In 2025, China experienced a pronounced warm–wet climate regime. The national annual mean temperature tied with the 2024 record as the highest observed since 1961, while nationwide annual precipitation exceeded the climatological norm. Multiple rainstorm sequences unfolded throughout the year, with record-breaking daily and cumulative rainfall recorded across North China, Northeast China and Inner Mongolia during summer. The country registered its highest annual count of high-temperature days on record, and central and eastern China experienced their fourth-strongest high temperature process since 1961. Both typhoon genesis and landfall numbers were above average, characterized by complex and variable tracks, with autumn typhoons frequently affecting South China. Meteorological drought was generally mild, though regional droughts showed distinct periodic characteristics. Cold air incursions occurred at near-climatological frequencies, though cold wave outbreaks were anomalously frequent. Severe convective weather processes became more frequent and locally destructive, and national gale-day totals hit a 1991-era high. Spring sand-dust activity also exceeded long-term mean levels. Notably, meteorological disasters in 2025 yielded lower fatalities, missing-person counts, crop-affected area, and direct economic losses relative to the 2015–2024 average.

The air pollution transmission channel in North China, also termed the '2 + 26' cities, has the most severe pollution problem in China. Based on the meteorological and environmental observation data from 2014 to 2022, the spatial-temporal features of the air quality index (AQI) in the '2 + 26' cities are first compared to reveal the different changes in winter and summer. Since the issue of the Air Pollution Prevention and Control Action Plan in China in 2013, the winter AQI averaged at the '2 + 26' cities shows a significant decreasing trend of -9.725 mu g m-3 per year from 2014 to 2022, but it shows much slight variation in summer. In summer, the ozone (O3) pollutant is the major contributor to the AQI. Results indicate that higher Tmax and lower relative humidity (RH) are conducive to higher O3 concentration and more severe air pollution. The averaged Tmax at these cities has a significant increasing trend of 0.28 degrees C per decade, while RH decreases also significantly at a rate of -1.08% per decade. This may be the main reason why the summer O3 concentration maintains stability at a high level in the recent 9 years. Results also indicate that the 'heat dome' effect, characterised by a persistent high pressure and warming air subsidence from the upper to lower troposphere, is reinforcing in recent years, and this is favourable for the occurrence of long-lasting dry-type high temperatures and the enhancement of O3 pollution. Projections from 19 CMIP6 models show that the high pressure system will remarkably strengthen in the near, middle, and long terms under the moderate emission scenario (SSP2-4.5). Therefore, the 'heat dome' effect will exacerbate the ozone pollution in the future.

The Three Gorges Region (TGR) of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024. The annual mean temperature in the TGR was 18.6 degrees C, which was 1.2 degrees C above normal and marked the highest level since 1961. All four seasons were warmer than normal, with spring and autumn both recording their highest temperatures since 1961. Additionally, the TGR recorded 57.2 high-temperature days in 2024, reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days. Annual rainfall was 11.2 % below normal, with spring, summer, and autumn all being drier than normal. However, the number of heavy rain days was slightly higher than normal. The annual mean wind speed in the TGR ranked as the second-highest since 1961, only slightly lower than in 2022. The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023. In 2024, the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration, accompanied by generally severe meteorological drought conditions. During the year, the TGR also experienced frequent and intense cooling events, an early onset of heavy rainfall (including severe convective weather), and exceptionally extreme rainstorm events.

The spatial distribution of precipitation anomalies during flood season and characteristics of drought and flood disasters in China are directly affected by the speed and stagnation of the East Asian summer monsoon (EASM). EASM is significantly affected by external forcing such as sea surface temperature, land surface processes, ice and snow cover, and internal dynamic anomalies of atmospheric circulation. The sea surface temperature (SST) anomaly and its evolution have always been important factors for predicting precipitation during the flood season, considering lead time and the strength of precipitation prediction in flood season.Based on the scientific understanding and application of the mechanism of El Niño-southern oscillation (ENSO) cycle and other Ocean SST on the key factors of EASM, the prediction skill of flood season precipitation is reviewed. According to a prediction evaluation spanning over 40 years of historical records, the prediction accuracy for different types of rainfall pattern, the prediction accuracy of rain types in 1981-1990, 1991-2000, 2001-2010, and 2011-2020 is 50%/30%, 60%/30%, 50%/40%, and 70%/50%, respectively. In other words, the prediction of the primary rainfall patterns during the flood season in China is closer to the observation, and the accuracy of predicting spatial distribution patterns of drought and flood has significantly improved. This improvement can be attributed to the in-depth understanding of the impact of SST on EASM activities and enhancements made to dynamic climate models. In the history of flood season prediction, there have been both successful and unsuccessful cases. The years with low prediction accuracy and significant flooding events are as follows: 1983, 1991, 1999, 2003, and 2014. The primary basis for prediction is analyzed, revealing that the limited understanding of the mechanism of SST affecting the EASM had a great impact on the skill of precipitation predictions during the flood season. Among these factors, the influence of different phases of the ENSO cycle, the asymmetry of ENSO's influence, the change in ENSO spatial patterns, and the influence of other local seas, such as the Indian Ocean SST anomaly, all play important roles.The importance of multi-factor and multi-scale synergy theory and application, as well as the technical support of the objectification method for prediction, are emphasized in summarizing causes for low prediction skill cases. Finally, some suggestions for improving future flood season precipitation predictions are put forward, and it is emphasized that the development of a multi-factor and multi-time scale synergistic theory, an objective climate prediction method, and an integrated system for monitoring, predictions and impact assessment will significantly enhance predictions and provide services for flood season precipitation.

Based on daily observation data of the Three Gorges Region (TGR) of the Yangtze River basin and global reanalysis data, the climate characteristics, climate events, and meteorological disasters of the TGR in 2022 and 2023 were analyzed. For the TGR, the average annual temperature for 2022 and 2023 was 0.8 degrees C and 0.4 degrees C higher than normal, respectively, making them the two warmest years in the past decade. In 2022, the TGR experienced its warmest summer on record. The average air temperature was 2.4 degrees C higher than the average, and there were 24.8 days of above-average high temperature days during summer. Rainfall in the TGR varied significantly between 2022 and 2023. Annual rainfall was 18.4 % below normal and drier than normal in most parts of the region. In contrast, the precipitation in 2023 was considerably higher than the long-term average, and above normal for almost the entire year. The average wind speed exhibited minimal variation between the two years. However, the number of foggy days and relative humidity increased in 2023 compared to 2022. In 2022-2023, the TGR mainly experienced meteorological disasters such as extreme high temperatures, regional heavy rain and flooding, overcast rain, and inverted spring chill. Analysis indicates that the abnormal western Pacific subtropical high and the abnormal persistence of the eastward-shifted South Asian high were the two important drivers of the durative enhancement of record-breaking high temperature in the summer of 2022.

China witnessed a warm and dry climate in 2023. The annual surface air temperature reached a new high of 10.71 degrees C, with the hottest autumn and the second hottest summer since 1961. Meanwhile, the annual precipitation was the second lowest since 2012, at 615.0 mm. Precipitation was less than normal from winter to summer, but more in autumn. Consistent with the annual condition, precipitation in the flood season from May to September was also the second lowest since 2012, which was 4.3% less than normal, with the anomalies in the central and eastern parts of China being higher in central areas and lower in the north and south. On the contrary, the West China Autumn Rain brought much more rainfall than normal, with an earlier start and later end. Although there was less annual precipitation in 2023, China suffered seriously from heavy precipitation events and floods. In particular, from the end of July to the beginning of August, a rare, extremely strong rainstorm caused by Typhoon Dussuri hit Beijing, Tianjin, and Hebei, causing an abrupt alteration from drought to flood conditions in North China. By contrast, Southwest China experienced continuous drought from the previous autumn to current spring. In early summer, North China and the Huanghuai region experienced the strongest high-temperature process since 1961. Nevertheless, there were more cold-air processes than normal impacting China, with the most severe of the year occurring in mid-January. Unexpectedly, in spring, there were more sand and dust occurrences in northern China.

全球气候变暖加剧,高温、干旱等极端性天气灾害增多,热应激严重影响我国畜牧业的发展,尤其是对奶牛养殖业更为明显.为了了解我国不同地区奶牛受热应激的影响情况,依据全国奶牛的分布情况挑选黑龙江、宁夏、湖北、上海、广东和四川6个代表性地区,利用1961-2020年的气象数据分析各地区的温度变化特征,同时采用温湿度指数(temperature humidity index,THI)分析了近10年(2011-2020年)6个地区热应激环境的总体变化规律及对奶牛产奶量的影响.结果表明:近60年来,6个地区温度变化整体均呈上升趋势,热应激环境逐渐变大.南方地区热应激出现的时间普遍早于北方,程度也相对更严重.热应激对各地区奶牛产奶量产生了不同程度的影响,其中上海地区奶牛产奶量受热应激影响最大.通过对不同地区的温度、湿度等综合分析,能够更好地了解热应激对我国不同地区奶牛生产性能的影响,对指导热应激下奶牛的饲养管理,提高奶牛养殖的经济效益提供科学依据.

China experienced a warm and dry climate in 2022. The average annual surface air temperature (SAT) was 10.51 degrees C, which was the second highest since 1961. The annual average rainfall was 606.1 mm, which was the lowest since 2012. The seasonal SAT broke the record in spring, summer, and autumn, while the SAT in winter was slightly cooler. More rainfall was observed in winter and spring, but less in summer and autumn. During the flood season from May to September, rainfall was 11.9% less than normal, which was the third lowest since 1961. The spatial distribution of rainfall anomalies exhibited a wet/dry pattern in the north/south of central and eastern China. The onset of the rainy season was generally earlier but with significant differences in rainfall. More rainfall was observed in the pre-flood season in South China and the rainy season in North China and Northeast China. In contrast, less rainfall occurred in the Mei-yu season in the middle and lower reaches of the Yangtze and Huaihe River valleys, the southwestern rainy season, and the autumn rainy season in West China. In 2022, China's drought and flood disasters were stark, and heat waves were strong. Severe droughts occurred along the Yangtze River valley during summer and autumn, while heavy rainfall and flooding struck South China in the pre-flood season and Northeast China in June-July. A historically strongest summer heat wave occurred in central and eastern China, while drastic cooling prevailed in most of China at the end of November. Landfalling typhoons were extremely less frequent.

The North China mid-summer (July) precipitation (NCJP) contributes the largest proportion of total annual precipitation in North China, with significant interdecadal and interannual variability. The interannual variability of the NCJP was further investigated on the basis of a study of its interdecadal variability and found that a sea surface temperature (SST) pattern in July located in the northwest Pacific, defined here as the northwest Pacific SST tripole (NWPT), can significantly influence the interannual variability of the NCJP, and that this relationship is regulated by the decadal northern North Atlantic SST (NNASST). Diagnostic analysis and the linear baroclinic model experiment indicate that the positive (negative) NWPT in July can excite an anomalous anticyclone (cyclone) in the region centered on the Korean peninsula and an anomalous cyclone (anticyclone) in the northwest Pacific off southeast Japan, thereby strengthening (weakening) the NCJP. When the decadal NNASST is in a significantly positive phase, the positive geopotential height anomalies it excites in the northwestern region off North China are not favorable for the connection between the NWPT and the NCJP. When the decadal NNASST is in a negative or insignificantly positive phase, the July NWPT and the NCJP have a significant positive correlation on interannual timescale.

基于北京、天津、河北、山东、河南5省(直辖市)437个国家级气象站数据和美国气象环境预报中心(National Centers for Environmental Prediction,NCEP)及美国国家大气研究中心(National Center for Atmospheric Research,NCAR)制作的日平均再分析数据,采用气候统计诊断方法,对2023年6-7月我国华北、黄淮高温天气的特点及其成因进行分析.结果表明,2023年6-7月华北、黄淮地区平均气温和平均最高气温均为1961年以来历史同期最高.北京、天津、河北、山东、河南5省(直辖市)的平均气温和平均最高气温均明显高于常年同期,其中北京市、天津市、河北省的平均气温和平均最高气温均为1961年以来历史同期最高.北京市、天津市和河北省的高温日数均为1961年以来历史同期最多.华北、黄淮地区有200个国家级气象观测站日最高气温达到或超过40℃;有126个国家级气象观测站日最高气温达极端事件监测标准,其中河北井陉、河南林州、北京汤河口等26个国家级气象观测站达到或突破历史极值.2023年6月21日至7月9日的华北、黄淮地区高温过程的综合强度,在近33年的中国历次区域性高温过程中排名第1.诊断分析表明,全球变暖是这次极端高温热浪事件发生的大背景,大气环流异常是高温持续且极端性突出的直接原因.

2023年7月29日至8月1日,京津冀地区出现极端强降雨过程,多地出现严重城市内涝、洪水和地质灾害,并造成重大人员伤亡.这次极端强降雨过程累计雨量大、持续时间长、影响范围广.京津冀地区4d平均降雨量175 mm,超过平均年降水量的1/3.在全球气候变化与快速城镇化的背景下,极端暴雨对我国城市经济社会平稳运行的冲击和影响在增大.现有城市设防标准不适应气候变化下新的防汛形势,气象灾害监测预报预警能力及部门协同联动机制等仍存在短板不足,城市公众防灾避灾意识仍有欠缺.为此建议,持续加强极端降水事件对城市影响研究,提高监测、预报、预警服务能力,加强城市治理力度,增强城市防御气象灾害的"韧性",同时应积极推动气象灾害科普宣传,不断提高极端灾害公众防御意识.

The prediction of summer precipitation over the Yangtze River basin (YRB) has long been challenging, especially during June–July (JJ), when the mei-yu generally occurs. This study explores the potential signal for the YRB precipitation in JJ and reveals that the Tibetan Plateau tropospheric temperature (TPTT) in the middle and upper levels during the preceding December–January (DJ) is significantly correlated with JJ YRB precipitation. The close connection between the DJ TPTT anomaly with JJ YRB precipitation may be due to the joint modulation of the DJ ENSO and spring TP soil temperatures. The lagged response to an anomalously cold TPTT during the preceding DJ is a TPTT that is still anomalously cold during the following JJ. The lower TPTT can lead to an anomalous anticyclone to the east of Lake Baikal, an anomalous cyclone at the middle latitudes of East Asia, and an anomalous anticyclone over the western North Pacific. Meanwhile, the East Asian westerly jet shifts southward in response to the meridional thermal gradient caused by the colder troposphere extending from the TP to the east of Lake Baikal. The above-mentioned circulation anomalies constitute the positive anomaly of the East Asia-Pacific pattern, known to be conducive to more precipitation over the YRB. Since the DJ TPTT contains both the land (TP soil temperature) and ocean (ENSO) signals, it has a closer relationship with the JJ precipitation over the YRB than the DJ ENSO alone. Therefore, the preceding DJ TPTT can be considered an alternative predictor of the JJ YRB precipitation.

Based on daily observation data in the Three Gorges Region (TGR) of the Yangtze River Basin and global re-analysis data, the authors analyzed the climate characteristics and associated temporal variations in the main meteorological factors in 2021, as well as the year's climatic events and meteorological disasters. The 2021 av-erage temperature was 0.2 degrees C above the 1991-2020 average and the 13th-warmest year since 1961. Seasonally, winter and autumn were both warmer than usual. The annual mean precipitation was 12.8% above normal, and most regions experienced abundant rainfall throughout the year. The seasonal variation in precipitation was significant and the TGR had a wetter-than-normal spring and summer. The number of rainstorm days was higher than normal; the wind speed was above normal; and the relative humidity was higher than normal. In terms of rain acidity, 2021 was tied with 2020 as the lowest since 1999. From mid-September to early October 2021, the TGR experienced exceptional high-temperature weather, which was driven by abnormal activity of mid-and high-latitude atmospheric circulation over the Eurasian continent and the western Pacific subtropical high (WPSH). In addition, a strong blocking high over the Ural Mountains accompanied by intense mid-latitude westerly winds prevented cyclonic disturbances from extending to the subtropical region. As a result, under the combined effect of the weaker-than-normal cold-air activities and the anomalous WPSH, the TGR experienced extreme high-temperature weather during early autumn 2021.

根据近60年华北地区236站逐日降水量资料和2021年夏季NCEP再分析资料,对2021年中国华北雨季的气候特征及其成因进行分析.结果表明,2021年华北雨季于7月12日开始,较常年偏早6 d;于9月9日结束,较常年偏晚22 d;平均雨量为276.4 mm,较常年偏多103.2％;雨季长度为59 d,为1961年以来的第2长.2020年8月至2021年4月的拉尼娜事件是2021年华北雨季偏强的重要外因,也是最重要的年际预测信号;另外,2020年冬季和2021年春季青藏高原积雪偏少是2021年我国北方降水偏多的另一年际预测信号.而造成2021年华北雨季偏强的直接原因则是大气环流异常,500 hPa东亚中高纬呈现"东高西低"的距平环流分布,贝加尔湖至我国长江下游的大槽非常有利于冷空气的南下,850 hPa我国长江以北地区受到异常气旋环流东北侧的偏南风距平控制,给北方地区带来良好的水汽输送.冷暖空气在北方地区交汇,造成华北东部等地降水偏多.

2020年10月至2021年2月上旬,受拉尼娜事件和大气环流异常的共同影响,我国江南南部、华南大部及西南的云南等地降水量较常年同期明显偏少,2020年11月上旬气象干旱开始露头并迅速发展,出现了较为严重的秋冬连旱.此次干旱过程影响范围广、干旱日数多、强度强,造成江南、华南及西南的云南等地湖库蓄水大幅减少,森林火险气象等级偏高.2021年2月8—11日,我国南方地区出现明显降水,江南、华南气象干旱解除,但西南的云南等地干旱仍然持续.从气候特征、干旱演变过程入手,分析了此次干旱过程的特点及气候成因,以期为从事气候影响评价和服务的科研人员提供相关信息,同时也为防旱抗旱工作提供参考依据.

2019年秋季,我国大部地区气温较常年同期偏高,全国平均气温为1961年以来同期第三高;降水空间分布非常不均匀,呈"西多东少、北多南少"的特征.异常成因分析表明,秋季欧亚中高纬度槽脊活动频繁,冷空气势力接近常年同期,西太平洋副热带高压较常年同期偏强偏西偏北,副热带高压西段位于南海西侧上空,有利于西南暖湿水汽向我国西部地区输送,菲律宾东北部为较强的气旋距平环流控制,导致我国南方地区受偏北气流控制,水汽条件偏差.进一步研究表明,海温异常是影响2019年秋季我国气候异常的最主要外强迫因子,2019年7月弱的中部型El Ni?o事件结束,秋季海温分布偏向于中部型El Ni?o.东亚副热带环流显示出清晰的响应.

West China is one of the country’s largest precipitation centres in autumn. This region’s agriculture and people are highly vulnerable to the variability in the autumn rain. This study documents that the water vapour for West China autumn precipitation (WCAP) is from the Bay of Bengal, the South China Sea and the Western Pacific. A strong convergence of the three water vapour transports (WVTs) and their encounter with the cold air from the northern trough over Lake Barkersh-Lake Baikal result in the intense WCAP. Three predictors in the preceding spring or summer are identified for the interannual variability of WCAP: (1) sea surface temperature in the Indo-Pacific warm pool in summer, (2) soil moisture from the Hexi Corridor to the Hetao Plain in summer and (3) snow cover extent over East Europe and West Siberian in spring. The cold SSTAs contribute to an abnormal regional meridional circulation and intensified WVTs. The wet soil results in greater air humidity and anomalous southerly emerging over East Asia. Reduced snow cover stimulates a Rossby wave train that weakens the cold air, favouring autumn rainfall in West China. The three predictors, which demonstrate the influences of air-sea interaction, land surface processes and the cryosphere on the WCAP, have clear physical significance and are independent with each other. We then develop a new statistical prediction model with these predictors and the multilinear regression analysis method. The predicted and observed WCAP shows high correlation coefficients of 0.63 and 0.51 using cross-validation tests and independent hindcasts, respectively.

Sever floods occurred in southern China and droughts were prevalent in northern China in the summer of 2014.Most predicted models in China missed the southern rain band in their flood season predictions conducted in March 2014,which led to relatively low prediction accuracy.Based on the higher prediction skill for summer sea level pressure of climate models and the significant relationship between the preceding winter Tibetan Plateau Snow and summer precipitation in the south,a new Hybrid Statistical Downscaling Prediction (abbreviated as HSDP) method for summer precipitation anomaly prediction in China was proposed in this paper.The method can integrate the information of the highly predictable circulation from climate models and the influential signal of Tibet Plateau Snow in the preceding winter to improve the dynamical-statistical combination prediction for summer precipitation in the south.Using this method,a statistical downscaling model was established based on the climate prediction model of National Climate Center of China.The cross validation of seasonal prediction for the summer precipitation in the south was performed and the results showed that the HSDP improved the multi-year average of anomaly correlation coefficient from-0.006 to 0.24,and it had a higher predicting skill than the original climate model in most years.Using HSDP,the precipitation prediction for the summer of 2014 could well capture the basic situations,i.e.floods in southern China and droughts in northern China,and the positive precipitation anomaly in the south.The anomaly correlation coefficient could reach 0.43.This result indicated that the HSDP has a great operational application prospect with regard to summer precipitation prediction in China.

The data of daily precipitation in the mid-lower reaches of the Yangtze River and the reanalysis data of NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research)which have been treated with the physical decomposition on atmospheric variables were used to study the significant char-acteristics of the low-frequency atmospheric disturbances during heavy rainfall events in 1998 based on the methods of Morlet wavelet analysis and Lanczos band-pass filters.The results show that before August it is the precipitation high incidence period,especially for the rainstorms in the mid-lower reaches of the Yangtze River in 1998.There are two kinds of low-frequency oscillations during heavy rainfall events;the 12-24 days low-frequency oscillations (LFO)mainly occur from January to April,and the 30-60 days LFO usually occur from June to August.Heavy rainfall events during January to April in this region are related to the 12-24 days low-frequency disturbed cyclones (or anticyclones)at 850 hPa that move eastward from the Sichuan Basin vicinity in the east side of the Tibetan Plateau,while the heavy rainfall events during May to August are related to the 30-36 days low-frequency disturbed cyclones (or anticyclones)that move westward from the sea surface of the south of the Japan main island.The geopotential height field of the 12-24 days low-frequency disturbances shows a vertical baroclinic structure,and its central axis tilts towards the west,which is different from that of the 30-60 days low-frequency disturbances charac-terized by barotropicity.The strongest signals of 12-24 days low-frequency disturbances that cause the heavy rain-fall from January to April in this region are located around 925-850 hPa and originate from the east side of the Ti-betan Plateau and the mid-high latitudes,respectively.However,the strongest signals of 30-60 days low-frequency disturbances are mostly located around 850-500 hPa and are generated from the eastern and central parts of the Pa-cific Ocean and the near place of the equator,respectively.