This study evaluates seasonal precipitation forecasts over China produced by statistically postprocessing multiple-output fields from the European Centre for Medium-Range Weather Forecasts' System4 (SYS4) coupled ocean-atmosphere general circulation model (CGCM). To ameliorate systematic deficiencies in the SYS4 precipitation forecasts, we apply a Bayesian joint probability (BJP) modeling approach to calibrate the raw forecasts. To improve the skill of the calibration forecasts, we use six large-scale climate indices, calculated from SYS4 sea surface temperature forecasts, to establish a set of BJP statistical bridging models to forecast precipitation. The calibration forecasts and bridging forecasts are merged through Bayesian model averaging to combine strengths of the different models. The BJP calibration effectively removes bias and improves statistical reliability of the raw forecasts. The calibration forecasts are skillful at a 0 month lead in most seasons, but skill decreases sharply at a 1 month lead. The skill of the bridging forecasts is more stable at different lead times. Consequently, the merged calibration and bridging forecasts at a 1 month lead are clearly more skillful than the calibration forecasts, and the skill is maintained out to a 4 month lead. The forecast framework used in this study can help to better realize the potential of CGCM ensemble forecasts. The increased reliability as well as improved skill of seasonal precipitation forecasts suggests that the system proposed here could be a useful operational forecasting tool.

Polycystic ovary syndrome (PCOS) affects approximately 7% of the reproductive-age women. A growing body of evidence indicated that epigenetic mechanisms contributed to the development of PCOS. The role of DNA modification in human PCOS ovary granulosa cell is still unknown in PCOS progression. Global DNA methylation and hydroxymethylation were detected between PCOS’ and controls’ granulosa cell. Genome-wide DNA methylation was profiled to investigate the putative function of DNA methylaiton. Selected genes expressions were analyzed between PCOS’ and controls’ granulosa cell. Our results showed that the granulosa cell global DNA methylation of PCOS patients was significant higher than the controls’. The global DNA hydroxymethylation showed low level and no statistical difference between PCOS and control. 6936 differentially methylated CpG sites were identified between control and PCOS-obesity. 12245 differential methylated CpG sites were detected between control and PCOS-nonobesity group. 5202 methylated CpG sites were significantly differential between PCOS-obesity and PCOS-nonobesity group. Our results showed that DNA methylation not hydroxymethylation altered genome-wide in PCOS granulosa cell. The different methylation genes were enriched in development protein, transcription factor activity, alternative splicing, sequence-specific DNA binding and embryonic morphogenesis. YWHAQ, NCF2, DHRS9 and SCNA were up-regulation in PCOS-obesity patients with no significance different between control and PCOS-nonobesity patients, which may be activated by lower DNA methylaiton. Global and genome-wide DNA methylation alteration may contribute to different genes expression and PCOS clinical pathology.

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