Articles | Volume 17, issue 7
05 Jul 2013
Research article | 05 Jul 2013
Expected changes in future temperature extremes and their elevation dependency over the Yellow River source region
Y. Hu et al.
No articles found.
Dirk-Jan D. Kok, Saket Pande, Jules B. van Lier, Angela R. C. Ortigara, Hubert Savenije, and Stefan Uhlenbrook
Hydrol. Earth Syst. Sci., 22, 5781–5799,Short summary
Phosphorus (P) is important to global food security. Thus it is concerning that natural P reserves are predicted to deplete within the century. Here we explore the potential of P recovery from wastewater (WW) at global scale. We identify high production and demand sites to determine optimal market prices and trade flows. We show that 20 % of the agricultural demand can be met, yet only 4 % can be met economically. Nonetheless, this recovery stimulates circular economic development in WW treatment.
Dirk-Jan Daniel Kok, Saket Pande, Angela Renata Cordeiro Ortigara, Hubert Savenije, and Stefan Uhlenbrook
Proc. IAHS, 376, 83–86,Short summary
Phosphorus is necessary for the development of crops and is therefore essential in safeguarding our food security. Several studies predict that our rock phosphate reserves, used to create synthetic, phosphatic fertilizers, may become depleted within this century. This study roughly approximates for which areas in Africa we can instead recover phosphorus from wastewater in order to reduce our dependancy on unsustainable rock phosphate.
Khalid Hassaballah, Yasir Mohamed, Stefan Uhlenbrook, and Khalid Biro
Hydrol. Earth Syst. Sci., 21, 5217–5242,Short summary
The Dinder and Rahad experienced significant hydrological changes in recent years. Some claim that this is due to land use & land cover change (LULCC). Specific studies on LULCC in the Dinder and Rahad basins are still missing. This paper aims to understand the LULCC in the Dinder and Rahad and its implications on streamflow using satellite data and hydrological modelling. We expect that this study will be of high importance for decision making related to water resource planning and management.
Khalid Hassaballah, Yasir Mohamed, and Stefan Uhlenbrook
Hydrol. Earth Syst. Sci. Discuss.,
Manuscript not accepted for further reviewShort summary
In this research, we investigated the hydro-climatology of the Dinder and Rahad Rivers (tributaries of the Blue Nile, Sudan/Ethiopia), and its implications on wetlands ecosystems of the Dinder National Park (DNP) in Sudan. Rahad annual flow shows significant increasing trend. Dinder River shows decreasing trends in August maxima. The alterations in the Dinder river flow are likely affect the ecosystems of the DNP negatively, especially for species that depend on the seasonal flow patterns.
V. V. Camacho Suarez, A. M. L. Saraiva Okello, J. W. Wenninger, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 19, 4183–4199,Short summary
Isotope and hydrochemical tracers are tested providing new insights to isotope hydrograph in semi-arid areas in southern Africa. This study provides a spatial hydrochemical characterization of surface and groundwater sources, end member mixing analysis, and two- and three-component hydrograph separations. Results showed that the Kaap catchment is mainly dominated by groundwater sources, and direct runoff is positively correlated with the Antecedent Precipitation Index during the wet season.
E. Teferi, S. Uhlenbrook, and W. Bewket
Earth Syst. Dynam., 6, 617–636,Short summary
This study concludes that integrated analysis of course and fine-scale, inter-annual and intra-annual trends enables a more robust identification of changes in vegetation condition. Seasonal trend analysis was found to be very useful in identifying changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis were performed. The finer-scale intra-annual trend analysis revealed trends that were more linked to human activities.
P. Trambauer, M. Werner, H. C. Winsemius, S. Maskey, E. Dutra, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 19, 1695–1711,
F. E. F. Mussá, Y. Zhou, S. Maskey, I. Masih, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 19, 1093–1106,
A. M. L. Saraiva Okello, I. Masih, S. Uhlenbrook, G. P. W. Jewitt, P. van der Zaag, and E. Riddell
Hydrol. Earth Syst. Sci., 19, 657–673,Short summary
We studied long-term daily records of rainfall and streamflow of the Incomati River basin in southern Africa. We used statistical analysis and the Indicators of Hydrologic Alteration tool to describe the spatial and temporal variability flow regime. We found significant declining trends in October flows, and low flow indicators; however, no significant trend was found in rainfall. Land use and flow regulation are larger drivers of temporal changes in streamflow than climatic forces in the basin.
O. Munyaneza, A. Mukubwa, S. Maskey, S. Uhlenbrook, and J. Wenninger
Hydrol. Earth Syst. Sci., 18, 5289–5301,
I. Masih, S. Maskey, F. E. F. Mussá, and P. Trambauer
Hydrol. Earth Syst. Sci., 18, 3635–3649,
M. Maharjan, M. S. Babel, and S. Maskey
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript not accepted
H. Calderon and S. Uhlenbrook
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript has not been submitted
P. Trambauer, S. Maskey, M. Werner, F. Pappenberger, L. P. H. van Beek, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 2925–2942,
S. Tekleab, J. Wenninger, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 2415–2431,
P. M. Nyenje, L. M. G. Meijer, J. W. Foppen, R. Kulabako, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 1009–1025,
P. Trambauer, E. Dutra, S. Maskey, M. Werner, F. Pappenberger, L. P. H. van Beek, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 193–212,
M. B. Mabrouk, A. Jonoski, D. Solomatine, and S. Uhlenbrook
Hydrol. Earth Syst. Sci. Discuss.,
Revised manuscript not accepted
Y. Zhou, J. Wenninger, Z. Yang, L. Yin, J. Huang, L. Hou, X. Wang, D. Zhang, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 17, 2435–2447,
T. Euser, H. C. Winsemius, M. Hrachowitz, F. Fenicia, S. Uhlenbrook, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 17, 1893–1912,
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Stochastic approachesStochastic daily rainfall generation on tropical islands with complex topographyModeling seasonal variations of extreme rainfall on different timescales in GermanyCompound flood potential from storm surge and heavy precipitation in coastal China: dependence, drivers, and impactsInfluence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basinConditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic processComparison of statistical downscaling methods for climate change impact analysis on precipitation-driven droughtTechnical Note: Temporal disaggregation of spatial rainfall fields with generative adversarial networksA standardized index for assessing sub-monthly compound dry and hot conditions with application in ChinaAssessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analoguesA new discrete multiplicative random cascade model for downscaling intermittent rainfall fieldsModelling rainfall with a Bartlett–Lewis process: new developmentsNonstationary stochastic rain type generation: accounting for climate driversConditional simulation of surface rainfall fields using modified phase annealingClimate influences on flood probabilities across EuropeFlood-related extreme precipitation in southwestern Germany: development of a two-dimensional stochastic precipitation modelA hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescalesMapping rainfall hazard based on rain gauge data: an objective cross-validation framework for model selectionOn the skill of raw and post-processed ensemble seasonal meteorological forecasts in DenmarkEstimating radar precipitation in cold climates: the role of air temperature within a non-parametric frameworkDealing with non-stationarity in sub-daily stochastic rainfall modelsRainfall disaggregation for hydrological modeling: is there a need for spatial consistence?Design water demand of irrigation for a large region using a high-dimensional Gaussian copulaModeling the changes in water balance components of the highly irrigated western part of BangladeshA classification algorithm for selective dynamical downscaling of precipitation extremesSeasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistencyEvaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchmentA nonparametric statistical technique for combining global precipitation datasets: development and hydrological evaluation over the Iberian PeninsulaCensored rainfall modelling for estimation of fine-scale extremesAn adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in FrancePrecipitation extremes on multiple timescales – Bartlett–Lewis rectangular pulse model and intensity–duration–frequency curvesDoes nonstationarity in rainfall require nonstationary intensity–duration–frequency curves?A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transformRegionalizing nonparametric models of precipitation amounts on different temporal scalesA combined statistical bias correction and stochastic downscaling method for precipitationCan local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basinPrecipitation ensembles conforming to natural variations derived from a regional climate model using a new bias correction schemeTechnical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studiesNonstationarity of low flows and their timing in the eastern United StatesClimatological characteristics of raindrop size distributions in Busan, Republic of KoreaCorrection of real-time satellite precipitation with satellite soil moisture observationsStochastic approach to analyzing the uncertainties and possible changes in the availability of water in the future based on scenarios of climate changeAttribution of European precipitation and temperature trends to changes in synoptic circulationSpatial and temporal variability of rainfall in the Nile BasinInter-comparison of statistical downscaling methods for projection of extreme precipitation in EuropeImperfect scaling in distributions of radar-derived rainfall fieldsSatellite-driven downscaling of global reanalysis precipitation products for hydrological applicationsThe effect of flow and orography on the spatial distribution of the very short-term predictability of rainfall from composite radar imagesEffect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of MelbourneSimulation of rainfall time series from different climatic regions using the direct sampling techniqueThe role of retrospective weather forecasts in developing daily forecasts of nutrient loadings over the southeast US
Lionel Benoit, Lydie Sichoix, Alison D. Nugent, Matthew P. Lucas, and Thomas W. Giambelluca
Hydrol. Earth Syst. Sci., 26, 2113–2129,Short summary
This study presents a probabilistic model able to reproduce the spatial patterns of rainfall on tropical islands with complex topography. It sheds new light on rainfall variability at the island scale, and explores the links between rainfall patterns and atmospheric circulation. The proposed model has been tested on two islands of the tropical Pacific, and demonstrates good skills in simulating both site-specific and island-scale rain behavior.
Jana Ulrich, Felix S. Fauer, and Henning W. Rust
Hydrol. Earth Syst. Sci., 25, 6133–6149,Short summary
The characteristics of extreme precipitation on different timescales as well as in different seasons are relevant information, e.g., for designing hydrological structures or managing water supplies. Therefore, our aim is to describe these characteristics simultaneously within one model. We find similar characteristics for short extreme precipitation at all considered stations in Germany but pronounced regional differences with respect to the seasonality of long-lasting extreme events.
Jiayi Fang, Thomas Wahl, Jian Fang, Xun Sun, Feng Kong, and Min Liu
Hydrol. Earth Syst. Sci., 25, 4403–4416,Short summary
A comprehensive assessment of compound flooding potential is missing for China. We investigate dependence, drivers, and impacts of storm surge and precipitation for coastal China. Strong dependence exists between driver combinations, with variations of seasons and thresholds. Sea level rise escalates compound flood potential. Meteorology patterns are pronounced for low and high compound flood potential. Joint impacts from surge and precipitation were much higher than from each individually.
Jamie Towner, Andrea Ficchí, Hannah L. Cloke, Juan Bazo, Erin Coughlan de Perez, and Elisabeth M. Stephens
Hydrol. Earth Syst. Sci., 25, 3875–3895,Short summary
We examine whether several climate indices alter the magnitude, timing and duration of floods in the Amazon. We find significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative SST years in the central Pacific Ocean. This response is not repeated when the negative anomaly is positioned further east. These results have important implications for both social and physical sectors working towards the improvement of flood early warning systems.
Jieru Yan, Fei Li, András Bárdossy, and Tao Tao
Hydrol. Earth Syst. Sci., 25, 3819–3835,Short summary
Accurate spatial precipitation estimates are important in various fields. An approach to simulate spatial rainfall fields conditioned on radar and rain gauge data is proposed. Unlike the commonly used Kriging methods, which provide a Kriged mean field, the output of the proposed approach is an ensemble of estimates that represents the estimation uncertainty. The approach is robust to nonlinear error in radar estimates and is shown to have some advantages, especially when estimating the extremes.
Hossein Tabari, Santiago Mendoza Paz, Daan Buekenhout, and Patrick Willems
Hydrol. Earth Syst. Sci., 25, 3493–3517,
Sebastian Scher and Stefanie Peßenteiner
Hydrol. Earth Syst. Sci., 25, 3207–3225,Short summary
In hydrology, it is often necessary to infer from a daily sum of precipitation a possible distribution over the day – for example how much it rained in each hour. In principle, for a given daily sum, there are endless possibilities. However, some are more likely than others. We show that a method from artificial intelligence called generative adversarial networks (GANs) can
learnwhat a typical distribution over the day looks like.
Jun Li, Zhaoli Wang, Xushu Wu, Jakob Zscheischler, Shenglian Guo, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 1587–1601,Short summary
We introduce a daily-scale index, termed the standardized compound drought and heat index (SCDHI), to measure the key features of compound dry-hot conditions. SCDHI can not only monitor the long-term compound dry-hot events, but can also capture such events at sub-monthly scale and reflect the related vegetation activity impacts. The index can provide a new tool to quantify sub-monthly characteristics of compound dry-hot events, which are vital for releasing early and timely warning.
Damien Raynaud, Benoit Hingray, Guillaume Evin, Anne-Catherine Favre, and Jérémy Chardon
Hydrol. Earth Syst. Sci., 24, 4339–4352,Short summary
This research paper proposes a weather generator combining two sampling approaches. A first generator recombines large-scale atmospheric situations. A second generator is applied to these atmospheric trajectories in order to simulate long time series of daily regional precipitation and temperature. The method is applied to daily time series in Switzerland. It reproduces adequately the observed climatology and improves the reproduction of extreme precipitation values.
Hydrol. Earth Syst. Sci., 24, 3699–3723,Short summary
A new way to downscale rainfall fields based on the notion of equal-volume areas (EVAs) is proposed. Experiments conducted on 100 rainfall events in the Netherlands show that the EVA method outperforms classical methods based on fixed grid cell sizes, producing fields with more realistic spatial structures. The main novelty of the method lies in its adaptive sampling strategy, which avoids many of the mathematical challenges associated with the presence of zero rainfall values.
Christian Onof and Li-Pen Wang
Hydrol. Earth Syst. Sci., 24, 2791–2815,Short summary
The randomised Bartlett–Lewis (RBL) model is widely used to synthesise rainfall time series with realistic statistical features. However, it tended to underestimate rainfall extremes at sub-hourly and hourly timescales. In this paper, we revisit the derivation of equations that represent rainfall properties and compare statistical estimation methods that impact model calibration. These changes effectively improved the RBL model's capacity to reproduce sub-hourly and hourly rainfall extremes.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 24, 2841–2854,Short summary
At subdaily resolution, rain intensity exhibits a strong variability in space and time due to the diversity of processes that produce rain (e.g., frontal storms, mesoscale convective systems and local convection). In this paper we explore a new method to simulate rain type time series conditional to meteorological covariates. Afterwards, we apply stochastic rain type simulation to the downscaling of precipitation of a regional climate model.
Jieru Yan, András Bárdossy, Sebastian Hörning, and Tao Tao
Hydrol. Earth Syst. Sci., 24, 2287–2301,Short summary
For applications such as flood forecasting of urban- or town-scale distributed hydrological modeling, high-resolution quantitative precipitation estimation (QPE) with enough accuracy is the most important driving factor and thus the focus of this paper. Considering the fact that rain gauges are sparse but accurate and radar-based precipitation estimates are inaccurate but densely distributed, we are merging the two types of data intellectually to obtain accurate QPEs with high resolution.
Eva Steirou, Lars Gerlitz, Heiko Apel, Xun Sun, and Bruno Merz
Hydrol. Earth Syst. Sci., 23, 1305–1322,Short summary
We investigate whether flood probabilities in Europe vary for different large-scale atmospheric circulation conditions. Maximum seasonal river flows from 600 gauges in Europe and five synchronous atmospheric circulation indices are analyzed. We find that a high percentage of stations is influenced by at least one of the climate indices, especially during winter. These results can be useful for preparedness and damage planning by (re-)insurance companies.
Florian Ehmele and Michael Kunz
Hydrol. Earth Syst. Sci., 23, 1083–1102,Short summary
The risk estimation of precipitation events with high recurrence periods is difficult due to the limited timescale with meteorological observations and an inhomogeneous distribution of rain gauges, especially in mountainous terrains. In this study a spatially high resolved analytical model, designed for stochastic simulations of flood-related precipitation, is developed and applied to an investigation area in Germany but is transferable to other areas. High conformity with observations is found.
Jeongha Park, Christian Onof, and Dongkyun Kim
Hydrol. Earth Syst. Sci., 23, 989–1014,Short summary
Rainfall data are often unavailable for the analysis of water-related problems such as floods and droughts. In such cases, researchers use rainfall generators to produce synthetic rainfall data. However, data from most rainfall generators can serve only one specific purpose; i.e. one rainfall generator cannot be applied to analyse both floods and droughts. To overcome this issue, we invented a multipurpose rainfall generator that can be applied to analyse most water-related problems.
Juliette Blanchet, Emmanuel Paquet, Pradeebane Vaittinada Ayar, and David Penot
Hydrol. Earth Syst. Sci., 23, 829–849,Short summary
We propose an objective framework for estimating rainfall cumulative distribution functions in a region when data are only available at rain gauges. Our methodology allows us to assess goodness-of-fit of the full distribution, but with a particular focus on its tail. It is applied to daily rainfall in the Ardèche catchment in the south of France. Results show a preference for a mixture of Gamma distribution over seasons and weather patterns, with parameters interpolated with a thin plate spline.
Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 22, 6591–6609,Short summary
The present study evaluates the skill of a seasonal forecasting system for hydrological relevant variables in Denmark. Linear scaling and quantile mapping were used to correct the forecasts. Uncorrected forecasts tend to be more skillful than climatology, in general, for the first month lead time only. Corrected forecasts show a reduced bias in the mean; are more consistent; and show a level of accuracy that is closer to, although no higher than, that of ensemble climatology, in general.
Kuganesan Sivasubramaniam, Ashish Sharma, and Knut Alfredsen
Hydrol. Earth Syst. Sci., 22, 6533–6546,Short summary
This study investigates the use of gauge precipitation and air temperature observations to ascertain radar precipitation in cold climates. The use of air temperature as an additional variable in a non-parametric model improved the estimation of radar precipitation significantly. Further, it was found that the temperature effects became insignificant when air temperature was above 10 °C. The findings from this study could be important for using radar precipitation for hydrological applications.
Lionel Benoit, Mathieu Vrac, and Gregoire Mariethoz
Hydrol. Earth Syst. Sci., 22, 5919–5933,Short summary
We propose a method for unsupervised classification of the space–time–intensity structure of weather radar images. The resulting classes are interpreted as rain types, i.e. pools of rain fields with homogeneous statistical properties. Rain types can in turn be used to define stationary periods for further stochastic rainfall modelling. The application of rain typing to real data indicates that non-stationarity can be significant within meteorological seasons, and even within a single storm.
Hannes Müller-Thomy, Markus Wallner, and Kristian Förster
Hydrol. Earth Syst. Sci., 22, 5259–5280,Short summary
Rainfall time series are disaggregated from daily to hourly values to be used for rainfall–runoff modeling of mesoscale catchments. Spatial rainfall consistency is implemented afterwards using simulated annealing. With the calibration process applied, observed runoff statistics (e.g., summer and winter peak flows) are represented well. However, rainfall datasets with under- or over-estimation of spatial consistency lead to similar results, so the need for a good representation can be questioned.
Xinjun Tu, Yiliang Du, Vijay P. Singh, Xiaohong Chen, Kairong Lin, and Haiou Wu
Hydrol. Earth Syst. Sci., 22, 5175–5189,Short summary
For given frequencies of precipitation of a large region, design water demands of irrigation of the entire region among three methods, i.e., equalized frequency, typical year and most-likely weight function, slightly differed, but their alterations in sub-regions were complicated. A design procedure using the most-likely weight function in association with a high-dimensional copula, which built a linkage between regional frequency and sub-regional frequency of precipitation, is recommended.
A. T. M. Sakiur Rahman, M. Shakil Ahmed, Hasnat Mohammad Adnan, Mohammad Kamruzzaman, M. Abdul Khalek, Quamrul Hasan Mazumder, and Chowdhury Sarwar Jahan
Hydrol. Earth Syst. Sci., 22, 4213–4228,
Edmund P. Meredith, Henning W. Rust, and Uwe Ulbrich
Hydrol. Earth Syst. Sci., 22, 4183–4200,Short summary
Kilometre-scale climate-model data are of great benefit to both hydrologists and end users studying extreme precipitation, though often unavailable due to the computational expense associated with such high-resolution simulations. We develop a method which identifies days with enhanced risk of extreme rainfall over a catchment, so that high-resolution simulations can be performed only when such a risk exists, reducing computational expense by over 90 % while still well capturing the extremes.
Diana Lucatero, Henrik Madsen, Jens C. Refsgaard, Jacob Kidmose, and Karsten H. Jensen
Hydrol. Earth Syst. Sci., 22, 3601–3617,Short summary
The skill of an experimental streamflow forecast system in the Ahlergaarde catchment, Denmark, is analyzed. Inputs to generate the forecasts are taken from the ECMWF System 4 seasonal forecasting system and an ensemble of observations (ESP). Reduction of biases is achieved by processing the meteorological and/or streamflow forecasts. In general, this is not sufficient to ensure a higher level of accuracy than the ESP, indicating a modest added value of a seasonal meteorological system.
Sanjeev K. Jha, Durga L. Shrestha, Tricia A. Stadnyk, and Paulin Coulibaly
Hydrol. Earth Syst. Sci., 22, 1957–1969,Short summary
The output from numerical weather prediction (NWP) models is known to have errors. River forecast centers in Canada mostly use precipitation forecasts directly obtained from American and Canadian NWP models. In this study, we evaluate the forecast performance of ensembles generated by a Bayesian post-processing approach in cold climates. We demonstrate that the post-processing approach generates bias-free forecasts and provides a better picture of uncertainty in the case of an extreme event.
Md Abul Ehsan Bhuiyan, Efthymios I. Nikolopoulos, Emmanouil N. Anagnostou, Pere Quintana-Seguí, and Anaïs Barella-Ortiz
Hydrol. Earth Syst. Sci., 22, 1371–1389,Short summary
This study investigates the use of a nonparametric model for combining multiple global precipitation datasets and characterizing estimation uncertainty. Inputs to the model included three satellite precipitation products, an atmospheric reanalysis precipitation dataset, satellite-derived near-surface daily soil moisture data, and terrain elevation. We evaluated the technique based on high-resolution reference precipitation data and further used generated ensembles to force a hydrological model.
David Cross, Christian Onof, Hugo Winter, and Pietro Bernardara
Hydrol. Earth Syst. Sci., 22, 727–756,Short summary
Extreme rainfall is one of the most significant natural hazards. However, estimating very large events is highly uncertain. We present a new approach to construct intense rainfall using the structure of rainfall generation in clouds. The method is particularly effective at estimating short-duration extremes, which can be the most damaging. This is expected to have immediate impact for the estimation of very rare downpours, with the potential to improve climate resilience and hazard preparedness.
Jérémy Chardon, Benoit Hingray, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 22, 265–286,Short summary
We present a two-stage statistical downscaling model for the probabilistic prediction of local precipitation, where the downscaling statistical link is estimated from atmospheric circulation analogs of the current prediction day. The model allows for a day-to-day adaptive and tailored downscaling. It can reveal specific predictors for peculiar and non-frequent weather configurations. This approach noticeably improves the skill of the prediction for both precipitation occurrence and quantity.
Christoph Ritschel, Uwe Ulbrich, Peter Névir, and Henning W. Rust
Hydrol. Earth Syst. Sci., 21, 6501–6517,Short summary
A stochastic model for precipitation is used to simulate an observed precipitation series; it is compared to the original series in terms of intensity–duration frequency curves. Basis for the latter curves is a parametric model for the duration dependence of the underlying extreme value model allowing a consistent estimation of one single duration-dependent distribution using all duration series simultaneously. The stochastic model reproduces the curves except for very rare extreme events.
Poulomi Ganguli and Paulin Coulibaly
Hydrol. Earth Syst. Sci., 21, 6461–6483,Short summary
Using statistical models, we test whether nonstationary versus stationary models show any significant differences in terms of design storm intensity at different durations across Southern Ontario. We find that detectable nonstationarity in rainfall extremes does not necessarily lead to significant differences in design storm intensity, especially for shorter return periods. An update of 2–44 % is required in current design standards to mitigate the risk of storm-induced urban flooding.
Daniele Nerini, Nikola Besic, Ioannis Sideris, Urs Germann, and Loris Foresti
Hydrol. Earth Syst. Sci., 21, 2777–2797,Short summary
Stochastic generators are effective tools for the quantification of uncertainty in a number of applications with weather radar data, including quantitative precipitation estimation and very short-term forecasting. However, most of the current stochastic rainfall field generators cannot handle spatial non-stationarity. We propose an approach based on the short-space Fourier transform, which aims to reproduce the local spatial structure of the observed rainfall fields.
Tobias Mosthaf and András Bárdossy
Hydrol. Earth Syst. Sci., 21, 2463–2481,Short summary
Parametric distribution functions are commonly used to model precipitation amounts at gauged and ungauged locations. Nonparametric distributions offer a more flexible way to model precipitation amounts. However, the nonparametric models do not exhibit parameters that can be easily regionalized for application at ungauged locations. To overcome this deficiency, we present a new interpolation scheme for nonparametric models and evaluate the usage of daily gauges for sub-daily resolutions.
Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann
Hydrol. Earth Syst. Sci., 21, 1693–1719,Short summary
For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.
Aline Murawski, Gerd Bürger, Sergiy Vorogushyn, and Bruno Merz
Hydrol. Earth Syst. Sci., 20, 4283–4306,Short summary
To understand past flood changes in the Rhine catchment and the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. Here the link between patterns and local climate is tested, and the skill of GCMs in reproducing these patterns is evaluated.
Kue Bum Kim, Hyun-Han Kwon, and Dawei Han
Hydrol. Earth Syst. Sci., 20, 2019–2034,Short summary
A primary advantage of using model ensembles for climate change impact studies is to represent the uncertainties associated with models through the ensemble spread. Currently, most of the conventional bias correction methods adjust all the ensemble members to one reference observation. As a result, the ensemble spread is degraded during bias correction. However the proposed method is able to correct the bias and conform to the ensemble spread so that the ensemble information can be better used.
E. P. Maurer, D. L. Ficklin, and W. Wang
Hydrol. Earth Syst. Sci., 20, 685–696,Short summary
To translate climate model output from its native coarse scale to a finer scale more representative of that at which societal impacts are experienced, a common method applied is statistical downscaling. A component of many statistical downscaling techniques is quantile mapping (QM). QM can be applied at different spatial scales, and here we study how skill varies with spatial scale. We find the highest skill is generally obtained when applying QM at approximately a 50 km spatial scale.
S. Sadri, J. Kam, and J. Sheffield
Hydrol. Earth Syst. Sci., 20, 633–649,Short summary
Low flows are a critical part of the river flow regime but little is known about how they are changing in response to human influences and climate. We analyzed low flow records across the eastern US and identified sites that were minimally influenced by human activities. We found a general increasing trend in low flows across the northeast and decreasing trend across the southeast that are likely driven by changes in climate. The results have implications for how we manage our water resources.
S.-H. Suh, C.-H. You, and D.-I. Lee
Hydrol. Earth Syst. Sci., 20, 193–207,Short summary
This paper was written to find the climatological characteristics of raindrop size distribution (DSD) with respect to the wind direction in Busan, Korea. The data were collected by POSS disdrometer during 4 years (2001–2004). Busan shows the tendency of land-sea breeze. When sea wind blows during rainfall period, mean size and number concentration of raindrop are smaller and larger than that of land wind blows, respectively. It means that the features of DSD depend on the wind direction.
W. Zhan, M. Pan, N. Wanders, and E. F. Wood
Hydrol. Earth Syst. Sci., 19, 4275–4291,
G. G. Oliveira, O. C. Pedrollo, and N. M. R. Castro
Hydrol. Earth Syst. Sci., 19, 3585–3604,Short summary
The objective of this study was to analyze the changes and uncertainties related to water availability in the future, in the Ijuí River basin (south of Brazil), using a stochastic approach. In general the results showed a trend to increased flows. It can be concluded that there is a tendency to increase the hydrological variability during the period between 2011 and 2040, which indicates the possibility of occurrence of time series with more marked periods of droughts and floods.
A. K. Fleig, L. M. Tallaksen, P. James, H. Hisdal, and K. Stahl
Hydrol. Earth Syst. Sci., 19, 3093–3107,
C. Onyutha and P. Willems
Hydrol. Earth Syst. Sci., 19, 2227–2246,Short summary
Variability of rainfall in the Nile Basin was found linked to the large-scale atmosphere-ocean interactions. This finding is vital for a number of water management and planning aspects. To give just one example, it may help in obtaining improved quantiles for flood or drought/water scarcity risk management. This is especially important under conditions of (1) questionable data quality, and (2) data scarcity. These conditions are typical of the Nile Basin and inevitably need to be addressed.
M. A. Sunyer, Y. Hundecha, D. Lawrence, H. Madsen, P. Willems, M. Martinkova, K. Vormoor, G. Bürger, M. Hanel, J. Kriaučiūnienė, A. Loukas, M. Osuch, and I. Yücel
Hydrol. Earth Syst. Sci., 19, 1827–1847,
M. J. van den Berg, L. Delobbe, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 18, 5331–5344,
H. Seyyedi, E. N. Anagnostou, E. Beighley, and J. McCollum
Hydrol. Earth Syst. Sci., 18, 5077–5091,Short summary
The paper presents a methodology for using global precipitation products from satellite remote sensing to error-correct and downscale global atmospheric reanalysis precipitation data sets. It is shown that streamflow simulations from the satellite-adjusted precipitation reanalysis give similar statistics to the ones derived by high-resolution ground-based radar rainfall data sets. This approach can be applied globally to derive improved flood frequency maps over data-poor areas.
L. Foresti and A. Seed
Hydrol. Earth Syst. Sci., 18, 4671–4686,
A. G. Yilmaz, I. Hossain, and B. J. C. Perera
Hydrol. Earth Syst. Sci., 18, 4065–4076,
F. Oriani, J. Straubhaar, P. Renard, and G. Mariethoz
Hydrol. Earth Syst. Sci., 18, 3015–3031,
J. Oh, T. Sinha, and A. Sankarasubramanian
Hydrol. Earth Syst. Sci., 18, 2885–2898,
Anandhi, A., Srinivas, V. V., Nagesh Kumar, D., and Nanjundiah, R. S.: Role of predictors in downscaling surface temperature to river basin in India for IPCC SRES scenarios using support vector machine, Int. J. Climatol. 29, 583–603, https://doi.org/10.1002/joc.1719, 2009.
Beniston, M. and Rebetez, M.: Regional behavior of minimum temperatures in Switzerland for the period 1979–1993, Theor. Appl. Climatol., 53, 231–243, 1996.
Beniston, M., Diaz, H., and Bradley, R.: Climatic change at high elevation sites: an overview, Climatic Change, 36, 233–251, 1997.
Chen, B., Chao, W., and Liu, X.: Enhanced climatic warming in the Tibetan Plateau due to doubling CO2: a model study, Clim. Dynam., 20, 401–413, 2003.
Chen, D. and Chen, Y.: Association between winter temperature in China and upper air circulation over East Asia revealed by canonical correlation analysis, Global Planet. Change, 37, 315–325, 2003.
Chu, J., Xia, J., Xu, C., and Singh, V.: Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China, Theor. Appl. Climatol., 99, 149–161, https://doi.org/10.1007/s00704-009-0129-6, 2010.
Diaz, H. F. and Bradley, R. S.: Temperature variations during the last century at high elevation sites, Climatic Change, 36, 253–279, 1997.
Diaz, H. F. and Eischeid, J. K.: Disappearing 'alpine tundra' Köppen climatic type in the western United States, Geophys. Res. Lett., 34, L18707, https://doi.org/10.1029/2007GL031253, 2007.
Fan, F., Mann, M. E., Lee, S., and Evans, J. L.: Observed and modeled changes in the South Asian Summer Monsoon over the historical period, J. Climate, 23, 5193–5205, 2010.
Fischer, E. and Schär, C.: Future changes in daily summer temperature variability: driving processes and role for temperature extremes, Clim. Dynam., 33, 917–935, 2009.
Giorgi, F.: Climate change hot-spots, Geophys. Res. Lett., 33, L08707, https://doi.org/10.1029/2006GL025734, 2006.
Giorgi, F., Hurrell, J., Marinucci, M., and Beniston, M.: Elevation dependency of the surface climate change signal: a model study, J. Climate, 10, 288–296, 1997.
Ghosh, S.: SVM-PGSL coupled approach for statistical downscaling to predict rainfall from GCM output, J. Geophys. Res., 115, D22102, https://doi.org/10.1029/2009JD013548, 2010.
Haylock, M. R., Cawley, G. C., Harpham, C., Wilby, R. L., and Goodess, C. M.: Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios, Int. J. Climatol., 26, 1397–1415, https://doi.org/10.1002/joc.1318, 2006.
Hu, Y., Maskey, S., Uhlenbrook, S., and Zhao, H.: Streamflow trends and climate linkages in the source region of the Yellow River, China, Hydrol. Process., 25, 3399–3411, https://doi.org/10.1002/hyp.8069, 2011.
Hu, Y., Maskey, S., and Uhlenbrook, S.: Trends in temperature and precipitation extremes in the Yellow River source region, China, Climatic Change, 110, 403–429, https://doi.org/10.1007/s10584-011-0056-2, 2012.
Hu, Y., Maskey, S., and Uhlenbrook, S.: Downscaling daily precipitation over the Yellow River source region in China: a comparison of three statistical downscaling methods, Theor. Appl. Climatol., 112, 447–460, https://doi.org/10.1007/s00704-012-0745-4, 2013.
Hundecha, Y. and Bárdossy, A.: Statistical downscaling of extremes of daily precipitation and temperature and construction of their future scenarios, Int. J. Climatol., 28, 589–610, https://doi.org/10.1002/joc.1563, 2008.
Immerzeel, W. W., van Beek, L. P. H., and Bierkens, M. F. P.: Climate change will affect the Asian water towers, Science, 328, 1382–1385, 2010.
IPCC – Intergovernmental Panel on Climate Change: Climate change 2007: the Physical Science Basis Summary for Policymakers Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, 996 pp., 2007.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, B., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K. C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP-NCAR 40-year reanalysis project, B. Am. Meteorol. Soc., 77, 437–471, 1996.
Kjellström, E., Bärring, L., Jacob, D., Jones, R., Lenderink, G., and Schär, C.: Modelling daily temperature extremes: recent climate and future changes over Europe, Climatic Change, 81, 249–265, https://doi.org/10.1007/s10584-006-9220-5, 2007.
Lan, Y., Zhao, G., Zhang, Y., Wen, J., Liu, J., and Hu, X.: Response of runoff in the source region of the Yellow River to climate warming, Quatern. Int., 226, 60–65, https://doi.org/10.1016/j.quaint.2010.03.006, 2010.
Liu, X. and Chen, B.: Climatic warming in the Tibetan Plateau during recent decades, Int. J. Climatol., 20, 1729–1742, 2000.
Liu, X., Yin, Z. Y., Shao, X., and Qin, N.: Temporal trends and variability of daily maximum and minimum, extreme temperature events, and growing season length over the eastern and central Tibetan Plateau during 1961–2003, J. Geophys. Res., 111, D19109, https://doi.org/10.1029/2005JD006915, 2006.
Liu, X., Cheng, Z., Yan, L., and Yin, Z.: Elevation dependency of recent and future minimum surface air temperature trends in the Tibetan Plateau and its surroundings, Global Planet. Change, 68, 164–174, 2009.
Lu, A., Kang, S., Li, Z., and Theakstone, W.: Altitude effects of climatic variation on Tibetan Plateau and its vicinities, J. Earth Sci., 21, 189–198, 2010.
Marengo, J. A., Rusticucci, M., Penalba, O., and Renom, M.: An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century: part 2: historical trends, Climatic Change, 98, 509–529, 2010.
Maskey, S., Uhlenbrook, S., and Ojha, S.: An analysis of snow cover changes in the Himalayan region using MODIS snow products and in-situ temperature data, Climatic Change, 108, 391-400, https://doi.org/10.1007/s10584-011-0181-y, 2011.
Qin, J., Yang, K., Liang, S., and Guo, X.: The altitudinal dependence of recent rapid warming over the Tibetan Plateau, Climatic Change, 97, 321–327, 2009.
Ramanathan, V., Crutzen, P. J., Kiehl, J. T., and Rosenfeld, D.: Atmosphere – Aerosols, climate, and the hydrological cycle Science, 294, 2119–2124, https://doi.org/10.1126/science.1064034, 2001.
Rangwala, I., Miller, J., and Xu, M.: Warming in the Tibetan Plateau: possible influences of the changes in surface water vapor, Geophys. Res. Lett., 36, L06703, https://doi.org/10.1029/2009GL037245, 2009.
Rangwala, I. and Miller, J.: Climate change in mountains: a review of elevation-dependent warming and its possible causes, Climatic Change, 114, 527–547, https://doi.org/10.1007/s10584-012-0419-3, 2012.
Rangwala, I., Miller, J., Russell, G., and Xu, M.: Using a global climate model to evaluate the influences of water vapor, snow cover and atmospheric aerosol on warming in the Tibetan Plateau during the twenty-first century, Clim. Dynam., 34, 859–872, 2010.
Schoof, J. T., Shin, D. W., Cocke, S., LaRow, T. E., Lim, Y. K., and O'Brien, J. J.: Dynamically and statistically downscaled seasonal temperature and precipitation hindcast ensembles for the southeastern USA, Int. J. Climatol., 29, 243–257, https://doi.org/10.1002/joc.1717, 2009.
Shrestha, A. B. and Aryal, R.: Climate change in Nepal and its impact on Himalayan glaciers, Reg. Environ. Change, 11 (Suppl 1), S65–S77, https://doi.org/10.1007/s10113-010-0174-9, 2011.
Tebaldi, C., Hayhoe, K., Arblaster, J., and Meel, G.: Going to the extremes: an intercomparison of model-simulated historical and future changes in extreme events, Climatic Change, 79, 185–211, https://doi.org/10.1007/s10584-006-9051-4, 2006.
Viviroli, D., Archer, D. R., Buytaert, W., Fowler, H. J., Greenwood, G. B., Hamlet, A. F., Huang, Y., Koboltschnig, G., Litaor, M. I., López-Moreno, J. I., Lorentz, S., Schädler, B., Schreier, H., Schwaiger, K., Vuille, M., and Woods, R.: Climate change and mountain water resources: overview and recommendations for research, management and policy, Hydrol. Earth Syst. Sci., 15, 471–504, https://doi.org/10.5194/hess-15-471-2011, 2011.
Wang, X., Yang, T., Shao, Q., Acharya, K., Wang, W., and Yu, Z.: Statistical downscaling of extremes of precipitation and temperature and construction of their future scenarios in an elevated and cold zone, Stoch. Environ. Res. Risk A., 26, 405–418, https://doi.org/10.1007/s00477-011-0535-z, 2012.
Wang, X., Zhou, W., Wang, D., and Wang, C.: The impact of the summer Asian Jet Stream biases on surface air temperature in mid-eastern China in IPCC AR4 models, Int. J. Climatol., 33, 265–276, https://doi.org/10.1002/joc.3419, 2013.
Wetterhall, F., Bárdossy, A., Chen, D., Halldin, S., and Xu, C.: Daily precipitation downscaling techniques in three Chinese regions, Water Resour. Res., 42, W11423, https://doi.org/10.1029/2005WR004573, 2006.
Wetterhall, F., Halldin, S., and Xu, C. Y.: Seasonality properties of four statistical downscaling methods in central Sweden, Theor. Appl. Climatol., 87, 123–137, https://doi.org/10.1007/s00704-005-0223-3, 2007.
Wilby, R. L. and Dawson, C. W.: The statistical DownScaling Model: insights from one decade of application, Int. J. Climatol., 33, 1707–1719, https://doi.org/10.1002/joc.3544, 2013.
Wilby, R. L. and Wigley, T. M. L.: Precipitation predictors for downscaling: observed and general circulation model relationships, Int. J. Climatol., 20, 641–661, 2000.
Wilby, R. L., Dawson, C. W., and Barrow, E. W.: SDSM – a decision support tool for the assessment of regional climate change impacts, Environ. Model. Softw., 17, 145–157, 2002.
Wilby, R. L., Tomlinson, O. J., and Dawson, C. W.: Multi-site simulation of precipitation by conditional resampling, Clim. Res., 23, 183–194, 2003.
Xu, Z., Zhao, F., and Li, J.: Response of streamflow to climate change in the headwater catchment of the Yellow River basin, Quatern. Int., 208, 62–75, 2009.
Yang, J.-S., Chung, E.-S., Kim, S.-U., and Kim, T.-W.: Prioritization of water management under climate change and urbanization using multi-criteria decision making methods, Hydrol. Earth Syst. Sci., 16, 801–814, https://doi.org/10.5194/hess-16-801-2012, 2012.
Yang, T., Hao, X., Shao, Q., Xu, C., Zhao, C., Chen, X., and Wang, W.: Multi-model ensemble projections in temperature and precipitation extremes of the Tibetan Plateau in the 21st century, Global Planet. Change, 80–81, 1–13, https://doi.org/10.1016/j.gloplacha.2011.08.006, 2012.
You, Q., Kang, S., Pepin, N., and Yan, Y.: Relationship between trends in temperature extremes and elevation in the eastern and central Tibetan Plateau, 1961–2005, Geophys. Res. Lett., 35, L04704, https://doi.org/10.1029/2007GL032669, 2008.
Zhang, Q., Xu, C., Zhang, Z., Ren, G., and Chen, Y.: Climate change or variability? The case of Yellow river as indicated by extreme maximum and minimum air temperature during 1960–2004, Theor. Appl. Climatol., 93, 35–43, https://doi.org/10.1007/s00704-007-0328-y, 2008.
Zhou, T. J. and Yu, R. C.: Twentieth-century surface air temperature over China and the globe simulated by coupled climate models, J. Climate, 19, 5843–5858, https://doi.org/10.1175/JCLI3952.1, 2006.