Articles | Volume 16, issue 9
https://doi.org/10.5194/hess-16-3383-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-16-3383-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Technical note
| 
21 Sep 2012
Technical note |
| 21 Sep 2012
Technical Note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods
L. Gudmundsson
The Norwegian Meteorological Institute, Oslo, Norway
now at: Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland
J. B. Bremnes
The Norwegian Meteorological Institute, Oslo, Norway
J. E. Haugen
The Norwegian Meteorological Institute, Oslo, Norway
T. Engen-Skaugen
The Norwegian Meteorological Institute, Oslo, Norway
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Mathematical applications
Using statistical models to depict the response of multi-timescale drought to forest cover change across climate zones
Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations
The most extreme rainfall erosivity event ever recorded in China up to 2022: the 7.20 storm in Henan Province
The role of atmospheric rivers in the distribution of heavy precipitation events over North America
Study on a mother wavelet optimization framework based on change-point detection of hydrological time series
Projected changes in droughts and extreme droughts in Great Britain strongly influenced by the choice of drought index
Atmospheric water transport connectivity within and between ocean basins and land
Technical Note: Space–time statistical quality control of extreme precipitation observations
The relative importance of antecedent soil moisture and precipitation in flood generation in the middle and lower Yangtze River basin
Rainfall pattern analysis in 24 East Asian megacities using a complex network
Comparison between canonical vine copulas and a meta-Gaussian model for forecasting agricultural drought over China
Analysis of flash droughts in China using machine learning
Performance-based comparison of regionalization methods to improve the at-site estimates of daily precipitation
The use of personal weather station observations to improve precipitation estimation and interpolation
The 2018 northern European hydrological drought and its drivers in a historical perspective
Assimilating shallow soil moisture observations into land models with a water budget constraint
Emerging climate signals in the Lena River catchment: a non-parametric statistical approach
Near-0 °C surface temperature and precipitation type patterns across Canada
A universal multifractal approach to assessment of spatiotemporal extreme precipitation over the Loess Plateau of China
Significant spatial patterns from the GCM seasonal forecasts of global precipitation
Bayesian performance evaluation of evapotranspiration models based on eddy covariance systems in an arid region
Technical note: An improved Grassberger–Procaccia algorithm for analysis of climate system complexity
The influence of long-term changes in canopy structure on rainfall interception loss: a case study in Speulderbos, the Netherlands
Geostatistical assessment of warm-season precipitation observations in Korea based on the composite precipitation and satellite water vapor data
Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets
Does the GPM mission improve the systematic error component in satellite rainfall estimates over TRMM? An evaluation at a pan-India scale
Assessment of an ensemble seasonal streamflow forecasting system for Australia
Technical note: Combining quantile forecasts and predictive distributions of streamflows
Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes
Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē–Atbara river basin, Ethiopia
Seasonal streamflow forecasting by conditioning climatology with precipitation indices
Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts
Flood triggering in Switzerland: the role of daily to monthly preceding precipitation
Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China
Explaining and forecasting interannual variability in the flow of the Nile River
Drought severity–duration–frequency curves: a foundation for risk assessment and planning tool for ecosystem establishment in post-mining landscapes
Characterising the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves
Spatial analysis of precipitation in a high-mountain region: exploring methods with multi-scale topographic predictors and circulation types
Variability of extreme precipitation over Europe and its relationships with teleconnection patterns
Drought evolution characteristics and precipitation intensity changes during alternating dry–wet changes in the Huang–Huai–Hai River basin
Structural break or long memory: an empirical survey on daily rainfall data sets across Malaysia
Calibration of aerodynamic roughness over the Tibetan Plateau with Ensemble Kalman Filter analysed heat flux
Spectral representation of the annual cycle in the climate change signal
Simultaneous estimation of land surface scheme states and parameters using the ensemble Kalman filter: identical twin experiments
Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression
Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland
El Niño-Southern Oscillation and water resources in the headwaters region of the Yellow River: links and potential for forecasting
A summer climate regime over Europe modulated by the North Atlantic Oscillation
Introducing a rainfall compound distribution model based on weather patterns sub-sampling
Yan Li, Bo Huang, and Henning W. Rust
Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024, https://doi.org/10.5194/hess-28-321-2024, 2024
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The inconsistent changes in temperature and precipitation induced by forest cover change are very likely to affect drought condition. We use a set of statistical models to explore the relationship between forest cover change and drought change in different timescales and climate zones. We find that the influence of forest cover on droughts varies under different precipitation and temperature quantiles. Forest cover also could modulate the impacts of precipitation and temperature on drought.
Magdalena Uber, Michael Haller, Christoph Brendel, Gudrun Hillebrand, and Thomas Hoffmann
Hydrol. Earth Syst. Sci., 28, 87–102, https://doi.org/10.5194/hess-28-87-2024, https://doi.org/10.5194/hess-28-87-2024, 2024
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We calculated past, present and future rainfall erosivity in central Europe from high-resolution precipitation data (3 km and 1 h) generated by the COSMO-CLM convection-permitting climate model. Future rainfall erosivity can be up to 84 % higher than it was in the past. Such increases are much higher than estimated previously from regional climate model output. Convection-permitting simulations have an enormous and, to date, unexploited potential for the calculation of future rainfall erosivity.
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023, https://doi.org/10.5194/hess-27-4563-2023, 2023
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An exceptionally heavy rainfall event occurred on 20 July 2021 in central China (the 7.20 storm). The storm presents a rare opportunity to examine the extreme rainfall erosivity. The storm, with an average recurrence interval of at least 10 000 years, was the largest in terms of its rainfall erosivity on record over the past 70 years in China. The study suggests that extreme erosive events can occur anywhere in eastern China and are not necessarily concentrated in low latitudes.
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023, https://doi.org/10.5194/hess-27-2645-2023, 2023
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Employing event synchronization and complex networks analysis, we reveal a cascade of heavy rainfall events, related to intense atmospheric rivers (ARs): heavy precipitation events (HPEs) in western North America (NA) that occur in the aftermath of land-falling ARs are synchronized with HPEs in central and eastern Canada with a delay of up to 12 d. Understanding the effects of ARs in the rainfall over NA will lead to better anticipating the evolution of the climate dynamics in the region.
Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng
Hydrol. Earth Syst. Sci., 27, 2325–2339, https://doi.org/10.5194/hess-27-2325-2023, https://doi.org/10.5194/hess-27-2325-2023, 2023
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Under the joint action of climate–human activities the use of runoff data whose mathematical properties have changed has become the key to watershed management. To determine whether the data have been changed, the number and the location of changes, we proposed a change-point detection framework. The problem of determining the parameters of wavelet transform has been solved by comparing the accuracy of identifying change points. This study helps traditional models adapt to environmental changes.
Nele Reyniers, Timothy J. Osborn, Nans Addor, and Geoff Darch
Hydrol. Earth Syst. Sci., 27, 1151–1171, https://doi.org/10.5194/hess-27-1151-2023, https://doi.org/10.5194/hess-27-1151-2023, 2023
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In an analysis of future drought projections for Great Britain based on the Standardised Precipitation Index and the Standardised Precipitation Evapotranspiration Index, we show that the choice of drought indicator has a decisive influence on the resulting projected changes in drought characteristics, although both result in increased drying. This highlights the need to understand the interplay between increasing atmospheric evaporative demand and drought impacts under a changing climate.
Dipanjan Dey, Aitor Aldama Campino, and Kristofer Döös
Hydrol. Earth Syst. Sci., 27, 481–493, https://doi.org/10.5194/hess-27-481-2023, https://doi.org/10.5194/hess-27-481-2023, 2023
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One of the most striking and robust features of climate change is the acceleration of the atmospheric water cycle branch. Earlier studies were able to provide a quantification of the global atmospheric water cycle, but they missed addressing the atmospheric water transport connectivity within and between ocean basins and land. These shortcomings were overcome in the present study and presented a complete synthesised and quantitative view of the atmospheric water cycle.
Abbas El Hachem, Jochen Seidel, Florian Imbery, Thomas Junghänel, and András Bárdossy
Hydrol. Earth Syst. Sci., 26, 6137–6146, https://doi.org/10.5194/hess-26-6137-2022, https://doi.org/10.5194/hess-26-6137-2022, 2022
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Through this work, a methodology to identify outliers in intense precipitation data was presented. The results show the presence of several suspicious observations that strongly differ from their surroundings. Many identified outliers did not have unusually high values but disagreed with their neighboring values at the corresponding time steps. Weather radar and discharge data were used to distinguish between single events and false observations.
Qihua Ran, Jin Wang, Xiuxiu Chen, Lin Liu, Jiyu Li, and Sheng Ye
Hydrol. Earth Syst. Sci., 26, 4919–4931, https://doi.org/10.5194/hess-26-4919-2022, https://doi.org/10.5194/hess-26-4919-2022, 2022
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This study aims to further evaluate the relative importance of antecedent soil moisture and rainfall on flood generation and the controlling factors. The relative importance of antecedent soil moisture and daily rainfall present a significant correlation with drainage area; the larger the watershed, and the more essential the antecedent soil saturation rate is in flood generation, the less important daily rainfall will be.
Kyunghun Kim, Jaewon Jung, Hung Soo Kim, Masahiko Haraguchi, and Soojun Kim
Hydrol. Earth Syst. Sci., 26, 4823–4836, https://doi.org/10.5194/hess-26-4823-2022, https://doi.org/10.5194/hess-26-4823-2022, 2022
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This study applied a new methodology (complex network), instead of using classic methods, to establish the relationships between rainfall events in large East Asian cities. The relationships show that western China and Southeast Asia have a lot of influence on each other. Moreover, it is confirmed that the relationships arise from the effect of the East Asian monsoon. In future, complex network may be able to be applied to analyze the concurrent relationships between extreme rainfall events.
Haijiang Wu, Xiaoling Su, Vijay P. Singh, Te Zhang, Jixia Qi, and Shengzhi Huang
Hydrol. Earth Syst. Sci., 26, 3847–3861, https://doi.org/10.5194/hess-26-3847-2022, https://doi.org/10.5194/hess-26-3847-2022, 2022
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Agricultural drought forecasting lies at the core of overall drought risk management and is critical for food security and drought early warning. Using three-dimensional scenarios, we attempted to compare the agricultural drought forecast performance of a canonical vine copula (3C-vine) model and meta-Gaussian (MG) model over China. The findings show that the 3C-vine model exhibits more skill than the MG model when using 1– to 3-month lead times for forecasting agricultural drought.
Linqi Zhang, Yi Liu, Liliang Ren, Adriaan J. Teuling, Ye Zhu, Linyong Wei, Linyan Zhang, Shanhu Jiang, Xiaoli Yang, Xiuqin Fang, and Hang Yin
Hydrol. Earth Syst. Sci., 26, 3241–3261, https://doi.org/10.5194/hess-26-3241-2022, https://doi.org/10.5194/hess-26-3241-2022, 2022
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In this study, three machine learning methods displayed a good detection capacity of flash droughts. The RF model was recommended to estimate the depletion rate of soil moisture and simulate flash drought by considering the multiple meteorological variable anomalies in the adjacent time to drought onset. The anomalies of precipitation and potential evapotranspiration exhibited a stronger synergistic but asymmetrical effect on flash droughts compared to slowly developing droughts.
Abubakar Haruna, Juliette Blanchet, and Anne-Catherine Favre
Hydrol. Earth Syst. Sci., 26, 2797–2811, https://doi.org/10.5194/hess-26-2797-2022, https://doi.org/10.5194/hess-26-2797-2022, 2022
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Reliable prediction of floods depends on the quality of the input data such as precipitation. However, estimation of precipitation from the local measurements is known to be difficult, especially for extremes. Regionalization improves the estimates by increasing the quantity of data available for estimation. Here, we compare three regionalization methods based on their robustness and reliability. We apply the comparison to a dense network of daily stations within and outside Switzerland.
András Bárdossy, Jochen Seidel, and Abbas El Hachem
Hydrol. Earth Syst. Sci., 25, 583–601, https://doi.org/10.5194/hess-25-583-2021, https://doi.org/10.5194/hess-25-583-2021, 2021
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In this study, the applicability of data from private weather stations (PWS) for precipitation interpolation was investigated. Due to unknown errors and biases in these observations, a two-step filter was developed that uses indicator correlations and event-based spatial precipitation patterns. The procedure was tested and cross validated for the state of Baden-Württemberg (Germany). The biggest improvement is achieved for the shortest time aggregations.
Sigrid J. Bakke, Monica Ionita, and Lena M. Tallaksen
Hydrol. Earth Syst. Sci., 24, 5621–5653, https://doi.org/10.5194/hess-24-5621-2020, https://doi.org/10.5194/hess-24-5621-2020, 2020
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This study provides an in-depth analysis of the 2018 northern European drought. Large parts of the region experienced 60-year record-breaking temperatures, linked to high-pressure systems and warm surrounding seas. Meteorological drought developed from May and, depending on local conditions, led to extreme low flows and groundwater drought in the following months. The 2018 event was unique in that it affected most of Fennoscandia as compared to previous droughts.
Bo Dan, Xiaogu Zheng, Guocan Wu, and Tao Li
Hydrol. Earth Syst. Sci., 24, 5187–5201, https://doi.org/10.5194/hess-24-5187-2020, https://doi.org/10.5194/hess-24-5187-2020, 2020
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Data assimilation is a procedure to generate an optimal combination of the state variable in geoscience, based on the model outputs and observations. The ensemble Kalman filter (EnKF) scheme is a widely used assimilation method in soil moisture estimation. This study proposed several modifications of EnKF for improving this assimilation. The study shows that the quality of the assimilation result is improved, while the degree of water budget imbalance is reduced.
Eric Pohl, Christophe Grenier, Mathieu Vrac, and Masa Kageyama
Hydrol. Earth Syst. Sci., 24, 2817–2839, https://doi.org/10.5194/hess-24-2817-2020, https://doi.org/10.5194/hess-24-2817-2020, 2020
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Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.
Eva Mekis, Ronald E. Stewart, Julie M. Theriault, Bohdan Kochtubajda, Barrie R. Bonsal, and Zhuo Liu
Hydrol. Earth Syst. Sci., 24, 1741–1761, https://doi.org/10.5194/hess-24-1741-2020, https://doi.org/10.5194/hess-24-1741-2020, 2020
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This article provides a Canada-wide analysis of near-0°C temperature conditions (±2°C) using hourly surface temperature and precipitation type observations from 92 locations for the 1981–2011 period. Higher annual occurrences were found in Atlantic Canada, although high values also occur in other regions. Trends of most indicators show little or no change despite a systematic warming over Canada. A higher than expected tendency for near-0°C conditions was also found at some stations.
Jianjun Zhang, Guangyao Gao, Bojie Fu, Cong Wang, Hoshin V. Gupta, Xiaoping Zhang, and Rui Li
Hydrol. Earth Syst. Sci., 24, 809–826, https://doi.org/10.5194/hess-24-809-2020, https://doi.org/10.5194/hess-24-809-2020, 2020
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We proposed an approach that integrates universal multifractals and a segmentation algorithm to precisely identify extreme precipitation (EP) and assess spatiotemporal EP variation over the Loess Plateau, using daily data. Our results explain how EP contributes to the widely distributed severe natural hazards. These findings are of great significance for ecological management in the Loess Plateau. Our approach is also helpful for spatiotemporal EP assessment at the regional scale.
Tongtiegang Zhao, Wei Zhang, Yongyong Zhang, Zhiyong Liu, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 24, 1–16, https://doi.org/10.5194/hess-24-1-2020, https://doi.org/10.5194/hess-24-1-2020, 2020
Guoxiao Wei, Xiaoying Zhang, Ming Ye, Ning Yue, and Fei Kan
Hydrol. Earth Syst. Sci., 23, 2877–2895, https://doi.org/10.5194/hess-23-2877-2019, https://doi.org/10.5194/hess-23-2877-2019, 2019
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Accurately evaluating evapotranspiration (ET) is a critical challenge in improving hydrological process modeling. Here we evaluated four ET models (PM, SW, PT–FC, and AA) under the Bayesian framework. Our results reveal that the SW model has the best performance. This is in part because the SW model captures the main physical mechanism in ET; the other part is that the key parameters, such as the extinction factor, could be well constrained with observation data.
Chongli Di, Tiejun Wang, Xiaohua Yang, and Siliang Li
Hydrol. Earth Syst. Sci., 22, 5069–5079, https://doi.org/10.5194/hess-22-5069-2018, https://doi.org/10.5194/hess-22-5069-2018, 2018
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The original Grassberger–Procaccia algorithm for complex analysis was modified by incorporating the normal-based K-means clustering technique and the RANSAC algorithm. The calculation accuracy of the proposed method was shown to outperform traditional algorithms. The proposed algorithm was used to diagnose climate system complexity in the Hai He basin. The spatial patterns of the complexity of precipitation and air temperature reflected the influence of the dominant climate system.
César Cisneros Vaca, Christiaan van der Tol, and Chandra Prasad Ghimire
Hydrol. Earth Syst. Sci., 22, 3701–3719, https://doi.org/10.5194/hess-22-3701-2018, https://doi.org/10.5194/hess-22-3701-2018, 2018
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The influence of long-term changes in canopy structure on rainfall interception loss was studied in a 55-year old forest. Interception loss was similar at the same site (38 %), when the forest was 29 years old. In the past, the forest was denser and had a higher storage capacity, but the evaporation rates were lower. We emphasize the importance of quantifying downward sensible heat flux and heat release from canopy biomass in tall forest in order to improve the quantification of evaporation.
Sojung Park, Seon Ki Park, Jeung Whan Lee, and Yunho Park
Hydrol. Earth Syst. Sci., 22, 3435–3452, https://doi.org/10.5194/hess-22-3435-2018, https://doi.org/10.5194/hess-22-3435-2018, 2018
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Understanding the precipitation characteristics is essential to design an optimal observation network. We studied the spatial and temporal characteristics of summertime precipitation systems in Korea via geostatistical analyses on the ground-based precipitation and satellite water vapor data. We found that, under a strict standard, an observation network with higher resolution is required in local areas with frequent heavy rainfalls, depending on directional features of precipitation systems.
Wenbin Liu, Fubao Sun, Yanzhong Li, Guoqing Zhang, Yan-Fang Sang, Wee Ho Lim, Jiahong Liu, Hong Wang, and Peng Bai
Hydrol. Earth Syst. Sci., 22, 351–371, https://doi.org/10.5194/hess-22-351-2018, https://doi.org/10.5194/hess-22-351-2018, 2018
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The dynamics of basin-scale water budgets over the Tibetan Plateau (TP) are not well understood nowadays due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q) in 18 TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g. in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations).
Harsh Beria, Trushnamayee Nanda, Deepak Singh Bisht, and Chandranath Chatterjee
Hydrol. Earth Syst. Sci., 21, 6117–6134, https://doi.org/10.5194/hess-21-6117-2017, https://doi.org/10.5194/hess-21-6117-2017, 2017
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High-quality satellite precipitation forcings have provided a viable alternative to hydrologic modeling in data-scarce regions. Ageing TRMM sensors have recently been upgraded to GPM, promising enhanced spatio-temporal resolutions. Statistical and hydrologic evaluation of GPM measurements across 86 Indian river basins revealed improved low rainfall estimates with reduced effects of climatology and topography.
James C. Bennett, Quan J. Wang, David E. Robertson, Andrew Schepen, Ming Li, and Kelvin Michael
Hydrol. Earth Syst. Sci., 21, 6007–6030, https://doi.org/10.5194/hess-21-6007-2017, https://doi.org/10.5194/hess-21-6007-2017, 2017
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We assess a new streamflow forecasting system in Australia. The system is designed to meet the need of water agencies for 12-month forecasts. The forecasts perform well in a wide range of rivers. Forecasts for shorter periods (up to 6 months) are generally informative. Forecasts sometimes did not perform well in a few very dry rivers. We test several techniques for improving streamflow forecasts in drylands, with mixed success.
Konrad Bogner, Katharina Liechti, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 21, 5493–5502, https://doi.org/10.5194/hess-21-5493-2017, https://doi.org/10.5194/hess-21-5493-2017, 2017
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The enhanced availability of many different weather prediction systems nowadays makes it very difficult for flood and water resource managers to choose the most reliable and accurate forecast. In order to circumvent this problem of choice, different approaches for combining this information have been applied at the Sihl River (CH) and the results have been verified. The outcome of this study highlights the importance of forecast combination in order to improve the quality of forecast systems.
Matthew B. Switanek, Peter A. Troch, Christopher L. Castro, Armin Leuprecht, Hsin-I Chang, Rajarshi Mukherjee, and Eleonora M. C. Demaria
Hydrol. Earth Syst. Sci., 21, 2649–2666, https://doi.org/10.5194/hess-21-2649-2017, https://doi.org/10.5194/hess-21-2649-2017, 2017
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The commonly used bias correction method called quantile mapping assumes a constant function of error correction values between modeled and observed distributions. Our article finds that this function cannot be assumed to be constant. We propose a new bias correction method, called scaled distribution mapping, that does not rely on this assumption. Furthermore, the proposed method more explicitly accounts for the frequency of rain days and the likelihood of individual events.
Tesfay G. Gebremicael, Yasir A. Mohamed, Pieter v. Zaag, and Eyasu Y. Hagos
Hydrol. Earth Syst. Sci., 21, 2127–2142, https://doi.org/10.5194/hess-21-2127-2017, https://doi.org/10.5194/hess-21-2127-2017, 2017
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This study was conducted to understand the spatio-temporal variations of streamflow in the Tekezē basin. Results showed rainfall over the basin did not significantly change. However, streamflow experienced high variabilities at seasonal and annual scales. Further studies are needed to verify hydrological changes by identifying the physical mechanisms behind those changes. Findings are useful as prerequisite for studying the effects of catchment management dynamics on the hydrological processes.
Louise Crochemore, Maria-Helena Ramos, Florian Pappenberger, and Charles Perrin
Hydrol. Earth Syst. Sci., 21, 1573–1591, https://doi.org/10.5194/hess-21-1573-2017, https://doi.org/10.5194/hess-21-1573-2017, 2017
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The use of general circulation model outputs for streamflow forecasting has developed in the last decade. In parallel, traditional streamflow forecasting is commonly based on historical data. This study investigates the impact of conditioning historical data based on circulation model precipitation forecasts on seasonal streamflow forecast quality. Results highlighted a trade-off between the sharpness and reliability of forecasts.
Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3601–3618, https://doi.org/10.5194/hess-20-3601-2016, https://doi.org/10.5194/hess-20-3601-2016, 2016
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This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.
P. Froidevaux, J. Schwanbeck, R. Weingartner, C. Chevalier, and O. Martius
Hydrol. Earth Syst. Sci., 19, 3903–3924, https://doi.org/10.5194/hess-19-3903-2015, https://doi.org/10.5194/hess-19-3903-2015, 2015
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We investigate precipitation characteristics prior to 4000 annual floods in Switzerland since 1961. The floods were preceded by heavy precipitation, but in most catchments extreme precipitation occurred only during the last 3 days prior to the flood events. Precipitation sums for earlier time periods (like e.g. 4-14 days prior to floods) were mostly average and do not correlate with the return period of the floods.
G. H. Fang, J. Yang, Y. N. Chen, and C. Zammit
Hydrol. Earth Syst. Sci., 19, 2547–2559, https://doi.org/10.5194/hess-19-2547-2015, https://doi.org/10.5194/hess-19-2547-2015, 2015
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This study compares the effects of five precipitation and three temperature correction methods on precipitation, temperature, and streamflow through loosely coupling RCM (RegCM) and a distributed hydrological model (SWAT) in terms of frequency-based indices and time-series-based indices. The methodology and results can be used for other regions and other RCM and hydrologic models, and for impact studies of climate change on water resources at a regional scale.
M. S. Siam and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 19, 1181–1192, https://doi.org/10.5194/hess-19-1181-2015, https://doi.org/10.5194/hess-19-1181-2015, 2015
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This paper explains the different natural modes of interannual variability in the flow of the Nile River and also presents a new index based on the sea surface temperature (SST) over the southern Indian Ocean to forecast the flow of the Nile River. It also presents a new hybrid forecasting algorithm that can be used to predict the Nile flow based on indices of the SST in the eastern Pacific and southern Indian oceans.
D. Halwatura, A. M. Lechner, and S. Arnold
Hydrol. Earth Syst. Sci., 19, 1069–1091, https://doi.org/10.5194/hess-19-1069-2015, https://doi.org/10.5194/hess-19-1069-2015, 2015
G. Panthou, T. Vischel, T. Lebel, G. Quantin, and G. Molinié
Hydrol. Earth Syst. Sci., 18, 5093–5107, https://doi.org/10.5194/hess-18-5093-2014, https://doi.org/10.5194/hess-18-5093-2014, 2014
D. Masson and C. Frei
Hydrol. Earth Syst. Sci., 18, 4543–4563, https://doi.org/10.5194/hess-18-4543-2014, https://doi.org/10.5194/hess-18-4543-2014, 2014
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The question of how to utilize information from the physiography/topography in the spatial interpolation of rainfall is a long-standing discussion in the literature. In this study we test ideas that go beyond the approach in popular interpolation schemes today. The key message of our study is that these ideas can at best marginally improve interpolation accuracy, even in a region where a clear benefit would intuitively be expected.
A. Casanueva, C. Rodríguez-Puebla, M. D. Frías, and N. González-Reviriego
Hydrol. Earth Syst. Sci., 18, 709–725, https://doi.org/10.5194/hess-18-709-2014, https://doi.org/10.5194/hess-18-709-2014, 2014
D. H. Yan, D. Wu, R. Huang, L. N. Wang, and G. Y. Yang
Hydrol. Earth Syst. Sci., 17, 2859–2871, https://doi.org/10.5194/hess-17-2859-2013, https://doi.org/10.5194/hess-17-2859-2013, 2013
F. Yusof, I. L. Kane, and Z. Yusop
Hydrol. Earth Syst. Sci., 17, 1311–1318, https://doi.org/10.5194/hess-17-1311-2013, https://doi.org/10.5194/hess-17-1311-2013, 2013
J. H. Lee, J. Timmermans, Z. Su, and M. Mancini
Hydrol. Earth Syst. Sci., 16, 4291–4302, https://doi.org/10.5194/hess-16-4291-2012, https://doi.org/10.5194/hess-16-4291-2012, 2012
T. Bosshard, S. Kotlarski, T. Ewen, and C. Schär
Hydrol. Earth Syst. Sci., 15, 2777–2788, https://doi.org/10.5194/hess-15-2777-2011, https://doi.org/10.5194/hess-15-2777-2011, 2011
S. Nie, J. Zhu, and Y. Luo
Hydrol. Earth Syst. Sci., 15, 2437–2457, https://doi.org/10.5194/hess-15-2437-2011, https://doi.org/10.5194/hess-15-2437-2011, 2011
G. Ibarra-Berastegi, J. Saénz, A. Ezcurra, A. Elías, J. Diaz Argandoña, and I. Errasti
Hydrol. Earth Syst. Sci., 15, 1895–1907, https://doi.org/10.5194/hess-15-1895-2011, https://doi.org/10.5194/hess-15-1895-2011, 2011
R. Schiemann, R. Erdin, M. Willi, C. Frei, M. Berenguer, and D. Sempere-Torres
Hydrol. Earth Syst. Sci., 15, 1515–1536, https://doi.org/10.5194/hess-15-1515-2011, https://doi.org/10.5194/hess-15-1515-2011, 2011
A. Lü, S. Jia, W. Zhu, H. Yan, S. Duan, and Z. Yao
Hydrol. Earth Syst. Sci., 15, 1273–1281, https://doi.org/10.5194/hess-15-1273-2011, https://doi.org/10.5194/hess-15-1273-2011, 2011
G. Wang, A. J. Dolman, and A. Alessandri
Hydrol. Earth Syst. Sci., 15, 57–64, https://doi.org/10.5194/hess-15-57-2011, https://doi.org/10.5194/hess-15-57-2011, 2011
F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara
Hydrol. Earth Syst. Sci., 14, 951–964, https://doi.org/10.5194/hess-14-951-2010, https://doi.org/10.5194/hess-14-951-2010, 2010
Cited articles
Angus, J. E.: The Probability Integral Transform and Related Results, SIAM Review, 36, 652–654, 1994.
Ashfaq, M., Bowling, L. C., Cherkauer, K., Pal, J. S., and Diffenbaugh, N. S.: Influence of climate model biases and daily-scale temperature and precipitation events on hydrological impacts assessment: A case study of the United States, J. Geophys. Res., 115, D14116, https://doi.org/10.1029/2009JD012965, 2010.
Bo{é}, J., Terray, L., Habets, F., and Martin, E.: Statistical and dynamical downscaling of the Seine basin climate for hydro-meteorological studies, Int. J. Climatol., 27, 1643–1655, https://doi.org/10.1002/joc.1602, 2007.
Cannon, A. J.: Probabilistic Multisite Precipitation Downscaling by an Expanded Bernoulli-Gamma Density Network, J. Hydrometeorol., 9, 1284–1300, https://doi.org/10.1175/2008JHM960.1, 2008.
Cannon, A. J.: Neural networks for probabilistic environmental prediction: Conditional Density Estimation Network Creation and Evaluation (CaDENCE) in R, Comput. Geosci., 41, 126–135, https://doi.org/10.1016/j.cageo.2011.08.023, 2012.
Chen, C., Haerter, J. O., Hagemann, S., and Piani, C.: On the contribution of statistical bias correction to the uncertainty in the projected hydrological cycle, Geophys. Res. Lett., 38, L20403, https://doi.org/10.1029/2011GL049318, 2011{a}.
Chen, J., Brissette, F. P., and Leconte, R.: Uncertainty of downscaling method in quantifying the impact of climate change on hydrology, J. Hydrol., 401, 190–202, https://doi.org/10.1016/j.jhydrol.2011.02.020, 2011{b}.
Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On the need for bias correction of regional climate change projections of temperature and precipitation, Geophys. Res. Lett., 35, L20709, https://doi.org/10.1029/2008GL035694, 2008.
Dosio, A. and Paruolo, P.: Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate, J. Geophys. Res., 116, D16106, https://doi.org/10.1029/2011JD015934, 2011.
Engen-Skaugen, T.: Refinement of dynamically downscaled precipitation and temperature scenarios, Climatic Change, 84, 365–382, https://doi.org/10.1007/s10584-007-9251-6, 2007.
Førland, E. J., Benestad, R. E., Flatø, F., Hanssen-Bauer, I., Haugen, J. E., Isaksen, K., Sorteberg, A., and Ådlandsvik, B.: Climate development in North Norway and the Svalbard region during 1900–2100, Tech. Rep. 128, Norwegian Polar Institute, available at: http://www.npolar.no (last access: 15 May 2012), 2009.
Førland, E. J., Benestad, R., Hanssen-Bauer, I., Haugen, J. E., and Skaugen, T. E.: Temperature and Precipitation Development at Svalbard 1900–2100, Advances in Meteorology, 2011, 893790, https://doi.org/10.1155/2011/893790, 2011.
Haerter, J. O., Hagemann, S., Moseley, C., and Piani, C.: Climate model bias correction and the role of timescales, Hydrol. Earth Syst. Sci., 15, 1065–1079, https://doi.org/10.5194/hess-15-1065-2011, 2011.
Hastie, T., Tibshirani, R., and Friedman, J. H.: The Elements of Statistical Learning, Springer, 2001.
Ines, A. V. and Hansen, J. W.: Bias correction of daily GCM rainfall for crop simulation studies, Agr. Forest Meteorol., 138, 44–53, https://doi.org/10.1016/j.agrformet.2006.03.009, 2006.
Johnson, F. and Sharma, A.: Accounting for interannual variability: A comparison of options for water resources climate change impact assessments, Water Resour. Res., 47, W04508, https://doi.org/10.1029/2010WR009272, 2011.
Johnson, F. and Sharma, A.: A nesting model for bias correction of variability at multiple time scales in general circulation model precipitation simulations, Water Resour. Res., 48, W01504, https://doi.org/10.1029/2011WR010464, 2012.
Li, H., Sheffield, J., and Wood, E. F.: Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching, J. Geophys. Res., 115, D10101, https://doi.org/10.1029/2009JD012882, 2010.
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Theme{ß}l, M., Venema, V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and Thiele-Eich, I.: Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user, Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009RG000314, 2010.
Mooley, D. A.: Gamma Distribution Probability Model for Asian Summer Monsoon Monthly Rainfall, Mon. Weather Rev., 101, 160–176, https://doi.org/10.1175/1520-0493(1973)101<0160:GDPMFA>2.3.CO;2, 1973.
Panofsky, H. W. and Brier, G. W.: Some Applications of Statistics to Meteorology, The Pennsylvania State University Press, Philadelphia, 1968.
Piani, C., Haerter, J., and Coppola, E.: Statistical bias correction for daily precipitation in regional climate models over Europe, Theor. Appl. Climatol., 99, 187–192, https://doi.org/10.1007/s00704-009-0134-9, 2010{a}.
Piani, C., Weedon, G., Best, M., Gomes, S., Viterbo, P., Hagemann, S., and Haerter, J.: Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models, J. Hydrol., 395, 199–215, https://doi.org/10.1016/j.jhydrol.2010.10.024, 2010{b}.
R Development Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, available at: http://www.R-project.org/ (last access: 15 May 2012), 2011.
Rauscher, S., Coppola, E., Piani, C., and Giorgi, F.: Resolution effects on regional climate model simulations of seasonal precipitation over Europe, Clim. Dynam., 35, 685–711, https://doi.org/10.1007/s00382-009-0607-7, 2010.
Reichle, R. H. and Koster, R. D.: Bias reduction in short records of satellite soil moisture, Geophys. Res. Lett., 31, L19501, https://doi.org/10.1029/2004GL020938, 2004.
Reichler, T. and Kim, J.: How Well Do Coupled Models Simulate Today's Climate?, B. Am. Meteorol. Soc., 89, 303–311, https://doi.org/10.1175/BAMS-89-3-303, 2008.
Rojas, R., Feyen, L., Dosio, A., and Bavera, D.: Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations, Hydrol. Earth Syst. Sci., 15, 2599–2620, https://doi.org/10.5194/hess-15-2599-2011, 2011.
Schmidli, J., Frei, C., and Vidale, P. L.: Downscaling from GCM precipitation: a benchmark for dynamical and statistical downscaling methods, Int. J. Climatol., 26, 679–689, https://doi.org/10.1002/joc.1287, 2006.
Schmidli, J., Goodess, C. M., Frei, C., Haylock, M. R., Hundecha, Y., Ribalaygua, J., and Schmith, T.: Statistical and dynamical downscaling of precipitation: An evaluation and comparison of scenarios for the European Alps, J. Geophys. Res., 112, D04105, https://doi.org/10.1029/2005JD007026, 2007.
Sunyer, M., Madsen, H., and Ang, P.: A comparison of different regional climate models and statistical downscaling methods for extreme rainfall estimation under climate change, Atmos. Res., 103, 119–128, https://doi.org/10.1016/j.atmosres.2011.06.011, 2012.
Teutschbein, C. and Seibert, J.: Regional Climate Models for Hydrological Impact Studies at the Catchment Scale: A Review of Recent Modeling Strategies, Geography Compass, 4, 834–860, https://doi.org/10.1111/j.1749-8198.2010.00357.x, 2010.
Teutschbein, C. and Seibert, J.: Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods, J. Hydrol., 16, 12–29, https://doi.org/10.1016/j.jhydrol.2012.05.052, 2012.
Theme{ß}l, M. J., Gobiet, A., and Leuprecht, A.: Empirical-statistical downscaling and error correction of daily precipitation from regional climate models, Int. J. Climatol., 31, 1530–1544, https://doi.org/10.1002/joc.2168, 2011.
Theme{ß}l, M. J., Gobiet, A., and Heinrich, G.: Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal, Climatic Change, 112, 449–468, https://doi.org/10.1007/s10584-011-0224-4, 2012.
Thom, H. C. S.: Approximate convolution of the gamma and mixed gamma distributions, Mon. Weather Rev., 96, 883–886, https://doi.org/10.1175/1520-0493(1968)096<0883:ACOTGA>2.0.CO;2, 1968.
Turco, M., Quintana-Segu\'i, P., Llasat, M. C., Herrera, S., and Gutiérrez, J. M.: Testing MOS precipitation downscaling for ENSEMBLES regional climate models over Spain, J. Geophys. Res., 116, D18109, https://doi.org/10.1029/2011JD016166, 2011.
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Bechtold, V. D. C., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Berg, L. V. D., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 reanalysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2005.
Widmann, M., Bretherton, C. S., and Salath{é}, E. P.: Statistical Precipitation Downscaling over the Northwestern United States Using Numerically Simulated Precipitation as a Predictor, J. Climate, 16, 799–816, https://doi.org/10.1175/1520-0442(2003)016<0799:SPDOTN>2.0.CO;2, 2003.
Winkler, J. A., Guentchev, G. S., Liszewska, M., Perdinan, and Tan, P.-N.: Climate Scenario Development and Applications for Local/Regional Climate Change Impact Assessments: An Overview for the Non-Climate Scientist – Part II: Considerations When Using Climate Change Scenarios, Geography Compass, 5, 301–328, https://doi.org/10.1111/j.1749-8198.2011.00426.x, 2011{a}.
Winkler, J. A., Guentchev, G. S., Perdinan, Tan, P.-N., Zhong, S., Liszewska, M., Abraham, Z., Nied{ź}wied{ź}, T., and Ustrnul, Z.: Climate Scenario Development and Applications for Local/Regional Climate Change Impact Assessments: An Overview for the Non-Climate Scientist – Part I: Scenario Development Using Downscaling Methods, Geography Compass, 5, 275–300, https://doi.org/10.1111/j.1749-8198.2011.00425.x, 2011{b}.
Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D. P.: Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs, Climatic Change, 62, 189–216, https://doi.org/10.1023/B:CLIM.0000013685.99609.9e, 2004.
