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Rainfall forecasts for the summer monsoon season in the Yangtze River basin (YRB) allow decision-makers to plan for possible flooding, which can affect the lives and livelihoods of millions of people. A trial climate service was developed in 2016, producing a prototype seasonal forecast product for use by stakeholders in the region, based on rainfall forecasts directly from a dynamical model. Here, we describe an improved service based on a simple statistical downscaling approach. Through using dynamical forecast of an East Asian summer monsoon (EASM) index, seaso-nal mean rainfall for the upper and middle/lower reaches of YRB can be forecast separately by use of the statistical downscaling, with significant skills for lead times of up to at least three months. The skill in different sub-basin regions of YRB varies with the target season. The rainfall forecast skill in the middle/lower reaches of YRB is significant in May–June–July (MJJ), and the forecast skill for rainfall in the upper reaches of YRB is significant in June–July–August (JJA). The mean rainfall for the basin as a whole can be skillfully forecast in both MJJ and JJA. The forecasts issued in 2019 gave good guidance for the enhanced rainfall in the MJJ period and the near-average conditions in JJA. Initial feedback from users in the basin suggests that the improved forecasts better meet their needs and will enable more robust decision-making.

Winter 2015/16 exhibited contrasting weather patterns in western Europe. Early winter saw a succession of high-impact storms, and December was the wettest calendar month recorded in the United Kingdom. February experienced a shift to relatively cooler conditions. Overall, the winter was well forecast by GloSea5, the Met Office’s seasonal prediction system, capturing the positive North Atlantic Oscillation (NAO) in early winter and the northwesterly pattern of flow in February. In this paper, we use a series of atmospheric relaxation experiments to investigate tropical drivers of these signals and the shift in pressure patterns over the course of the winter. While December’s positive NAO is highly consistent with the strong El Niño event in the tropical Pacific Ocean, this pattern is shown to be modified by wavelike activity from the tropical Atlantic Ocean. The result is a shift in the direction of the prevailing flow from westerly to southwesterly, helping to explain the unusually high U.K. precipitation. In February, the surface pressure pattern is characteristic of a strong (rather than a moderate) El Niño, driven by the eastward extension of the Walker circulation. The relaxation experiments indicate that both the Pacific and Atlantic basins play a role in explaining the phenomena of winter 2015/16. To correctly predict the extratropical response over northern Europe, an accurate representation of tropical forcings in both basins is required.

Variations of surface air temperature (SAT) are key in affecting the hydrological cycle, ecosystems and agriculture in western China in summer. This study assesses the seasonal forecast skill and reliability of SAT in western China, using the GloSea5 operational forecast system from the UK Met Office. Useful predictions are demonstrated, with considerable skill over most regions of western China. The temporal correlation coefficients of SAT between model predictions and observations are larger than 0.6, in both northwestern China and the Tibetan Plateau. There are two important sources of skill for these predictions in western China: interannual variation of SST in the western Pacific and the SST trend in the tropical Pacific. The tropical SST change in the recent two decades, with a warming in the western Pacific and cooling in the eastern Pacific, which is reproduced well by the forecast system, provides a large contribution to the skill of SAT in northwestern China. Additionally, the interannual variation of SST in the western Pacific gives rise to the reliable prediction of SAT around the Tibetan Plateau. It modulates convection around the Maritime Continent and further modulates the variation of SAT on the Tibetan Plateau via the surrounding circulation. This process is evident irrespective of detrending both in observations and the model predictions, and acts as a source of skill in predictions for the Tibetan Plateau. The predictability and reliability demonstrated in this study is potentially useful for climate services providing early warning of extreme climate events and could imply useful economic benefits.

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.

We investigate seasonal forecasts of the winter North Atlantic Oscillation (NAO) and their relationship with the stratosphere. Climatological frequencies of sudden stratospheric warming (SSW) and strong polar vortex (SPV) events are well represented and the predicted risk of events varies between 25 and 90% from winter to winter, indicating predictability beyond the deterministic range. The risk of SSW and SPV events relates to predicted NAO as expected, with NAO shifts of −6.5 and +4.8 hPa in forecast members containing SSW and SPV events. Most striking of all is that forecast skill of the surface winter NAO vanishes from these hindcasts if members containing SSW events are excluded.