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In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China. [ABSTRACT FROM AUTHOR]

ABSTRACT In this article, the analysis of simulated and projected climatic changes in the Indus River Basin ( IRB) is presented. The performance of the regional climate model COSMO-CLM ( CCLM) driven by the global circulation model MPI-ESM-LR is evaluated on the ability of reproducing temperature, precipitation, and wind pattern for the period 1961-2005. There exist quantitative biases, especially in precipitation pattern, which are associated to the diverse reproduction of the atmospheric circulation by the global circulation model. The overall results show that CCLM is able to satisfyingly capture the dominant spatial characteristics in annual temperature and precipitation time series, including the warming trend, and the seasonal variations. The changes in precipitation and temperature over the IRB are projected for the mid- (2046-2065) and late-21st century (2081-2100). Relative to the baseline period (1986-2005), the average annual temperature will increase during the mid- and late-21st century over the whole basin. Extreme temperature events, i.e. heat waves, are more likely to occur. An increase in summer temperature is also projected especially in the upper IRB, where the persistent increase is likely to cause further melting of glaciers. The annual precipitation will decrease in both the mid- and late-21st century with significant spatial changes. A decrease in the monsoon precipitation is also projected, particularly in the central and southern plains of lower altitudes, which might be highly related to the reduction of wet air from the Indian Ocean and the increment in outflow to the east of the IRB. For winter and spring precipitation, except for the late-21st century under the representative climate pathway (RCP) 2.6, a decreasing trend is projected, which might be caused by the reduction of water vapour from the west. This will further weaken the availability of water resources in these seasons, especially in the upper IRB of higher altitudes. [ABSTRACT FROM AUTHOR]

In this study, the intensity, area, and duration of droughts in China are analyzed using the Standardized Precipitation Index (SPI). The SPI was calculated on monthly data for 530 meteorological stations in China for the period 1960-2013. The time series were analyzed for ten major hydrological regions of China, respectively. The relationships between the intensity and the area of droughts for a specific duration were analyzed by the intensity-area-duration method. The results show that areas with a significant trend in dryness can be found in a band reaching from the southwest to the northeast of China, while areas with significant trends in wetness are especially detected in the northern river basins in recent decades. In addition, for recent years (2000-2013), most of the ten major hydrological regions show opposite trends in the SPI when compared to the whole study period (1960-2013) except for the central and southwestern parts of China. This dryness/wetness trends are related to the intensity and duration of drought events, which have been stronger and lasted longer in the detected dryness band except for some northern river basins. A regional shift of drought centers is found from the northwest to the southeast within Central China. Moreover, a decreasing trend in drought area is observed, which might be related to the regional changes in precipitation pattern associated with the atmosphere-ocean interaction. Changes in the SST of the Tropical Pacific and the Tropical Indian Ocean may have resulted in frequent severe drought events of small areal extent in the central and southwestern parts of China. For the study period, the most severe droughts that covered large areas mainly occurred in the north and west of China during the mid-to-late twentieth century. However, in the early twenty-first century, the most severe droughts were located in the southwest of China covering areas less than 0.7 million km. Conclusively, drought areas show a decreasing tendency, while more intense droughts of longer duration have been experienced, especially in the south of China, in the last decades. [ABSTRACT FROM AUTHOR]

This study identifies daily Meiyu-like East Asian Summer Monsoon patterns that are linked to precipitation observations in the Poyang lake catchment. This analysis provides insight into the dynamics of strong, local precipitation events and has the potential to improve projections of precipitation from coarse-grid numerical simulations. Precipitation observations between 1960 and 1999 are taken from 13 rain gauges located in the Poyang lake catchment, which is a sub-catchment of the Yangtze River. The analysis shows that the observations are linked to daily patterns of relative vorticity at 850 hPa (Vo850) and vertical velocity at 500 hPa (W500) taken from the ERA-40 re-analysis data set. The patterns are derived by two approaches: (a) empirical orthogonal function (EOF) analysis and (b) rotated EOF analysis. Vo850 and W500 refer to geostrophic and ageostrophic processes, respectively. A logistic regression connects the large-scale dynamics to the local observations, whereby a forward regression selects the patterns best suited as predictors for the probability of exceeding thresholds of 24 h accumulated rainfall at the gauges. The regression model is verified by cross-validation. The spatial structure of the detected patterns can be interpreted in terms of well-known meso-α-scale disturbances called Southwest vortices. Overall, the proposed EOF and rotated EOF patterns are both related to physical processes and have the potential to work as predictors for exceedance rates of local precipitation in the Poyang catchment. [ABSTRACT FROM AUTHOR]

Numerous dams and reservoirs in the Yangtze River basin have been constructed. Thus understanding the variability of hydroclimatological time series is important for the development of an optimal reservoir management strategy. This is crucial for life in the densely populated basin known to be highly susceptible to floods and droughts. Time series of annual precipitation totals and precipitation totals from May to September (the rainy season) for the period from 1961 to 2002 were averaged within the subbasins of the Yangtze River. The resulting time series were analyzed for similarities and differences and continuous wavelet transforms were produced to identify inherent quasi-periodicity. The western subbasins have shown a diverse pattern of periods with high and low precipitation variance. We have detected prominent periods of high precipitation variance for the central and eastern subbasins in the 1980s and 1990s, respectively. [ABSTRACT FROM AUTHOR]

Time series of the average annual Palmer drought severity index (PDSI) and standardized precipitation index (SPI) were calculated for 483 meteorological stations in China using monthly data from 1961 to 2005. The time series were analyzed for 10 large regions covering the territory of China and represented by seven river basins and three areas in the southeast, southwest, and northwest. Results show that the frequencies of both dry and wet years for the whole period are lower for southern basins than for the northern ones when estimated by PDSI but very similar for all basins when calculated by SPI. The frequencies of dry and wet years calculated for 5- and 15-yr subperiods by both indices show the upward dry trends for three northeastern basins, Songhuajiang, Liaohe, and Haihe; a downward dry trend for the northwest region; a downward wet trend for the Yellow River basin; and an upward wet trend for the northwest region. Trend detection using PDSI indicates statistically significant negative trends for many stations in the northeastern basins (Songhuajiang, Liaohe, Haihe, and Yellow) and in the middle part of the Yangtze, whereas statistically significant positive trends were found in the mountainous part of the northwest region and for some stations in the upper and lower Yangtze. A moderately high and statistically significant correlation between the percentage of runoff anomaly (PRA) and the annual average PDSI and SPI was found for six large rivers. The results confirm that PDSI and SPI indices can be used to describe the tendency of dryness and wetness severity and for comparison in climate impact assessment. [ABSTRACT FROM AUTHOR]

Based on the daily observational precipitation data at 147 stations in the Yangtze River Basin during 1960–2005 and projected daily data of 79 grid cells from the ECHAM5/ MPI-OM model in the 20th and 21st century, time series of precipitation extremes which contain AM (Annual Maximum) and MI (Munger Index) are constructed. The distribution feature of precipitation extremes is analyzed based on the two index series. Three principal results were obtained, as stated in the sequel. (i) In the past half century, the intensity of extreme heavy precipitation and drought events was higher in the mid-lower Yangtze than in the upper Yangtze reaches. Although the ECHAM5 model still can’t capture the precipitation extremes over the Yangtze River Basin satisfactorily, spatial pattern of the observed and the simulated precipitation extremes are much similar to each other. (ii) For quantifying the characteristics of extremely high and extremely low precipitation over the Yangtze River Basin, four probability distributions are used, namely: General Extreme Value (GEV), General Pareto (GPA), General Logistic (GLO), and Wakeby (WAK). It was found that WAK can adequately describe the probability distribution of precipitation extremes calculated from both observational and projected data. (iii) Return period of precipitation extremes show spatially different changes under three greenhouse gas emission scenarios. The 50-year heavy precipitation and drought events from simulated data during 1951–2000 will become more frequent, with return period below 25 years, for the most mid-lower Yangtze region in 2001–2050. The changing character of return periods of precipitation extremes should be taken into account for the hydrological design and future water resources management. [ABSTRACT FROM AUTHOR]

Abstract: The suspected impact of climate warming on precipitation distribution is examined in the Yangtze River Basin. Daily precipitation data for 147 meteorological stations from 1961–2000 and monthly discharge data for three stations in the basin have been analyzed for temporal and spatial trends. The methods used include the Mann–Kendall test and simple regression analysis. The results show (1) a significant positive trend in summer precipitation at many stations especially for June and July, with the summer precipitation maxima in the middle and lower Yangtze River basin in the 1990s; (2) a positive trend in rainstorm frequency that is the main contributor to increased summer precipitation in the basin; and (3) a significant positive trend in flood discharges in the middle and lower basin related to the spatial patterns and temporal trends of both precipitation and individual rainstorms in the last 40 years. The rainstorms have aggravated floods in the middle and lower Yangtze River Basin in recent decades. The observed trends in precipitation and rainstorms are possibly caused by variations of atmospheric circulation (weakened summer monsoon) under climate warming. [Copyright &y& Elsevier]

Precipitation trends in the Yangtze River catchment (PR China) have been analyzed for the past 50 years by applying the Mann-Kendall trend test and geospatial analyses. Monthly precipitation trends of 36 stations have been calculated. Significant positive trends at many stations can be observed for the summer months, which naturally show precipitation maxima. They were preceded and/or followed by negative trends. This observation points towards a concentration of summer precipitation within a shorter period of time. The analysis of a second data set on a gridded basis with 0.5° resolution reveals trends with distinct spatial patterns. The combination of classic trend tests and spatially interpolated precipitation data sets allows the spatiotemporal visualization of detected trends. Months with positive trends emphasize the aggravation of severe situation in a region, which is particularly prone to flood disasters during summer. Reasons for the observed trends were found in variations in the meridional wind pattern at the 850 hPa level, which account for an increased transport of warm moist air to the Yangtze River catchment during the summer months. [ABSTRACT FROM AUTHOR]

Abstract: Significant quasi-cycles in precipitation time series of 132 climate stations spread over China from 1951 to 2002 have been detected by applying Autocorrelation Spectral Analysis (ASA). By the same method, significant quasi-cycles have also been identified in time series of the potential influencing factors: Southern Oscillation Index (SOI), Sea Surface Temperature (SST) and Sea Level Pressure (SLP). Similarities between some precipitation time series spectra and the spectrum of a potential driving force have been detected; e.g. several series from the Yangtze River''s middle reaches show 3–4-year cycles which are similar to the SOI and several SST signals. These time series have been further investigated by low-pass filtering with the Savitzky–Golay filter and by means of correlation analysis. It is proved that the SOI and the SSTs of the Bay of Bengal are in relatively stable anti-phase. However, no stable link between these signals and the precipitation series in the Yangtze River basin can be detected. Subsequent analyses of 850hPa winds lead to the outcome that certain wind patterns could either suppress or force the SST and SOI teleconnection signals. [Copyright &y& Elsevier]

Since the 1950s, the population in the arid to hyperarid Tarim River basin has grown rapidly concurrent with an expansion of irrigated agriculture. This threatens the Tarim River basin's natural ecosystems and causes water shortages, even though increased discharges in the headwaters have been observed more recently. These increases have mainly been attributed to receding glaciers and are projected to cease when the glaciers are unable to provide sufficient amounts of meltwater. Under these circumstances water management will face a serious challenge in adapting its strategies to changes in river discharge, which to a greater extent will depend on changes in precipitation. In this paper, we aim to develop accurate seasonal predictions of precipitation to improve water resources management. Possible predictors of precipitation for the Tarim River basin were either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 and NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data in monthly resolution. To evaluate the significance of the predictors, they were then correlated with the monthly precipitation dataset GPCCv6 extracted for the Tarim River basin for the period 1961 to 2010. Prior to the Spearman rank correlation analyses, the precipitation data were averaged over the subbasins of the Tarim River. The strongest correlations were mainly detected with lead times of four and five months. Finally, an artificial neural network model, namely a multilayer perceptron (MLP), and a multiple linear regression (LR) model were developed each in two different configurations for the Aksu River subbasin, predicting precipitation five months in advance. Overall, the MLP using all predictors shows the best performance. The performance of both models drops only slightly when restricting the model input to the SST of the Black Sea and the Siberian High Intensity (SHI) pointing towards their importance as predictors. [ABSTRACT FROM AUTHOR]

The simulation results of CMIP5 (Coupled Model Inter-comparison Project phase 5) multi-model ensemble in the Indus River Basin (IRB) are compared with the CRU (Climatic Research Unit) and APHRODITE (Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation) datasets. The systematic bias between simulations and observations is corrected by applying the equidistant Cumulative Distribution Functions matching method (EDCDFm) and high-resolution simulations are statistically downscaled. Then precipitation and temperature are projected for the IRB for the mid-21st century (2046–2065) and late 21st century (2081–2100). The results show that the CMIP5 ensemble captures the dominant features of annual and monthly mean temperature and precipitation in the IRB. Based on the downscaling results, it is projected that the annual mean temperature will increase over the entire basin, relative to the 1986–2005 reference period, with greatest changes in the Upper Indus Basin (UIB). Heat waves are more likely to occur. An increase in summer temperature is projected, particularly for regions of higher altitudes in the UIB. The persistent increase of summer temperature might accelerate the melting of glaciers, and has negative impact on the local freshwater availability. Projections under all RCP scenarios show an increase in monsoon precipitation, which will increase the possibility of flood disaster. A decreasing trend in winter and spring precipitation in the IRB is projected except for the RCP2.6 scenario which will cause a lower contribution of winter and spring precipitation to water resources in the mid and high altitude areas of the IRB. [ABSTRACT FROM AUTHOR]

In recent years, an expansion of irrigated agriculture and rapid population growth have threatened the Tarim River basin's natural ecosystems and caused water shortages. Improving the water resources management in the basin requires accurate seasonal precipitation forecasts. Based on previous research, possible predictors of precipitation were selected and either downloaded directly or calculated using NCEP/NCAR Reanalysis 1 or NOAA Extended Reconstructed Sea Surface Temperature (SST) V3b data. Predictors were correlated with precipitation data, provided by the National Climate Centre of the China Meteorological Administration for the period 1961 to 2010 and averaged over the subbasins of the Tarim River. The Spearman rank correlation analyses with lead times of up to six months (or two seasons) revealed significant (at the 1% level) and strong (ρ ≤ −0.6 or ρ ≥ 0.6) correlations of precipitation in all subbasins with the SST and monsoon indices as well as with the Siberian High Intensity (SHI) and the Westerly Circulation Index (WCI). Lastly, we demonstrate the setup of a forecast model based on a multiple linear regression on the example of the Hotan River subbasin. This model predicts precipitation 5 months in advance with reasonable accuracy in two out of three configurations. [ABSTRACT FROM AUTHOR]

Abstract: This study investigated future changes of dryness/wetness in ten large river basins: the Songhuajiang River basin, the Liaohe River basin, the Haihe River basin, the Yellow River basin, the Huaihe River basin, the Yangtze River basin, the Pearl River basin, the Southeast River basins, the Southwest River basins and the Northwest Inland River basins across China during the first 50 years of the 21st century. The study was carried out according to the Standardized Precipitation Index (SPI), which is calculated by monthly precipitation data of ECHAM5/MPI-OM. Three anthropogenic greenhouse gas emission scenarios, SRES-A2, SRES-A1B and SRES-B1 have been considered. The frequency of dry/wet periods in these river basins was calculated and the trend detected by the Mann–Kendall non-parametric test. The results reveal that there is a trend towards drier conditions from northeast to southwest China in scenario A2 and a similar spatial distribution pattern in scenario A1B and B1. Areas with a high frequency of drought are detected under all three scenarios. In the next half century, the Haihe River basin, northeast China, is expected to show a significant trend towards drier conditions, which pass the 95% confidence level in scenario A2. In the Yellow River basin, the Huaihe River basin, the Yangtze River basin and the Pearl River basin, an obvious trend towards wetter conditions has been detected in scenario A1B. The Songhuajiang River basin, the Haihe River basin, the Yellow River basin and the Huaihe River basin show a trend towards wetter conditions, which passed the 90% confidence level in scenario B1. The future dryness/wetness frequency situation is complex in the ten large river basins. [ABSTRACT FROM AUTHOR]

Abstract: Gridded climate data sets are widely used in the analysis, modeling and forecasting of the consequences of climate change. The objective of this study is to compare the impact of different climate datasets (station vs. gridded) on the parameterization of a hydrological model (developed using SWAT2005) of the River Xiangxi, the largest tributary of Yangtze River in the Hubei part of the Three Gorges Reservoir. Climate data used in this study derive from two sources: point daily observations from the Xingshan meteorological station (STN) and gridded (0.5°×0.5°) monthly observations of the CRU TS3.0 global dataset (CRU) downscaled to daily data using a weather generator. Data from 1970 to 1974 were applied for sensitivity analyses and autocalibration and subsequently validate hindcasts over the period 1976–1986. Despite there being only slight differences in mean annual precipitation (1003mm vs. 1052mm) between STN and CRU, the data differ more in their estimates of the number of rain days (136 vs. 112) and wet days standard deviation (11.75mm vs. 18.49mm). The mean, maximum and minimum temperatures from CRU are all lower than those from STN. SWAT parameter sensitivity analysis results show slight differences in the relative rank of the most sensitive parameters, with the differences mainly caused by the lower temperature and more intensive rainfall in CRU relative to STN. Autocalibrated parameters showed very similar values, except for the surface runoff lag coefficient which is higher for the CRU dataset compared to that derived from the STN dataset. Statistic results for discharge simulated based on CRU compared rather well with that based on STN CRU as evaluated using the standard statistics of the Nash–Sutcliffe efficiency, coefficient of determination, and percent error. The sensitivity analysis and autocalibration tool embedded in SWAT2005 is a powerful utility in hydrological modeling of the River Xiangxi, and the CRU dataset appears to be appropriate for application to hydrological modeling in this case, thus providing a good basis for climate change studies. [Copyright &y& Elsevier]

Droughts reflect the extent of water deficit on the land surface, and can be quantified by various indices. In current study, potential evapotranspiration (PET), which is one of factors that have great influence on the drought condition, is estimated by a set of models. The set consists of four temperature-decisive models (Hamon, Hargreaves-Samani, Oudin, Thornthwaite), two radiation-decisive models (Energy-Only and Priestley-Taylor) and two synthesis models (Penman and Penman-Monteith). Subsequently, Standardized Precipitation Evapotranspiration Index (SPEI) is applied to assess the spatial and temporal distributions of droughts for the arid, the semi-arid and semi-humid, as well as the humid climatic zones in China for 1961–2017. The results show that: (1) Taking China as a whole, annual PET estimated by Penman-Monteith (P-M) formula is about 1000 mm, which is in the middle of the range of results from eight algorithms. Annual PET values estimated by radiation-decisive methods are relatively close to those obtained by P-M, while temperature-decisive methods yield lower values and the largest disparity among the different PET models can be up to 2.5 fold. (2) Comparing to drought records, both P-M and Thornthwaite are suitable for assessing drought condition on the national scale, but the drought assessed by the Thornthwaite method is worse than that by the P-M method in 1990–2017 when warming is faster than before in the arid region. (3) Increase first and then decrease of values of the SPEI index are detected in China for 1961–2017 by all PET estimations. Averaged over entire China, the wetting trend has changed to drying in the early 1990s by P-M-based SPEI. More meteorological stations are found to experience droughts after the early 1990s, particularly in the western humid region and the central semi-arid and semi-humid region. In contrast, a wetness tendency is found in the arid region. (4) Patterns of the drought frequency and duration by all PET algorithms maintain relatively good correspondence in the semi-arid and semi-humid region as well as the humid region. But in the arid region, drought frequency obtained by P-M is lower than for radiation-decisive and temperature-decisive models, while drought duration is longer. • Eight algorithms clustered into three groups are used to estimate potential evapotranspiration (PET) for China in 1961–2017. • A wetness trend is detected by synthesis and radiation-decisive models based SPEI, while getting drier by temperature-decisive models in the arid region. • A case study in China shows that choice of potential evapotranspiration formulas influences largely on drought assessment. [ABSTRACT FROM AUTHOR]