been observed, but the model indicates a 1‐in‐40 chance of three or more continuous weeks of wind drought each winter, with the single most prolonged simulated event lasting 5 weeks. There is a doubling of the likelihood of these prolonged wind drought events during El Niño, indicating that monitoring and predicting the state of the tropical Pacific may be useful in assessing the risk of wind drought events in an upcoming winter. [ABSTRACT FROM AUTHOR]

Northern Europe and the UK experienced an exceptionally warm and wet winter in 2019/20, driven by an anomalously positive North Atlantic Oscillation (NAO). This positive NAO was well forecast by several seasonal forecast systems, suggesting that this winter the NAO was highly predictable at seasonal lead times. A very strong positive Indian Ocean dipole (IOD) event was also observed at the start of winter. Here we use composite analysis and model experiments, to show that the IOD was a key driver of the observed positive NAO. Using model experiments that perturb the Indian Ocean initial conditions, two teleconnection pathways of the IOD to the north Atlantic emerge: a tropospheric teleconnection pathway via a Rossby wave train travelling from the Indian Ocean over the Pacific and Atlantic, and a stratospheric teleconnection pathway via the Aleutian region and the stratospheric polar vortex. These pathways are similar to those for the El Niño Southern Oscillation link to the north Atlantic which are already well documented. The anomalies in the north Atlantic jet stream location and strength, and the associated precipitation anomalies over the UK and northern Europe, as simulated by the model IOD experiments, show remarkable agreement with those forecast and observed. [ABSTRACT FROM AUTHOR]

The Coupled Model Intercomparison Project 6 protocol suggests prescribing preindustrial ozone concentrations in abrupt‐4xCO2 simulations. This leads to a mismatch between the thermal tropopause, which rises due to climate change, and the ozone tropopause, which remains fixed. The result is unphysically high ozone concentrations in the upper troposphere, leading to a warm bias in cold point temperature and increased stratospheric water vapor. In the U.K. physical climate model HadGEM3‐GC3.1 this increases the surface climate sensitivity. In the future, other climate models without interactive ozone schemes may face similar problems. We describe a method to interactively redistribute ozone in climate simulations, which removes the inconsistency between the thermal and ozone tropopause heights while retaining the prescribed ozone distribution as closely as possible. This removes unphysical consequences of the tropopause mismatch, while still allowing a fair comparison against other Coupled Model Intercomparison Project 6 model simulations. After each model year, the monthly mean, zonal mean, thermal tropopause is formed based on the previous two model years. The ozone tropopause is defined at 1 km below the thermal tropopause by setting ozone concentrations there to 80 ppbv, and smoothing appropriately. The mass of ozone removed from the troposphere is added to the stratosphere thus conserving the total mass of ozone. This redistribution is then applied proportionally to the 3‐D monthly mean ozone concentrations. The climate model is run for the following year, using this redistributed ozone, and then the whole process is repeated. Results are presented from preindustrial and abrupt‐4xCO2 simulations, but this method can be used for any climate simulation. Key Points: Prescribed ozone in climate projections leads to unphysical ozone amounts in the upper troposphereThese impact stratospheric water vapor and surface temperatureSimple ozone redistribution is able to remove these impacts [ABSTRACT FROM AUTHOR]

Skilful climate predictions of the winter North Atlantic Oscillation and Arctic Oscillation out to a few months ahead have recently been demonstrated, but the source of this predictability remains largely unknown. Here we investigate the role of the Tropics in this predictability. We show high levels of skill in tropical rainfall predictions, particularly over the Pacific but also the Indian and Atlantic Ocean basins. Rainfall fluctuations in these regions are associated with clear signatures in tropical and extratropical atmospheric circulation that are approximately symmetric about the Equator in boreal winter. We show how these patterns can be explained as steady poleward propagating linear Rossby waves emanating from just a few key source regions. These wave source 'hotspots' become more or less active as tropical rainfall varies from winter to winter but they do not change position. Finally, we show that predicted tropical rainfall explains a highly significant fraction of the predicted year-to-year variation of the winter North Atlantic Oscillation. [ABSTRACT FROM AUTHOR]

Korean winter temperature exhibits significant year‐to‐year variability, an extreme example of which was the severe cold winter of 2012/2013. Such events can have significant societal and financial impacts. We investigate the seasonal forecast skill for Korean winter temperature using Met Office initialised climate prediction systems. We find significant skill using two independent hindcasts covering the last decades. Observed Korean winter temperature variability appears to be driven by large‐scale dynamical circulation anomalies with centers over the northwest Pacific High (PH) and the Siberian High (SH). While the model has a good simulation of these observed teleconnections, we find that skilfully predicted PH variability dominates the model skill. This is due to the relatively strong PH teleconnection to highly predictable tropical Pacific and Indian Ocean variability. Whereas, observed SH variability is currently much less predictable in seasonal forecast systems. Furthermore, we find that the modelled SH exhibits lower predictability than the observed SH, suggesting a model "signal‐to‐noise" problem over extratropical East Asia which is similar to that reported over northern Europe. We explore one possible pathway, the representation of stratosphere–troposphere coupling, by examining the model simulation of stratospheric sudden warming (SSWs) events. While the SSW frequency and the spatial pattern of surface circulation response appears well simulated, the amplitude of the model response over SH appears anomalously weak. Nevertheless, we conclude that current seasonal forecasts of Korean winter temperature are skilful and have the potential to provide useful climate services. Seasonal prediction of Korean winter temperature and associated circulation. (a) Time series of DJF temperature over Korea in observations (black) and ensemble mean hindcasts from GloSea5 (red) and DePreSys3 (blue). Maps show correlations between the temperature over Korea and mean sea level pressure (MSLP) using observations (b) and ensemble members (c). In (d) we investigate the relationship between observed Korean temperature and the model ensemble mean MSLP predictions. Stippling identifies where correlations are significant at the 90% level according to a two‐tailed t test. The green box shows Korea and black boxes show SH and PH. [ABSTRACT FROM AUTHOR]