Estimating the probability and consequences of drought disasters is an important task in drought risk assessment, which contributes to the development of mitigation strategies. Based on rainfall data from 2481 stations and the drought-affected arable land of each province from 1961 to 2021, a probabilistic analysis model of drought duration, drought severity and the proportion of affected farmland area (PAFA) was constructed by a three-dimensional copula function. The results show that the distribution functions of drought duration, drought severity and the PAFA are well given based on the principle of maximum entropy and can pass the Kolmogorov–Smirnov (K-S) distribution test with a significance level of 0.05. Among the three Archimedean copulas, Frank’s method has a relatively better accuracy, suggesting that it captures the dependencies between drought characteristics better and is more suitable for constructing joint distribution functions. The value of PAFA in Gansu, Inner Mongolia, Shanxi and Liaoning is about 0.3, which is higher than other provinces. Drought duration and drought severity levels of 3 to 4 are the main causes of a PAFA greater than 0.3, which can be used as an early warning line for drought risk. At the same level of PAFA, the drought in the southern region lasted longer and was more intense.

In recent years, the dry-wet transition (DWT), which often leads to regional floods and droughts, has become increasingly frequent in the Poyang Lake basin and the Dongting Lake basin (hereinafter referred to as the two-lake region). This study aims to investigate the early warning signals (EWSs) for DWT events. Firstly, based on the standardized precipitation index (SPI) at 161 meteorological stations in the two-lake region from 1961 to 2020, the two-lake region is divided into four sub-regions by the Rotational Empirical Orthogonal Function (REOF) analysis method. Then, the occurrence time of the DWT events in each sub-region is determined by the moving t-test (MTT) technique. Finally, by using two indicators (variance and the auto-correlation coefficient) to describe the critical slowing down (CSD) phenomenon, the EWSs denoting the DWT events in all sub-regions are investigated. The results reveal that there was a significant dry-to-wet (wet-to-dry) event around 1993 (2003) in the two-lake region during the last 60 years. The phenomenon of CSD, where the auto-correlation coefficient and variance increases are found in all sub-regions around 10 years before the DWT, suggests that it can be taken as an EWS for the DWT events. This study confirms the effectiveness of applying the slowing down theory in investigating the EWSs for abrupt changes in the two-lake region, aiming to provide a theoretical basis for effective prevention and mitigation against disasters in this region. Moreover, it is expected to be well-applied to the middle and lower reaches of the Yangtze River.

This paper takes Poa annua L. as the research object and studies the law of physiological and ecological stress of 1-Chloronaphthalene (CN-1) and Octachloronaphthalene (CN-75) by using various physiological and biochemical indexes of Poa annua L. cultivated with soil under the stress of CN-1 and CN-75 of different concentrations. According to the research, the chlorophyll a and b first increase and then decrease with the increase of the concentration of CN-1, and continue to decrease with the increase of CN-75; Soluble sugar and soluble protein in plants decrease first and then increase with the increase of CN-1, and continue to decrease with the increase of CN-75; MDA in plants increases first and then decreases with the increase of the concentration of CN-1 and CN-75. The proline content in plants also increases first and then decreases with the increase of concentration of CN-1 and CN-75. Based on the research, it can be seen that the tolerance of the plant to CN-75 is not good as to CN-1.

The spring sand-dust weather can be disastrous in China. It seriously endangers agricultural production, transportation, air quality, people’s lives and property, and is a subject of sustained and extensive concern. Currently, few studies have been conducted to analyze sand-dust events in North China from the perspective of sand-dust processes. Although there are a few studies on the spatio-temporal variation characteristics of sand-dust processes, they are mainly based on outdated data or case studies of major sand-dust events. In this study, the evolution characteristics of sand-dust processes in China over the last 60 years are studied based on the identification method and several characteristic quantities (including duration and impact range) of sand-dust weather processes defined in the Operational Regulations of Monitoring and Evaluation for Regional Weather and Climate Processes newly issued by the China Meteorological Administration in 2019. First, through statistics, we obtain the annual occurrence frequency, annual days, and the annual number of affected stations of sand-dust processes (including sand-dust storms, blowing sand, and suspended dust) from January 1961 to May 2021. Based on the Mann–Kendall test (MK) and Ensemble Empirical Mode Decomposition (EEMD), we analyzed evolution trends and probability distribution characteristics of annual occurrence frequency, annual days, and the annual number of affected stations of sand-dust processes. In addition, we investigate the start time of the first and the last dust processes in each of the past 60 years, as well as the seasonal distribution characteristics of sand-dust processes. The results show that under the background of global warming, the sand-dust weather in China tends to decrease significantly. Specifically, the annual occurrence frequency and annual days showed an upward trend before the 1980s and a significant downward trend after that, as well as the significant turnarounds in the annual number of dust processes that occurred in the 1990s and around 2010. Moreover, the sand-dust processes tend to start later and end earlier. The sand-dust processes are mainly concentrated between March and May, with the highest occurrence probability in April.

This report is a summary of China's climate, as well as major weather and climate events, during 2021. In 2021, the mean temperature in China was 10.5 degrees C, which was 1.0 degrees C above normal (1981-2010 average) and broke the highest record since 1951. The annual rainfall in China was 672.1 mm, which was 6.7% above normal. Also, the annual rainfall in northern China was 40.2% above normal, which ranked second highest since 1961. The rainstorm intensity in the rainy season was strong and featured significant extremes, and disasters caused by rainstorms and flooding were more serious than the average in the past decade. In particular, the extremely strong rainstorm in Henan during July and autumn caused flooding in the middle and lower reaches of the Yellow River with severe consequences. Heatwaves occurred more frequently than normal, and their durations in southern China were longer than normal in summer and autumn. Phased drought was obvious, and caused serious impacts in South China. The number of generated and landfalling typhoons was lower than normal; however, Typhoon In-fa broke the record for the longest overland duration, held since 1949, and affected a wide area. Severe convective weather and extreme windy weather occurred frequently, causing serious impacts. The number of cold waves was more than normal, which caused wide-ranging extremely low temperatures in many places. Sandstorms appeared earlier than normal in 2021, and the number of strong dust storm processes was more than normal.

本文基于临界慢化的理论,采用太平洋年代际振荡(Pacific Decadal Oscillation,PDO)指数的近百年(1900～2019年)历史数据及未来百年(2006～2100年)模式模拟数据,首先通过滑动t检验确定PDO位相转变的时间,进而借助于表征临界慢化现象的方差和自相关系数,研究了PDO年代际位相转折的早期预警信号.结果表明:(1)近百年来PDO发生了4次显著的位相转变,每次位相转变前的5～10年可以提取到早期预警信号;(2)通过对CMIP5气候模式资料计算得到的PDO进行统计合成得到未来百年的PDO序列,检测结果表明在2040年和2080年前后发生年代际转折,转折前的5～10年能够检测到早期预警信号;(3)近百年和未来百年PDO序列的位相转变及早期预警信号研究证实在PDO发生位相转变之前方差和自相关系数总能提前数年给出预警信号,也揭示了未来PDO的转折时间.

Extreme precipitation occurring on consecutive days may substantially increase the risk of related impacts, but changes in such events have not been studied at a global scale. Here we use a unique global dataset based on in situ observations and multimodel historical and future simulations to analyze the changes in the frequency of extreme precipitation on consecutive days (EPCD). We further disentangle the relative contributions of variations in precipitation intensity and temporal correlation of extreme precipitation to understand the processes that drive the changes in EPCD. Observations and climate model simulations show that the frequency of EPCD is increasing in most land regions, in particular, in North America, Europe, and the Northern Hemisphere high latitudes. These increases are primarily a consequence of increasing precipitation intensity, but changes in the temporal correlation of extreme precipitation regionally amplify or reduce the effects of intensity changes. Changes are larger in simulations with a stronger warming signal, suggesting that further increases in EPCD are expected for the future under continued climate warming.

In this study, the temporal variation of actual evapotranspiration (AE) over China during 1980–2015 is analysed based on an ensemble of six reanalyses and a complementary‐relationship‐based AE dataset. The results reveal that annual mean AE in China increases significantly, and the major regime shift occurred around 1998. Accordingly, long‐term mean AE changes from 1999–2015 relative to 1980–1997 are computed to quantify the spatial pattern of AE trends. In general, annual AE increases significantly in southern and northwestern China but decreases significantly in northeastern China and eastern Tibetan Plateau. Then we examine the primary cause for changes in AE using the Budyko framework, in which the change of climate is represented by changes in precipitation and potential evapotranspiration and the shift in landscape characteristics is represented by the parameter n. Overall, increasing potential evapotranspiration is the main contributor to the increase of AE in southeastern China. Increasing potential evapotranspiration and the parameter n are the main contributors to the increase of AE in southwestern China. Decreasing AE in northeastern China and eastern Tibetan Plateau are respectively caused by changes in precipitation and the parameter n, whereas the combination of these two factors has led to increasing AE in northwestern China. It is shown here that the contribution of the parameter n is comparable to that of climate change in western China. A positive correlation is found between vegetation coverage and the parameter n; however, vegetation type, catchment slope, irrigation practices, and glacial meltwater also have an impact on regional n. A concurrent occurrence of the negative contribution of parameter n and positive vegetation coverage change is found in the forest land of northeastern and southeastern China. Decreasing irrigation water is likely the main reason for the negative contribution of n in cropland of the North China Plain.

At present, high-resolution drought indices are scarce, and this problem has restricted the development of refined drought analysis to some extent. This study explored the possibility of calculating the standardized precipitation index (SPI) with short-term precipitation sequences in China, based on data from 2416 precipitation observation stations covering the time period from 1961 to 2019. The result shows that it is feasible for short-sequence stations to calculate SPI index, based on the spatial interpolation of the precipitation distribution parameters of the long-sequence station. Error analysis denoted that the SPI error was small in east China and large in west China, and the SPI was more accurate when the observation stations were denser. The SPI error of short-sequence sites was mostly less than 0.2 in most areas of eastern China and the consistency rate for the drought categories was larger than 80%, which was lower than the error using the 30-year precipitation samples. Further analysis showed that the estimation error of the distribution parameters β and q was the most important cause of SPI error. Two drought monitoring examples show that the SPI of more than 50,000 short-sequence sites can correctly express the spatial distribution of dry and wet and have refined spatial structure characteristics.

In the calculation of the standardized precipitation index (SPI) index, it is necessary to select a certain period of precipitation samples as the reference climate state, and the SPI obtained by different reference climate states have different size. Therefore, the influence of different reference climate states on the accuracy of SPI calculation is worth analyzing. Based on the monthly precipitation data of 1184 stations in China from 1961 to 2010, the influence of the selection of the reference climatic state in the calculation of SPI was analyzed. Using 30 consecutive years as the duration of the reference climatic state, 1961–2010 is divided into three periods 1961–1990, 1971–2000, 1981–2010. Taking the SPI obtained from the entire period as the standard value, the spatial distribution of SPI error and the accuracy of SPI classification based on each reference period were analyzed. Then, the resampling method was used to analyze the influence of time-continuous precipitation samples on the size of SPI. The results show that the SPI error of most sites is less than 0.2, and the accuracy of SPI classification is more than 80%. Although the errors of SPI mostly come from extreme drought and extremely wet, this does not affect the accuracy of the recognition of extreme drought and extremely wet. In most regions, it is reliable to calculate SPI based on the precipitation data of continuous 30 years, but the reliability of SPI is relatively low in areas with frequent drought. The results of the resampling analysis and 30-year sliding analysis show that the distribution parameters have noticeable turning characteristics, and the precipitation distribution parameters of nearly 85% stations had noticeable turning point before 1985, which led to the precipitation data of continuous 30 years easily overestimate the dry/wet.

In this study, the standardized precipitation index (SPI) data in Hunan Province from 1961 to 2020 is adopted. Based on the critical slowing down theory, the moving t-test is firstly used to determine the time of drought-flood state transition in the Dongting Lake basin. Afterwards, by means of the variance and autocorrelation coefficient that characterize the phenomenon of critical slowing down, the early-warning signals indicating the drought-flood state in the Dongting Lake basin are explored. The results show that an obvious drought-to-flood (flood-to-drought) event occurred around 1993 (2003) in the Dongting Lake basin in recent 60 years. The critical slowing down phenomena of the increases in the variance and autocorrelation coefficient, which are detected 5–10 years in advance, can be considered as early-warning signals indicating the drought-flood state transition. Through the studies on the drought-flood state and related early-warning signals for the Dongting Lake basin, the reliabilities of the variance and autocorrelation coefficient-based early-warning signals for abrupt changes are demonstrated. It is expected that the wide application of this method could provide important scientific and technological support for disaster prevention and mitigation in the Dongting Lake basin, and even in the middle and lower reaches of the Yangtze River.

Actual evapotranspiration (AE) is a crucial processes in terrestrial ecosystems. Global warming is expected to increase AE; however, various AE estimation methods or models give inconsistent trends. This study analyzed AE variability in China during 1982–2015 based on the Budyko framework (AE_Budyko), a complementary-relationship-based product (AE_CR), and the weighted average of six reanalyses (AE_WAR). Because the response of AE to driving factors and the performances of AE datasets are both scale-dependent, China has been categorized into six distinct climatic areas. From a regional perspective, the X-12-ARIMA method was used to decompose monthly AE into the trend, seasonal, and irregular components. We examined the main characteristics of these components and the relationships of climate factors with AE. The results indicate that the trend component of AE increased from the mid-1990s to the early 2000s and more recently in the hyper-arid and arid areas. Increasing AE was observed from 1982 to the early 1990s in the semi-arid and dry sub-humid areas. AE increased significantly and had substantial interannual variability for the entire period in the sub-humid and humid areas. Increased precipitation and water supply from terrestrial water storage contributed significantly to increasing AE in the drylands. The simultaneous occurrence of increasing precipitation and wet-day frequency caused increasing AE in the dry sub-humid area. Increased AE could be explained by the increased energy supply and precipitation in the sub-humid and humid areas. Precipitation had the strongest influence on the irregular component of AE in drylands. AE and potential evapotranspiration had a strong positive correlation in the sub-humid and humid areas. Regarding data availability, a discrepancy existed in the trend component of AE_CR because soil moisture was not explicitly considered, whereas the irregular component of AE_Budyko contained distinct variations in humid and sub-humid areas.

Droughts have more impact on crops than any other natural disaster. Therefore, drought risk assessments, especially quantitative drought risk assessments, are significant in order to understand and reduce the negative impacts associated with droughts, and a quantitative risk assessment includes estimating the probability and consequences of hazards. In order to achieve this goal, we built a model based on the three-dimensional (3D) Copula function for the assessment of the proportion of affected farmland areas (PAFA) based on the idea of internally combining the drought duration, drought intensity, and drought impact. This model achieves the “internal combination” of drought characteristics and drought impacts rather than an “external combination.” The results of this model are not only able to provide the impacts at different levels that a drought event (drought duration and drought intensity) may cause, but are also able to show the occurrence probability of impact at each particular level. We took Huize County and Mengzi County in Yunnan Province as application examples based on the meteorological drought index (SPI), and the results showed that the PAFAs obtained by the method proposed in this paper were basically consistent with the actual PAFAs in the two counties. Moreover, due to the meteorological drought always occurring before an agricultural drought, we can get SPI predictions for the next month or months and can further obtain more abundant information on a drought warning and its impact. Therefore, the method proposed in this paper has values both on theory and practice.

Abstract. Climate change could be expressed as a climate system transiting from the initial state to a new state in a short time. By considering the short period as a continued process, which is called transition process, more details of climate change would be described according to analysis the time sequence self. We had proposed a method to quantify the transition process of the Pacific Decadal Oscillation (PDO) time sequence and global sea surface temperature system. And the quantitative relationships among the parameters characterizing the abrupt changes is revealed during the transition process. In this paper, we develop this method to predict the end moment (state) if the transition process has not been completed. Application of prediction method to the PDO sequences indicates that the PDO index increased from a stable stage before 2011 and gradually evolved to a transition process, and it was likely to end in 2015, which is consistent with observations.

Extreme precipitation often persists for multiple days with variable duration but has usually been examined at fixed duration. Here we show that considering extreme persistent precipitation by complete event with variable duration, rather than a fixed temporal period, is a necessary metric to account for the complexity of changing precipitation. Observed global mean annual‐maximum precipitation is significantly stronger (49.5%) for persistent extremes than daily extremes. However, both globally observed and modeled rates of relative increases are lower for persistent extremes compared to daily extremes, especially for Southern Hemisphere and large regions in the 0‐45°N latitude band. Climate models also show significant differences in the magnitude and partly even the sign of local mean changes between daily and persistent extremes in global warming projections. Changes in extreme precipitation therefore are more complex than previously reported, and extreme precipitation events with varying duration should be taken into account for future climate change assessments.

This study used the daytime hourly precipitation records and divided them into four types of duration to examine the impact of different daytime precipitation conditions on Urban Heat Island Intensity (UHII) over Beijing city. Results show that the magnitude differences of UHII are in close relation with the length of Continuous Precipitation Hours of Daytime (CPHD). The longer the CPHD, the less obvious the average UHI. When continuous precipitation events dominate the daytime, the diurnal variation pattern of UHII will be changed greatly. There are generally two (strong and weak) stable stages of UHII in no-rainy condition, while it disappears completely in the longest continuous daytime precipitation conditions. However, the diurnal cycles of UHII differences between each of the rainy daytimes and no-rain daytimes appear similar, with all of the dual peaks of the UHII differences occurring around sunrise (0600-0700 LST) and sunset (2000 LST), and the minimum of the UHII differences appearing stably from 1100 to 1500 LST.

2018年,我国气候属于正常年景,气候灾害偏轻.全国平均气温为10.09℃,较常年偏高0.54℃,春、夏季气温创历史新高,秋、冬季气温接近常年.全国平均降水量为673.8 mm,较常年偏多7.0％.全国降水夏、秋季偏多,冬季偏少,春季接近常年同期.华南前汛期开始晚,结束早,雨量少;西南雨季开始和结束均接近常年,雨量多;入梅晚、出梅早,梅雨量少;华北雨季开始和结束均早,雨量多;华西秋雨开始和结束均晚,雨量少;东北雨季开始和结束均接近常年,雨量少.2018年,生成和登陆台风多、登陆位置偏北、灾损严重.低温冷冻害及雪灾频发,损失偏重.其他气象灾害,如暴雨洪涝、干旱、强对流、沙尘暴影响均偏轻.

A major experimental drought research project entitled "Mechanisms and Early Warning of Drought Disasters over Northern China" (DroughtEX_China) was launched by the Ministry of Science and Technology of China in 2015. The objective of DroughtEX_China is to investigate drought disaster mechanisms and provide early-warning information via multisource observations and multiscale modeling. Since the implementation of DroughtEX_China, a comprehensive V-shape in situ observation network has been established to integrate different observational experiment systems for different landscapes, including crops in northern China. In this article, we introduce the experimental area, observational network configuration, ground- and air-based observing/testing facilities, implementation scheme, and data management procedures and sharing policy. The preliminary observational and numerical experimental results show that the following are important processes for understanding and modeling drought disasters over arid and semiarid regions: 1) the soil water vapor-heat interactions that affect surface soil moisture variability, 2) the effect of intermittent turbulence on boundary layer energy exchange, 3) the drought-albedo feedback, and 4) the transition from stomatal to nonstomatal control of plant photosynthesis with increasing drought severity. A prototype of a drought monitoring and forecasting system developed from coupled hydroclimate prediction models and an integrated multisource drought information platform is also briefly introduced. DroughtEX_China lasted for four years (i.e., 2015-18) and its implementation now provides regional drought monitoring and forecasting, risk assessment information, and a multisource data-sharing platform for drought adaptation over northern China, contributing to the global drought information system (GDIS).

Climate in China was at a normal level in 2017 and relatively fewer climate disasters occurred. Annual mean temperature 10.39℃ over China was 0.84℃ higher than normal years.In terms of high tem-perature,July and September had the highest temperature compared to that in the same periods since 1951,and the day highs at 113 stations broke the historical records.The annual mean precipitation over China was 641.3 mm,which increased 1.8% than normal years.Compared with the normal,precipitation was less in winter and more in summer,and approached normal in spring and autumn.The daily rainfall at 31 stations exceeded historical extremes,of which many stations were found in the areas where torrential rain seldom occurs.Besides,the continuous precipitation at 47 stations exceeded historical extremes.Pre-cipitation in the pre-flood season in South China and in rainy season in Southwest China decreased by 9% and 4%,respectively.Precipitation in Meiyu season increased by 6% but was significantly less than that of 2015 and 2016.The rainy season in North China was shortened by 10 days and the rainfall was 28% less than normal.However,the autumn rainfall in West China increased by 49%,getting to the highest since 1984.The rainy season in Northeast China was short with rainfall 14% less than normal.Moreover,rain-storm processes presented frequently,and extremely severely,resulting in great damages.There were more landing typhoons,which were more frequent,concentrated and regionally overlapping.High temperature occurred for more days in China,appearing early in northern China but more intense in sou-thern China.The effects of other disasters such as drought,freezing,snowstorms,dust in spring and haze were light.