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The atmospheric activity on Kalimantan Island (KI) is important for regulating regional weather and climate. This study investigates the effect of autumn soil moisture over KI on following winter precipitation over southern China (SC) during 1968–2014. The results show that the autumn soil moisture over the KI has a significant negative correlation with subsequent winter precipitation over SC. The correlation remains statistically significant when using partial correlation to filter out the concurrent influences of El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) signals. The soil moisture anomalies over KI, which initiate in the autumn and persist into the winter, lead to changes in local thermal conditions and atmospheric temperature. Negative soil moisture anomalies over KI will result in positive heating anomalies of the atmosphere above the land surface. This atmospheric heating causes ascending motion, which creates a semi‐closed vertical circulation from KI to the tropical northwest Pacific. This vertical circulation would strengthen the northwest Pacific anticyclone and weaken the East Asian winter monsoon (EAWM). Consequently, southwesterly water vapour flux prevails in the SC as well as the South China Sea (SCS), facilitating the transportation of more water vapour into the SC. Simultaneously, water vapour convergence in the SC. Collectively, these contribute to an addition of precipitation over SC. [ABSTRACT FROM AUTHOR]

The North China Plain, a crucial region for winter wheat cultivation, exhibits yield deeply affected by the variability of winter precipitation. This study examines the interdecadal variation in the relationship between the North Pacific Oscillation (NPO) and winter precipitation in the North China Plain (WPNC). Utilizing the East Asian winter monsoon (EAWM) as an intermediary, we have observed an interdecadal variation in the relationship between WPNC and NPO after the late‐1990s. Before 1994, the relationship between NPO and EAWM/WPNC both exhibited a significant positive correlation, while after 1998, their correlation decreased and became insignificant. This interdecadal variation can be attributed to the eastward shift of the winter NPO's location after the late‐1990s. Our investigation found that the eastward shift of the NPO's location is closely linked to the phase transition of the Atlantic Multidecadal Oscillation (AMO) phase after the late‐1990s. The warm sea surface temperatures (SST) over the North Atlantic cause ascending motion, and the outflows induce a compensatory anticyclonic circulation over the North Pacific. The easterlies anomaly on the south side of the anticyclone weakens climatological westerlies, increasing SST and upper‐level air temperatures in the North Pacific through the wind–evaporation–SST–longwave radiation effect. The resulting warmer air strengthens the atmospheric temperature gradient, enhancing the vertical integration of baroclinic energy conversion and shifting the NPO eastward, reducing its correlation with WPNC. [ABSTRACT FROM AUTHOR]

By observing well‐known sea surface temperature (SST) indices and outputs from Climate Forecast System version 2 (CFSv2) hindcasts and predictions, in this study, we developed a hybrid statistical downscaling prediction model (HSDPM) based on a timescale decomposition approach, which effectively improved the forecasting ability of summer (June–August) precipitation over Hainan Island (HNSP) in China; this precipitation presented multiple obvious timescale variabilities. We found that the interannual variability of the HNSP is closely related to the observed North Atlantic tripole SST anomalies in the preceding winter and the summer sea level pressure over the South China Sea by CFSv2 predicted in March. On the other hand, the interdecadal variability in the HNSP is linked to the prewinter Pacific Interdecadal Oscillation (PDO) according to the observations, the CFSv2 predictions of the summer surface air temperature over the tropical central‐east Pacific. On this basis, both the interannual and interdecadal components of the HNSP are effectively predicted using the corresponding predictors via multiple regression; thus, the HSDPM is ultimately established by combining the above two components. Compared with the original CFSv2 model, the HSDPM model achieves a considerable improvement in performance in predicting the HNSP. Specifically, the temporal correlation coefficient, ratio of root‐mean‐square error and anomaly sign consistency rate between the observed and HSDPM‐predicted HNSPs are 0.70, 17.4% and 80.5%, respectively, which are significantly greater than the above three forecasting index values of 0.23, 38.3% and 48.8%, respectively, obtained from the original CFSv2 predictions. The application of the HSDPM may be beneficial for drought and flood prevention and mitigation in Hainan Island. [ABSTRACT FROM AUTHOR]

The seasonal cycle (SC) of surface air temperature is a substantial element in climatology. Some basic and important topics in climate change studies are based on accurate and reliable estimation of SCs, such as percentile‐based indices of extremes and probability density function (PDF) changes of daily temperatures. For both of them, most studies characterized SCs using averages of multi‐days windows, which is not smooth and accurate enough representing the extreme thresholds and climatological normal of SCs. It is necessary to construct smooth and reasonable SCs for more accurate estimation of temperature changes on extreme thresholds and PDFs. In this study, we propose a flexible method based on generalized additive models for location scale and shape and penalized b‐spline smoothing technique with respective distributions to construct smooth SCs and SC for extreme temperatures (SCETs). The accuracy of the constructed smooth SCETs is good with the estimation biases of percentiles tending to be zero. The constructed smooth SCET also exhibits good stability over time, such that the magnitude changes of temperatures on each calendar day are close to climatic changes of mean temperature when the concerned period shifts. Based on the constructed smooth SCs, climatic changes by seasons and PDFs between two periods, 1961–1990 and 1991–2020, are examined over China. The increase of thresholds for hot extremes in spring during the recent period is prominent, while the increase of thresholds for daytime cold extremes in summer over a part of central to southern China is also notable. The smooth SCs and SCETs based on our flexible statistical modelling framework can characterize daily extreme temperatures reasonably and accurately, and should be expected to have more applications for a better understanding of climate changes related to distributions and seasonal cycles. [ABSTRACT FROM AUTHOR]

Under global warming, the summer surface air temperature (SAT) change signal in the northern mid‐latitudes is generally the most significant, while the SAT change in North China (NC) shows distinct local characteristics. Using simulations from the Coupled Model Intercomparison Project Phase 6 and observation from Berkeley Earth Surface Temperature, this study reveals an unusually weak signal of summer SAT change in NC since the 1960s. This uniquely weak signal can be attributed to the small net contribution of external forcings, mainly from anthropogenic greenhouse gases (GHG) and aerosols (AA). Compared to other land regions in the same latitudinal band, the GHG‐induced warming was weaker and AA‐induced cooling was stronger in NC, resulting in the weakest SAT change signal and thus the lowest signal‐to‐noise ratio. This weaker GHG‐induced warming plays a more important role in the SAT change difference between NC and other land regions in the same latitudinal zone. Under different emission scenarios in the future, the signal‐to‐noise ratio in NC will become as large as those in the other land regions in the same latitudinal band and the northern hemisphere, which is partly due to the smaller relative differences in the SAT change signal between NC and the other two regions. The projections of SAT change indicate that climate change in NC will probably become more violent and vulnerable. [ABSTRACT FROM AUTHOR]

Based on the daily average temperature data of 2374 stations in China from 1993 to 2022 and the monthly average temperature data of European Centre for Medium‐Range Weather Forecasts (ECMWF) System5 in winter, this article analyses the intraseasonal variations of winter surface air temperature (SAT) over China by using seasonal empirical orthogonal function decomposition (S‐EOF) and compare the prediction skill differences of the first three dominant modes in ECMWF System5. The first mode (S‐EOF1) is characterized by out‐of‐phase changes in SAT anomalies (SATA) between December and January. Both the Siberian high (SH) and the central Pacific El Niño‐Southern Oscillation (CP ENSO) can impact S‐EOF1. The second mode (S‐EOF2) is characterized by consistency in warm anomalies over the Northeast and Qinghai‐Tibet Plateau's variation, while the other areas are characterized by the out‐of‐phase change in SATA. S‐EOF2 is closely related to Arctic oscillation (AO). The third mode is characterized by alternating changes over 3 months in winter, which is related to the Pacific meridional mode (PMM) and the North Atlantic SST tripole (NAT). Comparing the ECMWF System5 prediction skill for the first three leading modes for the intraseasonal variations in winter SAT, the prediction skill is not high. The model did not predict the extent of warm anomalies and the intraseasonal fluctuation in S‐EOF1, which may be due to the poor prediction skills for the range and intensity of the CP ENSO and the SH. The second mode has the highest prediction skill among the three modes. For the prediction skill of AO is good. The model can capture the intraseasonal reverse SATA between December and January but did not capture the reverse SATAs between January and February. Because the model does not predict obvious PMM and NAT well. [ABSTRACT FROM AUTHOR]

The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across 12 climatic zones based on the ensemble of the five well‐performing high‐resolution downscaled climate models for each zone. There are warming patterns for the mean near‐surface air temperature (Tm), maximum near‐surface air temperature (Tmax), minimum near‐surface air temperature (Tmin) as well as heatwave and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30–0.31 and 0.64–0.67°C·decade−1. The extent of frost event (FE) are projected to decrease at a rate of −1912 and −4442 day·km−2·decade−1 while the extent of heatwave event (HE) increase at a rate of 1116 and 3557 day·km−2·decade−1 under RCP4.5 and RCP8.5 scenarios, respectively. A higher increment in temperatures, a decreasing trend in diurnal temperature range (DTR), frost days and FE are highlighted in the western and northern zones, while these trends are opposite in southern zones. The warming is likely to get faster in the current colder zones (western and northern zones) while heatwave is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming. [ABSTRACT FROM AUTHOR]

In 2021/2022 winter, an intraseasonal surface air temperature (SAT) reversal occurred in China, shifting from regional warm to cold phase in late January 2022. The intraseasonal variations of winter SAT in China are tightly connected with 500 hPa potential height. In particular, the Arctic Oscillation (AO) positive phase is diagnosed to be contributing to the SAT reversal. Under its influence, the intraseasonal build‐up and collapse of blockings over Urals Mountain led to the cold surges in February 2022. Seasonal prediction systems (SPSs) such as NCEP_CFSv2, EC_SYSTEM5 and BCC_CSM1.1 are assessed to have poor predictability in this SAT reversal and similar historical events, owing to not only the poor skills in winter SAT predictions but also the integral inertia in SPSs. Prediction skill only increases as the forecasting time approaches, owing to initial values. Besides, the SPSs can simulate the physical process of the influence on SAT from circulation. The poor predictability is attributed to the poor prediction skills in mid–high latitude circulation pattern and potential height over China. [ABSTRACT FROM AUTHOR]

This study analyses the spring climate anomalies under different configurations of western North Pacific anticyclone (WNPA) and Siberian high (SH). Compared to the WNPA alone with increased precipitation over southern China, the out‐of‐phase configuration (strong‐WNPA–weak‐SH) can enhance the WNPA‐related southwesterlies over eastern China, favouring increased precipitation with larger amplitude over southern China and southern Northeast China. Differently, the in‐phase configuration (strong‐WNPA–strong‐SH) decreases and confines WNPA‐related southwesterlies over southern China, causing decreased precipitation over eastern Southwest China; additionally, the WNPA‐related southwesterlies converge with SH‐related northwesterlies over the lower reaches of the Yangtze River, causing increased precipitation there. For surface air temperature, the WNPA alone induces warming over western Southwest China through changing heat flux, while the SH alone induces cooling over northern China through changing temperature advection, and over Northwest and southern China through changing heat flux. In the out‐of‐phase configuration, warming expands into Northern China due to the cooperation of weakening SH. In the in‐phase configuration, SH‐related cooling mainly occurs to the north of the Yangtze River because of the obstruction of WNPA. Further analysis indicates the eastern Pacific (EP) and central Pacific (CP) El Niño‐Southern Oscillation (ENSO), European low and Ural high contribute to the different configurations of WNPA and SH. The EP ENSO‐related zonal overturning circulation intensifies the WNPA and European low‐induced warm advection weakens the SH, resulting in the out‐of‐phase configuration. The CP ENSO‐related zonal overturning circulation intensifies the WNPA with a northeast–southwest tilt and Ural high‐induced cold advection intensifies SH, resulting in the in‐phase configuration. [ABSTRACT FROM AUTHOR]

In this study, we focus on the features and predictability of winter 2‐m air temperature (t2m) over China under different intensities of La Niña events. The seasonal and intraseasonal prediction skills of winter t2m over China are examined by four state‐of‐art seasonal climate forecast models. The results show that the China winter t2m anomaly is sensitive to the intensity of La Niña. Strong and moderate (S/M) La Niña events are often accompanied by cold winter over China, while a positive anomaly of mean t2m over China frequently occurs in the weak La Niña events. The intensity difference of the East Asian winter monsoon (EAWM) results in this discrepancy. All models have a slightly higher anomaly correlation coefficient (ACC) for the S/M La Niña than that for the weak La Niña in leading 1 month (LT1). Both individual models and MME exhibit higher skills of anomaly sign consistency rate (ASCR) for the S/M La Niña, which implies that models predict t2m anomaly over China more accurately in the S/M La Niña events. Furthermore, the winter t2m over China presents larger intraseasonal variability for the S/M La Niña than that for the weak La Niña. Models can capture the t2m anomaly over China more accurately when the temperature varies gently with small intraseasonal variability during winter for the S/M La Niña. [ABSTRACT FROM AUTHOR]

This paper describes the construction of a 0.25° × 0.25° daily soil temperature (TS) data set at six soil depths (i.e., 0, 5, 10, 15, 20, and 40 cm) based on a homogenized TS at more than 2,000 meteorological stations across mainland of China for 1960–2017. First, at each station, the observed TS is split into a daily climatology of 1981–2010 and a daily anomaly for 1960–2017. Then, they are respectively interpolated to 0.25° × 0.25° horizontal resolution by using the thin‐plain spline and the angular distance weight interpolation methods. Finally, a gridded multilayer TS data set is constructed from the sum of the above two gridded products. Latitude, longitude, and high‐resolution digital elevation models are explicitly incorporated into the interpolation processes. Selectivity tests indicate that the optimal interpolation distance for the TS anomaly field is 500 km, where the gridded data set may have maximum coverage of the entire Chinese mainland. The results show that the gridded TS climatology is slightly lower than the station observations. The differences between gridded and the station‐based TS varies ±3°C, with relatively large in SW and TIBET. For the gridded anomaly fields, the cross‐validation shows that the mean absolute errors between gridded and station‐based TS are generally less than 0.6°C in the YZ, SW, and SC, but they are above 1.0°C in the NW and TIBET due to the sparse station distribution and large topographic relief. From 1961 to 2016, the seasonal variability of the gridded TS is generally consistent with that of the surface air temperature. The gridded TS over the majority of land displays significantly positive trends in both summer and winter (p > 95%), indicating an overall warming land surface in China. The long‐term gridded TS data not only preserves the spatial features represented in the station observations, but also provides a spatio‐temporal continuous long‐term product of mainland China. Thus, it may be used in future studies, for example, evaluation of land surface model simulations, validation of satellite retrievals, land‐atmosphere interactions, and climate change. [ABSTRACT FROM AUTHOR]

China's surface air temperature is increasing due to global warming, so it is interesting that how low temperatures would be changed during the growth period of winter wheat in future. We focused on the low temperatures of winter wheat from 2021 to 2050, using temperatures under the high emission scenario Representative Concentration Pathway 8.5 (RCP8.5) projected by the RegCM4.4 regional climate model. The results showed that the annual mean temperature was projected to increase by 0.42°C⋅decade−1 in the northern and by 0.35°C⋅decade−1 in the southern winter wheat region. Furthermore, the temperature was expected to increase rapidly in spring, which could advance the dates of flowering and the start of the grain‐filling period. Using the genetic parameters determined by the calibration and validation of WOFOST and bias‐corrected projected meteorological data, simulations of winter wheat growth were performed over the winter wheat region for 2021–2050. The simulated number of days to the flowering period of winter wheat for 2041–2050 was on average 6.5 days less than in 2021–2030, due to the spring warming. Because of the earlier start of the growing season, winter wheat could face negative effects by being subjected to low temperatures. Indeed, the number of low‐temperature days was projected to increase by 110% from 2041 to 2050 compared to 2021–2030, and the number of killing degree days (KDDs) is projected to increase by 120% at the same time. If the number of days to flowering did not change, the number of low‐temperature days and KDDs only changed slightly, showing that the negative influence of low temperature was mainly caused by the advancement of the flowering date. The effect of low temperature on growth was underestimated when the response of winter wheat growth to global warming was not considered. [ABSTRACT FROM AUTHOR]

Based on the long‐range correlation (LRC) of daily air temperature records in China, the simulation performance of 11 Coupled Model Intercomparison Project Phase 6 (CMIP6) models is first evaluated in this study. And then, those CMIP6 models which can reproduce LRC of the well in observed records are selected for multi‐model ensemble mean. The results indicate that multi‐model ensemble mean can significantly reduce model uncertainty in reproducing LRC characteristics of daily air temperature records. Comparing the differences of the scaling exponents of the ensemble mean temperature data between the historical well‐mixed greenhouse gas, historical natural‐only, historical anthropogenic aerosols, and historical experiments, the LRC characteristics of different temperature variables show some difference. It means that the different forcings are critical for the model to reproduce the LRC characteristics of different temperature variables well. Generally, the influence of anthropogenic forcing enhances LRC of daily maximum air temperature in parts of northern China. Therefore, anthropogenic forcing is very important for CMIP6 models to accurately reproduce the strength of LRC for observed daily air maximum temperature in northern China. [ABSTRACT FROM AUTHOR]

Knowledge of the difference between soil and air temperatures (ΔT) is helpful to improve our understanding on the land‐atmosphere thermal interactions and temperature‐dependent soil processes. Based on 272 stations across China, this study investigated the spatiotemporal variations of the annual and seasonal ΔT (difference between soil temperature at a depth of 0.4 m and air temperature) from 1981 to 2014, and quantified the relative contributions of multiple environmental variables (snow cover, precipitation, vegetation, soil moisture, and solar radiation) to ΔT variation for the first time. Air temperature primarily controls soil temperature dynamics, but the asynchronous trends of soil and air temperatures may lead to the complexity of the land‐atmosphere relationship. Almost no apparent trends in ΔT were detected for the entire China (except in summer), but the spatial heterogeneity of trends was evident. Snow cover conditions greatly dominated the ΔT dynamics both annually and seasonally (except in summer). The relative contribution of snow cover duration to ΔT variation was significantly greater than that of mean snow depth for the entire China, but the regional differences in the contributions of the two variables were noticeable at different seasons. The greening of vegetation closely associated with the ΔT variation in annual, autumn and winter, and soil moisture exerted a great influence on summer ΔT, associated with sunshine duration (a proxy for surface solar radiation). The amount of precipitation made a slight impact on ΔT at either seasonal or annual scales. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) is an agricultural base of the country. It suffered a severe drought in 2014. During the drought, the western Pacific subtropical high is stronger than normal and stretches to the west. The warm and moist air in the southwest edge of the high transports northwestwards and thus cannot affect NEC. Over high latitudes, in the regions west and east to NEC, there are large anomalies in geopotential height, which favour meridional exchange and may lead to stronger‐than‐normal cold air intrusions. Because of the lack of warm and moist air supply from the south while the invasion of the cold and dry air from the north, the atmosphere over NEC is finally drier and colder than normal in saturation levels. Based on the physical relation between seasonal precipitation and relative humidity, along with the defined Cq and CT, indicators for measuring the changes in moisture and temperature, the effects of water vapour and air temperature on the drought can be linearly separated, and thus compared. Results reveal that, at middle and high levels, the dryness of the air, which plays a positive role in the drought, can offset the negative effect of the coldness, and the atmosphere over NEC then maintains a lower‐than‐normal relative humidity. In the near‐surface level, the air is drier and warmer than normal, which facilitates the drought. [ABSTRACT FROM AUTHOR]

This study focuses on the trends and the causes of variation in actual evapotranspiration (AET) around the warming hiatus over China by a comprehensive analysis applying various temporal–spatial methods. It is observed that the annual AET showed a different trend around 2000 for China as a whole. By employing segmented regression analysis for detecting warming hiatus points, high temporal inconsistency can be found in eight climatic regions of China. The impacts of meteorological variables on AET were further identified by affecting the intensity and relative change of meteorological factors. AET was highly correlated (p <.01) with solar radiation in the southeast (R = 0.80) and air specific humidity in the northwest areas (R = 0.83). AET changes presented the highest sensitivity to specific humidity in Northwest before 2006 and in north central China after 2003, with sensitivity coefficients of 1.48 and 1.74, respectively. Three variables, including air specific humidity (with an average contribution rate of ~17% in the northwest), short‐wave radiation and air temperature, can be the main factors that lead to the changes in AET. The specific meteorological factors varied from region to region: the changes in AET can be ascribed to the increased wind and short‐wave radiation in north central China and east China, the decreased air temperature in Tibetan Plateau, the increased specific humidity in southeast China during warming hiatus, and so on. After the warming hiatus occurred, the dominant factor of AET trends changed from air specific humidity to short‐wave radiation and other factors. Generally, air specific humidity and air temperature have played leading roles in AET trends during the past 30 years. [ABSTRACT FROM AUTHOR]

The surface air temperature seasonal cycle in China has clearly changed in response to global warming, but its future projection has yet to be studied. Here, we investigate the performance and projection of the temperature seasonal cycle in China in 32 global climate models participating in the Coupled Model Intercomparison Project 6 (CMIP6). The characteristics of the temperature seasonal cycle, as represented by the amplitude and phase, are measured by the Fourier transform. The results show that the CMIP6 models can reasonably capture the observed typical temperature seasonal cycle feature with clear north–south gradients both for amplitude and phase in China. In the twenty‐first century, the models robustly project a delay in the phase across the whole country and a reduction in the amplitude in most of China relative to the reference period. Those changes are similar in the two shared socioeconomic pathway (SSP) scenarios, with overall larger magnitudes in the SSP5‐8.5 scenario than in the SSP2‐4.5 scenario. Projected amplitude changes are mainly linked to surface energy flux changes, especially latent heat flux changes. In response to future global warming, larger increases in the latent heat flux and thus stronger surface evaporative cooling lead to weaker surface warming in summer than in winter, contributing to a decrease in the amplitude of the temperature seasonal cycle in most regions of China. [ABSTRACT FROM AUTHOR]

Investigating the spatial and temporal changes in snow cover over mountain areas is significant for understanding the impact of regional climate variability. In this study, using cloud‐removed snow cover data, which are generated based on Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products, the spatiotemporal changes of snow cover fraction (SCF) and its relationship with temperature and precipitation changes from 2002 to 2020 were examined over Altai Mountains, China. The results demonstrate that the distribution and changes of SCF are highly spatiotemporally heterogeneous. Within a year, the maximum SCF occurs in January at 98.6%, and the minimum appears in July at 8.7%. The annual‐mean SCF shows an increasing trend at 0.09%·annum−1, owing to the significantly increasing SCF in the snow accumulation period at 0.5%·annum−1 and the decreasing SCF in the snow melting period at −0.2%·annum−1. The SCF distribution, as well as its interannual change, is greatly influenced by elevation. During the snow cover period, a positive linear correlation between SCF and elevation is found at 0.02%·m−1 (p <.01). The annual‐mean SCF decreases in the area below 1,200 m, whereas it increases in the area above 1,200 m. Accordingly, the elevation‐dependent SCF results in various SCF distributions on different slopes and watersheds. The SCF shows an apparent pattern in different aspects, with similar SCFs between the north and east aspects and between the west and south aspects but a difference between the northeast aspects and the westsouth aspects. The SCF is negatively correlated with air temperature (r = −0.74, p < 0.01) and positively correlated with precipitation (r = 0.74, p < 0.01). In addition, temperature shows a significant and larger correlation with SCF in both the snow accumulation and melting periods, indicating the major factor of temperature for the changes in SCF. [ABSTRACT FROM AUTHOR]

In winter 2020/2021, several episodes of cold air outbreaks have wreaked havoc across much of China, resulting in exceptionally low temperatures over northern‐to‐southeastern China. Our analysis shows that the anomalous circulation leading to the cold wave in China was characterized as: (a) a strengthening of the Siberian high, (b) a deepening of the East Asian trough, and (c) a weakening of the stratospheric polar vortex. Prior to the winter, in summer and autumn, the largest sea ice loss along the Siberian coast was observed. We therefore address the question whether the substantial sea ice loss has contributed to the cold wave. First, applying singular value decomposition (SVD) analysis, we find strong coherence between the autumn Arctic sea ice coverage and temperatures over the central‐to‐east Asian region with the sea ice component (SVD1_SIC) reaching a record high in 2020 and displaying a decadal shift around 2005. Associated with both the interannual and decadal variations of the SVD1_SIC, there are similar circulation anomalies as described in (a), (b) and (c) above. Second, applying self‐organizing maps, wintertime daily air temperatures are clustered into nine nodes with Node‐1 mostly resembling "warm Arctic, cold Eurasia" pattern. The frequency of Node‐1 shows a similar decadal shift as observed in SVD_SIC1 above, with a correlation of about 0.56. Associated with Node‐1, the circulation anomalies are consistent with features highlighted in (a), (b) and (c) above. Thus, taking all the evidence into account, we conclude that the substantial sea ice loss along the Siberian coast contributed significantly to the 2020/2021 winter cold wave in China. The mechanism behind the contribution in this study highlights that the Arctic sea ice loss is favourable for certain circulation patterns on climate timescale, reinforcing disruptive chain of reactions on weather timescale, and leading to severe cold events. [ABSTRACT FROM AUTHOR]

The last millennium (LM, 1000–1850 AD) is crucial for studying historical climate change on decadal to multidecadal timescales. The summer surface air temperature (SAT) evolutions on regional scales (e.g. over China) are more uncertain than the globe/Northern Hemisphere, especially in response to external forcing factors and internal climate variability. Here, we provide one‐signal (full‐forcing) fingerprints of summer SAT in China derived from three large ensemble model archives with a multi‐proxy reconstruction during the LM, Little Ice Age (LIA, 1451–1850 AD), and Medieval Climate Anomaly (MCA, 1000–1250 AD), respectively. Our results show that (a) SATs in the northeast, southeast, northwest, and Tibetan Plateau (TP) regions of China show evident decreasing trends during the LM. External forcing response from all model archives agrees with the regional SAT reconstruction but underestimates variability in northwest China at the multidecadal timescale. (b) During the LIA, the summer regional SAT exhibits a cold condition in the reconstruction and simulations, especially in the northeast and northwest regions of China. External forcing responses in most model archives are the dominant factor on multidecadal SAT evolutions in the southeast, northeast, and TP regions of China and decadal SAT evolutions in northwest China. (c) During the MCA, detection and attribution of SAT shows that internal climate variability dominates in southeast, northeast, and TP regions of China, but external forcing dominates in northwest China at decadal to multidecadal timescales. These results contribute to a better understanding of the causes and mechanisms of regional climate change. [ABSTRACT FROM AUTHOR]

The rising of near‐surface air temperature is the most obvious manifestation of global warming. The analysis of the probability distribution function (PDF) of temperature can deep our understanding of the current characteristics of climate and extreme temperature changes. In this study, the daily maximum, minimum and mean temperature observations from meteorological stations are analysed to construct the temperature anomaly PDF during 1961–2016 over China. The skewness and kurtosis of the PDF are compared between the 1961–1990 and 1991–2016 periods. The non‐Gaussian tails of the PDF are also identified to qualify the deviation of the temperature probability density curve. The results show that near‐surface air temperature in China increased during the recent decades. The daily minimum temperature increased more than the daily maximum temperature did, while the temperature increase in winter was larger than that in summer. The largest increase detected was 1.29°C for the daily minimum temperature in winter, contrasting with the smallest increase of 0.51°C recorded for the daily minimum temperature in summer between the two study periods. The temperature anomaly PDF generally presented a positive skewness in winter and a slightly negative skewness in summer. Obvious non‐Gaussian tails in the temperature anomaly PDF were present in the majority of the study sites. Most areas showed a short cold tail in winter (except for southwestern China), and long cold tails were mainly observed in summer. These results can improve our understanding of the variation of extreme temperatures, and of the responses to global warming. [ABSTRACT FROM AUTHOR]

As a direct manifestation of global warming, the air temperature has been reported to rise significantly during the last several decades. Meanwhile, precipitation around the world has also changed profoundly. Therefore, it is important to unravel the long‐term changes in temperature and precipitation as well as their relationship. This study investigates the characteristics of temperature and precipitation in China from 1961 to 2018. Based on theoretical simulations, the effect of cloud droplet growth and precipitation formation on cloud temperature change has been determined. It has been found that for a specific cloud, the change in surface tension with temperature can increase the supersaturation rate in the cloud, which promotes precipitation by about 10%·K−1. A real dataset was then used to analyse the state change in temperature and precipitation under climate change. Precipitation showed an increasing trend by 13.9%·K−1 throughout China with increasing temperature, which reflects the combined effect of the decrease in rainfall frequency and the increase in rainfall intensity. This indicates that the theoretical simulations could provide a reference model to analyse the actual precipitation–temperature relationship (PTR). In addition, the PTR showed large regional variations: 5.1%·K−1 in North China, 5.6%·K−1 in the Northeast region, 19.6%·K−1 in the Yangtze River valley, 20.4%·K−1 in the Southeast, 14.1%·K−1 in the Southwest, and 9.2%·K−1 in the Northwest, which may be limited by the relative humidity. [ABSTRACT FROM AUTHOR]

During 1998–2013, global surface air temperature increased more slowly than greenhouse gas concentrations, and therefore this period was defined as a "global warming hiatus." The characteristics of climate extremes in China during this period are still not clear. In this study, based on 2,841 meteorological station observations in China, the trends of precipitation and temperature extremes during the global warming hiatus were investigated relative to the reference period (RF) (1982–1997) and the whole historical period (HIS) (1982–2017). Machine learning was used to capture the nonlinear regression of climate extremes, and the Theil–Sen method with the Mann–Kendall significant test was used to calculate the slopes of their linear trends. During the global warming hiatus, annual and summer (JJA) warmest days TXx and the number of summer days SU over the whole of China and most of its four subregions were found to decrease relative to the HIS and RF periods. Annual and winter (DJF) coldest nights TNn over China and its four subregions were found to decrease moderately relative to the HIS and RF periods, whereas the number of frost days FD increased consistently. Precipitation extremes showed more temporal and spatial variability than temperature extremes. Trends of annual and JJA wet extremes during the hiatus were found to decrease relative to the HIS and RF periods, whereas the dry extreme index during the hiatus was found to increase generally over China and in most subregions. Lighter winds and lower relative humidity over most areas of China might have contributed to less pronounced trends of wet extremes during the hiatus period. [ABSTRACT FROM AUTHOR]

Freezing level height (FLH) is the altitude of a location where the air temperature is 0°C. The FLH denotes the approximate position for water phase transitions from liquid (or vapour) to solid but not vapour to liquid. Based on temperature and height data on the ground surface to heights with an atmospheric pressure of 400 hPa, the monthly FLH at 118 radiosonde stations located in China are derived for the 1958–2017 period. The monthly and annual climatology during 1981–2010 and the seasonal, intra‐annual and decadal variabilities of the FLH during 1958–2017, along with its long‐term trends, were quantitatively evaluated at the regional scale and for individual stations. FLH climatology is generally related to season, zone and topography. The annual FLH anomalies decline initially, followed by a rise, with synchronous changes in the temperature in the lower and middle troposphere; the anomalies in south‐eastern China are partly associated with El Niño–Southern Oscillation events. The increasing trends of FLH are closely associated with tropospheric warming and show evident regional and seasonal differences. Stronger increasing trends are observed in northern and western China in autumn or winter (particularly in recent decades). The changes in FLH have implications on long‐term trends in equilibrium line altitude (ELA) of glaciers in Tianshan Mountains, snow cover extent in melt season and hail frequency in China especially in high‐elevations. During recent decades, the evolution of the FLH and major composition in the cryosphere has accelerated as a response to tropospheric warming. The study on FLH change can provide valuable information for the evaluation of glaciers, snow cover extent and hail frequency in China from a new perspective; which is helpful for understanding regional hydrological processes and climate changes better. Further application of FLH in cryosphere monitoring can improve water management and flood forecasting in headwater regions in China. [ABSTRACT FROM AUTHOR]

Uneven and sparse surface air temperature (Ta) observations challenge the understanding of the atmosphere‐land interactions and global environmental changes. Lapse rate (γ) is thought of with great potential to obtain accurate long‐term and high‐resolution Ta dataset. However, previous studies on γ over China were solely based on observed data, which limited our understanding since few stations are distributed in western China. In this study, an improved procedure for estimating γ by combining sparse observations and newly released ERA5 reanalysis data was proposed. The spatial heterogeneity in γ over China and its influencing factors (e.g., topography, climate, and vegetation) were then explored. A re‐examination of long‐term spatiotemporal variations in γ and its potential driving forces over China was also performed at grid scales. The results demonstrated that our γ estimations reproduced similar patterns to those derived from observations. The subsequent analyses revealed that the annual and seasonal variability in γ varied substantially among different altitude gradients, land cover types, and climate zones. The vital role played by vegetation covers in regulating local γ was emphasized in this study, which was poorly assessed previously. Moreover, γ in low altitude zones showed lower values but strong temporal fluctuations and contributed more to the interannual variability in γ over China, which could be mainly attributed to human activities. The present findings can provide an alternative method for estimating γ and be further used to assess regional or global temperature changes. [ABSTRACT FROM AUTHOR]

The global mean surface temperature does not increase monotonously over the past decades, with accelerated warming from the late 1970s to 1998 and followed by the warming slowdown during 1998–2013 (the so‐called warming hiatus). This study assessed and compared the temporal evolutions of sea surface temperature (SST) trends in the East China Seas (ECS, including Bohai, Yellow and East China Sea) and other key ocean regions. The results revealed an amplified response of ECS SST to both global warming acceleration and hiatus. This amplification was manifested as remarkably enhanced winter warming rates in the ECS of over 1.1 and 0.8°C⋅decade–1 for the 1980–1989 and 1990–1999, respectively, and as an obvious cooling trend of nearly −0.5°C⋅decade‑1 during 1998–2013. The enhanced response can be explained well by the combined effects of the Kuroshio Current (KC) and East Asian Winter Monsoon (EAWM). The weakened EAWM during the 1980s, accompanied by lower wind speeds and higher air temperatures, impeded the releases of latent and sensible heat fluxes from the ocean to the atmosphere, resulting in rapid ECS warming. During 1998–2013, the strengthened EAWM led to the enhanced cooling trend in the ECS. In addition, the volume transport of the KC east of Taiwan strengthened (weakened) during the 1990s (2000s), which might also have contributed to the enhanced warming (cooling) in the ECS. Our research suggests their sensitivity makes the ECS potentially vulnerable to the effects of global climate change, which has important implications regarding regional impact assessments. [ABSTRACT FROM AUTHOR]

Heat waves (HWs) are expected to increase in many parts of the world under climate warming. However, most existing studies examined the changes in HWs that are derived from air temperature only, possible different changes in humid HWs that consider the combined effects of relative humidity (RH) are much less understood. This study investigates the spatial and temporal changes in two different HW types, namely, dry and humid HWs, in China from 1961 to 2014. Analysis results show that, on average, humid HWs in China occur 20% more frequently than dry HWs. Dry HWs are more commonly located in northern China, while humid events mainly appear in monsoonal southern and eastern regions. It is also found that all measures of both dry and humid HWs across China have been increasing during the past decades, and humid HWs exhibit a more prominent intensifying trend than dry ones. In particular, the national mean frequency, participating days, magnitude, and duration of dry (humid) HWs increased by 0.061 (0.069) events decade−1, 0.32 (0.39) days decade−1, 0.53 (0.62) °C decade−1, and 0.19 (0.21) days decade−1, respectively. These trends vary in different parts of China. The largest increment of dry HW frequency appears in the arid region of northwest China, while the fastest increase of the humid HW frequency is observed in southeastern China. Given the additional stress induced by high humidity to extreme high temperature, we suggest that future climate change mitigation and adaption should consider the change and impacts of humid heat events. [ABSTRACT FROM AUTHOR]

The annual temperature cycle affects atmospheric circulation, biomass cycling, and human life. Its variation is influenced by surface solar radiation, which plays a key role in surface energy budgets. In this study, the Fourier transform method is used to analyse the spatial distribution and long‐term variations in temperature phase, amplitude, and baseline terms between 1960 and 2016 in China. Mean surface air temperature has a north–south gradient for phase, amplitude, and baseline. The regional mean phase values of the maximum, minimum, and mean temperatures in South China are larger than in North China, indicating that the timing of the annual cycle in Southern China is several days later than in Northern China. At the national scale, the annual maximum, minimum, and mean surface air temperature cycles are advancing, decreasing in range, and have a rising baseline. Linear regression is used to quantify the effect of surface solar radiation on temperature by removing its contribution on the raw maximum and mean temperatures. The surface solar radiation increases the phase of maximum and mean daily air temperatures, but reduces the amplitude and baseline. The surface solar radiation effect on maximum temperature is especially significant on the Yunnan‐Guizhou Plateau located in the south‐southwest. The phase of maximum temperature adjusted for solar radiation for the Plateau is similar to South China at the same latitude and later than the raw maximum temperature. [ABSTRACT FROM AUTHOR]

Changes in soil temperature will exert an important influence on the management and utilization of vegetation and agricultural production, whereas the spatiotemporal variations in soil temperature under different vegetation regions across China remain largely unknown. The shallow soil temperatures (0–20 cm) during the growing season (May–September) from 1965 to 2014 across China were analysed, and the findings showed that the spatial distribution of shallow soil temperature was determined primarily by latitude in eastern China (east of 110°E), and by altitude in western China (west of 110°E) with some high (low) temperature centres. The vegetation regions with relatively low soil temperatures are mainly concentrated in high altitude and high latitude areas, which have relatively large differences in soil temperature at different depths and relatively high soil warming rates. Over the past 50 years, shallow soil temperatures increased greatly during the growing season at the site, vegetation region and nation scales, but the warming rate and its relationship with climate change varied greatly. The soil temperature variables were affected substantially by air temperature and precipitation in the subtropical forest and tropical forest regions but were affected primarily by air temperature in the other vegetation regions. This difference may be due to the spatial difference in precipitation amounts across China, which affected the soil temperature via soil moisture feedback. Further study indicated that the warming rate in shallow soil was higher in stations (vegetation regions) with less precipitation than in those with more precipitation. [ABSTRACT FROM AUTHOR]

A regional Climate‐Weather Research and Forecasting (CWRF) model with a 30‐km horizontal resolution was applied to simulate the East Asian summer monsoon (EASM) and climate in China from 1980 to 2016. As compared with observations and reanalysis data, the model can reasonably reproduce the spatial distributions of the climatological mean atmospheric circulation and water vapour transport in East Asia, as well as the seasonal advance and retreat of EASM and rain bands. The correlation coefficient between the EASM circulation index in the simulation and reanalysis is.97. The model can well represent the geographic distributions of summer mean temperature and precipitation over most of China. However, model biases still exist, in particular the skill in the Yangtze–Huaihe River basin is relatively low. The simulated climatological mean temperature and precipitation deviations from observations may be related to the model's systematic circulation biases, with a thicker lower troposphere (i.e., higher temperature between 500 and 1,000 hPa) over most of China (except for the south and southwest) and a thinner one over the coastal oceans in summertime. Compared with the reanalysis, the model overestimates the land‐ocean thermal contrast, which causes the South Asian High shifted to the north and east, as well as the subtropical high and tropical convective activity located further north and persisted longer. Consequently, more water vapour transports northward, leading to more precipitation over North China–Northeast China and less precipitation over the Yangtze and Huaihe River basin. Therefore, the enhanced land‐ocean thermal contrast may be a major factor for the stronger EASM in the model, and corresponding precipitation and temperature biases in China. This analysis provides important information for further improving model performance in EASM simulation. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is an essential component of the hydrological cycle and is crucial to water resources management and assessment. Spatiotemporal variations in ET0 and their attribution to five climatic variables (maximum and minimum air temperatures, solar radiation, vapour pressure, and wind speed) were estimated for the non‐monsoon region of China from 1961–2017 meteorological data by using the Penman–Monteith equation and the partial‐differential method. The association between ET0 and atmospheric circulation patterns was explored by applying Pearson's correlation analysis. The annual ET0 series had two earlier shift points, the first showing a significant increase from 1961 to 1973 (period I) and the second showing a significant decrease from 1974 to 1994 (period II). ET0 has significantly increased again since 1994 (period III). Wind speed has been the dominant contributing factor to ET0 followed by maximum air temperature during all three periods, but the contribution gap between minimum and maximum air temperatures is narrowing. ET0 has been strongly correlated with eight selected teleconnection indices in some regions, but the locations and spatial extents have varied considerably for different indices. Eight relationships with ET0 were divided into four groups: North Atlantic Oscillation and Arctic Oscillation (mainly the northwest non‐monsoon region), Pacific North American Index and Pacific Decadal Oscillation (mainly the northern non‐monsoon region), Antarctic Oscillation and Atlantic Multidecadal Oscillation (mainly the Hexi Corridor and the southern Xinjiang), and East Asian Summer Monsoon Index and South China Sea Summer Monsoon Index (mainly the southeast non‐monsoon region). The Antarctic Oscillation, Atlantic Multidecadal Oscillation, and South China Sea Summer Monsoon Index indicated more potential for predicting ET0. When we used Pearson's correlation analysis to analyse the relationship between atmospheric circulation and the dominant factors affecting ET0, we found that the circulation patterns are likely to affect the variation in ET0 by influencing the dominant climatic variables. [ABSTRACT FROM AUTHOR]

The low‐latitude highlands (LLH) of China are situated in the subtropical southwest China. The spring climatic characteristics of the LLH were previously regarded as being governed by remote sea surface temperature forcing and large‐scale atmospheric circulations. Recent studies qualitatively demonstrated that the LLH is a relatively strong soil moisture (SM)‐surface air temperature (SAT) coupling region in China during spring. In this study, the quantitative spring SM‐SAT coupling (mean of March and April before wet season) is further statistically analysed using two different SM data sources (one reanalysis data set and one land surface assimilation product). The results show that significant negative SM‐SAT feedbacks mainly occur in the western and middle part of the LLH. Over these areas, 10–50% of the total SAT variance could be explained by the SM‐induced negative feedbacks with a feedback parameter of −0.2°C·(standardized SM)−1 to −0.8°C·(standardized SM)−1. Further analyses show that SM negatively impacts Bowen ratio in the western and middle part of the LLH where Bowen ratio positively affects SAT, therefore significant negative SM‐SAT feedbacks occur therein. The potential impact of India–Burma Trough (IBT) on the SM‐SAT coupling is also investigated in this study, the results of which suggest that SM‐SAT coupling and the effects of SM on land surface energy balance may be immune to the influence of the IBT. Furthermore, SM and IBT may comparably affect SAT in the western and middle part of the LLH. This highlights that SM might have prominent effects on the subseasonal predictability of spring SAT over these areas. [ABSTRACT FROM AUTHOR]

Spring soil moisture over the vast region from the lower and middle reaches of the Yangtze River valley to North China (YRNC) can significantly influence East Asian summer monsoon (EASM) via May surface temperature. This study further validates the role of May surface temperature in linking spring soil moisture with summer monsoon circulation and rainfall over eastern China. The role of May surface temperature over YRNC in the ensuing EASM and precipitation over eastern China are investigated by observational analyses and numerical simulations. Given the long "memory" of soil temperature (ST) and its highly consistent with surface temperature, experiments are performed by altering ST as a substitution. The results show that YRNC spring surface temperature anomalies have a significant influence on EASM and precipitation over eastern China. The negative May ST anomalies correspond to an abnormal cooling in the surface and tropospheric atmosphere around the YRNC, which narrows the land‐ocean thermal contrast, resulting in a weakened EASM. An anomalous anticyclone extends from southeastern China to the Philippine Islands, and an anomalous cyclone occupies northeastern China. Consequently, rainfall anomalously decreases over southeastern China and increases over northeastern China. The convergence of warm and humid southerly airflows and cold northerly winds conduces to an enhanced rainfall around the Yangtze River valley. The opposite occurs for the positive ST anomalies. Further simulations show that abnormal wet (dry) spring soil can lead to negative (positive) ST and surface temperature anomalies in May over the YRNC. Hence, the surface air temperature in May is the bridge for the effect of the YRNC spring soil moisture on the EASM and precipitation over eastern China. [ABSTRACT FROM AUTHOR]

Two skilful 2‐month‐leading hybrid downscaling prediction schemes in October for winter surface air temperature (SAT) over China are proposed in this paper. The schemes are based on the year‐to‐year increment approach and the coupled climate patterns between the winter SAT over China and its predictors. Observed North Pacific sea surface temperature (SST) from the preceding July to September, Arctic sea ice concentration (SIC) in the preceding August and winter sea level pressure (SLP) over pan Eurasia from version 2 of the Climate Forecast System (CFSv2) are selected as the predictors based on the fundamental physics. Individual‐predictor schemes (IP‐schemes), that is, SLP‐scheme, SST‐scheme, SIC‐scheme, indicate that these predictors exhibit prediction skills in different regions. Multi‐predictor scheme I (MP‐schemeI) is developed by combining three predictors. However, MP‐schemeI shows limited skill in predicting SAT over Northeast China (NECTA), due to the limited skill of CFSv2 over the extratropics. Thus, MP‐schemeII is established, in which a hybrid downscaling model for NECTA is constructed. These two MP‐schemes have comparable prediction skill over China, but MP‐schemeII outperforms MP‐schemeI over NEC. The temporal (spatial) anomaly correlation coefficient (ACC) increases from 0.23 (0.15) in MP‐schemeI to 0.36 (0.21) in MP‐schemeII, and the ratio of the same sign of anomalous years (Anomalous‐RSS) improves from 39.1% to 56.5% over NEC. For the winter SAT over China, the MP‐schemes greatly enhance the prediction compared with CFSv2 outputs and the IP‐schemes. The temporal (spatial) ACC increases from 0.29 (0.05) in CFSv2 to 0.52 (0.29) in the MP‐schemes, and the station‐average root‐mean‐square error decreases by about 48.0% compared with CFSv2. Moreover, the RSS (Anomalous‐RSS) of the winter SAT over China is 55.9% (47.4%) in CFSv2 and 64.7% (63.2%) in the MP‐schemes. This indicates that the MP‐schemes perform better in predicting anomalous winters. [ABSTRACT FROM AUTHOR]

Derived from realistic global warming scenarios, long‐term projections of spatial patterns in precipitation and temperature in hydrology and climatology can serve to evaluate climate risk, explore sources of renewable energies and allow local‐scale data to inform decisions regarding agricultural, ecosystem, social, recreational and economic activities. Under the CORDEX‐EA project, the precipitation and temperature projections (2020–2045) for the economically and socially important region of Northwestern China were derived from high‐resolution regional climate model (RCM) simulations for RCP 4.5 and 8.5 scenarios, and compared against a historical period or baseline of 1980–2005. Drawing data from four key RCMs [Weather Research and Forecasting (WRF); Regional Spectral Model (RSM); Regional Climate Model version 4.0 (RegCM4); Mesoscale Model version 5 (MM5)], reliable local‐scale projections were generated by applying suitable bias correction that accords with the multivariate bias correction (MBC) approach. To validate this approach and then evaluate climate change impacts, the adjusted precipitation and temperature estimated from bias‐corrected models for the historical period were compared to the observed data. The results showed that the simulated spatiotemporal distribution of multiyear average precipitation and temperature appear to fit relatively well with the observations, however, the wet‐cold and dry‐warm climate‐related biases were still evident for the high altitude regions. Bias‐corrected future projections of RCMs indicated spatially averaged annual precipitation is expected to rise by about 23.6 and 35.3 mm under the RCP 4.5 and 8.5 scenarios, respectively, while spatially averaged annual temperature is expected to rise by about 1.95 and 1.10°C. Precipitation is projected to increase in all seasons, albeit, more so in the cold season (i.e., boreal winter and spring) than the warm season (i.e., boreal summer and autumn). The annual increase is expected to be about 56.7% under the RCP 4.5 scenario, compared to 67.6% under the RCP 8.5 scenario. The changes of mean temperature in winter are expected to be significant, −37.8% under both RCP scenarios. For spring, the mean temperature will rise by 23.1% (28.9%) under the RCP 4.5 (8.5) scenario. A MBC approach was found to be effective in yielding reliable projected changes in precipitation and temperature variables. The proposed approach has important implications for climatological studies and evaluation of climate change impacts on localized regions, not only in China, but also in other similar areas of the world, where decisions for managing climate risk must be implemented by policy makers, government, industry and stakeholders. [ABSTRACT FROM AUTHOR]

Global climate change is likely to affect reference evapotranspiration (ET0), which is important for agricultural water resources and food security. Analysis of ET0 changes is also important for understanding climate change and its impacts on hydrology. In this study, ET0 was calculated from 2020 to 2099 in nine agricultural regions and the entire country of China utilizing the Penman–Monteith method based on bias‐corrected climate data from the global climate models MIROC‐ESM‐CHEM, NorES1‐M, IPSL‐CM5A‐LR, GFDL‐ESM 2M and HadGEM2‐ES under future climate change scenarios. The spatiotemporal characteristics of seasonal and annual ET0 and climatic variables were analysed based on the Mann–Kendall test with trend‐free prewhitening (TFPW‐MK) and Sen's slope estimator. Sensitivity coefficient and multivariate regression were used to identify factors controlling the change in ET0. The results showed that seasonal and annual air temperature and precipitation both increased under all climate scenarios, and the majority of relative humidity and wind speed values showed downward trends during 2020–2099. The lowest annual ET0 values were found in the NECR and QTR, and the SCR had the maximum ET0. Both the TFPW‐MK and slope statistics showed an upward trend of seasonal ET0 during 2020–2059 under all scenarios. During 2060–2099, seasonal ET0 values showed a slight and nonsignificant downward trend under RCP 2.6, while upward trends were produced in other scenarios. Areas with high ET0 values were located in the SCR, GXR and HHHR, while low ET0 values mainly occurred in the NECR and QTR. The ET0 for the four seasons in the SCR was higher than that in the other regions, and the summer ET0 was the highest compared with that in the other seasons overall. For the attribution assessment, Tavg is the main controlling variables to ET0 trends under the interaction of multiple climatic factors though RH is the most sensitive. [ABSTRACT FROM AUTHOR]

Based on the Coordinated Regional Downscaling Experiment‐East Asia second phase (CORDEX‐EA‐II) with higher resolution, model results driven by ERA‐Interim reanalysis using WRF, RegCM4 and CCLM are evaluated against the observational datasets including CN05.1, CRU and GPCP during the period of 1989–2009. The results show that the RCMs have the capability to simulate the annual and seasonal mean surface air temperature and precipitation, however, some biases are produced. The biases are highly dependent on the geophysical locations and the RCMs applied, and CCLM agrees better with the observed precipitation over ocean. CCLM also outperforms the other two RCMs in simulating the interannual variations of temperature and precipitation in most sub‐regions, which can be attributed to its better presentation of the interannual variation of large scale circulation. Generally, all the three RCMs can well reproduce the seasonal cycles of the surface air temperature in most sub‐regions, however, only in the northern regions of China can the RCMs well reproduce the seasonal cycles of precipitation. [ABSTRACT FROM AUTHOR]

A large‐scale high air temperature event in China during July 2017 is examined using observational reanalysis data. Based on this case study, summer extreme hot events (EHEs) over China are classified into five types using the self‐organizing map (SOM) method. The five EHE types include those over northeast China (NEC type), northwest China (NWC type), north China (NC type), mid‐eastern China (MEC type) and south China (SC type). All types are associated with sustainable anticyclones (EHE anticyclones). Composite analysis shows that the EHE anticyclone in northern China (corresponding to the NEC, NWC and NC types) is primarily formed by downstream wave train propagation from upstream blocking, while EHE anticyclone formation in southern China (corresponding to the MEC and SC types) is driven by the joint action of downstream wave train propagation and westward movement of the western Pacific subtropical high. Moreover, the upstream blocking and downstream EHE anticyclone embedded in the wave train play important roles in maintaining the wave train. The upstream blocking acts as an energy source for downstream EHE anticyclone intensification and leads to EHE formation, with the intensified zonal wind at certain latitudes affecting the wave train propagation direction. This finding indicates that the upstream blocking with intensified zonal wind at certain latitudes may serve as an indicator for the prediction of EHE anticyclones over China. As a consequence of the persistent EHE anticyclone, the land surface is primarily warmed by enhanced shortwave radiation through reduced regional cloud cover. For the NWC and NC types, heating of the lower atmosphere takes place via the sensible heat flux; whereas, for the NEC, MEC and SC types, the main heating terms are the latent heat flux, sensible heat flux and upward longwave radiation. [ABSTRACT FROM AUTHOR]

Observational analyses reveal substantial cooling anomalies in East China, during the global hiatus period (1998–2013), particularly in winter. The factors contributing to the winter cooling anomalies and the underlying mechanisms are studied. The results highlight the substantial roles played by two factors: Arctic sea ice reduction (i.e., sea ice area in Barents‐Kara Seas, SIA) and the sea surface temperature (SST) cooling anomalies in the Kuroshio extension region (KSST). Together, these factors contribute to approximate 90% of the trend anomaly of East China's area averaged surface air temperature (ECT). The individual contributions from SIA and KSST are investigated based on observational diagnostic analyses and sensitivity experiments. The results show that the contributions from the two factors are similar. Both SIA and KSST induce intensified geopotential height over the mid‐to‐high latitudes of the Eurasian continent, with the maximum over the Ural Mountains extending toward Lake Baikal. These anomalies intensify the Ural blocking activities and Mongolian cold high. Meanwhile, both forcings cause negative 500‐hPa geopotential height (Z500) anomalies over the central North Pacific that extends westward to East Asia, intensifying the climatological East Asian grand trough. However, KSST causes positive Z500 anomalies over the Bering Sea, but SIA does not. The enhanced Ural blocking activities and the deepened East Asian grand trough jointly favour the intensification of the East Asian winter monsoon, thus causing cooling anomalies in East China. [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]

The spatiotemporal pattern of precipitation is significantly changing with global climate change. Snowfall is a solid phase of precipitation and an important water resource. With two gridded data sets of APHRO (Asia Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation of Water Resources) and CN05.1, this study analyses the changes in the spatiotemporal pattern of snowfall in a snow‐dominant region of China from 1961 to 2015. The results indicate the significant increasing trend of winter snowfall in horizontal and altitude dimension in snow‐dominant regions, but the winter snowing season length shortened. For the frequency of snowfall intensity level, light, and heavy snowfall and snowstorms increased, but moderate snowfall showed no change. However, the intensity of extreme snowfall in once‐in‐a‐century was decreasing in all of the snow‐dominant regions. In the altitude dimension, the increasing trend in snow‐dominant conditions was not uniform, which may be related to change in air temperature and water vapour through the vertical atmospheric levels. The upwards trend in snowfall may be caused by the increase of atmospheric water content rather than the change of snowy weather conditions. In addition, the change values of climate indices can also contribute to snowfall increasing in snow‐dominant regions. [ABSTRACT FROM AUTHOR]

Accurate vegetation cover data are important for realistic simulation of regional climate. The default vegetation parameters from Global Land Cover 2000, currently incorporated into global climate models and used in regional climate model RegCM, are not realistic for China, which may have contributed to serious bias in surface climate simulation. In this study, a new set of vegetation parameters considering the Plant Functional Type (PFT) fractions and the corresponding monthly leaf area index (PFT_LAI), were developed based on the land cover and MODIS LAI data sets. The regional climate model RegCM4.5 coupled with the land surface model CLM4.5 were utilized to test the performance of the new vegetation parameters by comparing simulations with observations using different surface parameters. The surface energy balance was analysed to examine the effects of changed vegetation parameters on regional climate. The results showed that the new parameters were more accurate than the GLC2000 parameters when describing the distribution of crops, grassland, and forests over China. The improved vegetation parameters reduced model biases for winter air temperature and precipitation over southern China by 0.9°C and 8%, respectively, and reduced the winter temperature and summer precipitation biases over northeastern China by approximately 0.7°C and 8%, respectively. More accurate surface albedo are the main reasons for reductions in model bias. However, certain biases, such as the cold and dry bias over the Tibetan Plateau, still remained in the simulation results using our new vegetation data. [ABSTRACT FROM AUTHOR]

Declining pan evaporation (Epan) across many continents in the past decades despite global warming is gaining attention of hydrology and climate science communities. While Geo‐detector is considered useful for attributing the spatio‐temporal variation of a certain geography‐related element, it has not been applied for Epan attribution. Based on the Geo‐detector, we first attribute the spatio‐temporal variation of Epan across China in 1961–2001. The results show that relative humidity is the primary factor influencing the temporal dynamics of Epan, followed by sunshine duration, maximum air temperature and wind speed. In the northwest China (south China and east China), wind speed, air temperature and relative humidity (relative humidity, sunshine duration, wind speed and air temperature) are the dominant factors of Epan variations. The results obtained are comparable to the previous studies using other statistical methods (i.e., the partial differential method, Pearson correlation coefficient and multiple regression), which reveal the usefulness of Geo‐detector for attributing and diagnosing the spatio‐temporal variations of Epan. Moreover, more detailed spatial information and interactions among meteorological elements can be obtained using Geo‐detector. These findings should provide helpful references for understanding the mass and energy budgets at different spatial–temporal scales under global warming. [ABSTRACT FROM AUTHOR]

As the climate system is known to be warming unevenly, the open question of whether there has been a significant warming "hiatus" at global or regional scales has attracted worldwide attention. With annual mean air temperature (Tmean) setting new records subsequent to 2012, it is reasonable to reanalyse the presence of an apparent decelerated warming trend in China. We therefore examined the shifts of temperature trends in China between 1980 and 2017 using homogenized records from 798 meteorological stations via the Breaks For Additive Season and Trend (BFAST) method and Mann–Kendall and Sen's slope estimator statistical tests. The results show that Tmean at the country level exhibited monotonic increase with a positive break occurring around 1997, and the warming rate during 1980–2017 (0.36 °C/decade) was slightly higher than that during 1980–1997, which suggests that this positive break did not overwhelm the overall continuous warming trend. Spatial records show that most areas west of 108°E or south of 30°N within the country experienced a continual warming trend over the study period and that negative break that occurred around 2010 was major contributor to temporary decelerated warming trend detected in other areas, especially in Northeast China. Hence, this study highlights annual air temperature has continued to rise overall in China since 1980, while considerable regional differences have been detected within the shifts of temperature trends. Annual air temperature has continued to rise overall in China since 1980, albeit with short‐term fluctuations (a). Most areas west of 108°E or south of 30°N within the country has experienced a continual warming trend, whereas negative break that occurred around 2010 was a major contributor to the temporary decelerated warming trend detected in other areas (b). [ABSTRACT FROM AUTHOR]

Temperature sensitivity (ST) of phenology, defined as the shift of phenophase with per unit change of preseason temperature, has been widely used to quantify phenological response to climate change. The spatial variation in ST of spring phenology has been well studied for several woody plants, but how to explain it became a challenge. Several hypotheses to explain the spatial variation in ST have been proposed, but studies examining all potential factors together were very limited. In this study, using first flowering date (FFD) data for five widespread woody plants at 47 stations in China and the other five species at 421 stations in central Europe during 1964–2014, we calculated ST by using the Sen's slope of FFD on mean preseason temperature for each species at each station. Subsequently, multiple regression analysis was applied to examining whether ST followed the geographical (latitudinal, longitudinal, or vertical) gradients. At last, four potential influencing factors of ST were tested by Spearman partial correlation analysis. We found that ST of FFD was higher at lower latitude for most species in China. However, in central Europe, the variation of ST did not follow the geographical gradient for most species. Only one species (Fraxinus excelsior) showed a latitudinal gradient, and one (Betula pendula) showed a longitudinal gradient. For most species in both regions, the strength of FFD–temperature relationship and the preseason length could account for the spatial variation of ST to a more considerable extent compared to preseason temperature variance and chilling conditions. Our results suggest that we need to consider the effects of multiple factors on phenological response to temperature when simulating future phenological change. The spatial patterns of the temperature sensitivity (ST) of first flowering date (FFD) for five woody plants in China. [ABSTRACT FROM AUTHOR]

In December 2015, the Paris Agreement was reached in an effort to limit global warming to below 1.5 °C. However, there is few scientific literature assessing changes in the climate with 1.5 °C of warming over China. We investigated changes in climate extremes in China that generally present high impacts on society. The results indicated that an additional warming of 0.5 °C would lead to significant increases in temperature and precipitation extremes across China. Both the temperatures on the hottest days and the frequencies of heat events across China are estimated to be lower when limiting warming to 1.5 °C compared to 2.0 °C. Events such as the record heat case in the summer of 2013 over eastern China would be approximately 28% less likely to occur if warming was limited to below 1.5 °C. Moreover, China would experience reduced precipitation extremes, although this projection is accompanied by a relatively lower confidence level than for changes in temperature extremes. High‐impact heavy rain events similar to that in the summer of 2012 over northern China (Beijing) that led to severe urban waterlogging and loss of life would be less likely if there is no more than 0.5 °C of warming. Similarly, the odds of wide‐ranging severe droughts, as witnessed in the summer of 2014 over north China, are projected to decrease clearly. The positive effects of limiting warming on changes in climate extremes are thus clear, and limiting warming should be encouraged regardless of the political and socio‐economic goals of a country. [ABSTRACT FROM AUTHOR]

The self‐calibrating Palmer drought severity index (scPDSI) was computed based on the four atmospheric reanalysis data sets combined with observational data over China during 1980–2015. The discrepancies of scPDSI among the four reanalysis data sets show the necessity of integrating multiple data sets. Drought characteristics, such as drought area, severity, duration, and frequency were examined based on multi‐data set mean scPDSI. The results reveal that significant drying trends are found in Qinghai‐Tibet Plateau, southwest, southeast and entire China. Drought area (drought severity) has increased (decreased) by about 1.16% (0.015%) per decade over entire China. Trends in drought duration, temporally averaged severity and frequency also indicate that droughts become more serious in each region during the past 36 years. The identification of drought events in each month by the clustering algorithm shows that droughts over China are more and more frequent. In addition, 65 separate drought events with the duration longer than 3 months were identified under the area threshold of 150,000 km2. Through severity‐area‐duration analysis, the 2005–2015 drought is found to be the prominent event. [ABSTRACT FROM AUTHOR]

ABSTRACT: Using daily output from 29 climate models provided by the Coupled Model Intercomparison Project Phase 5, we project signals in 12 extreme temperature indices and 12 extreme precipitation indices relative to 1986–2005 over China associated with a 2 °C global warming above pre‐industrial levels under representative concentration pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). The model output reflects the following projected changes: (1) It is robust and statistically significant that warm extremes are more frequent, more persistent, and more intense than those during the baseline period of 1986–2005, and local signals emerge from natural internal variability over most of China. In particular, southern China faces severe heat stress in summer based on warm extreme indices. (2) It is robust and statistically significant that there are fewer cold extremes in China. Most models show no significant changes in the longest duration and intensity of most cold extremes in southern China and northwest China. (3) The multi‐model median shows that more frequent and more intense wet extremes that deliver greater amounts of extreme precipitation occur in China, with a regional mean increase of 16.7–42.8 mm (8–42%) in total amount of annual wet extremes, but these changes are not significant and do not exceed natural internal variability over most of the country. Spatially, the Tibetan Plateau and northeast China have robust and significant changes in part of precipitation extremes, and some changes begin to emerge from natural internal variability at local scale. There are benefits to limiting global warming for China, including less frequent and less persistent warm extremes when comparing 1.5 °C with 2 °C of global warming and a later occurrence of significant changes in climate extremes when compared an intermediate mitigation scenario RCP4.5 with a high emission scenario RCP8.5. [ABSTRACT FROM AUTHOR]

ABSTRACT: Western China (WC) is located in the arid and semi‐arid belt of the mid‐latitudes. Understanding the causes of the large temperature increases experienced in this region is of great importance because both the fragile ecological environment and the human societies in WC are highly vulnerable to changes in climate. We conducted a detection and attribution analysis on the annual mean temperature using an optimal fingerprinting method by comparing observations based on homogenized station data with simulations conducted using the models that participated in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The results show that the increase in the mean temperature can be attributed to human activities. The effect of anthropogenic (ANT) forcing can be detected in single‐signal detection analyses when the response to the ANT forcing is compared directly with the observations. This effect can also be separated from the influence of the natural external forcing in two‐signal analyses. The warming attributable to the ANT forcing explains most of the observed regional warming. The models appear to have underestimated the observed warming, suggesting that the projected future temperature increases based on raw output from the model simulations may have also been underestimated. [ABSTRACT FROM AUTHOR]

ABSTRACT We analysed observations of daily maximum and minimum air and soil surface temperatures collected between 1965 and 2007 in the temperate steppe region of North China to understand the climatology and trends of the diurnal temperature range. Sunshine duration and precipitation records were also analysed for their relationships with the changes in temperatures. In general, the daily maximum soil surface temperatures ( SSTmax) are generally much higher than the daily maximum air temperature (Tmax), and the daily minimum soil surface temperature ( SSTmin) are slightly lower than the daily minimum air temperature (Tmin) throughout the year. Consequently, the soil surface diurnal temperature range ( SSDTR) is much higher than diurnal temperature range of air temperatures ( DTR). As with air temperatures, soil surface temperatures have warmed significantly over the study period at most stations, increasing by 0.62 °C per decade for SSTmax and 0.64 °C per decade for SSTmin for the region overall. Annual and seasonal SSTmax and SSTmin have increased faster than Tmax and Tmin, except for SSTmax in winter. Declines in air DTR have been commonly observed, but in our study SSDTR decreases only in winter, driven by a steep decline after 2000, mostly resulting from strong increases in SSTmin and slight decreases in SSTmax. Both annual and seasonal calculations indicate that the decline in air DTR mainly coincided with a period of rapid decrease in sunshine duration before 1990. Total cloud amount decreased during this period, so the changes in total cloud amount could not be the cause for decrease in sunshine duration and DTR before 1990. SSDTR shows a different pattern: the rapid decrease of SSDTR in winter season since the end of 1990 coincides with a decrease in sunshine duration and an increase in total cloud amount, which may have contributed to the decrease in winter SSDTR in the new millennium. [ABSTRACT FROM AUTHOR]