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In this paper, monthly, maximum seasonal, and maximum annual hydrometeorological (i.e., evaporation, lake water levels, and rainfall) data series from the Kariba catchment area of the Zambezi River basin, Zimbabwe, have been analyzed in order to determine appropriate probability distribution models of the underlying climatology from which the data were generated. In total, 16 probability distributions were considered and the Kolmogorov-Sminorv (KS), Anderson-Darling (AD), and chi-square (χ2) goodness-of-fit (GoF) tests were used to evaluate the best-fit probability distribution model for each hydrometeorological data series. A ranking metric that uses the test statistic from the three GoF tests was formulated and used to select the most appropriate probability distribution model capable of reproducing the statistics of the hydrometeorological data series. Results showed that, for each hydrometeorological data series, the best-fit probability distribution models were different for the different time scales, corroborating those reported in the literature. The evaporation data series was best fit by the Pearson system, the Lake Kariba water levels series was best fit by the Weibull family of probability distributions, and the rainfall series was best fit by the Weibull and the generalized Pareto probability distributions. This contribution has potential applications in such areas as simulation of precipitation concentration and distribution and water resources management, particularly in the Kariba catchment area and the larger Zambezi River basin, which is characterized by (i) nonuniform distribution of a network of hydrometeorological stations, (ii) significant data gaps in the existing observations, and (iii) apparent inherent impacts caused by climatic extreme events and their corresponding variability. [ABSTRACT FROM AUTHOR]

The Colorado River basin (CRB) supplies water to approximately 40 million people and is essential to hydropower generation, agriculture, and industry. In this study, a monthly water balance model is used to compute hydroclimatic water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff) for the period 1901-2014 across the entire CRB. The time series of monthly runoff is aggregated to compute wateryear runoff and then used to identify drought periods in the basin. For the 1901-2014 period, eight basinwide drought periods were identified. The driest drought period spanned years 1901-04, whereas the longest drought period occurred during 1943-56. The eight droughts were primarily driven by winter precipitation deficits rather than warm temperature anomalies. In addition, an analysis of prehistoric drought for the CRB--computed using tree-ring-based reconstructions of the Palmer drought severity index--indicates that during some past centuries drought frequency was higher than during the twentieth century and that some centuries experienced droughts that were much longer than those during the twentieth century. More frequent or longer droughts than those that occurred during the twentieth century, combined with continued warming associated with climate change, may lead to substantial future water deficits in the CRB. [ABSTRACT FROM AUTHOR]

The upper Colorado River basin (UCRB) is one of the primary sources of water for the western United States, and increasing temperatures likely will elevate the risk of reduced water supply in the basin. Although variability in water-year precipitation explains more of the variability in water-year UCRB streamflow than water-year UCRB temperature, since the late 1980s, increases in temperature in the UCRB have caused a substantial reduction in UCRB runoff efficiency (the ratio of streamflow to precipitation). These reductions in flow because of increasing temperatures are the largest documented temperature-related reductions since record keeping began. Increases in UCRB temperature over the past three decades have resulted in a mean UCRB water-year streamflow departure of −1306 million m3 (or −7% of mean water-year streamflow). Additionally, warm-season (April through September) temperature has had a larger effect on variability in water-year UCRB streamflow than the cool-season (October through March) temperature. The greater contribution of warm-season temperature, relative to cool-season temperature, to variability of UCRB flow suggests that evaporation or snowmelt, rather than changes from snow to rain during the cool season, has driven recent reductions in UCRB flow. It is expected that as warming continues, the negative effects of temperature on water-year UCRB streamflow will become more evident and problematic. [ABSTRACT FROM AUTHOR]

The southwestern United States is highly sensitive to drought, prompting efforts to understand and predict its hydroclimate. Oftentimes, the emphasis is on wintertime precipitation variability, yet the southwestern United States exhibits a summertime monsoon where a significant portion of annual precipitation falls through daily convection activities manifested by a midtropospheric ridge of high pressure. Here, we examine synoptic patterns of the southwestern ridge through a k-means clustering analysis and assess how these synoptic patterns translate into streamflow changes in the upper Colorado River basin. A linear perspective suggests ∼17% of upper Colorado River discharge at the Lee's Ferry, Arizona, gauge comes from summertime monsoon rains. The ridge of high pressure exhibits diversity in its intensity, structure, and position, inducing changes in moisture advection and precipitation. A ridge shifted north or east of its climatological center increases moisture and precipitation over the southwestern United States, while a ridge toward the south or northwest inhibits precipitation. A ridge east of its climatological center contributes to increased streamflow, whereas a ridge west or northwest of its climatological center decreases streamflow. Cooling in the central tropical Pacific and the Pacific meridional mode region favors an eastward shift of the ridge of high pressure corresponding to wet days. Eastern tropical Pacific warming favors a southward shift of the ridge corresponding to dry days. These results support an intermediate scale between climate forcing and summertime Colorado River discharge through changes in the intensity, structure, and position of the southwestern ridge of high pressure, integral to the U.S. Southwest hydroclimate. [ABSTRACT FROM AUTHOR]

Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitation P and temperature T footprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonal P and T (e.g., R2 = 0.50 for May–September T). These were disaggregated to monthly values, which were then routed through a water balance model to generate "indirectly" reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r = 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change. Significance Statement: We show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime. [ABSTRACT FROM AUTHOR]

Recent severe droughts, extreme floods, and increasing differences between seasonal high and low flows on the Amazon River may represent a twenty-first-century increase in the amplitude of the hydrologic cycle over the Amazon Basin. These precipitation and streamflow changes may have arisen from natural ocean-atmospheric variability, deforestation within the drainage basin of the Amazon River, or anthropogenic climate change. Tree-ring reconstructions of wetseason precipitation extremes, substantiated with historical accounts of climate and river levels on the Amazon River and in northeast Brazil found in the Brazilian Digital Library, indicate that the recent river-level extremes on the Amazon may have been equaled or possibly exceeded during the preinstrumental nineteenth century. The "Forgotten Drought" of 1865 was the lowest wet-season rainfall total reconstructed with tree-rings in the eastern Amazon from 1790 to 2016 and appears to have been one of the lowest stream levels observed on the Amazon River during the historical era according to firsthand descriptions by Louis Agassiz, his Brazilian colleague Joao Martins da Silva Coutinho, and others. Heavy rains and flooding are described during most of the tree-ring-reconstructed wet extremes, including the complete inundation of "First Street" in Santarem, Brazil, in 1859 and the overtopping of the Bittencourt Bridge in Manaus, Brazil, in 1892. These extremes in the tree-ring estimates and historical observations indicate that recent high and low flow anomalies on the Amazon River may not have exceeded the natural variability of precipitation and streamflow during the nineteenth century. [ABSTRACT FROM AUTHOR]

Knowledge gain in the characteristics and mechanisms of drought propagation is indispensable for timely drought early warning and risk reduction over the grassland eco-region. This study focused on the Xilin River basin, which is a typical inland river basin located in the Inner Mongolia temperate steppe, China. The characteristics of meteorological and hydrological drought were assessed by applying the standardized precipitation index and standardized streamflow index. The propagation relationship between meteorological and hydrological droughts was then investigated from both static and dynamic perspectives, and the possible reasons for its temporal dynamics were discussed by considering environmental factors. Our results showed that the Xilin River basin has suffered from more serious meteorological drought than hydrological drought during the past 60 years, with a stationary evolution of meteorological drought but an overall drying trend in hydrological drought. The propagation from meteorological to hydrological droughts exhibited obvious seasonality, characterized by stronger intensity and shorter response time in the wet season. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, especially showing a significant trend in April, May, and August. The dynamic changes in propagation time affected by regional forces were principally ruled by the precipitation variation positively and strongly, and they were moderately controlled by temperature, vegetation cover, and deep-layer soil moisture, with season-dependent effects. The effects of low-frequency atmospheric anomalies on drought propagation will be further investigated in future studies, which are expected to provide a better understanding of the physical mechanism of the large-scale climate forcing on local drought condition. Significance Statement: A new research approach was proposed to assess the propagation relationship between meteorological and hydrological drought from both static and dynamic perspectives, and the possible reasons for the temporal dynamics were discussed by considering environmental factors. Focusing on an inland river basin over the Inner Mongolia typical steppe, the propagation from meteorological to hydrological droughts showed obvious seasonality. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, which could be explained by the regional hydrometeorological conditions. The advanced understanding of drought propagation provides a scientific base for water resources planning and drought management within a grassland region. [ABSTRACT FROM AUTHOR]

The trend analysis approach is adopted for the prediction of future climatological behavior and climate change impact on agriculture, the environment, and water resources. In this study, the innovative trend pivot analysis method (ITPAM) and trend polygon star concept method were applied for precipitation trend detection at 11 stations located in the Soan River basin (SRB), Potohar region, Pakistan. Polygon graphics of total monthly precipitation data were created and trends length and slope were calculated separately for arithmetic mean and standard deviation. As a result, the innovative methods produced useful scientific information and helped in identifying, interpreting, and calculating monthly shifts under different trend behaviors, that is, increase in some stations and decrease in others of precipitation data. This increasing and decreasing variability emerges from climate change. The risk graphs of the total monthly precipitation and monthly polygonal trends appear to show changes in the trend of meteorological data in the Potohar region of Pakistan. The monsoonal rainfall of all stations shows a complex nature of behavior, and monthly distribution is uneven. There is a decreasing trend of rainfall in high land stations of SRB with a significant change between the first dataset and the second dataset in July and August. It was examined that monsoon rainfall is increasing in lowland stations indicating a shifting pattern of monsoonal rainfall from highland to lowland areas of SRB. The increasing and decreasing trends in different periods with evidence of seasonal variations may cause irregular behavior in the water resources and agricultural sectors. Significance Statement: The monthly polygonal trends with risk graphs of total monthly precipitation data depicted a clear picture of climate change effects in the Potohar region of Pakistan. The monsoonal rainfall showed a significant decreasing trend in highland stations and an increasing trend in lowland stations, indicating a shifting pattern of monsoonal rainfall from highland to lowland areas. [ABSTRACT FROM AUTHOR]

In the propagation from meteorological to hydrological drought, there are time-lag and step-abrupt effects, quantified in terms of propagation time and threshold, which play an important role in hydrological drought early warning. However, seasonal drought propagation time and threshold and their dynamics as well as the corresponding driving mechanism remain unknown in a changing environment. To this end, the standardized precipitation index (SPI) and standardized runoff index (SRI) were used respectively to characterize meteorological and hydrological droughts and to determine the optimal propagation time. Then, a seasonal drought propagation framework based on Bayesian network was proposed for calculating the drought propagation threshold with SPI. Finally, the seasonal dynamics and preliminary attribution of propagation characteristics were investigated based on the random forest model and correlation analysis. The results show that 1) relatively short propagation time (less than 9 months) and large propagation threshold (from −3.18 to −1.19) can be observed in the Toxkan River basins (subbasin II), especially for spring, showing low drought resistance; 2) drought propagation time shows an extended trend in most seasons, while the drought propagation threshold displays an increasing trend in autumn and winter in the Aksu River basin (subbasins I–II), and the opposite characteristics in the Hotan and Yarkant River basins (subbasins III–V); and 3) the impacts of precipitation, temperature, potential evapotranspiration, and soil moisture on drought propagation dynamics are inconsistent across subbasins and seasons, noting that reservoirs serve as a buffer to regulate the propagation from meteorological to hydrological droughts. The findings of this study can provide scientific guidelines for watershed hydrological drought early warning and risk management. Significance Statement: The aim of this study is to better understand how the delayed and step-abrupt effects of propagation from meteorological drought to hydrological drought can be characterized through propagation time and threshold. These response indicators determine the resistance of a catchment to hydrological droughts and meteorological droughts. They can help water resources management agencies to mitigate hydrological droughts by taking measures such as water storage, increasing revenue, and reducing expenditure. The findings of this study can provide scientific guidelines for watershed hydrological drought early warning and risk management. [ABSTRACT FROM AUTHOR]

This study analyzes the atmospheric variability that caused the largest floods affecting the town of Tortosa, Spain, in the mouth of the Ebro River (northeast Iberian Peninsula). The Tortosa flood database and flood marks in the nearby town of Xerta are used to define the more relevant flooding episodes (discharges >2900 m3 s−1) of the 1600–2005 period. We explore the atmospheric variability based on low-frequency patterns and synoptic types applying a multivariable analysis to grids at sea level pressure and geopotential at 500 hPa provided by the twentieth-century V3 Reanalysis Project for the instrumental period (since 1836). Output from the Last Millennium Ensemble Project was used to analyze the sea level pressure over the pre-instrumental period (before 1836). Our analysis includes 33 flood episodes. Four synoptic types are related to floods in Tortosa since 1836, characterized by low pressure systems that interact with the Mediterranean warm air mass and promote atmospheric destabilization. Flooding in Tortosa is related to relative high values of solar activity, positive Northern Hemisphere temperature anomalies, and NAO in positive phase. This result indicates that the major floods are related to zonal atmospheric circulations (west-to-east cyclone transfer). During winter, the main impact of the floods is located at the western part of the basin, and the Pyrenean subbasins are affected during autumn. The major finding is that similar flood behavior is detected since 1600, improving our understanding of past climates, enhancing the knowledge base for some aspects and impacts of climate change, and reducing uncertainty about future outcomes. Significance Statement: A total of 33 large floods (>2900 m3 s−1) were registered since 1600 in Tortosa, Spain, located at the mouth of the Ebro River (northeast Iberian Peninsula). They occur associated with low pressure systems that interact with the Mediterranean warm air mass promoting atmospheric destabilization. The floods in Tortosa are also associated with other important processes occurring at significantly longer time scales: high values of solar activity, positive Northern Hemisphere temperature anomalies, and NAO in positive phase, indicating that the major floods are related to zonal atmospheric circulations. The major finding is that we detect similar flood behaviors since 1600, improving our understanding of past climates, enhancing the knowledge base for some aspects and impacts of climate change, and reducing uncertainty about future outcomes. [ABSTRACT FROM AUTHOR]

In this study, a nonstationary standardized precipitation index (NSPI) is calculated by fitting precipitation data to the nonstationary gamma model with climate indices as covariates and compared with stationary standardized precipitation index (SSPI) in fitting observed precipitation and identifying meteorological droughts during 1964-2016 in the Yangtze River basin (YRB). Results show that changing trends of NSPI are roughly consistent with those of SSPI, but the NSPI performs better than SSPI for fitting precipitation. Using the NSPI, spatiotemporal variations and joint return period of drought characteristics are investigated by using modified Mann-Kendall and copula function. It is found that the west YRB experiences mostly severe droughts but shows a mitigating tendency, while in the north-central region, moderate droughts are dominant but have an aggravating tendency. Drought peak shares a spatial distribution pattern similar to intensity, with higher averages in the west and south-central basin and lower averages in the north-central part, but they exhibit a higher occurrence frequency of droughts. The joint return periods of drought characteristics reveal that slight and moderate droughts with duration D of no more than 3 months are more likely to occur in the YRB with return periods of 2-25 years. The severe- and extreme-intensity droughts with more than 3-month duration occur rarely in the YRB, but extreme peak droughts with slight or moderate intensity could hit most of the basin in 100 years. In addition, for most drought scenarios, droughts exhibit longer return periods in the north-central and southeast parts relative to other regions of the YRB. [ABSTRACT FROM AUTHOR]

The major tributary of the lower Colorado River, the Gila River, is a critical source of water for human and natural environments in the southwestern United States. Warmer and drier than the upper Colorado River basin, with less snow and a bimodal precipitation regime, the Gila River is controlled by a set of climatic conditions that is different from the controls on upper Colorado River flow. Unlike the Colorado River at Lees Ferry in Arizona, the upper Gila River and major Gila River tributaries, the Salt and Verde Rivers, do not yet reflect significant declines in annual streamflow, despite warming trends. Annual streamflow is dominated by cool-season precipitation, but the monsoon influence is discernable as well, variable across the basin and complicated by an inverse relationship with cool-season precipitation in the Salt and Verde River basins. Major multiyear streamflow droughts in these two basins have frequently been accompanied by wet monsoons, suggesting that monsoon precipitation may partially offset the impacts of a dry cool season. While statistically significant trends in annual streamflow are not evident, decreases in autumn and spring streamflow reflect warming temperatures and some decreases in spring precipitation. Because climatic controls vary with topography and the influence of the monsoon, the impact of warming on streamflow in the three subbasins is somewhat variable. However, given relationships between climate and streamflow, current trends in hydroclimate, and projections for the future, it would be prudent to expect declines in Gila River water supplies in the coming decades. Significance Statement: This research investigates the climatic controls on the Gila River and its major tributaries, the Verde and Salt Rivers, to gain insights on how trends in climate may impact future water supply. The Gila River is the major tributary of the lower Colorado River, but, unlike the situation for the upper Colorado River, no significant decreasing trends in annual streamflow are evident despite warming temperatures. Climate–streamflow relationships are more complex in this part of the Colorado River basin, and several factors may be buffering streamflow to the impact of warming. However, given the key climatic controls on streamflow, current and emerging trends in climate, and projections for the future, declines in streamflow should be expected in the future. [ABSTRACT FROM AUTHOR]

The approximately century-long instrumental record of precipitation over land reflects a single sampling of internal variability. Thus, the spatiotemporal evolution of the observations is only one realization of "what could have occurred" given the same climate system and boundary conditions but different initial conditions. While climate models can be used to produce initial-condition large ensembles that explicitly sample different sequences of internal variability, an analogous approach is not possible for the real world. Here, we explore the use of a statistical model for monthly precipitation to generate synthetic ensembles based on a single record. When tested within the context of the NCAR Community Earth System Model version 1 Large Ensemble (CESM1-LE), we find that the synthetic ensemble can closely reproduce the spatiotemporal statistics of variability and trends in winter precipitation over the extended contiguous United States and that it is difficult to infer the climate change signal in a single record given the magnitude of the variability. We additionally create a synthetic ensemble based on the Global Precipitation Climatology Centre (GPCC) dataset, termed the GPCC-synth-LE; comparison of the GPCC-synth-LE with the CESM1-based ensembles reveals differences in the spatial structures and magnitudes of variability, highlighting the advantages of an observationally based ensemble. We finally use the GPCC-synth-LE to analyze three water resource metrics in the upper Colorado River basin: frequency of dry, wet, and whiplash years. Thirty-one-year "climatologies" in the GPCC-synth-LE can differ by over 20% in these key water resource metrics due to sampling of internal variability, and individual ensemble members in the GPCC-synth-LE can exhibit large near-monotonic trends over the course of the last century due to sampling of internal variability alone. [ABSTRACT FROM AUTHOR]

The provision of climate services has the potential to generate adaptive capacity and help coffee farmers become or remain profitable by integrating climate information in a risk-management framework. Yet, to achieve this goal, it is necessary to identify the local demand for climate information, the relationships between coffee yield and climate variables, and farmers' perceptions and to examine the potential actions that can be realistically put in place by farmers at the local level. In this study, we assessed the climate information demands from coffee farmers and their perception on the climate impacts to coffee yield in the Samalá watershed in Guatemala. After co-identifying the related candidate climate predictors, we propose an objective, flexible forecast system for coffee yield that is based on precipitation. The system, known as NextGen, analyzes multiple historical climate drivers to identify candidate predictors and provides both deterministic and probabilistic forecasts for the target season. To illustrate the approach, a NextGen implementation is conducted in the Samalá watershed in southwestern Guatemala. The results suggest that accumulated June–August precipitation provides the highest predictive skill associated with coffee yield for this region. In addition to a formal cross-validated skill assessment, retrospective forecasts for the period 1989–2009 were compared with agriculturalists' perception on the climate impacts to coffee yield at the farm level. We conclude with examples of how demand-based climate service provision in this location can inform adaptation strategies like optimum shade, pest control, and fertilization schemes months in advance. These potential adaptation strategies were validated by local agricultural technicians at the study site. Significance Statement: In this study we wanted to provide climate services to coffee farmers in Guatemala who currently face challenges associated with climate variability and change. To do this, we first assessed what climate information they currently have at the farm level, how they use it in decision-making processes, and what improvements would benefit their risk-management framework (e.g., shade management) In addition, we evaluated farmers' perceptions related to the impact of climate to their coffee productivity. We verified the historical impact of several climate variables on coffee yield at the study site location and found that total rainfall for June–August is associated with coffee yield as originally referred by farmers. After identifying rainfall as one of the critical factors associated with coffee yield in this particular watershed of Guatemala, we moved to create a model that could help coffee farmers to forecast precipitation and the associated coffee yield months in advance. We then validated each of the management activities that could be put in place at the farm level with local technical and extension agricultural services in the region, including managing shade, adapting fertilization schemes, and managing weed removal at the farm level. [ABSTRACT FROM AUTHOR]

Compound droughts and heat waves have garnered increasing attentions due to their disastrous impacts on the structure and function of ecosystems and societies. A drought is generally characterized by a precipitation deficit, and its negative impact can be amplified by the simultaneous occurrence of a heat wave. More recent studies have highlighted the multicharacteristics of compound droughts and heat waves, which may call for improved efforts on assessing the impact of compound extremes. In this study, a compound drought and heat wave magnitude index (CDHMI) is built to characterize the severity of compound extremes in the Huai River basin (HRB) during 1961–2017. The CDHMI considers the impact of both drought/extreme heat conditions and the duration of drought/extreme heat. In addition, the magnitude index has been graded according to the degree of severity to detect the most drastic extreme compound events. The results show that from 1961 to 2017, mild and moderate events occurred more often than severe events. A significant increase in all compound events was observed from 2003 to 2017. Compound drought and heat wave events, especially in drought status, have increased significantly with the global climate warming in recent decades. The assessment of the impact for compound drought and heat wave events over the HRB needs to be improved in the context of global climate changing. Therefore, the CDHMI can be used to accurately assess the risk of compound droughts and heat waves. [ABSTRACT FROM AUTHOR]

Monthly to seasonal precipitation extremes, both flood and drought, are important components of regional climates worldwide, and are the subjects of numerous investigations. However, variability in and transition between precipitation extremes, and associated impacts are the subject of far fewer studies. Recent such events in the Midwest region of the United States, such as the 2011-12 flood to drought transition in the upper Mississippi River basin and the flood to drought transition experienced in parts of Kentucky, Ohio, Indiana, and Illinois in 2019, have sparked concerns of increased variability and rapid transitions between precipitation extremes and compounded economic and environmental impacts. In response to these concerns, this study focuses on characterizing variability and change in Midwest precipitation extremes and transitions between extremes over the last 70 years. Overall we find that the Midwest as a region has gotten wetter over the last seven decades, and that in general the annual maximum and median wetness, defined using the standardized precipitation index (SPI), have increased at a larger magnitude than the annual minimum. We find large areas of the southern Midwest have experienced a significant increase in the annual SPI range and associated magnitude of transition between annual maximum and minimum SPI. We additionally find wet to dry transitions between extremes have largely increased in speed (i.e., less time between extremes), while long-term changes in transition frequency are more regional within the Midwest. [ABSTRACT FROM AUTHOR]

The Indus River basin is highly vulnerable to water scarcity due to increasing population, unsustainable management practices, and climate change. Yet the regional hydroclimate and precipitation dynamics remain poorly understood. Using running trend and spectral analysis with multiple gauge-based, remote sensing, and reanalysis precipitation datasets, this study analyzes precipitation temporal variability, its subregional variations, and the main seasonal drivers, particularly the South Asian monsoon. The results uncover remarkable alternation of long-term positive and negative interdecadal precipitation trends in the basin over the past half century. These trends have led to substantial changes in water input over the region at the time scales comparable to climate assessment periods (30 years), and therefore this high intrinsic variability must be accounted for in climate change adaptation studies. This study also reconstructs onset and withdrawal dates of the South Asian monsoon that exhibit interdecadal variability, but their dominant modes differ from that of annual precipitation. The findings hypothesize that higher-frequency variability in El Niño–Southern Oscillation is likely to have a pronounced impact on monsoon onset and duration in the studied region. [ABSTRACT FROM AUTHOR]

The mid-Pacific trough (MPT), occurring in the upper troposphere during boreal summer, acts as an atmospheric bridge connecting the climate variations over Asia, the Pacific, and North America. The first (second) mode of empirical orthogonal function analysis of the MPT, which accounts for 20.3% (13.4%) of the total variance, reflects a change in its intensity on the southwestern (northeastern) portion of the trough. Both modes are significantly correlated with the variability of tropical Pacific sea surface temperature (SST). Moreover, the first mode is affected by Atlantic SST via planetary waves that originate from the North Atlantic and propagate eastward across the Eurasian continent, and the second mode is influenced by the Arctic sea ice near the Bering Strait by triggering an equatorward wave train over the northeast Pacific. A stronger MPT shown in the first mode is significantly linked to drier and warmer conditions in the Yangtze River basin, southern Japan, and the northern United States and wetter conditions in South Asia and northern China, while a stronger MPT shown in the second mode is associated with a drier and warmer southwestern United States. In addition, an intensified MPT (no matter whether in the southwestern or the northeastern portion) corresponds to more tropical cyclones (TCs) over the western North Pacific (WNP) and fewer TCs over the eastern Pacific (EP) in summer, which is associated with the MPT-induced ascending and descending motions over the WNP and the EP, respectively. [ABSTRACT FROM AUTHOR]

Projected climate change effects on hydrology are investigated for the 2041-60 horizon under the A2 emission scenarios using a multimodel approach over two snowmelt-dominated catchments in Canada. An ensemble of 105 members was obtained by combining seven snow models (SMs), five potential evapotranspiration (PET) methods, and three hydrological model (HM) structures. The study was performed using highresolution simulations from the Canadian Regional Climate Model (CRCM-15 km) driven by two members of the third-generation Canadian Coupled Global Climate Model (CGCM3). This study aims to compare various combinations of SM-PET-HM in terms of their ability to simulate streamflows under the current climate and to evaluate how they affect the assessment of the climate change-induced hydrological impacts at the catchment scale. The variability of streamflow response caused by the use of different SMs (degree-day versus degree-day/energy balance), PET methods (temperature-based versus radiation-based methods), and HM structures is evaluated, as well as the uncertainty due to the natural climate variability (CRCM intermember variability). The hydroclimatic simulations cover 1961-90 in the present period and 2041-60 in the future period. The ensemble spread of the climate change signal on streamflow is large and varies with catchments. Using the variance decomposition on three hydrologic indicators, theHMstructure was found to make the most substantial contribution to uncertainty, followed by the choice of the PET methods or natural climate variability, depending on the hydrologic indicator and the catchment. Snow models played a minor, almost negligible role in the assessment of the climate change impacts on streamflow for the study catchments. [ABSTRACT FROM AUTHOR]

For 14 alternative climate futures, water yield and snow water equivalent (SWE) throughout the contiguous United States (CONUS) were projected over the twenty-first century using the Variable Infiltration Capacity model (VIC). The futures correspond to climate projections from seven CMIP5 models each forced by two representative concentration pathways for greenhouse gases (RCP4.5 and RCP8.5). With both RCPs, decreases in water yields are projected for roughly two-thirds of the CONUS, and in 60% of that area-mainly at more northern latitudes, where the greatest temperature increases are expected-this occurs despite projected increases in precipitation. The greatest relative decreases in yield are projected for the southern Great Plains and the Southwest, where temperature and precipitation changes combine to decrease yield. Snow accumulation is projected to decrease almost everywhere by the latter half of the century, with the time of peak SWE in some basins projected to occur up to 2 months earlier than it now does. These changes, should they come to pass, will challenge the adaptation capacity of future water management. [ABSTRACT FROM AUTHOR]

Long-term (1901-2012) changes in hydroclimatic variables in the 18 Indian subcontinental basins were examined with hydrology simulated using the Variable Infiltration Capacity model (VIC). Changepoint analysis using the sequential Mann-Kendall test showed two distinct periods (1901-47 and 1948-2012) for the domain-averaged monsoon season (June-September) precipitation. Hydrologic changes for the entire water budget were estimated for both periods. In the pre-1948 period, a majority of the river basins experienced increased monsoon season precipitation, evapotranspiration (ET), and surface water availability (as defined by total runoff). Alternatively, in the post-1948 period, monsoon season precipitation declined in 11 of the 18 basins, with statistically significant trends in one (the Ganges basin), and most (15) basins experienced significant warming trends. Additionally, in the post-1948 period, the mean monsoon season ET and surface water availability declined in eight (with significant declines in four) basins. The results indicate that changes in ET and surface water availability in the pre- and post-1948 periods were largely driven by the changes in the monsoon season precipitation rather than air temperature, despite prominent warming after 1975. Coupled modes of variability of sea surface temperature (SST) and surface water availability indicated El Niño-Southern Oscillation (ENSO) as the leading mode. The second mode was identified as the trend mode for surface water availability in the subcontinental river basins, which was largely driven by SST anomalies in the Indian and Atlantic Ocean regions. This indicates that surface water availability in India's subcontinental basins may be affected in the future in response to changes in large-scale climate variability. [ABSTRACT FROM AUTHOR]

A linear mixed-effects (LME) model is developed to discriminate the sources of variation in the changes of several precipitation characteristics over the Rhine basin as projected by an ensemble of 191 global climate model (GCM) simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The uncertainty in climate change projections originates from natural internal variability, imperfect climate models, and the unpredictability of future greenhouse gas forcing. The LME model allows for the quantification of the contribution of these sources of uncertainty as well as the interaction between greenhouse gas forcing and climate model. In addition, dependence between climate models can be accounted for by using a two-level LME model in which the GCMs are grouped according to their atmospheric circulation model. Statistical models of varied complexity are assessed by the Akaike information criterion. More than 60% of the variance of the changes in mean summer precipitation and various quantiles of 5-day summer precipitation at the end of the twenty-first century can be explained by the climate model. Differences between climate models are also the main source of uncertainty for the changes in three drought characteristics in the summer half-year. In winter, the differences between GCMs are smaller, and natural variability explains a large proportion of the variance of the changes. Natural variability is also the main source of uncertainty for the changes in two indices of extreme precipitation. The contribution of the forcing scenario to the variance of the changes is generally less than 25%. [ABSTRACT FROM AUTHOR]

Previous research has shown that the temperature and precipitation variability in the Upper Colorado River basin (UCRB) is correlated with large-scale climate variability [i.e., El Niño-Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO)]. But this correlation is not very strong, suggesting the need to look beyond the statistics. Looking at monthly contributions across the basin, results show that February is least sensitive to variability, and a wet October could be a good predictor for a wet season. A case study of a wet and a dry year (with similar ENSO/PDO conditions) shows that the occurrence of a few large accumulating events is what drives the seasonal variability, and these large events can happen under a variety of synoptic conditions. Looking at several physical factors that can impact the amount of accumulation in any given event, it is found that large accumulating events (>10 mm in one day) are associated with westerly winds at all levels, higher wind speeds at all levels, and greater amounts of total precipitable water. The most important difference between a large accumulating and small accumulating event is the presence of a strong (>4 m s−1) low-level westerly wind. Because much more emphasis should be given to this more local feature, as opposed to large-scale variability, an accurate seasonal forecast for the basin is not producible at this time. [ABSTRACT FROM AUTHOR]

Water managers across the United States face the need to make informed policy decisions regarding long-term impacts of climate change on water resources. To provide a scientifically informed basis for this, the evolution of important components of the basin-scale water balance through the end of the twenty-first century is estimated. Bias-corrected and spatially downscaled climate projections, from phase 3 of the Coupled Model Intercomparison Project (CMIP3) of the World Climate Research Programme, were used to drive a spatially distributed Variable Infiltration Capacity (VIC) model of hydrologic processes in the Salt-Verde basin in the southwestern United States. From the suite of CMIP3 models, the authors select a five-model subset, including three that best reproduce the historical climatology for the study region, plus two others to represent wetter and drier than model average conditions, so as to represent the range of GCM prediction uncertainty. For each GCM, data for three emission scenarios (A1B, A2, and B1) were used to drive the hydrologic model into the future. The projections of this model ensemble indicate a statistically significant 25% decrease in streamflow by the end of the twenty-first century. The primary cause for this change is due to projected decreases in winter precipitation accompanied by significant (temperature driven) reductions in storage of snow and increased winter evaporation. The results show that water management in central Arizona is highly likely to be impacted by changes in regional climate. [ABSTRACT FROM AUTHOR]

This study evaluates the simulation of the Indian Ocean Basin (IOB) mode and relevant physical processes in models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Historical runs from 20 CMIP5 models are available for the analysis. They reproduce the IOB mode and its close relationship to El Niño-Southern Oscillation (ENSO). Half of the models capture key IOB processes: a downwelling oceanic Rossby wave in the southern tropical Indian Ocean (TIO) precedes the IOB development in boreal fall and triggers an antisymmetric wind anomaly pattern across the equator in the following spring. The anomalous wind pattern induces a second warming in the north Indian Ocean (NIO) through summer and sustains anticyclonic wind anomalies in the northwest Pacific by radiating a warm tropospheric Kelvin wave. The second warming in the NIO is indicative of ocean-atmosphere interaction in the interior TIO. More than half of the models display a double peak in NIO warming, as observed following El Niño, while the rest show only one winter peak. The intermodel diversity in the characteristics of the IOB mode seems related to the thermocline adjustment in the south TIO to ENSO-induced wind variations. Almost all the models show multidecadal variations in IOB variance, possibly modulated by ENSO. [ABSTRACT FROM AUTHOR]

Variability of the climate in the headwater drainage basins of the Yangtze River and Yellow River during 1961-2010 was investigated by examining four typical climatic variables: daily minimum, mean, and maximum temperatures and daily precipitation. The results indicate that the temporal trends vary among the climatic variables and the time periods examined. The increase in daily minimum temperature began later than the daily mean and maximum temperatures, but the increase rate of the former was relatively greater after 1985. The abrupt increases in precipitation that occurred near 1978 were much clearer than the three temperature variables. Four dominant periodicities (3, 7, 11, and 18-20 yr) of temperature and precipitation were identified, and these variation patterns directly determined the periodic discharge variations in the two rivers. Under climate change impacts, periodic variations in temperature and precipitation at long temporal scales were intensified after the 1980s. Comparatively, climate change more severely impacts the minimum temperature and precipitation than the maximum and mean temperatures in the study area, and the variability of daily precipitation is more complex than the three temperature variables. Overall, the headwater drainage basin of the Yellow River is more susceptible to climate change compared with the other basin. After 2008, the increase rate of temperature (especially the daily mean and minimum temperatures) became greater, and precipitation showed a downward trend in the study areas. These trends are unfavorable for the safety of water resources and for eco-environmental safety in the two basins. [ABSTRACT FROM AUTHOR]