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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]

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]

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]

Using hindcast and forecast data from advanced prediction systems of NCEP CFSv2 and JMA/MRI CPSv2 for the winter 1982/1983–2017/2018, this study investigates the predictability of the climatology and dominant modes of winter-mean surface air temperature (SAT) over East Asia. Although the simulated climatological mean SAT has a large bias over most of the mainland China, both models show high forecasting skills for the principal components (PC1 and PC2) of the two major modes (northern and southern temperature modes) of the winter-mean SAT over East Asia 1 month in advance. In comparison, the MRI-CPSv2 performs better than the CFSv2 in simulating the spatial distribution of the northern temperature mode and the associated circulation anomalies aloft, but the CFSv2 has better performance than the MRI-CPSv2 in simulating the spatial distribution of southern temperature mode and its linkage to the Arctic Oscillation and Eurasian pattern. Furthermore, both models well simulate the impacts of the dipole sea surface temperature (SST) anomalies over the mid-latitude North Pacific and El Niño–Southern Oscillation on the northern and southern temperature modes, respectively. Accordingly, the forecasting skill and signal-to-noise ratio of the PC1 (PC2) are significantly improved in the years with strong SST anomalies over the mid-latitude North Pacific (tropical central-eastern Pacific), particularly for the CFSv2 (MRI-CPSv2) predictions. These results are beneficial for understanding the interannual predictability of the East Asian winter climate. [ABSTRACT FROM AUTHOR]

In the context of global warming, determining to what extent natural variability and external forcing have an impact on climate change is crucial for formulating mitigation policies and adaptation plans. We quantifiably and effectively separate unnatural trends from the global land surface air temperature (SAT) changes during 1951–2015 by calculating the long‐term correlation exponent through detrended fluctuation analysis and applying mainly probability statistics methods. We provide effective discriminated evidence for whether the observed SAT change exceeds its natural internal variability. Furthermore, we search the range of SAT changes caused by unnatural trends, and identify their corresponding minimum contributions to warming relative trends in different regions. The unnatural warming of the mid‐ to high latitude inland areas of Eurasia and North America is basically high, and the warming responses to unnatural forcing are most intense in these areas. Compared to earlier detection, we find the minimum unnatural trend contributes more than 80% to the observed SAT change in North America, northern Greenland, eastern Africa, and the mid‐ to high latitudes of Eurasia. In addition, the temporal evolutions of unnatural trends in key areas are determined. In North Africa, Western Australia, the United States and Mexico, the unnatural impact became significant at the earliest. Meanwhile, the overall unnatural trend in North Africa is the most significant, followed by western Brazil, and grows most rapidly over time in the two key areas. [ABSTRACT FROM AUTHOR]