Articles | Volume 17, issue 6
https://doi.org/10.5194/hess-17-2195-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-2195-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network
Institute of Earth Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
M. Ben-Asher
Department of Geological & Environmental Sciences, Ben Gurion University of the Negev, Beer-Sheva, Israel
Department of Geography, Hebrew University of Jerusalem, Jerusalem, Israel
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Judith Eeckman, Brian De Grenus, Floreana Miesen, James Thornton, Philip Brunner, and Nadav Peleg
EGUsphere, https://doi.org/10.5194/egusphere-2024-1832, https://doi.org/10.5194/egusphere-2024-1832, 2024
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The fate of liquid water from melting snow in winter and spring is difficult to understand in the mountains. This work uses uncommon methods to accurately track the dynamics of snowmelt and infiltration at different depths in the ground and at different altitudes. The results show that melting snow quickly infiltrates into the upper layers of the soil but is also quickly transferred into the surface layer of the soil along the slopes towards the river.
Tabea Cache, Milton Salvador Gomez, Tom Beucler, Jovan Blagojevic, João Paulo Leitao, and Nadav Peleg
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We introduce a new deep-learning model that addresses limitations of existing urban flood models in handling varied terrains and rainfall events. Our model subdivides the city into small patches and presents a novel approach to incorporate broader spatial information. It accurately predicts high-resolution flood maps across diverse rainfall events and cities (on a minutes and meters scale) that haven’t been seen by the model, which offers valuable insights for urban flood mitigation strategies.
Mosisa Tujuba Wakjira, Nadav Peleg, Johan Six, and Peter Molnar
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While rainwater is a key resource in crop production, its productivity faces challenges from climate change. Using a simple model of climate, water, and crop yield interactions, we found that rain-scarce croplands in Ethiopia are likely to experience decreases in crop yield during the main growing season, primarily due to future temperature increases. These insights are crucial for shaping future water management plans, policies, and informed decision-making for climate adaptation.
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.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
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Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, https://doi.org/10.5194/tc-16-3469-2022, 2022
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Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
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Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
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Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
Short summary
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We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
N. Peleg, E. Shamir, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 19, 567–581, https://doi.org/10.5194/hess-19-567-2015, https://doi.org/10.5194/hess-19-567-2015, 2015
Judith Eeckman, Brian De Grenus, Floreana Miesen, James Thornton, Philip Brunner, and Nadav Peleg
EGUsphere, https://doi.org/10.5194/egusphere-2024-1832, https://doi.org/10.5194/egusphere-2024-1832, 2024
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The fate of liquid water from melting snow in winter and spring is difficult to understand in the mountains. This work uses uncommon methods to accurately track the dynamics of snowmelt and infiltration at different depths in the ground and at different altitudes. The results show that melting snow quickly infiltrates into the upper layers of the soil but is also quickly transferred into the surface layer of the soil along the slopes towards the river.
Talia Rosin, Francesco Marra, and Efrat Morin
Hydrol. Earth Syst. Sci., 28, 3549–3566, https://doi.org/10.5194/hess-28-3549-2024, https://doi.org/10.5194/hess-28-3549-2024, 2024
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Knowledge of extreme precipitation probability at various spatial–temporal scales is crucial. We estimate extreme precipitation return levels at multiple scales (10 min–24 h, 0.25–500 km2) in the eastern Mediterranean using radar data. We show our estimates are comparable to those derived from averaged daily rain gauges. We then explore multi-scale extreme precipitation across coastal, mountainous, and desert regions.
Shai Abir, Hamish A. McGowan, Yonatan Shaked, Hezi Gildor, Efrat Morin, and Nadav G. Lensky
Atmos. Chem. Phys., 24, 6177–6195, https://doi.org/10.5194/acp-24-6177-2024, https://doi.org/10.5194/acp-24-6177-2024, 2024
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Understanding air–sea heat exchange is vital for studying ocean dynamics. Eddy covariance measurements over the Gulf of Eilat revealed a 3.22 m yr-1 evaporation rate, which is inconsistent with bulk formulae estimations in stable atmospheric conditions, requiring bulk formulae to be revisited in these environments. The surface fluxes have a net cooling effect on the gulf water on an annual mean (-79 W m-2), balanced by a strong exchange flux between the Red Sea and the Gulf of Eilat.
Tabea Cache, Milton Salvador Gomez, Tom Beucler, Jovan Blagojevic, João Paulo Leitao, and Nadav Peleg
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-63, https://doi.org/10.5194/hess-2024-63, 2024
Revised manuscript under review for HESS
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We introduce a new deep-learning model that addresses limitations of existing urban flood models in handling varied terrains and rainfall events. Our model subdivides the city into small patches and presents a novel approach to incorporate broader spatial information. It accurately predicts high-resolution flood maps across diverse rainfall events and cities (on a minutes and meters scale) that haven’t been seen by the model, which offers valuable insights for urban flood mitigation strategies.
Mosisa Tujuba Wakjira, Nadav Peleg, Johan Six, and Peter Molnar
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-37, https://doi.org/10.5194/hess-2024-37, 2024
Revised manuscript under review for HESS
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While rainwater is a key resource in crop production, its productivity faces challenges from climate change. Using a simple model of climate, water, and crop yield interactions, we found that rain-scarce croplands in Ethiopia are likely to experience decreases in crop yield during the main growing season, primarily due to future temperature increases. These insights are crucial for shaping future water management plans, policies, and informed decision-making for climate adaptation.
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
Short summary
Short summary
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.
Nadav Peleg, Herminia Torelló-Sentelles, Grégoire Mariéthoz, Lionel Benoit, João P. Leitão, and Francesco Marra
Nat. Hazards Earth Syst. Sci., 23, 1233–1240, https://doi.org/10.5194/nhess-23-1233-2023, https://doi.org/10.5194/nhess-23-1233-2023, 2023
Short summary
Short summary
Floods in urban areas are one of the most common natural hazards. Due to climate change enhancing extreme rainfall and cities becoming larger and denser, the impacts of these events are expected to increase. A fast and reliable flood warning system should thus be implemented in flood-prone cities to warn the public of upcoming floods. The purpose of this brief communication is to discuss the potential implementation of low-cost acoustic rainfall sensors in short-term flood warning systems.
Michael Schirmer, Adam Winstral, Tobias Jonas, Paolo Burlando, and Nadav Peleg
The Cryosphere, 16, 3469–3488, https://doi.org/10.5194/tc-16-3469-2022, https://doi.org/10.5194/tc-16-3469-2022, 2022
Short summary
Short summary
Rain is highly variable in time at a given location so that there can be both wet and dry climate periods. In this study, we quantify the effects of this natural climate variability and other sources of uncertainty on changes in flooding events due to rain on snow (ROS) caused by climate change. For ROS events with a significant contribution of snowmelt to runoff, the change due to climate was too small to draw firm conclusions about whether there are more ROS events of this important type.
Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias
Hydrol. Earth Syst. Sci., 26, 4013–4032, https://doi.org/10.5194/hess-26-4013-2022, https://doi.org/10.5194/hess-26-4013-2022, 2022
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Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.
Francesco Marra, Moshe Armon, and Efrat Morin
Hydrol. Earth Syst. Sci., 26, 1439–1458, https://doi.org/10.5194/hess-26-1439-2022, https://doi.org/10.5194/hess-26-1439-2022, 2022
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We present a new method for quantifying the probability of occurrence of extreme rainfall using radar data, and we use it to examine coastal and orographic effects on extremes. We identify three regimes, directly related to precipitation physical processes, which respond differently to these forcings. The methods and results are of interest for researchers and practitioners using radar for the analysis of extremes, risk managers, water resources managers, and climate change impact studies.
Yoav Ben Dor, Francesco Marra, Moshe Armon, Yehouda Enzel, Achim Brauer, Markus Julius Schwab, and Efrat Morin
Clim. Past, 17, 2653–2677, https://doi.org/10.5194/cp-17-2653-2021, https://doi.org/10.5194/cp-17-2653-2021, 2021
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Laminated sediments from the deepest part of the Dead Sea unravel the hydrological response of the eastern Mediterranean to past climate changes. This study demonstrates the importance of geological archives in complementing modern hydrological measurements that do not fully capture natural hydroclimatic variability, which is crucial to configure for understanding the impact of climate change on the hydrological cycle in subtropical regions.
Yair Rinat, Francesco Marra, Moshe Armon, Asher Metzger, Yoav Levi, Pavel Khain, Elyakom Vadislavsky, Marcelo Rosensaft, and Efrat Morin
Nat. Hazards Earth Syst. Sci., 21, 917–939, https://doi.org/10.5194/nhess-21-917-2021, https://doi.org/10.5194/nhess-21-917-2021, 2021
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Flash floods are among the most devastating and lethal natural hazards worldwide. The study of such events is important as flash floods are poorly understood and documented processes, especially in deserts. A small portion of the studied basin (1 %–20 %) experienced extreme rainfall intensities resulting in local flash floods of high magnitudes. Flash floods started and reached their peak within tens of minutes. Forecasts poorly predicted the flash floods mostly due to location inaccuracy.
Moshe Armon, Francesco Marra, Yehouda Enzel, Dorita Rostkier-Edelstein, and Efrat Morin
Hydrol. Earth Syst. Sci., 24, 1227–1249, https://doi.org/10.5194/hess-24-1227-2020, https://doi.org/10.5194/hess-24-1227-2020, 2020
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Heavy precipitation events (HPEs), occurring around the globe, lead to natural hazards as well as to water resource recharge. Rainfall patterns during HPEs vary from one case to another and govern their effect. Thus, correct prediction of these patterns is crucial for coping with HPEs. However, the ability of weather models to generate such patterns is unclear. Here, we characterise rainfall patterns during HPEs based on weather radar data and evaluate weather model simulations of these events.
Nadav Peleg, Chris Skinner, Simone Fatichi, and Peter Molnar
Earth Surf. Dynam., 8, 17–36, https://doi.org/10.5194/esurf-8-17-2020, https://doi.org/10.5194/esurf-8-17-2020, 2020
Short summary
Short summary
Extreme rainfall is expected to intensify with increasing temperatures, which will likely affect rainfall spatial structure. The spatial variability of rainfall can affect streamflow and sediment transport volumes and peaks. The sensitivity of the hydro-morphological response to changes in the structure of heavy rainfall was investigated. It was found that the morphological components are more sensitive to changes in rainfall spatial structure in comparison to the hydrological components.
Davide Zoccatelli, Francesco Marra, Moshe Armon, Yair Rinat, James A. Smith, and Efrat Morin
Hydrol. Earth Syst. Sci., 23, 2665–2678, https://doi.org/10.5194/hess-23-2665-2019, https://doi.org/10.5194/hess-23-2665-2019, 2019
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This study presents a comparison of flood properties over multiple Mediterranean and desert catchments. While in Mediterranean areas floods are related to rainfall amount, in deserts we observed a strong connection with the characteristics of the more intense part of storms. Because of the different mechanisms involved, despite having significantly shorter and more localized storms, deserts are able to produce floods with a magnitude comparable to Mediterranean areas.
William Amponsah, Pierre-Alain Ayral, Brice Boudevillain, Christophe Bouvier, Isabelle Braud, Pascal Brunet, Guy Delrieu, Jean-François Didon-Lescot, Eric Gaume, Laurent Lebouc, Lorenzo Marchi, Francesco Marra, Efrat Morin, Guillaume Nord, Olivier Payrastre, Davide Zoccatelli, and Marco Borga
Earth Syst. Sci. Data, 10, 1783–1794, https://doi.org/10.5194/essd-10-1783-2018, https://doi.org/10.5194/essd-10-1783-2018, 2018
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The EuroMedeFF database comprises 49 events that occurred in France, Israel, Germany, Slovenia, Romania, and Italy. The dataset may be of help to hydrologists as well as other scientific communities because it offers benchmark data for the verification of flash flood hydrological models and for hydro-meteorological forecast systems. It provides, moreover, a sample of rainfall and flood discharge extremes in different climates.
Idit Belachsen, Francesco Marra, Nadav Peleg, and Efrat Morin
Hydrol. Earth Syst. Sci., 21, 5165–5180, https://doi.org/10.5194/hess-21-5165-2017, https://doi.org/10.5194/hess-21-5165-2017, 2017
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Spatiotemporal rainfall patterns in arid environments are not well-known. We derived properties of convective rain cells over the arid Dead Sea region from a long-term radar archive. We found differences in cell properties between synoptic systems and between flash-flood and non-flash-flood events. Large flash floods are associated with slow rain cells, directed downstream with the main catchment axis. Results from this work can be used for hydrological models and stochastic storm simulations.
Francesco Marra, Efrat Morin, Nadav Peleg, Yiwen Mei, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 21, 2389–2404, https://doi.org/10.5194/hess-21-2389-2017, https://doi.org/10.5194/hess-21-2389-2017, 2017
Short summary
Short summary
Rainfall frequency analyses from radar and satellite estimates over the eastern Mediterranean are compared examining different climatic conditions. Correlation between radar and satellite results is high for frequent events and decreases with return period. The uncertainty related to record length is larger for drier climates. The agreement between different sensors instills confidence on their use for rainfall frequency analysis in ungauged areas of the Earth.
Nadav Peleg, Frank Blumensaat, Peter Molnar, Simone Fatichi, and Paolo Burlando
Hydrol. Earth Syst. Sci., 21, 1559–1572, https://doi.org/10.5194/hess-21-1559-2017, https://doi.org/10.5194/hess-21-1559-2017, 2017
Short summary
Short summary
We investigated the relative contribution of the spatial versus climatic rainfall variability for flow peaks by applying an advanced stochastic rainfall generator to simulate rainfall for a small urban catchment and simulate flow dynamics in the sewer system. We found that the main contribution to the total flow variability originates from the natural climate variability. The contribution of spatial rainfall variability to the total flow variability was found to increase with return periods.
N. Peleg, E. Shamir, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 19, 567–581, https://doi.org/10.5194/hess-19-567-2015, https://doi.org/10.5194/hess-19-567-2015, 2015
E. Shamir, L. Ben-Moshe, A. Ronen, T. Grodek, Y. Enzel, K. P. Georgakakos, and E. Morin
Hydrol. Earth Syst. Sci., 17, 1021–1034, https://doi.org/10.5194/hess-17-1021-2013, https://doi.org/10.5194/hess-17-1021-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Uncertainty analysis
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Influence of three phases of El Niño–Southern Oscillation on daily precipitation regimes in China
Dual-polarized quantitative precipitation estimation as a function of range
Reconstruction of droughts in India using multiple land-surface models (1951–2015)
Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system
Exploratory studies into seasonal flow forecasting potential for large lakes
Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China
Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate
Providing a non-deterministic representation of spatial variability of precipitation in the Everest region
Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada
Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones
Characteristics of rainfall events in regional climate model simulations for the Czech Republic
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Uncertainties in calculating precipitation climatology in East Asia
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Multi-objective parameter optimization of common land model using adaptive surrogate modeling
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Estimating the water needed to end the drought or reduce the drought severity in the Carpathian region
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Laurent Strohmenger, Eric Sauquet, Claire Bernard, Jérémie Bonneau, Flora Branger, Amélie Bresson, Pierre Brigode, Rémy Buzier, Olivier Delaigue, Alexandre Devers, Guillaume Evin, Maïté Fournier, Shu-Chen Hsu, Sandra Lanini, Alban de Lavenne, Thibault Lemaitre-Basset, Claire Magand, Guilherme Mendoza Guimarães, Max Mentha, Simon Munier, Charles Perrin, Tristan Podechard, Léo Rouchy, Malak Sadki, Myriam Soutif-Bellenger, François Tilmant, Yves Tramblay, Anne-Lise Véron, Jean-Philippe Vidal, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 27, 3375–3391, https://doi.org/10.5194/hess-27-3375-2023, https://doi.org/10.5194/hess-27-3375-2023, 2023
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We present the results of a large visual inspection campaign of 674 streamflow time series in France. The objective was to detect non-natural records resulting from instrument failure or anthropogenic influences, such as hydroelectric power generation or reservoir management. We conclude that the identification of flaws in flow time series is highly dependent on the objectives and skills of individual evaluators, and we raise the need for better practices for data cleaning.
Rui Guo and Alberto Montanari
Hydrol. Earth Syst. Sci., 27, 2847–2863, https://doi.org/10.5194/hess-27-2847-2023, https://doi.org/10.5194/hess-27-2847-2023, 2023
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The present study refers to the region of Bologna, where the availability of a 209-year-long daily rainfall series allows us to make a unique assessment of global climate models' reliability and their predicted changes in rainfall and multiyear droughts. Our results suggest carefully considering the impact of uncertainty when designing climate change adaptation policies for droughts. Rigorous use and comprehensive interpretation of the available information are needed to avoid mismanagement.
Zun Yin, Kirsten L. Findell, Paul Dirmeyer, Elena Shevliakova, Sergey Malyshev, Khaled Ghannam, Nina Raoult, and Zhihong Tan
Hydrol. Earth Syst. Sci., 27, 861–872, https://doi.org/10.5194/hess-27-861-2023, https://doi.org/10.5194/hess-27-861-2023, 2023
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Land–atmosphere (L–A) interactions typically focus on daytime processes connecting the land state with the overlying atmospheric boundary layer. However, much prior L–A work used monthly or daily means due to the lack of daytime-only data products. Here we show that monthly smoothing can significantly obscure the L–A coupling signal, and including nighttime information can mute or mask the daytime processes of interest. We propose diagnosing L–A coupling within models or archiving subdaily data.
Lei Xu, Nengcheng Chen, Chao Yang, Hongchu Yu, and Zeqiang Chen
Hydrol. Earth Syst. Sci., 26, 2923–2938, https://doi.org/10.5194/hess-26-2923-2022, https://doi.org/10.5194/hess-26-2923-2022, 2022
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Precipitation forecasting has potential uncertainty due to data and model uncertainties. Here, an integrated predictive uncertainty modeling framework is proposed by jointly considering data and model uncertainties through an uncertainty propagation theorem. The results indicate an effective predictive uncertainty estimation for precipitation forecasting, indicating the great potential for uncertainty quantification of numerous predictive applications.
Thibault Lemaitre-Basset, Ludovic Oudin, Guillaume Thirel, and Lila Collet
Hydrol. Earth Syst. Sci., 26, 2147–2159, https://doi.org/10.5194/hess-26-2147-2022, https://doi.org/10.5194/hess-26-2147-2022, 2022
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Increasing temperature will impact evaporation and water resource management. Hydrological models are fed with an estimation of the evaporative demand of the atmosphere, called potential evapotranspiration (PE). The objectives of this study were (1) to compute the future PE anomaly over France and (2) to determine the impact of the choice of the method to estimate PE. Our results show that all methods present similar future trends. No method really stands out from the others.
Jing Xu, François Anctil, and Marie-Amélie Boucher
Hydrol. Earth Syst. Sci., 26, 1001–1017, https://doi.org/10.5194/hess-26-1001-2022, https://doi.org/10.5194/hess-26-1001-2022, 2022
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The performance of the non-dominated sorting genetic algorithm II (NSGA-II) is compared with a conventional post-processing method of affine kernel dressing. NSGA-II showed its superiority in improving the forecast skill and communicating trade-offs with end-users. It allows the enhancement of the forecast quality since it allows for setting multiple specific objectives from scratch. This flexibility should be considered as a reason to implement hydrologic ensemble prediction systems (H-EPSs).
Emixi Sthefany Valdez, François Anctil, and Maria-Helena Ramos
Hydrol. Earth Syst. Sci., 26, 197–220, https://doi.org/10.5194/hess-26-197-2022, https://doi.org/10.5194/hess-26-197-2022, 2022
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We investigated how a precipitation post-processor interacts with other tools for uncertainty quantification in a hydrometeorological forecasting chain. Four systems were implemented to generate 7 d ensemble streamflow forecasts, which vary from partial to total uncertainty estimation. Overall analysis showed that post-processing and initial condition estimation ensure the most skill improvements, in some cases even better than a system that considers all sources of uncertainty.
Haowen Yue, Mekonnen Gebremichael, and Vahid Nourani
Hydrol. Earth Syst. Sci., 26, 167–181, https://doi.org/10.5194/hess-26-167-2022, https://doi.org/10.5194/hess-26-167-2022, 2022
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The development of high-resolution global precipitation forecasts and the lack of reliable precipitation forecasts over Africa motivates this work to evaluate the precipitation forecasts from the Global Forecast System (GFS) over the Niger river basin in Africa. The GFS forecasts, at a 15 d accumulation timescale, have an acceptable performance; however, the forecasts are highly biased. It is recommended to apply bias correction to GFS forecasts before their application.
Hadush Meresa, Conor Murphy, Rowan Fealy, and Saeed Golian
Hydrol. Earth Syst. Sci., 25, 5237–5257, https://doi.org/10.5194/hess-25-5237-2021, https://doi.org/10.5194/hess-25-5237-2021, 2021
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The assessment of future impacts of climate change is associated with a cascade of uncertainty linked to the modelling chain employed in assessing local-scale changes. Understanding and quantifying this cascade is essential for developing effective adaptation actions. We find that not only do the contributions of different sources of uncertainty vary by catchment, but that the dominant sources of uncertainty can be very different on a catchment-by-catchment basis.
Qichun Yang, Quan J. Wang, Kirsti Hakala, and Yating Tang
Hydrol. Earth Syst. Sci., 25, 4773–4788, https://doi.org/10.5194/hess-25-4773-2021, https://doi.org/10.5194/hess-25-4773-2021, 2021
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Forecasts of water losses from land surface to the air are highly valuable for water resource management and planning. In this study, we aim to fill a critical knowledge gap in the forecasting of evaporative water loss. Model experiments across Australia clearly suggest the necessity of correcting errors in input variables for more reliable water loss forecasting. We anticipate that the strategy developed in our work will benefit future water loss forecasting and lead to more skillful forecasts.
Mostafa Tarek, François Brissette, and Richard Arsenault
Hydrol. Earth Syst. Sci., 25, 3331–3350, https://doi.org/10.5194/hess-25-3331-2021, https://doi.org/10.5194/hess-25-3331-2021, 2021
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It is not known how much uncertainty the choice of a reference data set may bring to impact studies. This study compares precipitation and temperature data sets to evaluate the uncertainty contribution to the results of climate change studies. Results show that all data sets provide good streamflow simulations over the reference period. The reference data sets also provided uncertainty that was equal to or larger than that related to general circulation models over most of the catchments.
Liming Wang, Songjun Han, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 25, 375–386, https://doi.org/10.5194/hess-25-375-2021, https://doi.org/10.5194/hess-25-375-2021, 2021
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It remains unclear at which timescale the complementary principle performs best in estimating evaporation. In this study, evaporation estimation was assessed over 88 eddy covariance monitoring sites at multiple timescales. The results indicate that the generalized complementary functions perform best in estimating evaporation at the monthly scale. This study provides a reference for choosing a suitable time step for evaporation estimations in relevant studies.
Okjeong Lee, Jeonghyeon Choi, Jeongeun Won, and Sangdan Kim
Hydrol. Earth Syst. Sci., 24, 5077–5093, https://doi.org/10.5194/hess-24-5077-2020, https://doi.org/10.5194/hess-24-5077-2020, 2020
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The uncertainty of the model interpreting rainfall extremes with temperature is analyzed. The performance of the model focuses on the reliability of the output. It has been found that the selection of temperatures suitable for extreme levels plays an important role in improving model reliability. Based on this, a methodology is proposed to quantify the degree of uncertainty inherent in the change in rainfall extremes due to global warming.
Chao Gao, Martijn J. Booij, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 24, 3251–3269, https://doi.org/10.5194/hess-24-3251-2020, https://doi.org/10.5194/hess-24-3251-2020, 2020
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This paper studies the impact of climate change on high and low flows and quantifies the contribution of uncertainty sources from representative concentration pathways (RCPs), global climate models (GCMs) and internal climate variability in extreme flows. Internal climate variability was reflected in a stochastic rainfall model. The results show the importance of internal climate variability and GCM uncertainty in high flows and GCM and RCP uncertainty in low flows especially for the far future.
Marc Schleiss, Jonas Olsson, Peter Berg, Tero Niemi, Teemu Kokkonen, Søren Thorndahl, Rasmus Nielsen, Jesper Ellerbæk Nielsen, Denica Bozhinova, and Seppo Pulkkinen
Hydrol. Earth Syst. Sci., 24, 3157–3188, https://doi.org/10.5194/hess-24-3157-2020, https://doi.org/10.5194/hess-24-3157-2020, 2020
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A multinational assessment of radar's ability to capture heavy rain events is conducted. In total, six different radar products in Denmark, the Netherlands, Finland and Sweden were considered. Results show a fair agreement, with radar underestimating by 17 %-44 % on average compared with gauges. Despite being adjusted for bias, five of six radar products still exhibited strong conditional biases with intensities of 1–2% per mm/h. Median peak intensity bias was significantly higher, reaching 44 %–67%.
Xudong Zhou, Jan Polcher, Tao Yang, and Ching-Sheng Huang
Hydrol. Earth Syst. Sci., 24, 2061–2081, https://doi.org/10.5194/hess-24-2061-2020, https://doi.org/10.5194/hess-24-2061-2020, 2020
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This article proposes a new estimation approach for assessing the uncertainty with multiple datasets by fully considering all variations in temporal and spatial dimensions. Comparisons demonstrate that classical metrics may underestimate the uncertainties among datasets due to an averaging process in their algorithms. This new approach is particularly suitable for overall assessment of multiple climatic products, but can be easily applied to other spatiotemporal products in related fields.
Lionel Berthet, François Bourgin, Charles Perrin, Julie Viatgé, Renaud Marty, and Olivier Piotte
Hydrol. Earth Syst. Sci., 24, 2017–2041, https://doi.org/10.5194/hess-24-2017-2020, https://doi.org/10.5194/hess-24-2017-2020, 2020
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An increasing number of flood forecasting services assess and communicate the uncertainty associated with their forecasts. We present a crash-testing framework that evaluates the quality of hydrological forecasts in an extrapolation context. Overall, the results highlight the challenge of uncertainty quantification when forecasting high flows. They show a significant drop in reliability when forecasting high flows and considerable variability among catchments and across lead times.
Shaoning Lv, Bernd Schalge, Pablo Saavedra Garfias, and Clemens Simmer
Hydrol. Earth Syst. Sci., 24, 1957–1973, https://doi.org/10.5194/hess-24-1957-2020, https://doi.org/10.5194/hess-24-1957-2020, 2020
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Passive remote sensing of soil moisture has good potential to improve weather forecasting via data assimilation in theory. We use the virtual reality data set (VR01) to infer the impact of sampling density on soil moisture ground cal/val activity. It shows how the sampling error is growing with an increasing sampling distance for a SMOS–SMAP scale footprint in about 40 km, 9 km, and 3 km. The conclusion will help in understanding the passive remote sensing soil moisture products.
Thanh Le and Deg-Hyo Bae
Hydrol. Earth Syst. Sci., 24, 1131–1143, https://doi.org/10.5194/hess-24-1131-2020, https://doi.org/10.5194/hess-24-1131-2020, 2020
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Here we investigate the response of global evaporation to main climate modes, including the Indian Ocean Dipole (IOD), the North Atlantic Oscillation (NAO) and the El Niño–Southern Oscillation (ENSO). Our results indicate that ENSO is an important driver of evaporation for many regions, while the impacts of NAO and IOD are substantial. This study allows us to obtain insight about the predictability of evaporation and, hence, may help to improve the early-warning systems of climate extremes.
Jean-Philippe Baudouin, Michael Herzog, and Cameron A. Petrie
Hydrol. Earth Syst. Sci., 24, 427–450, https://doi.org/10.5194/hess-24-427-2020, https://doi.org/10.5194/hess-24-427-2020, 2020
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The amount of precipitation falling in the Indus River basin remains uncertain while its variability impacts 100 million inhabitants. A comparison of datasets from diverse sources (ground remote observations, model outputs) reduces this uncertainty significantly. Grounded observations offer the most reliable long-term variability but with important underestimation in winter over the mountains. By contrast, recent model outputs offer better estimations of total amount and short-term variability.
Kamal Ahmed, Dhanapala A. Sachindra, Shamsuddin Shahid, Mehmet C. Demirel, and Eun-Sung Chung
Hydrol. Earth Syst. Sci., 23, 4803–4824, https://doi.org/10.5194/hess-23-4803-2019, https://doi.org/10.5194/hess-23-4803-2019, 2019
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This study evaluated the performance of 36 CMIP5 GCMs in simulating seasonal precipitation and maximum and minimum temperature over Pakistan using spatial metrics (SPAtial EFficiency, fractions skill score, Goodman–Kruskal's lambda, Cramer's V, Mapcurves, and Kling–Gupta efficiency) for the period 1961–2005. NorESM1-M, MIROC5, BCC-CSM1-1, and ACCESS1-3 were identified as the most suitable GCMs for simulating all three climate variables over Pakistan.
Sungmin O and Ulrich Foelsche
Hydrol. Earth Syst. Sci., 23, 2863–2875, https://doi.org/10.5194/hess-23-2863-2019, https://doi.org/10.5194/hess-23-2863-2019, 2019
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We analyze heavy local rainfall to address questions regarding the spatial uncertainty due to the approximation of areal rainfall using point measurements. Ten years of rainfall data from a dense network of 150 rain gauges in southeastern Austria are employed, which permits robust examination of small-scale rainfall at various horizontal resolutions. Quantitative uncertainty information from the study can guide both data users and producers to estimate uncertainty in their own rainfall dataset.
Aifeng Lv, Bo Qu, Shaofeng Jia, and Wenbin Zhu
Hydrol. Earth Syst. Sci., 23, 883–896, https://doi.org/10.5194/hess-23-883-2019, https://doi.org/10.5194/hess-23-883-2019, 2019
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ENSO-related changes in daily precipitation regimes are currently ignored by the scientific community. We analyzed the anomalies of daily precipitation and hydrological extremes caused by different phases of ENSO events, as well as the possible driving mechanisms, to reveal the influence of ENSO on China's daily precipitation regimes. Our results provide a valuable tool for daily precipitation prediction and enable the prioritization of adaptation efforts ahead of extreme events in China.
Micheal J. Simpson and Neil I. Fox
Hydrol. Earth Syst. Sci., 22, 3375–3389, https://doi.org/10.5194/hess-22-3375-2018, https://doi.org/10.5194/hess-22-3375-2018, 2018
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Many researchers have expressed that one of the main difficulties in modeling watershed hydrology is that of obtaining continuous, widespread weather input data, especially precipitation. The overarching objective of this study was to provide a comprehensive study of three weather radars as a function of range. We found that radar-estimated precipitation was best at ranges between 100 and 150 km from the radar, with different radar parameters being superior at varying distances from the radar.
Vimal Mishra, Reepal Shah, Syed Azhar, Harsh Shah, Parth Modi, and Rohini Kumar
Hydrol. Earth Syst. Sci., 22, 2269–2284, https://doi.org/10.5194/hess-22-2269-2018, https://doi.org/10.5194/hess-22-2269-2018, 2018
Sanjib Sharma, Ridwan Siddique, Seann Reed, Peter Ahnert, Pablo Mendoza, and Alfonso Mejia
Hydrol. Earth Syst. Sci., 22, 1831–1849, https://doi.org/10.5194/hess-22-1831-2018, https://doi.org/10.5194/hess-22-1831-2018, 2018
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We investigate the relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1–7). For this purpose, we develop and implement a regional hydrologic ensemble prediction system (RHEPS). Overall analysis shows that implementing both preprocessing and postprocessing ensures the most skill improvements, but postprocessing alone can often be a competitive alternative.
Kevin Sene, Wlodek Tych, and Keith Beven
Hydrol. Earth Syst. Sci., 22, 127–141, https://doi.org/10.5194/hess-22-127-2018, https://doi.org/10.5194/hess-22-127-2018, 2018
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The theme of the paper is exploration of the potential for seasonal flow forecasting for large lakes using a range of stochastic transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes.
Fan Yang, Hui Lu, Kun Yang, Jie He, Wei Wang, Jonathon S. Wright, Chengwei Li, Menglei Han, and Yishan Li
Hydrol. Earth Syst. Sci., 21, 5805–5821, https://doi.org/10.5194/hess-21-5805-2017, https://doi.org/10.5194/hess-21-5805-2017, 2017
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In this paper, we show that CLDAS has the highest spatial and temporal resolution, and it performs best in terms of precipitation, while it overestimates the shortwave radiation. CMFD also has high resolution and its shortwave radiation data match well with the station data; its annual-mean precipitation is reliable but its monthly precipitation needs improvements. Both GLDAS and CN05.1 over mainland China need to be improved. The results can benefit researchers for forcing data selection.
Rachel Bazile, Marie-Amélie Boucher, Luc Perreault, and Robert Leconte
Hydrol. Earth Syst. Sci., 21, 5747–5762, https://doi.org/10.5194/hess-21-5747-2017, https://doi.org/10.5194/hess-21-5747-2017, 2017
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Meteorological forecasting agencies constantly work on pushing the limit of predictability farther in time. However, some end users need proof that climate model outputs are ready to be implemented operationally. We show that bias correction is crucial for the use of ECMWF System4 forecasts for the studied area and there is a potential for the use of 1-month-ahead forecasts. Beyond this, forecast performance is equivalent to using past climatology series as inputs to the hydrological model.
Judith Eeckman, Pierre Chevallier, Aaron Boone, Luc Neppel, Anneke De Rouw, Francois Delclaux, and Devesh Koirala
Hydrol. Earth Syst. Sci., 21, 4879–4893, https://doi.org/10.5194/hess-21-4879-2017, https://doi.org/10.5194/hess-21-4879-2017, 2017
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The central part of the Himalayan Range presents tremendous heterogeneity in terms of topography and climatology, but the representation of hydro-climatic processes for Himalayan catchments is limited due to a lack of knowledge in such poorly instrumented environments. The proposed approach is to characterize the effect of altitude on precipitation by considering ensembles of acceptable altitudinal factors. Ensembles of acceptable values for the components of the water cycle are then provided.
Jefferson S. Wong, Saman Razavi, Barrie R. Bonsal, Howard S. Wheater, and Zilefac E. Asong
Hydrol. Earth Syst. Sci., 21, 2163–2185, https://doi.org/10.5194/hess-21-2163-2017, https://doi.org/10.5194/hess-21-2163-2017, 2017
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This study was conducted to quantify the spatial and temporal variability of the errors associated with various gridded precipitation products in Canada. Overall, WFDEI [GPCC] and CaPA performed best with respect to different performance measures, followed by ANUSPLIN and WEDEI [CRU]. Princeton and NARR demonstrated the lowest quality. Comparing the climate model-simulated products, PCIC ensembles generally performed better than NA-CORDEX ensembles in terms of reliability in four seasons.
Danlu Guo, Seth Westra, and Holger R. Maier
Hydrol. Earth Syst. Sci., 21, 2107–2126, https://doi.org/10.5194/hess-21-2107-2017, https://doi.org/10.5194/hess-21-2107-2017, 2017
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This study assessed the impact of baseline climate conditions on the sensitivity of potential evapotranspiration (PET) to a large range of plausible changes in temperature, relative humidity, solar radiation and wind speed at 30 Australian locations. Around 2-fold greater PET changes were observed at cool and humid locations compared to others, indicating potential for elevated water loss in the future. These impacts can be useful to inform the selection of PET models under a changing climate.
Vojtěch Svoboda, Martin Hanel, Petr Máca, and Jan Kyselý
Hydrol. Earth Syst. Sci., 21, 963–980, https://doi.org/10.5194/hess-21-963-2017, https://doi.org/10.5194/hess-21-963-2017, 2017
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The study presents validation of precipitation events as simulated by an ensemble of regional climate models for the Czech Republic. While the number of events per season, seasonal total precipitation due to heavy events and the distribution of rainfall depths are simulated relatively well, event maximum precipitation and event intensity are strongly underestimated. This underestimation cannot be explained by scale mismatch between point observations and area average (climate model simulations).
Martin Hanel, Petr Máca, Petr Bašta, Radek Vlnas, and Pavel Pech
Hydrol. Earth Syst. Sci., 20, 4307–4322, https://doi.org/10.5194/hess-20-4307-2016, https://doi.org/10.5194/hess-20-4307-2016, 2016
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The paper is focused on assessment of the contribution of various sources of uncertainty to the estimated rainfall erosivity factor. It is shown that the rainfall erosivity factor can be estimated with reasonable precision even from records shorter than recommended, provided good spatial coverage and reasonable explanatory variables are available. The research was done as an update of the R factor estimates for the Czech Republic, which were later used for climate change assessment.
Jean-Philippe Vidal, Benoît Hingray, Claire Magand, Eric Sauquet, and Agnès Ducharne
Hydrol. Earth Syst. Sci., 20, 3651–3672, https://doi.org/10.5194/hess-20-3651-2016, https://doi.org/10.5194/hess-20-3651-2016, 2016
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Possible transient futures of winter and summer low flows for two snow-influenced catchments in the southern French Alps show a strong decrease signal. It is however largely masked by the year-to-year variability, which should be the main target for defining adaptation strategies. Responses of different hydrological models strongly diverge in the future, suggesting to carefully check the robustness of evapotranspiration and snowpack components under a changing climate.
Louise Arnal, Maria-Helena Ramos, Erin Coughlan de Perez, Hannah Louise Cloke, Elisabeth Stephens, Fredrik Wetterhall, Schalk Jan van Andel, and Florian Pappenberger
Hydrol. Earth Syst. Sci., 20, 3109–3128, https://doi.org/10.5194/hess-20-3109-2016, https://doi.org/10.5194/hess-20-3109-2016, 2016
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Forecasts are produced as probabilities of occurrence of specific events, which is both an added value and a challenge for users. This paper presents a game on flood protection, "How much are you prepared to pay for a forecast?", which investigated how users perceive the value of forecasts and are willing to pay for them when making decisions. It shows that users are mainly influenced by the perceived quality of the forecasts, their need for the information and their degree of risk tolerance.
K. Sunilkumar, T. Narayana Rao, and S. Satheeshkumar
Hydrol. Earth Syst. Sci., 20, 1719–1735, https://doi.org/10.5194/hess-20-1719-2016, https://doi.org/10.5194/hess-20-1719-2016, 2016
Vincent Roth and Tatenda Lemann
Hydrol. Earth Syst. Sci., 20, 921–934, https://doi.org/10.5194/hess-20-921-2016, https://doi.org/10.5194/hess-20-921-2016, 2016
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The Soil and Water Assessment Tool (SWAT) suggests using the CFSR global rainfall data for modelling discharge and soil erosion in data-scarce parts of the world. These data are freely available and ready to use for SWAT modelling. However, simulations with the CFSR data in the Ethiopian Highlands were unable to represent the specific regional climates and showed high discrepancies. This article compares SWAT simulations with conventional rainfall data and with CFSR rainfall data.
J. Kim and S. K. Park
Hydrol. Earth Syst. Sci., 20, 651–658, https://doi.org/10.5194/hess-20-651-2016, https://doi.org/10.5194/hess-20-651-2016, 2016
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This study examined the uncertainty in climatological precipitation in East Asia, calculated from five gridded analysis data sets based on in situ rain gauge observations from 1980 to 2007. It is found that the regions of large uncertainties are typically lightly populated and are characterized by severe terrain and/or very high elevations. Thus, care must be taken in using long-term trends calculated from gridded precipitation analysis data for climate studies over such regions in East Asia.
M. F. Rios Gaona, A. Overeem, H. Leijnse, and R. Uijlenhoet
Hydrol. Earth Syst. Sci., 19, 3571–3584, https://doi.org/10.5194/hess-19-3571-2015, https://doi.org/10.5194/hess-19-3571-2015, 2015
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Commercial cellular networks are built for telecommunication purposes. These kinds of networks have lately been used to obtain rainfall maps at country-wide scales. From previous studies, we now quantify the uncertainties associated with such maps. To do so, we divided the sources or error into two categories: from microwave link measurements and from mapping. It was found that the former is the source that contributes the most to the overall error in rainfall maps from microwave link network.
S. H. Alemohammad, K. A. McColl, A. G. Konings, D. Entekhabi, and A. Stoffelen
Hydrol. Earth Syst. Sci., 19, 3489–3503, https://doi.org/10.5194/hess-19-3489-2015, https://doi.org/10.5194/hess-19-3489-2015, 2015
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This paper introduces a new variant of the triple collocation technique with multiplicative error model. The method is applied, for the first time, to precipitation products across the central part of continental USA. Results show distinctive patterns of error variance in each product that are estimated without a priori assumption of any of the error distributions. The correlation coefficients between each product and the truth are also estimated, which provides another performance perspective.
M. S. Raleigh, J. D. Lundquist, and M. P. Clark
Hydrol. Earth Syst. Sci., 19, 3153–3179, https://doi.org/10.5194/hess-19-3153-2015, https://doi.org/10.5194/hess-19-3153-2015, 2015
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A sensitivity analysis is used to examine how error characteristics (type, distributions, and magnitudes) in meteorological forcing data impact outputs from a physics-based snow model in four climates. Bias and error magnitudes were key factors in model sensitivity and precipitation bias often dominated. However, the relative importance of forcings depended somewhat on the selected model output. Forcing uncertainty was comparable to model structural uncertainty as found in other studies.
S. Garrigues, A. Olioso, J. C. Calvet, E. Martin, S. Lafont, S. Moulin, A. Chanzy, O. Marloie, S. Buis, V. Desfonds, N. Bertrand, and D. Renard
Hydrol. Earth Syst. Sci., 19, 3109–3131, https://doi.org/10.5194/hess-19-3109-2015, https://doi.org/10.5194/hess-19-3109-2015, 2015
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Land surface model simulations of evapotranspiration are assessed over a 12-year Mediterranean crop succession. Evapotranspiration mainly results from soil evaporation when it is simulated over a Mediterranean crop succession. This leads to a high sensitivity to the soil parameters. Errors on soil hydraulic properties can lead to a large bias in cumulative evapotranspiration over a long period of time. Accounting for uncertainties in soil properties is essential for land surface modelling.
W. Gong, Q. Duan, J. Li, C. Wang, Z. Di, Y. Dai, A. Ye, and C. Miao
Hydrol. Earth Syst. Sci., 19, 2409–2425, https://doi.org/10.5194/hess-19-2409-2015, https://doi.org/10.5194/hess-19-2409-2015, 2015
S. O. Los
Hydrol. Earth Syst. Sci., 19, 1713–1725, https://doi.org/10.5194/hess-19-1713-2015, https://doi.org/10.5194/hess-19-1713-2015, 2015
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The study evaluates annual precipitation (largely rainfall) amounts for the tropics and subtropics; precipitation was obtained from ground observations, satellite observations and numerical weather forecasting models.
- Annual precipitation amounts from ground and satellite observations were the most realistic.
- Newer weather forecasting models better predicted annual precipitation than older models.
- Weather forecasting models predicted inaccurate precipitation amounts for Africa.
A. Kann, I. Meirold-Mautner, F. Schmid, G. Kirchengast, J. Fuchsberger, V. Meyer, L. Tüchler, and B. Bica
Hydrol. Earth Syst. Sci., 19, 1547–1559, https://doi.org/10.5194/hess-19-1547-2015, https://doi.org/10.5194/hess-19-1547-2015, 2015
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The paper introduces a high resolution precipitation analysis system which operates on 1 km x 1 km resolution with high frequency updates of 5 minutes. The ability of such a system to adequately assess the convective precipitation distribution is evaluated by means of an independant, high resolution station network. This dense station network allows for a thorough evaluation of the analyses under different convective situations and of the representativeness error of raingaue measurements.
C. H. Wu, G. R. Huang, and H. J. Yu
Hydrol. Earth Syst. Sci., 19, 1385–1399, https://doi.org/10.5194/hess-19-1385-2015, https://doi.org/10.5194/hess-19-1385-2015, 2015
T. Antofie, G. Naumann, J. Spinoni, and J. Vogt
Hydrol. Earth Syst. Sci., 19, 177–193, https://doi.org/10.5194/hess-19-177-2015, https://doi.org/10.5194/hess-19-177-2015, 2015
P. López López, J. S. Verkade, A. H. Weerts, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 18, 3411–3428, https://doi.org/10.5194/hess-18-3411-2014, https://doi.org/10.5194/hess-18-3411-2014, 2014
G. Naumann, E. Dutra, P. Barbosa, F. Pappenberger, F. Wetterhall, and J. V. Vogt
Hydrol. Earth Syst. Sci., 18, 1625–1640, https://doi.org/10.5194/hess-18-1625-2014, https://doi.org/10.5194/hess-18-1625-2014, 2014
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