Search

Using the prediction data from the Global Seasonal Forecast version 5 (GloSea5) during the 1993–2016 period, the probabilistic prediction skills of the midsummer (July and August) surface air temperature (SAT) over the middle and lower reach of the Yangtze River valley (MLYR) are evaluated by the ranked probabilistic skill score. We found that the GloSea5 better predicts below-normal (BN) events than above-normal (AN) events at a long lead time, as well as the associated western Pacific subtropical high (WPSH) and circumglobal teleconnection (CGT) anomaly. This result reveals the asymmetry of the probabilistic prediction skills of the midsummer MLYR SAT, which is related to the asymmetric effect of predictability sources: the warm midsummer ENSO favors BN events via promoting the eastward retreat of the WPSH, whereas the cold midsummer ENSO exhibits weak effect on AN events due to the induced southwestward expansion of the WPSH; the warm mid-latitude North Atlantic (MNA) promotes AN events via projecting its influence onto the atmospheric teleconnections such as the CGT, but not vice versa. The GloSea5 exhibits strong response to both two predictability sources, but fails to reproduce the asymmetric effect of predictability sources especially for ENSO, which limits the prediction skills of AN events. On the other hand, the worse (better) simulations of the warm MNA (warm midsummer ENSO) lead to the lower (higher) prediction skills of AN (BN) events. These results are useful for better understanding the predictability of the midsummer SAT over the MLYR. [ABSTRACT FROM AUTHOR]

The record‐long 2020 Meiyu season since 1961 caused severe floods over the Yangtze and Huaihe River valleys (YHRV). Why the Meiyu duration doubled in 2020 remains a puzzle. We show that the long‐lasting Meiyu can be divided into three stages: advanced‐onset, strong‐persisting, and delayed‐withdrawal. The advanced‐onset was associated with an extremely negative‐phase East Atlantic/West Russia teleconnection. The strong‐persisting was attributed to a positive‐phase Pacific–Japan (PJ) pattern sustained by La Niña's rapid development. The delayed withdrawal was related to the combined effect of a positive PJ pattern and a mid‐troposphere "two ridge–one trough" pattern over Asia. Two subseasonal forecasting systems predicted the positive rainfall anomalies over the YHRV in the first two stages, but not the third stage, which may be associated with poor prediction of the two ridge–one trough pattern. These results highlight the role of subseasonal evolution in extreme climate events. Plain Language Summary: During the northward advance of the East Asian summer monsoon, the East Asian subtropical region is normally characterized by a quasi‐stationary rainband that persists from mid‐June to mid‐July, which is known as Meiyu in China and Baiu in Japan. Both the duration and the accumulated rainfall of the 2020 Meiyu set the highest record since 1961, which caused a severe flood and an enormous economic loss in the Yangtze and Huaihe River valleys (YHRV), central‐eastern China. We investigated the mechanism and predictions of this long‐lasting flood. The record‐long 2020 Meiyu can be divided into three stages: advanced‐onset, strong‐persisting, and delayed withdrawal. The advanced‐onset stage was mainly induced by the extratropical climate anomalies associated with the East Atlantic/West Russia teleconnection. In contrast, the strong‐persisting stage was due to the enhanced tropical forcing via triggering the Pacific–Japan pattern. The delayed withdrawal stage arises from the combined effect of tropical forcing and mid‐latitude teleconnection. The current advanced forecasting systems can predict the positive rainfall anomalies over the YHRV in the first two stages, but not the third stage. These findings advance our understanding of the extreme 2020 flood and help improve future extreme monsoon prediction. Key Points: The long‐lasting 2020 Meiyu season was characterized by three stages: advanced‐onset, strong‐persisting, and delayed withdrawalThe mid‐latitude teleconnection played a crucial role in the 2020 Meiyu onset and withdrawal, while tropical forcing's role is enhanced in the last two stagesAdvanced forecasting systems cannot predict the delayed withdrawal due to the failure in predicting the mid‐latitude teleconnection [ABSTRACT FROM AUTHOR]

By using the hindcast and forecast data from the National Centers for Environmental Prediction Climate Forecast System version 2 (NCEP CFSv2) for the 1982–2018 period, we investigate the forecasting skills of the mid‐summer (July and August) surface air temperature (SAT) at interannual timescales in this study. Although CFSv2 predictions show a warm bias for the climatological mean SAT over the Yangtze River valley (25°–32°N, 105°–122°E), they show a consistent and great performance in predicting the interannual variability of the mid‐summer SAT over this region until 4 months in advance, where the linear correlation coefficient between the predicted and observed time series reaches +0.65, +0.51 and + 0.68 for 4, 2 and 0 months in advance, respectively. The CFSv2 predictions well simulate the linkage between the SAT anomalies over the Yangtze River valley and the anomalous atmospheric circulation aloft, including the circumglobal teleconnection and zonal extension of the Western Pacific Subtropical High. However, CFSv2 has trouble in simulating the associated vertical velocity, cloud cover and solar radiation anomalies, except for 0 months in advance. The persistent forecasting skills result from the accurate response of the circumglobal teleconnection and Western Pacific Subtropical High to the El Niño/Southern Oscillation and sea surface temperature (SST) anomalies over the mid‐latitude North Atlantic. Correspondingly, the forecasting skill, signal and signal‐to‐noise ratio are effectively improved in the years with strong mid‐summer SST anomalies over the tropical central‐eastern Pacific or mid‐latitude North Atlantic. These results are useful for understanding the predictability of the mid‐summer SAT over the Yangtze River valley. [ABSTRACT FROM AUTHOR]

The occurrence of a Ural blocking (UB) event is an important precursor of severe cold air outbreaks in Siberia and East Asia, and thus is significant to accurately predict UB events. Using subseasonal to seasonal (S2S) models of the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Environment and Climate Change Canada (ECCC), we evaluated the predictability of a persistent UB event on 18 to 26 January 2012. Results showed that the ECCC model was superior to the ECMWF model in predicting the development stage of the UB event ten days in advance, while the ECMWF model had better predictions than the ECCC model for more than ten days in advance and the decaying stage of the UB event. By comparing the dynamic and thermodynamic evolution of the UB event predicted by the two models via the geostrophic vorticity tendency equation and temperature tendency equation, we found that the ECCC model better predicted the vertical vorticity advection, ageostrophic vorticity tendency, the tilting effect, horizontal temperature advection, and adiabatic heating during the development stage, whereas the ECMWF model better predicted the three dynamic and the two thermodynamic terms during the decaying stage. In addition, during both the development and decaying stages, the two models were good (bad) at predicting the vortex stretching term (horizontal vorticity advection), with the PCC between both the predictions and the observations larger (smaller) than +0.70 (+0.10) Thus, we suggest that the prediction of the persistent UB event in the S2S model might be improved by the better prediction of the horizontal vorticity advection. [ABSTRACT FROM AUTHOR]