Articles | Volume 23, issue 2
https://doi.org/10.5194/hess-23-773-2019
© Author(s) 2019. 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-23-773-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Feb 2019
Research article |
| 12 Feb 2019
| 12 Feb 2019
Multivariate stochastic bias corrections with optimal transport
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212,
CEA-CNRS-UVSQ, IPSL & U Paris-Saclay, Gif-sur-Yvette, France
Mathieu Vrac
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212,
CEA-CNRS-UVSQ, IPSL & U Paris-Saclay, Gif-sur-Yvette, France
Philippe Naveau
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212,
CEA-CNRS-UVSQ, IPSL & U Paris-Saclay, Gif-sur-Yvette, France
Pascal Yiou
Laboratoire des Sciences du Climat et de l'Environnement, UMR 8212,
CEA-CNRS-UVSQ, IPSL & U Paris-Saclay, Gif-sur-Yvette, France
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Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
Yoann Robin and Aurélien Ribes
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We propose a multivariate bias correction (MBC) method to adjust the spatial and/or inter-variable properties of climate simulations, while also accounting for their temporal dependences (e.g., autocorrelations).
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Existing approaches to quantify the emergence of climate change require several user choices that make these approaches less objective. We present an approach that uses a minimum number of choices and showcase its application in the extremely sensitive, permafrost-dominated region of eastern Siberia. Designed as a Python toolbox, it allows for incorporating climate model, reanalysis, and in situ data to make use of numerous existing data sources and reduce uncertainties in obtained estimates.
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
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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.
Florentin Breton, Mathieu Vrac, Pascal Yiou, Pradeebane Vaittinada Ayar, and Aglaé Jézéquel
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-26, https://doi.org/10.5194/esd-2020-26, 2020
Revised manuscript not accepted
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We investigate North Atlantic weather seasonality over 1979–2100 by classifying year-round fields of 500 hPa geopotential height from one reanalysis dataset and 12 climate models. Generally, models have seasonal structures similar to the reanalyses. Historical winter (summer) conditions decrease (increase), due to uniform Z500 increase (i.e. uniform warming). However, relative to the increasing Z500 seasonal cycle, future seasonality (spatial patterns, seasonal cycle) appears almost stationary.
Pascal Yiou and Aglaé Jézéquel
Geosci. Model Dev., 13, 763–781, https://doi.org/10.5194/gmd-13-763-2020, https://doi.org/10.5194/gmd-13-763-2020, 2020
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This paper presents an adaptation of a method of "importance sampling" to simulate large ensembles of extreme heat waves (i.e., the most extreme heat waves that could be), given a fixed returned period. We illustrate how this algorithm works for European heat waves and investigate the atmospheric features of such ensembles of events. We argue that such an algorithm can be used to simulate other types of events, including cold spells or prolonged episodes of precipitation.
Giulia Carella, Mathieu Vrac, Hélène Brogniez, Pascal Yiou, and Hélène Chepfer
Earth Syst. Sci. Data, 12, 1–20, https://doi.org/10.5194/essd-12-1-2020, https://doi.org/10.5194/essd-12-1-2020, 2020
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Observations of relative humidity for ice clouds over the tropical oceans from a passive microwave sounder are downscaled by incorporating the high-resolution variability derived from simultaneous co-located cloud profiles from a lidar. By providing a method to generate pseudo-observations of relative humidity at high spatial resolution, this work will help revisit some of the current key barriers in atmospheric science.
Anna Denvil-Sommer, Marion Gehlen, Mathieu Vrac, and Carlos Mejia
Geosci. Model Dev., 12, 2091–2105, https://doi.org/10.5194/gmd-12-2091-2019, https://doi.org/10.5194/gmd-12-2091-2019, 2019
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This work is dedicated to a new model that reconstructs the surface ocean partial pressure of carbon dioxide (pCO2) over the global ocean on a monthly 1°×1° grid. The model is based on a feed-forward neural network and represents the nonlinear relationships between pCO2 and the ocean drivers. Reconstructed pCO2 has a satisfying accuracy compared to independent observational data and shows a good agreement in seasonal and interannual variability with three existing mapping methods.
Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, https://doi.org/10.5194/esd-10-271-2019, 2019
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The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Pascal Yiou and Céline Déandréis
Geosci. Model Dev., 12, 723–734, https://doi.org/10.5194/gmd-12-723-2019, https://doi.org/10.5194/gmd-12-723-2019, 2019
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We devised a system that simulates large ensembles of forecasts for European temperatures and the North Atlantic Oscillation index. This system is based on a stochastic weather generator that samples analogs of SLP. This paper provides statistical tests of temperature and NAO forecasts for timescales of days to months. We argue that the forecast skill of the system is significantly positive and could be used as a baseline for numerical weather forecast.
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
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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.
Claire Waelbroeck, Sylvain Pichat, Evelyn Böhm, Bryan C. Lougheed, Davide Faranda, Mathieu Vrac, Lise Missiaen, Natalia Vazquez Riveiros, Pierre Burckel, Jörg Lippold, Helge W. Arz, Trond Dokken, François Thil, and Arnaud Dapoigny
Clim. Past, 14, 1315–1330, https://doi.org/10.5194/cp-14-1315-2018, https://doi.org/10.5194/cp-14-1315-2018, 2018
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Recording the precise timing and sequence of events is essential for understanding rapid climate changes and improving climate model predictive skills. Here, we precisely assess the relative timing between ocean and atmospheric changes, both recorded in the same deep-sea core over the last 45 kyr. We show that decreased mid-depth water mass transport in the western equatorial Atlantic preceded increased rainfall over the adjacent continent by 120 to 980 yr, depending on the type of climate event.
Guillaume Latombe, Ariane Burke, Mathieu Vrac, Guillaume Levavasseur, Christophe Dumas, Masa Kageyama, and Gilles Ramstein
Geosci. Model Dev., 11, 2563–2579, https://doi.org/10.5194/gmd-11-2563-2018, https://doi.org/10.5194/gmd-11-2563-2018, 2018
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It is still unclear how climate conditions, and especially climate variability, influenced the spatial distribution of past human populations. Global climate models (GCMs) cannot simulate climate at sufficiently fine scale for this purpose. We propose a statistical method to obtain fine-scale climate projections for 15 000 years ago from coarse-scale GCM outputs. Our method agrees with local reconstructions from fossil and pollen data, and generates sensible climate variability maps over Europe.
Mathieu Vrac
Hydrol. Earth Syst. Sci., 22, 3175–3196, https://doi.org/10.5194/hess-22-3175-2018, https://doi.org/10.5194/hess-22-3175-2018, 2018
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This study presents a multivariate bias correction method named R2D2 to adjust both the 1d-distributions and inter-variable/site dependence structures of climate simulations in a high-dimensional context, while providing some stochasticity. R2D2 is tested on temperature and precipitation reanalyses and illustrated on future simulations. In both cases, R2D2 is able to correct the spatial and physical dependence, opening proper use of climate simulations for impact (e.g. hydrological) models.
Adjoua Moise Famien, Serge Janicot, Abe Delfin Ochou, Mathieu Vrac, Dimitri Defrance, Benjamin Sultan, and Thomas Noël
Earth Syst. Dynam., 9, 313–338, https://doi.org/10.5194/esd-9-313-2018, https://doi.org/10.5194/esd-9-313-2018, 2018
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This study uses the cumulative distribution function transform (CDF-t) method to provide bias-corrected data over Africa using WFDEI as a reference dataset. It is shown that CDF-t is very effective in removing the biases and reducing the high inter-GCM scattering. Differences with other bias-corrected GCM data are mainly due to the differences among the reference datasets, particularly for surface downwelling shortwave radiation, which has a significant impact in terms of simulated maize yields.
Yoann Robin, Pascal Yiou, and Philippe Naveau
Nonlin. Processes Geophys., 24, 393–405, https://doi.org/10.5194/npg-24-393-2017, https://doi.org/10.5194/npg-24-393-2017, 2017
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If climate is viewed as a chaotic dynamical system, its trajectories yield on an object called an attractor. Being perturbed by an external forcing, this attractor could be modified. With Wasserstein distance, we estimate on a derived Lorenz model the impact of a forcing similar to climate change. Our approach appears to work with small data sizes. We have obtained a methodology quantifying the deformation of well-known attractors, coherent with the size of data available.
Emanuele Bevacqua, Douglas Maraun, Ingrid Hobæk Haff, Martin Widmann, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, https://doi.org/10.5194/hess-21-2701-2017, 2017
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We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme impacts to society which are driven by statistically dependent climatic variables. Based on this model we study compound floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model includes meteorological predictors which (1) provide insight into the physical processes underlying CEs, as well as into the temporal variability, and (2) allow us to statistically downscale CEs.
Pascal Yiou, Aglaé Jézéquel, Philippe Naveau, Frederike E. L. Otto, Robert Vautard, and Mathieu Vrac
Adv. Stat. Clim. Meteorol. Oceanogr., 3, 17–31, https://doi.org/10.5194/ascmo-3-17-2017, https://doi.org/10.5194/ascmo-3-17-2017, 2017
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The attribution of classes of extreme events, such as heavy precipitation or heatwaves, relies on the estimate of small probabilities (with and without climate change). Such events are connected to the large-scale atmospheric circulation. This paper links such probabilities with properties of the atmospheric circulation by using a Bayesian decomposition. We test this decomposition on a case of extreme precipitation in the UK, in January 2014.
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
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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.
Allison H. Baker, Dorit M. Hammerling, Sheri A. Mickelson, Haiying Xu, Martin B. Stolpe, Phillipe Naveau, Ben Sanderson, Imme Ebert-Uphoff, Savini Samarasinghe, Francesco De Simone, Francesco Carbone, Christian N. Gencarelli, John M. Dennis, Jennifer E. Kay, and Peter Lindstrom
Geosci. Model Dev., 9, 4381–4403, https://doi.org/10.5194/gmd-9-4381-2016, https://doi.org/10.5194/gmd-9-4381-2016, 2016
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We apply lossy data compression to output from the Community Earth System Model Large Ensemble Community Project. We challenge climate scientists to examine features of the data relevant to their interests and identify which of the ensemble members have been compressed, and we perform direct comparisons on features critical to climate science. We find that applying lossy data compression to climate model data effectively reduces data volumes with minimal effect on scientific results.
Jérôme Pernin, Mathieu Vrac, Cyril Crevoisier, and Alain Chédin
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 115–136, https://doi.org/10.5194/ascmo-2-115-2016, https://doi.org/10.5194/ascmo-2-115-2016, 2016
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Here, we propose a classification methodology of various space-time atmospheric datasets into discrete air mass groups homogeneous in temperature and humidity through a probabilistic point of view: both the classification process and the data are probabilistic. Unlike conventional classification algorithms, this methodology provides the probability of belonging to each class as well as the corresponding uncertainty, which can be used in various applications.
Benjamin Grouillet, Denis Ruelland, Pradeebane Vaittinada Ayar, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 20, 1031–1047, https://doi.org/10.5194/hess-20-1031-2016, https://doi.org/10.5194/hess-20-1031-2016, 2016
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This original paper provides a guideline to select statistical downscaling methods (SDMs) in climate change impact studies (CCIS) to minimize uncertainty from downscaling. Three SDMs were applied to NCEP reanalysis and 2 GCM data values. We then analyzed the sensitivity of the hydrological model to the various downscaled data via 5 hydrological indicators representing the main features of the hydrograph. Our results enable selection of the appropriate SDMs to be used to build climate scenarios.
M.-S. Deroche, M. Choux, F. Codron, and P. Yiou
Nat. Hazards Earth Syst. Sci., 14, 981–993, https://doi.org/10.5194/nhess-14-981-2014, https://doi.org/10.5194/nhess-14-981-2014, 2014
P. Yiou, M. Boichu, R. Vautard, M. Vrac, S. Jourdain, E. Garnier, F. Fluteau, and L. Menut
Clim. Past, 10, 797–809, https://doi.org/10.5194/cp-10-797-2014, https://doi.org/10.5194/cp-10-797-2014, 2014
P. Yiou
Geosci. Model Dev., 7, 531–543, https://doi.org/10.5194/gmd-7-531-2014, https://doi.org/10.5194/gmd-7-531-2014, 2014
G. A. Schmidt, J. D. Annan, P. J. Bartlein, B. I. Cook, E. Guilyardi, J. C. Hargreaves, S. P. Harrison, M. Kageyama, A. N. LeGrande, B. Konecky, S. Lovejoy, M. E. Mann, V. Masson-Delmotte, C. Risi, D. Thompson, A. Timmermann, L.-B. Tremblay, and P. Yiou
Clim. Past, 10, 221–250, https://doi.org/10.5194/cp-10-221-2014, https://doi.org/10.5194/cp-10-221-2014, 2014
Related subject area
Subject: Global hydrology | Techniques and Approaches: Theory development
Estimating the sensitivity of the Priestley–Taylor coefficient to air temperature and humidity
A hydrologist's guide to open science
From mythology to science: the development of scientific hydrological concepts in Greek antiquity and its relevance to modern hydrology
Comment on: “A review of the complementary principle of evaporation: from the original linear relationship to generalized nonlinear functions” by Han and Tian (2020)
Global distribution of hydrologic controls on forest growth
Inter-annual variability of the global terrestrial water cycle
Using R in hydrology: a review of recent developments and future directions
A simple tool for refining GCM water availability projections, applied to Chinese catchments
Necessary storage as a signature of discharge variability: towards global maps
Should seasonal rainfall forecasts be used for flood preparedness?
Hydroclimatic variability and predictability: a survey of recent research
HESS Opinions: A planetary boundary on freshwater use is misleading
Controls on hydrologic drought duration in near-natural streamflow in Europe and the USA
Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches
Action-based flood forecasting for triggering humanitarian action
Improving together: better science writing through peer learning
A two-parameter Budyko function to represent conditions under which evapotranspiration exceeds precipitation
Hydrological recurrence as a measure for large river basin classification and process understanding
Storm type effects on super Clausius–Clapeyron scaling of intense rainstorm properties with air temperature
Accounting for environmental flow requirements in global water assessments
Hydroclimatic regimes: a distributed water-balance framework for hydrologic assessment, classification, and management
HESS Opinions "A perspective on isotope versus non-isotope approaches to determine the contribution of transpiration to total evaporation"
Estimates of the climatological land surface energy and water balance derived from maximum convective power
A general framework for understanding the response of the water cycle to global warming over land and ocean
A physically based approach for the estimation of root-zone soil moisture from surface measurements
Globalization of agricultural pollution due to international trade
Data-driven scale extrapolation: estimating yearly discharge for a large region by small sub-basins
Hydrologic benchmarking of meteorological drought indices at interannual to climate change timescales: a case study over the Amazon and Mississippi river basins
A worldwide analysis of trends in water-balance evapotranspiration
Thermodynamic limits of hydrologic cycling within the Earth system: concepts, estimates and implications
Hydrological drought across the world: impact of climate and physical catchment structure
Global hydrobelts and hydroregions: improved reporting scale for water-related issues?
Evaluation of water-energy balance frameworks to predict the sensitivity of streamflow to climate change
Technical note: Towards a continuous classification of climate using bivariate colour mapping
Recycling of moisture in Europe: contribution of evaporation to variability in very wet and dry years
Ziwei Liu, Hanbo Yang, Changming Li, and Taihua Wang
Hydrol. Earth Syst. Sci., 28, 4349–4360, https://doi.org/10.5194/hess-28-4349-2024, https://doi.org/10.5194/hess-28-4349-2024, 2024
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The determination of the coefficient α in the Priestley–Taylor equation is empirical. Based on an atmospheric boundary layer model, we derived a physically clear and parameter-free expression to investigate the behavior of α. We showed that the temperature dominates changes in α and emphasized that the variation of α with temperature should be considered for long-term hydrological predictions. Our works advance and promote the most classical models in the field.
Caitlyn A. Hall, Sheila M. Saia, Andrea L. Popp, Nilay Dogulu, Stanislaus J. Schymanski, Niels Drost, Tim van Emmerik, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 647–664, https://doi.org/10.5194/hess-26-647-2022, https://doi.org/10.5194/hess-26-647-2022, 2022
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Impactful open, accessible, reusable, and reproducible hydrologic research practices are being embraced by individuals and the community, but taking the plunge can seem overwhelming. We present the Open Hydrology Principles and Practical Guide to help hydrologists move toward open science, research, and education. We discuss the benefits and how hydrologists can overcome common challenges. We encourage all hydrologists to join the open science community (https://open-hydrology.github.io).
Demetris Koutsoyiannis and Nikos Mamassis
Hydrol. Earth Syst. Sci., 25, 2419–2444, https://doi.org/10.5194/hess-25-2419-2021, https://doi.org/10.5194/hess-25-2419-2021, 2021
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This paper is the result of new research of ancient and early modern sources about the developments of the concept of the hydrological cycle and of hydrology in general. It shows that the flooding of the Nile was the first geophysical problem formulated in scientific terms in the cradle of natural philosophy and science in the 6th century BC. Aristotle was able to find the correct solution to the problem, which he tested through what it appears to be the first scientific expedition in history.
Richard D. Crago, Jozsef Szilagyi, and Russell Qualls
Hydrol. Earth Syst. Sci., 25, 63–68, https://doi.org/10.5194/hess-25-63-2021, https://doi.org/10.5194/hess-25-63-2021, 2021
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The sigmoid-shaped complementary relationship (CR) for regional evaporation proposed by Han and Tian (2018, 2020) is reconsidered in terms of (1) its ability to give reasonable evaporation results from sites worldwide, (2) evidence for the three-state evaporation process it posits, (3) the validity of the proof provided by Han and Tian (2018), and (4) the relevance of model studies that seem to support it. Arguments for the sigmoid shape deserve to be taken seriously but remain unconvincing.
Caspar T. J. Roebroek, Lieke A. Melsen, Anne J. Hoek van Dijke, Ying Fan, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 24, 4625–4639, https://doi.org/10.5194/hess-24-4625-2020, https://doi.org/10.5194/hess-24-4625-2020, 2020
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Vegetation is a principal component in the Earth system models that are used for weather, climate and other environmental predictions. Water is one of the main drivers of vegetation; however, the global distribution of how water influences vegetation is not well understood. This study looks at spatial patterns of photosynthesis and water sources (rain and groundwater) to obtain a first understanding of water access and limitations for the growth of global forests (proxy for natural vegetation).
Dongqin Yin and Michael L. Roderick
Hydrol. Earth Syst. Sci., 24, 381–396, https://doi.org/10.5194/hess-24-381-2020, https://doi.org/10.5194/hess-24-381-2020, 2020
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We focus on the initial analysis of inter-annual variability in the global terrestrial water cycle, which is key to understanding hydro-climate extremes. We find that (1) the partitioning of inter-annual variability is totally different with the mean state partitioning; (2) the magnitude of covariances can be large and negative, indicating the variability in the sinks can exceed variability in the source; and (3) the partitioning is relevant to the water storage capacity and snow/ice presence.
Louise J. Slater, Guillaume Thirel, Shaun Harrigan, Olivier Delaigue, Alexander Hurley, Abdou Khouakhi, Ilaria Prosdocimi, Claudia Vitolo, and Katie Smith
Hydrol. Earth Syst. Sci., 23, 2939–2963, https://doi.org/10.5194/hess-23-2939-2019, https://doi.org/10.5194/hess-23-2939-2019, 2019
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This paper explores the benefits and advantages of R's usage in hydrology. We provide an overview of a typical hydrological workflow based on reproducible principles and packages for retrieval of hydro-meteorological data, spatial analysis, hydrological modelling, statistics, and the design of static and dynamic visualizations and documents. We discuss some of the challenges that arise when using R in hydrology as well as a roadmap for R’s future within the discipline.
Joe M. Osborne and F. Hugo Lambert
Hydrol. Earth Syst. Sci., 22, 6043–6057, https://doi.org/10.5194/hess-22-6043-2018, https://doi.org/10.5194/hess-22-6043-2018, 2018
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We want to estimate how much water will be available in a river basin (runoff) at the end of the 21st century. Climate models alone are considered unsuitable for this task due to biases in representing the present-day climate. We show that the output from these models can be corrected using a simple mathematical framework. This approach narrows the range of future runoff projections for the Yellow river in China by 34 %. It serves as a quick tool for updating projections from climate models.
Kuniyoshi Takeuchi and Muhammad Masood
Hydrol. Earth Syst. Sci., 21, 4495–4516, https://doi.org/10.5194/hess-21-4495-2017, https://doi.org/10.5194/hess-21-4495-2017, 2017
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There are many global maps of hydrology and water resources, but none on necessary storage to smooth out discharge variability. This paper provides a methodology to create such a map, taking the Ganges–Brahmaputra–Meghna basin as an example. Necessary storage is calculated by a new method, intensity–duration–frequency curves of flood and drought (FDC–DDC). Necessary storage serves as a signature of hydrological variability and its geographical distribution provides new insights for hydrology.
Erin Coughlan de Perez, Elisabeth Stephens, Konstantinos Bischiniotis, Maarten van Aalst, Bart van den Hurk, Simon Mason, Hannah Nissan, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 21, 4517–4524, https://doi.org/10.5194/hess-21-4517-2017, https://doi.org/10.5194/hess-21-4517-2017, 2017
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Disaster managers would like to use seasonal forecasts to anticipate flooding months in advance. However, current seasonal forecasts give information on rainfall instead of flooding. Here, we find that the number of extreme events, rather than total rainfall, is most related to flooding in different regions of Africa. We recommend several forecast adjustments and research opportunities that would improve flood information at the seasonal timescale in different regions.
Randal D. Koster, Alan K. Betts, Paul A. Dirmeyer, Marc Bierkens, Katrina E. Bennett, Stephen J. Déry, Jason P. Evans, Rong Fu, Felipe Hernandez, L. Ruby Leung, Xu Liang, Muhammad Masood, Hubert Savenije, Guiling Wang, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 3777–3798, https://doi.org/10.5194/hess-21-3777-2017, https://doi.org/10.5194/hess-21-3777-2017, 2017
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Large-scale hydrological variability can affect society in profound ways; floods and droughts, for example, often cause major damage and hardship. A recent gathering of hydrologists at a symposium to honor the career of Professor Eric Wood motivates the present survey of recent research on this variability. The surveyed literature and the illustrative examples provided in the paper show that research into hydrological variability continues to be strong, vibrant, and multifaceted.
Maik Heistermann
Hydrol. Earth Syst. Sci., 21, 3455–3461, https://doi.org/10.5194/hess-21-3455-2017, https://doi.org/10.5194/hess-21-3455-2017, 2017
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In 2009, the "planetary boundaries" were introduced. They consist of nine global control variables and corresponding "thresholds which, if crossed, could generate unacceptable environmental change". The idea has been very successful, but also controversial. This paper picks up the debate with regard to the boundary on "global freshwater use": it argues that such a boundary is based on mere speculation, and that any exercise of assigning actual numbers is arbitrary, premature, and misleading.
Erik Tijdeman, Sophie Bachmair, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 20, 4043–4059, https://doi.org/10.5194/hess-20-4043-2016, https://doi.org/10.5194/hess-20-4043-2016, 2016
Anne F. Van Loon, Kerstin Stahl, Giuliano Di Baldassarre, Julian Clark, Sally Rangecroft, Niko Wanders, Tom Gleeson, Albert I. J. M. Van Dijk, Lena M. Tallaksen, Jamie Hannaford, Remko Uijlenhoet, Adriaan J. Teuling, David M. Hannah, Justin Sheffield, Mark Svoboda, Boud Verbeiren, Thorsten Wagener, and Henny A. J. Van Lanen
Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, https://doi.org/10.5194/hess-20-3631-2016, 2016
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In the Anthropocene, drought cannot be viewed as a natural hazard independent of people. Drought can be alleviated or made worse by human activities and drought impacts are dependent on a myriad of factors. In this paper, we identify research gaps and suggest a framework that will allow us to adequately analyse and manage drought in the Anthropocene. We need to focus on attribution of drought to different drivers, linking drought to its impacts, and feedbacks between drought and society.
Erin Coughlan de Perez, Bart van den Hurk, Maarten K. van Aalst, Irene Amuron, Deus Bamanya, Tristan Hauser, Brenden Jongma, Ana Lopez, Simon Mason, Janot Mendler de Suarez, Florian Pappenberger, Alexandra Rueth, Elisabeth Stephens, Pablo Suarez, Jurjen Wagemaker, and Ervin Zsoter
Hydrol. Earth Syst. Sci., 20, 3549–3560, https://doi.org/10.5194/hess-20-3549-2016, https://doi.org/10.5194/hess-20-3549-2016, 2016
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Many flood disaster impacts could be avoided by preventative action; however, early action is not guaranteed. This article demonstrates the design of a new system of forecast-based financing, which automatically triggers action when a flood forecast arrives, before a potential disaster. We establish "action triggers" for northern Uganda based on a global flood forecasting system, verifying these forecasts and assessing the uncertainties inherent in setting a trigger in a data-scarce location.
Mathew A. Stiller-Reeve, Céline Heuzé, William T. Ball, Rachel H. White, Gabriele Messori, Karin van der Wiel, Iselin Medhaug, Annemarie H. Eckes, Amee O'Callaghan, Mike J. Newland, Sian R. Williams, Matthew Kasoar, Hella Elisa Wittmeier, and Valerie Kumer
Hydrol. Earth Syst. Sci., 20, 2965–2973, https://doi.org/10.5194/hess-20-2965-2016, https://doi.org/10.5194/hess-20-2965-2016, 2016
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Scientific writing must improve and the key to long-term improvement of scientific writing lies with the early-career scientist (ECS). We introduce the ClimateSnack project, which aims to motivate ECSs to start writing groups around the world to improve their skills together. Writing groups offer many benefits but can be a challenge to keep going. Several ClimateSnack writing groups formed, and this paper examines why some of the groups flourished and others dissolved.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
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The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
R. Fernandez and T. Sayama
Hydrol. Earth Syst. Sci., 19, 1919–1942, https://doi.org/10.5194/hess-19-1919-2015, https://doi.org/10.5194/hess-19-1919-2015, 2015
P. Molnar, S. Fatichi, L. Gaál, J. Szolgay, and P. Burlando
Hydrol. Earth Syst. Sci., 19, 1753–1766, https://doi.org/10.5194/hess-19-1753-2015, https://doi.org/10.5194/hess-19-1753-2015, 2015
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We present an empirical study of the rates of increase in precipitation intensity with air temperature using high-resolution 10 min precipitation records in Switzerland. We estimated the scaling rates for lightning (convective) and non-lightning event subsets and show that scaling rates are between 7 and 14%/C for convective rain and that mixing of storm types exaggerates the relations to air temperature. Doubled CC rates reported by other studies are an exception in our data set.
A. V. Pastor, F. Ludwig, H. Biemans, H. Hoff, and P. Kabat
Hydrol. Earth Syst. Sci., 18, 5041–5059, https://doi.org/10.5194/hess-18-5041-2014, https://doi.org/10.5194/hess-18-5041-2014, 2014
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Freshwater ecosystems encompass the most threatened species on earth. Environmental flow requirements need to be addressed globally to provide sufficient water for humans and nature. We present a comparison of five environmental flow methods validated with locally calculated EFRs. We showed that methods based on monthly average flow such as the variable monthly flow method are more reliable than methods based on annual thresholds. A range of EFRs was calculated for large river basins.
P. K. Weiskel, D. M. Wolock, P. J. Zarriello, R. M. Vogel, S. B. Levin, and R. M. Lent
Hydrol. Earth Syst. Sci., 18, 3855–3872, https://doi.org/10.5194/hess-18-3855-2014, https://doi.org/10.5194/hess-18-3855-2014, 2014
S. J. Sutanto, B. van den Hurk, P. A. Dirmeyer, S. I. Seneviratne, T. Röckmann, K. E. Trenberth, E. M. Blyth, J. Wenninger, and G. Hoffmann
Hydrol. Earth Syst. Sci., 18, 2815–2827, https://doi.org/10.5194/hess-18-2815-2014, https://doi.org/10.5194/hess-18-2815-2014, 2014
A. Kleidon, M. Renner, and P. Porada
Hydrol. Earth Syst. Sci., 18, 2201–2218, https://doi.org/10.5194/hess-18-2201-2014, https://doi.org/10.5194/hess-18-2201-2014, 2014
M. L. Roderick, F. Sun, W. H. Lim, and G. D. Farquhar
Hydrol. Earth Syst. Sci., 18, 1575–1589, https://doi.org/10.5194/hess-18-1575-2014, https://doi.org/10.5194/hess-18-1575-2014, 2014
S. Manfreda, L. Brocca, T. Moramarco, F. Melone, and J. Sheffield
Hydrol. Earth Syst. Sci., 18, 1199–1212, https://doi.org/10.5194/hess-18-1199-2014, https://doi.org/10.5194/hess-18-1199-2014, 2014
C. O'Bannon, J. Carr, D. A. Seekell, and P. D'Odorico
Hydrol. Earth Syst. Sci., 18, 503–510, https://doi.org/10.5194/hess-18-503-2014, https://doi.org/10.5194/hess-18-503-2014, 2014
L. Gong
Hydrol. Earth Syst. Sci., 18, 343–352, https://doi.org/10.5194/hess-18-343-2014, https://doi.org/10.5194/hess-18-343-2014, 2014
E. Joetzjer, H. Douville, C. Delire, P. Ciais, B. Decharme, and S. Tyteca
Hydrol. Earth Syst. Sci., 17, 4885–4895, https://doi.org/10.5194/hess-17-4885-2013, https://doi.org/10.5194/hess-17-4885-2013, 2013
A. M. Ukkola and I. C. Prentice
Hydrol. Earth Syst. Sci., 17, 4177–4187, https://doi.org/10.5194/hess-17-4177-2013, https://doi.org/10.5194/hess-17-4177-2013, 2013
A. Kleidon and M. Renner
Hydrol. Earth Syst. Sci., 17, 2873–2892, https://doi.org/10.5194/hess-17-2873-2013, https://doi.org/10.5194/hess-17-2873-2013, 2013
H. A. J. Van Lanen, N. Wanders, L. M. Tallaksen, and A. F. Van Loon
Hydrol. Earth Syst. Sci., 17, 1715–1732, https://doi.org/10.5194/hess-17-1715-2013, https://doi.org/10.5194/hess-17-1715-2013, 2013
M. Meybeck, M. Kummu, and H. H. Dürr
Hydrol. Earth Syst. Sci., 17, 1093–1111, https://doi.org/10.5194/hess-17-1093-2013, https://doi.org/10.5194/hess-17-1093-2013, 2013
M. Renner, R. Seppelt, and C. Bernhofer
Hydrol. Earth Syst. Sci., 16, 1419–1433, https://doi.org/10.5194/hess-16-1419-2012, https://doi.org/10.5194/hess-16-1419-2012, 2012
A. J. Teuling
Hydrol. Earth Syst. Sci., 15, 3071–3075, https://doi.org/10.5194/hess-15-3071-2011, https://doi.org/10.5194/hess-15-3071-2011, 2011
B. Bisselink and A. J. Dolman
Hydrol. Earth Syst. Sci., 13, 1685–1697, https://doi.org/10.5194/hess-13-1685-2009, https://doi.org/10.5194/hess-13-1685-2009, 2009
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Short summary
Bias correction methods are used to calibrate climate model outputs with respect to observations. In this article, a non-stationary, multivariate and stochastic bias correction method is developed based on optimal transport, accounting for inter-site and inter-variable correlations. Optimal transport allows us to construct a joint distribution that minimizes energy spent in bias correction. Our methodology is tested on precipitation and temperatures over 12 locations in southern France.
Bias correction methods are used to calibrate climate model outputs with respect to...
