Articles | Volume 23, issue 9
https://doi.org/10.5194/hess-23-3823-2019
© 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-23-3823-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Sep 2019
Research article |
| 18 Sep 2019
| 18 Sep 2019
Using nowcasting technique and data assimilation in a meteorological model to improve very short range hydrological forecasts
Maria Laura Poletti
CORRESPONDING AUTHOR
CIMA Research Foundation, Savona, Italy
Francesco Silvestro
CIMA Research Foundation, Savona, Italy
Silvio Davolio
Institute of Atmospheric Sciences and Climate, CNR ISAC, Bologna, Italy
Flavio Pignone
CIMA Research Foundation, Savona, Italy
Nicola Rebora
CIMA Research Foundation, Savona, Italy
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Florian Pantillon, Silvio Davolio, Elenio Avolio, Carlos Calvo-Sancho, Diego S. Carrió, Stavros Dafis, Emmanouil Flaounas, Emanuele Silvio Gentile, Juan Jesus Gonzalez-Aleman, Suzanne Gray, Mario Marcello Miglietta, Platon Patlakas, Ioannis Pytharoulis, Didier Ricard, Antonio Ricchi, and Claudio Sanchez
EGUsphere, https://doi.org/10.5194/egusphere-2024-1105, https://doi.org/10.5194/egusphere-2024-1105, 2024
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Cyclone Ianos of September 2020 was a high impact but poorly predicted medicane ("Mediterranean hurricane"). A community effort of numerical modeling provides robust results to improve its prediction. It is found that the representation of local thunderstorms controls the interaction of Ianos with a jet stream at larger scales and its subsequent evolution. The results help understanding the peculiar dynamics of medicanes and provide guidance for the next generation of weather and climate models.
Claudio Sanchez, Suzanne Gray, Ambrogio Volonte, Florian Pantillon, Segolene Berthou, and Silvio Davolio
EGUsphere, https://doi.org/10.5194/egusphere-2023-2431, https://doi.org/10.5194/egusphere-2023-2431, 2023
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Medicane Ianos was a very intense cyclone which led to harmful impacts over Greece. We explore what processes are important for the forecasting of medicane Ianos, with the use of the MetOffice weather model. There is a preceding precipitation event before Ianos’s birth, whose energetics generate a bubble in the tropopause. This bubble creates the necessary conditions for Ianos to emerge and strengthen, the processes are enhanced in simulations with a warmer Mediterranean Sea.
Christian Ferrarin, Florian Pantillon, Silvio Davolio, Marco Bajo, Mario Marcello Miglietta, Elenio Avolio, Diego S. Carrió, Ioannis Pytharoulis, Claudio Sanchez, Platon Patlakas, Juan Jesús González-Alemán, and Emmanouil Flaounas
Nat. Hazards Earth Syst. Sci., 23, 2273–2287, https://doi.org/10.5194/nhess-23-2273-2023, https://doi.org/10.5194/nhess-23-2273-2023, 2023
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The combined use of meteorological and ocean models enabled the analysis of extreme sea conditions driven by Medicane Ianos, which hit the western coast of Greece on 18 September 2020, flooding and damaging the coast. The large spread associated with the ensemble highlighted the high model uncertainty in simulating such an extreme weather event. The different simulations have been used for outlining hazard scenarios that represent a fundamental component of the coastal risk assessment.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Edoardo Cremonese, Umberto Morra di Cella, Sara Ratto, and Hervé Stevenin
Geosci. Model Dev., 15, 4853–4879, https://doi.org/10.5194/gmd-15-4853-2022, https://doi.org/10.5194/gmd-15-4853-2022, 2022
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Knowing in real time how much snow and glacier ice has accumulated across the landscape has significant implications for water-resource management and flood control. This paper presents a computer model – S3M – allowing scientists and decision makers to predict snow and ice accumulation during winter and the subsequent melt during spring and summer. S3M has been employed for real-world flood forecasting since the early 2000s but is here being made open source for the first time.
Emmanouil Flaounas, Silvio Davolio, Shira Raveh-Rubin, Florian Pantillon, Mario Marcello Miglietta, Miguel Angel Gaertner, Maria Hatzaki, Victor Homar, Samira Khodayar, Gerasimos Korres, Vassiliki Kotroni, Jonilda Kushta, Marco Reale, and Didier Ricard
Weather Clim. Dynam., 3, 173–208, https://doi.org/10.5194/wcd-3-173-2022, https://doi.org/10.5194/wcd-3-173-2022, 2022
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This is a collective effort to describe the state of the art in Mediterranean cyclone dynamics, climatology, prediction (weather and climate scales) and impacts. More than that, the paper focuses on the future directions of research that would advance the broader field of Mediterranean cyclones as a whole. Thereby, we propose interdisciplinary cooperation and additional modelling and forecasting strategies, and we highlight the need for new impact-oriented approaches to climate prediction.
Mario Marcello Miglietta and Silvio Davolio
Hydrol. Earth Syst. Sci., 26, 627–646, https://doi.org/10.5194/hess-26-627-2022, https://doi.org/10.5194/hess-26-627-2022, 2022
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The main results emerging from the HyMeX SOP1 campaign and in the subsequent research activity in three Italian target areas are highlighted through conceptual models and through the identification of the relevant mesoscale environmental characteristics conducive to heavy rain events.
Samira Khodayar, Silvio Davolio, Paolo Di Girolamo, Cindy Lebeaupin Brossier, Emmanouil Flaounas, Nadia Fourrie, Keun-Ok Lee, Didier Ricard, Benoit Vie, Francois Bouttier, Alberto Caldas-Alvarez, and Veronique Ducrocq
Atmos. Chem. Phys., 21, 17051–17078, https://doi.org/10.5194/acp-21-17051-2021, https://doi.org/10.5194/acp-21-17051-2021, 2021
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Heavy precipitation (HP) constitutes a major meteorological threat in the western Mediterranean. Every year, recurrent events affect the area with fatal consequences. Despite this being a well-known issue, open questions still remain. The understanding of the underlying mechanisms and the modeling representation of the events must be improved. In this article we present the most recent lessons learned from the Hydrological Cycle in the Mediterranean Experiment (HyMeX).
Francesco Silvestro, Antonio Parodi, Lorenzo Campo, and Luca Ferraris
Hydrol. Earth Syst. Sci., 22, 5403–5426, https://doi.org/10.5194/hess-22-5403-2018, https://doi.org/10.5194/hess-22-5403-2018, 2018
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In this work we adopted a high-resolution meteorological reanalysis dataset together with a rainfall downscaling algorithm and a rainfall bias correction technique in order to produce input for a hydrological model; the resulting modeling chain allows the production of long time series of distributed hydrological variables in the Liguria region of Italy, located in the northern part of Italy. The aim is to evaluate how such a kind of modeling chain is able to reproduce the hydrology in an area.
Francesco Silvestro, Nicola Rebora, Lauro Rossi, Daniele Dolia, Simone Gabellani, Flavio Pignone, Eva Trasforini, Roberto Rudari, Silvia De Angeli, and Cristiano Masciulli
Nat. Hazards Earth Syst. Sci., 16, 1737–1753, https://doi.org/10.5194/nhess-16-1737-2016, https://doi.org/10.5194/nhess-16-1737-2016, 2016
P. Stocchi and S. Davolio
Adv. Sci. Res., 13, 7–12, https://doi.org/10.5194/asr-13-7-2016, https://doi.org/10.5194/asr-13-7-2016, 2016
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Three heavy rain events over NE Alps were simulated using a high-resolution model to evaluate the effect of the SST of the Adriatic Sea.
These preliminary results show that SST influences the surface heat fluxes over the sea, but does not necessary affect the vertical integrated water vapour flux across the coast.
The response of heavy precipitation to a SST change is complex: SST affects the PBL characteristics and thus the flow dynamics and its interaction with orography.
F. Silvestro, S. Gabellani, R. Rudari, F. Delogu, P. Laiolo, and G. Boni
Hydrol. Earth Syst. Sci., 19, 1727–1751, https://doi.org/10.5194/hess-19-1727-2015, https://doi.org/10.5194/hess-19-1727-2015, 2015
A. Hally, O. Caumont, L. Garrote, E. Richard, A. Weerts, F. Delogu, E. Fiori, N. Rebora, A. Parodi, A. Mihalović, M. Ivković, L. Dekić, W. van Verseveld, O. Nuissier, V. Ducrocq, D. D'Agostino, A. Galizia, E. Danovaro, and A. Clematis
Nat. Hazards Earth Syst. Sci., 15, 537–555, https://doi.org/10.5194/nhess-15-537-2015, https://doi.org/10.5194/nhess-15-537-2015, 2015
R. Ferretti, E. Pichelli, S. Gentile, I. Maiello, D. Cimini, S. Davolio, M. M. Miglietta, G. Panegrossi, L. Baldini, F. Pasi, F. S. Marzano, A. Zinzi, S. Mariani, M. Casaioli, G. Bartolini, N. Loglisci, A. Montani, C. Marsigli, A. Manzato, A. Pucillo, M. E. Ferrario, V. Colaiuda, and R. Rotunno
Hydrol. Earth Syst. Sci., 18, 1953–1977, https://doi.org/10.5194/hess-18-1953-2014, https://doi.org/10.5194/hess-18-1953-2014, 2014
A. Buzzi, S. Davolio, P. Malguzzi, O. Drofa, and D. Mastrangelo
Nat. Hazards Earth Syst. Sci., 14, 1325–1340, https://doi.org/10.5194/nhess-14-1325-2014, https://doi.org/10.5194/nhess-14-1325-2014, 2014
F. Silvestro, N. Rebora, and G. Cummings
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhessd-1-7497-2013, https://doi.org/10.5194/nhessd-1-7497-2013, 2013
Revised manuscript not accepted
S. Davolio, M. M. Miglietta, T. Diomede, C. Marsigli, and A. Montani
Hydrol. Earth Syst. Sci., 17, 2107–2120, https://doi.org/10.5194/hess-17-2107-2013, https://doi.org/10.5194/hess-17-2107-2013, 2013
F. Silvestro, S. Gabellani, F. Delogu, R. Rudari, and G. Boni
Hydrol. Earth Syst. Sci., 17, 39–62, https://doi.org/10.5194/hess-17-39-2013, https://doi.org/10.5194/hess-17-39-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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Global total precipitable water variations and trends over the period 1958–2021
Assessing decadal- to centennial-scale nonstationary variability in meteorological drought trends
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Potential for historically unprecedented Australian droughts from natural variability and climate change
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140-year daily ensemble streamflow reconstructions over 661 catchments in France
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Predicting extreme sub-hourly precipitation intensification based on temperature shifts
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Hydroclimatic processes as the primary drivers of the Early Khvalynian transgression of the Caspian Sea: new developments
Accounting for hydroclimatic properties in flood frequency analysis procedures
An increase in the spatial extent of European floods over the last 70 years
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A semi-parametric hourly space–time weather generator
A principal-component-based strategy for regionalisation of precipitation intensity–duration–frequency (IDF) statistics
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Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
A genetic particle filter scheme for univariate snow cover assimilation into Noah-MP model across snow climates
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Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
The agricultural expansion in South America’s Dry Chaco: Regional hydroclimate effects
Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks
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Hybrid forecasting: blending climate predictions with AI models
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Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
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Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
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Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-42, https://doi.org/10.5194/hess-2024-42, 2024
Revised manuscript accepted for HESS
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The recent development of the a new meteorological dataset providing precipitation and temperature over France – FYRE Climate – has been transformed to streamflow time series over 1871–2012 through the used of a hydrological model. This led to the creation of the daily hydrological reconstructions called HyDRE and HyDRE. These two reconstructions are evaluated allow to better understand the variability of past hydrology over France.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
EGUsphere, https://doi.org/10.5194/egusphere-2023-3040, https://doi.org/10.5194/egusphere-2023-3040, 2024
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Forecasting river flows months in advance is crucial for many water sectors and society. In N. America, snowmelt is a key driver of river flow. This study presents a statistical workflow using snow data to forecast flows months ahead in N. American snow-fed rivers. Variations in predictability across the continent are evident, raising concerns about future river flow predictability amid a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
EGUsphere, https://doi.org/10.5194/egusphere-2023-2890, https://doi.org/10.5194/egusphere-2023-2890, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extents' trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
EGUsphere, https://doi.org/10.5194/egusphere-2023-2164, https://doi.org/10.5194/egusphere-2023-2164, 2023
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We used a systematic method to fine-tune two widely used models in 263 river basins in the Western U.S. Then, we developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins . We assessed factors that influence the performance of the parameter estimation and extension. We also checked how well the two models could simulate high and low river flows and saw notable enhancements. This helps studies on regional river flow simulation and forecast.
Annalina Lombardi, Barbara Tomassetti, Valentina Colaiuda, Ludovico Di Antonio, Paolo Tuccella, Mario Montopoli, Giovanni Ravazzani, Frank Silvio Marzano, Raffaele Lidori, and Giulia Panegrossi
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-214, https://doi.org/10.5194/hess-2023-214, 2023
Revised manuscript accepted for HESS
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the Cellular Automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, and Aliaksandr Volchak
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-181, https://doi.org/10.5194/hess-2023-181, 2023
Revised manuscript accepted for HESS
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using 5 bias-corrected GCM outputs under three shared socioeconomic pathways, five hydrological models and a deep learning model.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
María Agostina Bracalenti, Omar Vicente Müller, Miguel Angel Lovino, and Ernesto Hugo Berbery
EGUsphere, https://doi.org/10.5194/egusphere-2023-1427, https://doi.org/10.5194/egusphere-2023-1427, 2023
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The Gran Chaco is a large dry forest in South America that has been heavily deforested, particularly in the Dry Chaco subregion. This deforestation has changed the land’s characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
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Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
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Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
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The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
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We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
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Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
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There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
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High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Ivan Vorobevskii, Thi Thanh Luong, Rico Kronenberg, Thomas Grünwald, and Christian Bernhofer
Hydrol. Earth Syst. Sci., 26, 3177–3239, https://doi.org/10.5194/hess-26-3177-2022, https://doi.org/10.5194/hess-26-3177-2022, 2022
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In the study we analysed the uncertainties of the meteorological data and model parameterization for evaporation modelling. We have taken a physically based lumped BROOK90 model and applied it in three different frameworks using global, regional and local datasets. Validating the simulations with eddy-covariance data from five stations in Germany, we found that the accuracy model parameterization plays a bigger role than the quality of the meteorological forcing.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
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Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Huajin Lei, Hongyu Zhao, and Tianqi Ao
Hydrol. Earth Syst. Sci., 26, 2969–2995, https://doi.org/10.5194/hess-26-2969-2022, https://doi.org/10.5194/hess-26-2969-2022, 2022
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How to combine multi-source precipitation data effectively is one of the hot topics in hydrometeorological research. This study presents a two-step merging strategy based on machine learning for multi-source precipitation merging over China. The results demonstrate that the proposed method effectively distinguishes the occurrence of precipitation events and reduces the error in precipitation estimation. This method is robust and may be successfully applied to other areas even with scarce data.
Alexane Lovat, Béatrice Vincendon, and Véronique Ducrocq
Hydrol. Earth Syst. Sci., 26, 2697–2714, https://doi.org/10.5194/hess-26-2697-2022, https://doi.org/10.5194/hess-26-2697-2022, 2022
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The hydrometeorological skills of two new nowcasting systems for forecasting Mediterranean intense rainfall events and floods are investigated. The results reveal that up to 75 or 90 min of forecast the performance of the nowcasting system blending numerical weather prediction and extrapolation of radar estimation is higher than the numerical weather model. For lead times up to 3 h the skills are equivalent in general. Using these nowcasting systems for flash flood forecasting is also promising.
Cited articles
Acquaotta, F., Faccini, F., Fratianni, S., Paliaga, G., and Sacchini, A.:
Rainfall intensity in the Genoa Metropolitan Area: secular variations and
consequences, Weather, 73, 356–362,
https://doi.org/10.1002/wea.3208, 2018.
Antonetti, M., Horat, C., Sideris, I. V., and Zappa, M.: Ensemble flood forecasting considering dominant runoff processes – Part 1: Set-up and application to nested basins (Emme, Switzerland), Nat. Hazards Earth Syst. Sci., 19, 19–40, https://doi.org/10.5194/nhess-19-19-2019, 2019.
Atencia, A., Rigo, T., Sairouni, A., Moré, J., Bech, J., Vilaclara, E., Cunillera, J., Llasat, M. C., and Garrote, L.: Improving QPF by blending techniques at the Meteorological Service of Catalonia, Nat. Hazards Earth Syst. Sci., 10, 1443–1455, https://doi.org/10.5194/nhess-10-1443-2010, 2010.
Berenguer, M., Corral, C., Sánchez-Diezma, R., and Sempere-Torres, D.:
Hydrological validation of a radar-based nowcasting technique, J. Hydrometeorol., 6,
532–549, https://doi.org/10.1175/JHM433.1 , 2005.
Berenguer, M., Sempere-Torres, D., and Pegram, G. G.: SBMcast – An ensemble
nowcasting technique to assess the uncertainty in rainfall forecasts by
Lagrangian extrapolation, J. Hydrol., 404, 226–240,
https://doi.org/10.1016/j.jhydrol.2011.04.033 , 2011.
Bick, T., Simmer, C., Trömel, S., Wapler, K., Hendricks Franssen, H. J.,
Stephan, K., Blahak, U., Schraff, C., Reich, H., Zeng, Y., and Potthast, R.: Assimilation of 3D radar reflectivities with an ensemble Kalman filter on
the convective scale,
Q. J. Roy. Meteor. Soc., 142, 1490–1504, https://doi.org/10.1002/qj.2751,
2016
Borga, M.: Accuracy of radar rainfall estimates for streamflow simulation.
J. Hydrol., 267, 26–39, https://doi.org/10.1016/S0022-1694(02)00137-3, 2002.
Bowler, N. E., Pierce, C. E., and Seed, A. W.: STEPS: A probabilistic
precipitation forecasting scheme which merges an extrapolation nowcast with
downscaled NWP, Q. J. Roy. Meteor. Soc.,
132, 2127–2155, https://doi.org/10.1256/qj.04.100, 2006.
Brown, T. A.: Admissible scoring systems for continuous distributions.
Manuscript P-5235, The Rand Corporation, Santa Monica, CA, USA, 22 pp., 1974.
Buzzi, A., Davolio, S., D'Isidoro, M., and Malguzzi, P.: The impact of
resolution and of MAP reanalysis on the simulations of heavy precipitation
during MAP cases, Meteorol. Z., 13, 91–97,
https://doi.org/10.1127/0941-2948/2004/0013-0091, 2004.
Buzzi, A., Davolio, S., Malguzzi, P., Drofa, O., and Mastrangelo, D.: Heavy rainfall episodes over Liguria in autumn 2011: numerical forecasting experiments, Nat. Hazards Earth Syst. Sci., 14, 1325–1340, https://doi.org/10.5194/nhess-14-1325-2014, 2014.
Cenci, L., Laiolo, P., Gabellani, S., Campo, L., Silvestro, F., Delogu, F.,
Boni, G., and Rudari, R.: Assimilation of H-SAF Soil Moisture Products for
Flash Flood Early Warning Systems. Case Study: Mediterranean Catchments,
IEEE J. Sel. Top. Appl., 9, 5634–5646,
https://doi.org/10.1109/JSTARS.2016.2598475, 2016.
Collier, C. G.: Objective rainfall forecasting using data from the United
Kingdom weather radar network. In Nowcasting: Mesoscale Observations and
Short-Range Prediction. Proceedings of International Symposium, Hamburg,
Germany, 25–28 August, 1981, edited by: Battrick, B. and Mort, J., ESA SP-165,
p. 201, 1981.
Davolio, S., Silvestro, F., and Malguzzi, P.: Effects of increasing
horizontal resolution in a convection-permitting model on flood forecasting:
The 2011 dramatic events in Liguria, Italy, J. Hydrometeorol.,
16, 1843–1856, https://doi.org/10.1175/JHM-D-14-0094.1, 2015.
Davolio, S., Silvestro, F., and Gastaldo, T.: Impact of Rainfall
Assimilation on High-Resolution Hydrometeorological Forecasts over Liguria,
Italy, J. Hydrometeorol., 18, 2659–2680,
https://doi.org/10.1175/JHM-D-17-0073.1, 2017a.
Davolio, S., Henin, R., Stocchi, P., and Buzzi, A.: Bora wind and heavy
persistent precipitation: Atmospheric water balance and role of air–sea
fluxes over the Adriatic Sea, Q. J. Roy. Meteor. Soc., 143, 1165–1177,
https://doi.org/10.1002/qj.3002, 2017b.
Delrieu, G., Nicol, J., Yates, E., Kirstetter, P. E., Creutin, J. D.,
Anquetin, S., Obled, C., Saulnier G. M., and Payrastre, O.: The catastrophic
flash-flood event of 8–9 September 2002 in the Gard Region, France: a first
case study for the Cévennes–Vivarais Mediterranean Hydrometeorological
Observatory, J. Hydrometeorol., 6, 34–52, https://doi.org/10.1175/JHM-400.1, 2005.
Dow, G. and Macpherson, B.: Benefit of convective-scale data assimilation
and observing systems in the UK models, Forecasting Research Technical Report 585, Met Office, UK, 2013.
Drobinski, P., Ducrocq, V., Alpert, P., Anagnostou, E., Béranger, K., Borga, M., Braud, I., Chanzy, A., Davolio, S., Delrieu, G., Estournel, C., Filali Boubrahmi, N., Font, J., Grubisic, V., Gualdi, S., Homar, V., Ivancan-Picek, B., Kottmeier, C., Kotroni, V., Lagouvardos, K., Lionello, P., Llasat, M. C., Ludwig, W., Lutoff, C., Mariotti, A., Richard, E., Romero R., Rotunno, R., Roussot, O., Ruin, I., Somot, S., Taupier-Letage, I., Tintore, J., Uijlenhoet, R., and Wernli, H.: HyMeX: A 10-year multidisciplinary program
on the Mediterranean water cycle, B. Am. Meteorol. Soc., 95, 1063–1082,
https://doi.org/10.1175/BAMS-D-12-00242.1, 2014.
Ducrocq, V., Nuissier, O., Ricard, D., Lebeaupin, C., and Thouvenin, T.: A
numerical study of three catastrophic precipitating events over southern
France. II: Mesoscale triggering and stationarity factors, Q. J. Roy. Meteor. Soc., 134, 131–145,
https://doi.org/10.1002/qj.199, 2008.
Faccini, F., Piccazzo, M., and Robbiano, A.: Natural hazards in San
Fruttuoso of Camogli (Portofino Park, Italy): a case study of a debris flow
in a coastal environmen, B. Soc. Geol. Ital.,
128, 641–654, https://doi.org/10.3301/IJG.2009.128.3.641, 2009.
Faccini, F., Robbiano, A., and Sacchini, A.: Geomorphic hazards and intense rainfall: the case study of the Recco Stream catchment (Eastern Liguria, Italy), Nat. Hazards Earth Syst. Sci., 12, 893–903, https://doi.org/10.5194/nhess-12-893-2012, 2012.
Fiori, E., Comellas, A., Molini, L., Rebora, N., Siccardi, F., Gochis, D.
J., Tanelli, S., and Parodi, A.: Analysis and hindcast simulations of an extreme
rainfall event in the Mediterranean area: The Genoa 2011 case, Atmos.
Res., 138, 13–29, https://doi.org/10.1016/j.atmosres.2013.10.007, 2014.
Foresti, L., Reyniers, M., Seed, A., and Delobbe, L.: Development and verification of a real-time stochastic precipitation nowcasting system for urban hydrology in Belgium, Hydrol. Earth Syst. Sci., 20, 505–527, https://doi.org/10.5194/hess-20-505-2016, 2016.
Gabellani, S., Silvestro, F., Rudari, R., and Boni, G.: General calibration methodology for a combined Horton-SCS infiltration scheme in flash flood modeling, Nat. Hazards Earth Syst. Sci., 8, 1317–1327, https://doi.org/10.5194/nhess-8-1317-2008, 2008.
Germann, U. and Zawadzki, I.: Scale-dependence of the predictability of
precipitation from continental radar images. Part I: Description of the
methodology, Mon. Weather Rev., 130, 2859–2873,
https://doi.org/10.1175/1520-0493(2002)130<2859:SDOTPO>2.0.CO;2, 2002.
Germann, U., Zawadzki, I., and Turner, B.: Predictability of precipitation
from continental radar images. Part IV: Limits to prediction, J.
Atmos. Sci., 63, 2092–2108, https://doi.org/10.1175/JAS3735.1,
2006.
Giannoni, F., Roth., G., and Rudari, R.: A Semi – Distributed Rainfall –
Runoff Model Based on a Geomorphologic Approach, Phys. Chem.
Earth, 25, 665–671 https://doi.org/10.1016/S1464-1909(00)00082-4,
2000.
Giannoni, F., Roth., G., and Rudari, R.: A procedure for drainage network
identification from geomorphology and its application to the prediction of
the hydrologic response, Adv. Water Resour., 28, 567–581,
https://doi.org/10.1016/j.advwatres.2004.11.013, 2005.
Golding, B. W.: Nimrod: A system for generating automated very short range
forecasts, Meteorol. Appl., 5, 1–16,
https://doi.org/10.1017/S1350482798000577, 1998.
Haiden, T., Kann, A., Wittmann, C., Pistotnik, G., Bica, B., and Gruber, C.:
The Integrated Nowcasting through Comprehensive Analysis (INCA) system and
its validation over the Eastern Alpine region, Weather Forecast., 26, 166–183,
https://doi.org/10.1175/2010WAF2222451.1, 2011.
Hersbach, H.: Decomposition of the continuous ranked probability score for
ensemble prediction systems, Weather Forecast., 15, 559–570,
https://doi.org/10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2, 2000.
Kain, J. S.: The Kain–Fritsch convective parameterization: An up-date, J.
Appl. Meteorol., 43, 170–181,
https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Kain, J. S., Weiss, S. J., Levit, J. J., Baldwin, M. E., and Bright, D. R.:
Examination of convection-allowing configurations of the WRF model for the
prediction of severe convective weather: The SPC/NSSL Spring Program 2004,
Weather Forecast., 21, 167–181, https://doi.org/10.1175/WAF906.1, 2006.
Kilambi, A. and Zawadzki, I.: An evaluation of ensembles based upon MAPLE
precipitation nowcasts and NWP precipitation forecasts, in: Preprints, 32nd
Conf. on Radar Meteorology, 22–29 October 2005, Albuquerque, NM, USA, Amer.
Meteor. Soc., vol. 4, P3R, 2005.
Kober, K., Craig, G. C., Keil, C., and Dörnbrack, A.: Blending a
probabilistic nowcasting method with a high-resolution numerical weather
prediction ensemble for convective precipitation forecasts, Q. J. Roy. Meteor. Soc., 138, 755–768,
https://doi.org/10.1002/qj.939, 2012.
Kyznarova, H., Salek, M., and Novak, P.: Preliminary results of use of INCA
system in the Czech Hydrometeorological Institute, Proceedings of ERAD2012, 25–29 June 2012,
Toulouse, France, 2012.
Kyznarova, H., Novak, P., Brezkova, L., Janal, P., and Salek, M.:
Precipitation output of INCA system: evaluation and use. In EGU General
Assembly Conference Abstracts, vol. 15, EGU General Assembly, 7–12 April 2013, Vienna,
Austria, 2013EGUGA..15.9089K, 2013.
Liechti, K. and Zappa, M.: Verification of Short-Range Hydrological
Forecasts, Handbook of Hydrometeorological Ensemble Forecasting, Springer, Berlin, Heidelberg, Germany, 953–975, 2019.
Liechti, K., Panziera, L., Germann, U., and Zappa, M.: The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps, Hydrol. Earth Syst. Sci., 17, 3853–3869, https://doi.org/10.5194/hess-17-3853-2013, 2013.
Lin, C., Vasić, S., Kilambi, A., Turner, B., and Zawadzki, I.:
Precipitation forecast skill of numerical weather prediction models and
radar nowcasts, Geophys. Res. Lett., 32, L14801, https://doi.org/10.1029/2005GL023451, 2005.
Malguzzi, P., Grossi, G., Buzzi, A., Ranzi, R., and Buizza, R.: The 1966
“century” flood in Italy: A meteorological and hydrological revisitation,
J. Geophys. Res., 111, D24106, https://doi.org/10.1029/2006JD007111, 2006.
Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous
probability distributions, Manage. Sci., 22, 1087–109,
https://doi.org/10.1287/mnsc.22.10.1087, 1976.
Metta, S., von Hardenberg, J., Ferraris, L., Rebora, N., and Provenzale, A.:
Precipitation nowcasting by a spectral-based nonlinear stochastic model,
J. Hydrometeorol., 10, 1285–1297,
https://doi.org/10.1175/2009JHM1120.1, 2009.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual
models part I – A discussion of principles, J. Hydrol., 10,
282–290, https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Nerini, D., Germann, U., and Foresti, L.: A Bayesian framework based on the
ensemble Kalman filter for flow-dependent integration of weather radar
extrapolation nowcasts and NWP precipitation fields, in: EGU General Assembly
Conference Abstracts, vol. 20, p. 4865, EGU General Assembly, 4–13 April 2018, Vienna,
Austria, 2018EGUGA..20.4865N, 2018.
Panziera, L., Germann, U., Gabella, M., and Mandapaka, P. V.:
NORA – Nowcasting of Orographic Rainfall by means of Analogues, Q. J. Roy.
Meteorol. Soc., 137, 2106–2123, https://doi.org/10.1002/qj.878, 2011.
Parodi, A., Boni, G., Ferraris, L., Siccardi, F., Pagliara, P., Trovatore,
E., and Kranzlmueller, D.: The “perfect storm”: From across the Atlantic
to the hills of Genoa, Eos, Transactions American Geophysical Union, 93,
225–226, https://doi.org/10.1029/2012EO240001, 2012.
Rebora, N., Molini, L., Casella, E., Comellas, A., Fiori, E., Pignone, F., Siccardi, F., Silvestro, F., Tanelli, S., and Parodi, A.: Extreme rainfall in the Mediterranean: What can we
learn from observations?, J. Hydrometeorol., 14, 906–922,
https://doi.org/10.1175/JHM-D-12-083.1, 2013.
Rossa, A. M., Del Guerra, F. L., Borga, M., Zanon, F., Settin, T., and
Leuenberger, D.: Radar-driven high-resolution hydro-meteorological forecasts
of the 26 September 2007 Venice flash flood, J. Hydrol., 394,
230–244, https://doi.org/10.1016/j.jhydrol.2010.08.035, 2010.
Seed, A. W.: A dynamic and spatial scaling approach to advection
forecasting, J. Appl. Meteorol., 42, 381–388,
https://doi.org/10.1175/1520-0450(2003)042<0381:ADASSA>2.0.CO;2, 2003.
Silvestro, F. and Rebora, N.: Operational verification of a framework for the probabilistic nowcasting of river discharge in small and medium size basins, Nat. Hazards Earth Syst. Sci., 12, 763-776, https://doi.org/10.5194/nhess-12-763-2012, 2012.
Silvestro, F., Rebora, N., and Ferraris, L.: An algorithm for real-time
rainfall rate estimation by using polarimetric radar: RIME, J. Hydrometeorol., 10, 227–240,
https://doi.org/10.1175/2008JHM1015.1, 2009.
Silvestro, F., Gabellani, S., Giannoni, F., Parodi, A., Rebora, N., Rudari, R., and Siccardi, F.: A hydrological analysis of the 4 November 2011 event in Genoa, Nat. Hazards Earth Syst. Sci., 12, 2743–2752, https://doi.org/10.5194/nhess-12-2743-2012, 2012.
Silvestro, F., Gabellani, S., Delogu, F., Rudari, R., and Boni, G.: Exploiting remote sensing land surface temperature in distributed hydrological modelling: the example of the Continuum model, Hydrol. Earth Syst. Sci., 17, 39–62, https://doi.org/10.5194/hess-17-39-2013, 2013.
Silvestro, F., Rebora, N., Cummings, G., and Ferraris, L.: Experiences of
dealing with flash floods using an ensemble hydrological nowcasting chain:
implications of communication, accessibility and distribution of the
results, J. Flood Risk Manage., 10, 446–462, https://doi.org/10.1111/jfr3.12161, 2015a.
Silvestro, F., Gabellani, S., Rudari, R., Delogu, F., Laiolo, P., and Boni, G.: Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data, Hydrol. Earth Syst. Sci., 19, 1727–1751, https://doi.org/10.5194/hess-19-1727-2015, 2015b.
Silvestro, F., Rebora, N., Giannoni, F., Cavallo, A., and Ferraris, L.: The
flash flood of the Bisagno Creek on 9th October 2014: An “unfortunate”
combination of spatial and temporal scales, J. Hydrol., 541, 50–62,
https://doi.org/10.1016/j.jhydrol.2015.08.004, 2016.
Silvestro, F., Parodi, A., Campo, L., and Ferraris, L.: Analysis of the streamflow extremes and long-term water balance in the Liguria region of Italy using a cloud-permitting grid spacing reanalysis dataset, Hydrol. Earth Syst. Sci., 22, 5403–5426, https://doi.org/10.5194/hess-22-5403-2018, 2018.
Sinclair, S. and Pegram, G.: Combining radar and rain gauge rainfall
estimates using conditional merging, Atmos. Sci. Lett., 6, 19–22,
https://doi.org/10.1002/asl.85, 2005.
Sokol, Z. and Zacharov, P.: Nowcasting of precipitation by an NWP model
using assimilation of extrapolated radar reflectivity, Q. J. Roy. Meteor. Soc., 138, 1072–1082,
https://doi.org/10.1002/qj.970, 2012.
Stanki, H. R., Wilson, L. J., and Burrows, W. R.: Survey of common
verification methods in meteorology, WMO/TD 358, World Meteorological Organization, Geneva, Switzerland, 114 pp., 1989.
Sun, J., Xue, M., Wilson, J. W., Zawadzki, I., Ballard, S. P.,
Onvlee-Hooimeyer, J., Joe, P., Barker, D. M., Li, P.-W., Golding, B., Xu,
M., and Pinto, J.: Use of NWP for nowcasting convective precipitation. Recent
progress and challenges, B. Am. Meteorol. Soc., 95, 409–426,
https://doi.org/10.1175/BAMS-D-11-00263.1, 2014.
Thorndahl, S., Einfalt, T., Willems, P., Nielsen, J. E., ten Veldhuis, M.-C., Arnbjerg-Nielsen, K., Rasmussen, M. R., and Molnar, P.: Weather radar rainfall data in urban hydrology, Hydrol. Earth Syst. Sci., 21, 1359–1380, https://doi.org/10.5194/hess-21-1359-2017, 2017.
Trinh, B. N., Thielen-del Pozo, J., and Thirel, G.: The reduction continuous
rank probability score for evaluating discharge forecasts from hydrological
ensemble prediction systems, Atmos. Sci. Lett., 14, 61–65,
https://doi.org/10.1002/asl2.417, 2013.
Unger, D. A.: A method to estimate the continuous ranked probability score.
Preprints, Ninth Conf. on Probability and Statistics in Atmospheric
Sciences, 9–11 October 1985, Virginia Beach, VA, USA, Amer. Meteor. Soc.,
206–213, 1985.
Vieux, B. E. and Bedient, P. B.: Assessing urban hydrologic prediction
accuracy through event reconstruction, J. Hydrol., 299, 217–236,
https://doi.org/10.1016/j.jhydrol.2004.08.005, 2004.
Wang, G., Wong, W. K., Hong, Y., Liu, L., Dong, J., and Xue, M.: Improvement
of forecast skill for severe weather by merging radar-based extrapolation
and storm-scale NWP corrected forecast, Atmos. Res., 154, 14–24,
https://doi.org/10.1016/j.atmosres.2014.10.021, 2015.
Weisman, M. L., Davies, C., Wang, W., Manning, K. W., and Klemp, J. B.:
Experiences with 0-36-h explicit convective fore- casts with the WRF-ARW
model, Weather Forecast., 23, 407–437,
https://doi.org/10.1175/2007WAF2007005.1, 2008.
Wilson, J. W. and Roberts, R. D.: Summary of convective storm initiation
and evolution during IHOP: Observational and modeling perspective, Mon. Weather Rev.,
134, 23–47, https://doi.org/10.1175/MWR3069.1, 2006.
Wilson, J. W., Crook, N. A., Mueller, C. K., Sun, J., and Dixon, M.:
Nowcasting thunderstorms: A status report, B. Am.
Meteorol. Soc., 79, 2079,
https://doi.org/10.1175/1520-0477(1998)079<2079:NTASR>2.0.CO;2, 1998.
Xu, G. and Chandrasekar, V.: Operational feasibility of
neural-network-based radar rainfall estimation, IEEE Geosci. Remote
Sens. Lett., 2, 13–17, https://doi.org/10.1109/LGRS.2004.842338,
2005.
Short summary
In this work a probabilistic rainfall nowcasting model, a non-hydrostatic high-resolution numerical weather prediction (NWP) model corrected with data assimilation, and a distributed hydrological model are used together with radar observations to implement a hydrological nowcasting chain. This chain is used to obtain a useful discharge prediction in small catchments with a time horizon of 2–8 h.
In this work a probabilistic rainfall nowcasting model, a non-hydrostatic high-resolution...
