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Cold and warm temperature extremes predominantly occurring in winter gained much more attention than mean temperatures. On the basis of daily maximum and minimum surface air temperature records at 303 meteorological stations in China, the spatial and temporal distributions of five indices for winter (DJF: December, subsequent January and February) temperature extremes are analysed during 1961-2003. For the majority of stations, the frequency of cold days/nights decreases by − 1.33/− 2.98 and warm days/nights increases by 0.92/2.35 d/decade, respectively. Cold days/nights are significantly negatively correlated with the Arctic Oscillation (AO) index, while warm days/nights are positively correlated with the AO. The diurnal temperature range (DTR) has a declining trend with rate of − 0.25 °C/decade and positive correlation with the AO index. Compared with other regions in China, stations in the northern China have larger trend magnitudes and stronger correlations with the AO index, and the AO can explain more than 50% of winter temperature extreme change in China. Compared with the annual basis, the winter temperature extremes have larger trend magnitudes, which reflect the rapid warming. During strongly positive AO index years, enhanced contrast tropospheric temperature (defined as the average of air temperature vertically integrated between 200 hPa and 1000 hPa based on the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis) between the north of China and the southern China weakens the East Asian winter monsoon which in turn reduces cold outbreaks in the northern and eastern China. The composites of large-scale atmospheric circulation are consistent with the asymmetrical changes of the geopotential height, zonal and meridional winds at high and mid latitudes at troposphere. Meanwhile, the linkage between the AO and solar activity also modulates the winter temperature extremes, while the mechanism needs to be investigated. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Northwest China forms the main part of the arid and semiarid areas in China, and even includes some extremely arid areas. This zone of interaction is affected by the westerlies and monsoons making it sensitive to global climate change. Drought is the main type of natural disaster affecting northwest China. Global warming has caused a gradual strengthening of the frequency and intensity of hot extremes, when dry conditions and heatwaves occur simultaneously or successively; as a result, that socioeconomic risks can increase considerably. The present study examined changes in concurrent droughts and hot extremes in northwest China during 1961–2017 based on data from 119 meteorological stations. The result shows that the frequency of concurrent droughts and hot extremes exhibited an increasing trend over most parts of northwest China, while a negative trend occurred in western Xinjiang and at some sites in Qinghai. Concurrent droughts and hot extremes appeared more often in May in western Xinjiang, and in summer in other parts of northwest China. Overall, the trends of such concurrent events, regardless of different definitions, increased from 1961–2017 over northwest China. In particular, from 1981–2017, the trend rose more significantly than in other decades, and reached an abrupt point of change in 1996. Although the trend changed from a positive significant signal to a negative one from 2001–2017, the trend grew 2–3 times from 1997–2017. Changes in large‐scale atmospheric circulation show that an anticyclonic circulation strengthened, increasing in geopotential height over the midhigh latitudes of Eurasia and was centred on Mongolia and Lake Baikal. This enhanced relative humidity in western Xinjiang and eastern Qinghai, and weakened it elsewhere from 1997–2017. These changes have contributed to the changes in the spatial distribution and trends in concurrent droughts and hot extremes in northwest China. Variations in the number of concurrent droughts and hot extremes for the period of 1961–2017 in northwest China. Red line for DH85, blue line for DH90. DH85 and DH90 indicate simultaneous a month 3‐month SPEI < −1.0 and hot extremes during which the daily maximum temperature exceeded the 85th and 90th percentiles for at least three consecutive days, respectively. [ABSTRACT FROM AUTHOR]

As semi‐enclosed and shallow seas, the Bohai and Yellow Seas (hereafter, BYS) marine ecosystems are more easily affected by natural and anthropogenic climate changes than those in the open oceans. An accurate assessment of sea surface temperature (SST) change is crucial for the near‐shore water environment. In this work, new high‐quality monthly mean SST time series from 11 in situ coastal hydrological stations at BYS for the period of 1960–2012 have been generated. Monthly mean SST time series were initially subjected to penalized maximal t (PMT) test, using homogeneous monthly mean surface air temperature (SAT) series as references. Homogenized monthly mean SST series were obtained by adjusting all significant change points which have been supported by historic metadata. Our study shows that there are 29 significant change points in these 11 SST series. The majority of them are caused by instrument changes and station relocations—both account for about 51.7 and 31%, respectively. Then, homogeneous SST series are used to assess the long‐term trends. As the regional average, the annual mean homogeneous SST series shows a rapid warming trend, with the rate of 0.21°C/decade. Compared to the homogeneous SST series, the original SST series underestimate the long‐term trend (only 0.13°C/decade), indicating the artificial change points usually result in a warm‐bias in the early period measurements. Seasonally, the most significant warming occurs in boreal winter during the period analysed. The relationships of the significant warming in boreal winter and atmospheric circulation modes have also been investigated. Results reflect the remarkable and direct influence of the East Asian Trough (EAT) on SST along the coastal BYS. [ABSTRACT FROM AUTHOR]