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The household is the basic unit of a residential community or building. High-resolution, long-term open data are necessary to help study residential electricity consumption, smart home technologies, and electricity flexibility technologies at household level. This paper introduces an IoT-based data collection platform (IDCP) consisting of gateways, sensors, and cloud servers. This platform can collect data on the occupant presence, indoor environment, window-opening states, and appliance electricity consumption simultaneously. This study deployed the IDCP in a single-family apartment in Beijing, China, and compiled a dataset, namely, CN-OBEE, including data on the per-minute occupant behavior, thermal environment, and appliance electricity use of the apartment for an entire year (from May 31, 2021, to May 31, 2022), and hourly meteorological data collected by the nearest national weather station during the same period. This dataset is the first detailed and publicly available occupant behavior and electricity use dataset for Chinese homes. As a regional feature, the dataset compiled by this study includes window-opening behavior and the use of split air conditioners (ACs). [ABSTRACT FROM AUTHOR]

The summer monsoon–affected area is a suitable area for agricultural production in China. Against the background of climate warming, the activity of the summer monsoon is changing significantly. The drought and flood disasters in this region are becoming more and more frequent and have a greater and more serious impact on agricultural production. Therefore, based on observational data from meteorological stations and yield loss data in agriculture caused by drought and flood disasters in summer monsoon–affected areas, this paper studied the characteristics of the hazard of disaster-causing factors, the risk of losses to agriculture caused by droughts and floods, and their correlation. Moreover, it compared and analyzed the variability of drought and flood hazard and risk to agriculture before and after a temperature rise. The results showed that the precipitation in summer monsoon–affected areas is obviously affected by monsoon activities, and there is an overall though non-significant positive correlation between annual average standardized precipitation evapotranspiration index (SPEI) and the summer monsoon activity index (MI). The drought disaster comprehensive loss rate (DCLR) was generally higher than the flood disaster comprehensive loss rate (FCLR). This shows that the impact of drought on agriculture production is significantly greater than that of floods in this area. The high hazard and risk areas for drought were mainly distributed along the edge of the summer monsoon area and in its vicinity, whereas the high hazard and risk areas for flooding were mainly distributed in the lower reach of the Yangtze, Songhua, and Liaohe Rivers. Among them, Liaoning, Jilin and Heilongjiang are high-risk superposition areas of drought and flood disasters. The hazards of drought and flood dominate the risk of disaster loss. Climate warming has significantly expanded the high-hazard and high-risk ranges in China for drought and flood disasters and has also changed their spatial distribution patterns. The high-hazard area for drought has shifted to the monsoon edge area, the high-risk area for drought has moved northward, and both the high-hazard and the high-risk areas for floods have clearly moved southward. The impact of climate warming on drought was more significant than on floods. This study provides important scientific guidance for formulating drought and flood disaster prevention planning and agricultural production development patterns in China. [ABSTRACT FROM AUTHOR]

Based on the precipitation records of 2474 meteorological stations, this study investigated precipitation characteristics and trends in China from 1961 to 2010, including spatiotemporal distribution and changes in average annual precipitation amount, number of days when daily precipitation > = 1, 5, 10, 25, 50 mm, and extreme precipitation indices. The results showed that: (1) in terms of annual average precipitation amount, both dry to wet, wet to wetter, and shifting between wet and dry showed decadal and climatical fluctuations in annual precipitation totals in space and time, with a clear shift in space from the 0 to 200 mm and above 400 mm precipitation levels to the 200 to 400 mm precipitation level. (2) In terms of graded precipitation days, three kinds of trend changes were observed: (a) enhancement, manifested as an increase in precipitation events, mainly in the northwest and northeast of China; (b) reduction, manifested as a decrease in precipitation events, mainly in the central parts of China; and (c) polarization, which is manifested as a decrease in gentle and light precipitation events but an increase in dry days, heavy, and rainstorm precipitation events, primarily along coastal area in southeast China. (3) In terms of extreme precipitation events, precipitation persistence showed a decreasing trend, but an increasing trend in precipitation intensity and magnitude in most regions of China. This paper also presents the relationship between certain atmospheric circulation indices and the seasonal precipitation of summer and winter. The distribution characteristics and changes in minor precipitation events were highlighted, including gentle and light rain events. Relevant findings can provide scientific guidance for water resource management and conservation. [ABSTRACT FROM AUTHOR]

Climate is an important tourism resource and a vital component of the attractiveness of a destination. Climate has a strong impact on supply and demand in the tourism industry. Most studies concerning the distribution of tourism climate resources are based on point measurements from meteorological stations. Tourism climate distribution maps with high resolution are required. In this paper, the tourism climate index (TCI) and spatial interpolation based on polynomial regression are used to analyze the distribution of summer tourism climate resources in China. The results indicate that there exists an obvious positive linear relationship between the TCI and latitude and a quadratic relationship between the TCI and elevation. The tourism climate is unfavorable in 8% of the study area, acceptable in 34% of the study area, good and very good in 36% of the study area, and excellent in 22% of the study area. From the perspective of climate, the places comfortable for summer tourism are mainly concentrated to the north of 35°N, on the second elevation step, and in the temperate continental climate zone. The tourism climate information provided is accurate at the 90% level for most areas. [ABSTRACT FROM AUTHOR]

Growing evidence indicates that extreme heat and rain may occur in succession within short time periods and cause greater impacts than individual events separated in time and space. Therefore, many studies have examined the impacts of compound hazard events on the social-ecological system at various scales. The definition of compound events is fundamental for such research. However, there are no existing studies that support the determination of time interval between individual events of a compound rainstorm and heatwave (CRH) event, which consists of two or more potentially qualifying component heatwave and rainstorm events. To address the deficiency in defining what individual events can constitute a CRH event, this study proposed a novel method to determine the maximum time interval for CRH events through the change in CRH event frequency with increasing time interval between individual events, using southern China as a case study. The results show that the threshold identified by the proposed method is reasonable. For more than 90% of the meteorological stations, the frequency of CRH events has reached a maximum when the time interval is less than or equal to the threshold. This study can aid in time interval selection, which is an important step for subsequent study of CRH events. [ABSTRACT FROM AUTHOR]

Based on daily mean temperature data from 32 meteorological stations in the study area, this paper discusses the relationship between the changes in the climatic growing season and altitude and the differences in the northern (NSQM) and southern (SSQM) slopes of the Qinling Mountains (QMs) from 1985 to 2015. Our analyses generated three primary results. First, the spatial distribution patterns of the growing season start (GSS), growing season end (GSE), and growing season length (GSL) exhibited an altitudinal gradient and differences between the NSQM and SSQM. The occurrence time of the GSS, GSE, and the GSL of the NSQM was approximately 15 days later, 10 days earlier, and 25 days shorter respectively than that of the SSQM. Second, the three factors exhibited regular changes with an increasing elevation gradient: the GSS, GSE, and GSL were gradually delayed, advanced, and shortened, respectively. In the area below 1800 m above sea level, the GSS, GSE, and GSL of the NSQM was later, earlier, and shorter, respectively, than that of the SSQM; while the changing trends in the three were opposite in the areas above 2700 m; and the three in the areas between 1800 and 2700 m varied little in the NSQM and SSQM. The sensitivities of the GSS, GSE, and GSL of the NSQM and SSQM to elevation also reflected in the trends of inter-annual variability. Third, among the different altitudinal vegetation belts from low-altitude to high-altitude areas, the occurrence time of the GSS and GSE and the duration of the GSL in the alpine meadow areas were all exchanged in the NSQM and SSQM. The GSS, GSE, and GSL of the NSQM were earlier, later, and longer respectively than that of the SSQM. [ABSTRACT FROM AUTHOR]

Near-surface atmospheric moisture is a key environmental and hydro-climatic variable that has significant implications for the natural and human systems. However, high-resolution moisture data are severely lacking for fine-scale studies. Here, we develop the first 1 km high spatial resolution dataset of monthly moisture index collection in China (HiMIC-Monthly) over a long period of 2003~2020. HiMIC-Monthly is generated by the light gradient boosting machine algorithm (LightGBM) based on observations at 2,419 weather stations and multiple covariates, including land surface temperature, vapor pressure, land cover, impervious surface proportion, population density, and topography. This collection includes six commonly used moisture indices, enabling fine-scale assessment of moisture conditions from different perspectives. Results show that the HiMIC-Monthly dataset has a good performance, with R2 values for all six moisture indices exceeding 0.96 and root mean square error and mean absolute error values within a reasonable range. The dataset exhibits high consistency with in situ observations over various spatial and temporal regimes, demonstrating broad applicability and strong reliability. [ABSTRACT FROM AUTHOR]

Amidst the escalating impacts of global warming, the occurrence and severity of compound extreme weather events have risen significantly, presenting substantial threats to both lives and property. Existing response strategies predominantly focus on individual events, often overlooking the cumulative effects rising from their inherent complexity. To address this critical gap, we conducted a thorough examination of sequential extreme precipitation–heatwave compound events (SEPHCE) in China from 1975 to 2020, utilizing data from 1929 meteorological stations. Our investigation revealed a consistent rise in the frequency and duration of SEPHCE, with a particularly notable surge since 1993. Furthermore, shorter interval events disproportionately affected the regions of southwestern and southeast coastal China. Furthermore, SEPHCE onset times exhibited advancement, and the endings were delayed, thereby intensifying the overall trend. These findings underscore the pressing need to prioritize effective planning and adaptation strategies to mitigate the impact of these compound event, while also addressing the potential exacerbation of inequality resulting from climate change. [ABSTRACT FROM AUTHOR]

In this paper, the daily precipitation data measured at 58 meteorological stations were used, and the spatial and temporal variability of daily precipitation and precipitation extrema in the Yangtze River Delta (YRD) during 1958-2007 was investigated using the indicator of discrete wavelet entropy; then, the urbanization effects were further analyzed. Results indicate that the daily precipitation variability in YRD, especially in the mid YRD with highly urbanized city clusters, is determined by the comprehensive impacts of atmospheric circulation, urbanizations, and the Taihu Lake. Compared with the results in 1958-1985, the variability of daily precipitation and precipitation extrema becomes more complex in 1986-2007, and daily precipitation variability is more complex in the mid YRD relative to the north and south. The precipitation extrema with bigger magnitudes show more complex variability. Urbanizations cause more complexity and fluctuations of daily precipitation in the mid YRD in 1986-2007, reflecting more uncertainty of daily precipitation variability, while the urbanization effects vary with regions and precipitation magnitudes. The variability of precipitation extrema with maximum values is mainly determined by natural atmospheric circulation but has little relationship with urbanizations; however, the variability of those precipitation extrema with general values is determined by both urbanizations and the Taihu Lake in YRD over the last three decades. [ABSTRACT FROM AUTHOR]

Land surface temperature(LST) is an important indicator to study climate change and test the performance of regional climate model simulation. RegCM4.6 is the representative version of regional climate model RegCM, which is coupled with advanced third-generation land surface model NCAR CLM4.5. Currently, RegCM4.6 has become an important tool to study regional climate change in China. However, its ability to simulate land surface temperature in mainland China and the reasons for its deviation have not been systematically studied, and targeted improvement work is lacking. The present study is the first to employ LST data collected from 809 Chinese meteorological stations from the last 30 years to comprehensively assess the ability of CLM4.5 to simulate LST. Sensitivity tests of soil thermal conductivity (STC) were carried out to improve the model. Although the coupled regional climate model could accurately simulate the temporal and spatial variation of LST, a cold bias of 2~8 °C existed for all of mainland China, which was larger in seasons with more precipitation and greater soil moisture than other seasons. Deviation increased from southeast to northwest. which was caused by the incoming long-wave radiation, sensible heat, and latent heat simulated. There was a significant linear relationship between the observed and simulated LSTs, with correlation coefficients for all the stations ranged from 0.75 to 0.9 (P < 0.001). The observed LST increased at a rate of 0.58 °C/decade, but the simulated LST increased at a lower rate. Assessment of three different STC schemes showed that the Lu-Ren scheme was the most suitable for LST simulation in mainland China. Developing a new STC scheme that considers the role of water vapor can effectively improve the model when used in mainland China. [ABSTRACT FROM AUTHOR]

Using data collected from 22 urban and 65 rural meteorological stations in northwestern China between 1961 and 2009, this paper presents a study concerning the effects of urbanization on air temperature trends. To distinguish among the potential influences that stem from the economic development levels, population scales, and geographic environments of the cities in this region, the 49-year study period was divided into two periods: a period of less economic development, from 1961 to 1978, and a period of greater economic development, from 1979 to 2009. Each of the cities was classified as a megalopolis, large, or medium-small, depending on the population, and each was classified as a plateau, plain, or oasis city, depending on the surrounding geography. The differences in the air temperature trends between cities and the average of their rural counterparts were used to examine the warming effects of urbanization. The results of this study indicate that the magnitude of warming effects due to urbanization depends not only on a city's economic level, but also on the population scale and geographic environment of the city. The urbanization of most cities in northwestern China resulted in considerable negative warming effects during 1961-1978 but evidently positive effects during 1979-2009. The population scale of a city represents a significant factor: a city with a larger population has a stronger warming influence, regardless of whether the effect is negative or positive. Among the three geographic environments of the cities considered, plateaus and plains more significantly enhance warming effects than oases. The urban population trend has a very significant logarithm relationship with the urban temperature effect, but no clear relationships between urban temperature effects and city elevation were detected. The majority of the temperature trends, accounting for more than 60 % of the trends during 1961-2009, can be explained by natural factors, although urbanization has had some obvious effects on temperatures in northwestern China. [ABSTRACT FROM AUTHOR]

Solar radiation is an essential and important variable to many models. However, it is measured at a very limited number of meteorological stations in the world. Developing method for accurate estimation of solar radiation from measured meteorological variables has been a focus and challenging task. This paper presents the method of solar radiation estimation using support vector machine (SVM). The main objective of this work is to examine the feasibility of SVM and explore its potential in solar radiation estimation. A total of 20 SVM models using different combinations of sunshine ratio, maximum and minimum air temperature, relative humidity, and atmospheric water vapor pressure as input attributes are explored using meteorological data at 15 stations in China. These models significantly outperform the empirical models with an average 14 % higher accuracy. When sunshine duration data are available, model SVM2 using sunshine ratio and air temperature range is proposed. It significantly outperforms the empirical models with an average 26 % higher accuracy. When sunshine duration data are not available, model SVM19 using maximum temperature, minimum temperature and atmospheric water vapor pressure is proposed. It significantly outperforms the temperature-based empirical models with an average of 18 % higher accuracy. The remarkable improvement indicates that the SVM method would be a promising alternative over traditional approaches for estimation of solar radiation at any locations. [ABSTRACT FROM AUTHOR]

Using 51 meteorological stations in the arid region of northwest China in the mountain, oasis, and the desert areas obtained from 1960 to 2010, this paper conducted a comparative analysis for detecting temperature and precipitation changes in the diverse environments. In recent 50 years, temperature has increased at 0.325, 0.339, and 0.360 °C per decade in the mountain, oasis, and the desert areas, respectively; and also, precipitation has increased at 10.15, 6.29, and 0.87 mm per decade, but in which the increasing trend of precipitation in desert area was not significant. Before the 1990s, the increase in temperature was the fastest in the desert area, up to 0.214 °C per decade, but was the slowest in the mountain area, only 0.103 °C per decade. The temperature rising was faster after the 1990s, 0.606 °C per decade, in the oasis area was fastest, but was the slowest in the desert region with 0.402 °C per decade. The precipitation in each area was stable from 1960 to 1986, but an increase in the oasis and mountain area was larger from 1987 to 2010. [ABSTRACT FROM AUTHOR]

This paper focuses on the primary causes of changes in potential evapotranspiration (ETo) in order to comprehensively understand climate change and its impact on hydrological cycle. Based on modified Penman-Monteith model, ETo is simulated, and its changes are attributed by analyzing the sensitivity of ETo to influence meteorological variables together with their changes for 595 meteorological stations across China during the period 1961–2008. Results show the decreasing trends of ETo in the whole country and in most climate regions except the cold temperate humid region in Northeast China. For China as a whole, the decreasing trend of ETo is primarily attributed to wind speed due to its significant decreasing trend and high sensitivity. Relative humidity is the highest sensitive variable; however, it has negligible effect on ETo for its insignificant trend. The positive contribution of temperature rising to ETo is offset by the effect of wind speed and sunshine duration. In addition, primary causes to ETo changes are varied for differing climate regions. ETo changes are attributed to decreased wind speed in most climate regions mainly distributed in West China and North China, to declined sunshine duration in subtropical and tropical humid regions in South China, and to increased maximum temperature in the cold temperate humid region. [ABSTRACT FROM AUTHOR]

This paper presents the patterns and trends of haze over 31 provincial capitals in China between 1980 and 2005. The haze measurements were based on human visual range observations at 31 synoptic meteorological stations operated by the China Meteorological Administration (CMA). The high haze regions were found in largely populated cities such as Chongqing, Beijing, and Shenyang, while the low haze regions were located in the cities with small populations such as Lhasa, Kunming, and Guiyang in southwestern China and Haikou in southern China. The haziness of the 12 cities shows a significantly (95%) decreasing trend, while that of the 13 cities shows a significantly increasing trend over the 25-year study period. The increases are evident in the eastern and southwestern cities in China. It has also been found that there is a decreasing haze trend in winter but an increasing trend in summer for many cities. Nonetheless, the causality for the reduction of aerosol emissions has not been established. This report is the first survey and preliminary analysis done on haze patterns and trends from 1980 to 2005 over the capital cities of 31 provinces in Mainland China. [ABSTRACT FROM AUTHOR]

Climate system anomalies and intensified human disturbances have different impacts on the hydrological cycle at different scales, chiefly leading to prominent spatio-temporal heterogeneities in precipitation distributions. It is of great significance to accurately detect the non-stationary changes of precipitation. Focusing on the Inner Mongolia section of the Yellow River basin which is considered as the key ecological barrier in northern China, the best probabilistic model with time-varying moments was established to fit the wet-season precipitation series from 1988 to 2017 for 38 meteorological stations. Considering four three-parameter distributions, time was used as covariate to describe the linear or nonlinear change of each parameter, and model optimization was performed by Akaike Information Criterion. Combined with conventional methods including the Trend-Free Pre-Whitening Mann–Kendall trend test and Sen's slope estimator, the non-stationary behaviors of wet-season precipitation variability were quantitatively captured. Results showed that the generalized gamma distribution performed best in fitting the wet-season precipitation series in the study area, characterized with high skewness and heavy tails. The non-stationary characteristics of the wet-season precipitation were obvious in most areas during the past 30 years, especially in the central region. The non-stationarities of wet-season precipitation manifested in a downward trend in the mean value, an increase in dispersion degree and significant changes in distribution shape with time, consequently adding the uncertainty to wet-season precipitation process and raising the risk of extreme conditions. The findings of this study provide scientific references to water resources management, drought resistance, and disaster reduction. [ABSTRACT FROM AUTHOR]

Extreme snow loads can collapse roofs. This load is calculated based on the ground snow load (that is, the snow water equivalent on the ground). However, snow water equivalent (SWE) measurements are unavailable for most sites, while the ground snow depth is frequently measured and recorded. A new simple practical algorithm was proposed in this study to evaluate the SWE by utilizing ground snow depth, precipitation data, wind speed, and air temperature. For the evaluation, the precipitation was classified as snowfall or rainfall according to the air temperature, the snowfall or rainfall was then corrected for measurement error that is mainly caused by wind-induced undercatch, and the effect of snow water loss was considered. The developed algorithm was applied and validated using data from 57 meteorological stations located in the northeastern region of China. The annual maximum SWE obtained based on the proposed algorithm was compared with that obtained from the actual SWE measurements. The return period values of the annual maximum ground snow load were estimated and compared to those obtained according to the procedure suggested by the Chinese structural design code. The comparison indicated that the use of the proposed algorithm leads to a good estimated SWE or ground snow load. Its use allowed the estimation of the ground snow load for sites without SWE measurement and facilitated snow hazard mapping. [ABSTRACT FROM AUTHOR]

In China, grape is one of the top five fruit crops for both bearing acreage and production. Recently, national grape production has been stalling because of an increase in drought events. In order to combat the adverse effects of drought on grape production, it is imperative to understand the historical drought trend and frequency during the growing season. In this study, we focused on agricultural drought during the four growth periods of grape: bud break-flowering, flowering-veraison, veraison-berry maturation, and berry maturation-leaf fall. Based on the weather data from 429 meteorological stations, we computed the Crop Water Deficit Index (CWDI) in the five main grape-growing regions of China: Northeast China, North China, Northwest China, Southwest China, and Southeast China. Then, we evaluated the CWDI-based drought distribution and trend in the study regions, as well as the frequency of different degrees of drought. The results showed that exceptional drought was occurring frequently in Xinjiang Uyghur Autonomous Region, northern Gansu province, and northern Ningxia Hui Autonomous Region. Among the four study growth periods of grape, exceptional drought was the most expansive during bud break-flowering. What's more, exceptional drought coverage during bud break-flowering in the study regions was increasing from 1981 to 2016. Analysis of butterfly structure showed that the occurrence of drought was continuous and persistent in northern China. Our study results could serve as guideposts to highlight Chinese grape production industry's vulnerability to agricultural drought against the background of climate change. [ABSTRACT FROM AUTHOR]

Located in the eastern edge of the Sichuan Basin (SCB) in the southwest China, Chongqing is a mountainous region with typical complex topographic features. Using the hourly rainfall observation data of high-density 1686 meteorological stations in Chongqing during warm season from 2009 to 2016, we investigated the diurnal characteristics of precipitation affected by complex topography. The complex mountainous terrain has a significant impact on diurnal variations and distinct regional features of rainfall amount, frequency, and intensity. The stations located in the higher complex mountainous areas have greater rainfall amount, frequency, and intensity than those in the lower surrounding areas. In addition, the detailed characteristics of the rainfall amount and frequency in the four study regions further show that the rainfall amount and frequency significantly increase with the rise of elevation, especially in the area that terrain height sharply increases along the mountain extending direction. The diurnal variation of the rainfall amount is characterized by a bimodal structure with a dominant early-morning peak occurring at approximately 0700 LST (23 UTC) and a weaker secondary late-afternoon peak at approximately 1600 LST (08 UTC), while the rainfall frequency has a single early-morning peak. The terrain height has a significant impact on the proportions of the early-morning rainfall. With the elevation increasing in the four study regions, the proportions of rainfall amount (frequency) that occurs during early-morning period decrease. [ABSTRACT FROM AUTHOR]

It is of great significance to study on the shift of temperature zone boundaries for revealing the climate change pattern and its environmental effects. Based on daily average temperature data from 32 standard meteorological stations in the Qinling Mountains from 1964 to 2015, the growing season start and end (GSS and GSE) of the climatic growing season parameters were calculated based on a temperature threshold of 10 °C, and the growing season length (GSL) was obtained by subtracting GSE from GSS. We have analyzed the spatiotemporal variations of these parameters in the Qinling Mountains and the shift rules of the warm temperate zone and northern subtropics zone boundaries in China over the past 52 years. Our research generated three primary results. First, the spatial distribution and changing trends of the GSS, GSE, and GSL were significantly different before and after abrupt changes in temperature. After the abrupt change, the coverages of the three were all gradually expanding to the higher altitude areas. The change rates of the three were faster, the trends were more significant, and the differences between the north and the south were obvious, especially in the northern slope. Second, the boundaries of both the warm temperate zone and the northern subtropical zone in China showed upward position shifts, and the area coverage changed along the northern and southern slopes of the Qinling Mountains, and the change amplitudes were even greater after the abrupt change in temperature. Third, there was a significant north–south difference in the response of China's temperature zones to climate change. The temperature zone on the northern slope was more sensitive to climate warming. It is worth emphasizing that the shifts of the temperature zones did not change the fact that the Qinling Mountains are the boundary between China's subtropical and the warm temperate zones. The north subtropical zone is still located on the southern slope of the Qinling Mountains, and the northern slope is still in the warm temperate zone. [ABSTRACT FROM AUTHOR]

According to the daily maximum and minimum temperature and the precipitation at 40 meteorological stations in the Daqing River Basin of China during 1980–2015, the spatial and temporal trends of extreme temperature and precipitation are analyzed. The trend strengths, stability, and magnitude are calculated for ten indices of temperature and eight indices of precipitation. The results show that trends of extreme temperature indices are significant, but extreme precipitation indices are insignificant. Through the extreme temperature indices, the cold indices of extreme temperature decrease steadily and the warm indices of extreme temperature rise steadily, indicating that the trends of temperature rising in the basin are obvious and stable. In addition, indices of the extreme precipitation indicate that the consecutive dry days (CDD) decrease, the heavy precipitation days (R20) and the consecutive wet days (CWD) increase, and the annual total precipitation (PRCPTOT) increases steadily. The results have certain scientific value for climate change and a series of impacts brought by climate change in the Daqing River Basin. [ABSTRACT FROM AUTHOR]

The variability of air temperature extremes exerts a great influence on agricultural production and the global hydrologic cycle. It has been the focus of attention for the past several decades. Using observed surface air temperature from 192 meteorological stations in South China maintained by the China Meteorological Administration, this study computed and analyzed 10 extreme temperature indices and the mean temperature at multiple spatiotemporal scales for the period from 1961 to 2018. These indices were analyzed with particular reference to the growing season of rice. Results showed that the variation trends of all annual indices exhibited different north–south patterns across decades, and the most recent 20-year period experienced greater warming than previous periods. The regional averaged rates of the annual mean maximum temperature, the annual mean minimum temperature, summer days, and tropical nights were 0.163 °C decade−1, 0.197 °C decade−1, 1.2 days decade−1, and 5.4 days decade−1, respectively. Except for the month of April, the southern region mostly experienced stronger warming than the northern region, especially in summer and autumn. Nighttime warming was usually greater than daytime warming, especially in June and October. Most temperature indices showed very weak correlations with large-scale atmospheric oscillations. [ABSTRACT FROM AUTHOR]

ERA5 is the latest fifth-generation reanalysis global atmosphere dataset from the European Centre for Medium-Range Weather Forecasts, replacing ERA-Interim as the next generation of representative satellite-observational data on the global scale. ERA5 data have been evaluated and applied in different regions, but the performances are inconsistent. Meanwhile, there are few precise evaluations of ERA5 precipitation data over long time series have been performed in Chinese mainland. This study evaluates the temporal-spatial performance of ERA5 precipitation data from 1979 to 2018 based on gridded-ground meteorological station observational data across China. The results showed that ERA5 data could capture the annual and seasonal patterns of observed precipitation in China well, with correlation coefficient values ranging from 0.796 to 0.945, but ERA5 slightly overestimated precipitation in the summer. Nonetheless, the results also showed that the accuracy of the precipitation products was strongly correlated with topographic distribution and climatic divisions. The performance of ERA5 shows spatial inherently across China that the highest correlation coefficient values locate in eastern, Northwestern and North China and the lowest biases locate in Southeast China. This study provides a reliable data assessment of the ERA5 data and precipitation trend analyses in China. The results provide accuracy references for the further use of precipitation satellite data for hydrological calculations and climate numerical simulations. [ABSTRACT FROM AUTHOR]

The data of fog days from weather observation stations in China and the NCEP/NCAR re-analysis data from 1954 to 2007 are used to investigate the combined effects of El Niño and Southern Oscillation (ENSO) and Arctic Oscillation (AO) on the number of winter fog days in eastern China. The results show that during El Niño, the enhanced low-level southwesterly warm-moist airflow could lead to the temperature rise and humidity increase in eastern China. Note that the rate of humidity increase is faster than the rate of temperature rise, which makes the air in eastern China easy to be saturated. Besides, in winter, North China is dominated by the sinking airflow, so a large-value area of fog days appears in eastern China with the center in North China. While in La Niña years, the atmospheric circulation and its influence on the fog days are the opposite. During the positive AO period, the East Asian trough weakens and the low-level westerly jet moves northward, preventing northwesterly cold air from moving southward. The warming and humidification of North China and the slight temperature drop in South China would cause more fog days in North China and fewer fog days in South China. The effect of negative AO is opposite to that of positive AO. The combined effects of ENSO and AO are far greater than the sum of their individual effects. Under El Niño and positive AO, the number of fog days would increase significantly in North China during the whole winter. Besides, ENSO has greater impacts than AO during early winter and vice versa during later winter. [ABSTRACT FROM AUTHOR]

Based on daily meteorological data from 693 weather stations for the period 1960–2017, the characteristics of dryness/wetness trends and their relation with reference crop evapotranspiration (ET0) and precipitation changes were assessed in China. The results showed that the semi-arid/semi-humid areas and humid areas of southwestern China experienced a drying trend, while the arid areas in northwestern China and the humid areas in southern China became wetter over the past 58 years. The dryness/wetness trends were highly sensitive to the variability of ET0 in the arid and semi-arid areas and to precipitation in the humid and semi-humid areas. Regional differences in the contributions of ET0 and precipitation to the dryness/wetness trends were significant. In the arid areas, the average contribution of ET0 was 7% larger than that of precipitation, except in winter. A decreased ET0 due to a reduction in wind speed and the increase in precipitation led to a wetting trend in these areas. In the semi-arid/semi-humid areas, ET0 had a significantly larger effect on the dryness/wetness trends than precipitation. Contribution of ET0 was about 21% larger than that of precipitation in spring and about 7% larger at the annual timescale. Due to an increase in ET0 because of rising temperature and decrease in precipitation, the areas tended to be drier. In humid areas, precipitation was the dominant factor for the wetting trends. Contribution of precipitation was about 4 to 10% larger than that of ET0 in summer and at the annual timescale and even completely dominated the trend of SPEI in winter. However, contribution of ET0 in spring was slightly larger than that of precipitation in the humid areas, and a significant increase in temperature led to an increase in ET0 and resulted in a tendency of dryness. Aside from the reduction in precipitation, increased evapotranspiration had comparable contributions to the trends of dryness, even greater than that of precipitation in the drying season and in drying areas. Our findings suggested that the effects of ET0 against the background of global warming deserve more attention in future studies of dryness/wetness or drought. [ABSTRACT FROM AUTHOR]

There is an urgent need to understand the characteristics of both precipitation and drought in arid regions of China. Different indexes may provide differing results in terms of the detection and estimation of the temporal and spatial extent of droughts. In this study, the temporal and spatial characteristics of rainfall and drought at 53 meteorological stations from 1960 to 2016 across the Xinjiang region of China were analyzed. Four precipitation-related indexes (precipitation concentration degree (PCD), precipitation concentration period (PCP), standardized precipitation index (SPI), and long-cycle drought–flood abrupt alternation index (LDFAI)) were used to investigate the spatial and temporal patterns of drought and flood. In addition, the Bayesian method and Pettitt test were used as detection tools to identify changing points in precipitation time series. The study indicated the following: (1) a wetting tendency was evident in recent years and was supported by the upward trend in SPI and inter-decadal variation in summer precipitation; (2) the spatial patterns and tendencies of PCD, PCP, and SPI were markedly different in southern and northern Xinjiang; (3) compared with the Pettitt test, use of the Bayesian method provided data closer to the real drought events; (4) it is suggested that multiple indices be used for detecting precipitation and drought characteristics as use of the SPI may lead to other indexes related to flood and drought risks being ignored. [ABSTRACT FROM AUTHOR]

The accurate estimation of wind power is crucial not only to conduct wind energy research but also to improve policy and planning decisions for the national government. However, reliable wind speed datasets at turbine height that can be used for wind power estimation in China are very limited. In this study, the simulated wind profile (expressed by a power-law approach) is optimized using radiosonde wind speed measurements. The wind speed at a typical turbine height (80 m) is then constructed using the optimized wind profile and 10-m wind speed measured at each conventional meteorological station throughout the country. Compared with measurements, the constructed wind speed has reasonable errors (0.08 m s−1 in mean bias, 0.89 m s−1 in root mean square error, and 0.90 in correlation coefficient), which are much smaller than the model errors. Further comparison shows the constructing method in the current study outperforms the other similar statistical methods. Therefore, this method and the constructed wind speed dataset are suggested for wind energy research in China. [ABSTRACT FROM AUTHOR]

A stepwise cluster analysis (SCA) method is developed to downscale the daily mean surface temperature of 23 meteorological stations over the Beijing-Tianjin-Hebei (BTH) region in North China. Through comparisons of three evaluation indicators, including correction coefficients (CORRs), root mean square errors (RMSEs), and mean relative errors (MREs), between model simulations and observations, the SCA is proven to be capable of simulating the daily mean temperature in the baseline period (1961–2005). The projections of mean surface temperature under RCP4.5 and RCP8.5 scenarios are then developed using the SCA model. The results show that the mean surface temperature at most stations would keep increasing in future throughout the twenty-first century. The largest magnitude and rate of temperature increase are reported in the northwest mountains of the BTH region (especially obvious in winter), suggesting that the response to climate change in highland regions is more sensitive than that in low elevations. It is also reported that the projected changes in mean surface temperature in coastal regions are smaller than those in plain areas. This could be due to ocean's moderating influence in the HadGEM2-ES. In terms of seasonal changes in surface temperature, the smallest magnitude of warming is expected in summer while the highest is likely to occur in winter, especially under RCP8.5 emission scenarios. Furthermore, the annual cycle analysis for temperature changes suggests that the highest amplitude of warming is expected in cold months (i.e., February or December) while the smallest is likely to occur in warm months (i.e., July or August). [ABSTRACT FROM AUTHOR]

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When meteorological stations are quite unevenly distributed, a simple regional arithmetic mean of observation data may assign an excessive weight to one region with dense stations, which affects the representativeness of the regional mean. In this study, we used the homogenized monthly maximum (Tmax), mean (Tm), and minimum (Tmin) temperature dataset at more than 2400 national surface meteorological stations in China. Based on a thin plate spline (TPS) interpolation method, we selected a three-dimensional (longitude, latitude, and elevation above sea level) interpolation model that is suitable for the temperature curve surface fitting in China, and constructed a gridded temperature dataset with a horizontal resolution of 0.5° during 1961 to 2015. Cross-validation indicates that the annual average of generalized cross-validation (GCV) is relatively small, and the ratio of GCV to the observed temperature is relatively low. Both the root of GCV and the root-mean-square error of temperature are smaller than those of the previous temperature gridded products. A comparison between our dataset and the Climate Research Unit (CRU) TS4.02 dataset indicates that the CRU's data overestimate the warming trend in China during 1961–1984, whereas underestimate the warming trend during 1985–2015. [ABSTRACT FROM AUTHOR]

The Huaihe River Plain (HRP) is one of the main planting areas of winter wheat in China. Uncertain and erratic distribution of precipitation and the shortage of water resources are the major limitations to crop growth in this region. In this study, the spatial and temporal distributions of effective precipitation during the different growth stages of winter wheat in the HRP were examined using a daily precipitation time series of 53 years (1961/1962~2013/2014) from 42 meteorological stations. The effective accumulative temperature index method was used to interpolate the winter wheat growth period data (recorded by 4 representative agro-meteorological stations). The Mann–Kendall method was used to check the statistical significance of the trends. The following conclusions are based on these results. (1) The effective accumulative temperature index method can be used to interpolate the observed data. (2) The effective precipitation results show downward trends with magnitudes of 0~− 6 mm/decade for the majority of the stations during certain stages (the tillering date to the jointing date, the jointing date to the heading date, and the entire growth period). (3) Most of the stations show strong downward trends during the growth stages corresponding to the tillering date to the jointing date and the jointing date to the heading date but show insignificant trends during other stages. (4) The spatially averaged effective precipitation data show very strong downward trends during the tillering to heading stage and weak downward trends over the entire growth period. [ABSTRACT FROM AUTHOR]

Based on daily mean temperature data from 32 meteorological stations in the Qinling Mountains (QMs) of China, we analyzed the characteristics and differences of the spatiotemporal changes in the climatic growing season (CGS) in the QMs from 1964 to 2015. Our results are as follows. First, over the past 52 years, the temperature of the QMs significantly increased at a mean rate of 0.22 °C/decade (P < 0.01) in over 98.04% of the area. Significant north–south spatial differences were observed in temperature changes; also, significant differences in the temperature changing trends were observed before and after the abrupt change in temperature. Second, the spatial distributions of the mean growing season start (GSS), end (GSE), and length (GSL) in the QMs varied based on regional differences in latitude and topography. Notably, the GSS, GSE, and GSL were gradually delayed, advanced, and shortened, respectively, as latitude and elevation increased. After the abrupt change in temperature, whether it is in the NSQM (northern slopes of the QMs) or the SSQM (southern slopes of the QMs), the GSS, GSE, and GSL expanded into high-elevation areas. Third, over the past 52 years, the GSS in the QMs exhibited a significant advancing trend of 2.7 days/decade, the GSE was delayed at a rate of 0.66 days/decade, and the GSL displayed a significant extension of 3.36 days/decade. Before the abrupt change in temperature, the GSS, GSE, and GSL exhibited non-significant changing trends; however, the trends in the GSS, GSE, and GSL were more significant after the abrupt change than before. Fourth, the GSS, GSE, and GSL trends in the QMs were significantly different in the NSQM and SSQM regions. After the abrupt change, the GSS, GSE, and GSL trends along the NSQM were more significant than those along the SSQM. [ABSTRACT FROM AUTHOR]

Historical temperature records are often partially biased by the urban heat island (UHI) effect. However, the exact magnitude of these biases is an ongoing, controversial scientific question, especially in regions like China where urbanization has greatly increased in recent decades. Previous studies have mainly used statistical information and selected static population targets, or urban areas in a particular year, to classify urban-rural stations and estimate the influence of urbanization on observed warming trends. However, there is a lack of consideration for the dynamic processes of urbanization. The Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are three major urban agglomerations in China which were selected to investigate the spatiotemporal heterogeneity of urban expansion effects on observed warming trends in this study. Based on remote sensing (RS) data, urban area expansion processes were taken into consideration and the relationship between urban expansion rates and warming trends was investigated using data from 975 meteorological stations throughout China. Although urban areas constitute less than 1% of land in China, more than 90% of the meteorological stations experienced urban land use change and the average urban expansion rate was 0.33%/a. There was also a significant positive relationship between observed warming trends and urban expansion rates. Background warming, without the influence of urbanization and extra warming induced by urbanization processes, was estimated using a linear regression model based on observed warming trends and urban expansion rates. On average, urbanization led to an additional annual warming of 0.034 ± 0.005 °C/10a. This urbanization warming effect was 0.050 ± 0.007 °C/10a for minimum temperatures and 0.008 ± 0.004 °C/10a for maximum temperatures. Moreover, it appeared that urbanization induced greater warming on the minimum temperature during the cold season and maximum temperature during the warm season. [ABSTRACT FROM AUTHOR]

Better investigation of extreme precipitation in large river basins is important for hydro-meteorological research and water resources management. Based on daily precipitation data from 17 national meteorological stations in Nenjiang River Basin (NRB) during 1959–2011, spatial-temporal characteristics and trends of seven extreme precipitation indices were analyzed in this study using Mann-Kendall non-parametric test and the ensemble empirical mode decomposition (EEMD) method. We found that almost all selected extreme precipitation indices declined in regionally averaged values, except maximum 5-day precipitation amount (Rx5day). Both extreme precipitation indices and their trends demonstrated spatial varieties. Generally, lower basin obtained less extreme precipitation and tended to be drier. But the amount and intensity of extreme precipitation in upper basin, where are more humid, are rising. Extreme precipitation indices presented apparent non-linear process with periodic oscillations of 1.63–1.94a for IMF1 to 25–31a for IMF4. The findings of this study are useful for the management of water resources in NRB, as well as provide reference information for precipitation evolution under climate change in other regions. [ABSTRACT FROM AUTHOR]

Understanding the changing characteristics and related mechanisms behind precipitation extremes is crucial for developing adaptive measures of water resource management as well as flood risk management. Based on daily precipitation measurement taken at 57 meteorological stations from 1960 to 2016, the variability of precipitation extremes over the Yangtze River Delta (YRD) is analyzed utilizing a Mann-Kendall trend test as well as a Hurst exponent analysis. Moreover, the climatic teleconnection that occurs from large-scale atmospheric circulation and such precipitation extremes is also investigated with the help of a wavelet coherence analysis. Results indicate that most extreme precipitation indices predominantly exhibit significant positive trends, indicating a wetting trend in the YRD over the past 61 years. Meanwhile, the contribution of precipitation of very wet days to annual total wet-day precipitation increased significantly. Furthermore, the increasing trend of precipitation extremes in the YRD is found to be attributable to the frequency and intensity, rather than to the duration of extreme precipitation events. The patterns of variation in these precipitation extremes reveal dramatic spatial heterogeneity, with extreme events concentrated primarily along the coastal plains. Overall, the YRD will likely face more severe flood risks in the foreseeable future. This is especially the case for the southern and central-western regions of the YRD. In contrast, the northern region of the YRD is forecast to become drier over time. The increasing trends in precipitation extremes for the YRD observed in this study are found to be linked closely with the positive anomalies of the El Niño-Southern Oscillation as well as the negative anomalies of the East Asian summer monsoon. [ABSTRACT FROM AUTHOR]

Global warming has considerably challenged the natural environment and livelihood conditions. Understanding potential future changes in critical climatic variables, such as temperature and precipitation, is important for regional agricultural and water resource management. This study proposes a new approach to the application of the Long Ashton Research Station Weather Generator (LARS-WG) in Coupled Model Intercomparison Project Phase 5 (CMIP5) emission scenarios and aims to test its applicability in cold areas and to evaluate the response of temperature and precipitation, in amount and form, under future warmer climate trends. Three stations in northeastern China are set as case sites, and 50 years of daily weather observations are used for model calibration and validation. Future synthetic time-series of daily precipitation and daily maximum and minimum temperatures is generated by the calibrated LARS-WG based on three Representative Concentration Pathway (RCP) scenarios with various radiative forcing levels of 14 general circulation models (GCMs) outputs for the periods 2041–2060 (2050s) and 2061–2080 (2070s). The results show that the CMIP5 scenarios can be successfully used in a LARS-WG model and that the model performs well in cold weather conditions to repeat the current status of the case sites; the model is able to provide downscaling analysis for future daily weather generation via updating calibrated model parameters based on various GCM outputs. A generally warming and wetting conversion would last into the future for the study sites, but there is great inconsistency among different GCMs. An ensemble approach is adopted with mean values of multi-GCMs to avoid the uncertainty associated with using a single GCM, based on which the changes in the form of precipitation are further estimated. As a result of the decrease in freezing conditions, although annual precipitation will continue to increase in the future, there will be relatively less annual snowfall, which will be primarily focused in deep winter. Such changes in snow cover conditions will potentially disturb the original rules of local overwintering agriculture. In addition, more intense and earlier snowmelt discharge and more rainfall in summer will latently impact the watershed hydrologic process. The influences of climate change are significant, and related projects for agricultural and water resource management should be of great concern in local decision-making. [ABSTRACT FROM AUTHOR]

The temporal and spatial characteristics of drought disasters in Southern China were analyzed by using the daily observation data from 252 meteorological stations and drought disaster data in 14 provinces, autonomous regions, and municipalities of Southern China during 1961–2015. The characteristics of drought disaster risk were determined, and the countermeasures for prevention and control were also suggested. The results showed that the annual precipitation fluctuated and has no obvious linear trend in Southern China in the past 55 years. However, the average annual precipitation decreased significantly and its oscillation amplitude is increasing in the early twenty-first century. The annual average temperature exhibited a significant upward trend in these years in the research area. The increasing rate was even higher than the global means. The temperature has increased since 1976, and an abrupt change was occurred in 1997. Area with high risk of drought was concentrated mainly in Southwest China. With the climatic warming, the drought frequency and intensity and the drought-affected areas have been increasing, as well as the risk of drought disaster. The risk area of secondary highest drought disaster expanded dramatically after 1997. In the future, the occurrence of droughts may increase in Southern China. Therefore, it is necessary to enhance risk management for drought disasters by implementing eco-environmental modifications in the vulnerable areas, as well as ensuring food security in the agricultural production areas, addressing the uneven spatial and temporal distributions of water resources and the discrepancy between supply and demand, and enhancing the prevention and control of drought disaster risk. [ABSTRACT FROM AUTHOR]

Global increases in duration and prevalence of droughts require detailed drought characterization at various spatial and temporal scales. In this study, drought severity in Xinjiang, China was investigated between 1961 and 2012. Using meteorological data from 55 weather stations, the UNEP (1993) index ( I ), Erinç's aridity index ( I ), and Sahin's aridity index ( I ) were calculated at the monthly and annual timescales and compared to the Penman-Monteith based standard precipitation evapotranspiration index (SPEI). Drought spatiotemporal variability was analyzed for north (NX), south (SX), and entire Xinjiang (EX). I could not be calculated at 51 stations in winter as T was below 0. At the monthly timescale, I , I , and I correlated poorly to SPEI because of seasonality and temporal variability, but annual I , I , and I correlated well with SPEI. Annual I , I , and I showed strong spatial variability. The 15 extreme droughts denoted by monthly SPEI occurred in NX but out of phase in SX. Annual precipitation, maximum temperature, and relative and specific humidity increased, while air pressure and potential evapotranspiration decreased over 1961-2012. The resulting increases in the four drought indices indicated that drought severity in Xinjiang decreased, because the local climate became warmer and wetter. [ABSTRACT FROM AUTHOR]

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year) occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year) in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period. [ABSTRACT FROM AUTHOR]

Highly concentrated precipitation, where a large percentage of annual precipitation occurs over a few days, may include a high risk of flooding and severe soil erosion. Thus, areas with severe erosion such as the Loess Plateau in China are particularly vulnerable to highly concentrated precipitation events due to climate change. In this study, we investigated spatial and temporal patterns in the concentration of rainfall in the Middle Yellow River (MYR) from the last 56 years (1958-2013). We used daily and monthly precipitation data from 26 meteorological stations in the study area to calculate the precipitation concentration index (PCI) and the concentration index (CI). The southern and northern parts of the MYR were characterized by a lower CI with a decreasing trend, while the middle parts had a higher CI with an increasing trend. High PCI values occurred in the southern MYR, while lower PCIs with a more homogenous rainfall distribution were found mainly in the northern parts of the MYR. The annual PCI and CI exhibited positive trends at most stations, although only a minority of stations had significant trends ( P < 0.05). At seasonal scales, CI exhibited significantly increasing trends in winter at most stations, while a few stations had significant trends in the other three seasons. These findings provide important reference information to facilitate ecological restoration and farming operations in the study region. [ABSTRACT FROM AUTHOR]

Monthly rainfall in the Heihe River Basin (HRB) was simulated by the dynamical downscaling model (DDM) and statistical downscaling model (SDM). The rainy-season rainfall in the HRB obtained by SDM and DDM was compared with the observed datasets (OBS) over the period of 2003-2012. The results showed the following: (1) Both methods reasonably reproduced the spatial pattern of rainy-season rainfall in the HRB with a high-level skill. Rainfall simulated by DDM was better than that by SDM in the upstream, with biases of −12.09 and −13.59 %, respectively; rainfall simulated by SDM was better than that by DDM in the midstream, with biases of 3.91 and −23.22 %, respectively; there was little difference between the rainfall simulated by SDM and DDM in the downstream, with biases of −10.89 and −9.50 %, respectively. (2) Both methods reasonably reproduced monthly rainfall in rainy season in different subregions. Rainfall simulated by DDM was better than that by SDM in May and July in the upstream, whereas rainfall simulated by SDM was closer to OBS except August in the midstream and except August and September in the downstream. (3) For multi-year mean rainy-season rainfall in different stations, there was a little difference between the rainfall simulated by DDM and SDM in Tuole station in the upstream, with biases of −13.16 and −12.40 %, respectively; rainfall in Zhangye station simulated by SDM was overestimated with bias of 14.02 %, and rainfall simulated by DDM was underestimated with bias of −14.60 %; rainfall in Dingxin station simulated by DDM was reproduced better than that by SDM, with biases of −19.34 and −32.75 %, respectively. [ABSTRACT FROM AUTHOR]

Using the hourly precipitation records of meteorological stations in Shanghai, covering a period of almost a century (1916-2014), the long-term variation of extreme heavy precipitation in Shanghai on multiple spatial and temporal scales is analyzed, and the effects of urbanization on hourly rainstorms studied. Results show that: (1) Over the last century, extreme hourly precipitation events enhanced significantly. During the recent urbanization period from 1981 to 2014, the frequency of heavy precipitation increased significantly, with a distinct localized and abrupt characteristic. (2) The spatial distribution of long-term trends for the occurrence frequency and total precipitation intensity of hourly heavy precipitation in Shanghai shows a distinct urban rain-island feature; namely, heavy precipitation was increasingly focused in urban and suburban areas. Attribution analysis shows that urbanization in Shanghai contributed greatly to the increase in both frequency and intensity of heavy rainfall events in the city, thus leading to an increasing total precipitation amount of heavy rainfall events. In addition, the diurnal variation of rainfall intensity also shows distinctive urban-rural differences, especially during late afternoon and early nighttime in the city area. (3) Regional warming, with subsequent enhancement of water vapor content, convergence of moisture flux and atmospheric instability, provided favorable physical backgrounds for the formation of extreme precipitation. This accounts for the consistent increase in hourly heavy precipitation over the whole Shanghai area during recent times. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET) is the key factor for hydrologic water balance, irrigation scheduling, and water resources planning. Based on Food and Agriculture Organization (FAO) Penman-Monteith method and the climate variables of 57 meteorological stations from 1960 to 2010 in southwest China, the spatial and temporal distributions of ET were analyzed by using Mann-Kendall test and Sen's slope estimator. Sensitivity coefficient was used to analyze the sensitivities of ET to four climate variables, and the key climate variables attributed to ET change were determined. Result showed that there was a slight downward trend of ET from 1960 to 2010 and spatially increasing trend from northeast to southwest in annual time scale. Results also showed that ET had relatively higher sensitivity to wind speed and mean air temperature, and wind speed was the dominant variable for change of ET in southwest China. The inverse relationship between increasing air temperature and decreasing evaporation, 'evaporation paradox,' existed in southwest China, and the negative contribution of wind speed to the changes of ET offset the positive contribution of air temperature. [ABSTRACT FROM AUTHOR]

The Taklimakan Desert is the source of most blowing dust events in China. However, previous studies of sandstorms in this region have not included data from the inner desert because of the difficulty in making observations in this area. In this study, the spatial and temporal variations of blowing dust events, including sandstorms and blowing sand, and its relations with climatic parameters in the Taklimakan Desert were analyzed using data from ten desert-edge meteorological stations during 1961 to 2010 and two inner-desert meteorological stations during 1988 to 1990, 1996 to 2010, and 1992 to 2010. The results identified two regions (Pishan-Hotan-Minfeng and Xiaotang-Tazhong) where blowing dust events occur on average more than 80 days per year. The regions with the highest occurrence of sandstorms, blowing sand, and blowing dust events were different, with sandstorms centered in the north of the desert (Xiaotang, 46.9 days), whereas the central location for blowing sand (Pishan, 86.4 days) and blowing dust events (Minfeng, 113.5 days) activity was located at the southwestern and southern edges of the desert, respectively. The occurrence of sandstorms generally decreased from 1961 to 2010, while the occurrence of blowing sand increased from 1961 to 1979 and then generally decreased. The temporal variation of blowing dust events was mainly affected by the occurrence of strong wind and daily temperature, with average correlation coefficients of 0.46 and −0.41 for these variables across the whole desert. [ABSTRACT FROM AUTHOR]

Drought is a recurrent disaster that occurs in virtually all climatic zones of the world. However, drought characteristics vary substantially among different climatic regions. In this study, multifractal and wavelet analyses are used to characterize drought based on monthly precipitation. The rainfall data of 28 precipitation stations from 1958 to 2011 in Jilin province were collected to calculate the standardized precipitation index (SPI), and the negative monthly SPI time-series is used in a multiscaling approach to determine drought characteristics in Jilin province. Simple scaling and multiscaling analyses show significant variations in monthly droughts in the region. Morlet wavelet analysis also shows that significant cycles and multiple time-scales of drought exist in all stations. Cross wavelet analysis shows that drought occurrence in the region is mainly influenced by different climatic factor scales. However, different factors have different degrees of influence at different regions. The enduring influence of medium and long-term climatic patterns (such as El Niño events) may lead to the simple scaling behavior of drought for some regions. [ABSTRACT FROM AUTHOR]

February-May temperature strongly affects ecological processes and socio-economics in central China, yet its long-term variability has not been thoroughly assessed due to the shortness of instrumental records. In order to improve the understanding of the regularities of temperature variability in central China, in this study, we present a new tree-ring chronology from the Shengnongjia Mountains in central China which provides a valuable 245-year record of temperature variability. The reconstructed temperature correlated strongly with February-May mean temperature records of the Fangxian meteorological station from AD 1958 to AD 2011, and the derived reconstruction explained 44.5 % of the instrumental temperature variation during this period. The study shows that this region experienced three warm periods and two cool periods, i.e., the major warm periods occurred in AD 1783-1806, AD 1879-1909, and AD 1975 to the present, whereas the cool intervals occurred in AD 1807-1878 and AD 1910-1974. This reconstruction could aid in the evaluation of regional climate variability in subtropical China. [ABSTRACT FROM AUTHOR]

Using observed surface temperature data from about 570 meteorological stations in China, the linear temperature trend over the last 50 years (1962-2011) is estimated. Average warming rates at all stations are 0.284 ± 0.142, 0.200 ± 0.163, and 0.392 ± 0.193 °C/10 a for annual, June-July-August (JJA), and December-January-February (DJF) mean temperatures, respectively. The warming rates (°C/a) have a regressed slope of 0.001 with latitude, and their relationship with latitude using data from stations below 1,000 m altitude is estimated at 0.009 °C/(10 a · degree). A k-means clustering is constructed using correlation coefficients to quantify the closeness. The clustering schemes with k = 5 and k = 10 are successfully implemented for annual, DJF, and JJA mean temperatures. The k = 10 scheme showed greater ability to distinguish different locations than the k = 5 clustering. In both schemes, the mean estimated warming rates are averaged over stations in each cluster. The clusters in DJF are much different than those for the entire year and for JJA. The average warming rate in each cluster is estimated and compared. Using stations in the cluster of high-elevation southeast Tibetan Plateau, the relationship between warming rates and altitude is estimated at 1.0 × 10 °C/(10 a · 100 m). [ABSTRACT FROM AUTHOR]

Daily records including the 0-cm average ground surface temperature (AGST) and average air temperature (AAT) from 557 meteorological stations over China from 1951 to 2010 are analyzed by employing the detrended fluctuation analysis (DFA) method. Different long-range correlation behaviors are found between AGST and AAT. The results show that the regional-averaged, minimum, and maximum values of the scaling exponents for AGST are shifted to the higher values than those for AAT over China. Furthermore, the number of stations where the differences of the scaling exponents between AGST and AAT is greater than zero accounts for about 87 % of the total. The probability distributions of the exponent differences are concentrated on the value of 0.04. Then, we make a numerical test to prove the significance of the difference in exponents by shuffling the data records which have removed the seasonal cycle. The results show that the difference of scaling exponents between AGST and AAT is significant. Through the comparison and analysis of AGST and AAT, we find that AGST seems to be more sensitive to detect temperature persistence changes. [ABSTRACT FROM AUTHOR]

Both inter- and intra-annual changes in air temperature are impacted by global climate change. Sine curves, such as T = Asin(ω t + φ), adjust the 10-day mean air temperature T contributed by the corresponding number of 10-day t within a year. Based on the curve, relative indices were defined as follows: A, indicating the annual maximum 10-day air temperature; t and t, representing the starting and ending time of the warm season; t and t, indicating the starting and ending time of the growing season; l and l, denoting the length of the warm and growing seasons. The objective of this study was to evaluate the inter- and intra-annual distribution characteristics of the 10-day mean air temperature and the associated spatial patterns, changing trends, and abrupt points in 128 meteorological stations across Northwestern China during 1961 to 2010 by using the selected indices. The results showed that the 2010s had the fastest increase in air temperature during the study period across the study area. Altitude was an important factor affecting the selected indices. Annual mean air temperature ( T) and A were high in low-altitude areas, where the warm and growing season came earlier and ended later, and vice versa. The values of T and A had increased by 1.65 and 0.65 °C during the past 50 years, respectively. The warm and growing season had come earlier by 9 and 7.5 days and ended later by 7.5 and 6 days during the past 50 years, respectively. Therefore, the warm season has gotten longer by 16 days and the growing season by 14 days in the study area during the past 50 years. The abrupt increase of T, A, t, t, t, t, l, and l detected at the 0.05 significance level took place in the late 1960s and that of A occurred in the late 1980s. The inter- and intra-annual distribution of air temperature in Northwestern China has changed during the last five decades, and it is reasonable to expect those changes to continue for a period under global climate change. [ABSTRACT FROM AUTHOR]

The surface air temperatures measured at 68 meteorological stations in the arid northwestern China during 1979-2012 are compared with temperatures interpolated from the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Reanalysis 2 (NCEP R2) and the European Center for Medium-Range Weather Forecasts ERA-Interim. The altitude effects on reanalysis temperature errors are discussed, and the interpolated reanalysis data are calibrated by altitude errors between reanalysis and observation. Using a simple correction method with a constant lapse rate, the elevation-related errors can be greatly removed and an improvement is achieved for the interpolated temperature from both NCEP R2 and ERA-Interim. The cold bias of reanalysis data becomes weak after calibration. On an annual basis, root mean square error of temperature derived from NCEP R2 for each stations has decreased from 6.0 (raw data) to 2.6 °C (calibrated data) and that from ERA-Interim has decreased from 3.2 to 1.4 °C. Similarly, correlation coefficients between raw reanalysis-based and observed temperature are 0.191 and 0.709 for NCEP R2 and ERA-Interim, respectively, whereas the correlation coefficients using the calibrated annual data are 0.819 and 0.932 for NCEP R2 and ERA-Interim, respectively. Generally, ERA-Interim is closer to the ground-based observations than NCEP R2. The topographic correction is more effective in summer than in winter, which may be related to the temperature inversion in winter. Evaluation and correction of reanalysis datasets is a crucial work before the gridded data are applied in climate research, and the altitude-related errors should be calibrated especially in the regions with complex topography. [ABSTRACT FROM AUTHOR]