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In this paper, we examined the spatial and temporal variations in precipitation amount, frequency, and intensity in China based on daily precipitation data from 2050 weather stations from 1973 to 2016. We used two Markov chain parameters to quantify the wet persistence and dry persistence that characterizes the temporal pattern of wet and dry days, respectively. We found that China's annual precipitation changed little from 1973 to 2016, but varied dramatically from 524 to 688mm yr-1, with an average of 592 mm yr-1, during this period. China's precipitation frequency, the number of days with effective precipitation (.0.1mmday21) in a year, significantly decreased at a rate of 0.9 days decade21 from 1973 to 2016, but precipitation intensity significantly increased at a rate of 0.12 mm day-1 decade-1 during the same period. Of the changes in China's total precipitation amount, precipitation intensity played a dominant role, contributing 70.8%, while precipitation frequency contributed the remaining 29.2%. Little change was found in the wet persistence in China over the period of 1973-2016, but the dry persistence significantly increased with an average increasing trend of 1.62 3 1023 probability per decade during the same period, and no significant correlations were found between these two variables. China's precipitation also changed nonuniformly in space, with increasing trends in precipitation amount, frequency, intensity, and wet persistence in western and northeastern China but decreasing trends in the Sichuan basin, northeast of Inner Mongolia, and the Beijing-Tianjin-Hebei region. [ABSTRACT FROM AUTHOR]

The statistical methods based on extreme value theory have been traditionally used in meteorology and hydrology for a long time. Due to climate change and variability, the hypothesis of stationarity in meteorological or hydrological time series was usually not satisfied. In this paper, a nonstationary extreme value analysis was conducted for annual maximum daily precipitation (AMP) at 631 meteorological stations over China for the period 1951–2013. Stationarity of all 631 AMP time series was firstly tested using KPSS test method, and only 48 AMP time series showed non-stationarity at 5% significance level. The trends of these 48 nonstationary AMP time series were further tested using M-K test method. There were 25 nonstationary AMP time series mainly distributed in southern and western China showing significant positive trend at 5% level. Another 5 nonstationary AMP time series with significant negative trends were near northern urban agglomeration, Sichuan Basin, and central China. For these nonstationary AMP time series with significant positive or negative trends, the location parameter in generalized extreme value (GEV) distribution was assumed to be time-varying, and the trends were successfully characterized by the nonstationary GEV models. For the remaining 18 nonstationary AMP time series mainly in the eastern portion of China, no significant trend was detected. The correlation analysis showed that only 5 nonstationary AMP time series were significantly correlated with one or two of the four climate indices EASMI, WPI, SOI, and PDO. Then, the location and scale parameters in the GEV distribution were modeled as functions of the significantly correlated climate indices. The modeling results in this study showed that the nonstationary GEV distributions performed better than their stationary equivalents. Finally, 20-year and 50-year return levels of precipitation extremes at all 631 stations were estimated using the best fitting distribution for the year 1961 and 2013, respectively. [ABSTRACT FROM AUTHOR]

Multisource meteorological precipitation products are an important way to make up for a lack of observation sites or a lack of precipitation data in areas with a complex topography. They have important value for local industrial, agricultural, and ecological water use calculations, as well as for water resource evaluation and management. The Yunnan-Kweichow Plateau is located in southwest China and has a relatively backward economy and few meteorological stations. At the same time, the terrain is dominated by mountain valleys, precipitation is greatly affected by the terrain, and meteorological data are lacking, making the calculation of local water resources difficult. In this study, the applicability of the 3-hourly merged high-quality/IR estimates (3B42) of the Tropical Rainfall Measuring Mission (TRMM), China Meteorological Forcing Dataset (CMFD), and China Meteorological Assimilation Driving Datasets (CMADS) in the Yunnan-Kweichow Plateau was analyzed using multiple evaluation indicators of different temporal scales and precipitation intensity levels as well as the spatial distribution of the indicators based on measured daily precipitation data from 59 national meteorological basic stations in the study area in 2008–2018. The results showed that (1) the three products had performed well and could be applied to the calculation of local water resources with CMFD performing the best; (2) the performance of precipitation products was slightly worse on the daily scale, and the overall performance of the yearly, quarterly, and monthly scales was better; (3) good results were achieved in most regions, but there were also some regions with prominent overestimation and underestimation; (4) the three precipitation products had the highest probabilities of detection and the lowest false alarm rates for no rain and light rain, and the probability of detection gradually decreased with an increase in the precipitation intensity; and (5) the mean absolute error of precipitation products in rainy months is large, so the accuracy of products in the calculation of heavy rain and flood will be limited. [ABSTRACT FROM AUTHOR]

This study analyzes the variation trends of temperature and precipitation in the Dadu River Basin of China based on observed records from fourteen meteorological stations. The magnitude of trends was estimated using Sen’s linear method while its statistical significance was evaluated using Mann-Kendall’s test. The results of analysis depict increase change from northwest to southeast of annual temperature and precipitation in space. In temporal scale, the annual temperature showed significant increase trend and the annual precipitation showed increase trend. For extreme indices, the trends for temperature are more consistent in the region compared to precipitation. This paper has practical meanings for an effective management of climate risk and provides a foundation for further study of hydrological situation in this river basin. [ABSTRACT FROM AUTHOR]

Timely and accurate monitoring of droughts is important for implementing an effective response and for minimizing economic losses. In this paper, the duration and amount of deficit in precipitation before every severe drought were analyzed for 124 meteorological stations based on the weather data from 1961 to 2012. The results showed that deficit in precipitation over a period as short as three months or even shorter could lead to severe drought and the cumulative timescales of precipitation deficit in southwestern China were longer than those in southern China. The distribution of the critical amount of precipitation deficit showed a clear regional difference. Deficits in the western parts of southwestern China and parts of southern China are above 60%, or even above 80%, higher than the other area ranging between 40% and 60%. On the whole, the critical amount of the deficit preceding severe droughts for the humid southwestern and southern China was lower than that for the semiarid and semihumid areas. The results offer a sound basis for monitoring and forecasting droughts in southern and southwestern China and for issuing early warnings. [ABSTRACT FROM AUTHOR]

In this paper, the diurnal variations of various clouds are analyzed using hourly cloud observations at weather stations in China from 1985 to 2011. In combination with merged hourly precipitation data, the relationship between the diurnal variations of clouds and precipitation in the summers from 2008 to 2011 are studied. The results show that the occurrence frequencies of total cloud and various cloud types exhibit significant diurnal variations. The diurnal variations of the occurrence frequencies of altocumulus and stratocumulus show a bimodal pattern, with peaks appearing in the early morning and late afternoon. The early morning peaks of altocumulus and stratocumulus appear earlier in the summer than in the other seasons, while the late afternoon maxima show an opposite trend. The occurrence frequency of nimbostratus peaks in the morning between 07 and 12 LST (local solar time), and the peak value lags 2 to 3 h from west to east along the Yangtze River valley; meanwhile, the diurnal variation shows no clear differences caused by changes in the latitude or seasons. Cumulus shows an afternoon (14 LST) maximum, while cumulonimbus peaks in the late afternoon during 16–20 LST, and both of them present a great diurnal range. Cirrus usually reaches its peak at 17–18 LST, and it differs by 1 to 2 h with a change in the latitude. The results of the study first show that the diurnal variations of precipitation among different regions are dominated by different clouds. The upper reaches of the Yangtze River valley present a midnight precipitation maximum that is mainly dominated by cumulonimbus. For the middle reaches of the Yangtze River valley impacted by nimbostratus, the precipitation peaks in the early morning. In South and Northeast China, the precipitation peaks in the afternoon and is determined by the diurnal variations of convective clouds. In the region between the Yangtze River valley and Yellow River valley, the precipitation peaks in the early morning and afternoon; the early morning peak is mainly determined by stratiform clouds, while the afternoon peak is closely related to convective clouds. [ABSTRACT FROM AUTHOR]

This paper is focused on the probability modeling with a range of distribution models over two inland river basins in China, together with the estimations of return levels on various return periods. Both annual and seasonal maximum precipitations (MP) are investigated based on daily precipitation data at 13 stations from 1960 to 2010 in Heihe River and Shiyang River basins. Results show that GEV, Burr, and Weibull distributions provide the best fit to both annual and seasonal MP. Exponential and Pareto 2 distributions show the worst fit. The estimated return levels for spring MP show decreasing trends from the upper to the middle and then to the lower reaches totally speaking. Summer MP approximates to annual MP both in the quantity and in the spatial distributions. Autumn MP shows a little higher value in the estimated return levels than Spring MP, while keeping consistent with spring MP in the spatial distribution. It is also found that the estimated return levels for annual MP derived from various distributions differ by 22%, 36%, and 53% on average at 20-year, 50-year, and 100-year return periods, respectively. [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]

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 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]

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]

High-spatial-resolution and long-term climate data are highly desirable for understanding climate-related natural processes. China covers a large area with a low density of weather stations in some (e.g., mountainous) regions. This study describes a 0.5 ′ (∼ 1 km) dataset of monthly air temperatures at 2 m (minimum, maximum, and mean proxy monthly temperatures, TMPs) and precipitation (PRE) for China in the period of 1901–2017. The dataset was spatially downscaled from the 30 ′ Climatic Research Unit (CRU) time series dataset with the climatology dataset of WorldClim using delta spatial downscaling and evaluated using observations collected in 1951–2016 by 496 weather stations across China. Prior to downscaling, we evaluated the performances of the WorldClim data with different spatial resolutions and the 30 ′ original CRU dataset using the observations, revealing that their qualities were overall satisfactory. Specifically, WorldClim data exhibited better performance at higher spatial resolution, while the 30 ′ original CRU dataset had low biases and high performances. Bicubic, bilinear, and nearest-neighbor interpolation methods employed in downscaling processes were compared, and bilinear interpolation was found to exhibit the best performance to generate the downscaled dataset. Compared with the evaluations of the 30 ′ original CRU dataset, the mean absolute error of the new dataset (i.e., of the 0.5 ′ dataset downscaled by bilinear interpolation) decreased by 35.4 %–48.7 % for TMPs and by 25.7 % for PRE. The root-mean-square error decreased by 32.4 %–44.9 % for TMPs and by 25.8 % for PRE. The Nash–Sutcliffe efficiency coefficients increased by 9.6 %–13.8 % for TMPs and by 31.6 % for PRE, and correlation coefficients increased by 0.2 %–0.4 % for TMPs and by 5.0 % for PRE. The new dataset could provide detailed climatology data and annual trends of all climatic variables across China, and the results could be evaluated well using observations at the station. Although the new dataset was not evaluated before 1950 owing to data unavailability, the quality of the new dataset in the period of 1901–2017 depended on the quality of the original CRU and WorldClim datasets. Therefore, the new dataset was reliable, as the downscaling procedure further improved the quality and spatial resolution of the CRU dataset and was concluded to be useful for investigations related to climate change across China. The dataset presented in this article has been published in the Network Common Data Form (NetCDF) at 10.5281/zenodo.3114194 for precipitation (Peng, 2019a) and 10.5281/zenodo.3185722 for air temperatures at 2 m (Peng, 2019b) and includes 156 NetCDF files compressed in zip format and one user guidance text file. [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]

Diurnal cycle of surface air temperature T is an important metric indicating the feedback of land-atmospheric interaction to global warming, whereas the ability of current reanalyses to reproduce its variation had not been assessed adequately. Here, we evaluate the daily maximum temperature Tmax, daily minimum temperature Tmin, and diurnal temperature range (DTR) in five reanalyses based on observations collected at 2253 weather stations over China. Our results show that the reanalyses reproduce Tmin very well; however, except for Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), they substantially underestimate Tmax and DTR by 1.21°-6.84°8 over China during the period of 1980-2014. MERRA-2 overestimates Tmax and DTR by 0.35° and 0.81°C, which are closest with observation. The reanalyses are skillful in reproducing the interannual variability of Tmax and Tmin but relatively poor for DTR. All reanalyses underestimate the warming trend of Tmin by 0.13°-0.17°C(10 yr)-1 throughoutChina during 1980-2014, and underestimate the warming trend of Tmax by 0.24°-0.40°C (10 yr)-1 in northwestern China while overestimating this quantity by 0.18°-0.33°C (10 yr)-1 in southeastern China. These trend biases in Tmax and Tmin introduce a positive trend bias in DTR of 0.01°-0.26°C (10 yr)-1 within China, especially in the north China plain and southeastern China. In the five reanalyses, owing to the sensitivity discrepancies and trend biases, the surface solar radiation Rs and precipitation frequency (PF) are notable deviation sources of the diurnal cycle of air temperature, which explain 31.0%-38.7% (31.9%-37.8%) and 9.8%-22.2% (7.4%-15.3%) of the trend bias in Tmax (DTR) over China, respectively. [ABSTRACT FROM AUTHOR]

The diurnal variation of rainfall over China associated with landfalling tropical cyclones (TCs) is investigated using hourly rain gauge observations obtained from 2425 conventional meteorological stations in China. Records between 12 h prior to landfall and 12 h after landfall of 450 landfalling TCs in China from 1957 to 2014 are selected as samples. The harmonic analysis shows an obvious diurnal signal in TC rainfall with a rain-rate peak in the early morning and a minimum in the afternoon. The diurnal cycle in the outer region (between 400- and 900-km radii from the storm center) is found to be larger than in the core region (within 400 km of the storm center). This could be attributed to the effect of land on the inner core of the storms as the diurnal cycle is distinct in the core region well before landfall. As the result of this diurnal cycle, TCs making landfall at night tend to have cumulative precipitation, defined as the precipitation cumulated from the time at landfall to 12 h after landfall, about 30% larger than those making landfall around noon or afternoon. Moreover, the radial propagation of the diurnal cycle in TC rain rate, which has been a controversial phenomenon in some previous studies with remote sensing observations, was not present in this study that is based on rain gauge observations. Results also show that the diurnal signal has little dependence on the storm intensity 12 h prior to landfall. [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]

Drought disasters cause great economic losses in China every year, especially in its southwest, and they have had a major influence on economic development, lives, and property. In this study, precipitation and drought hazards were examined for a region covering Yunnan, Guizhou, and Guangxi Provinces to assess the spatial and temporal distribution of different drought hazard grades in this region. Annual precipitation data from 90 meteorological stations in or around the study area were collected and organized for the period of 1964-2013. A spatiotemporal covariance model was calculated and fitted. The Bayesian maximum entropy (BME) method, which considers physical knowledge bases to reduce errors, was used to provide an optimal estimation of annual precipitation. Regional annual precipitation distributions were determined. To analyze the spatiotemporal patterns of the drought hazard, the annual standardized precipitation index was used to measure drought severity. A method that involves space-time scan statistics was used to detect the most likely spatiotemporal clusters of the drought hazards. Test-significance p values for all of the calculated clusters were less than 0.001, indicating a high significance level. The results showed that Yunnan Province was a drought-prone area, especially in its northwest and center, followed by Guizhou Province. In addition, Yunnan and Guizhou Provinces were cluster areas of severe and extreme drought. The most likely cluster year was 1966; it was clustered five times during the study period. In this study, the evolutionary process of drought hazards, including spatiotemporal distribution and spatiotemporal clustering characteristics, was considered. The results may be used to provide support for prevention and mitigation of drought in the study area such as optimizing the distribution of drought-resisting resources, drought monitoring, and evaluating potential drought impacts. [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]

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]

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]

As an important global data resource, reanalysis is widely applied for climate impact studies of the past several decades. For the first time, monthly mean temperature and monthly total precipitation derived from the newest generation reanalysis product-the ECMWF twentieth-century reanalysis dataset (ERA-20CM)-is quantitatively evaluated based on probability density functions and 702 meteorological stations during the period of 1960-2009 across China. This study attempts to investigate how well each member ensemble prediction of ERA-20CM performs for different regions. Generally, all ensemble predictions in ERA-20CM are able to recreate the real conditions on a comparable level. More than 90% of the observed probability for temperature and more than 80% of the probabilities for precipitation could be captured by ERA-20CM over China. However, the performance changes significantly from region to region because of different topographical features and climate characteristics. The Tibetan Plateau is the most difficult to model for all member ensembles. The Jianhuai region is the area with the best performance for both temperature and precipitation. Although the best and worst ensembles for temperature and precipitation for each region were selected according to the skill scores, the differences among the 10-member ensemble predictions are negligible. This evaluation would be helpful for the potential users of reanalysis data, such as ERA-20CM for local climate impact assessments in China. [ABSTRACT FROM AUTHOR]

Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998-2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China. [ABSTRACT FROM AUTHOR]

To project local precipitation at the existing meteorological stations in China's Beijing-Tianjin-Hebei region in the future, local daily precipitation was simulated for three periods (2006–2030, 2031–2050, and 2051–2070) under RCP 4.5 and RCP 8.5 emission scenarios. These projections were statistically downscaled using a weather generator (BCC/RCG-WG) and the output of five global climate models. Based on the downscaled daily precipitation at 174 stations, eight indices describing mean and extreme precipitation climates were calculated. Overall increasing trends in the frequency and intensity of the mean and extreme precipitation were identified for the majority of the stations studied, which is in line with the GCMs' output. However, the downscaling approach enables more local features to be reflected, adding value to applications at the local scale. Compared with the baseline during 1961–2005, the regional average annual precipitation and its intensity are projected to increase in all three future periods under both RCP 4.5 and RCP 8.5. The projected changes in the number of days with precipitation are relatively small across the Beijing-Tianjin-Hebei region. The regional average annual number of days with precipitation would increase by 0.2~1.0% under both RCP 4.5 and RCP 8.5, except during 2031–2050 under RCP 8.5 when it would decrease by 0.7%. The regional averages of annual days with precipitation ≥25 mm and ≥40 mm, the greatest one-day and five-day precipitation in the Beijing-Tianjin-Hebei region, are projected to increase by 8~30% during all the three periods. The number of days with daily precipitation ≥40 mm was projected to increase most significantly out of the eight indices, indicating the need to consider increased flooding risk in the future. The average annual maximum number of consecutive days without precipitation in the Beijing-Tianjin-Hebei region is projected to decrease, and the drought risk in this area is expected to decrease. [ABSTRACT FROM AUTHOR]

Low accuracy and coarse spatial resolution are the two main drawbacks of satellite precipitation products. Therefore, calibration and downscaling are necessary before these products are applied. This study proposes a two-step framework to improve the accuracy of satellite precipitation estimates. The first step is data merging based on optimum interpolation (OI), and the second step is downscaling based on geographically weighted regression (GWR); therefore, the framework is called OI-GWR. An Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) product is used to demonstrate the effectiveness of OI-GWR in the Tianshan Mountains, China. First, the original IMERG precipitation data (OIMERG) are merged with rain gauge data using the OI method to produce corrected IMERG precipitation data (CIMERG). Then, using CIMERG as the first guess and the normalized difference vegetation index (NDVI) as the auxiliary variable, GWR is utilized for spatial downscaling. The two-step OI-GWR method is compared with several traditional methods, including GWR downscaling (Ori_GWR) and spline interpolation. The cross-validation results show that (1) the OI method noticeably improves the accuracy of OIMERG, and (2) the 1-km downscaled data obtained using OI-GWR are much better than those obtained from Ori_GWR, spline interpolation, and OIMERG. The proposed OI-GWR method can contribute to the development of high-resolution and high-accuracy regional precipitation datasets. However, it should be noted that the method proposed in this study cannot be applied in regions without any meteorological stations. In addition, further efforts will be needed to achieve daily- or hourly-scale downscaling of precipitation. [ABSTRACT FROM AUTHOR]

In this study, the major winter wheat planting area of China is selected as the study area, with the time scale of the growth period of winter wheat (a total of 56 growth periods during October 1961 to May 2016). The significance, stability, magnitude of the trend and the average trend of the study area with eight temperature indices and seven precipitation indices of 453 meteorological stations are tested by Mann–Kendall method and Sen's nonparametric method. The following observation can be made: (1) the cold extreme indices show strong and stable downward trend in most of the stations in the study area, while the hot extreme indices show a strong and stable upward trend, especially in the northern winter wheat planting area and the north of the southern winter wheat planting area. (2) The trends of extreme precipitation indices in most of the sites in the study area are insignificant and unstable. Only in R20mm, a significant and stable decreasing trend is shown in some stations, which is mainly located in the northern winter wheat planting area and part of the central and western regions in the study area. The results in some ways could enrich the references for understanding the climate change in the growth period of winter wheat in the region and help to formulate a better agronomic management practice of winter wheat. [ABSTRACT FROM AUTHOR]