Articles | Volume 24, issue 5
https://doi.org/10.5194/hess-24-2671-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-2671-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 May 2020
Research article |
| 26 May 2020
| 26 May 2020
Uncovering the shortcomings of a weather typing method
Els Van Uytven
CORRESPONDING AUTHOR
Department of Civil Engineering, Hydraulics Section, KU Leuven, Kasteelpark 40, box 2448, 3001 Leuven, Belgium
Jan De Niel
Department of Civil Engineering, Hydraulics Section, KU Leuven, Kasteelpark 40, box 2448, 3001 Leuven, Belgium
Patrick Willems
Department of Civil Engineering, Hydraulics Section, KU Leuven, Kasteelpark 40, box 2448, 3001 Leuven, Belgium
Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
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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
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Vincent Wolfs, Quan Tran Quoc, and Patrick Willems
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C. Onyutha and P. Willems
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Revised manuscript not accepted
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To investigate the possible change in catchment behavior, which may interfere with the flow-rainfall relationship, three rainfall-runoff models were applied to the main catchments of the Nile Basin in Africa based on inputs covering the period from 1940 to 2003. There was close agreement between the changes in the observed and simulated overland flow from all the models. Thus, change in catchment behavior due to anthropogenic influence in the Nile basin over the selected time period was minimal.
L.-P. Wang, S. Ochoa-Rodríguez, C. Onof, and P. Willems
Hydrol. Earth Syst. Sci., 19, 4001–4021, https://doi.org/10.5194/hess-19-4001-2015, https://doi.org/10.5194/hess-19-4001-2015, 2015
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A new methodology is proposed in this paper, focusing on improving the applicability of the operational weather radar data to urban hydrology with rain gauge data. The proposed methodology employed a simple yet effective technique to extract additional information (called local singularity structure) from radar data, which was generally ignored in related works. The associated improvement can be particularly seen in capturing storm peak magnitudes, which is critical for urban applications.
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
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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
A. Ochoa, L. Pineda, P. Crespo, and P. Willems
Hydrol. Earth Syst. Sci., 18, 3179–3193, https://doi.org/10.5194/hess-18-3179-2014, https://doi.org/10.5194/hess-18-3179-2014, 2014
D. Vrebos, T. Vansteenkiste, J. Staes, P. Willems, and P. Meire
Hydrol. Earth Syst. Sci., 18, 1119–1136, https://doi.org/10.5194/hess-18-1119-2014, https://doi.org/10.5194/hess-18-1119-2014, 2014
D. E. Mora, L. Campozano, F. Cisneros, G. Wyseure, and P. Willems
Hydrol. Earth Syst. Sci., 18, 631–648, https://doi.org/10.5194/hess-18-631-2014, https://doi.org/10.5194/hess-18-631-2014, 2014
M. T. Taye and P. Willems
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-7857-2013, https://doi.org/10.5194/hessd-10-7857-2013, 2013
Revised manuscript not accepted
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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Yan Li, Bo Huang, Chunping Tan, Xia Zhang, Francesco Cherubini, and Henning W. Rust
Hydrol. Earth Syst. Sci., 29, 1637–1658, https://doi.org/10.5194/hess-29-1637-2025, https://doi.org/10.5194/hess-29-1637-2025, 2025
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Deforestation has a significant impact on climate, yet its effects on drought remain less understood. This study investigates how deforestation affects drought across various climate zones and timescales. Findings indicate that deforestation leads to drier conditions in tropical regions and wetter conditions in arid areas, with minimal effects in temperate zones. Long-term drought is more affected than short-term drought, offering valuable insights into vegetation–climate interactions.
Iván Noguera, Jamie Hannaford, and Maliko Tanguy
Hydrol. Earth Syst. Sci., 29, 1295–1317, https://doi.org/10.5194/hess-29-1295-2025, https://doi.org/10.5194/hess-29-1295-2025, 2025
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The study provides a detailed characterisation of flash drought in the UK for 1969–2021. The spatio-temporal distribution and trends of flash droughts are highly variable, with important regional and seasonal contrasts. In the UK, flash drought development responds primarily to precipitation variability, while the atmospheric evaporative demand plays a secondary role. We also found that the North Atlantic Oscillation is the main circulation pattern controlling flash drought development.
Geert Lenderink, Nikolina Ban, Erwan Brisson, Ségolène Berthou, Virginia Edith Cortés-Hernández, Elizabeth Kendon, Hayley J. Fowler, and Hylke de Vries
Hydrol. Earth Syst. Sci., 29, 1201–1220, https://doi.org/10.5194/hess-29-1201-2025, https://doi.org/10.5194/hess-29-1201-2025, 2025
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Future extreme rainfall events are influenced by changes in both absolute and relative humidity. The impact of increasing absolute humidity is reasonably well understood, but the role of relative humidity decreases over land remains largely unknown. Using hourly observations from France and the Netherlands, we find that lower relative humidity generally leads to more intense rainfall extremes. This relation is only captured well in recently developed convection-permitting climate models.
Alexis Bédard-Therrien, François Anctil, Julie M. Thériault, Olivier Chalifour, Fanny Payette, Alexandre Vidal, and Daniel F. Nadeau
Hydrol. Earth Syst. Sci., 29, 1135–1158, https://doi.org/10.5194/hess-29-1135-2025, https://doi.org/10.5194/hess-29-1135-2025, 2025
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Precipitation data from an automated observational network in eastern Canada showed a temperature interval where rain and snow could coexist. Random forest models were developed to classify the precipitation phase using meteorological data to evaluate operational applications. The models demonstrated significantly improved phase classification and reduced error compared to benchmark operational models. However, accurate prediction of mixed-phase precipitation remains challenging.
Lorenzo Silvestri, Miriam Saraceni, Bruno Brunone, Silvia Meniconi, Giulia Passadore, and Paolina Bongioannini Cerlini
Hydrol. Earth Syst. Sci., 29, 925–946, https://doi.org/10.5194/hess-29-925-2025, https://doi.org/10.5194/hess-29-925-2025, 2025
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This work demonstrates that seasonal forecasts of soil moisture are a valuable resource for groundwater management in the areas of the Central Mediterranean where longer memory timescales are found. In particular, they show significant correlation coefficients and forecast skill for the deepest soil moisture at 289 cm depth. Wet and dry events can be predicted 6 months in advance, and, in general, dry events are better captured than wet events.
Mohammad A. Farmani, Ali Behrangi, Aniket Gupta, Ahmad Tavakoly, Matthew Geheran, and Guo-Yue Niu
Hydrol. Earth Syst. Sci., 29, 547–566, https://doi.org/10.5194/hess-29-547-2025, https://doi.org/10.5194/hess-29-547-2025, 2025
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Soil moisture memory (SMM) shows how long soil stays moist after rain, impacting climate and ecosystems. Current models often overestimate SMM, causing inaccuracies in evaporation predictions. We enhanced a land model, Noah-MP, to include better water flow and ponding processes, and we tested it against satellite and field data. This improved model reduced overestimations and enhanced short-term predictions, helping create more accurate climate and weather forecasts.
Felipe Lobos-Roco, Jordi Vilà-Guerau de Arellano, and Camilo del Río
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Water resources are fundamental for the social, economic, and natural development of (semi-)arid regions. Precipitation decreases due to climate change obligate us to find new water resources. Fog harvesting (FH) emerges as a complementary resource in regions where it is abundant but untapped. This research proposes a model to estimate FH potential in coastal (semi-)arid regions. This model could have broader applicability worldwide in regions where FH could be a viable water source.
Kyle R. Mankin, Sushant Mehan, Timothy R. Green, and David M. Barnard
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We assess 63 gridded ground (G), satellite (S), and reanalysis (R) climate datasets. Higher-density station data and less-hilly terrain improved climate data. In mountainous and humid regions, dataset types performed similarly; however, R outperformed G when underlying data had low station density. G outperformed S or R datasets, although better streamflow modeling did not always follow. Hydrologic analyses need datasets that better represent climate variable dependencies and complex topography.
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Hydrol. Earth Syst. Sci., 29, 45–65, https://doi.org/10.5194/hess-29-45-2025, https://doi.org/10.5194/hess-29-45-2025, 2025
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We present a new method to calculate the chance of heavy downpour and the maximum rainfall expected over a 25-year period. It is designed to analyse global climate models' reproduction of past and future climates. For the Nordic countries, it projects a wetter climate in the future with increased intensity but not necessarily more wet days. The analysis also shows that rainfall intensity is sensitive to future greenhouse gas emissions, while the number of wet days appears to be less affected.
Chien-Yu Tseng, Li-Pen Wang, and Christian Onof
Hydrol. Earth Syst. Sci., 29, 1–25, https://doi.org/10.5194/hess-29-1-2025, https://doi.org/10.5194/hess-29-1-2025, 2025
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This study presents a new algorithm to model convective storms. We used advanced tracking methods to analyse 165 storm events in Birmingham (UK) and reconstruct storm cell life cycles. We found that cell properties like intensity and size are interrelated and vary over time. The new algorithm, based on vine copulas, accurately simulates these properties and their evolution. It also integrates an exponential shape function for realistic rainfall patterns, enhancing its hydrological applicability.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
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This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Peter E. Levy and the COSMOS-UK team
Hydrol. Earth Syst. Sci., 28, 4819–4836, https://doi.org/10.5194/hess-28-4819-2024, https://doi.org/10.5194/hess-28-4819-2024, 2024
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach that is closely linked to direct measurements of soil moisture at a network sites across the UK, to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212) and to remotely sensed satellite estimates.
Amy C. Green, Chris Kilsby, and András Bárdossy
Hydrol. Earth Syst. Sci., 28, 4539–4558, https://doi.org/10.5194/hess-28-4539-2024, https://doi.org/10.5194/hess-28-4539-2024, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well in generating realistic weather radar images visually for a large range of event types.
Peyman Abbaszadeh, Keyhan Gavahi, and Hamid Moradkhani
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-209, https://doi.org/10.5194/hess-2024-209, 2024
Revised manuscript accepted for HESS
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The Hybrid Ensemble and Variational Data Assimilation framework for Environmental System (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three Southeastern U.S. watersheds during hurricanes, HEAVEN assimilates real-time USGS streamflow data, boosting forecast accuracy.
Ling Zhang, Lu Li, Zhongshi Zhang, Joël Arnault, Stefan Sobolowski, Anthony Musili Mwanthi, Pratik Kad, Mohammed Abdullahi Hassan, Tanja Portele, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-278, https://doi.org/10.5194/hess-2024-278, 2024
Revised manuscript accepted for HESS
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To address challenges related to unreliable hydrological simulations, we present an enhanced hydrological simulation with a refined climate model and a more comprehensive hydrological model. The model with the two parts outperforms that without, especially in migrating bias in peak flow and dry-season flow. Our findings highlight the enhanced hydrological simulation capability with the refined climate and lake module contributing 24 % and 76 % improvement, respectively.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
Hydrol. Earth Syst. Sci., 28, 4455–4476, https://doi.org/10.5194/hess-28-4455-2024, https://doi.org/10.5194/hess-28-4455-2024, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a reliable historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
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Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Simon Moulds, Louise Slater, Louise Arnal, and Andrew Wood
EGUsphere, https://doi.org/10.31223/X5X405, https://doi.org/10.31223/X5X405, 2024
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Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to four months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to four months ahead in many locations, although in general the skill declines with increasing lead time.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
Hydrol. Earth Syst. Sci., 28, 4127–4155, https://doi.org/10.5194/hess-28-4127-2024, https://doi.org/10.5194/hess-28-4127-2024, 2024
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Forecasting river flow months in advance is crucial for water sectors and society. In North America, snowmelt is a key driver of flow. This study presents a statistical workflow using snow data to forecast flow months ahead in North American snow-fed rivers. Variations in the river flow predictability across the continent are evident, raising concerns about future predictability in a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
Ningpeng Dong, Haoran Hao, Mingxiang Yang, Jianhui Wei, Shiqin Xu, and Harald Kunstmann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-212, https://doi.org/10.5194/hess-2024-212, 2024
Revised manuscript accepted for HESS
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Hydrometeorological forecasting is crucial for managing water resources and mitigating extreme weather impacts, yet current long-term forecast products are often embedded with uncertainties. We develop a deep learning based modelling framework to improve 30-day rainfall and streamflow forecasts by combining advanced neural networks and outputs from physical models. With the forecast error reduced by up to 32%, the framework has the potential to enhance water management and disaster preparedness.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci., 28, 3305–3326, https://doi.org/10.5194/hess-28-3305-2024, https://doi.org/10.5194/hess-28-3305-2024, 2024
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Kazeem Ishola, Gerald Mills, Ankur Sati, Benjamin Obe, Matthias Demuzere, Deepak Upreti, Gourav Misra, Paul Lewis, Daire Walsh, Tim McCarthy, and Rowan Fealy
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-304, https://doi.org/10.5194/hess-2023-304, 2024
Revised manuscript accepted for HESS
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The global soil information contributes to uncertainty in many models that monitor soil hydrothermal changes. Using the NOAH-MP model with two different global soil information, we show under-represented soil properties in wet loam soil, leading to dry bias in soil moisture. The dry bias is higher and drought categories are more severe in SOILGRIDS. We conclude that models should consider using detailed regionally-derived soil information, to reduce model uncertainties.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Kun Xie, Lu Li, Hua Chen, Stephanie Mayer, Andreas Dobler, Chong-Yu Xu, and Ozan Mert Gokturk
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-68, https://doi.org/10.5194/hess-2024-68, 2024
Revised manuscript accepted for HESS
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We compared extreme precipitations in Norway from convection-permitting models at 3 km resolution (HCLIM3) and regional climate model at 12 km (HCLIM12) and show that the HCLIM3 is more accurate than HCLIM12 in predicting the intense rainfalls that can lead to floods, especially at local scales. This is more clear in hourly extremes than daily. Our research suggests using more detailed climate models could improve forecasts, helping the local society brace for the impacts of extreme weather.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Cited articles
Addor, N., Rohrer, M., Furrer, R., and Seibert, J.: Propagation of biases in
climate models from the synoptic to the regional scale: Implications for bias
adjustment, J. Geophys. Res.-Atmos., 121, 2075–2089,
https://doi.org/10.1002/2015JD024040, 2016. a
Alfieri, L., Feyen, L., and Di Baldassarre, G.: Increasing flood risk under
climate change: a pan-European assessment of the benefits of four adaptation
strategies, Climatic Change, 136, 507–521, https://doi.org/10.1007/s10584-016-1641-1,
2016. a
Ansell, T. J., Jones, P. D., Allan, R. J., Lister, D., Parker, D. E., Brunet,
M., Moberg, A., Jacobeit, J., Brohan, P., Rayner, N. A., Aguilar, E.,
Alexandersson, H., Barriendos, M., Brandsma, T., Cox, N. J., Della-Marta,
P. M., Drebs, A., Founda, D., Gerstengarbe, F., Hickey, K., Jónsson,
T., Luterbacher, J., Nordli, Ø., Oesterle, H., Petrakis, M., Philipp, A.,
Rodwell, M. J., Saladie, O., Sigro, J., Slonosky, V., Srnec, L., Swail, V.,
García-Suárez, A. M., Tuomenvirta, H., Wang, X., Wanner, H.,
Werner, P., Wheeler, D., and Xoplaki, E.: Daily mean sea level pressure
reconstructions for the European-North Atlantic region for the period
1850–2003, J. Climate, 19, 2717–2742, https://doi.org/10.1175/JCLI3775.1,
2006 (data available at: https://www.metoffice.gov.uk/hadobs/emslp/, last access: 10 May 2020). a, b
Anstey, J. A., Davini, P., Gray, L. J., Woollings, T. J., Butchart, N.,
Cagnazzo, C., Christiansen, B., Hardiman, S. C., Osprey, S. M., and Yang, S.:
Multi-model analysis of Northern Hemisphere winter blocking: Model biases and
the role of resolution, J. Geophys. Res.-Atmos., 118,
3956–3971, https://doi.org/10.1002/jgrd.50231, 2013. a, b
Arakawa, A.: The Cumulus Parameterization Problem: Past, Present, and Future,
J. Climate, 17, 2493–2525,
https://doi.org/10.1175/1520-0442(2004)017<2493:RATCPP>2.0.CO;2, 2004. a
Åström, H. L., Sunyer, M., Madsen, H., Rosbjerg, D., and
Arnbjerg-Nielsen, K.: Explanatory analysis of the relationship between
atmospheric circulation and occurrence of flood-generating events in a
coastal city, Hydrol. Process., 30, 2773–2788,
https://doi.org/10.1002/hyp.10767, 2016. a, b
Barbero, R., Westra, S., Lenderink, G., and Fowler, H. J.: Temperature-extreme
precipitation scaling: a two-way causality?, Int. J.
Climatol., 38, e1274–e1279, https://doi.org/10.1002/joc.5370, 2018. a
Barnes, E. A. and Screen, J. A.: The impact of Arctic warming on the
midlatitude jet-stream: Can it? Has it? Will it?, WIRES: Climate Change, 6, 277–286, https://doi.org/10.1002/wcc.337, 2015. a
Benestad, R. E., Hanssen-Bauer, I., and Chen, D.: Empirical-Statistical
Downscaling, WORLD SCIENTIFIC, https://doi.org/10.1142/6908, 2008. a
Blenkinsop, S., Fowler, H. J., Barbero, R., Chan, S. C., Guerreiro, S. B., Kendon, E., Lenderink, G., Lewis, E., Li, X.-F., Westra, S., Alexander, L., Allan, R. P., Berg, P., Dunn, R. J. H., Ekström, M., Evans, J. P., Holland, G., Jones, R., Kjellström, E., Klein-Tank, A., Lettenmaier, D., Mishra, V., Prein, A. F., Sheffield, J., and Tye, M. R.: The INTENSE project: using observations and models to understand the past, present and future of sub-daily rainfall extremes, Adv. Sci. Res., 15, 117–126, https://doi.org/10.5194/asr-15-117-2018, 2018. a
Brekke, L. D., Maurer, E. P., Anderson, J. D., Dettinger, M. D., Townsley,
E. S., Harrison, A., and Pruitt, T.: Assessing reservoir operations risk
under climate change, Water Resour. Res., 45, 1–16,
https://doi.org/10.1029/2008WR006941, 2009. a
Brisson, E., Demuzere, M., Kwakernaak, B., and Van Lipzig, N. P.: Relations between atmospheric circulation and precipitation in Belgium, Meteorol. Atmos. Phys., 111, 27–39, https://doi.org/10.1007/s00703-010-0103-y, 2011. a
Bürger, G., Murdock, T. Q., Werner, A. T., Sobie, S. R., and Cannon, A. J.:
Downscaling Extremes – An Intercomparison of Multiple Statistical Methods for Present Climate, J. Climate, 25, 4366–4388,
https://doi.org/10.1175/JCLI-D-11-00408.1, 2012. a
Casanueva, A., Herrera, S., Fernández, J., and Gutiérrez, J. M.:
Towards a fair comparison of statistical and dynamical downscaling in the
framework of the EURO-CORDEX initiative, Climatic Change, 137, 411–426,
https://doi.org/10.1007/s10584-016-1683-4, 2016. a
Cristiano, E., ten Veldhuis, M.-C., Gaitan, S., Ochoa Rodriguez, S., and van de Giesen, N.: Critical scales to explain urban hydrological response: an application in Cranbrook, London, Hydrol. Earth Syst. Sci., 22, 2425–2447, https://doi.org/10.5194/hess-22-2425-2018, 2018. a
Davini, P., Corti, S., D'Andrea, F., Rivière, G., and von Hardenberg, J.:
Improved Winter European Atmospheric Blocking Frequencies in High-Resolution
Global Climate Simulations, J. Adv. Model. Earth Syst.,
9, 2615–2634, https://doi.org/10.1002/2017MS001082, 2017. a
Demuzere, M., Werner, M., van Lipzig, N. P. M., and Roeckner, E.: An analysis
of present and future ECHAM5 pressure fields using a classification of
circulation patterns, Int. J. Climatol., 29, 1796–1810,
https://doi.org/10.1002/joc.1821, 2009. a
De Niel, J., Demarée, G., and Willems, P.: Weather Typing-Based Flood
Frequency Analysis Verified for Exceptional Historical Events of Past 500
Years Along the Meuse River, Water Resour. Res., 53, 8459–8474,
https://doi.org/10.1002/2017WR020803, 2017. a
Deser, C., Phillips, A., Bourdette, V., and Teng, H.: Uncertainty in climate
change projections: The role of internal variability, Clim. Dynam., 38,
527–546, https://doi.org/10.1007/s00382-010-0977-x, 2012. a
De Troch, R.: The application of the ALARO-0 model for regional climate
modeling in Belgium: extreme precipitation and unfavorable conditions for
the dispersion of air pollutants under present and future climate conditions,
available at: https://biblio.ugent.be/publication/7247081 (last access: 10 May 2020), 2016. a
Dixon, K. W., Lanzante, J. R., Nath, M. J., Hayhoe, K., Stoner, A.,
Radhakrishnan, A., Balaji, V., and Gaitán, C. F.: Evaluating the
stationarity assumption in statistically downscaled climate projections: is
past performance an indicator of future results?, Climatic Change, 135,
395–408, https://doi.org/10.1007/s10584-016-1598-0, 2016. a, b
Dottori, F., Szewczyk, W., Ciscar, J.-C., Zhao, F., Alfieri, L., Hirabayashi,
Y., Bianchi, A., Mongelli, I., Frieler, K., Betts, R., and Feyen, L.:
Increased human and economic losses from river flooding with anthropogenic
warming, Nat. Clim. Change, 8, 781–786, https://doi.org/10.1038/s41558-018-0257-z, 2018. a
Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions “Should we apply bias correction to global and regional climate model data?”, Hydrol. Earth Syst. Sci., 16, 3391–3404, https://doi.org/10.5194/hess-16-3391-2012, 2012. a
Emori, S. and Brown, S. J.: Dynamic and thermodynamic changes in mean and
extreme precipitation under changed climate, Geophys. Res. Lett.,
32, 1–5, https://doi.org/10.1029/2005GL023272, 2005. a
Fadhel, S., Rico-Ramirez, M. A., and Han, D.: Uncertainty of
Intensity–Duration–Frequency (IDF) curves due to varied climate baseline
periods, J. Hydrol., 547, 600–612,
https://doi.org/10.1016/j.jhydrol.2017.02.013, 2017. a
Flaounas, E., Drobinski, P., Vrac, M., Bastin, S., Lebeaupin-Brossier, C.,
Stéfanon, M., Borga, M., and Calvet, J. C.: Precipitation and
temperature space-time variability and extremes in the Mediterranean region:
Evaluation of dynamical and statistical downscaling methods, Clim.
Dynam., 40, 2687–2705, https://doi.org/10.1007/s00382-012-1558-y, 2013. a
Fu, G., Charles, S. P., Chiew, F. H., Ekström, M., and Potter, N. J.:
Uncertainties of statistical downscaling from predictor selection:
Equifinality and transferability, Atmos. Res., 203, 130–140,
https://doi.org/10.1016/j.atmosres.2017.12.008, 2018. a, b
Gutmann, E., Pruitt, T., Clark, M. P., Brekke, L., Arnold, J. R., Raff, D. A.,
and Rasmussen, R. M.: An intercomparison of statistical downscaling methods
used for water resource assessments in the United States, Water Resour.
Res., 50, 7167–7186, https://doi.org/10.1002/2014WR015559, 2014. a
Haberlandt, U., Belli, A., and Bárdossy, A.: Statistical downscaling of
precipitation using a stochastic rainfall model conditioned on circulation
patterns – an evaluation of assumptions, Int. J.
Climatol., 35, 417–432, https://doi.org/10.1002/joc.3989, 2015. a
Hartung, K., Svensson, G., and Kjellström, E.: Resolution, physics and
atmosphere–ocean interaction – How do they influence climate model
representation of Euro-Atlantic atmospheric blocking?, Tellus A, 69, 1406252,
https://doi.org/10.1080/16000870.2017.1406252, 2017. a
Hertig, E., Merkenschlager, C., and Jacobeit, J.: Change points in
predictors–predictand relationships within the scope of statistical
downscaling, Int. J. Climatol., 37, 1619–1633,
https://doi.org/10.1002/joc.4801, 2017. a
Hertig, E., Maraun, D., Bartholy, J., Pongracz, R., Vrac, M., Mares, I.,
Gutiérrez, J. M., Wibig, J., Casanueva, A., and Soares, P. M. M.:
Comparison of statistical downscaling methods with respect to extreme events
over Europe: Validation results from the perfect predictor experiment of the
COST Action VALUE, Int. J. Climatol., 39, 3846–3867,
https://doi.org/10.1002/joc.5469, 2018. a
Hewitson, B. C., Daron, J., Crane, R. G., Zermoglio, M. F., and Jack, C.:
Interrogating empirical-statistical downscaling, Climatic Change, 122,
539–554, https://doi.org/10.1007/s10584-013-1021-z, 2014. a
Horton, P. and Brönnimann, S.: Impact of global atmospheric reanalyses
on statistical precipitation downscaling, Clim. Dynam., 52, 5189–5211,
https://doi.org/10.1007/s00382-018-4442-6, 2018. a
Jenkinson, A. and Collison, F.: An initial climatology of gales over the North Sea, Synoptic Climatology Branch Memorandum, Meteorological Office, Bracknell, UK, 62, 1977. a
Jones, P. D., Hulme, M., and Briffa, K. R.: A comparison of Lamb circulation
types with an objective classification scheme, Int. J.
Climatol., 13, 655–663, https://doi.org/10.1002/joc.3370130606, 1993. a
Jury, M. W., Herrera, S., Gutiérrez, J. M., and Barriopedro, D.:
Blocking representation in the ERA-Interim driven EURO-CORDEX RCMs, Clim.
Dynam., 52, 3291–3306, https://doi.org/10.1007/s00382-018-4335-8, 2018. a
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M.,
Ebisuzaki, W., Higgins, W., Janowiak, 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, 437–472, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996 (data available at: https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html, last access: 10 May 2020). a, b
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014. a
Kröner, N.: Identifying and quantifying large-scale drivers of European
climate change, ETH Zürich, https://doi.org/10.3929/ethz-a-010793497,
2016. a
Kröner, N., Kotlarski, S., Fischer, E., Lüthi, D., Zubler, E., and
Schär, C.: Separating climate change signals into thermodynamic,
lapse-rate and circulation effects: theory and application to the European
summer climate, Clim. Dynam., 48, 3425–3440,
https://doi.org/10.1007/s00382-016-3276-3, 2017. a
Lanzante, J. R., Dixon, K. W., Nath, M. J., Whitlock, C. E., and Adams-Smith,
D.: Some Pitfalls in Statistical Downscaling of Future Climate, B. Am. Meteorol. Soc., 99, 791–803,
https://doi.org/10.1175/BAMS-D-17-0046.1, 2018. a
Lenderink, G. and van Meijgaard, E.: Increase in hourly precipitation
extremes beyond expectations from temperature changes, Nat. Geosci., 1, 511–514, https://doi.org/10.1038/ngeo262, 2008. a
Lenderink, G., Barbero, R., Loriaux, J. M., and Fowler, H. J.:
Super-Clausius-Clapeyron scaling of extreme hourly convective precipitation
and its relation to large-scale atmospheric conditions, J. Climate,
30, 6037–6052, https://doi.org/10.1175/JCLI-D-16-0808.1, 2017. a
Le Roux, R., Katurji, M., Zawar-Reza, P., Quénol, H., and Sturman, A.:
Comparison of statistical and dynamical downscaling results from the WRF
model, Environ. Modell. Softw., 100, 67–73,
https://doi.org/10.1016/j.envsoft.2017.11.002, 2018. a
Li, J., Johnson, F., Evans, J., and Sharma, A.: A comparison of methods to
estimate future sub-daily design rainfall, Adv. Water Resour., 110,
215–227, https://doi.org/10.1016/j.advwatres.2017.10.020, 2017. a
Manola, I., van den Hurk, B., De Moel, H., and Aerts, J. C. J. H.: Future extreme precipitation intensities based on a historic event, Hydrol. Earth Syst. Sci., 22, 3777–3788, https://doi.org/10.5194/hess-22-3777-2018, 2018. a, b, c
Maraun, D.: Bias Correcting Climate Change Simulations – a Critical Review, Current Climate Change Reports, 2, 211–220, https://doi.org/10.1007/s40641-016-0050-x, 2016. a
Maraun, D. and Widmann, M.: Statistical Downscaling and Bias Correction for
Climate Research, Cambridge University Press, https://doi.org/10.1017/9781107588783,
2018. a, b, c
Maraun, D., Wetterhall, F., 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
developements to bridge the gap between dynamical models and the end user,
Rev. Geophys., 48, 1–38, https://doi.org/10.1029/2009RG000314,
2010. a, b, c
Maraun, D., Widmann, M., and Gutiérrez, J. M.: Statistical downscaling
skill under present climate conditions: A synthesis of the VALUE perfect
predictor experiment, Int. J. Climatol., 39, 3692–3703,
https://doi.org/10.1002/joc.5877, 2018. a
Mehrotra, R. and Sharma, A.: A Resampling Approach for Correcting Systematic
Spatiotemporal Biases for Multiple Variables in a Changing Climate, Water
Resour. Res., 55, 754–770, https://doi.org/10.1029/2018WR023270, 2019. a, b
Mendoza, P. A., Mizukami, N., Ikeda, K., Clark, M. P., Gutmann, E. D., Arnold,
J. R., Brekke, L. D., and Rajagopalan, B.: Effects of different regional
climate model resolution and forcing scales on projected hydrologic changes,
J. Hydrol., 541, 1003–1019, https://doi.org/10.1016/j.jhydrol.2016.08.010,
2016. a
Merkenschlager, C., Hertig, E., and Jacobeit, J.: Non-stationarities in the
relationships of heavy precipitation events in the Mediterranean area and the
large-scale circulation in the second half of the 20th century, Global
Planet. Change, 151, 108–121, https://doi.org/10.1016/j.gloplacha.2016.10.009,
2017. a
Ntegeka, V. and Willems, P.: Trends and multidecadal oscillations in rainfall
extremes, based on a more than 100-year time series of 10 min rainfall
intensities at Uccle, Belgium, Water Resour. Res., 44, 1–15,
https://doi.org/10.1029/2007WR006471, 2008. a, b
Otero, N., Sillmann, J., and Butler, T.: Assessment of an extended version of the Jenkinson–Collison classification on CMIP5 models over Europe, Clim. Dynam., 50, 1559–1579, https://doi.org/10.1007/s00382-017-3705-y, 2018. a, b, c
Philipp, A., Beck, C., Huth, R., and Jacobeit, J.: Development and comparison of circulation type classifications using the COST 733 dataset and software, Int. J. Climatol., 36, 2673–2691, https://doi.org/10.1002/joc.3920,
2016. a
Pithan, F., Shepherd, T. G., Zappa, G., and Sandu, I.: Climate model biases in
jet streams, blocking and storm tracks resulting from missing orographic
drag, Geophys. Res. Lett., 43, 7231–7240,
https://doi.org/10.1002/2016GL069551, 2016. a
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., Van Lipzig, N. P., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475,
2015. a
Roberts, D. R., Wood, W. H., and Marshall, S. J.: Assessments of downscaled
climate data with a high-resolution weather station network, Int.
J. Climatol., 39, 3091–3103, https://doi.org/10.1002/joc.6005, 2019. a
Rybka, H. and Tost, H.: Uncertainties in future climate predictions due to convection parameterisations, Atmos. Chem. Phys., 14, 5561–5576, https://doi.org/10.5194/acp-14-5561-2014, 2014. a
Sachindra, D. A., Ahmed, K., Shahid, S., and Perera, B. J. C.: Cautionary note on the use of genetic programming in statistical downscaling, Int.
J. Climatol., 38, 3449–3465, https://doi.org/10.1002/joc.5508, 2018. a
Salvadore, E., Bronders, J., and Batelaan, O.: Hydrological modelling of
urbanized catchments: A review and future directions, J. Hydrol.,
529, 62–81, https://doi.org/10.1016/j.jhydrol.2015.06.028, 2015. a
Salvi, K., Ghosh, S., and Ganguly, A. R.: Credibility of statistical
downscaling under nonstationary climate, Clim. Dynam., 46, 1991–2023,
https://doi.org/10.1007/s00382-015-2688-9, 2016. a, b
Sanderson, B. M., Wehner, M., and Knutti, R.: Skill and independence weighting for multi-model assessments, Geosci. Model Dev., 10, 2379–2395, https://doi.org/10.5194/gmd-10-2379-2017, 2017. a
Santos, J. A., Belo-Pereira, M., Fraga, H., and Pinto, J. G.: Understanding
climate change projections for precipitation over western Europe with a
weather typing approach, J. Geophys. Res.-Atmos., 121,
1170–1189, https://doi.org/10.1002/2015JD024399, 2016. a, b
Scaife, A. A., Copsey, D., Gordon, C., Harris, C., Hinton, T., Keeley, S.,
O'Neill, A., Roberts, M., and Williams, K.: Improved Atlantic winter blocking
in a climate model, Geophys. Res. Lett., 38, L23703,
https://doi.org/10.1029/2011GL049573, 2011. a
Schiemann, R. and Frei, C.: How to quantify the resolution of surface climate by circulation types: An example for Alpine precipitation, Phys.
Chem. Earth, 35, 403–410, https://doi.org/10.1016/j.pce.2009.09.005, 2010. a
Schoof, J. T.: Statistical Downscaling in Climatology, Geography Compass, 7,
249–265, https://doi.org/10.1111/gec3.12036, 2013. a, b
Shepherd, T. G., Boyd, E., Calel, R. A., Chapman, S. C., Dessai, S., Dima-West,
I. M., Fowler, H. J., James, R., Maraun, D., Martius, O., Senior, C. A.,
Sobel, A. H., Stainforth, D. A., Tett, S. F. B., Trenberth, K. E., van den
Hurk, B. J. J. M., Watkins, N. W., Wilby, R. L., and Zenghelis, D. A.:
Storylines: an alternative approach to representing uncertainty in physical
aspects of climate change, Climatic Change, 151, 555–571,
https://doi.org/10.1007/s10584-018-2317-9, 2018. a
Sørup, H. J. D., Davidsen, S., Löwe, R., Thorndahl, S. L., Borup, M., and Arnbjerg-Nielsen, K.: Evaluating catchment response to artificial
rainfall from four weather generators for present and future climate, Water
Sci. Technol., 77, 2578–2588, https://doi.org/10.2166/wst.2018.217, 2018. a
Souverijns, N., Thiery, W., Demuzere, M., and Lipzig, N. P. M. V.: Drivers of
future changes in East African precipitation Drivers of future changes in
East African precipitation, Environ. Res. Lett., 11, 1–9,
https://doi.org/10.1088/1748-9326/11/11/114011, 2016. a
Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J.,
Nauels, A., Xia, Y., Bex, V., and Midgley, P.: Summary for Policymakers, book
section SPM, Cambridge University Press, Cambridge, UK
and New York, NY, USA, 1–30, https://doi.org/10.1017/CBO9781107415324.004, 2013. a
Stryhal, J. and Huth, R.: Classifications of winter Euro-Atlantic circulation
patterns: An intercomparison of five atmospheric reanalyses, J.
Climate, 30, 7847–7861, https://doi.org/10.1175/JCLI-D-17-0059.1, 2017. a
Stryhal, J. and Huth, R.: Classifications of winter atmospheric circulation
patterns: validation of CMIP5 GCMs over Europe and the North Atlantic,
Clim. Dynam., 52, 3575–3598, https://doi.org/10.1007/s00382-018-4344-7, 2018. a, b
Stryhal, J. and Huth, R.: Trends in winter circulation over the British Isles
and central Europe in twenty-first century projections by 25 CMIP5 GCMs,
Clim. Dynam., 52, 1063–1075, https://doi.org/10.1007/s00382-018-4178-3, 2019. a, b
Sunyer, M. A., Hundecha, Y., Lawrence, D., Madsen, H., Willems, P., Martinkova, M., Vormoor, K., Bürger, G., Hanel, M., Kriaučiūnienė, J., Loukas, A., Osuch, M., and Yücel, I.: Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe, Hydrol. Earth Syst. Sci., 19, 1827–1847, https://doi.org/10.5194/hess-19-1827-2015, 2015. a, b
Tabari, H. and Willems, P.: Lagged influence of Atlantic and Pacific climate
patterns on European extreme precipitation, Sci. Rep., 8, 5748,
https://doi.org/10.1038/s41598-018-24069-9, 2018. a, b
Tabari, H., De Troch, R., Giot, O., Hamdi, R., Termonia, P., Saeed, S., Brisson, E., Van Lipzig, N., and Willems, P.: Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?, Hydrol. Earth Syst. Sci., 20, 3843–3857, https://doi.org/10.5194/hess-20-3843-2016, 2016. a, b, c
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the experiment design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012 (data available at: https://esgf.llnl.gov/, last access: 10 May 2020). a
Termonia, P., Van Schaeybroeck, B., De Cruz, L., De Troch, R.,
Caluwaerts, S., Giot, O., Hamdi, R., Vannitsem, S., Duchêne, F.,
Willems, P., Tabari, H., Van Uytven, E., Hosseinzadehtalaei, P., Van
Lipzig, N., Wouters, H., Vanden Broucke, S., van Ypersele, J. P., Marbaix,
P., Villanueva-Birriel, C., Fettweis, X., Wyard, C., Scholzen, C.,
Doutreloup, S., De Ridder, K., Gobin, A., Lauwaet, D., Stavrakou, T.,
Bauwens, M., Müller, J. F., Luyten, P., Ponsar, S., Van den Eynde,
D., and Pottiaux, E.: The CORDEX.be initiative as a foundation for climate
services in Belgium, Climate Services, 11, 49–61, https://doi.org/10.1016/j.cliser.2018.05.001,
2018. a, b
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., 456–457, 12–29,
https://doi.org/10.1016/j.jhydrol.2012.05.052, 2012. a
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., 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., 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. Meteor. Soc., 131,
2961–3012, https://doi.org/10.1256/qj.04.176, 2005 (data available at: http://apps.ecmwf.int/datasets/, last access: 10 May 2020). a, b
Vaittinada Ayar, P., Vrac, M., Bastin, S., Carreau, J., Déqué,
M., and Gallardo, C.: Intercomparison of statistical and dynamical
downscaling models under the EURO- and MED-CORDEX initiative framework:
present climate evaluations, Clim. Dynam., 46, 1301–1329,
https://doi.org/10.1007/s00382-015-2647-5, 2016. a, b
Vanden Broucke, S., Wouters, H., Demuzere, M., and van Lipzig, N. P. M.: The
influence of convection-permitting regional climate modeling on future
projections of extreme precipitation: dependency on topography and
timescale, Clim. Dynam., 52, 5303–5324, https://doi.org/10.1007/s00382-018-4454-2, 2018. a
Van de Vyver, H., Van Schaeybroeck, B., De Troch, R., Hamdi, R., and Termonia,
P.: Modeling the scaling of short-duration precipitation extremes with
temperature, Earth and Space Science, 6, 2031–2041, https://doi.org/10.1029/2019EA000665, 2019. a, b, c, d
Vansteenkiste, T., Tavakoli, M., Ntegeka, V., Smedt, F. D., Batelaan, O.,
Pereira, F., and Willems, P.: Intercomparison of hydrological model
structures and calibration approaches in climate scenario impact projections,
J. Hydrol., 519, 743–755,
https://doi.org/10.1016/j.jhydrol.2014.07.062, 2014. a
Van Uytven, E. and Willems, P.: Greenhouse gas scenario sensitivity and
uncertainties in precipitation projections for central Belgium, J.
Hydrol., 558, 9–19, https://doi.org/10.1016/j.jhydrol.2018.01.018, 2018. a, b
Wang, L., Ranasinghe, R., Maskey, S., van Gelder, P. H. A. J. M., and Vrijling,
J. K.: Comparison of empirical statistical methods for downscaling daily
climate projections from CMIP5 GCMs: A case study of the Huai River Basin,
China, Int. J. Climatol., 36, 145–164,
https://doi.org/10.1002/joc.4334, 2016. a
Wang, Y., Sivandran, G., and Bielicki, J. M.: The stationarity of two
statistical downscaling methods for precipitation under different choices of
cross-validation periods, Int. J. Climatol., 38,
e330–e348, https://doi.org/10.1002/joc.5375, 2018. a
Wasko, C., Lu, W. T., and Mehrotra, R.: Relationship of extreme precipitation,
dry-bulb temperature, and dew point temperature across Australia,
Environ. Res. Lett., 13, 074031, https://doi.org/10.1088/1748-9326/aad135, 2018. a, b
Watterson, I. G., Bathols, J., and Heady, C.: What influences the skill of
climate models over the continents?, B. Am. Meteorol.
Soc., 95, 689–700, https://doi.org/10.1175/BAMS-D-12-00136.1, 2014. a
Werner, A. T. and Cannon, A. J.: Hydrologic extremes – an intercomparison of multiple gridded statistical downscaling methods, Hydrol. Earth Syst. Sci., 20, 1483–1508, https://doi.org/10.5194/hess-20-1483-2016, 2016. a
Widmann, M., Bedia, J., Gutiérrez, J. M., Bosshard, T., Hertig, E., Maraun,
D., Casado, M. J., Ramos, P., Cardoso, R. M., Soares, P. M. M., Ribalaygua,
J., Pagé, C., Fischer, A. M., Herrera, S., and Huth, R.: Validation of
spatial variability in downscaling results from the VALUE perfect predictor
experiment, Int. J. Climatol., 39, 3819–3845,
https://doi.org/10.1002/joc.6024, 2019. a
Wilby, R. L. and Wigley, T. M. L.: Precipitation predictors for downscaling:
Oberserved and General Circulation Model relationships, Int. J. Climatol.,
20, 641–661, https://doi.org/10.1002/(Sici)1097-0088(200005)20:6<641::Aid-Joc501>3.0.Co;2-1, 2000. a
Willems, P.: Compound intensity/duration/frequency-relationships of
extreme precipitation for two seasons and two storm types, J.
Hydrol., 233, 189–205, 2000. a
Willems, P.: Multidecadal oscillatory behaviour of rainfall extremes in
Europe, Climatic Change, 120, 931–944, https://doi.org/10.1007/s10584-013-0837-x,
2013a.
a, b, c
Willems, P.: Revision of urban drainage design rules after assessment of
climate change impacts on precipitation extremes at Uccle, Belgium, J. Hydrolo., 496, 166–177, https://doi.org/10.1016/j.jhydrol.2013.05.037,
2013b. a
Willems, P. and Vrac, M.: Statistical precipitation downscaling for
small-scale hydrological impact investigations of climate change, J.
Hydrol., 402, 193–205, https://doi.org/10.1016/j.jhydrol.2011.02.030, 2011. a, b, c
Woollings, T., Barriopedro, D., Methven, J., Son, S.-W., Martius, O., Harvey,
B., Sillmann, J., Lupo, A. R., and Seneviratne, S.: Blocking and its Response
to Climate Change, Current Climate Change Reports, 4, 287–300,
https://doi.org/10.1007/s40641-018-0108-z, 2018. a, b
Wootten, A., Terando, A., Reich, B. J., Boyles, R. P., and Semazzi, F.:
Characterizing sources of uncertainty from global climate models and
downscaling techniques, J. Appl. Meteorol. Clim., 56,
3245–3262, https://doi.org/10.1175/JAMC-D-17-0087.1, 2017. a
Yang, C., Wang, N., and Wang, S.: A comparison of three predictor selection
methods for statistical downscaling, Int. J. Climatol.,
37, 1238–1249, https://doi.org/10.1002/joc.4772, 2017. a
Yang, Y., Tang, J., Xiong, Z., Wang, S., and Yuan, J.: An intercomparison of
multiple statistical downscaling methods for daily precipitation and
temperature over China: present climate evaluations, Clim. Dynam., 53, 4629–4649,
https://doi.org/10.1007/s00382-019-04809-x, 2019. a
Zappa, G., Masato, G., Shaffrey, L., Woollings, T., and Hodges, K.: Linking
Northern Hemisphere blocking and storm track biases in the CMIP5 climate
models, Geophys. Res. Lett., 41, 135–139,
https://doi.org/10.1002/2013GL058480, 2014. a
Zhang, X., Zwiers, F. W., Li, G., Wan, H., and Cannon, A. J.: Complexity in
estimating past and future extreme short-duration rainfall, Nat.
Geosci., 10, 255–259, https://doi.org/10.1038/ngeo2911, 2017. a, b
Short summary
In recent years many methods have been developed for the statistical downscaling of climate model outputs. Each statistical downscaling method has strengths and limitations, but those are rarely evaluated. This paper illustrates an approach to evaluating the skill of statistical downscaling methods for the specific purpose of impact analysis in hydrology.
In recent years many methods have been developed for the statistical downscaling of climate...
