ABSTRACT:The anthropogenic (ANT) influence on the intensity of temperature extremes in China is detected over the period 1958-2012 using the newest homogenized daily observation data set and multi-model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We applied an optimal fingerprinting method to compare spatial-temporal changes in the intensity of temperature extremes, including annual maxima of daily maximum and daily minimum temperatures (warmest day and night, TXx and TNx) and annual minima of daily maximum and daily minimum temperatures (coldest day and night, TXn and TNn). For China as a whole, the results show that the ANT influence can be robustly detected in all four extreme indices. The ANT signal is also clearly separable from the response to natural-only (NAT) forcing in the two-signal analyses. The NAT signal was detectable for the warmest night TNx but not for other indices. At smaller regional scales for Eastern and Western China, the ANT signals were also clearly detected in the changes of temperature extremes. With the use of more observational data and multi-model simulations, this study updates a previous work and confirms that the human influence can be robustly detected in the changes of extreme temperature intensity in China.

Anthropogenic influence on the frequencies of warm days, cold days, warm nights, and cold nights are detected in the observations of Chinese temperature data covering 1958–2002. We used an optimal fingerprinting method to compare these temperature indices computed from a newly homogenized observational data set with those from simulations conducted with multiple climate models that participated in the Coupled Model Intercomparison Project Phase 5. We found the clear anthropogenic signals in the observational records of frequency changes in warm and cold days and nights. We also found that the models appear to be doing a better job in simulating the observed frequencies of daytime extremes than nighttime extremes. The model‐simulated variability appears to be consistent with that of the observations, providing confidence on the detection results. Additionally, the anthropogenic signal can be clearly detected at subnational scales, with detectable human influence found in Eastern and Western China separately.

The anthropogenic-induced global warming and local urbanization exert important influences on temperature extremes in Eastern China. Here we use China station observations and climate models to investigate their effects on the warm and cold days and nights simultaneously. We quantified the contribution from these two factors based on an optimal fingerprinting method. We find that both anthropogenic and urbanization signals can be clearly detected and separated from each other in the nighttime temperature extremes. The effect of urbanization may explain as much as one third of the observed changes in cold and warm nights while the urbanization signal is weak in the daytime extremes. The results are robust against sampling uncertainty in the estimate of urbanization signal, but uncertainty due to collinearity between the urbanization signal and global warming is difficult to assess. Plain Language SummaryUnderstanding the causes behind changes in temperature extremes is of significance for reliably projecting future climate change. Previous studies have separately shown that global warming and the urbanization effects are the two important drivers for the increase of warm extremes and decrease of cold extremes in Eastern China. In this study, we consider these two factors simultaneously using an optimal fingerprinting method. We find that climate models can well reproduce the observed changes in extreme temperature when the urbanization effects are included. Both global warming and urbanization have contributed to changes in nighttime temperature extremes, with global warming contributing slightly more. On the other hand, changes in daytime temperature extremes seem to be predominantly due to global warming.

The influences of tropospheric blocking high on the stratospheric sudden warming (SSW) and the SSW-induced feedback on the lower atmosphere are analyzed with NCEP (National Center for Environmental Prediction) 2 reanalysis data. Daily mean data from 1979 to 2010 are used to perform statistical and dynamical analyses. According to different distribution features of polar vortex, which can be ascribed to different activities of blocking highs, we have obtained two warming patterns in vortex splitting and displacement patterns. For vortex splitting events, in the Eurasian-North American (ENA) paratype, with disturbances of Atlantic and Aleutian blocking highs, polar vortex is split into two parts that locate at Eurasian and North American continents respectively, while in the Atlantic-East Asian (AEA) paratype, two low-pressure centers derived from the split vortex are situated in the Atlantic and East Asian regions, and two blocking systems occurring in the Urals and North American areas precede these splitting processes. For vortex displacement events, in the Aleutian-Intrusion (AI) paratype, the polar vortex is displaced to the west European and Atlantic areas by the intrusive Aleutian high and this pattern always corresponds to the blocking events occurring in the Pacific basin only. Similarly, the vortex is pushed to the west Eurasian continent by the intrusive North American high-pressure system in the North American-Intrusion (NAI) paratype, which is closely related to the blocking over these areas. The second subject of the research is that whether the anomalous stratospheric signals can be propagated to the lower atmosphere, which is depended on the intensity, duration and position of the disturbed vortex. According to our case studies, geopotential height anomalies can be propagated to the troposphere in strong SSW years, taking about 10-15 d for the decrease from 10 to 500 hPa, leading to apparent variations in the geopotential height and temperature fields. stratospheric sudden warming, blocking high, polar vortex, stratospheric feedback, tropospheric anomalies Citation:Lu C H, Ding Y H. Observational responses of stratospheric sudden warming to blocking highs and its feedbacks on the troposphere.

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