Articles | Volume 17, issue 10
https://doi.org/10.5194/hess-17-4189-2013
© Author(s) 2013. 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-17-4189-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Oct 2013
Research article |
| 28 Oct 2013
Optimising predictor domains for spatially coherent precipitation downscaling
S. Radanovics
Irstea, UR HHLY, 5 rue de La Doua, 69100 Villeurbanne, France
J.-P. Vidal
Irstea, UR HHLY, 5 rue de La Doua, 69100 Villeurbanne, France
E. Sauquet
Irstea, UR HHLY, 5 rue de La Doua, 69100 Villeurbanne, France
A. Ben Daoud
Compagnie Nationale du Rhône (CNR), 2 rue André Bonin, 69316 Lyon Cedex 04, France
G. Bontron
Compagnie Nationale du Rhône (CNR), 2 rue André Bonin, 69316 Lyon Cedex 04, France
Related authors
No articles found.
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-46, https://doi.org/10.5194/hess-2023-46, 2023
Preprint under review for HESS
Short summary
Short summary
Mediterranean floods are causing major damages, and recent studies have shown, despite the increase in intense rainfall, that there was no increase in river floods. This study reveals that during 1959–2021 the seasonality of floods has changed in the Mediterranean basins. There is also an increased frequency of floods linked to short episodes of intense rain, and a decrease in episodes linked to soil saturation. These changes need to be taken into consideration to adapt flood warning systems.
Hanieh Seyedhashemi, Florentina Moatar, Jean-Philippe Vidal, and Dominique Thiéry
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-451, https://doi.org/10.5194/essd-2022-451, 2023
Preprint under review for ESSD
Short summary
Short summary
This paper presents pas and future dataset of daily time series of discharge and stream temperature for 52 278 reaches over the Loire River basin (100,000 km2 ) in France, using a thermal and hydrological models. Past data are provided over the 1963–2019. Future data are available over the 1976–2100 period under different future climate change models (warm and cold, intermediate, and hot and dry) and scenarios (optimistic, intermediate and pesimistic).
Samuel Morin, Hugues François, Marion Réveillet, Eric Sauquet, Louise Crochemore, Flora Branger, Etiene Leblois, and Marie Dumont
EGUsphere, https://doi.org/10.5194/egusphere-2022-1186, https://doi.org/10.5194/egusphere-2022-1186, 2022
Short summary
Short summary
Ski resorts are a key socio-economic asset of several mountain areass. Grooming and snowmaking are routinely used to manage the snow cover on ski pistes, but despite vivid debate, little is known about their impact on water resources downstreams. This study quantifies, for the pilot ski resort La Plagne in the French Alps, the impact of grooming and snowmaking on downstream river flow. Hydrological impacts are mostly apparent at the seasonal scale but rather neutral on the annual scale.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
Short summary
Short summary
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Aurélien Beaufort, Jacob S. Diamond, Eric Sauquet, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 3477–3495, https://doi.org/10.5194/hess-26-3477-2022, https://doi.org/10.5194/hess-26-3477-2022, 2022
Short summary
Short summary
We developed one of the largest stream temperature databases to calculate a simple, ecologically relevant metric – the thermal peak – that captures the magnitude of summer thermal extremes. Using statistical models, we extrapolated the thermal peak to nearly every stream in France, finding the hottest thermal peaks along large rivers without forested riparian zones and groundwater inputs. Air temperature was a poor proxy for the thermal peak, highlighting the need to grow monitoring networks.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
Short summary
Short summary
Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Hanieh Seyedhashemi, Jean-Philippe Vidal, Jacob S. Diamond, Dominique Thiéry, Céline Monteil, Frédéric Hendrickx, Anthony Maire, and Florentina Moatar
Hydrol. Earth Syst. Sci., 26, 2583–2603, https://doi.org/10.5194/hess-26-2583-2022, https://doi.org/10.5194/hess-26-2583-2022, 2022
Short summary
Short summary
Stream temperature appears to be increasing globally, but its rate remains poorly constrained due to a paucity of long-term data. Using a thermal model, this study provides a large-scale understanding of the evolution of stream temperature over a long period (1963–2019). This research highlights that air temperature and streamflow can exert joint influence on stream temperature trends, and riparian shading in small mountainous streams may mitigate warming in stream temperatures.
Manuel Fossa, Bastien Dieppois, Nicolas Massei, Matthieu Fournier, Benoit Laignel, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 25, 5683–5702, https://doi.org/10.5194/hess-25-5683-2021, https://doi.org/10.5194/hess-25-5683-2021, 2021
Short summary
Short summary
Hydro-climate observations (such as precipitation, temperature, and river discharge time series) reveal very complex behavior inherited from complex interactions among the physical processes that drive hydro-climate viability. This study shows how even small perturbations of a physical process can have large consequences on some others. Those interactions vary spatially, thus showing the importance of both temporal and spatial dimensions in better understanding hydro-climate variability.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, and Olivier Vannier
Clim. Past, 17, 1857–1879, https://doi.org/10.5194/cp-17-1857-2021, https://doi.org/10.5194/cp-17-1857-2021, 2021
Short summary
Short summary
This article presents FYRE Climate, a dataset providing daily precipitation and temperature spanning the 1871–2012 period at 8 km resolution over France. FYRE Climate has been obtained through the combination of daily and yearly observations and a gridded reconstruction already available through a statistical technique called data assimilation. Results highlight the quality of FYRE Climate in terms of both long-term variations and reproduction of extreme events.
Nicolas Massei, Daniel G. Kingston, David M. Hannah, Jean-Philippe Vidal, Bastien Dieppois, Manuel Fossa, Andreas Hartmann, David A. Lavers, and Benoit Laignel
Proc. IAHS, 383, 141–149, https://doi.org/10.5194/piahs-383-141-2020, https://doi.org/10.5194/piahs-383-141-2020, 2020
Short summary
Short summary
This paper presents recent thoughts by members of EURO-FRIEND Water project 3 “Large-scale-variations in hydrological characteristics” about research needed to characterize and understand large-scale hydrology under global changes. Emphasis is put on the necessary efforts to better understand 1 – the impact of low-frequency climate variability on hydrological trends and extremes, 2 – the role of basin properties on modulating the climate signal producing hydrological responses on the basin scale.
Kerstin Stahl, Jean-Philippe Vidal, Jamie Hannaford, Erik Tijdeman, Gregor Laaha, Tobias Gauster, and Lena M. Tallaksen
Proc. IAHS, 383, 291–295, https://doi.org/10.5194/piahs-383-291-2020, https://doi.org/10.5194/piahs-383-291-2020, 2020
Short summary
Short summary
Numerous indices exist for the description of hydrological drought, some are based on absolute thresholds of overall streamflows or water levels and some are based on relative anomalies with respect to the season. This article discusses paradigms and experiences with such index uses in drought monitoring and drought analysis to raise awareness of the different interpretations of drought severity.
Jordi Bolibar, Antoine Rabatel, Isabelle Gouttevin, Clovis Galiez, Thomas Condom, and Eric Sauquet
The Cryosphere, 14, 565–584, https://doi.org/10.5194/tc-14-565-2020, https://doi.org/10.5194/tc-14-565-2020, 2020
Short summary
Short summary
We introduce a novel approach for simulating glacier mass balances using a deep artificial neural network (i.e. deep learning) from climate and topographical data. This has been added as a component of a new open-source parameterized glacier evolution model. Deep learning is found to outperform linear machine learning methods, mainly due to its nonlinearity. Potential applications range from regional mass balance reconstructions from observations to simulations for past and future climates.
Yves Tramblay, Louise Mimeau, Luc Neppel, Freddy Vinet, and Eric Sauquet
Hydrol. Earth Syst. Sci., 23, 4419–4431, https://doi.org/10.5194/hess-23-4419-2019, https://doi.org/10.5194/hess-23-4419-2019, 2019
Short summary
Short summary
In the present study the flood trends have been assessed for a large sample of 171 basins located in southern France, which has a Mediterranean climate. Results show that, despite the increase in rainfall intensity previously observed in this area, there is no general increase in flood magnitude. Instead, a reduction in the annual number of floods is found, linked to a decrease in soil moisture caused by the increase in temperature observed in recent decades.
Eric Sauquet, Bastien Richard, Alexandre Devers, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 23, 3683–3710, https://doi.org/10.5194/hess-23-3683-2019, https://doi.org/10.5194/hess-23-3683-2019, 2019
Short summary
Short summary
This study aims to identify catchments and the associated water uses vulnerable to climate change. Vulnerability is considered here to be the likelihood of water restrictions which are unacceptable for agricultural uses. This study provides the first regional analysis of the stated water restrictions, highlighting heterogeneous decision-making processes; data from a national system of compensation to farmers for uninsurable damages were used to characterize past failure events.
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, Benjamin Graff, and Jean-Michel Soubeyroux
Earth Syst. Sci. Data, 11, 241–260, https://doi.org/10.5194/essd-11-241-2019, https://doi.org/10.5194/essd-11-241-2019, 2019
Short summary
Short summary
SCOPE Climate is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France. It is the first century-long gridded high-resolution homogeneous dataset available over France. It thus paves the way for studying local historical meteorological events and for assessing the local climate variability from the end of the 19th century.
Aurélien Beaufort, Nicolas Lamouroux, Hervé Pella, Thibault Datry, and Eric Sauquet
Hydrol. Earth Syst. Sci., 22, 3033–3051, https://doi.org/10.5194/hess-22-3033-2018, https://doi.org/10.5194/hess-22-3033-2018, 2018
Short summary
Short summary
Streams which may stop flowing are poorly gauged. To improve their characterisation, we use an extended network providing monthly visual observations stating whether streams are flowing or not across France. These observations are combined with discharge and groundwater level in models to predict daily regional probability of drying. This approach allows identification of the most impacted regions by flow intermittence and estimation of the probability of drying dynamics over the last 27 years.
Gregor Laaha, Tobias Gauster, Lena M. Tallaksen, Jean-Philippe Vidal, Kerstin Stahl, Christel Prudhomme, Benedikt Heudorfer, Radek Vlnas, Monica Ionita, Henny A. J. Van Lanen, Mary-Jeanne Adler, Laurie Caillouet, Claire Delus, Miriam Fendekova, Sebastien Gailliez, Jamie Hannaford, Daniel Kingston, Anne F. Van Loon, Luis Mediero, Marzena Osuch, Renata Romanowicz, Eric Sauquet, James H. Stagge, and Wai K. Wong
Hydrol. Earth Syst. Sci., 21, 3001–3024, https://doi.org/10.5194/hess-21-3001-2017, https://doi.org/10.5194/hess-21-3001-2017, 2017
Short summary
Short summary
In 2015 large parts of Europe were affected by a drought. In terms of low flow magnitude, a region around the Czech Republic was most affected, with return periods > 100 yr. In terms of deficit volumes, the drought was particularly severe around S. Germany where the event lasted notably long. Meteorological and hydrological events developed differently in space and time. For an assessment of drought impacts on water resources, hydrological data are required in addition to meteorological indices.
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, Alexandre Devers, and Benjamin Graff
Hydrol. Earth Syst. Sci., 21, 2923–2951, https://doi.org/10.5194/hess-21-2923-2017, https://doi.org/10.5194/hess-21-2923-2017, 2017
Short summary
Short summary
The historical depth of streamflow observations in France is extended through daily hydrometeorogical reconstructions from 1871 onwards over a large set of near-natural catchments. Innovative approaches are proposed to identify and intercompare extreme low-flow events from these reconstructions, both in time and across France in a homogeneous way over more than 140 years. Analyses bring forward recent well-known events like 1976 and 1989–1990 but also much older ones like 1878 and 1893.
Jean-Philippe Vidal, Benoît Hingray, Claire Magand, Eric Sauquet, and Agnès Ducharne
Hydrol. Earth Syst. Sci., 20, 3651–3672, https://doi.org/10.5194/hess-20-3651-2016, https://doi.org/10.5194/hess-20-3651-2016, 2016
Short summary
Short summary
Possible transient futures of winter and summer low flows for two snow-influenced catchments in the southern French Alps show a strong decrease signal. It is however largely masked by the year-to-year variability, which should be the main target for defining adaptation strategies. Responses of different hydrological models strongly diverge in the future, suggesting to carefully check the robustness of evapotranspiration and snowpack components under a changing climate.
Laurie Caillouet, Jean-Philippe Vidal, Eric Sauquet, and Benjamin Graff
Clim. Past, 12, 635–662, https://doi.org/10.5194/cp-12-635-2016, https://doi.org/10.5194/cp-12-635-2016, 2016
Short summary
Short summary
This paper describes a daily high-resolution reconstruction of precipitation and temperature fields in France from 1871 onwards. A statistical method linking atmospheric circulation to local precipitation is refined for taking advantage of recently published global long-term atmospheric and oceanic reconstructions. The resulting data set allows filling in the spatial and temporal data gaps in historical surface observations, and improving our knowledge on the local-scale climate variability.
J. Hall, B. Arheimer, G. T. Aronica, A. Bilibashi, M. Boháč, O. Bonacci, M. Borga, P. Burlando, A. Castellarin, G. B. Chirico, P. Claps, K. Fiala, L. Gaál, L. Gorbachova, A. Gül, J. Hannaford, A. Kiss, T. Kjeldsen, S. Kohnová, J. J. Koskela, N. Macdonald, M. Mavrova-Guirguinova, O. Ledvinka, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, M. Osuch, J. Parajka, R. A. P. Perdigão, I. Radevski, B. Renard, M. Rogger, J. L. Salinas, E. Sauquet, M. Šraj, J. Szolgay, A. Viglione, E. Volpi, D. Wilson, K. Zaimi, and G. Blöschl
Proc. IAHS, 370, 89–95, https://doi.org/10.5194/piahs-370-89-2015, https://doi.org/10.5194/piahs-370-89-2015, 2015
I. Giuntoli, J.-P. Vidal, C. Prudhomme, and D. M. Hannah
Earth Syst. Dynam., 6, 267–285, https://doi.org/10.5194/esd-6-267-2015, https://doi.org/10.5194/esd-6-267-2015, 2015
Short summary
Short summary
We assessed future changes in high and low flows globally using runoff projections from global hydrological models (GHMs) driven by global climate models (GCMs) under the RCP8.5 scenario. Further, we quantified the relative size of uncertainty from GHMs and from GCMs using ANOVA. We show that GCMs are the major contributors to uncertainty overall, but GHMs increase their contribution for low flows and can equal or outweigh GCM uncertainty in snow-dominated areas for both high and low flows.
J. Hall, B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z. W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione, and G. Blöschl
Hydrol. Earth Syst. Sci., 18, 2735–2772, https://doi.org/10.5194/hess-18-2735-2014, https://doi.org/10.5194/hess-18-2735-2014, 2014
K. Kochanek, B. Renard, P. Arnaud, Y. Aubert, M. Lang, T. Cipriani, and E. Sauquet
Nat. Hazards Earth Syst. Sci., 14, 295–308, https://doi.org/10.5194/nhess-14-295-2014, https://doi.org/10.5194/nhess-14-295-2014, 2014
T. H. Snelder, T. Datry, N. Lamouroux, S. T. Larned, E. Sauquet, H. Pella, and C. Catalogne
Hydrol. Earth Syst. Sci., 17, 2685–2699, https://doi.org/10.5194/hess-17-2685-2013, https://doi.org/10.5194/hess-17-2685-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Stochastic approaches
Technical note: A stochastic framework for identification and evaluation of flash drought
Stochastic simulation of reference rainfall scenarios for hydrological applications using a universal multi-fractal approach
Atmospheric conditions favouring extreme precipitation and flash floods in temperate regions of Europe
A storm-centered multivariate modeling of extreme precipitation frequency based on atmospheric water balance
Probabilistic subseasonal precipitation forecasts using preceding atmospheric intraseasonal signals in a Bayesian perspective
Stochastic daily rainfall generation on tropical islands with complex topography
A gridded multi-site precipitation generator for complex terrain: An evaluation in the Austrian Alps
Modeling seasonal variations of extreme rainfall on different timescales in Germany
Compound flood potential from storm surge and heavy precipitation in coastal China: dependence, drivers, and impacts
Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin
Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process
Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought
Technical Note: Temporal disaggregation of spatial rainfall fields with generative adversarial networks
A standardized index for assessing sub-monthly compound dry and hot conditions with application in China
Assessment of meteorological extremes using a synoptic weather generator and a downscaling model based on analogues
A new discrete multiplicative random cascade model for downscaling intermittent rainfall fields
Modelling rainfall with a Bartlett–Lewis process: new developments
Nonstationary stochastic rain type generation: accounting for climate drivers
Conditional simulation of surface rainfall fields using modified phase annealing
Climate influences on flood probabilities across Europe
Flood-related extreme precipitation in southwestern Germany: development of a two-dimensional stochastic precipitation model
A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales
Mapping rainfall hazard based on rain gauge data: an objective cross-validation framework for model selection
On the skill of raw and post-processed ensemble seasonal meteorological forecasts in Denmark
Estimating radar precipitation in cold climates: the role of air temperature within a non-parametric framework
Dealing with non-stationarity in sub-daily stochastic rainfall models
Rainfall 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 copula
Modeling the changes in water balance components of the highly irrigated western part of Bangladesh
A classification algorithm for selective dynamical downscaling of precipitation extremes
Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency
Evaluation of ensemble precipitation forecasts generated through post-processing in a Canadian catchment
A nonparametric statistical technique for combining global precipitation datasets: development and hydrological evaluation over the Iberian Peninsula
Censored rainfall modelling for estimation of fine-scale extremes
An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France
Precipitation extremes on multiple timescales – Bartlett–Lewis rectangular pulse model and intensity–duration–frequency curves
Does 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 transform
Regionalizing nonparametric models of precipitation amounts on different temporal scales
A combined statistical bias correction and stochastic downscaling method for precipitation
Can local climate variability be explained by weather patterns? A multi-station evaluation for the Rhine basin
Precipitation ensembles conforming to natural variations derived from a regional climate model using a new bias correction scheme
Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies
Nonstationarity of low flows and their timing in the eastern United States
Climatological characteristics of raindrop size distributions in Busan, Republic of Korea
Correction of real-time satellite precipitation with satellite soil moisture observations
Stochastic approach to analyzing the uncertainties and possible changes in the availability of water in the future based on scenarios of climate change
Attribution of European precipitation and temperature trends to changes in synoptic circulation
Spatial and temporal variability of rainfall in the Nile Basin
Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe
Yuxin Li, Sisi Chen, Jun Yin, and Xing Yuan
Hydrol. Earth Syst. Sci., 27, 1077–1087, https://doi.org/10.5194/hess-27-1077-2023, https://doi.org/10.5194/hess-27-1077-2023, 2023
Short summary
Short summary
Flash drought is referred to the rapid development of drought events with a fast decline of soil moisture, which has serious impacts on agriculture, the ecosystem, human health, and society. While flash droughts have received much research attention, there is no consensus on its definition. Here we used a stochastic water balance framework to quantify the timing of soil moisture crossing different thresholds, providing an efficient tool for diagnosing and monitoring flash droughts.
Arun Ramanathan, Pierre-Antoine Versini, Daniel Schertzer, Remi Perrin, Lionel Sindt, and Ioulia Tchiguirinskaia
Hydrol. Earth Syst. Sci., 26, 6477–6491, https://doi.org/10.5194/hess-26-6477-2022, https://doi.org/10.5194/hess-26-6477-2022, 2022
Short summary
Short summary
Reference rainfall scenarios are indispensable for hydrological applications such as designing storm-water management infrastructure, including green roofs. Therefore, a new method is suggested for simulating rainfall scenarios of specified intensity, duration, and frequency, with realistic intermittency. Furthermore, novel comparison metrics are proposed to quantify the effectiveness of the presented simulation procedure.
Judith Meyer, Malte Neuper, Luca Mathias, Erwin Zehe, and Laurent Pfister
Hydrol. Earth Syst. Sci., 26, 6163–6183, https://doi.org/10.5194/hess-26-6163-2022, https://doi.org/10.5194/hess-26-6163-2022, 2022
Short summary
Short summary
We identified and analysed the major atmospheric components of rain-intense thunderstorms that can eventually lead to flash floods: high atmospheric moisture, sufficient latent instability, and weak thunderstorm cell motion. Between 1981 and 2020, atmospheric conditions became likelier to support strong thunderstorms. However, the occurrence of extreme rainfall events as well as their rainfall intensity remained mostly unchanged.
Yuan Liu and Daniel B. Wright
Hydrol. Earth Syst. Sci., 26, 5241–5267, https://doi.org/10.5194/hess-26-5241-2022, https://doi.org/10.5194/hess-26-5241-2022, 2022
Short summary
Short summary
We present a new approach to estimate extreme rainfall probability and severity using the atmospheric water balance, where precipitation is the sum of water vapor components moving in and out of a storm. We apply our method to the Mississippi Basin and its five major subbasins. Our approach achieves a good fit to reference precipitation, indicating that the rainfall probability estimation can benefit from additional information from physical processes that control rainfall.
Yuan Li, Zhiyong Wu, Hai He, and Hao Yin
Hydrol. Earth Syst. Sci., 26, 4975–4994, https://doi.org/10.5194/hess-26-4975-2022, https://doi.org/10.5194/hess-26-4975-2022, 2022
Short summary
Short summary
The relationship between atmospheric intraseasonal signals and precipitation is highly uncertain and depends on the region and lead time. In this study, we develop a spatiotemporal projection, based on a Bayesian hierarchical model (STP-BHM), to address the above challenge. The results suggest that the STP-BHM model is skillful and reliable for probabilistic subseasonal precipitation forecasts over China during the boreal summer monsoon season.
Lionel Benoit, Lydie Sichoix, Alison D. Nugent, Matthew P. Lucas, and Thomas W. Giambelluca
Hydrol. Earth Syst. Sci., 26, 2113–2129, https://doi.org/10.5194/hess-26-2113-2022, https://doi.org/10.5194/hess-26-2113-2022, 2022
Short summary
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.
Hetal Dabhi, Mathias Rotach, and Michael Oberguggenberger
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-21, https://doi.org/10.5194/hess-2022-21, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
High-resolution precipitation data consistent both in space and time for current and future climate are required for climate change impact assessments, but it is very challenging for complex topography. We present a model that generates synthetic gridded data of daily precipitation at 1 km spatial resolution using observed meteorological station data as input and provides data where historical observations are not available. We evaluate this model for a mountainous region in the European Alps.
Jana Ulrich, Felix S. Fauer, and Henning W. Rust
Hydrol. Earth Syst. Sci., 25, 6133–6149, https://doi.org/10.5194/hess-25-6133-2021, https://doi.org/10.5194/hess-25-6133-2021, 2021
Short summary
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, https://doi.org/10.5194/hess-25-4403-2021, https://doi.org/10.5194/hess-25-4403-2021, 2021
Short summary
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, https://doi.org/10.5194/hess-25-3875-2021, https://doi.org/10.5194/hess-25-3875-2021, 2021
Short summary
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, https://doi.org/10.5194/hess-25-3819-2021, https://doi.org/10.5194/hess-25-3819-2021, 2021
Short summary
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, https://doi.org/10.5194/hess-25-3493-2021, https://doi.org/10.5194/hess-25-3493-2021, 2021
Sebastian Scher and Stefanie Peßenteiner
Hydrol. Earth Syst. Sci., 25, 3207–3225, https://doi.org/10.5194/hess-25-3207-2021, https://doi.org/10.5194/hess-25-3207-2021, 2021
Short summary
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, https://doi.org/10.5194/hess-25-1587-2021, https://doi.org/10.5194/hess-25-1587-2021, 2021
Short summary
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, https://doi.org/10.5194/hess-24-4339-2020, https://doi.org/10.5194/hess-24-4339-2020, 2020
Short summary
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.
Marc Schleiss
Hydrol. Earth Syst. Sci., 24, 3699–3723, https://doi.org/10.5194/hess-24-3699-2020, https://doi.org/10.5194/hess-24-3699-2020, 2020
Short summary
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, https://doi.org/10.5194/hess-24-2791-2020, https://doi.org/10.5194/hess-24-2791-2020, 2020
Short summary
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, https://doi.org/10.5194/hess-24-2841-2020, https://doi.org/10.5194/hess-24-2841-2020, 2020
Short summary
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, https://doi.org/10.5194/hess-24-2287-2020, https://doi.org/10.5194/hess-24-2287-2020, 2020
Short summary
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, https://doi.org/10.5194/hess-23-1305-2019, https://doi.org/10.5194/hess-23-1305-2019, 2019
Short summary
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, https://doi.org/10.5194/hess-23-1083-2019, https://doi.org/10.5194/hess-23-1083-2019, 2019
Short summary
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, https://doi.org/10.5194/hess-23-989-2019, https://doi.org/10.5194/hess-23-989-2019, 2019
Short summary
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, https://doi.org/10.5194/hess-23-829-2019, https://doi.org/10.5194/hess-23-829-2019, 2019
Short summary
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, https://doi.org/10.5194/hess-22-6591-2018, https://doi.org/10.5194/hess-22-6591-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-6533-2018, https://doi.org/10.5194/hess-22-6533-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-5919-2018, https://doi.org/10.5194/hess-22-5919-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-5259-2018, https://doi.org/10.5194/hess-22-5259-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-5175-2018, https://doi.org/10.5194/hess-22-5175-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-4213-2018, https://doi.org/10.5194/hess-22-4213-2018, 2018
Edmund P. Meredith, Henning W. Rust, and Uwe Ulbrich
Hydrol. Earth Syst. Sci., 22, 4183–4200, https://doi.org/10.5194/hess-22-4183-2018, https://doi.org/10.5194/hess-22-4183-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-3601-2018, https://doi.org/10.5194/hess-22-3601-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-1957-2018, https://doi.org/10.5194/hess-22-1957-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-1371-2018, https://doi.org/10.5194/hess-22-1371-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-727-2018, https://doi.org/10.5194/hess-22-727-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-22-265-2018, https://doi.org/10.5194/hess-22-265-2018, 2018
Short summary
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, https://doi.org/10.5194/hess-21-6501-2017, https://doi.org/10.5194/hess-21-6501-2017, 2017
Short summary
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, https://doi.org/10.5194/hess-21-6461-2017, https://doi.org/10.5194/hess-21-6461-2017, 2017
Short summary
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, https://doi.org/10.5194/hess-21-2777-2017, https://doi.org/10.5194/hess-21-2777-2017, 2017
Short summary
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, https://doi.org/10.5194/hess-21-2463-2017, https://doi.org/10.5194/hess-21-2463-2017, 2017
Short summary
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, https://doi.org/10.5194/hess-21-1693-2017, https://doi.org/10.5194/hess-21-1693-2017, 2017
Short summary
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, https://doi.org/10.5194/hess-20-4283-2016, https://doi.org/10.5194/hess-20-4283-2016, 2016
Short summary
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, https://doi.org/10.5194/hess-20-2019-2016, https://doi.org/10.5194/hess-20-2019-2016, 2016
Short summary
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, https://doi.org/10.5194/hess-20-685-2016, https://doi.org/10.5194/hess-20-685-2016, 2016
Short summary
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, https://doi.org/10.5194/hess-20-633-2016, https://doi.org/10.5194/hess-20-633-2016, 2016
Short summary
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, https://doi.org/10.5194/hess-20-193-2016, https://doi.org/10.5194/hess-20-193-2016, 2016
Short summary
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, https://doi.org/10.5194/hess-19-4275-2015, https://doi.org/10.5194/hess-19-4275-2015, 2015
G. G. Oliveira, O. C. Pedrollo, and N. M. R. Castro
Hydrol. Earth Syst. Sci., 19, 3585–3604, https://doi.org/10.5194/hess-19-3585-2015, https://doi.org/10.5194/hess-19-3585-2015, 2015
Short summary
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, https://doi.org/10.5194/hess-19-3093-2015, https://doi.org/10.5194/hess-19-3093-2015, 2015
C. Onyutha and P. Willems
Hydrol. Earth Syst. Sci., 19, 2227–2246, https://doi.org/10.5194/hess-19-2227-2015, https://doi.org/10.5194/hess-19-2227-2015, 2015
Short summary
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, https://doi.org/10.5194/hess-19-1827-2015, https://doi.org/10.5194/hess-19-1827-2015, 2015
Cited articles
Aspelien, T., Iversen, T., Bremnes, J. B., and Frogner, I.-L.: Short-range probabilistic forecasts from the Norwegian limited-area EPS: long-term validation and a polar low study, Tellus A, 63, 564–584, https://doi.org/10.1111/j.1600-0870.2010.00502.x, 2011.
Auffray, A., Clavel, A., Jourdain, S., Ben Daoud, A., Sauquet, E., Lang, M., Obled, C., Panthou, G., Gautheron, A., Gottardi, F., and Garçon, R.: Reconstitution hydrométéorologique de la crue de l'Isère de 1859 (Reconstructing the hydrometeorological scenario of the 1859 flood of the Isère river), La Houille Blanche, 44–50, https://doi.org/10.1051/lhb/2011005, 2011.
Auguie, B.: gridExtra: functions in Grid graphics, r package version 0.9.1, http://CRAN.R-project.org/package=gridExtra, last access: 24 October 2013, 2012.
Beaulant, A.-L., Joly, B., Nuissier, O., Somot, S., Ducrocq, V., Joly, A., Sevault, F., Deque, M., and Ricard, D.: Statistico-dynamical downscaling for Mediterranean heavy precipitation, Q. J. Roy. Meteorol. Soc., 137, 736–748, https://doi.org/10.1002/qj.796, 2011.
Bellone, E., Hughes, J. P., and Guttorp, P.: A hidden Markov model for downscaling synoptic atmospheric patterns to precipitation amounts, Clim. Res., 15, 1–12, 2000.
Ben Daoud, A.: Améliorations et développements d'une méthode de prévision probabiliste des pluies par analogie, Application à la prévision hydrologique sur les grands bassins fluviaux de la Saône et de la Seine, Thèse de doctorat, Université Joseph Fourier, Grenoble, 2010.
Ben Daoud, A., Sauquet, E., Lang, M., Obled, C., and Bontron, G.: La prévision des précipitations par recherche d'analogues: etat de l'art et perspectives (Precipitation forecasting through an analog sorting technique: state of the art and further investigations), La Houille Blanche, 6, 60–65, https://doi.org/10.1051/lhb/2009079, 2009.
Ben Daoud, A., Sauquet, E., Lang, M., Bontron, G., and Obled, C.: Precipitation forecasting through an analog sorting technique: a comparative study, Adv. Geosci., 29, 103–107, https://doi.org/10.5194/adgeo-29-103-2011, 2011a.
Ben Daoud, A., Sauquet, E., Lang, M., and Ramos, M.-H.: Peut-on étendre l'échéance de prévision des crues en optimisant la prévision de pluies par recherche d'analogues? Application au bassin de la Seine à Paris (Can we extend flood forecasting lead-time by optimising precipitation forecasting based on analogs? Application to the Seine river basin), La Houille Blanche, 37–43, https://doi.org/10.1051/lhb/2011004, 2011b.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Bivand, R. S., Pebesma, E. J., and Gomez-Rubio, V.: Applied spatial data analysis with R, http://www.asdar-book.org/, Springer, New York, NY, 2008.
Boé, J.: Changement global et cycle hydrologique : Une étude de régionalisation sur la France, Thèse de doctorat, 3, http://thesesups.ups-tlse.fr/227/, Université Toulouse, 2007.
Boé, J. and Terray, L.: A weather-type approach to analyzing winter precipitation in France: Twentieth-century trends and the role of anthropogenic forcing, J. Climate, 21, 3118–3133, https://doi.org/10.1175/2007JCLI1796.1, 2008.
Boé, J., Terray, L., Habets, F., and Martin, E.: A simple statistical-dynamical downscaling scheme based on weather types and conditional resampling, J. Geophys. Res., 111, D23106, https://doi.org/10.1029/2005JD006889, 2006.
Boé, 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.
Boé, J., Terray, L., Martin, E., and Habets, F.: Projected changes in components of the hydrological cycle in French river basins during the 21st century, Water Resour. Res., 45, W08426, https://doi.org/10.1029/2008WR007437, 2009.
Bontron, G.: Prévision quantitative des précipitations: adaptation probabiliste par recherche d'analogues, Utilisation des réanalyses NCEP/NCAR et application aux précipitations du Sud-Est de la France, Thèse de doctorat, Institut National Polytechnique de Grenoble, 2004.
Bontron, G. and Obled, C.: L'adaptation probabiliste des prévisions météorologiques pour la prévision hydrologique (A probabilistic adaptation of meteorological model outputs to hydrological forecasting), La Houille Blanche, 23–28, https://doi.org/10.1051/lhb:200501002, 2005.
Brigode, P., Bernardara, P., Gailhard, J., and Ribstein, P.: Optimization of the geopotential heights informatio used in a rainfall based weather patterns classification over Austria, Int. J. Climatol., 33, 1563–1573, https://doi.org/10.1002/joc.3535, 2013.
Brown, T. A.: Admissible scoring systems for continuous distributions, The Rand Paper Series P-5235, The Rand Corporation, Santa Monica, California, 1974.
Carreau, J. and Vrac, M.: Stochastic downscaling of precipitation with neural network conditional mixture models, Water Resour. Res., 47, W10502, https://doi.org/10.1029/2010WR010128, 2011.
Chandler, R. E.: On the use of generalized linear models for interpreting climate variability, Environmetrics, 16, 699–715, https://doi.org/10.1002/env.731, 2002.
Chen, J., Brissette, F. P., and Leconte, R.: A daily stochastic weather generator for preserving low-frequency of climate variability, J. Hydrol., 388, 480–490, https://doi.org/10.1016/j.jhydrol.2010.05.032, 2010.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Demargne, J., Brown, J., Liu, Y., Seo, D.-J., Wu, L., Toth, Z., and Zhu, Y.: Diagnostic verification of hydrometeorological and hydrologic ensembles, Atmos. Sci. Lett., 11, 114–122, https://doi.org/10.1002/asl.261, 2010.
Duband, D.: Prévision spatiale des hauteurs de précipitations journalières (A spatial forecast of daily precipitation heights), La Houille Blanche, 497–512, https://doi.org/10.1051/lhb/1981046, 1981.
Duffourg, F. and Ducrocq, V.: Origin of the moisture feeding the Heavy Precipitating Systems over Southeastern France, Nat. Hazards Earth Syst. Sci., 11, 1163–1178, https://doi.org/10.5194/nhess-11-1163-2011, 2011.
Friederichs, P. and Hense, A.: Statistical downscaling of extreme precipitation events using censored quantile regression, Mon. Weather Rev., 135, 2365–2378, https://doi.org/10.1175/MWR3403.1, 2007.
Garavaglia, F., Gailhard, J., Paquet, E., Lang, M., Garçon, R., and Bernardara, P.: Introducing a rainfall compound distribution model based on weather patterns sub-sampling, Hydrol. Earth Syst. Sci., 14, 951–964, https://doi.org/10.5194/hess-14-951-2010, 2010.
Guilbaud, S. and Obled, C.: Prévision quantitative des précipitations journalièes par une technique de recherche de journées antérieures analogues: optimisation du critère d'analogie (Daily quantitative precipitation forecast by an analogue technique: optimisation of the analogy criterion), Comptes Rendus de l'Académie des Sciences – Series IIA, Earth Planet. Sci., 327, 181–188, https://doi.org/10.1016/S1251-8050(98)80006-2, 1998.
Gutiérrez, J. M., San-Martín, D., Brands, S., Manzanas, R., and Herrera, S.: Reassessing statistical downscaling techniques for their robust application under climate change conditions, J. Climate, 26, 171–188, https://doi.org/10.1175/JCLI-D-11-00687.1, 2013.
Hagedorn, R., Hamill, T. M., and Whitaker, J. S.: Probabilistic forecast calibration using ECMWF and GFS ensemble reforecasts, Part I: Two-meter temperatures, Mon. Weather Rev., 136, 2608–2619, https://doi.org/10.1175/2007MWR2410.1, 2008.
Hamill, T. M. and Whitaker, J. S.: Probabilistic quantitative precipitation forecasts based on reforecast analogs: Theory and application, Mon. Weather Rev., 134, 3209–3229, https://doi.org/10.1175/MWR3237.1, 2006.
Hanssen-Bauer, I., Førland, E. J., Haugen, J. E., and Tveito, O. E.: Temperature and precipitation scenarios for Norway: comparison of results from dynamical and empirical downscaling, Clim. Res., 25, 15–27, https://doi.org/10.3354/cr025015, 2003.
Harrower, M. and Brewer, C. A.: ColorBrewer.org: An online tool for selecting colour schemes for maps, Cartogr. J., 40, 27–37, https://doi.org/10.1179/000870403235002042, 2003.
Hersbach, H.: Decomposition of the Continuous Ranked Probability Score for ensemble prediction systems, Weather Forecast., 15, 559–570, 2000.
Hertig, E., Paxian, A., Vogt, G., Seubert, S., Paeth, H., and Jacobeit, J.: Statistical and dynamical downscaling assessments of precipitation extremes in the Mediterranean area, Meteorol. Z., 21, 61–77, https://doi.org/10.1127/0941-2948/2012/0271, 2012.
Horton, P.: Améliorations et optimisation globale de la méthode des analogues pour la prévision statistique des précipitations, Développement d'un outil de prévision et application opérationnelle au bassin du Rhône à l'amont du Léman, Thèse de doctorat, Université de Lausanne, Switzerland, 2012.
Horton, P., Jaboyedoff, M., Metzger, R., Obled, C., and Marty, R.: Spatial relationship between the atmospheric circulation and the precipitation measured in the western Swiss Alps by means of the analogue method, Nat. Hazards Earth Syst. Sci., 12, 777–784, https://doi.org/10.5194/nhess-12-777-2012, 2012.
Ibarra-Berastegi, G., Saénz, J., Ezcurra, A., Elías, A., Diaz Argandoña, J., and Errasti, I.: Downscaling of surface moisture flux and precipitation in the Ebro Valley (Spain) using analogues and analogues followed by random forests and multiple linear regression, Hydrol. Earth Syst. Sci., 15, 1895–1907, https://doi.org/10.5194/hess-15-1895-2011, 2011.
Kallache, M., Vrac, M., Naveau, P., and Michelangeli, P.-A.: Nonstationary probabilistic downscaling of extreme precipitation, J. Geophys. Res., 116, D05113, https://doi.org/10.1029/2010JD014892, 2011.
Kalnay, E., Kanamitsu, M., Kistler, R. W. C., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janoviak, J., Mo, K. C., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D.: The NCEP/NCAR 40-year Reanalysis Project, B. Am. Meteorol. Soc., 77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996.
Klemeš, V.: Operational testing of hydrological simulation models, Hydrolog. Sci. J., 31, 13–24, 1986.
Lavaysse, C., Vrac, M., Drobinski, P., Lengaigne, M., and Vischel, T.: Statistical downscaling of the French Mediterranean climate: assessment for present and projection in an anthropogenic scenario, Nat. Hazards Earth Syst. Sci., 12, 651–670, https://doi.org/10.5194/nhess-12-651-2012, 2012.
Lémond, J., Dandin, P., Planton, S., Vautard, R., Pagé, C., Déqué, M., Franchistéguy, L., Geindre, S., Kerdoncuff, M., Li, L., Moisselin, J.-M., Noël, T., and Tourre, Y. M.: DRIAS: a step toward Climate Services in France, Adv. Sci. Res., 6, 179–186, https://doi.org/10.5194/asr-6-179-2011, 2011.
Liu, X. and Coulibaly, P.: Downscaling ensemble weather predictions for improved week-2 hydrologic forecasting, J. Hydrometeorol., 12, 1564–1580, https://doi.org/10.1175/2011JHM1366.1, 2011.
Lorenz, E. N.: Atmospheric predictability as revealed by naturally occurring analogues, J Atmos Sci, 26, 636–646, https://doi.org/10.1175/1520-0469(1969)26<636:APARBN>2.0.CO;2, 1969.
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themessl, 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.
Martin, E., Timbal, B., and Brun, E.: Downscaling of general circulation model outputs: simulation of the snow climatology of the French Alps and sensitivity to climate change, Clim. Dynam., 13, 45–56, https://doi.org/10.1007/s003820050152, 1997.
Marty, R., Zin, I., and Obled, C.: On adapting PQPFs to fit hydrological needs: the case of flash flood forecasting, Atmos. Sci. Lett., 9, 73–79, 2008.
Marty, R., Zin, I., Obled, C., Bontron, G., and Djerboua, A.: Toward real-time daily PQPF by an analog sorting approach: Application to flash-flood catchments, J. Appl. Meteorol. Clim., 51, 505–520, https://doi.org/10.1175/JAMC-D-11-011.1, 2012.
Marty, R., Zin, I., and Obled, C.: Sensitivity of hydrological ensemble forecasts to different sources and temporal resolutions of probabilistic quantitative precipitation forecasts: flash flood case studies in the Cévennes-Vivarais region (Southern France), Hydrol. Process., 27, 33–44, https://doi.org/10.1002/hyp.9543, 2013.
Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous probability distributions, Manage Sci., 22, 1087–1095, 1976.
Matulla, C., Zhang, X., Wang, X. L., Wang, J., Zorita, E., Wagner, S., and von Storch, H.: Influence of similarity measures on the performance of the analog method for downscaling daily precipitation, Clim. Dynam., 30, 133–144, https://doi.org/10.1007/s00382-007-0277-2, 2008.
Muluye, G. Y.: Deriving meteorological variables from numerical weather prediction model output: A nearest neighbor approach, Water Resour. Res., 47, W07509, https://doi.org/10.1029/2010WR009750, 2011.
Nam, D. H., Udo, K., and Mano, A.: Downscaling global weather forecast outputs using ANN for flood prediction, J. Appl. Math., 2011, 246–286, https://doi.org/10.1155/2011/246286, 2011.
Neuwirth, E.: RColorBrewer: ColorBrewer palettes, http://CRAN.R-project.org/package=RColorBrewer (last access: 24 October 2013), 2011.
Nuissier, O., Joly, B., Joly, A., Ducrocq, V., and Arbogast, P.: A statistical downscaling to identify the large-scale circulation patterns associated with heavy precipitation events over southern France, Q. J. Roy. Meteorol. Soc., 137, 1812–1827, https://doi.org/10.1002/qj.866, 2011.
Obled, C., Bontron, G., and Garçon, R.: Quantitative precipitation forecasts: a statistical adaptation of model outputs through an analogues sorting approach, Atmos. Res., 63, 303–324, https://doi.org/10.1016/S0169-8095(02)00038-8, 2002.
Pagé, C. and Terray, L.: Nouvelles projections climatiques à échelle fine sur la France pour le 21ème siècle : les scénarii SCRATCH2010, Technical Report TR/CMGC/10/58, CERFACS, Toulouse Cedex, France, 2010.
Pagé, C., Terray, L., and Boé, J.: Projections climatiques à échelle fine sur la France pour le 21ème siècle: les scénarii SCRATCH08, Technical note, Climate Modelling and Global Change TR/CMGC/08/64, CERFACS, Toulouse, France, 2008.
Pebesma, E. and Bivand, R.: Classes and methods for spatial data in R, r news 5th Edn., http://cran.r-project.org/doc/Rnews/ (last access: 24 October 2013), 2005.
Pierce, D.: ncdf: Interface to Unidata netCDF data files, r package version 1.6.6, http://CRAN.R-project.org/package=ncdf (last access: 24 October 2013), 2011.
Pincus, R. and Rew, R.: NetCDF Fortran 90 Guide, netcdf 4.1.3 Edn., UCAR Unidata, Boulder, Colorado, 2011.
Quintana-Seguí, P., Le Moigne, P., Durand, Y., Martin, E., Habets, F., Baillon, M., Canellas, C., Franchistéguy, L., and Morel, S.: Analysis of near-surface atmospheric variables: Validation of the SAFRAN analysis over France, J. Appl. Meteorol. Clim., 47, 92–107, https://doi.org/10.1175/2007JAMC1636.1, 2008.
Quintana Seguí, P., Ribes, A., Martin, E., Habets, F., and Boé, J.: Comparison of three downscaling methods in simulating the impact of climate change on the hydrology of Mediterranean basins, J. Hydrol., 383, 111–124, https://doi.org/10.1016/j.jhydrol.2009.09.050, 2010.
Quintana-Seguí, P., Habets, F., and Martin, E.: Comparison of past and future Mediterranean high and low extremes of precipitation and river flow projected using different statistical downscaling methods, Nat. Hazards Earth Syst. Sci., 11, 1411–1432, https://doi.org/10.5194/nhess-11-1411-2011, 2011.
Raje, D. and Mujumdar, P. P.: A comparison of three methods for downscaling daily precipitation in the Punjab region, Hydrol. Process., 25, 3575–3589, https://doi.org/10.1002/hyp.8083, 2011.
R Development Core Team: R: A Language and Environment for Statistical Computing, http://www.R-project.org/, R Foundation for Statistical Computing, Vienna, Austria, 2012.
Ricard, D., Ducrocq, V., and Auger, L.: A climatology of the mesoscale environment associated with Heavily Precipitating Events over a Northwestern Mediterranean Area, J. Appl. Meteorol. Clim., 51, 468–488, https://doi.org/10.1175/JAMC-D-11-017.1, 2012.
Sauter, T. and Venema, V.: Natural three-dimensional predictor domains for statistical precipitation downscaling, J. Climate, 24, 6132–6145, https://doi.org/10.1175/2011JCLI4155.1, 2011.
Teuling, A. J., Stöckli, R., and Seneviratne, S. I.: Bivariate colour maps for visualizing climate data, Int. J. Climatol., 31, 1408–1412, https://doi.org/10.1002/joc.2153, 2011.
Teutschbein, C., Wetterhall, F., and Seibert, J.: Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale, Clim. Dynam., 37, 2087–2105, https://doi.org/10.1007/s00382-010-0979-8, 2011.
Teweles, S. and Wobus, H. B.: Verification of prognostic charts, B. Am. Meteorol. Soc., 35, 455–463, 1954.
Themeßl, 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.
Timbal, B. and McAvaney, B. J.: An analogue-based method to downscale surface air temperature: application for Australia, Clim. Dynam., 17, 947–963, https://doi.org/10.1007/s003820100156, 2001.
Timbal, B., Dufour, A., and McAvaney, B.: An estimate of future climate change for western France using a statistical downscaling technique, Clim. Dynam., 20, 807–823, https://doi.org/10.1007/s00382-002-0298-9, 2003.
Timbal, B., Hope, P., and Charles, S.: Evaluating the consistency between statistically downscaled and global dynamical model climate change projections, J. Climate, 21, 6052–6059, https://doi.org/10.1175/2008JCLI2379.1, 2008.
Turco, M., Quintana Seguí, 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., Da Costa Bechtold, V., 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., Van De Berg, L., 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 re-analysis, Q. J. Roy. Meteorol. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2005.
Vidal, J.-P. and Wade, S. D.: A framework for developing high-resolution multi-model climate projections: 21st century scenarios for the UK, Int. J. Climatol., 28, 843–858, https://doi.org/10.1002/joc.1593, 2008.
Vidal, J.-P., Martin, E., Franchistéguy, L., Baillon, M., and Soubeyroux, J.-M.: A 50-year high-resolution atmospheric reanalysis over France with the Safran system, Int. J. Climatol., 30, 1627–1644, https://doi.org/10.1002/joc.2003, 2010.
Vidal, J.-P., Martin, E., Kitova, N., Najac, J., and Soubeyroux, J.-M.: Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios, Hydrol. Earth Syst. Sci., 16, 2935–2955, https://doi.org/10.5194/hess-16-2935-2012, 2012.
Voisin, N., Schaake, J. C., and Lettenmaier, D. P.: Calibration and downscaling methods for quantitative ensemble precipitation forecasts, Weather Forecast., 25, 1603–1627, https://doi.org/10.1175/2010WAF2222367.1, 2010.
Vrac, M., Stein, M., and Hayhoe, K.: Statistical downscaling of precipitation through nonhomogeneous stochastic weather typing, Clim. Res., 34, 169–184, https://doi.org/10.3354/cr00696, 2007.
Wetterhall, F., Halldin, S., and Xu, C.-y.: Statistical precipitation downscaling in central Sweden with the analogue method, J. Hydrol., 306, 174–190, https://doi.org/10.1016/j.jhydrol.2004.09.008, 2005.
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.
Wickham, H.: Reshaping data with the reshape package, J. Stat. Softw., 21, 1–20, 2007.
Wickham, H.: ggplot2: elegant graphics for data analysis, Use R!, Springer, New York, https://doi.org/10.1007/978-0-387-98141-3, 2009.
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., Hassan, H., and Hanaki, K.: Statistical downscaling of hydrometeorological variables using general circulation model output, J. Hydrol., 205, 1–19, https://doi.org/10.1016/S0022-1694(97)00130-3, 1998.
Zeileis, A. and Grothendieck, G.: zoo: S3 infrastructure for regular and irregular time series, J. Stat. Softw., 14, 1–27, 2005.
Zhang, F. and Georgakakos, A. P.: Joint variable spatial downscaling, Climatic Change, 111, 945–972, https://doi.org/10.1007/s10584-011-0167-9, 2012.
