A database containing sub-seasonal to seasonal forecasts from 11 operational 30 centres is available to the research community and will help advance our understanding of 31 the sub-seasonal to seasonal time range.Abstract 51 52Demands are growing rapidly in the operational prediction and applications communities for 53 forecasts that fill the gap between medium-range weather and long-range or seasonal 54

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

In early summer 2020, the Meiyu-Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. The enhanced Meiyu-Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu-Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO-western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu-Baiu rainfall in 2020 originated from the super IOD. Plain Language Summary In early summer 2020, Japan and central China suffered from serious floods due to torrential rainfall associated with the intensified Meiyu-Baiu front, which extends from central China to southern Japan. The results of climate model simulations indicated that a warm condition of the Indian Ocean (IO) was an underlying condition for the enhanced rainfall. We found that the warm IO condition can be traced back to the strong Indian Ocean Dipole (IOD) episode in 2019, which featured a pair of colder-than-normal and warmer-than-normal ocean temperatures west of the Sumatra coast and in the western IO, respectively. This IOD contributed to the IO warming in the following seasons through oceanic dynamics and monsoon modulation.

[1] Refinements to a prognostic scheme of skin sea surface temperature (SST) are proposed and tested. The refinements consist of two modifications of a Monin-Obukhov similarity function for stable conditions and mixing enhancement by the Langmuir circulation. The modified scheme is tested with the European Centre for Medium-Range Weather Forecasts model. The modified scheme shows better agreement of the diurnal SST amplitude with estimates from satellite observations. The scheme is also validated with moored buoy observations of the Arabian Sea Mixed Layer Dynamics Experiment. The off-line model with the modified scheme reproduces the observed diurnal SST variability well. Additionally, it is found that the parameterization of the effect of the Langmuir circulation enhances ocean mixing and reduces the diurnal variability of SST under wavy conditions.Citation: Takaya, Y., J.-R. Bidlot, A. C. M. Beljaars, and P. A. E. M. Janssen (2010), Refinements to a prognostic scheme of skin sea surface temperature,