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The two leading modes of winter surface air temperature (SAT) over China during 1961–2017 are a spatially consistent pattern and a north-south dipole pattern. Based on the two leading modes, the characteristics of the extreme cold and warm days in the two patterns, defined by the standard deviation larger than 1.28 or smaller than −1.28 in the time series of the two leading modes, are analyzed. With the increase of winter SAT during 1961–2017, the number of spatially consistent extreme cold days decreased and their occurrence was restricted to late December to early January, whereas the number of spatially consistent extreme warm days increased significantly in January and February. Global warming is associated with an increase in the spatially consistent extreme warm days and a decrease in spatially consistent extreme cold days, but has little relation to the sum of extreme cold and warm days of either the spatially consistent or north-south dipole pattern. The Siberian High (SH) is the main factor controlling the sum of spatially consistent extreme warm and cold days. The strong (weak) SH before (after) the 1990s corresponds to an increase (decrease) in the sum of the spatially consistent extreme warm and cold days. The occurrences of extreme south-cold-north-warm and extreme south-warm-north-cold days are related to the north-south difference of the SH. When the center of the SH is in mid-high latitudes, the extreme south-warm-north-cold (south-cold-north-warm) days occur more (less) often. During the winters of 1961–2017, the total number of extreme cold and warm days of the north-south dipole pattern changes negligibly. The North Atlantic meridional overturning circulation (AMOC) may be the main factor affecting the sum of the extreme cold and warm days of the two types of SAT pattern in China.

Under recent Arctic warming, boreal winters have witnessed severe cold surges over both Eurasia and North America, bringing about serious social and economic impacts. Here, we investigated the changes in daily surface air temperature (SAT) variability during the rapid Arctic warming period of 1988/89–2015/16, and found the daily SAT variance, mainly contributed by the sub-seasonal component, shows an increasing and decreasing trend over eastern Eurasia and North America, respectively. Increasing cold extremes (defined as days with daily SAT anomalies below 1.5 standard deviations) dominated the increase of the daily SAT variability over eastern Eurasia, while decreasing cold extremes dominated the decrease of the daily SAT variability over North America. The circulation regime of cold extremes over eastern Eurasia (North America) is characterized by an enhanced high-pressure ridge over the Urals (Alaska) and surface Siberian (Canadian) high. The data analyses and model simulations show the recent strengthening of the high-pressure ridge over the Urals was associated with warming of the Barents-Kara seas in the Arctic region, while the high-pressure ridge over Alaska was influenced by the offset effect of Arctic warming over the East Siberian-Chukchi seas and the Pacific decadal oscillation (PDO)-like sea surface temperature (SST) anomalies over the North Pacific. The transition of the PDO-like SST anomalies from a positive to negative phase cancelled the impact of Arctic warming, reduced the occurrence of extreme cold days, and possibly resulted in the decreasing trend of daily SAT variability in North America. The multi-ensemble simulations of climate models confirmed the regional Arctic warming as the driver of the increasing SAT variance over eastern Eurasia and North America and the overwhelming effect of SST forcing on the decreasing SAT variance over North America. Therefore, the regional response of winter cold extremes at midlatitudes to the Arctic warming could be different due to the distinct impact of decadal SST anomalies.

Despite ongoing climate change and warming, extreme cold events still negatively affect human society. Since cold air incursions are related to specific circulation patterns, the main aims of this study are (1) to validate how well current EURO-CORDEX regional climate models (RCMs) reproduce these synoptic links and (2) to assess possible future changes in atmospheric circulation conducive to cold events. Using anomalies of daily minimum temperature, we define cold days (CDs) in central Europe and analyse their characteristics over the historical (1979−2020) and future (2070−2099) periods. We classify wintertime atmospheric circulation by applying a novel technique based on Sammon mapping to the state-of-the-art ERA5 reanalysis output. We discover that circulation types (CT) conducive to CDs are characterised by easterly advection and/or clear-sky anticyclonic conditions. While the RCM ensemble generally reproduces these synoptic links relatively well, we observe biases in the occurrence of CDs in individual simulations. These biases can be attributed to inadequately reproduced frequencies of CTs conducive to CDs (primarily propagating from driving data), as well as to deviations in the conduciveness within these CTs (primarily originating in the RCMs). Interestingly, two competing trends are identified for the end of the twenty-first century: (1) most RCMs project an increased frequency of CTs conducive to CDs, suggesting more frequent CDs, while (2) the same CTs are projected to warm faster compared to their counterparts, suggesting weaker CDs. The interplay between these opposing trends contributes to the overall uncertainty surrounding the recurrence and severity of future winter extremes in central Europe.

Marginal seas are fundamental to humans for their importance in mariculture resources and commerce. Based on the NOAA 0.25 degree daily Optimum Interpolation (OI) sea surface temperature (SST) data set, spatiotemporal changes in mean and extreme SST in the East China Seas (ECSs) were examined for from 1982 to 2017. As a regional average, the annual mean SST has notably increased at a rate of 0.21 ± 0.08 °C per decade. The warming SST during 1982–2017 is probably related to the influence from a recent strengthening and westward extension of the WPSH. There are also notable warming trends in annual minimum and maximum SST. Spatially, the rapid warming of annual mean SSTs are located in the vicinity of the Yangtze Estuary, exceeding 0.2 °C per decade and part of the ECS-Kuroshio. This pattern may be largely affected by the spatial changes of minimum SST. Rapid warming of maximum SST can be found across the region, from the northern East China Sea (ECS) to the Bohai Sea. Since 1982, extreme hot days (EHDs) have undergone an obvious increasing trend, at a rate of 15.2 days per decade. Conversely, extreme cold days (ECDs) have been decreasing. Notably, the largest increase of EHDs appears in the western ECS and the Bohai Sea, which both have rich marine ecosystems. The trend of EHDs has a significant relationship to mean SST, suggesting that there will be a further increase in EHDs under continued warming in the ECSs. These findings emphasize the importance and urgency of strategies which should be planned for the adaptation and mitigation of specific types of extreme hot events in this region.

Based on the NECP/NCAR reanalysis dataset, the associations between the number of cold days (NCD) over East Asia (100–150° E, 25–55° N) and Arctic Oscillation (AO)/Arctic warming during 1956–2015 are explored. The results show the NCD was closely associated with AO during 1956–1990 and Arctic warming during 1991–2015. It reveals NCD over East Asia showed a downward trend and a significantly negative correlation with AO in the previous stage, while it presented an upward trend and notably positive association with Arctic warming in the later period. Meanwhile the increase in the earlier-stage AO will often be accompanied by the weakness of the Siberian high (SH), the Ural Mountains Blocking high (UBH), and the East Asian trough (EAT), and a “positive–negative–positive” wave band exist in the upper troposphere, which is linked with weakened northerly wind over East Asia. All these anomalies are unfavorable for the southward transportation of cold air, eventually leading to the decrease in NCD over East Asia. Additionally, when the near-surface temperature over the Arctic rises in the later period, on the one hand, SH reinforces and further results in more NCD over East Asia; on the other hand, the 1000–500 hPa thickness field displays a “north positive–south negative” pattern, which is conducive to the deceleration of the westerlies at mid-latitudes over Eurasia, and further bring about the enhancement of EAT and UBH, favoring the southward intrusion of cold air, finally, more NCD are generated.

Atmospheric blocking is one of the most impactful weather patterns in midlatitude regions, causing floods, droughts and unusually high or low temperatures. This study investigates the relationship between extremely cold days over Japan and its surroundings and North Pacific blocking in the European Centre for Medium‐range Weather Forecasts (ECMWF) re‐analysis (ERA‐40), phase 5 of the Coupled Model Intercomparison Project (CMIP5) for historical weather and the representative concentration pathway 8.5 (RCP8.5) experiments based on nine climate model datasets in the boreal winter season. Under the climate change conditions based on the RCP8.5 future scenario, extreme cold days (i.e. the first percentile of cold days) over Japan and its surroundings will become weaker but occur more widely when blocking is generated over the northwestern Sea of Okhotsk and its surroundings, because the blocking frequency over this area will decrease and the intensity will weaken.

A sequence of extreme cold events occurred across Eurasia and North America during winter 2020/21. Here, we explore the causes and associated mechanisms for the extremely cold temperatures using both observations and large-ensemble simulations. Experiments were conducted with observed ocean surface boundary conditions prescribed globally, and regionally to discern the specific influence of Arctic, tropical Pacific, and North Pacific drivers. Increased likelihood of daily cold extremes in mid-December to mid-January are found in Eurasian midlatitudes in response to reduced Arctic sea ice. Tropical sea surface temperature anomalies, more specifically the La Niña pattern, increased probability of extreme cold over high-latitude Eurasia in early January to early February. Both reduced Arctic sea ice and La Niña increased the probability of daily cold extremes over western North America in late January to late February. We conclude that a combination of reduced Arctic sea ice, La Niña, and a sudden stratospheric warming in January 2021 were factors in the February 2021 extreme cold wave that caused huge societal disruptions in Texas and the southern Great Plains. Although the magnitude of the simulated cold extremes are relatively small when compared with observed anomalies, the Arctic and Pacific Ocean surface conditions in winter 2020/21 increased the probability of cold days as cold or colder than observed by approximately 17%–43%.

Pakistan is one of the most vulnerable countries of the world to temperature extremes due to its predominant arid climate and geographic location in the fast temperature rising zone. Spatial distribution of the trends in annual and seasonal temperatures and temperature extremes over Pakistan has been assessed in this study. The gauge-based gridded daily temperature data of Berkeley Earth Surface Temperature (BEST) having a spatial resolution of 1° × 1° was used for the assessment of trends over the period 1960–2013 using modified Mann-Kendall test (MMK), which can discriminate the multi-decadal oscillatory variations from secular trends. The results show an increase in the annual average of daily maximum and minimum temperatures in 92 and 99% area of Pakistan respectively at 95% level of confidence. The annual temperature is increasing faster in southern high-temperature region compared to other parts of the country. The minimum temperature is rising faster (0.17–0.37 °C/decade) compared to maximum temperature (0.17–0.29 °C/decade) and therefore declination of diurnal temperature range (DTR) (− 0.15 to − 0.08 °C/decade) in some regions. The annual numbers of both hot and cold days are increasing in whole Pakistan except in the northern sub-Himalayan region. Heat waves are on the rise, especially in the hot Sindh plains and the Southern coastal region, while the cold waves are becoming lesser in the northern cold region. Obtained results contradict with the findings of previous studies on temperature trends, which indicate the need for reassessment of climatic trends in Pakistan using the MMK test to understand the anthropogenic impacts of climate change.

Atmospheric reanalyses are a valuable climate-related resource where in situ data are sparse. However, few studies have investigated the skill of reanalyses to represent extreme climate indices over the North American Arctic, where changes have been rapid and indigenous responses to change are critical. This study investigates temperature and precipitation extremes as defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) over a 17-yr period (2000–16) for regional and global reanalyses, namely the Arctic System Reanalysis, version 2 (ASRv2); North American Regional Reanalysis (NARR); European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis; Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2); and Global Meteorological Forcing Dataset for Land Surface Modeling (GMFD). Results indicate that the best performances are demonstrated by ASRv2 and ERA5. Relative to observations, reanalyses show the weakest performance over far northern basins (e.g., the Arctic and Hudson basins) where observing networks are less dense. Observations and reanalyses show consistent warming with decreased frequency and intensity of cold extremes. Cold days, cold nights, frost days, and ice days have decreased dramatically over the last two decades. Warming can be linked to a simultaneous increase in daily precipitation intensity over several basins in the domain. Moreover, the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) distinctly influence extreme climate indices. Thus, these findings detail the complexity of how the climate of the Arctic is changing, not just in an average sense, but in extreme events that have significant impacts on people and places.

Extreme climate events can cause large risks to ecosystems and human society in a short period. Investigating the changing trends of such events is essential for regional climate risk management. However, there is limited information on the regional assessment of the history and future trends of extreme climate events in Xinjiang, China. This study investigated the historical changes and projected trends of extreme climate events in Xinjiang based on observational data and Coupled Model Intercomparison Project phase 6 (CMIP6) model simulations. The results showed that the bias correction effectively reduced the bias of the CMIP6 model to the extreme climate indices simulation. During the period 1961–2014, the extreme indices representing warmth showed robust growth, while the extreme indices representing cold showed a robust decline. The intensity and frequency indices of extreme precipitation continued to increase, while consecutive dry days (CDDs) shortened and consecutive wet days (CWDs) lengthened. The changing trend of the extreme temperature indices had strong spatial consistency, while the changing trend of the extreme precipitation indices had obvious spatial heterogeneity. Based on the CMIP6 model simulations, the extreme climate indices in the twenty-first century were projected to continue the changing trend of the historical period (1961–2014). Compared with north Xinjiang (NXJ) and south Xinjiang (SXJ), the cold spell duration index (CSDI), cold nights (TN10p), cold days (TX10p), and extreme precipitation events in the Tianshan Mountains (TSM) were projected to experience stronger changes in the twenty-first century. The response of extreme temperature and extreme precipitation indices to global warming was approximately linear. Compared with SSP585, most extreme climate indices under the SSP245 scenario changed slightly in response to global warming. The superposition of the increase (decrease) in extreme warm (cold) events and the increase in extreme precipitation events will exacerbate the threat of extreme climate events to the agricultural and ecological security of the Xinjiang oasis, especially in the TSM. Given the limited water vapor sources and precipitation and the high rate of evapotranspiration, it is projected that the current situation of water shortages in Xinjiang will not be fundamentally changed.